bluuebunny/crossref_metadata_2025 huggingface dataset:
The Incremental Demise of Urban Green Spaces
Authors: Colding Johan , Gren Åsa , Barthel Stephan
Published: May 2020

More precise explanations are needed to better understand why public green spaces are diminishing in cities, leading to the loss of ecosystem services that humans receive from natural systems. This paper is devoted to the incremental change of green spaces—a fate that is largely undetectable by urban residents. The paper elucidates a set of drivers resulting in the subtle loss of urban green spaces and elaborates on the consequences of this for resilience planning of ecosystem services. Incremental changes of greenspace trigger baseline shifts, where each generation of humans tends to take the current condition of an ecosystem as the normal state, disregarding its previous states. Even well-intended political land-use decisions, such as current privatization schemes, can cumulatively result in undesirable societal outcomes, leading to a gradual loss of opportunities for nature experience. Alfred E. Kahn referred to such decision making as ‘the tyranny of small decisions.’ This is mirrored in urban planning as problems that are dealt with in an ad hoc manner with no officially formulated vision for long-term spatial planning. Urban common property systems could provide interim solutions for local governments to survive periods of fiscal shortfalls. Transfer of proprietor rights to civil society groups can enhance the resilience of ecosystem services in cities.
Queuing System with Two Types of Customers and Dynamic Change of a Priority
Authors: Klimenok Valentina , Dudin Alexander , Dudina Olga , Kochetkova Irina
Published: May 2020

The use of priorities allows us to improve the quality of service of inhomogeneous customers in telecommunication networks, inventory and health-care systems. An important modern direction of research is to analyze systems in which priority of a customer can be changed during his/her stay in the system. We considered a single-server queuing system with a finite buffer, where two types of customers arrive according to a batch marked Markov arrival process. Type 1 customers have non-preemptive priority over type 2 customers. Low priority customers are able to receive high priority after the random amount of time. For each non-priority customer accepted into the buffer, a timer, which counts a random time having a phase type distribution, is switched-on. When the timer expires, the customer with some probability leaves the system unserved and with the complimentary probability gains the high priority. Such a type of queues is typical in many health-care systems, contact centers, perishable inventory, etc. We describe the behavior of the system by a multi-dimensional continuous-time Markov chain and calculate a number of the stationary performance measures of the system including the various loss probabilities as well as the distribution function of the waiting time of priority customers. The illustrative numerical examples giving insights into the system behavior are presented.
Global Behavior of an Arbitrary-Order Nonlinear Difference Equation with a Nonnegative Function
Authors: Ma Wen-Xiu
Published: May 2020

Let k , l be two integers with k ≥ 0 and l ≥ 2 , c a real number greater than or equal to 1, and f a multivariable function satisfying f ( w 1 , w 2 , w 3 , ⋯ , w l ) ≥ 0 when w 1 , w 2 ≥ 0 . We consider an arbitrary order nonlinear difference equation with the indicated function f: z n + 1 = c ( z n + z n − k ) + ( c − 1 ) z n z n − k + c f ( z n , z n − k , w 3 , ⋯ , w l ) z n z n − k + f ( z n , z n − k , w 3 , ⋯ , w l ) + c , n ≥ 0 , where initial values z − k , z − k + 1 , ⋯ , z 0 are positive and w i , i ≥ 3 , are arbitrary functions of z j , n − k ≤ j ≤ n . We classify its solutions into three types with different asymptotic behaviors, and verify the global asymptotic stability of its positive equilibrium solution z ¯ = c .
Modified King’s Family for Multiple Zeros of Scalar Nonlinear Functions
Authors: Behl Ramandeep , Kansal Munish , Salimi Mehdi
Published: May 2020

There is no doubt that there is plethora of optimal fourth-order iterative approaches available to estimate the simple zeros of nonlinear functions. We can extend these method/methods for multiple zeros but the main issue is to preserve the same convergence order. Therefore, numerous optimal and non-optimal modifications have been introduced in the literature to preserve the order of convergence. Such count of methods that can estimate the multiple zeros are limited in the scientific literature. With this point, a new optimal fourth-order scheme is presented for multiple zeros with known multiplicity. The proposed scheme is based on the weight function strategy involving functions in ratio. Moreover, the scheme is optimal as it satisfies the hypothesis of Kung–Traub conjecture. An exhaustive study of the convergence is shown to determine the fourth order of the methods under certain conditions. To demonstrate the validity and appropriateness for the proposed family, several numerical experiments have been performed. The numerical comparison highlights the effectiveness of scheme in terms of accuracy, stability, and CPU time.
Locating Arrays with Mixed Alphabet Sizes
Authors: Shi Ce , Jin Hao , Tsuchiya Tatsuhiro
Published: May 2020

Locating arrays (LAs) can be used to detect and identify interaction faults among factors in a component-based system. The optimality and constructions of LAs with a single fault have been investigated extensively under the assumption that all the factors have the same values. However, in real life, different factors in a system have different numbers of possible values. Thus, it is necessary for LAs to satisfy such requirements. We herein establish a general lower bound on the size of mixed-level ( 1 ¯ , t ) -locating arrays. Some methods for constructing LAs including direct and recursive constructions are provided. In particular, constructions that produce optimal LAs satisfying the lower bound are described. Additionally, some series of optimal LAs satisfying the lower bound are presented.
Inherited Risk Factors of Thromboembolic Events in Patients with Primary Nephrotic Syndrome
Authors: Ismail Gener , Obrișcă Bogdan , Jurubiță Roxana , Andronesi Andreea , Sorohan Bogdan , Hârza Mihai
Published: May 2020

Background and objectives. Venous thromboembolic events (VTEs) are among the most important complications of nephrotic syndrome (NS). We conducted a study that aimed to determine the prevalence of inherited risk factors for VTE in NS and to identify which factors are independent predictors of VTE. Materials and Methods. Thirty-six consecutive patients with primary NS that underwent percutaneous kidney biopsy between January 2017 and December 2017 were enrolled in this retrospective, observational study. VTEs were the primary outcome. Baseline demographic and biochemical data were collected from medical records, and genetic testing was done for polymorphisms of Factor V, PAI, MTHFR, and prothrombin genes. Results. The incidence of VTE was 28%, and the median time to event was 3 months (IQR: 2–9). The prevalence of inherited risk factors was 14% for Factor V Leiden mutation, 5.6% for prothrombin G20210A, 44.5% for PAI, and 27.8% for each of the two polymorphisms of the MTHFR gene. On multivariate analysis, the presence of at least two mutations was independently associated with the risk of VTE (HR, 8.92; 95% confidence interval, CI: 1.001 to 79.58, p = 0,05). Conclusions. These findings suggest that genetic testing for inherited thrombophilia in NS could play an important role in detecting high-risk patients that warrant prophylactic anticoagulation.
Actual Nutrition and Dietary Supplementation in Lithuanian Elite Athletes
Authors: Baranauskas Marius , Jablonskienė Valerija , Abaravičius Jonas Algis , Stukas Rimantas
Published: May 2020

Background and objectives: Health is partly determined by the state of one’s nutrition; it stimulates the body’s functional and metabolic adaptations to physical strain and helps one prevent sports injuries and get in shape in terms of body composition. This study aims to investigate the actual nutrition and dietary supplements taken by elite Lithuanian athletes and to identify the relationship between the dietary intake, dietary supplementation and body composition of elite athletes. Materials and Methods: The research subjects were 76.7% of Lithuanian elite athletes (N = 247). The actual diet was investigated using the 24 h recall dietary survey method. Dietary supplementation was studied applying the questionnaire method. Measurements of body composition were performed using the BIA (bioelectrical impedance analysis) tetra-polar electrodes and measuring resistivity with 8–12 tangent electrodes at different frequencies of signal: 5, 50 and 250 kHz. Results: Results indicate that among the athletes, 62% use too few carbohydrates and 77% use too much fat. Although the 3.5% increase in lean body mass (95% CI: −0.107, 7.070) helps gain an increased protein intake with food (p = 0.057), 38% of athletes consume too little protein with food. The athletes mostly use carbohydrates (86%), vitamins (81%), protein supplements (70%), and multivitamins (62%). We did not determine the impact (p > 0.05) of individual or complex supplement use on the lean body mass (%) or fat mass (%) values of athletes. Conclusions: Athletes consume insufficient carbohydrates, vitamin D, calcium, polyunsaturated fatty acids, omega-3 and omega-6 fatty acids and too much fat, saturated fatty acids, cholesterol, and they use proteins irrationally. Sport nutritionists should also focus on the risk of malnutrition for female athletes. Nutritional supplements partially offset macronutrient and micronutrient deficiency. Nevertheless, the effect of food supplements on the body composition of athletes is too small compared to the normal diet. Athletes ought to prioritize the formation of eating habits and only then use supplements.
Pleomorphic Adenoma of External Auditory Canal: Case Report of First Endoscopic Resection and Literature Review
Authors: Beckmann Sven , Dettmer Matthias S. , Caversaccio Marco D. , Giger Roland , Anschuetz Lukas
Published: May 2020

Ceruminous pleomorphic adenoma is a very rare, mostly benign tumor originating from the ceruminal glands in the external auditory canal. Histologically, it is a mixed tumor with epithelial and stromal parts of different proportions, and is recognized today by the World Health Organization (WHO) as a ceruminous adenoma. Similar to the pleomorphic adenoma of salivary glands, recurrence or malignant degeneration with cellular atypia and metastasis can occur on rare occasions. Here, we describe an 87-year old female patient with a growing spherical mass in the right external auditory canal. After exclusive endoscopic tumor resection, a ceruminous pleomorphic adenoma was histologically diagnosed. Due to the absence of nuclear pleomorphism, no increased mitotic rate, no perineural invasion and no fusion transcripts of the MYB or MYBL1 gene loci, an adenoid cystic carcinoma could be excluded. The postoperative course was without any evidence of complications. A literature review identified 44 articles with 49 patients that were considered. Hearing loss and ear sensations were the most commonly reported symptoms. Most cases underwent an excision via an endaural or retroauricular approach. Recurrences were described in four patients, three of which had a malignant transformation.
AC/DC Fields Demodulation Methods of Resonant Electric Field Microsensor
Authors: Yang Pengfei , Wen Xiaolong , Chu Zhaozhi , Ni Xiaoming , Peng Chunrong
Published: May 2020

Electric field microsensors have the advantages of a small size, a low power consumption, of avoiding wear, and of measuring both direct-current (DC) and alternating-current (AC) fields, which are especially suited to applications in power systems. However, previous reports were chiefly concerned with proposing new structures or improving the resolution, and there are no systematic studies on the signal characteristics of the microsensor output and the demodulation methods under different electric fields. In this paper, the use of an improved resonant microsensor with coplanar electrodes, and the signal characteristics under a DC field, power frequency field, and AC/DC hybrid fields were thoroughly analyzed respectively, and matching demodulation methods derived from synchronous detection were proposed. We theoretically obtained that the frequencies of the detectable electric fields should be less than half of the resonant frequency of the microsensor, and that the sensitivities of the microsensor were identical for AC/DC hybrid fields with different frequencies. Experiments were conducted to verify the proposed demodulation methods. Within electric field ranges of 0–667 kV/m, the uncertainties were 2.4% and 1.5% for the most common DC and 50 Hz power frequency fields, respectively. The frequency characteristic test results of the microsensor were in agreement with those of the theoretical analysis in the range of 0–1 kHz.
Proteome Cold-Shock Response in the Extremely Acidophilic Archaeon, Cuniculiplasma divulgatum
Authors: Bargiela Rafael , Lanthaler Karin , Potter Colin M. , Ferrer Manuel , Yakunin Alexander F. , Paizs Bela , Golyshin Peter N. , Golyshina Olga V.
Published: May 2020

The archaeon Cuniculiplasma divulgatum is ubiquitous in acidic environments with low-to-moderate temperatures. However, molecular mechanisms underlying its ability to thrive at lower temperatures remain unexplored. Using mass spectrometry (MS)-based proteomics, we analysed the effect of short-term (3 h) exposure to cold. The C. divulgatum genome encodes 2016 protein-coding genes, from which 819 proteins were identified in the cells grown under optimal conditions. In line with the peptidolytic lifestyle of C. divulgatum, its intracellular proteome revealed the abundance of proteases, ABC transporters and cytochrome C oxidase. From 747 quantifiable polypeptides, the levels of 582 proteins showed no change after the cold shock, whereas 104 proteins were upregulated suggesting that they might be contributing to cold adaptation. The highest increase in expression appeared in low-abundance (0.001–0.005 fmol%) proteins for polypeptides’ hydrolysis (metal-dependent hydrolase), oxidation of amino acids (FAD-dependent oxidoreductase), pyrimidine biosynthesis (aspartate carbamoyltransferase regulatory chain proteins), citrate cycle (2-oxoacid ferredoxin oxidoreductase) and ATP production (V type ATP synthase). Importantly, the cold shock induced a substantial increase (6% and 9%) in expression of the most-abundant proteins, thermosome beta subunit and glutamate dehydrogenase. This study has outlined potential mechanisms of environmental fitness of Cuniculiplasma spp. allowing them to colonise acidic settings at low/moderate temperatures.
Pan-Genome-Based Analysis as a Framework for Demarcating Two Closely Related Methanotroph Genera Methylocystis and Methylosinus
Authors: Oshkin Igor Y. , Miroshnikov Kirill K. , Grouzdev Denis S. , Dedysh Svetlana N.
Published: May 2020

The Methylocystis and Methylosinus are two of the five genera that were included in the first taxonomic framework of methanotrophic bacteria created half a century ago. Members of both genera are widely distributed in various environments and play a key role in reducing methane fluxes from soils and wetlands. The original separation of these methanotrophs in two distinct genera was based mainly on their differences in cell morphology. Further comparative studies that explored various single-gene-based phylogenies suggested the monophyletic nature of each of these genera. Current availability of genome sequences from members of the Methylocystis/Methylosinus clade opens the possibility for in-depth comparison of the genomic potentials of these methanotrophs. Here, we report the finished genome sequence of Methylocystis heyeri H2T and compare it to 23 currently available genomes of Methylocystis and Methylosinus species. The phylogenomic analysis confirmed that members of these genera form two separate clades. The Methylocystis/Methylosinus pan-genome core comprised 1173 genes, with the accessory genome containing 4941 and 11,192 genes in the shell and the cloud, respectively. Major differences between the genome-encoded environmental traits of these methanotrophs include a variety of enzymes for methane oxidation and dinitrogen fixation as well as genomic determinants for cell motility and photosynthesis.
Chemical and Biological Aspects of Montanine-Type Alkaloids Isolated from Plants of the Amaryllidaceae Family
Authors: Koutová Darja , Maafi Negar , Havelek Radim , Opletal Lubomír , Blunden Gerald , Řezáčová Martina , Cahlíková Lucie
Published: May 2020

Plants of the Amaryllidaceae family are promising therapeutic tools for human diseases and have been used as alternative medicines. The specific secondary metabolites of this plant family, called Amaryllidaceae alkaloids (AA), have attracted considerable attention due to their interesting pharmacological activities. One of them, galantamine, is already used in the therapy of Alzheimer’s disease as a long acting, selective, reversible inhibitor of acetylcholinesterase. One group of AA is the montanine-type, such as montanine, pancracine and others, which share a 5,11-methanomorphanthridine core. So far, only 14 montanine-type alkaloids have been isolated. Compared with other structural-types of AA, montanine-type alkaloids are predominantly present in plants in low concentrations, but some of them display promising biological properties, especially in vitro cytotoxic activity against different cancerous cell lines. The present review aims to summarize comprehensively the research that has been published on the Amaryllidaceae alkaloids of montanine-type.
Enzymes, Biocatalysis and Chemical Biology
Authors: Serra Stefano
Published: May 2020

Chemical transformations that take advantage of biocatalysis are of great interest to chemists [...]
Carbonic Anhydrase-IX Guided Albumin Nanoparticles for Hypoxia-mediated Triple-Negative Breast Cancer Cell Killing and Imaging of Patient-derived Tumor
Authors: Tatiparti Katyayani , Rauf Mohd Ahmar , Sau Samaresh , Iyer Arun K.
Published: May 2020

Triple-Negative Breast Cancer (TNBC) is considered as the most onerous cancer subtype, lacking the estrogen, progesterone, and HER2 receptors. Evaluating new markers is an unmet need for improving targeted therapy against TNBC. TNBC depends on several factors, including hypoxia development, which contributes to therapy resistance, immune evasion, and tumor stroma formation. In this study, we studied the curcumin analogue (3,4-Difluorobenzylidene Curcumin; CDF) encapsulated bovine serum albumin (BSA) nanoparticle for tumor targeting. For tumor targeting, we conjugated Acetazolamide (ATZ) with CDF and encapsulated it in the BSA to form a nanoparticle (namely BSA-CDF-ATZ). The in vitro cytotoxicity study suggested that BSA-CDF-ATZ is more efficient when compared to free CDF. The BSA-CDF-ATZ nanoparticles showed significantly higher cell killing in hypoxic conditions compared to normoxic conditions, suggesting better internalization of the nanoparticles into cancer cells under hypoxia. Fluorescent-dye labeled BSA-CDF-ATZ revealed higher cell uptake of the nanoparticle compared to free dye indicative of better delivery, substantiated by a high rate of apoptosis-mediated cell death compared to free CDF. The significantly higher tumor accumulation and low liver and spleen uptake in TNBC patient-derived tumor xenograft models confirm the significant potential of BSA-CDF-ATZ for targeted TNBC imaging and therapy.
Plectrabarbene, a New Abietane Diterpene from Plectranthus barbatus Aerial Parts
Authors: Al Musayeib Nawal M. , Amina Musarat , Al-Hamoud Gadah Abdulaziz , Mohamed Gamal A. , Ibrahim Sabrin R.M. , Shabana Samah
Published: May 2020

A new abietane diterpene namely plectrabarbene (2), together with two known compounds: sugiol (1) and 11,14-dihydroxy-8,11,13-abietatrien-7-one (3) have been isolated from the aerial parts of Plectranthus barbatus Andr. (Labiatae). The structures of these compounds were determined by various spectral techniques (e.g., UV, IR, NMR, and FAB) and by comparison with the literature data. A molecular docking study of the isolated diterpenes (1–3) was performed with AChE to gain an insight into their AChE inhibition mechanism. The results of docking experiments revealed that the all tested compounds showed binding affinity at the active site of AchE in comparison to donepezil.
Synthesis, Redox Properties and Antibacterial Activity of Hindered Phenols Linked to Heterocycles
Authors: Koshelev Vladimir N. , Primerova Olga V. , Vorobyev Stepan V. , Ivanova Ludmila V.
Published: May 2020

A series of benzotriazole, cyclic amides and pyrimidine derivatives, containing 2,6-di-tert-butyl-phenol fragments, were synthesized. The redox properties of obtained compounds were studied using the cyclic voltammetry on a platinum electrode in acetonitrile. The oxidation potentials of all substances were comparable to those of BHT. The obtained compounds were tested for their antibacterial activity, and N-(2-(3,5-di-tert-butyl-4-hydroxyphenyl)-2-oxoethyl)isatin (32 μg/mL) exerted good activity against Staphylococcus aureus.
Uncovering the First Atypical DS-1-like G1P[8] Rotavirus Strains That Circulated during Pre-Rotavirus Vaccine Introduction Era in South Africa
Authors: Mwangi Peter N. , Mogotsi Milton T. , Rasebotsa Sebotsana P. , Seheri Mapaseka L. , Mphahlele M. Jeffrey , Ndze Valantine N. , Dennis Francis E. , Jere Khuzwayo C. , Nyaga Martin M.
Published: May 2020

Emergence of DS-1-like G1P[8] group A rotavirus (RVA) strains during post-rotavirus vaccination period has recently been reported in several countries. This study demonstrates, for the first time, rare atypical DS-1-like G1P[8] RVA strains that circulated in 2008 during pre-vaccine era in South Africa. Rotavirus positive samples were subjected to whole-genome sequencing. Two G1P[8] strains (RVA/Human-wt/ZAF/UFS-NGS-MRC-DPRU1971/2008/G1P[8] and RVA/Human-wt/ZAF/UFS-NGS-MRC-DPRU1973/2008/G1P[8]) possessed a DS-1-like genome constellation background (I2-R2-C2-M2-A2-N2-T2-E2-H2). The outer VP4 and VP7 capsid genes of the two South African G1P[8] strains had the highest nucleotide (amino acid) nt (aa) identities of 99.6–99.9% (99.1–100%) with the VP4 and the VP7 genes of a locally circulating South African strain, RVA/Human-wt/ZAF/MRC-DPRU1039/2008/G1P[8]. All the internal backbone genes (VP1–VP3, VP6, and NSP1-NSP5) had the highest nt (aa) identities with cognate internal genes of another locally circulating South African strain, RVA/Human-wt/ZAF/MRC-DPRU2344/2008/G2P[6]. The two study strains emerged through reassortment mechanism involving locally circulating South African strains, as they were distinctly unrelated to other reported atypical G1P[8] strains. The identification of these G1P[8] double-gene reassortants during the pre-vaccination period strongly supports natural RVA evolutionary mechanisms of the RVA genome. There is a need to maintain long-term whole-genome surveillance to monitor such atypical strains.
Effects of Graphene Nanosheets with Different Lateral Sizes as Conductive Additives on the Electrochemical Performance of LiNi0.5Co0.2Mn0.3O2 Cathode Materials for Li Ion Batteries
Authors: Hsu Ting-Hao , Liu Wei-Ren
Published: May 2020

In this study, we focus on lateral size effects of graphene nanosheets as conductive additives for LiNi0.5Co0.2Mn0.3O2 (NCM) cathode materials for Li-ion batteries. We used two different lateral sizes of graphene, 13 (GN-13) and 28 µm (GN-28). It can be found that the larger sheet sizes of graphene nanosheets give a poorer rate capability. The electrochemical measurements indicate that GN-13 delivers an average capacity of 189.8 mAh/g at 0.1 C and 114.2 mAh/g at 2 C and GN-28 exhibits an average capacity of 179.4 mAh/g at 0.1 C and only 6 mAh/g at 2 C. Moreover, according to the results of alternating current (AC) impedance, it can be found that the GN-28 sample has much higher resistance than that of GN-13. The reason might be attributed to that GN-28 has a longer diffusion distance of ion transfer and the mismatch of particle size between NCM and GN-28. The corresponding characterization might provide important reference for Li-ion battery applications.
Inside–Out Method for Simulating a Reactive Distillation Process
Authors: Wang Liang , Sun Xiaoyan , Xia Li , Wang Jianping , Xiang Shuguang
Published: May 2020

Reactive distillation is a technical procedure that promotes material strengthening and its simulation plays an important role in the design, research, and optimization of reactive distillation. The solution to the equilibrium mathematical model of the reactive distillation process involves the calculation of a set of nonlinear equations. In view of the mutual influence between reaction and distillation, the nonlinear enhancement of the mathematical model and the iterative calculation process are prone to fluctuations. In this study, an improved Inside–Out method was proposed to solve the reaction distillation process. The improved Inside–Out methods mainly involved—(1) the derivation of a new calculation method for the K value of the approximate thermodynamic model from the molar fraction summation equation and simplifying the calculation process of the K value, as a result; and (2) proposal for an initial value estimation method suitable for the reactive distillation process. The algorithm was divided into two loop iterations—the outer loop updated the relevant parameters and the inside loop solved the equations, by taking the isopropyl acetate reactive distillation column as an example for verifying the improved algorithm. The simulation results presented a great agreement with the reference, and only the relative deviation of the reboiler heat duty reached 2.57%. The results showed that the calculation results were accurate and reliable, and the convergence process was more stable.
AOC-OPTICS: Automatic Online Classification for Condition Monitoring of Rolling Bearing
Authors: Hotait Hassane , Chiementin Xavier , Rasolofondraibe Lanto
Published: May 2020

Bearings are essential components in rotating machines. They ensure the rotation and power transmission. So, these components are essential elements for industrial machines. Thus, real-time monitoring is required to detect a possible anomaly, diagnose the failure of rolling bearing and follow its evolution. This paper presents a methodology for automatic online implementation of fault diagnosis of rolling bearings, by AOC-OPTICS (automatic online classification monitoring based on ordering points to identify clustering structure, OPTICS). The algorithm consists of three phases namely: initialization, detection and follow-up. These phases use the combination of features extraction methods, smart ranking, features weighting and classification by the OPTICS method. Two methods have been integrated in the dimension reduction step to improve the efficiency of detection and the followed of the defect (relief method and t-distributed stochastic neighbor embedding method). Thus, the determination of the internal parameters of the OPTICS method is improved. A regression model and exponential model are used to track the fault. The analytical simulations discuss the influence of parameters automation. Experimental validation shows detection with 100% accuracy and regression models of monitoring reaching R 2 = 0.992 .
An Innovative Design of an Integrated MED-TVC and Reverse Osmosis System for Seawater Desalination: Process Explanation and Performance Evaluation
Authors: Al-hotmani Omer Mohamed Abubaker , Al-Obaidi Mudhar Abdul Alwahab , John Yakubu Mandafiya , Patel Raj , Mujtaba Iqbal Mohammed
Published: May 2020

In recent times two or more desalination processes have been combined to form integrated systems that have been widely used to resolve the limitations of individual processes as well as producing high performance systems. In this regard, a simple integrated system of the Multi Effect Distillation (MED)/Thermal Vapour Compression (TVC) and Permeate Reprocessing Reverse Osmosis (PRRO) process was developed by the same authors and confirmed its validity after a comparison study against other developed configurations. However, this design has a considerable amount of retentate flowrate and low productivity. To resolve this issue, two novel designs of MED and double reverse osmosis (RO) processes including Permeate and Retentate Reprocessing designs (PRRP and RRRO) are developed and modelled in this paper. To systematically assess the consistency of the presented designs, the performance indicators of the novel designs are compared against previous simple designs of MED and PRRO processes at a specified set of operating conditions. Results show the superiority of the integrated MED and double permeate reprocessing design. This has specifically achieved both economic and environmental advantages where total productivity is increased by around 9% and total retentate flowrate (disposed to water bodies) is reduced by 5% with a marginally reduced energy consumption.
Research on State Recognition and Failure Prediction of Axial Piston Pump Based on Performance Degradation Data
Authors: Guo Rui , Zhao Zhiqian , Huo Saiyu , Jin Zhijie , Zhao Jingyi , Gao Dianrong
Published: May 2020

Degradation state recognition and failure prediction are the key steps of prognostic and health management (PHM), which directly affect the reliability of the equipment and the selection of preventive maintenance strategy. Given the problem that the distinction between feature vectors is not obvious and the accuracy of fault prediction is low, a method based on multi-class Gaussian process classification and Gaussian process regression (GPR) is studied by the vibration signal and flow signal in six degraded states of the axial piston pump. For degradation state recognition, the variational mode decomposition (VMD) was used to decompose the vibration signal, and obtaining intrinsic mode function (IMF) components with rich information. Subsequently, multi-scale permutation entropy (MPE) was employed to select feature vectors of IMF components in different states. In order to reduce feature dimensions and improve recognition performance, ReliefF was used to select feature vectors with high weight, then a method based on multi-class Gaussian process classification was established by using these feature vectors to realize the research on the degradation state recognition. The test results demonstrate that the method can effectively identify the degradation state. Its recognition rate reaches 98.9%. Besides, for failure prediction, through the analysis of the wear process and wear mechanism of the valve plate, the curve fitting between the flow and the wear amount was performed by GPR to realize the failure prediction of the axial piston pump. Depending on the evaluation index, the GPR obtained a better failure prediction effect. The results will assist in the realization of predictive maintenance, and which also has significant practical value in project items.
Testing Walking-Induced Vibration of Floors Using Smartphones Recordings
Authors: Martinelli Luca , Racic Vitomir , Dal Lago Bruno Alberto , Foti Francesco
Published: May 2020

Smartphone technology is rapidly evolving, adding sensors of growing accuracy and precision. Structural engineers are among customers who indirectly benefit from such technological advances. This paper tests whether accelerometers installed in new generations of smartphones can reach the accuracy of professional accelerometers created for vibration monitoring of civil engineering structures, and how they can be useful. The paper describes an experimental study designed to measure walking-induced vibrations of a slender prefabricated prestressed concrete slab. Both traditional, high-accuracy, accelerometers and those integrated into commercial smartphones were used for experimental data collection. Direct comparison of the recordings yielded two key findings: the accuracy of smartphone accelerometers largely depends on the specific smartphone model, and nevertheless is satisfactory for preliminary modal testing at the very least. Furthermore, the smartphone measured accelerations of the lower back were used successfully to indirectly measure pedestrian walking loads.
Determination of the Regularization Parameter to Combine Heterogeneous Observations in Regional Gravity Field Modeling
Authors: Liu Qing , Schmidt Michael , Pail Roland , Willberg Martin
Published: May 2020

Various types of heterogeneous observations can be combined within a parameter estimation process using spherical radial basis functions (SRBFs) for regional gravity field refinement. In this process, regularization is in most cases inevitable, and choosing an appropriate value for the regularization parameter is a crucial issue. This study discusses the drawbacks of two frequently used methods for choosing the regularization parameter, which are the L-curve method and the variance component estimation (VCE). To overcome their drawbacks, two approaches for the regularization parameter determination are proposed, which combine the L-curve method and VCE. The first approach, denoted as “VCE-Lc”, starts with the calculation of the relative weights between the observation techniques by means of VCE. Based on these weights, the L-curve method is applied to determine the regularization parameter. In the second approach, called “Lc-VCE”, the L-curve method determines first the regularization parameter, and it is set to be fixed during the calculation of the relative weights between the observation techniques from VCE. To evaluate and compare the performance of the two proposed methods with the L-curve method and VCE, all these four methods are applied in six study cases using four types of simulated observations in Europe, and their modeling results are compared with the validation data. The RMS errors (w.r.t the validation data) obtained by VCE-Lc and Lc-VCE are smaller than those obtained from the L-curve method and VCE in all the six cases. VCE-Lc performs the best among these four tested methods, no matter if using SRBFs with smoothing or non-smoothing features. These results prove the benefits of the two proposed methods for regularization parameter determination when different data sets are to be combined.
A Convolutional Neural Network with Parallel Multi-Scale Spatial Pooling to Detect Temporal Changes in SAR Images
Authors: Chen Jia-Wei , Wang Rongfang , Ding Fan , Liu Bo , Jiao Licheng , Zhang Jie
Published: May 2020

In synthetic aperture radar (SAR) image change detection, it is quite challenging to exploit the changing information from the noisy difference image subject to the speckle. In this paper, we propose a multi-scale spatial pooling (MSSP) network to exploit the changed information from the noisy difference image. Being different from the traditional convolutional network with only mono-scale pooling kernels, in the proposed method, multi-scale pooling kernels are equipped in a convolutional network to exploit the spatial context information on changed regions from the difference image. Furthermore, to verify the generalization of the proposed method, we apply our proposed method to the cross-dataset bitemporal SAR image change detection, where the MSSP network (MSSP-Net) is trained on a dataset and then applied to an unknown testing dataset. We compare the proposed method with other state-of-arts and the comparisons are performed on four challenging datasets of bitemporal SAR images. Experimental results demonstrate that our proposed method obtain comparable results with S-PCA-Net on YR-A and YR-B dataset and outperforms other state-of-art methods, especially on the Sendai-A and Sendai-B datasets with more complex scenes. More important, MSSP-Net is more efficient than S-PCA-Net and convolutional neural networks (CNN) with less executing time in both training and testing phases.
Mapping Rice Paddy Based on Machine Learning with Sentinel-2 Multi-Temporal Data: Model Comparison and Transferability
Authors: Zhang Weichun , Liu Hongbin , Wu Wei , Zhan Linqing , Wei Jing
Published: May 2020

Rice is an important agricultural crop in the Southwest Hilly Area, China, but there has been a lack of efficient and accurate monitoring methods in the region. Recently, convolutional neural networks (CNNs) have obtained considerable achievements in the remote sensing community. However, it has not been widely used in mapping a rice paddy, and most studies lack the comparison of classification effectiveness and efficiency between CNNs and other classic machine learning models and their transferability. This study aims to develop various machine learning classification models with remote sensing data for comparing the local accuracy of classifiers and evaluating the transferability of pretrained classifiers. Therefore, two types of experiments were designed: local classification experiments and model transferability experiments. These experiments were conducted using cloud-free Sentinel-2 multi-temporal data in Banan District and Zhongxian County, typical hilly areas of Southwestern China. A pure pixel extraction algorithm was designed based on land-use vector data and a Google Earth Online image. Four convolutional neural network (CNN) algorithms (one-dimensional (Conv-1D), two-dimensional (Conv-2D) and three-dimensional (Conv-3D_1 and Conv-3D_2) convolutional neural networks) were developed and compared with four widely used classifiers (random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM) and multilayer perceptron (MLP)). Recall, precision, overall accuracy (OA) and F1 score were applied to evaluate classification accuracy. The results showed that Conv-2D performed best in local classification experiments with OA of 93.14% and F1 score of 0.8552 in Banan District, OA of 92.53% and F1 score of 0.8399 in Zhongxian County. CNN-based models except Conv-1D provided more desirable performance than non-CNN classifiers. Besides, among the non-CNN classifiers, XGBoost received the best result with OA of 89.73% and F1 score of 0.7742 in Banan District, SVM received the best result with OA of 88.57% and F1 score of 0.7538 in Zhongxian County. In model transferability experiments, almost all CNN classifiers had low transferability. RF and XGBoost models have achieved acceptable F1 scores for transfer (RF = 0.6673 and 0.6469, XGBoost = 0.7171 and 0.6709, respectively).
Individual Detection of Citrus and Avocado Trees Using Extended Maxima Transform Summation on Digital Surface Models
Authors: García-Murillo Daniel G. , Caicedo-Acosta J. , Castellanos-Dominguez G.
Published: May 2020

Individual tree detection (ITD) locates plants from images to estimate monitoring parameters, helping the management of forestry and agriculture systems. As a low-cost solution to help farm monitoring, digital surface models are increasingly involved together with mathematical morphology techniques within the framework of ITD tasks. However, morphology-based approaches are prone to omission and commission errors due to the shape and size of structuring elements. To reduce the error rate in ITD tasks, we introduce a morphological transform that is based on the local maxima segmentation (Cumulative Summation of Extended Maxima transform (SEMAX)) with the aim to enhance the seed selection by extracting information collected from different heights. Validation is performed on data collected from the plantations of citrus and avocado using different measures of precision. The results obtained by the SEMAX approach show that the devised ITD algorithm provides enough accuracy, and achieves the lowest false-negative rate than other compared state-of-art approaches do.
Spatial-Adaptive Siamese Residual Network for Multi-/Hyperspectral Classification
Authors: He Zhi , He Dan
Published: May 2020

Deep learning methods have been successfully applied for multispectral and hyperspectral images classification due to their ability to extract hierarchical abstract features. However, the performance of these methods relies heavily on large-scale training samples. In this paper, we propose a three-dimensional spatial-adaptive Siamese residual network (3D-SaSiResNet) that requires fewer samples and still enhances the performance. The proposed method consists of two main steps: construction of 3D spatial-adaptive patches and Siamese residual network for multiband images classification. In the first step, the spectral dimension of the original multiband images is reduced by a stacked autoencoder and superpixels of each band are obtained by the simple linear iterative clustering (SLIC) method. Superpixels of the original multiband image can be finally generated by majority voting. Subsequently, the 3D spatial-adaptive patch of each pixel is extracted from the original multiband image by reference to the previously generated superpixels. In the second step, a Siamese network composed of two 3D residual networks is designed to extract discriminative features for classification and we train the 3D-SaSiResNet by pairwise inputting the training samples into the networks. The testing samples are then fed into the trained 3D-SaSiResNet and the learned features of the testing samples are classified by the nearest neighbor classifier. Experimental results on three multiband image datasets show the feasibility of the proposed method in enhancing classification performance even with limited training samples.
Recycling of Waste Materials for Stabilizing Ash from Co-Combustion of Municipal Solid Wastes with an Olive By-Product: Soil Leaching Experiments
Authors: Vamvuka Despina , Alexandrakis Stelios , Alevizos George , Stratakis Antonios
Published: May 2020

In the context of the current environmental policies of the European Union promoting the recycling and reuse of waste materials, this work aimed at investigating the environmental impact of ashes produced from the co-combustion of municipal solid wastes with olive kernel in a fixed bed unit. Lignite fly ash, silica fume, wheat straw ash, meat and bone meal biochar, and mixtures of them were used as stabilizing ash materials. All solids were characterized by physical, chemical and mineralogical analyses. Column leaching tests of unstabilized and stabilized ash through a quarzitic soil were conducted, simulating field conditions. pH, electrical conductivity, chloride, sulphate and phosphate ions, major and trace elements in the leachates were measured. The results showed that alkaline compounds were partially dissolved in water extracts, increasing their pH and thus decreasing the leachability of heavy metals from the ash. Cr leached from unstabilized ash reached a hazardous level. Upon the stabilization of ash, the concentrations of heavy metals in the extracts were reduced between 9% and 100%, and were below legislation limits for disposal, apart from Cr. The latter was achieved only when meat and bone meal biochar was used as stabilizer. Entrapment of ash elements was assigned to the amorphous silica and to the phosphates of the stabilizing materials, as well as complexed silicates formed during the process.
Monitoring Workloads of a Professional Female Futsal Team over a Season: A Case Study
Authors: Lago-Fuentes Carlos , Jiménez-Loaisa Alejandro , Padrón-Cabo Alexis , Fernández-Villarino Marián , Mecías-Calvo Marcos , Travassos Bruno , Rey Ezequiel
Published: May 2020

The aims of this study were to describe the external and internal workloads in a professional female futsal team during a whole season and to compare workloads during different periods of the season. Ten professional female futsal players (age 22.8 ± 4.3 years; 5.1 ± 2.4 years of experience; weight 61.9 ± 7.1 kg; height 1.66 ± 0.06 m) participated voluntarily in this study during the whole season. The internal workload was measured by the session-Rate of perceived exertion (session-RPE) method, while the external workload was indirectly measured by considering the training and match volume and the type of contents of each session over 43 weeks. Mean sRPE throughout the season was 319.9 ± 127.1 arbitrary units (AU). Higher internal loads (total weekly training load and strain) were reported during the pre-season compared with the in-season mesocycles (p < 0.05); meanwhile, the fifth to eighth mesocycles of the in-season showed an oscillatory pattern. Finally, Monday was the most-demanding session during the in-season period over the Thursday (p < 0.05; effect size: 1.33) followed by match day, meanwhile no statistical differences were reported during different sessions of the pre-season microcycle (p > 0.05). This study suggests that microcycles of pre-season present a stable load pattern, meanwhile workloads during the in-season period report a tapering strategy in a professional female futsal team.
Comparative Effects of High-Intensity Interval Training vs Moderate-Intensity Continuous Training in Phase III of a Tennis-Based Cardiac Rehabilitation Program: A Pilot Randomized Controlled Trial
Authors: Villafaina Santos , Giménez-Guervós Pérez María José , Fuentes-García Juan Pedro
Published: May 2020

The aim of the present study was to investigate the effects of two tennis-based cardiac rehabilitation programs using two protocols: high-intensity interval training (HIIT) and moderate-intensity continuous training (MICT) in the body composition, physical fitness, heart rate variability, and health-related quality of life. It was performed as a single-blinded randomized controlled trial of 21 people with acute coronary syndrome. The 12-week cardiac rehabilitation program consisted of three sessions per week of 60 min with the main part consisting of 10 sets of 15 s with 15 s of active recovery at 85%–90% of their maximum heart rate or 40 min at 70%–85% of their maximum heart rate in the HIIT and the MICT groups, respectively. Results show that both cardiac rehabilitation programs improved the agility and the mental components of the health-related quality of life (p-value < 0.05). The HIIT protocol also showed a significant improvement in the flexibility of upper and lower limbs (p-value < 0.05). Moreover, significant group × time interaction was found in the handgrip strength in favor of the HIIT group (p-value = 0.035). Nevertheless, no significant effects on cardiorespiratory fitness or heart rate variability were found. Importantly, no adverse event was detected, so HIIT appears to be a safe and effective alternative for the rehabilitation of patients with acute coronary syndrome.
Understanding Chinese Residents’ Waste Classification from a Perspective of Intention–Behavior Gap
Authors: Zhang Leibao , Hu Qiuxian , Zhang Shuai , Zhang Wenyu
Published: May 2020

It remains uncertain as to whether people who support waste classification end up transforming such environmental initiation into reality. Thus, to investigate the intention and actual behavior of Chinese residents on waste classification and the influencing factors, this study integrated the theory of planned behavior (TPB) and norm activation model (NAM), and extended them by adding external information factors, namely information publicity type and information quality. A questionnaire survey was conducted in mainland China, and the primary data from 349 individuals were analyzed by partial least squares structural equation modeling (PLS-SEM) to verify the model. The conclusions confirmed that personal norm was a major predictor of residents’ waste classification intention, and there exists a gap between Chinese residents’ waste classification intentions and actual behaviors. Furthermore, strategies such as moral education and information publicity are important in policy implementation. These findings are helpful for Chinese policymakers in promoting and planning waste classification, and also provide experiences to other countries for combating similar waste problems in their metropolises.