bluuebunny/crossref_metadata_2025 huggingface dataset:
Performance of a Gasifier Reactor Prototype without a Blower Using Palm Oil Waste
Authors: Nur Chairat Arief Suardi , Antono Vendy , Prayudi Prayudi , Nurhasanah Roswati , Batih Hakimul
Published: December 2021

The usage of palm oil empty fruit bunches (EFBs) in the gasification process adds value to the empty bunches as a renewable energy source. In this study, we design and manufacture a new updraft type of gasifier reactor without a blower so that it does not require electric power in its operation, but uses power from engine suction. Our test results compare the use of biomass waste in conjunction with diesel fuel to run a diesel power plant for 20 min at a load of 10,000 W: diesel with coconut shell charcoal (350 mL), diesel with acacia wood charcoal (380 mL), and diesel with EFB charcoal (400 mL). The test shows that the highest efficient and the most optimal biomass in the gasification process is coconut shell charcoal, because coconut shell charcoal has a dense structure and, at the time of the experiment, the coconut shell charcoal was filled 15 cm below the gas outlet pipe hole. From the standpoint of the economic value of the gasifier reactor that is proposed in this study, the result with the lowest cost is that of diesel with EFB charcoal, because, in this experiment, EFBs were the biomass that was not purchased. The additional use of empty fruit bunches of charcoal is able to save 50% diesel usage.
Investigation of Effects of Copper, Zinc, and Strontium Doping on Electrochemical Properties of Titania Nanotube Arrays for Neural Interface Applications
Authors: Khudhair Dhurgham , Gaburro Julie , Hamedani Hoda Amani , Barlow Anders , Garmestani Hamid , Bhatti Asim
Published: December 2021

Direct interaction with the neuronal cells is a prerequisite to deciphering useful information in understanding the underlying causes of diseases and functional abnormalities in the brain. Precisely fabricated nanoelectrodes provide the capability to interact with the brain in its natural habitat without compromising its functional integrity. Yet, challenges exist in terms of the high cost and complexity of fabrication as well as poor control over the chemical composition and geometries at the nanoscale, all imposed by inherent limitations of current micro/nanofabrication techniques. In this work, we report on electrochemical fabrication and optimization of vertically oriented TiO2 nanotube arrays as nanoelectrodes for neural interface application. The effects of zinc, strontium, and copper doping on the structural, electrochemical, and biocompatibility properties of electrochemically anodized TiO2 nanotube arrays were investigated. It was found that doping can alter the geometric features, i.e., the length, diameter, and wall thickness, of the nanotubes. Among pure and doped samples, the 0.02 M copper-doped TiO2 nanotubes exhibited superior electrochemical properties, with the highest specific storage capacitance of 130 F g−1 and the lowest impedance of 0.295 KΩ. In addition, regeneration of Vero cells and neurons was highly promoted on (0.02 M) Cu-doped TiO2 nanotube arrays, with relatively small tube diameters and more hydrophilicity, compared with the other two types of dopants. Our results suggest that in situ doping is a promising method for the optimization of various structural and compositional properties of electrochemically anodized nanotube arrays and improvement of their functionality as a potential nanoelectrode platform for neural interfacing.
Numerical Study of Effect of Sawtooth Riblets on Low-Reynolds-Number Airfoil Flow Characteristic and Aerodynamic Performance
Authors: Yang Xiaopei , Wang Jun , Jiang Boyan , Li Zhi’ang , Xiao Qianhao
Published: December 2021

Riblets with an appropriate size can effectively restrain turbulent boundary layer thickness and reduce viscous drag, but the effects of riblets strongly depend on the appearance of the fabric that is to be applied and its operating conditions. In this study, in order to improve the aerodynamic performance of a low-pressure fan by using riblet technology, sawtooth riblets on NACA4412 airfoil are examined at the low Reynolds number of 1 × 105, and the airfoil is operated at angles of attack (AOAs) ranging from approximately 0° to 12°. The numerical simulation is carried out by employing the SST k–ω turbulence model through the Ansys Fluent, and the effects of the riblets’ length and height on aerodynamic performance and flow characteristics of the airfoil are investigated. The results indicate that the amount of drag reduction varies greatly with riblet length and height and the AOA of airfoil flow. By contrast, the riblets are detrimental to the airfoil in some cases. The most effective riblet length is found to be a length of 0.8 chord, which increases the lift and reduces the drag under whole AOA conditions, and the maximum improvements in both are 17.46% and 15.04%, respectively. The most effective height for the riblet with the length of 0.5 chord is 0.6 mm. This also improves the aerodynamic performance and achieves a change rate of 12.67% and 14.8% in the lift and drag coefficients, respectively. In addition, the riblets facilitate a greater improvement in airfoil at larger AOAs. The flow fields demonstrate that the riblets with a drag reduction effect form “the antifriction-bearing” structure near the airfoil surface and effectively restrain the trailing separation vortex. The ultimate cause of the riblet drag reduction effect is the velocity gradient at the bottom of the boundary layers being increased by the riblets, which results in a decrease in boundary thickness and energy loss.
Optimalization of Design Parameters of Experimental Installation Concerning Preparation of Liquid Feed Mixtures
Authors: Solonscikov Pavel , Barwicki Jan , Savinyh Peter , Gaworski Marek
Published: December 2021

The article describes the initial conditions for the development of universal mechanization means for the process of mixing dry and liquid components. The essence of the method is to study the motion of a particle with different constructive and physical properties of the medium. The mathematical model of particle motion is based on theoretical mechanics and hydraulics. In this case, the main purpose of the study is to find the optimal design parameters for the installation. At the beginning, a theoretical analysis of the installation was carried out using the methods of classical mechanics and hydraulics. Experimental studies were carried out in several stages. At the beginning, one-factor experiments were conducted, followed by allocating the main factors and determining their interaction. Then, using the methods of planning the experiment, we obtained the regression equations and further optimized the parameters to summarize the main findings of the article. Modern installations should have versatility in any technological line; for example, an installation is presented that can not only mix, but further transport the mixture like a conventional pump, while providing a dosing device that is necessary for the feeding of dry components. Theoretical studies have been carried out in which the design of the impeller is substantiated at various speeds. Experimental studies to determine the design parameters of the installation are in continuous operation. The degree of homogeneity was Θ = 74%, with β2 = 80 … 100° and βst = 65 … 102°, while the value of the consumption of electrical energy is equal to Eel = 0.265 … 0.28 kWh/t.
Evaluation of Maturity and Greenhouse Gas Emission in Co-Composting of Chicken Manure with Tobacco Powder and Vinasse/Mushroom Bran
Authors: Zhang Bangxi , Yin Rongxiu , Tan Yi , Fan Beibei , Li Hangyu , Peng Yutao , Yang Rende , Li Guoxue
Published: December 2021

This study investigated the effects of different proportions (0%, 5%, 10%, 15%) of bulking agent (vinasse, mushroom bran, and tobacco powder) on maturity and gaseous emissions in chicken manure composting. The results showed that all of the treatments reached the standard of harmless disposal. With the exception of the control treatment, the CH4, N2O, and NH3 emissions in the treatments that had been prepared using the addition of mixed bulking agents were effectively reduced by 2.9–30.6%, 8.30–80.9%, and 37.3–26.6%; their compost maturity also met the Chinese national standard. Specifically, 10% mushroom bran combined with 5% tobacco powder was the optimal combination for simultaneously improving the maturity and reducing greenhouse gas emission in chicken manure composting.
A Weighted EFOR Algorithm for Dynamic Parametrical Model Identification of the Nonlinear System
Authors: Li Yuqi , Yang Dayong , Wen Chuanmei
Published: December 2021

In this paper, the Nonlinear Auto-Regressive with exogenous inputs (NARX) model with parameters of interest for design (NARX-M-for-D), where the design parameter of the system is connected to the coefficients of the NARX model by a predefined polynomial function is studied. For the NARX-M-for-D of nonlinear systems, in practice, to predict the output by design parameter values are often difficult due to the uncertain relationship between the design parameter and the coefficients of the NARX model. To solve this issue and conduct the analysis and design, an improved algorithm, defined as the Weighted Extended Forward Orthogonal Regression (WEFOR), is proposed. Firstly, the initial NARX-M-for-D is obtained through the traditional Extended Forward Orthogonal Regression (EFOR) algorithm. Then a weight matrix is introduced to modify the polynomial functions with respect to the design parameter, and then an improved model, which is referred to as the final NARX-M-for-D is established. The genetic algorithm (GA) is used for deriving the weight matrix by minimizing the normalized mean square error (NMSE) over the data sets corresponding to the design parameter values used for modeling and first prediction. Finally, both the numerical and experimental studies are conducted to demonstrate the application of the WEFOR algorithm. The results indicate that the final NARX-M-for-D can accurately predict the system output of a nonlinear system. The new algorithm is expected to provide a reliable model for dynamic analysis and design of the nonlinear system.
HAZOP Ontology Semantic Similarity Algorithm Based on ACO-GRNN
Authors: Bai Yujie , Gao Dong , Peng Lanfei
Published: December 2021

Hazard and operability (HAZOP) is an important safety analysis method, which is widely used in the safety evaluation of petrochemical industry. The HAZOP analysis report contains a large amount of expert knowledge and experience. In order to realize the effective expression and reuse of knowledge, the knowledge ontology is constructed to store the risk propagation path and realize the standardization of knowledge expression. On this basis, a comprehensive algorithm of ontology semantic similarity based on the ant clony optimization generalized neural network (ACO-GRNN) model is proposed to improve the accuracy of semantic comparison. This method combines the concept name, semantic distance, and improved attribute coincidence calculation method, and ACO-GRNN is used to train the weights of each part, avoiding the influence of manual weighting. The results show that the Pearson coefficient of this method reaches 0.9819, which is 45.83% higher than the traditional method. It could solve the problems of semantic comparison and matching, and lays a good foundation for subsequent knowledge retrieval and reuse.
Removal of Heavy Metals from Wastewater Using Novel Polydopamine-Modified CNTs-Based Composite Membranes
Authors: Altaf Faizah , Ahmed Shakeel , Usman Muhammad , Batool Tahira , Shamshad Jaweria , Bocchetta Patrizia , Batool Rida
Published: December 2021

The presence of major heavy metals including Pb2+, Cu2+, Co2+, Ni2+, Hg2+, Cr6+, Cd2+, and Zn2+ in water is of great concern because they cannot degrade or be destroyed. They are toxic even at very low concentrations. Therefore, it is necessary to remove such toxicants from water. In the current study, polydopamine carbon nanotubes (PD-CNTs) and polysulfone (PS) composite membranes were prepared. The structural and morphological features of the prepared PDCN composite membranes were studied using FTIR, XRD, SEM, and EDS. The potential application of PDCNs for heavy metal removal was studied for the removal of Pb2+, Cr6+, and Cd2+ from wastewater. The maximum removal efficiency of 96.1% was obtained for Cr6+ at 2.6 pH using a composite membrane containing 1.0% PD-CNTs. The removal efficiencies decreased by 64.1 and 73.4, respectively, by enhancing the pressure from 0.50 up to 0.85 MPa. Under the same circumstances, the percentages of Pb+2 removal at 0.49 bar by the PDCNS membranes containing 0.5% and 1.0% PD-CNT were 70 and 90.3, respectively, and decreased to 54.3 and 57.0, respectively, upon increasing the pressure to 0.85 MPa. The results showed that PDCNS membranes have immense potential for the removal of heavy metals from water.
Leuconostoc mesenteroides and Pediococcus pentosaceus Non-Alcoholic Pearl Millet Beverage Enriched with Moringa oleifera Leaf Powder: Nutritional and Sensory Characteristics
Authors: Jideani Victoria A. , Ratau Mmaphuti A. , Okudoh Vincent I.
Published: December 2021

Non-alcoholic cereal beverages (NACB) are usually produced through uncontrolled fermentation driven by a cocktail of bacteria resulting in final product variability. Hence, to commercialise fermented traditional cereal beverages bioburden microbial cultures are required. This investigation aimed to evaluate the physicochemical, nutritional, and sensory characteristics of NACB produced using pure cultures of Leuconostoc mesenteroides and Pediococcus pentosaceus. Pearl millet extract (PME) pasteurised at 85 °C for 15 min and cooled to 40 °C was inoculated with Leuconostoc mesenteroides and Pediococcus pentosaceus at 0.050% and 0.025% (1:0.5), respectively, and fermented at 37 °C for 18 h, referred to as plain non-alcoholic pearl millet beverage (PNAPMB). Moringa supplemented non-alcoholic pearl millet beverage (MSNAPMB) was produced following the same method as PNAPMB but a 4% moringa leaf extract powder was added before hydration of the pearl millet powder. The traditional non-alcoholic pearl millet beverage (TNAPMB) was prepared by mixing water and pearl millet flour (1:1.25; PMF:Water) and hydrated for 3 h at 25 °C. The mixture was divided into ¼ slurry which was mixed with sprouted rice flour (SRF) and ¾ portion that was gelatinised with 1 L of boiling water and cooled to 40 °C. The two portions were mixed and fermented at 37 °C for 18 h, followed by sieving, dilution with water (1:0.5, filtrate:water), and pasteurization for 15 min at 85 °C. The growth of lactic acid bacteria, pH, total titratable acidity (TTA), and sugar in PNAPMB and MSNAPMB were determined at 3 h intervals during fermentation. The final beverages were also analysed for proximate, colour and metabolites. The lactic acid bacteria were significantly (p < 0.05) affected by the fermentation period and increased from 3.32 to 7.97 log CFU/mL (pH 4.14) and 3.58 to 8.38 log CFU/mL (pH 3.65) for PNAPMB and MSNAPMB, respectively. The total titratable acidity significantly (p < 0.05) increased from 0.14 to 0.22% and from 0.17 to 0.38% in PNAPMB and MSNAPMB, respectively. The protein, total fat, moisture total sugar, and carbohydrates differed significantly (p < 0.05) among the samples. PNAPMB was preferred by a consumer panel followed by MSNAPMB and TNAPMB. Volatile compounds with beneficial anti-inflammatory and anti-pathogenic properties were identified in the beverages. Innovative fermentation of pearl millet extract using purified bioburden cultures was possible and the added Moringa oleifera leaf powder improved the nutritional quality of the resulting beverage.
T-S Fuzzy Model-Based Fault Detection for Continuous Stirring Tank Reactor
Authors: Wang Yanqin , Ren Weijian , Liu Zhuoqun , Li Jing , Zhang Duo
Published: December 2021

Continuous stirring tank reactors are widely used in the chemical production process, which is always accompanied by nonlinearity, time delay, and uncertainty. Considering the characteristic of the actual reaction of the continuous stirring tank reactors, the fault detection problem is studied in terms of the T-S fuzzy model. Through a fault detection filter performance analysis, the sufficient condition for the filtering error dynamics is obtained, which meets the exponential stability in the mean square sense and the given performance requirements. The design of the fault detection filter is transformed into one that settles the convex optimization issue of linear matrix inequality. Numerical analysis shows the effectiveness of this scheme.
Approaching Sustainability Transition in Supply Chains as a Wicked Problem: Systematic Literature Review in Light of the Evolved Double Diamond Design Process Model
Authors: Pyykkö Harri , Suoheimo Mari , Walter Stefan
Published: December 2021

Transition from the status quo to more sustainable supply chain management (SSCM) practices is a highly complex and non-linear process with multiple drivers, but also obstacles, on the way. The impending strict regulatory framework, particularly in terms of the environmental dimensions of sustainability development (SD), is single-handedly opening the door to rapid and potentially disruptive change. The research literature on SSCM has increased exponentially over the last decade to meet the mounting demand for information on how to tackle often conflicting sustainability-related requirements while satisfying all internal and external stakeholders. Due to the continuously evolving and wicked nature of SSCM, a limited number of scholars have approached the issue with design thinking problem solving methodologies (DTPSMs). The results of a systematic literature review (SLR) were mirrored with the Evolved Double Diamond (EDD) design process model to formulate a design thinking overview and trace potential research gaps of selected frameworks and models regarding the sustainability transition (ST) of supply chains (SCs). The research results demonstrate that modelling the ST in SC as a wicked problem can contribute to the creation of more structured and novel SSCM models and frameworks, which take into deeper consideration the evolving nature of the issue and improve facilitation practices of stakeholder engagement.
The Kinetics Investigation of CO2 Absorption into TEA and DEEA Amine Solutions Containing Carbonic Anhydrase
Authors: Liu Bin , Cui Zhe , Tian Wende
Published: December 2021

Tertiary amines have been used as alternative absorbents for traditional primary and secondary amines in the process of carbon capture. However, the carbon dioxide (CO2) absorption rates in these kinds of amine are relatively slow, which implies greater investment and construction costs and limits the large-scale application of carbon capture. Carbonic anhydrase (CA) is considered to be an ideal homogeneous catalyst for accelerating the rate of CO2 into aqueous amine solution. In this work, CO2 absorption combining CA with two single aqueous tertiary amines, namely triethanolamine (TEA) and 2-(diethylamino)ethanol (DEEA), was studied by use of the stopped-flow apparatus over temperature ranging from 293 to 313 K. The concentrations of selected aqueous amine solution and CA used in the experiment were ranging among 0.1–0.5 kmol/m3 and 0–50 g/m3 , respectively. Compared to the solution without the addition of CA, the pseudo first-order reaction rate in the presence of CA (k0,withCA) is significantly increased. The values of k0,withCA have been calculated by a new kinetics model. The results of experimental and calculated k0,amine and k0,withCA in CO2-amine-H2O solutions were also investigated,respectively.
Optimal Design and Operation of Multi-Period Water Supply Network with Multiple Water Sources
Authors: Zhou Wenjin , Iqbal Kashif , Lv Xiaoming , Deng Chun
Published: December 2021

A water supply network is an essential part of industrial and urban water systems. The water intake in a conventional water supply network varies periodically over time, depending on the amount of available water resources and the demand at water sinks or water-using units. This paper establishes a super-structural mathematical model for the optimal design and operation of a multi-period water supply network with multiple water sources. It considers the flow rate fluctuation of raw water availability and the demand of water sinks during different periods. The influence of multi-period demand variation on technology and the capacity selection of desalination water stations is examined, which affects the overall cost of the water supply network. The operating cost penalty factor is introduced, which quantitatively clarifies how the network operating status influences the operating costs. The comparison results of three scenarios considering with and without multi-period variation of water demand verify the validity of the proposed model, i.e., for a municipal water price of 4 CNY·t−1 and penalty factor of 0.3, one reverse osmosis desalination unit of capacity 800 t·h−1 is selected. However, in the multi-period case, two reverse osmosis desalination units with capacities of 500 t·h−1 and 300 t·h−1 are selected. In both cases, the operating costs are different because of the different operating status of the network. The work can guide the design and operation of industrial and urban water supply networks.
Steady State Analysis of Impulse Customers and Cancellation Policy in Queueing-Inventory System
Authors: Vinitha V. , Anbazhagan N. , Amutha S. , Jeganathan K. , Joshi Gyanendra Prasad , Cho Woong , Seo Suseok
Published: December 2021

This article discusses the queueing-inventory model with a cancellation policy and two classes of customers. The two classes of customers are named ordinary and impulse customers. A customer who does not plan to buy the product when entering the system is called an impulse customer. Suppose the customer enters into the system to buy the product with a plan is called ordinary customer. The system consists of a pool of finite waiting areas of size N and maximum S items in the inventory. The ordinary customer can move to the pooled place if they find that the inventory is empty under the Bernoulli schedule. In such a situation, impulse customers are not allowed to enter into the pooled place. Additionally, the pooled customers buy the product whenever they find positive inventory. If the inventory level falls to s, the replenishment of Q items is to be replaced immediately under the (s, Q) ordering principle. Both arrival streams occur according to the independent Markovian arrival process (MAP), and lead time follows an exponential distribution. In addition, the system allows the cancellation of the purchased item only when there exist fewer than S items in the inventory. Here, the time between two successive cancellations of the purchased item is assumed to be exponentially distributed. The Gaver algorithm is used to obtain the stationary probability vector of the system in the steady-state. Further, the necessary numerical interpretations are investigated to enhance the proposed model.
Dynamic Model for Biomass and Proteins Production by Three Bacillus Thuringiensis ssp Kurstaki Strains
Authors: Monroy Tatiana Segura , Abdelmalek Nouha , Rouis Souad , Kallassy Mireille , Saad Jihane , Abboud Joanna , Cescut Julien , Bensaid Nadia , Fillaudeau Luc , Aceves-Lara César Arturo
Published: December 2021

Bacillus thuringiensis is a microorganism used for the production of biopesticides worldwide. In the present paper, different kinetic models were analyzed to study and compare three different strains of Bt ssp kurstaki (LIP, BLB1, and HD1). Bioperformances (vegetative cell, spore, substrate, and protein) and successive culture phases (oxidative growth, limitation and sporulation, and protein release) were depicted with an overarching aim to estimate total protein productivity, yield, and titer. In the end, two models were calibrated using experimental dataset (11 batches culture in 3 L bioreactor with semisynthetic medium), subsequently validated, and statistically compared. Both models satisfactorily followed the dynamics of the experimental data. Finally, a dynamic model was selected following the Akaike information criterion (AIC).
Measurement of Heat Transfer and Flow Resistance for a Packed Bed of Horticultural Products with the Implementation of a Single Blow Technique
Authors: Łapiński Adam , Śmierciew Kamil , Zou Huiming , Butrymowicz Dariusz
Published: December 2021

This paper provides the practical implementation of the single blow technique as an effective approach of average convective heat transfer coefficient measurement for a packed bed of horticultural products. The measurement approach was positively validated for the case of a packed bed of balls. The presented results cover heat transfer coefficient results for carrots stored in packed beds for two various arrangements (regular and irregular) and bed of apples under conditions of various turbulent intensity at the inlet to the bed. The turbulent intensity (defined as the ratio of the root mean square of the turbulent fluctuation of the air velocity to the mean air velocity) varied from 0.02 to 0.14. The applied velocity ranges for the tests refers to the conventional storage conditions. The heat transfer correlations were proposed based on the obtained results for each arrangement. It was demonstrated that due to flow laminarization inside the bed, the turbulence intensity has no significant effect on heat transfer inside the bed. Heat transfer enhancement of up to 25% was demonstrated for the case of the irregular carrot arrangement in the tested bed. The flow resistance correlations were additionally proposed for the tested beds. It was demonstrated that the product arrangement does not produce an important effect on the pressure drop.
Integration of Solar Chimney Power Plant with Photovoltaic for Co-Cooling, Power Production, and Water Desalination
Authors: Alkasrawi Malek , Abdelsalam Emad , Alnawafah Hamza , Almomani Fares , Tawalbeh Muhammad , Mousa Aya
Published: December 2021

This work explores the technical possibilities of increasing the efficiency of a standard solar chimney power plant (SCPP) by integrating it with photovoltaic (PV) panels. The integration is possible by using the collector circumference to install the PV collectors, which provide a heat sink, allow for the better harvesting of the solar radiation, and increase energy production. The new design led to an increase in the annual electricity production from 380 to 494 MWh and water production from 278 to 326 k tons/year compared with the standard SCPP, marking an increase of 30% and 17%, respectively. The results also show that the integration reduced the greenhouse gas emissions (GHG), the localized cost of energy, and the capital cost of investment by 30%, 36%, and 20%, respectively. The proposed design supports the sustainable replacement of the existing desalination plants with zero operational costs and an excellent reduction in greenhouse gas emissions.
Novel Module-Based Design Algorithm for Intensified Membrane Reactor Systems
Authors: Bishop Brent A. , Lima Fernando V.
Published: December 2021

The growing interest in intensified process units that improve efficiency by combining several phenomena into one unit, has led to a loss in degrees of freedom when addressing the control scheme of these units. Previous work demonstrated that a novel module-based design approach to membrane reactors could improve the operability index of membrane reactor systems. This approach sought to decouple the phenomena to regain some degrees of freedom for the control system. However, the computational time to determine such an optimal module design made this class of design problems intractable to solve in a reasonable amount of time. This work proposes a set of design heuristics for a new module-based design approach for membrane reactors. These heuristics are used in combination with a genetic algorithm formulation to produce a novel, two-staged algorithm for the design and control of membrane reactor systems. This algorithm is developed in Python and uses rigorous membrane reactor models built in AVEVA Process Simulation. The proposed algorithm solves the original non-polynomial (NP) complexity problem in polynomial time (P), while still being able to find the optimal designs discovered in previous work through exhaustive methods.
Publisher Transparency among Communications and Library and Information Science Journals: Analysis and Recommendations
Authors: López-Borrull Alexandre , Vállez Mari , Ollé Candela , Pérez-Montoro Mario
Published: December 2021

The principal goal of the research study is to analyze the transparency of a selection of academic journals based on an analysis model with 20 indicators grouped into 6 parameters. Given the evident interest in and commitment to transparency among quality academic journals and researchers’ difficulties in choosing journals that meet a set of criteria, we present indicators that may help researchers choose journals while also helping journals to consider what information from the editorial process to publish, or not, on their websites to attract authors in the highly competitive environment of today’s scholarly communication. To test the validity of the indicators, we analyze a small sample: the Spanish Communications and Library and Information Science journals listed in the Scimago Journal Rank. The results confirm that our analysis model is valid and can be extrapolated to other disciplines and journals.
Measurement of Neutron Dose Equivalent within and Outside of a LINAC Treatment Vault Using a Neutron Survey Meter
Authors: Tai Duong Thanh , Loan Truong Thi Hong , Sulieman Abdelmoneim , Tamam Nissren , Omer Hiba , Bradley David A.
Published: December 2021

This work concerns neutron doses associated with the use of a Siemens Primus M5497 electron accelerator, which is operated in the photon mode at 15 MV. The conditions offer a situation within which a fraction of the bremsstrahlung emission energies exceed the photoneutron threshold. For different field sizes, an investigation has been made of neutron dose equivalent values at various measurement locations, including: (i) At the treatment table, at a source-surface distance of 100 cm; (ii) at the level of the floor directly adjacent to the treatment table; and (iii) in the control room and patient waiting area. The evaluated neutron dose equivalent was found to range from 0.0001 to 8.6 mSv/h, notably with the greatest value at the level of the floor directly adjacent to the treatment couch (8.6 mSv/h) exceeding the greatest value on the treatment table (5.5 mSv/h). Low values ranging from unobservable to between 0.0001 to 0.0002 mSv/h neutron dose were recorded around the control room and patient waiting area. For measurements on the floor, the study showed the dose equivalent to be greatest with the jaws closed. These data, most particularly concerning neutron distribution within the treatment room, are of great importance in making steps towards improving patient safety via the provision of protective measures.
Metallic Nanoparticles: A Useful Prompt Gamma Emitter for Range Monitoring in Proton Therapy?
Authors: Penninckx Sébastien , Hespeels Félicien , Smeets Julien , Colaux Julien L. , Lucas Stéphane , Heuskin Anne-Catherine
Published: December 2021

In clinical practice, dose delivery in proton therapy treatment is affected by uncertainties related to the range of the beam in the patient, which requires medical physicists to introduce safety margins on the penetration depth of the beam. Although this ensures an irradiation of the entire clinical target volume with the prescribed dose, these safety margins also lead to the exposure of nearby healthy tissues and a subsequent risk of side effects. Therefore, non-invasive techniques that allow for margin reduction through online monitoring of prompt gammas emitted along the proton tracks in the patient are currently under development. This study provides the proof-of-concept of metal-based nanoparticles, injected into the tumor, as a prompt gamma enhancer, helping in the beam range verification. It identifies the limitations of this application, suggesting a low feasibility in a realistic clinical scenario but opens some avenues for improvement.
How Tibetan Nuns Become Khenmos: The History and Evolution of the Khenmo Degree for Tibetan Nuns
Authors: Padma’tsho (Baimacuo)
Published: December 2021

Tibetan Buddhist nuns are making history in numerous ways. They now meet in classrooms instead of tents, earn the title “Khenmo” after many years of dedicated study, and take exams that are standardized, frequent, and both written and oral. Additionally, the new educational system encourages Tibetan Jomos to take on more responsibility, increase their scholarship and practice, and obtain superior monastery/nunnery status. This article chronicles over two and a half decades of extensive fieldwork, covering the advances in monastic education and the rising standing of women in Larung Gar and contemporary China. These advances are in stark contrast to the limited opportunities for women in the past.
The Role of a Rapid Prevention of Ralstonia pickettii Growth during Dialysis in a Frail Patient
Authors: Colosimo Manuela , Citraro Maria Lucia , Donato Cinzia , Luciani Filippo , Gallelli Luca , Minchella Pasquale
Published: December 2021

Ralstonia pickettii is an opportunistic bacillus found in Pseudomonas species, with the ability to induce systemic infections. We report the case of a 69-year-old man, with a clinical history of myeloma, Type IIdiabetes, renal failure (grade IV), and colon cancer, that developed a severe bacterial infection, with acute asthenia and a fever, that appeared at the end of dialysis. Using theMALDI-TOF technology, the bacillus Ralstonia pickettii was identified, and an antimicrobial treatment was quickly started with a rapid microbiological remission.
Pretreatment of Lignocellulosic Biomass with 1-Ethyl-3-methylimidazolium Acetate for Its Eventual Valorization by Anaerobic Digestion
Authors: Marin-Batista Jose D. , Mohedano Angel F. , de la Rubia Angeles
Published: December 2021

This study assessed the breakdown of lignocellulosic biomass (LB) with the ionic liquid (IL) 1-ethyl-3-methylimidazolium acetate ([Emim][Ac]) as a pretreatment to increase the methane yield. The pretreatment was conducted for wheat straw (WS), barley straw (BS), and grape stem (GS) at 120 °C for 120 min, using several LB to [Emim][Ac] ratios (1:1, 1:3, and 1:5 w/w). Pretreatment significantly disrupted the lignocellulose matrix of each biomass into soluble sugars. GS showed the highest sugar yield, which was followed by WS, while BS was slightly hydrolyzed (175.3 ± 2.3, 158.2 ± 5.2, and 51.1 ± 3.1 mg glucose g–1 biomass, respectively). Likewise, the pretreatment significantly reduced the cellulose crystallinity index (CrI) of the resulting solid fractions of GS and WS by 15% and 9%, respectively, but slightly affected the CrI of BS (5%). Thus, BMP tests were only carried out for raw and hydrothermally and [Emim][Ac] (1:5) pretreated GS and WS. The untreated GS and WS showed similar methane yields to those achieved for the solid fraction obtained after pretreatment with an LB to [Emim][Ac] ratio of 1:5 (219 ± 10 and 368 ± 1 mL CH4 g–1 VS, respectively). The methane production of the solid plus liquid fraction obtained after IL pretreatment increased by 1.61- and 1.34-fold compared to the raw GS and WS, respectively.
Regional Government Revenue Forecasting: Risk Factors of Investment Financing
Authors: Batóg Barbara , Batóg Jacek
Published: December 2021

Accurate revenue prediction is a key factor for the reliable determination of the investment part of entire regional and local budgets, particularly during economic downturns and fiscal uncertainty. An unexpected decline in revenue requires the reduction in capital expenditures and forces the regional government to find additional sources to close the budget gaps. Current studies indicate that budget forecasts often underpredict revenue and use the available information inefficiently. In this article, the authors examine chosen methods of forecasting regional government revenue. In addition to classical forecasting models based on time series and causal models, an original structural forecasting procedure was proposed, which is effective especially in case of data delay. The reliability of applied methods was assessed using data from the Polish area of Zachodniopomorskie over the period 2000–2018. The found evidence supported results that were obtained by many other researchers, which indicated that less comprehensive methods of forecasting can provide reasonably accurate estimates.
A Novel, Oriented to Graphs Model of Robot Arm Dynamics
Authors: Boiadjiev George , Krastev Evgeniy , Chavdarov Ivan , Miteva Lyubomira
Published: December 2021

Robotics is an interdisciplinary field and there exist several well-known approaches to represent the dynamics model of a robot arm. The robot arm is an open kinematic chain of links connected through rotational and translational joints. In the general case, it is very difficult to obtain explicit expressions for the forces and the torques in the equations where the driving torques of the actuators produce desired motion of the gripper. The robot arm control depends significantly on the accuracy of the dynamic model. In the existing literature, the complexity of the dynamic model is reduced by linearization techniques or techniques like machine learning for the identification of unmodelled dynamics. This paper proposes a novel approach for deriving the equations of motion and the actuator torques of a robot arm with an arbitrary number of joints. The proposed approach for obtaining the dynamic model in closed form employs graph theory and the orthogonality principle, a powerful concept that serves as a generalization for the law of conservation of energy. The application of this approach is demonstrated using a 3D-printed planar robot arm with three degrees of freedom. Computer experiments for this robot are executed to validate the dynamic characteristics of the mathematical model of motion obtained by the application of the proposed approach. The results from the experiments are visualized and discussed in detail.
Factors Driving Changes in Vegetation in Mt. Qomolangma (Everest): Implications for the Management of Protected Areas
Authors: Zhang Binghua , Zhang Yili , Wang Zhaofeng , Ding Mingjun , Liu Linshan , Li Lanhui , Li Shicheng , Liu Qionghuan , Paudel Basanta , Zhang Huamin
Published: December 2021

The Mt. Qomolangma (Everest) National Nature Preserve (QNNP) is among the highest natural reserves in the world. Monitoring the spatiotemporal changes in the vegetation in this complex vertical ecosystem can provide references for decision makers to formulate and adapt strategies. Vegetation growth in the reserve and the factors driving it remains unclear, especially in the last decade. This study uses the normalized difference vegetation index (NDVI) in a linear regression model and the Breaks for Additive Seasonal and Trend (BFAST) algorithm to detect the spatiotemporal patterns of the variations in vegetation in the reserve since 2000. To identify the factors driving the variations in the NDVI, the partial correlation coefficient and multiple linear regression were used to quantify the impact of climatic factors, and the effects of time lag and time accumulation were also considered. We then calculated the NDVI variations in different zones of the reserve to examine the impact of conservation on the vegetation. The results show that in the past 19 years, the NDVI in the QNNP has exhibited a greening trend (slope = 0.0008/yr, p < 0.05), where the points reflecting the transition from browning to greening (17.61%) had a much higher ratio than those reflecting the transition from greening to browning (1.72%). Shift points were detected in 2010, following which the NDVI tendencies of all the vegetation types and the entire preserve increased. Considering the effects of time lag and time accumulation, climatic factors can explain 44.04% of the variation in vegetation. No climatic variable recorded a change around 2010. Considering the human impact, we found that vegetation in the core zone and the buffer zone had generally grown better than the vegetation in the test zone in terms of the tendency of growth, the rate of change, and the proportions of different types of variations and shifts. A policy-induced reduction in livestock after 2010 might explain the changes in vegetation in the QNNP.
Comparison of Field and SAR-Derived Descriptors in the Retrieval of Soil Moisture from Oil Palm Crops Using PALSAR-2
Authors: Shashikant Veena , Mohamed Shariff Abdul Rashid , Wayayok Aimrun , Kamal Md Rowshon , Lee Yang Ping , Takeuchi Wataru
Published: December 2021

Synthetic-aperture radar’s (SAR’s) capacity to resolve the cloud cover concerns encountered while gathering optical data has tremendous potential for soil moisture data retrieval using SAR data. It is possible to use SAR data to recover soil moisture because the backscatter coefficient is sensitive to both soil and vegetation by penetrating through the vegetation layer. This study investigated the feasibility of employing a SAR-derived radar vegetation index (RVI), the ratios of the backscatter coefficients using polarizations of HH/HV (RHH/HV) and HV/HH (RHH/HV) to an oil palm crops as vegetation indicators in the water cloud model (WCM) using phased-array L-band SAR-2 (PALSAR-2). These data were compared to the manual leaf area index (LAI) and a physical soil sampling method for computing soil moisture. The field data included the LAI input parameters and, more importantly, physical soil samples from which to calculate the soil moisture. The fieldwork was carried out in Chuping District, Perlis State, Malaysia. Corresponding PALSAR-2 data were collected on three observation dates in 2019: 17 January, 16 April, and 9 July. The results showed that the WCM modeled using the LAI under HV polarization demonstrated promising accuracy, with the root mean square error recorded as 0.033 m3/m3. This was comparable to the RVI and RHH/HV under HV polarization, which had accuracies of 0.031 and 0.049 m3/m3, respectively. The findings of this study suggest that SAR-based indicators, RHH/HV and RVI using PALSAR-2, can be used to reduce field-related input in the retrieval of soil moisture data using the WCM for oil palm crop.
Meteorological Drought Analysis and Return Periods over North and West Africa and Linkage with El Niño–Southern Oscillation (ENSO)
Authors: Henchiri Malak , Igbawua Tertsea , Javed Tehseen , Bai Yun , Zhang Sha , Essifi Bouajila , Ujoh Fanan , Zhang Jiahua
Published: December 2021

Droughts are one of the world’s most destructive natural disasters. In large regions of Africa, droughts can have strong environmental and socioeconomic impacts. Understanding the mechanism that drives drought and predicting its variability is important for enhancing early warning and disaster risk management. Taking North and West Africa as the study area, this study adopted multi-source data and various statistical analysis methods, such as the joint probability density function (JPDF), to study the meteorological drought and return years across a long term (1982–2018). The standardized precipitation index (SPI) was used to evaluate the large-scale spatiotemporal drought characteristics at 1–12-month timescales. The intensity, severity, and duration of drought in the study area were evaluated using SPI–12. At the same time, the JPDF was used to determine the return year and identify the intensity, duration, and severity of drought. The Mann-Kendall method was used to test the trend of SPI and annual precipitation at 1–12-month timescales. The pattern of drought occurrence and its correlation with climate factors were analyzed. The results showed that the drought magnitude (DM) of the study area was the highest in 2008–2010, 2000–2003, and 1984–1987, with the values of 5.361, 2.792, and 2.187, respectively, and the drought lasting for three years in each of the three periods. At the same time, the lowest DM was found in 1997–1998, 1993–1994, and 1991–1992, with DM values of 0.113, 0.658, and 0.727, respectively, with a duration of one year each time. It was confirmed that the probability of return to drought was higher when the duration of drought was shorter, with short droughts occurring more regularly, but not all severe droughts hit after longer time intervals. Beyond this, we discovered a direct connection between drought and the North Atlantic Oscillation Index (NAOI) over Morocco, Algeria, and the sub-Saharan countries, and some slight indications that drought is linked with the Southern Oscillation Index (SOI) over Guinea, Ghana, Sierra Leone, Mali, Cote d’Ivoire, Burkina Faso, Niger, and Nigeria.
Detecting Rock Glacier Displacement in the Central Himalayas Using Multi-Temporal InSAR
Authors: Zhang Xuefei , Feng Min , Zhang Hong , Wang Chao , Tang Yixian , Xu Jinhao , Yan Dezhao , Wang Chunling
Published: December 2021

Rock glaciers represent typical periglacial landscapes and are distributed widely in alpine mountain environments. Rock glacier activity represents a critical indicator of water reserves state, permafrost distribution, and landslide disaster susceptibility. The dynamics of rock glacier activity in alpine periglacial environments are poorly quantified, especially in the central Himalayas. Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) has been shown to be a useful technique for rock glacier deformation detection. In this study, we developed a multi-baseline persistent scatterer (PS) and distributed scatterer (DS) combined MT-InSAR method to monitor the activity of rock glaciers in the central Himalayas. In periglacial landforms, the application of the PS interferometry (PSI) method is restricted by insufficient PS due to large temporal baseline intervals and temporal decorrelation, which hinder comprehensive measurements of rock glaciers. Thus, we first evaluated the rock glacier interferometric coherence of all possible interferometric combinations and determined a multi-baseline network based on rock glacier coherence; then, we constructed a Delaunay triangulation network (DTN) by exploiting both PS and DS points. To improve the robustness of deformation parameters estimation in the DTN, we combined the Nelder–Mead algorithm with the M-estimator method to estimate the deformation rate variation at the arcs of the DTN and introduced a ridge-estimator-based weighted least square (WLR) method for the inversion of the deformation rate from the deformation rate variation. We applied our method to Sentinel-1A ascending and descending geometry data (May 2018 to January 2019) and obtained measurements of rock glacier deformation for 4327 rock glaciers over the central Himalayas, at least more than 15% detecting with single geometry data. The line-of-sight (LOS) deformation of rock glaciers in the central Himalayas ranged from −150 mm to 150 mm. We classified the active deformation area (ADA) of all individual rock glaciers with the threshold determined by the standard deviation of the deformation map. The results show that 49% of the detected rock glaciers (monitoring rate greater than 30%) are highly active, with an ADA ratio greater than 10%. After projecting the LOS deformation to the steep slope direction and classifying the rock glacier activity following the IPA Action Group guideline, 12% of the identified rock glaciers were classified as active and 86% were classified as transitional. This research is the first multi-baseline, PS, and DS network-based MT-InSAR method applied to detecting large-scale rock glaciers activity.