The above trapping and growth mechanism could also explain the reason why the particle size was so uniform as shown in Figure 4 . It was known that mean value and standard deviation of the particle size were determined by successive generation of nucleation and growth depending on the plasma conditions. If the growth conditions are homogeneous in the plasma volume, the process of successive nucleation can be avoided and monosized particle distributions can be achieved, where very sharp particle size distribution could be obtained [15] . It was also shown that mean value of the particle diameter was varied by the deposition time and plasma conditions [15] . These results were well consistent with our results in Figures 2, 7 , and 9.

If the growth conditions are homogeneous in the plasma volume, the process of successive nucleation can be avoided and monosized particle distributions can be achieved, where very sharp particle size distribution could be obtained.

It was also shown that mean value of the particle diameter was varied by the deposition time and plasma conditions.


This result showed that the nanoparticles were arrived at the substrate after the background layer formation. This meant that the nanoparticles were produced in a space of plasma and grew during their levitation in the discharge [12] [13] [14] . It was well known that the nanoparticles were able to be negatively charged by the electrons and were levitating near the sheath edge in front of the wall. Owing to the gas flow, these levitating nanoparticles were carried toward the sheath edge in front of Si substrate and maintained for a long time by a force balance between the electrostatic force by the retarding electric field near the sheath edge and the neutral drag force by the gas flow toward the substrate. In this case, the gravity force might not be so effective, because the mass of nanoparticles was not so much heavy. On the other hand, the background layer was growing independently on the surface of Si substrate during the discharge.

This meant that the nanoparticles were produced in a space of plasma and grew during their levitation in the discharge.


In the present study, an appropriate behavioral model of the trolleybus electromechanical system is developed, including the machine driving scheme. Exhaustive simulations based on this model are performed in Matlab/Simulink environment, covering the total operating range of the trolleybus; the results lead to an analytical functional model of the energy consumption estimation, as well as of the regenerative energy recovery potential; energy consumption/saving calculations are based on realistic transportation conditions. Finally, sustainability estimations regarding the necessary energy recovery apparatus are presented [15] .

Finally, sustainability estimations regarding the necessary energy recovery apparatus are presented.


Athens trolleybuses are a particularly widespread electric vehicle for mass transportation in Greece. OSY S.A. owns 91 single buses and 51 articulated buses, covering 25 route-lines in Athens center [1] . The main traction motor of the 8000-series single trolleybuses under study is an asynchronous machine of 210 kW rated power; from the perspective of limiting the trolleybus electric energy consumption, the focus is on investigating the regenerative energy saving potential and the efficiency of the machine driving scheme [1] .

OSY S.A. owns 91 single buses and 51 articulated buses, covering 25 route-lines in Athens center.

The main traction motor of the 8000-series single trolleybuses under study is an asynchronous machine of 210 kW rated power; from the perspective of limiting the trolleybus electric energy consumption, the focus is on investigating the regenerative energy saving potential and the efficiency of the machine driving scheme.


Determination of performance and emission characteristics of an internal combustion engine is complex, time consuming and costly [11] . Therefore, in order to eliminate these disadvantages and complexities, performance and emission of an engine can be modeled with using artificial neural network (ANN). An ANN system works as a biological neuron. Neurons receive input from the source, perform a non-linear operation, and predict final output [12] . In recent years, parallel to developments in computer technology, ANN has been applied to many problems in automotive engineering [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] [24] [25] .

Determination of performance and emission characteristics of an internal combustion engine is complex, time consuming and costly.

Neurons receive input from the source, perform a non-linear operation, and predict final output.

In recent years, parallel to developments in computer technology, ANN has been applied to many problems in automotive engineering.


In this paper, firstly, fuel properties and experimental results of diesel engine fueled with diesel, biodiesel and biodiesel-alcohol mixtures were obtained from another work of author [6] . Standard diesel, peanut methyl ester as biodiesel and methanol-ethanol-butanol as alcohols were utilized in the experiments. Then LR method was applied to experimental data to predict performance and emission data (torque, CO, NOx). It was seen that regression model approach was deficient to predict desired parameters. Therefore, ANN approach was used and seen that more accurate results were obtained than LR.

In this paper, firstly, fuel properties and experimental results of diesel engine fueled with diesel, biodiesel and biodiesel-alcohol mixtures were obtained from another work of author.


In the c-and X-ray detectors research work based on insulating and semi-insulating CdTe, it is well known that Te precipitation is common in CdTe material, irrespective of the growth technique [22] [23] [24] [25] [26] . It is also known that treatment similar to CdCl 2 , removes these precipitated Te [27] . Therefore, in PV development with CdTe thin films, Te precipitation occurs during growth of CdTe due to natural behaviour of Te even at ppm level, un-detected by many analytical techniques. Therefore, the electronic quality of Te-rich CdTe layers suffers drastically. CdCl 2 treatment removes this excess Te, improves stoichiometry of the material, converts CdTe layer into Cd-richness in ppm level and the electronic properties improve drastically. This gives rise to high efficiency of CdS/CdTe solar cells after CdCl 2 treatment.

In the c-and X-ray detectors research work based on insulating and semi-insulating CdTe, it is well known that Te precipitation is common in CdTe material, irrespective of the growth technique.

It is also known that treatment similar to CdCl 2 , removes these precipitated Te.


Centromere architecture. The alpha satellite repeat family forms ≈3% of the human genome (Hayden et al., 2013) . Each alpha satellite is formed by monomers, each approximately 171 nucleotides in length. Consecutive monomers form higher-order repeat (HOR) units in which blocks of multiple monomers form a larger domain that can be repeated thousands of times. Individual monomers within a HOR show low similarity to each other (50-90% sequence identity) while HORs within a single centromere show high sequence similarity (95%-100% sequence identity). Organization and nucleotide sequence of HORs is specific for a particular chromosome. Figure 1 shows a dot-plot of the consensus HOR sequence on the X centromere (referred to as DXZ1) formed by 12-monomers with length 2,055. HORs typically occupy multi megabase-sized segments that include rearrangements and transposon insertions (Sevim et al., 2016) .

Centromere architecture.

The alpha satellite repeat family forms ≈3% of the human genome.

HORs typically occupy multi megabase-sized segments that include rearrangements and transposon insertions.


Extending centroFlye for reconstructing multi-HOR centromeres. Although some centromeres are characterized by a single HOR (like DXZ1 HOR on chromosome X or D16Z2 HOR on chromosome 16), others contain multiple HORs. For example, chromosome 3 is built from four HORs: D3Z1 (total length 2102 kb on cen3), D3-2 (total length 461 kb), and two recently identified HORs with total lengths 217 kb and 64 kb, respectively (Uralsky et al., 2019) .

For example, chromosome 3 is built from four HORs: D3Z1 (total length 2102 kb on cen3), D3-2 (total length 461 kb), and two recently identified HORs with total lengths 217 kb and 64 kb, respectively.


The development of antibiotic-resistant bacteria due to the excessive use of antibiotics in animal production poses significant health risks to both livestock and humans (Van Boeckel et al., 2015) . In ruminants, the use of antibiotics to manipulate the microbial ecosystem to improve fibrous feed use has been discouraged due to several disadvantages such as toxicity, potential allergies, and residues in livestock products (Ramaswami et al., 2005) . Direct-fed microbials (DFM) or probiotics, which are defined as "a source of live naturally-occurring microorganisms", are currently being used as supplements for ruminants (Yoon and Stern, 1995) . Lactic acid bacteria as probiotics have been used in ruminant diets to enhance the beneficial microflora population, which in turn will prevent pathogenic microbial establishment. They positively influence the microbial ecosystem by establishing native gastrointestinal microbes in young calves and by contributing to the equilibrium of microbial groups in the gastrointestinal system (Bae et al., 2003; Ramaswami et al., 2005) . Although the beneficial effects of probiotics are undisputed, they could represent a threat to the host. Some probiotics have antibiotic resistance genes, particularly plasmid-encoded bacteria, which can be transferred between organisms (Marteau and Shanahan, 2003) .

The development of antibiotic-resistant bacteria due to the excessive use of antibiotics in animal production poses significant health risks to both livestock and humans.

In ruminants, the use of antibiotics to manipulate the microbial ecosystem to improve fibrous feed use has been discouraged due to several disadvantages such as toxicity, potential allergies, and residues in livestock products.

Direct-fed microbials (DFM) or probiotics, which are defined as "a source of live naturally-occurring microorganisms", are currently being used as supplements for ruminants.

They positively influence the microbial ecosystem by establishing native gastrointestinal microbes in young calves and by contributing to the equilibrium of microbial groups in the gastrointestinal system.

Some probiotics have antibiotic resistance genes, particularly plasmid-encoded bacteria, which can be transferred between organisms.


Regarding our immunohistochemical analysis of RAGEs, a predominance location around the cell membrane of AECs was observed in control lung tissues, as was previously described [55] . In contrast, RAGE was totally absent in the hyperplasic AECs and fibroblast foci from IPF lungs. Although this decrease of RAGE in fibrotic lung samples could be explained by the loss of AECs, some studies suggest that RAGE might be decreased from the beginning of AECs damage [33, 56] . Likewise, in our study we have observed that the loss of RAGE was not restricted only to protein expression, but also to the genetic expression. Hence, RAGE reduction is not only associated with Type I AECs' disappearance as a consequence of tissue remodeling, but also the areas of preserved parenchyma show a decreased RAGE expression.

Regarding our immunohistochemical analysis of RAGEs, a predominance location around the cell membrane of AECs was observed in control lung tissues, as was previously described.

Although this decrease of RAGE in fibrotic lung samples could be explained by the loss of AECs, some studies suggest that RAGE might be decreased from the beginning of AECs damage.


The performance of the predictor was measured using a simulation based on the activity based mobility model [4] . Multiple prediction methods were tested and the general result was that the prediction mechanism is quite successful in some scenarios, while not successful in others. While it is possible to tune the predictor for each simulated scenario, there is no simulation scenario available that is close enough to real mobile networks and thus makes this tuning a marginally useful effort. Therefore the current results are sufficient to conclude that the presented prediction mechanism is useful, and further improvements in its performance will need to be made only after it has been tested either in a real wireless network or with a simulator that is sufficiently reflective of a real wireless network.

The performance of the predictor was measured using a simulation based on the activity based mobility model.


Overall, our results highlight the need for greater efforts and more novel approaches to improving the awareness and comprehension of the role of agriculture in providing not only private goods, but also public good-types services with a socio-economic benefit dimension. In addition, new public and/or private mechanisms, able to generate benefits from these services for the rural communities, are necessary. Some examples could be new businesses or nature-based solutions for climate-change adaptation, natural-resource provision or risk reduction for natural disasters (Maes and Jacobs, 2017) .

Some examples could be new businesses or nature-based solutions for climate-change adaptation, natural-resource provision or risk reduction for natural disasters.


With regard to the method, the ANP approach has proved useful in dealing with the complex system of agricultural landscapes and its interrelations between a large number of relevant elements. However, we have found some limitations which should be considered in future assessments. First of all, reducing a complex system to an affordable number of relations for a questionnaire-based elicitation of judgements might represent a significant simplification (Meade and Sarkis, 1999; Nekhay et al., 2009) . As shown in our study, the use of participatory approaches (e.g. in network design and adaptation) can help greatly in ensuring that the system under study incorporates its most relevant elements. Secondly, scorings can be affected by the context, as respondents might focus too much on local specificities. Here, apart from a careful selection of case studies (e.g. sharing similar contexts) and surveyed individuals (e.g. selecting those with wider knowledge of not only the case study but also the surrounding areas), we recommend providing some key information which helps to contextualise the case study in the respondent's eyes. Thirdly, potential bias exists with regard to the perceived importance of certain elements, in particular, the evaluation of tangibles and intangibles and the potential risk of upward bias for scorings of private goods compared to public goods. However, we find that, compared to other approaches (mostly monetary-based), the approach proposed is useful when dealing with both types of elements at the same time. Additionally, triangulation of results and the discussion of both the scorings obtained and comparable results of other relevant assessments with the local experts represent an opportunity partly to overcome this bias.

First of all, reducing a complex system to an affordable number of relations for a questionnaire-based elicitation of judgements might represent a significant simplification.


The present study has unearthed some interesting points that were unexpected and require further analysis. Migration from rural areas was a controversial issue: about one-third clearly wished to migrate to an urban area. Therefore, the desire of about half of the total interviewees to stay in their villages challenges the prevailing narrative whereby it is assumed that youth are eager to migrate from rural areas as agriculture is not appealing [20] [21] [22] . Some respondents felt they could not leave their parents, which was particularly true for young women. Young women aspired to be educated, have better access to health care and other services, and have their own family. Young men wished to improve their agricultural activities, owning land and a farm, having access to training opportunities and establishing a more market-oriented production. However, further analysis is required to better understand the factors behind their desires and choices.

Therefore, the desire of about half of the total interviewees to stay in their villages challenges the prevailing narrative whereby it is assumed that youth are eager to migrate from rural areas as agriculture is not appealing.


Computerized image analysis techniques may meet the demand for such methods. Ideally, an image analysis procedure should reflect all of the characteristics of a biocrystallogram as a three-dimensional, colored ramification structure, coordinated with zones relative to the center. However, due to the present limitations set by computational capacity and speed, simpler approaches are preferable. In a limited number of previous studies, encouraging results have been reported [4] .

In a limited number of previous studies, encouraging results have been reported.


Excluding analytical chemistry approaches for the evaluation of food quality, there are numerous alternative methods (holistic methods) that do not focus on the analysis of single substances but regard foodstuffs as a whole. This approach is based on the proposition that life itself is more than the sum of its single constituent parts. The organization and structure of food are important factors. The conservation of this organization and structure is a sign of high food quality, and structural decomposition is synonymous with plant death. The purpose of complementary analysis methods is to help characterize the vital activity [1] . The biocrystallization method is one of the most important complementary analysis methods.

The purpose of complementary analysis methods is to help characterize the vital activity.


The biocrystallograms that are produced from agricultural products, such as vegetables, grains, fruits, and milk samples are based on three components: (a) an aqueous solution or extract of the sample in question, (b) an aqueous solution of dehydrate copper chloride, and (c) purified water. Any kind of additive will change the copper chloride crystallization. The process is influenced by the qualitative and quantitative variations in the macromolecules of the biological extracts, thus allowing food quality assessment [5] . When used to study human blood, the results are correlated with groups of pathologies and the concentration of blood protein, and are predictive of worsening illnesses. Early diagnosis seems possible in cancer research or in occupational medicine (risk indicators) [7] . The phenomena of biocrystallograms are based on ramification patterns, which may be divided into three major stages, extending from the center in all directions to the periphery of the image (Figure 2 ). In the first or 1-zone biocrystallogram, when increasing concentrations of agricultural extracts are applied relative to a given fixed concentration of CuCl 2 , transparent needles with enormous star-like formations extend in all directions to the periphery. The second, 2-zone structure goes through the crystallization center when it is divided by a vertical and horizontal axis. The needles are pointed, predominantly transparent, and of relatively equal length in the middle zone. These morphological features may be described by means of plant morphological terms, such as stems, branches, and needles. The last stage of a biocrystallogram is an optimal degree divided into a 3-zone structure with a center zone, middle zone, and marginal zone. In the third stage, a biocrystallogram exhibits various macro and microscopic morphological features that reflect the quality of the sample in question [5] .

The process is influenced by the qualitative and quantitative variations in the macromolecules of the biological extracts, thus allowing food quality assessment.

Early diagnosis seems possible in cancer research or in occupational medicine (risk indicators).

In the third stage, a biocrystallogram exhibits various macro and microscopic morphological features that reflect the quality of the sample in question.


To be able to talk about these (co)algebra categories representing homotopy theories, we need some notion of a homotopy theory on them. For Alg O this is just the one arising from the positive flat stable model structure. In the case of algebras we build this homotopy theory by hand using the box product to construct a topological A ∞ -category whose objects are algebras over the homotopical monad associated to loop-suspension and then take path components of the mapping spaces for the maps in the homotopy category. It is dual to work of Arone-Ching [1] .

It is dual to work of Arone-Ching.


To make these constructions homotopically meaningful in the context of Oalgebras, we fatten things up between every step of the resolution, and the replacements we weave into the resolution need to be particularly well behaved. We work with homotopy (co)algebras and extend techniques to that context, showing in particular that we still have a proper (co)bar construction. For more about these ideas, see Blumberg-Riehl [3] .

For more about these ideas, see Blumberg-Riehl.


Anything that makes it easier for associative memory to run smoothly will bias beliefs [3] . For System 1, understanding is first believing [3] . It is then up to System 2 to adopt or not the suggestions of System 1. Believing is our default mode of thinking. Moreover, there is an inborn readiness for us to separate physical and intentional causality [16, 17] . System 1 infers goals and desires where none exists, making us animists and creationists by default [18] . These two concepts of causality were shaped separately by evolutionary forces, and they may explain the ubiquity of religious beliefs [18] . They are rooted in System 1. System 1 sees the world of objects as separate from the world of minds, thus making it possible for us to envision soulless bodies and bodiless souls [18] . One consequence is to believe that an immaterial divinity is the ultimate cause of the physical world; another is to believe in the existence of an afterlife. These two characteristics are common to all religions [18] . Because being a nonbeliever requires more cognitive effort, it is likely that atheists may be endowed with a more vigilant System 2. This inference is confirmed in our study, where individuals who declare themselves atheists outperform believers on the CRT.

Anything that makes it easier for associative memory to run smoothly will bias beliefs.

For System 1, understanding is first believing.

Moreover, there is an inborn readiness for us to separate physical and intentional causality.

System 1 infers goals and desires where none exists, making us animists and creationists by default.

These two concepts of causality were shaped separately by evolutionary forces, and they may explain the ubiquity of religious beliefs.

They are rooted in System 1.

System 1 sees the world of objects as separate from the world of minds, thus making it possible for us to envision soulless bodies and bodiless souls.

These two characteristics are common to all religions.


Indeed, in our study, individuals who declare themselves atheists outperform believers on cognitive reflection tests. Believers are more automatic. Our study also confirms the role of gender on CRT performance. Males score higher, as previously shown [14] . We also consider other demographic characteristics -age, handedness, parenthood, and current emotional state -only to find these unrelated to CRT performance.

Believers are more automatic.

Males score higher, as previously shown.


In the field of electrochemical storage devices electrochemical double layer capacitors (EDLCs), which are also known as supercapacitors, are typically the desired technology when confronted with applications where fast delivery and/or uptake of energy is needed [1] [2] [3] [4] . The energy in EDLCs is stored in a double layer, which is formed during charging by separating the positively and negatively charged ions in the electrolyte and adsorbing them at the electrodes' surface with the opposite charge. This charging process is much faster than the redox reactions taking place in battery systems leading to charging and discharging times in the order of seconds, an excellent cycle life (>500,000 cycles) and high power outputs (10 kWÁkg -1 ) [1] [2] [3] [4] .

In the field of electrochemical storage devices electrochemical double layer capacitors (EDLCs), which are also known as supercapacitors, are typically the desired technology when confronted with applications where fast delivery and/or uptake of energy is needed.

This charging process is much faster than the redox reactions taking place in battery systems leading to charging and discharging times in the order of seconds, an excellent cycle life (>500,000 cycles) and high power outputs (10 kWÁkg -1 ).


The definitive diagnosis of KD is made through lymph node excision biopsy and histologic examination. There are several classic histologic features of KD. The affected lymph nodes have patchy necrotizing regions, particularly in the paracortical areas. They often contain wellcircumscribed areas of eosinophilic fibrinoid material with a substantial degree of karyorrhexis. Transformed lymphocytes (immunoblasts) may surround the necrotic areas, creating a characteristic mottled appearance at low magnification. Nuclear debris (nuclear dust) is evenly scattered throughout the necrotic areas and is associated with atypical mononuclear cells, which may be macrophages phagocytosing the debris. Another consistent histologic observation is the absence of granulocytes and plasma cells [7] .

Another consistent histologic observation is the absence of granulocytes and plasma cells.


There are many works studying on protectiveness of rust layer formed on weathering steel (WS) exposed to atmosphere and following results were reported [1] [2] [3] [4] [5] [6] [7] [8] [9] . The main phases of rust are different oxy-hydroxides as α-FeOOH (goethite), β-FeOOH (akaganeite) and γ-FeOOH (lepidocrocite), some spinel type of iron oxides such as magnetite Fe 3 O 4 are contained in the rust layer depending on environmental condition. Among them α-FeOOH forms a dense packed and uniform layer of nano-sized particles, which are closely attached to the under-laying steel substrate. The corrosion protective ability of WS is mainly attributed to this dense α-phase whose formation is stimulated by dry-wet-dry cycling. In addition, the enhanced corrosion resistance of WS is achieved by adding alloying elements in which copper (Cu) has the most pronounced beneficial effect. Cu may retard anodic dissolution of iron or decrease the electronics conductivity of the rust layer so that the flow rate of electrons reaching the sites for the cathodic reaction is decrease. As with copper, nickel (Ni) can form small amounts of relatively protective hydroxy-sulfates. Like copper hydroxyl-sulfates, they may improve the barrier effect by clogging pores of the corrosion product (CP) layer. Chromium (Cr) results in substitution of iron (Fe) by Cr in the α-phase, so that a densely packed layer of nanosize of α-(Fe 1−x Cr x )OOH is formed and mainly contributes to the long term stability of WS [1] . In the early stage of CP formation Cr, P and Cu have been observed in the layer of CP closest to the substrate. This paper introduces the results of exposing WS to outdoor atmosphere in very early stage (1 -30 days), the formation and protective characteristics of corrosion product are investigated and discussed.

There are many works studying on protectiveness of rust layer formed on weathering steel (WS) exposed to atmosphere and following results were reported.

Chromium (Cr) results in substitution of iron (Fe) by Cr in the α-phase, so that a densely packed layer of nanosize of α-(Fe 1−x Cr x )OOH is formed and mainly contributes to the long term stability of WS.


HD, as a method, has been previously described and defined in different papers and books [14, 41, 54, 55] . From that starting point, this article aimed to define and assess it as a detailed process step by step, to be applied in different fields to organize information about complex scenarios in a holistic and effective way. This method is poised to transcend beyond the design scene to be implemented by other scholars and workers in different sectors, thereby facilitating interdisciplinary discussions on SD. For more than over 10 years, this process has been proven in diverse case studies, from industry to communities to policy-making, allowing us to recognize and understand the benefits and limits of this method at different levels.

HD, as a method, has been previously described and defined in different papers and books.


The first step towards such sustainable livelihoods comes from paradigm shifts: discoveries in physics-quantum theories-have permitted the transition from Cartesian and Newtonian mechanisms (a linear model) to a holistic and ecological view of life [3] . Kate Raworth has interpreted this phenomenon in economic terms as a change in the mentality of 21st-century economists. In this framework, a different economy must be embedded and based on a dynamic complexity, which is distributive and regenerative by design, created by adaptable social humans who have grown agnostic and stay inside the safe zone for humanity, which they consider the planetary boundaries that Raworth called the "doughnut" [4] .

The first step towards such sustainable livelihoods comes from paradigm shifts: discoveries in physics-quantum theories-have permitted the transition from Cartesian and Newtonian mechanisms (a linear model) to a holistic and ecological view of life.

In this framework, a different economy must be embedded and based on a dynamic complexity, which is distributive and regenerative by design, created by adaptable social humans who have grown agnostic and stay inside the safe zone for humanity, which they consider the planetary boundaries that Raworth called the "doughnut".


These approaches towards complexity and its wickedness are based on the statement that "Systemic and inter-connected problems need systemic and inter-connected solutions" [5] . Consequently, these problems require the participation of experts from diverse background disciplines to achieve innovative solutions. Facilitating possible dialogues among technicians, economists, humanists, and many more, the designer acquires a key role, which is underlined by his/her competences and 1.

These approaches towards complexity and its wickedness are based on the statement that "Systemic and inter-connected problems need systemic and inter-connected solutions".


The aim of this paper is to propose a new contribution improving 2-D subdomain technique with Taylor polynomial by focusing on the consideration of iron. The proposed technique involves solution in polar coordinates of Laplace's and Poisson's equations in the stator yoke, stator slots and teeth, air-gap, rotor teeth, PMs, and rotor nonmagnetic regions. For the rotor (i.e., PMs/teeth) and stator (i.e., slots/teeth), we take the general solution considering the nonhomogeneous Neumann BCs. In addition to traditional interface conditions between two adjacent regions represented with radius value and interval of angles (e.g., between the air-gap and stator slots/teeth), we add the consideration of the interface conditions between two adjacent regions represented with angle value and interval of radius (e.g., between the PMs and the rotor teeth). The first type of interface conditions permits to get a system of linear equations according to Fourier series expansion, and the second type permits to obtain a system of equations according to Taylor series expansion. All results from the developed semi-analytical model are then compared to those found by FEM [26] . Figure 1 represents the topology of fractional-slot STPM machines with the definition of region where Region I represents the air-gap, Region II the nonmagnetic material under rotor magnetic (i.e., under PMs and rotor teeth), Region III the stator yoke, Region IV the buried PMs, Region V the rotor Figure 1 . Example of fractional-slot STPM machines (i.e., 24-slots/22-poles) with the definition of regions.

All results from the developed semi-analytical model are then compared to those found by FEM.


The cause of electric loss in distribution networks usually is divided into two major parts: technical and non-technical losses. Technical loss relates to the physical characteristic of the conductor and equipments and refers to the electric loss due to the carrying currents of the conductors. Some main sources of technical losses are as (1) Ohmic losses of primary line conductor, (2) Ohmic losses of secondary and service line conductor, (3) Load and no-load losses of Transformer, (4) Poor management of street lighting [1] .

Some main sources of technical losses are as (1) Ohmic losses of primary line conductor, (2) Ohmic losses of secondary and service line conductor, (3) Load and no-load losses of Transformer, (4) Poor management of street lighting.


However, the null energy condition is known to be violated by quantum effects [9] . This then raises the question of whether quantum corrections might enable fundamentally new and perhaps pathological gravitational phenomena. Indeed, it was recently established that traversable wormholes can be constructed in this way [10] . On the other hand, the conjectured Generalized Second Law of thermodynamics (GSL) would both limit the utility of traversable wormholes and prohibit even more troubling exotic physics [11] .

However, the null energy condition is known to be violated by quantum effects.

Indeed, it was recently established that traversable wormholes can be constructed in this way.

On the other hand, the conjectured Generalized Second Law of thermodynamics (GSL) would both limit the utility of traversable wormholes and prohibit even more troubling exotic physics.


In recurrent events analysis, the interest usually lies in modeling the occurrence of recurrent events conditional on covariates so that inference could be drawn about the effect of covariates on the recurrent events process. The main difference between various methods used in literature is the quantity modeled, or the parameter of interest. The model then chosen for the parameter of interest often resembles the Andersen-Gill multiplicative intensity model (Andersen and Gill (1982) ). Before we describe our full data model, we will now review some of these parameters of interest and the models used to describe them.

The model then chosen for the parameter of interest often resembles the Andersen-Gill multiplicative intensity model).


One general criticism of preference tests is that they only give information about the relative properties of the choices given, but do not indicate the importance an animal attaches to a preferred option. In order to interpret the results of preference tests and to be able to apply them to practical situations where an improvement in welfare is sought, the strength of the preferences should be established (Dawkins, 1983; Broom, 1988; Broom and Johnson, 1993; Duncan, 1992; Fraser, 1996) . Where animals show that they are willing to work hard for the choices offered, it is reasonable to conclude that their welfare is improved by achieving that objective (Broom, 1988) .

In order to interpret the results of preference tests and to be able to apply them to practical situations where an improvement in welfare is sought, the strength of the preferences should be established.

Where animals show that they are willing to work hard for the choices offered, it is reasonable to conclude that their welfare is improved by achieving that objective.


Laboratory housing conditions can deprive animals of the possibility to perform a full repertoire of normal behaviour (Van de Weerd and Baumans, 1995) . The inability to engage in species-specific behaviour may cause signs of suffering such as abnormal behaviour or pathology (Jensen and Toates, 1993) . Environmental enrichment alters the environment by introducing materials or objects which are stimulating for the animals and which allow them to express more of their natural behavioural repertoire, thereby enhancing their well-being. Different animal species may have different enrichment requirements and when introducing enrichment to an animal's environment, it is very important to evaluate whether or not the animal responds to the enrichment. Preference tests can be used to determine some general principles about species-relevant properties of enrichment devices (Mench, 1994) .

Laboratory housing conditions can deprive animals of the possibility to perform a full repertoire of normal behaviour.

The inability to engage in species-specific behaviour may cause signs of suffering such as abnormal behaviour or pathology.

Preference tests can be used to determine some general principles about species-relevant properties of enrichment devices.


Housing systems should be designed to allow animals to perform effective coping behaviour when confronted with aversive stimuli, in order to prevent poor welfare (Wechsler, 1995) . When housing systems cannot be altered immediately, the provision of environmental enrichment such as nesting materials may be a relatively easy, short-term solution to enhance well-being. Natural selection, domestication and experience have shaped decision making in animals in such a way that the resultant behaviour is optimally adapted to the current environmental circumstances. In general, this will enhance biological fitness and promote welfare (McFarland, 1977; Fraser, 1996) . It is therefore reasonable to conclude that animal welfare is improved by achieving the objective the animal is willing to work for, and that reaching this objective is experienced as positive (Van Rooijen, 1983 /1984 Broom, 1988) . Mice in this study were highly motivated to lie in nesting material, even when presented on a grid floor. Thus we may conclude that nesting material has a positive effect on their well-being.

Housing systems should be designed to allow animals to perform effective coping behaviour when confronted with aversive stimuli, in order to prevent poor welfare.

In general, this will enhance biological fitness and promote welfare.

It is therefore reasonable to conclude that animal welfare is improved by achieving the objective the animal is willing to work for, and that reaching this objective is experienced as positive.


In previous preference tests with nesting material, approximately half the number of (naive) mice made a combination of the most preferred nesting materials by dragging them from one cage to another (Van de Weerd et al., 1997) . In the present study, this behaviour was not seen. In both experiments, all mice spent most time in the cage with the nesting material and even in experiment 2, the mice did not drag the nesting material to the cage with the nest box to combine both commodities or at least lie in the bedding. It can be argued that they accepted the grid floor in order to rest in the nesting material, as the nesting material masks the structure of a grid floor. Fig. 6 shows the type of nests the mice made on the grid floors, which have the same shape as nests constructed on bedding. These results imply that nesting materials are much more attractive for mice than nest boxes. In natural settings, nest boxes may be used by rodents as a feeding post, as a storage for food, for the construction of a nest or for the bearing and raising of offspring as described by Ryszkowski and Truszkowski (19701. They may also offer an opportunity to hide from predators. In the laboratory the function of a nest box is more restricted, the main function probably is to offer a shelter against overexposure to light or to avoid aggressive cage mates (Van de Weerd and Baumans, 1995) . Nesting material has similar functions, but differs from nest boxes in that it can be manipulated to build a nest and by doing this, the mice are able to structure their environment (Van de Weerd et al., 1997) . Another main function of a nest is to shelter animals from variations in environmental temperatures (Brain and Rajendram, 1986) . Both males and females will build a nest when offered nesting materials and there is a strong genetic influence on nest-building behaviour (Lisk et al., 1969; Lee, 1972 Lee, , 1973 Lynch and Hegmann, 1972; Brain and Rajendram, 1986) .

In previous preference tests with nesting material, approximately half the number of (naive) mice made a combination of the most preferred nesting materials by dragging them from one cage to another.

In the laboratory the function of a nest box is more restricted, the main function probably is to offer a shelter against overexposure to light or to avoid aggressive cage mates.

Nesting material has similar functions, but differs from nest boxes in that it can be manipulated to build a nest and by doing this, the mice are able to structure their environment.

Another main function of a nest is to shelter animals from variations in environmental temperatures.

Both males and females will build a nest when offered nesting materials and there is a strong genetic influence on nest-building behaviour.


Perhaps, the biggest problem is related to the lack of a validated assay that can reliably measure the antioxidant and pro-oxidant capacity of samples, thus making it essential to test the capacity with different methods. As a result, authors tend to simplify the calculation method in order to amplify the number of testing procedures. However, the method used to measure and compute the antioxidant capacity has a major impact on the results, because in both in vivo and in vitro, the oxidation reactions are complex. The abbreviated approach to study the dose-response at one single-time expecting to find linear forms (as described by the non-kinetic approaches) frequently leads to unreliable results and misinterpretations, making it extremely difficult to compare the results from different assays. The preference of apparently simple assays, routinely applicable with minimal calculation requirements, is not very justifiable today, given the availability of computational applications and automatic equipment (such as microplate readers), whose combination provides adequate tools to work with data sets that allow accurate evaluations by the available non-linear modeling (Labuza & Dugan, 1971; Murado & Vázquez, 2010; Terpinc & Abramovič, 2010; Wardhani et al., 2013; Özilgen & Özilgen, 1990) . Despite the advisability of using mechanistic or empiric kinetic models as indicated by different authors, researchers continue to use simple calculation alternative methods more often than necessary.

The preference of apparently simple assays, routinely applicable with minimal calculation requirements, is not very justifiable today, given the availability of computational applications and automatic equipment (such as microplate readers), whose combination provides adequate tools to work with data sets that allow accurate evaluations by the available non-linear modeling.


Additionally, the arbitrary use of simple analytical procedures to calculate molecular properties, occasionally without a validation study, as well as a lack of statistical significance, has caused much controversy (Frankel, 1993; 1994; Huang et al., 2005; Koleva et al., 2002; Laguerre & Villeneuve, 2007; Naguib, 2000; Roginsky, 2005) . Commonly, the mathematical determinations of the OM capacity are based on a fixed endpoint without proper considerations of the kinetic behavior. The most typical and incorrect practice is to use the single-time dose-response of one commercial OM as a calibration curve (normally focusing on the linear range), and afterwards to compute the equivalent OM capacity of any type of sample by testing it only at one single-timedose, assuming too many false aspects as true.

Additionally, the arbitrary use of simple analytical procedures to calculate molecular properties, occasionally without a validation study, as well as a lack of statistical significance, has caused much controversy.


Burning wood pellets is mainly used for warm-up environments (commercial and residential environments), but it can also be used as fuel for generating electricity in industrial plants, or even in power plants. The versatility and availability of biomass, combined with its characteristic of renewable energy and do not contribute to global warming, and in addition its cost is an average 25-50 % less than fossil heating fuels, are strong arguments to enhance its use worldwide [1] [2] [3] [4] [5] . Moreover, the heterogeneity, low energy density, and variable humidity, combined with the high cost of transport, are limited challenges that must be overcome with new technologies and new products [6] [7] [8] [9] . In this context, torrefaction and pyrolysis are attractive alternatives for increasing energy density and decreasing the moisture content of the samples, based on thermochemical conversion in a non-oxidizing atmosphere (a procedure that contributes to the generation of an additional product of appreciable economic value). These advantages make interesting the use of pyrolyzed biomass for energy purposes, requiring, however, a proper characterization. Thus, the aim of this work was to produce and characterize biochar from pine pellet for further use of it as fuel. It has shown the caloric value, moisture content, density and immediate analysis of the most important properties of wood for use as fuel. Thus, the present study produced biochar of the pine pellet and determined the properties of the same following the above recommendation [10] [11] [12] .

The versatility and availability of biomass, combined with its characteristic of renewable energy and do not contribute to global warming, and in addition its cost is an average 25-50 % less than fossil heating fuels, are strong arguments to enhance its use worldwide.

Moreover, the heterogeneity, low energy density, and variable humidity, combined with the high cost of transport, are limited challenges that must be overcome with new technologies and new products.

Thus, the present study produced biochar of the pine pellet and determined the properties of the same following the above recommendation.


Our main conclusion is that both test suite size and mutation score influence fault detection. Our results support the claim that relatively strong correlations between mutation score and fault detection exist, as suggested by previous work [24] . However, these are simply a product of the dependence between mutation score and test suite size. Our data show that when controlling the test suite size (decouple mutation score from test suite size) all correlations become weak or moderate in the best case.

Our results support the claim that relatively strong correlations between mutation score and fault detection exist, as suggested by previous work.


The differences between these two evaluation metrics is important as they are extensively used in empirical studies [36] . Yet, it is unclear whether there are any practically significant differences between them. In case the differences are significant, one could draw different conclusions by using one metric over the other. Thus, investigating the potential differences between these metrics can be useful to other studies that compare test criteria and test methods.

The differences between these two evaluation metrics is important as they are extensively used in empirical studies.


Riverine and wetland ecosystems are largely subject to the flow regimes (magnitude, frequency, duration, seasonal timing, rates of change and water quality) (Zhang et al., 2012) . Many ecological problems, such as harmful algal blooms, loss of habitat and natural resources, hypoxia, and reduced water clarity, are exacerbated during low-flow periods (Dakova et al., 2000; Rolls et al., 2012) . To fully understand effects of low flow on these ecosystems, many hydrological-ecological researchers have been trying to identify qualitative or quantitative hydrological-ecological relationships between the attributes of low flow and ecosystem functions or patterns of biodiversity (Arthington et al., 2014; Dakova et al., 2000; Gebremariam et al., 2014; Rabalais et al., 2009; Rolls et al., 2012) . These relationships and linkages among flow regimes and ecosystems are useful for predicting responses of riverine ecosystems to global changes and helping watershed managers to identify effective measures to maintain the balance for the riverine and wetland ecosystems. Among these studies, relationships between the sustainable development of in-stream and off-stream ecosystems and the minimum flow are extensively studied (Arthington et al., 1992; Bonacci et al., 1998; Ferrar, 1989; Petts, 1996) . Lots of concepts or terminologies, such as "Minimum Flow", "Environmental Flow Requirements", "Ecological Flow Requirements", "Ecology Acceptable Flow Regime", "Minimum Acceptable Flows", are introduced and proposed. Although meanings and scopes of these concepts may be slightly different, all of them address on the relationships between the sustainable development of the riverine ecosystems and the low flow.

Riverine and wetland ecosystems are largely subject to the flow regimes (magnitude, frequency, duration, seasonal timing, rates of change and water quality).

Many ecological problems, such as harmful algal blooms, loss of habitat and natural resources, hypoxia, and reduced water clarity, are exacerbated during low-flow periods.

To fully understand effects of low flow on these ecosystems, many hydrological-ecological researchers have been trying to identify qualitative or quantitative hydrological-ecological relationships between the attributes of low flow and ecosystem functions or patterns of biodiversity.

Among these studies, relationships between the sustainable development of in-stream and off-stream ecosystems and the minimum flow are extensively studied.


The organisation of the paper is as follows. In §2, we prove a monotonicity inequality for the k-curvature operators. The monotonicity for k-Hessian operators can be obtained by a simple integration by parts [39] . But for the k-curvature operators, the computation is much more complicated.

The monotonicity for k-Hessian operators can be obtained by a simple integration by parts.


The notion of curvature measures in Theorem 1.1 is closely related to that of Federer's [20] . The curvature measures in Theorem 1.1 are defined in the domain Ω while Federer's are defined in the space R n+1 , supported on the graph of the function. But they are essentially the same as the curvature measures in Theorem 1.1 are projections of Federer's from R n+1 to R n . When k = n, the k-curvature is the Gauss curvature and the corresponding curvature measure has been extensively studied [34] .

The notion of curvature measures in Theorem 1.1 is closely related to that of Federer's.

When k = n, the k-curvature is the Gauss curvature and the corresponding curvature measure has been extensively studied.


As the measures for business performance showed unidimensionality, a single set of composite scores of these measures was used to represent the construct [14] . The 316 responses were sorted in descending order in terms of their mean scores of five performance measures. The first half of the responses were designated as relatively high performers and the second half were designated as relatively low performers. The results of non-response bias test on firm demographic factors (i.e., gross sales revenue, respondent position, number of years in business, number of employees, and product type) showed there were no significant differences between early and late groups of returned surveys. Factor analysis helped reduce the measures which showed high cross loading and/or low factor loading.

As the measures for business performance showed unidimensionality, a single set of composite scores of these measures was used to represent the construct.


For low performing firms, environmental diversity and complexity only significantly affected low cost strategy. The more diverse and complex the environment facing a firm is, the more emphasis low performers gives to cost reduction. Environmental dynamism significantly affected both low cost and quality strategies in a positive way; and the paths from environmental hostility to low cost and flexibility were positive and statistically significant. The low performers' strategy responses to environment were quite contrary to those of high performers. When confronting escalating dynamic and hostile environment, low performers always prioritized low cost as a key strategy although quality and flexibility were also given certain weights. The simultaneous emphasis of both cost leadership and differentiation by low performing Chinese apparel SMEs can be the phenomenon called "stuck in the middle" by Porter [34] . This has been observed by some researchers [3, 8] . In recent years, with intensifying competition in the global apparel market and climbing labor cost and tightening worker and environment protection laws in China, the transition of many Chinese apparel SMEs has not been either smooth or joyful [4] . On the one hand, the importance of cost advantage has been deeply rooted in the mindsets of those senior executives through their decadal successes. On the other hand, the rapidly deteriorating profit margin has forced them to explore alternative strategies which can help them survive and grow. However, the lack of sufficient capital and human resources has been the major constraint preventing SMEs from achieving competitive advantages in both cost leadership and differentiation at the same time.

The simultaneous emphasis of both cost leadership and differentiation by low performing Chinese apparel SMEs can be the phenomenon called "stuck in the middle" by Porter.

This has been observed by some researchers.

In recent years, with intensifying competition in the global apparel market and climbing labor cost and tightening worker and environment protection laws in China, the transition of many Chinese apparel SMEs has not been either smooth or joyful.


In the past three decades, the Chinese apparel industry has achieved spectacular growth, capturing a significant share of global production and trade. By the end of 2012, the industry including textile sector accounted for some 18 percent of China's manufacturing employment, 12 percent of China's GDP, 14 percent of its manufacturing value added, and 17 percent of its total exports [1] . China has become the largest producer and supplier of fibers, yarns, fabrics, and apparel in both volume and value terms. Today, it supplies approximately 33 percent of textiles and 40 percent of apparel by value in the global market [2] .

By the end of 2012, the industry including textile sector accounted for some 18 percent of China's manufacturing employment, 12 percent of China's GDP, 14 percent of its manufacturing value added, and 17 percent of its total exports.

Today, it supplies approximately 33 percent of textiles and 40 percent of apparel by value in the global market.


In moving from a self-sufficiency-based, centrally-planned system towards a commercially-driven, export oriented sector, the Chinese apparel industry experienced far-reaching changes. These profoundly affected the consumer needs, the product mix and distribution channels, and firm strategy and skill development [3] . As a result of these changes, Chinese firms have faced a dramatic escalation in the level of turbulence within their business environment. Against this backdrop, state-owned enterprises (SOEs), which were in the monopoly position, have radically declined. Meanwhile, the rise of private sector has fundamentally reshaped the contour of the industry and overtaken most output and export. Some estimates put the total number of private firms in the Chinese apparel industry at approximately 100,000. Of these, more than 80 percent are small and medium-sized enterprises (SMEs) [1] . Nowadays, the competitiveness of SMEs largely determines the growth of Chinese apparel industry [4] . The continued advancement of managerial skills and knowledge among SMEs plays a crucial role in achieving the national industry upgrading goal through transiting from originalequipment-manufacturer (OEM) which mainly competes on low cost to original-brand-manufacturer (OBM) and/or original-design-manufacturer (ODM) which focus on differentiation and added value.

These profoundly affected the consumer needs, the product mix and distribution channels, and firm strategy and skill development.

Of these, more than 80 percent are small and medium-sized enterprises (SMEs).

Nowadays, the competitiveness of SMEs largely determines the growth of Chinese apparel industry.


Endoscopists still face challenges in using M-NBI and the VSCS in clinical practice. The diagnostic reproducibility of this system was found to be relatively unsatisfactory, with a mean kappa value for interobserver agreement of 0.50 [11] . Furthermore, the mean diagnostic interobserver kappa value for trainees who had been performing endoscopies for less than 1 year but had never used M-NBI was only 0.40 [12] . In addition, the degree of confidence within each M-NBI diagnostic category (e.g., cancerous or noncancerous lesions) was found to be wide-ranging, from low to high confidence. The proportion of correct diagnoses with a high degree of confidence was reported to be only 50% in patients with a pathological diagnosis of cancer by screening endoscopy using M-NBI [9] . In addition, a method of easing the learning curve for M-NBI procedures has not yet been established [9] .

The diagnostic reproducibility of this system was found to be relatively unsatisfactory, with a mean kappa value for interobserver agreement of 0.50.

Furthermore, the mean diagnostic interobserver kappa value for trainees who had been performing endoscopies for less than 1 year but had never used M-NBI was only 0.40.

The proportion of correct diagnoses with a high degree of confidence was reported to be only 50% in patients with a pathological diagnosis of cancer by screening endoscopy using M-NBI.

In addition, a method of easing the learning curve for M-NBI procedures has not yet been established.


This work has emphasized that frame materials have a rich behavior even when the condition of scale separation is respected. It was illustrated by the study of the propagation of plane waves in a material with walls stiffer than floors. In that case, walls can experience bending at the macroscopic scale. The equivalent continuum is a second-grade medium at the leading order as for linear fiber reinforced composites [18] [19] [20] . But, contrary to the composites made of continuous materials, the second-grade effect only appears in one direction in frame materials. As a result, there is dispersion for the shear waves traveling in the direction of the walls and the anisotropy is strongly marked. The shear waves in the direction of the floors are generated by another mechanism called local bending. It is the same mechanism as for the shear waves in materials with similar walls and floors [17] . It consists of the bending of the elements between two neighboring nodes. Since the rigidities of the two types of bending have different orders of magnitude, the shear waves in the direction of the floors appear in another frequency range. Moreover there is no dispersion. Likewise, shear-compression waves appear in different frequency ranges according to their polarization because they are generated by two mechanisms: the tension-compression of the floors and the tensioncompression of the walls. These waves might also be associated with the local resonance in bending of the elements if the frequency ranges coincide. This causes additional kinematic conditions close to the frequencies of the even modes of the resonating elements. Moreover, if these elements are orthogonal to the direction of polarization, the properties of the macroscopic waves depend on an effective mass which is a function of the frequency. Consequently, there are bandgaps close to the frequencies of the odd modes of the resonating elements and dispersion. The latter differs from the dispersion associated with the macroscopic bending of the walls. Its importance is determined by the distribution of mass between the elements.

The equivalent continuum is a second-grade medium at the leading order as for linear fiber reinforced composites.

It is the same mechanism as for the shear waves in materials with similar walls and floors.

Moreover there is no dispersion.


The paper is organized as follows: The next section describes the model-simulated radar observations and assimilation system. Section 3 designs assimilation experiments with the proposed time-expanded sampling. Assimilation experiments are performed with perfect model and imperfect model settings in sections 4 and 5, respectively, to explore and demonstrate the merits of the proposed approach. Conclusions follow in section 6. Tong and Xue (2005, hereafter TX05 ) demonstrated the ability of the EnKF method in retrieving not only the wind and thermodynamic variables but also multiple microphysical species associated with a multiclass ice microphysics scheme by using the Advanced Regional Prediction System (ARPS) model (Xue et al. 2001) . They also discussed the relative role of radial velocity and reflectivity data as well as their spatial coverage in recovering the full flow and cloud fields. The current study uses the same ARPS configurations for the same storm case in TX05, that is, the 20 May 1977 Del City, Oklahoma, supercell (Ray et al. 1981) . The model configuration contains 12 prognostic state variables, including wind components u, , and w; perturbation potential temperature Ј; perturbation pressure pЈ; turbulence kinetic energy (TKE); and the mixing ratios for water vapor q , cloud water q c , rainwater q r , cloud ice q i , snow q s , and hail q h . As in TX05, all of these prognostic state variables except for TKE are subject to updating at each analysis step of assimilation.

Conclusions follow in section 6.

Tong and Xue (2005, hereafter TX05 ) demonstrated the ability of the EnKF method in retrieving not only the wind and thermodynamic variables but also multiple microphysical species associated with a multiclass ice microphysics scheme by using the Advanced Regional Prediction System (ARPS) model.

The current study uses the same ARPS configurations for the same storm case in TX05, that is, the 20 May 1977 Del City, Oklahoma, supercell.


The figures show that, except for the wp (Figure 7) , the highest GRG values have associated GRGe values that are small enough to ensure that these GRG values generally correspond to the best options. In the case of the wp, GRG 2 has such a high GRGe value because the ignition mass flow for this sequence has an associated uncertainty of 9.14% for the ignition mass flow. This uncertainty propagates along all of the operation sequence, resulting in a GRGe value of 2.58 × 10 −1 , which represents 38.60% of the GRG 2 value. Figure 6 presents the effect of the air mass flow on the ignition mass flow for the bp. The behavior of the bp (Figure 6 ) serves as a generic model for the other fuels that are under consideration. Although the air flow rates and velocities differ, three combustion phases are distinguishable for all of the fuels as a function of the supplied air mass flow [41] . The first phase corresponds to a linear increase in the combusted mass flow (the oxygen-limited phase), followed by a quasi-constant speed zone (the reaction-limited phase), followed by the third and last quenching phase (the convective cooling phase). These three phases are not as clearly distinguishable in the other fuels because of the lower flow rates. A continuous slanted line divides this figure into two zones and represents the fuel stoichiometric line. The measurements that correspond to the left-hand side of this line belong to the sub-stoichiometric regime, while the measurements on the right involve an excess of air. The fact that the stoichiometric regime was estimated for the whole fuel and not for the char must be taken into account.

Although the air flow rates and velocities differ, three combustion phases are distinguishable for all of the fuels as a function of the supplied air mass flow.


Of the different thermochemical conversion techniques, combustion is the most extensively used and developed technique for the utilization of biomass [3] . Thus, to increase combustion development, the whole process needs to be optimized in terms of efficiency and cost. Because of this necessity, developing research has focused on three main aspects: the fuel properties, boiler characteristics, and emissions [4] [5] [6] [7] [8] [9] [10] .

Of the different thermochemical conversion techniques, combustion is the most extensively used and developed technique for the utilization of biomass.

Because of this necessity, developing research has focused on three main aspects: the fuel properties, boiler characteristics, and emissions.


If a specific analysis is performed for each of the conditions that have a maximum ignition rate, the results indicate that this value decreases as it nears the stoichiometric condition, which is a consequence of the adverse effect of convection. The higher is the air requirement to reach the maximum, the higher is the heat that is lost by convection and the lower the rate and the energy that is supplied. By comparing the global rates (Table 3) , it can be seen that the maximum value is reached by the wp (0.069 kg m −2 s −1 ), which also have the broadest operating range when their combustion is conducted in a zone close to a 0.5 kg m −2 s −1 air mass flow. However, the os is the fuel that first reaches the extinction convection zone with an air flow of (0.352 kg m −2 s −1 ). There is a clear relation between the lower heating value (LHV) and the ignition front propagation speed. Thus, the best quality fuels (with higher LHV) reach higher ignition flow rate values [24] . Although the graphical representations of the maximum temperature and the ignition mass flow as a function of air flow (left area of plots) present information on the points that correspond to the best possible conditions, they do not take into account the individual and/or combined effect of the measured variable uncertainty. Thus, for the wp (Figure 7) , condition three could be considered the second best combination of values; however, the high GRGe value that corresponds to condition three invalidates this option. As expected, the selection of the optimal condition becomes more complex as more variables are taken into account; in this sense, GRA offers a simplification of the decision making when selecting the best combustion conditions. Moreover, the GRG and GRGe structured method avoids leaving the selection criteria to the observer, providing more valid results.

Thus, the best quality fuels (with higher LHV) reach higher ignition flow rate values.


An important issue that is related to the utilization of biomass as an energy resource is that biomass has a disperse origin. Due to this fact, and to reduce logistic costs, most operations occur in small-scale plants [11] . Of all the biomass low-output boiler combustion methods, fixed bed boilers are most desirable because of their simplicity, reduced costs, higher automation, and batch control, which, in turn, enable the feeding of heterogeneous biofuels [12] .

Due to this fact, and to reduce logistic costs, most operations occur in small-scale plants.

Of all the biomass low-output boiler combustion methods, fixed bed boilers are most desirable because of their simplicity, reduced costs, higher automation, and batch control, which, in turn, enable the feeding of heterogeneous biofuels.


More than 1 billion people on earth are deprived of the basic human need that is access to potable water [1] . As reported by the World Health Organization (WHO), in the year 2017, around 2.5 billion people around the globe were devoid of adequate sanitation, in addition to hundreds of millions having no access to water at all [2] . It is important to mention that even though two-thirds of the Earth's surface is covered with water, however, fresh water sources make up a mere 2.5% of the global water distribution [3] . Furthermore, our limited water resources are being polluted with passing time and the accumulation of waste and pollutants in water is making water unsafe for human use [4] . In addition to depleting fresh water sources and deteriorating water quality due to poor water management, booming global population, increasing urbanization, industrialization, and expanding economies are further increasing the global water demand [5] . Waterborne diseases (e.g., hepatitis (A, E), typhoid, and cholera) are a major factor of morbidity and mortality in developing countries, and millions of lives are lost every year due to use of untreated water [6, 7] . For example, typhoid fever is known as a major public health concern that is caused by a gram-negative bacterium Salmonella enterica serotype typhi (S. typhi). It is a leading cause of mortality and morbidity in developing countries, especially in Asia [8] . Around 24.2 million cases of typhoid fever with around 75,000-208,000 deaths were reported during 2016 [9] .

More than 1 billion people on earth are deprived of the basic human need that is access to potable water.

As reported by the World Health Organization (WHO), in the year 2017, around 2.5 billion people around the globe were devoid of adequate sanitation, in addition to hundreds of millions having no access to water at all.

It is important to mention that even though two-thirds of the Earth's surface is covered with water, however, fresh water sources make up a mere 2.5% of the global water distribution.

Furthermore, our limited water resources are being polluted with passing time and the accumulation of waste and pollutants in water is making water unsafe for human use.

In addition to depleting fresh water sources and deteriorating water quality due to poor water management, booming global population, increasing urbanization, industrialization, and expanding economies are further increasing the global water demand.

Waterborne diseases (e.g., hepatitis (A, E), typhoid, and cholera) are a major factor of morbidity and mortality in developing countries, and millions of lives are lost every year due to use of untreated water.

It is a leading cause of mortality and morbidity in developing countries, especially in Asia.

Around 24.2 million cases of typhoid fever with around 75,000-208,000 deaths were reported during 2016.


As well known, limit analysis represents a valuable alternative to expensive step-by-step nonlinear FE simulations, to predict the ultimate mechanical response of masonry structures at collapse. In particular, an upper bound approach combined with a FE discretization of the actual heterogeneous microstructure provides in a rather easy way failure mechanisms and the collapse loads. A typical drawback of this approach is however the simplifying assumption of perfectly-plastic material behavior for masonry and for the FRP/masonry interface, i.e. the softening effect with consequent strain localization and possible limited ductility are neglected [12] [13] . Comparisons with experimental data confirm that the present limit analysis computations are capable of well approximate both failure mechanisms and load carrying capacity of the arches. Such tool, thanks to its simplicity, turns out to be especially suitable for all the practitioners interested in a fast evaluation of the beneficial effect induced by FRP strip retrofitting.

A typical drawback of this approach is however the simplifying assumption of perfectly-plastic material behavior for masonry and for the FRP/masonry interface, i.e. the softening effect with consequent strain localization and possible limited ductility are neglected.


L. monocytogenes continues to be an important food safety concern [1] . The etiological agent of listeriosis is L. monocytogenes, a gram-positive bacterium that contaminates meat, dairy products, unwashed raw vegetables, cabbage, and ready-to-eat food [2] - [4] . In immune-compromised individuals, L. monocytogenes causes meningitis, encephalitis, abortion in pregnant women and neonatal infections [5] . In the vast majority of human cases, infection is the result of consumption of contaminated food [6] .

L. monocytogenes continues to be an important food safety concern.

The etiological agent of listeriosis is L. monocytogenes, a gram-positive bacterium that contaminates meat, dairy products, unwashed raw vegetables, cabbage, and ready-to-eat food.

In immune-compromised individuals, L. monocytogenes causes meningitis, encephalitis, abortion in pregnant women and neonatal infections.

In the vast majority of human cases, infection is the result of consumption of contaminated food.


Our result showed L. monocytogenes isolates from various different PFGE profiles (10 pulsotypes) at 80% relative genetic similarity. The data from these studies indicate that we have identical pattern from different source with the same 4b serotype. It was shown that RTE (2011-SE-10) unrelated Meat (2011-SE-11) shared identical patterns, suggesting that they were serologically related. These data are in concordance with C pattern. Previous study indicated that the genetic patterns of strains showed no association with any of the properties that correlated with their origin [28] . It was found that similar subtypes of strains could be found in different product types and in different processing environments. The results of the present study clearly indicate that the recovery of identical patterns forming various food and patient strains does not prove that a particular food is the vehicle of infection [29] . It has been proposed a similar finding with an identical PFGE pattern that was shared by dif-ferent serotypes, even from different flagella antigen groups [30] . It was shown that the poor correlation between serotyping and molecular subtyping may be due to horizontal gene transfers or point mutations in genomic DNA resulting in phenotypic shifts that affected serotyping [31] .

Previous study indicated that the genetic patterns of strains showed no association with any of the properties that correlated with their origin.

The results of the present study clearly indicate that the recovery of identical patterns forming various food and patient strains does not prove that a particular food is the vehicle of infection.

It has been proposed a similar finding with an identical PFGE pattern that was shared by dif-ferent serotypes, even from different flagella antigen groups.

It was shown that the poor correlation between serotyping and molecular subtyping may be due to horizontal gene transfers or point mutations in genomic DNA resulting in phenotypic shifts that affected serotyping.


At least two factors suggested that size should influence the probability of white crappie starvation during the experiment. First, large age-0 white crappies had a greater prewinter energy density than did small ones, in both the field and experiment studies. Second, the energetic condition of all sizes of fish in the experiment was considerably less than that of fish sampled from the field. Thus, in our view, small fishes were most likely to starve during the experiment. However, size offered no survival advantage, as large fish died just as early as small fish. Indeed, nearly all starved white crappies survived 133 d in the mild winter. These results suggest that size-dependent starvation does not directly influence winter survival in systems at similar latitudes as Ohio, as well as those to the north. Our results also are consistent with previous research in a Wisconsin pond that failed to document size-dependent overwinter mortality in white crappies (Toneys and Coble 1979) . To the south, however, size-dependent starvation might still occur. Here, warmer winter temperatures should lead to greater metabolic rates and potential depletion of energy stores.

Our results also are consistent with previous research in a Wisconsin pond that failed to document size-dependent overwinter mortality in white crappies.


Our two techniques were applied to the case of plane Poiseuille flow (corresponding to G → ∞) in order to provide further confidence in the numerical codes. However, as the Reynolds number for the purely steady plane Poiseuille flow R 1 is related to the combined Reynolds number according to equations (1.1) and (2.7), some care must be exercised when interpreting the values of R N that are predicted for neutral conditions. Further, as the length scaling based on the Stokes layer thickness is not relevant to the purely steady flow situation, the appropriate wavenumber is now ah for the Poiseuille flow. With these transformations noted, part of the neutral stability curve for steady Poiseuille flow, in a channel of half-width h = 6, is shown in figure 1c . Here, the solid line indicates the results obtained from the Floquet technique, while the open circle marks a prediction from the DNS approach. The results are consistent and suggest a critical Reynolds number of R = 481.02, which corresponds to R 2 = 5772.24 and a critical wavenumber of a = 0.17 (or ah = 1.02); these conditions are close to the well-known classical results for plane Poiseuille flow (Drazin & Reid 1995) . Thus, at both extremes of the possible values of G, the DNS and Floquet techniques produce results that are reassuringly in very good agreement with previously available data.

The results are consistent and suggest a critical Reynolds number of R = 481.02, which corresponds to R 2 = 5772.24 and a critical wavenumber of a = 0.17 (or ah = 1.02); these conditions are close to the well-known classical results for plane Poiseuille flow.


Classifications that take into account only parameters related to nuclear morphology have been proposed. These classifications have higher correlation with breast cancer biological behavior than those that take into consideration cytoarchitectural features. Therefore, they provide important clinical information with prognostic value [22] .

Therefore, they provide important clinical information with prognostic value.


In the present paper, we will begin in section 2 with a consideration of important limitations of the raw data, including some analysis of the time and space history of the reports. In doing so, we will show a number of problems associated with inhomogeneities in the reporting of severe weather. A major issue is the secular (i.e., nonmeteorological) trend in the number of nontornadic severe thunderstorm reports, which is even more dramatic than that reported for tornadoes (Weiss and Vescio 1998) . Section 3 will present the time and space distributions of nontornadic severe thunderstorm reports comparable to those presented in BDK03 for tornadoes, with modifications to account for the different characteristics of nontornadic severe weather reports. An abbreviated review of the BDK03 methodology will be included. Section 4 will present conclusions and offer some discussion concerning the application of the data and our analyses of those data.

A major issue is the secular (i.e., nonmeteorological) trend in the number of nontornadic severe thunderstorm reports, which is even more dramatic than that reported for tornadoes.


The layout of the paper is the following: in Section 2 we consider the quantities that describe the statistical properties encoded in any probability distribution function; theoretical explanations as well as observational constraints for ζ are given. Section 3 is devoted to the issue of the ζ series convergence and loop corrections in the framework of the δN formalism, as well as to the presentation of the current knowledge about primordial non-gaussianity in slow-roll inflationary models. A particular subclass of small-field slow-roll inflationary models is the subject of Section 4 as it is this subclass of models that generate significant levels of non-gaussianity. The available parameter space for this subclass of models is constrained in Section 5 by taking into account some observational requirements such as the COBE normalisation, the scalar spectral tilt, and the minimal amount of inflation. Another requirement of methodological nature, the possible tree-level or one-loop dominance in P ζ and/or B ζ , is considered in this section. The level of non-gaussianity f N L in the bispectrum B ζ is calculated in Section 6 for models where ζ is generated during inflation; a comparison with the current literature is made. Section 7 is devoted to central issues in the consistency of the approach followed such as satisfying necessary conditions for the convergence of the ζ series and working in a perturbative regime. Finally in Section 8 we conclude. The professional reader who is already familiarized with the present ideas on the cosmological non-gaussianity may skip Sections 2 and 3, leaping directly to the new material starting from Section 4. As regards the level of non-gaussianity τ N L in the trispectrum T ζ , it will be studied following the sequence of ideas presented above in a companion paper [35] .

Finally in Section 8 we conclude.

As regards the level of non-gaussianity τ N L in the trispectrum T ζ , it will be studied following the sequence of ideas presented above in a companion paper.


Due to the functional dependence of the amount of expansion, ζ is usually Taylor-expanded (see Eq. (29)) and truncated up to some desired order so that f N L and τ N L are easily calculated (see for instance Eq. (33)). Two key questions arise when noting that it is impossible to extract general and useful information from the ζ series expansion in Eq. (29) until one chooses a definite inflationary model and calculates explicitly the N derivatives. First of all, when writing a general expression for f N L or τ N L in terms of the N derivatives, how do we know that such an expression is correct if the series convergence has not been examined? Moreover, if the convergence radius of the ζ series is already known, why is each term is the ζ series supposed to be smaller than the previous one so that cutting the series at any desired order is thought to be enough to keep the leading terms? Nobody seems to have formulated these questions before and, by following a naive line of thinking, f N L and τ N L were calculated for slow-roll inflationary models with canonical kinetic terms without checking the ζ series convergence and keeping only the presumably leading tree-level terms [18, 19, 20, 22, 27, 28] .

Nobody seems to have formulated these questions before and, by following a naive line of thinking, f N L and τ N L were calculated for slow-roll inflationary models with canonical kinetic terms without checking the ζ series convergence and keeping only the presumably leading tree-level terms.


It should be noted that the ability to retrieve the full electric field of an optical probe is not unique to TEX, but is shared by other techniques, such as frequency domain holography (FDH) and single-shot supercontinuum spectral interferometry (SSSI) [23] [24] [25] . The key advantage of TEX over FDH and SSSI is that recovery of the probe amplitude and phase does not require any reference data and is obtained from the TEX interferograms by a single Fourier transform (FT) operation, making it significantly easier to use than the others. By contrast, FDH and SSSI provide the pure electric-field retrieval of the probe without convolution. Figure 1 shows the setup for TEX implemented on an LPA-based THz source [1, 21, 26] . Using ∼400mJ, 800 nm, 45 fs pulses focused into a 2 mm gas jet of helium, electron bunches with large energy spreads and subpicosecond bunch durations were produced, resulting in the generation of CTR in the range of 0-4 THz. A portion of the radially polarized cone of THz emission was asymmetrically sampled by collection with an off-axis parabola (OAP). The resulting collimated beam of THz was primarily linearly polarized, with a residual transversely polarized component analytically estimated to be at the 10% level. The THz beam was then refocused with a second OAP onto a 200 μm thick gallium phosphide (GaP) crystal cut along h1; 1; 0i. An optical pulse split from the pump beam that generated the electrons was overcompressed, resulting in a temporally chirped pulse ("probe") with a FWHM duration of 2 ps. A second fully compressed optical pulse ("reader"), measured to have a FWHM duration of 45 fs, was also split from the pump beam. The probe and the THz pulses were overlapped colinearly in the GaP crystal, resulting in the EO interaction. A polarizer was used to purify the polarization state of the incident probe, and a second polarizer (referred to as an "analyzer") was used to convert polarization rotations into amplitude modulations. A quarter wave plate was used to offset the transmission to the 50% level, allowing both positive and negative THz fields to be resolved. The transmitted probe pulse was then combined colinearly with, but temporally offset from, the reader and sent into a 0:27 m imaging spectrometer with a 14 bit, 1 MP cooled CCD detector, producing a spectral interferogram image ("TEXogram"). A pair of achromatic lenses was used to image the interaction plane to the input plane of the spectrometer, where the spectometer slit is used to select a spatiotemporal slice of the probe.

It should be noted that the ability to retrieve the full electric field of an optical probe is not unique to TEX, but is shared by other techniques, such as frequency domain holography (FDH) and single-shot supercontinuum spectral interferometry (SSSI).

Figure 1 shows the setup for TEX implemented on an LPA-based THz source.


Optical probing has long been an important tool for the characterization of ultrafast phenomena because of its versatility, sensitivity, and ability to resolve both spatial and temporal features with high resolution. Because of its simplicity, the configuration most commonly used to probe temporal dynamics is a multishot one in which the delay of a probe pulse shorter than the features to be resolved is scanned. However, this approach is impractical for experiments done at low repetition rates or those in which the signal varies significantly from shot to shot, motivating the development of techniques capable of recording temporal variations in a single shot. Such is the case for the field of THz-time-domain spectroscopy (TDS), which relies on optical mapping of the electric-field temporal waveforms of pulses of THz radiation via a technique known as electro-optic sampling (EOS) [1] [2] [3] [4] . In EOS, the THz pulse induces a transient birefringence in an electro-optically active crystal, which results in a polarization rotation of a copropagating optical probe pulse. The rotation is then converted to a temporal amplitude modulation by a polarizer.

Such is the case for the field of THz-time-domain spectroscopy (TDS), which relies on optical mapping of the electric-field temporal waveforms of pulses of THz radiation via a technique known as electro-optic sampling (EOS).


Let a D t 0 < t 1 < ::: < t m < t mC1 D T; J 0 D OEa; t 1 and J k D .t k ; t kC1 .k D 1; 2; :::; m/: The rest of this paper is organized as follows. In Section 2, some definitions and conclusions are presented. In Section 3, we give the formula of general solution for impulsive differential equations with Riemann-Liouville fractional-order q2 (1, 2) . In Section 4, an example is provided to expand the main result.

In Section 3, we give the formula of general solution for impulsive differential equations with Riemann-Liouville fractional-order q2.


The fast growth of wind farms and super grids has led to rising interest in multi-terminal direct current (MTDC) systems. Recent advances in modular multi-level converters (MMCs) have led to increased research on voltage source converter MTDC (VSC-MTDC) applications [1] [2] [3] . In particular, DC voltage control schemes such as voltage margin control and voltage droop control are being developed to realize stable and effective control for the DC voltage of an MTDC system [4] [5] [6] [7] .

Recent advances in modular multi-level converters (MMCs) have led to increased research on voltage source converter MTDC (VSC-MTDC) applications.

In particular, DC voltage control schemes such as voltage margin control and voltage droop control are being developed to realize stable and effective control for the DC voltage of an MTDC system.


Slow and inefficient software can easily frustrate users and cause financial losses. Although researchers have devoted decades to transparently improving software performance, performance bugs continue to pervasively degrade performance and waste computation resources in the field [40] . Meanwhile, current support for combating performance bugs is preliminary due to the poor understanding of real-world performance bugs.

Although researchers have devoted decades to transparently improving software performance, performance bugs continue to pervasively degrade performance and waste computation resources in the field.


In this procedure the use of finite width bins is essential to ensure the cancellations between the virtual and bremsstrahlung contributions, needed to obtain a physical prediction. There are many drawbacks to this method. First of all, the bin edges can cause issues in the cancellations leading to instabilities which might need to be regulated. Secondly, the higher order phase space is extended with respect to the Born phase space. Consequently higher order corrections for an observable cover kinematic regions not accessible to the Born results, leading to instabilities in the predictions. Finally, in contrast to Leading Order (LO), one cannot define a weight at higher orders to a single event [3, [19] [20] [21] . At LO each V + 1 jet event has a probabilistic weight associated with it, allowing the events to be unweighted. This is an important step as the subsequent showering and detector simulations are potentially time expensive. At NLO and beyond this is no longer possible, making higher order predictions far more cumbersome and time consuming [22, 23] .

Finally, in contrast to Leading Order (LO), one cannot define a weight at higher orders to a single event.

At NLO and beyond this is no longer possible, making higher order predictions far more cumbersome and time consuming.


Great advances have been made over the last decades in calculating scattering amplitudes contributing to higher order corrections for processes including jets [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] . In contrast the Monte Carlo methods of integrating over phase space have not evolved much, relying instead on advances in computer power. Given this, there was no urgency to develop improved phase space integration methods. However, the required precision of predictions needed for current and future experimental analyses makes the development of improved phase space integration methods a crucial task. In this paper, we will investigate the promising avenue of projective phase space generators [13] [14] [15] [16] [17] .

Great advances have been made over the last decades in calculating scattering amplitudes contributing to higher order corrections for processes including jets.

In this paper, we will investigate the promising avenue of projective phase space generators.


From a numerical viewpoint, calculating the higher order corrections to the event weight is vastly improved as the dimensionality of the phase space integration at NLO is only three and independent of the jet multiplicity. This makes the integration tractable and straightforward to optimize with a large variety of numerical integration options available. Each colored line in the event has its own independent 3-dimensional integration. The cancellations between virtual and soft/collinear can be fine-tuned per Born event. One drawback of the method is that the subtraction method has to match this approach. One has to ensure the subtraction term projects back to the Born event and not to a variety of different Born events. The more physically motivated slicing methods will not be affected by this issue since these methods always project back to the originating Born event [21, 32] .

The more physically motivated slicing methods will not be affected by this issue since these methods always project back to the originating Born event.


With respect to the specific risk of development of eating disorders as measured with the EAT-40, our results do not confirm other previous data in this regard. The current study shows that 5.95% of the participants have a score ≥ 30 on the EAT-40. Previous recent studies in the same context had shown percentages between 7.13% and 9.43% [45, 46] . The most important fact seems to be that among participants with EAT-40 ≥ 30, 66.60% considered that they were overweight while this percentage was 28.10% in the case of participants with EAT-40 < 30. With respect to the weight misperception, more than 40% of participants with EAT-40 ≥ 30 and normal weight considered that they were overweight, this percentage being 18.76% in the case of individuals with EAT-40 < 30. In addition, participants with EAT-40 ≥ 30 showed poorer self-reported physical activity and more dieting especially for aesthetic reasons.

Previous recent studies in the same context had shown percentages between 7.13% and 9.43%.


Periodic structures are defined as media featuring a repetitive pattern of discrete elements referred to as unit cells. The repetitive pattern can be established through a periodic modulation of the geometric or material properties, or can manifest as a result of certain boundary conditions imposed on the structure [26] . Periodic structures are known for their ability to inhibit the propagation of waves within certain frequency bands (referred to as bandgaps), thereby functioning as mechanical filters or waveguides [30, 45, 34, 22] . In addition, the velocity of wave propagation is also dependent on the frequency and direction of propagation, which leads to significant frequency-dependent energy directivity [31, 39, 47] .

The repetitive pattern can be established through a periodic modulation of the geometric or material properties, or can manifest as a result of certain boundary conditions imposed on the structure.

Periodic structures are known for their ability to inhibit the propagation of waves within certain frequency bands (referred to as bandgaps), thereby functioning as mechanical filters or waveguides.

In addition, the velocity of wave propagation is also dependent on the frequency and direction of propagation, which leads to significant frequency-dependent energy directivity.


Forkhead Box M1 (FOXM1) is a member of the Forkhead Box transcription factors which is essential for cell proliferation and apoptosis in the development and function of many organs [13] [14] [15] [16] [17] . We previously reported that aberrant upregulation of FOXM1 is associated with the progression and development of human cervical squamous cell carcinoma (SCC) [18] . Biochemical and functional studies confirmed that FOXM1 is critically involved in cervical cancer cell growth through upregulating cyclin B1, cyclin D1 and cdc25B and downregulating p27 and p21 expressions. These findings suggest that FOXM1 plays a vital role in cervical cancer cell growth and oncogenesis.

Forkhead Box M1 (FOXM1) is a member of the Forkhead Box transcription factors which is essential for cell proliferation and apoptosis in the development and function of many organs.

We previously reported that aberrant upregulation of FOXM1 is associated with the progression and development of human cervical squamous cell carcinoma (SCC).


In order to solve the more general inpainting problem, non-local methods use external training images to predict the missing pixel values. To fill an image hole, Hays and Efros proposed to cut and paste a semantically similar patch from a huge database [10] . To inpaint a scene, images of the same scenes are retrieved from the Internet [24] . The result is obtained by registering and blending the retrieved images. When the scene is not contained in the training set or can be hardly retrieved, it is difficult to fill parts of the scene by cutting and pasting. Unlike the previous hand-crafted matching and editing, sparse coding is proposed to recover the images from a learned dictionary [18] . Recently, inpainting by convolutional neural networks has shown promising results [19, 25] .

To fill an image hole, Hays and Efros proposed to cut and paste a semantically similar patch from a huge database.

To inpaint a scene, images of the same scenes are retrieved from the Internet.

Unlike the previous hand-crafted matching and editing, sparse coding is proposed to recover the images from a learned dictionary.

Recently, inpainting by convolutional neural networks has shown promising results.


The delicate aspect within this coupling clearly relies in the fact that the value of the integral average must be comparable to the scaling factor λ which itself is involved in the construction of its support. On such intrinsic cylinders the parabolic p-Laplacian system (1.2) behaves in a certain sense like ∂ t u − λ p−2 ∆u. Therefore, using cylinders of the type Q ̺,λ (z o ) allows to re-balance the occurring multiplicative factor λ p−2 by re-scaling u in time with a factor λ 2−p . For an application of the technic of intrinsic scaling in the context of higher integrability we refer to Kinnunen & Lewis [19, 20] .

For an application of the technic of intrinsic scaling in the context of higher integrability we refer to Kinnunen & Lewis.