bluuebunny/crossref_metadata_2025 huggingface dataset:
Pasteurization of Beer by Non-Thermal Technologies
Authors: Milani Elham A. , Silva Filipa V.M.
Published: March 2022

The pasteurization of beer occurs at the end of the industrial production, after fermentation. Generally, a mild thermal process (60°C) is employed aiming to inactivate the fermenting yeast and potential spoilage microorganisms, thus extending the beer shelf-life at room temperature. The heat treatment negatively affects the original beer freshness and flavor. In this study, beer pasteurization using emerging non-thermal technologies, namely, high-pressure processing (HPP), pulsed electric fields (PEF), and ultrasound (US), was reviewed, including the effect on microbial inactivation and beer quality. The combination of non-thermal methods with mild heat for more efficient pasteurization of beer was also reviewed. All technologies caused microbial inactivation in beer. However, room temperature HPP treatment was the most efficient method, delivering the minimum 15 PU (pasteurization units) to beer after seconds (e.g., 300 MPa for 27 s), as opposed to thermal and TS treatments which required several minutes, while causing a negative impact on beer sensory. As expected, PEF + heat caused a higher microbial inactivation than PEF alone, and yeast ascospores were more resistant than vegetative yeast cells. Non-thermal PEF (35–45 kV/cm) caused 3–5.8 log reductions in vegetative bacteria. Studies on thermal assisted PEF and ultrasound combined with low heat (50–55°C) showed processing times in the magnitude of microseconds for PEF pasteurization and 0.5–2 min (depending on the temperature) for TS pasteurization. With respect to impact of these technologies on beer quality, HPP, thermosonication (TS), high pressure homogenization (HPH), and dense phase CO2 (DPCD) treatments revealed less effect on beer sensory properties, better retaining the freshness of original beer, compared to thermally processed beers.
EEG Pattern Classification of Picking and Coordination Using Anonymous Random Walks
Authors: Zuckerman Inon , Mizrahi Dor , Laufer Ilan
Published: March 2022

Tacit coordination games are games where players are trying to select the same solution without any communication between them. Various theories have attempted to predict behavior in tacit coordination games. Until now, research combining tacit coordination games with electrophysiological measures was mainly based on spectral analysis. In contrast, EEG coherence enables the examination of functional and morphological connections between brain regions. Hence, we aimed to differentiate between different cognitive conditions using coherence patterns. Specifically, we have designed a method that predicts the class label of coherence graph patterns extracted out of multi-channel EEG epochs taken from three conditions: a no-task condition and two cognitive tasks, picking and coordination. The classification process was based on a coherence graph extracted out of the EEG record. To assign each graph into its appropriate label, we have constructed a hierarchical classifier. First, we have distinguished between the resting-state condition and the other two cognitive tasks by using a bag of node degrees. Next, to distinguish between the two cognitive tasks, we have implemented an anonymous random walk. Our classification model achieved a total accuracy value of 96.55%.
Production of Pelleted Biochar and Its Application as an Amendment in Paddy Condition for Reducing Methane Fluxes
Authors: Yun Jin-Ju , Park Jae-Hyuk , Acharya Bharat Sharma , Park Jong-Hwan , Cho Ju-Sik , Kang Se-Won
Published: March 2022

The global focus continues with respect to increasing agricultural productivity, such as in paddy soils using inorganic fertilizers. Such practices could adversely affect the agricultural environment by deteriorating soils and increasing greenhouse gas emissions. The aim of this study was to assess the effect of biochar pellet blended with condensed molasses soluble (CMS) on rice productivity, soil quality, and methane (CH4) emissions in a paddy condition for healthy agricultural ecosystem. This study used a commercial scale pyrolysis system to produce biochar at 600 °C from bamboo. The experiment consisted of three different treatments: control, inorganic fertilizer (IF, N-P-K = 90-45-57 kg ha−1), and biochar pellet (BC_PT, 1000 kg ha−1). Compared to other treatments, the biochar pellet decreased annual CH4 flux by 15.8–18.8%. The rice grain yield under inorganic fertilizer as conventional rice management was slightly more than applied biochar pellets, despite lower soil chemical properties. However, for long-term paddy management, including environmental protection and rice production, biochar pellets are better suited for maintaining a healthy agricultural ecosystem than conventional practices. Indeed, the application of biochar pellets appears to potentially reduce CH4 emissions and maintain stable rice productivity through the slow release of nutrients.
Ameliorating Seed Germination and Seedling Growth of Nano-Primed Wheat and Flax Seeds Using Seven Biogenic Metal-Based Nanoparticles
Authors: Bayat Maryam , Zargar Meisam , Murtazova Kheda Magomed-Salihovna , Nakhaev Magomed Ramzanovich , Shkurkin Sergey I.
Published: March 2022

Recently, large-scale agriculture has led to increasing crop production. To increase crop productivity in large-scale cropping systems, attempts have been made to make nano-fertilizers and deliver them to the crops by extension of nanotechnology. Hence, nano-fertilizers might be defined as nanoparticles that may directly assist in supplying essential nutrients for crop productivity. Seed germination is the first and the most susceptible stage in the plant’s growing phases, so could be considered as an index to evaluate the effect of newly developed materials such as nanoparticles (NPs), providing useful information for researchers. In our experiments, germination tests have been carried out in Petri dishes containing wet filter paper and nano-primed seeds. We had biosynthesized seven nanoparticles in our previous studies including calcinated and non-calcinated zinc oxide, zinc, magnesium oxide, silver, copper, and iron nanoparticles. The effect of these biogenic nanoparticles and their counterpart metallic salts including zinc acetate, magnesium sulfate, silver nitrate, copper sulfate, and iron (III) chloride was studied on two popularly grown plants, wheat and flax, in laboratory conditions to obtain preliminary information for future field experiments. Germination percentage, shoot length, root length, seedlings length, root–shoot ratio, seedling vigor index (SVI), shoot length stress tolerance index (SLSI), and root length stress tolerance index (RLSI) were calculated on the second and seventh days of the experiment. According to the results, the response of the plants to metal containing nanoparticles and metal salts mainly depend on the type of the metal, plant species, concentration of the NP suspension or salt solution, condition of the exposure, and the stage of growth.
Melatonin-Induced Resilience Strategies against the Damaging Impacts of Drought Stress in Rice
Authors: Li Yufei , Zhang Luqian , Yu Yufeng , Zeng Hongli , Deng Liyuan , Zhu Lifei , Chen Guanghui , Wang Yue
Published: March 2022

Drought is a severe abiotic stress that imposes a serious threat to rice productivity. Although previous studies have found that melatonin can promote seed germination, the physiological regulation mechanism of drought tolerance in rice seed germination mediated by exogenous melatonin is still unclear. In order to overcome these challenges, polyethylene glycol 6000 (PEG6000) at concentrations of 20% and 35% was used to simulate osmotic stress. Rice seeds were treated with different concentrations of melatonin (i.e., 0, 20, 100, and 500 μM) to study the effects on germination characteristics, growth and development, superoxide dismutase (SOD) activity, peroxidase (POD) activity, catalase (CAT) activity, malondialdehyde (MDA) content, and soluble protein content. The results showed that the seed soaking treatment using melatonin at a concentration of 100 μM under drought stress effectively promoted the germination rate and improved the biomass of rice seed shoots and roots. Meanwhile, this treatment reduced MDA content to alleviate the oxidative damage of rice seeds caused by drought stress. The two-way ANOVA showed that the effect of single melatonin soaking treatment on rice seed germination was more significant than that of single drought stress and the interaction of drought stress and melatonin (p < 0.05). Using the membership function method, it was shown that the critical gradient of rice seeds under drought stress was 35%, and the critical treatment of interactive treatment was 35% + 100 μM. Through grey correlation analysis, it was found that germination rate (7 d) had the highest grey correlation with melatonin seed soaking treatment to evaluate the mitigation effect of melatonin on drought stress. This study provides a theoretical basis for light and simple cultivation technology for the dry direct seeding of rice.
Evaluating the Behavioural Responses of Healthy Newborn Calves to a Thoracic Squeeze
Authors: Holdsworth Sophia E. , Kells Nikki J. , Vallée Emilie , Ward Neil , Mellor David J. , Beausoleil Ngaio J.
Published: March 2022

A thoracic squeeze has been observed to cause low-vigour neonates of various farmed mammal species, including calves, to enter a state of reduced responsiveness. The removal of the squeeze causes rapid recovery and the expression of normal, healthy behaviours. However, the responses of healthy calves to a thoracic squeeze have not yet been characterized. The responses of 16 healthy newborn calves to a thoracic squeeze are described, along with the effect of the squeeze’s application method on the response. Calves aged between 12 and 36 h were subjected to the squeeze using a rope (n = 8) or an inflation cuff (n = 8). In total, 13 of the 16 calves were induced into a state of reduced responsiveness, though neural reflexes persisted in nearly all of them. The squeeze was discontinued for nearly half of those induced before the end of the 10-min period, either due to spontaneous arousal or physiological instability. Both methods of application were equally effective at inducing reduced responsiveness, though responses to the cuff appeared to be more rapid than those to the rope. These findings support previous research on piglets and foals, and suggest that the behavioural responses to a thoracic squeeze are generalised across neonates of precocial farmed mammals; the findings provide a foundation for further research exploring the mechanisms underlying the response and the benefits that its application may bring for the performance of husbandry procedures.
A Narrative Review on the Approach to Antimicrobial Use in Ventilated Patients with Multidrug Resistant Organisms in Respiratory Samples—To Treat or Not to Treat? That Is the Question
Authors: Ling Lowell , Wong Wai-Tat , Lipman Jeffrey , Joynt Gavin Matthew
Published: March 2022

Multidrug resistant organisms (MDRO) are commonly isolated in respiratory specimens taken from mechanically ventilated patients. The purpose of this narrative review is to discuss the approach to antimicrobial prescription in ventilated patients who have grown a new MDRO isolate in their respiratory specimen. A MEDLINE and PubMed literature search using keywords “multidrug resistant organisms”, “ventilator-associated pneumonia” and “decision making”, “treatment” or “strategy” was used to identify 329 references as background for this review. Lack of universally accepted diagnostic criteria for ventilator-associated pneumonia, or ventilator-associated tracheobronchitis complicates treatment decisions. Consideration of the clinical context including signs of respiratory infection or deterioration in respiratory or other organ function is essential. The higher the quality of respiratory specimens or the presence of bacteremia would suggest the MDRO is a true pathogen, rather than colonization, and warrants antimicrobial therapy. A patient with higher severity of illness has lower safety margins and may require initiation of antimicrobial therapy until an alternative diagnosis is established. A structured approach to the decision to treat with antimicrobial therapy is proposed.
Optimizing U-Shaped Production Line Balancing Problem with Exchangeable Task Locations and Walking Times
Authors: Kuo Yiyo , Yang Taho , Huang Tzu-Lin
Published: March 2022

This present study proposes to solve the U-shaped production line balancing problem with two constraints. First, following the precedence relationships between any pair of tasks, the locations of tasks are exchangeable. Second, all tasks are designed to be performed in fixed locations. When two or more tasks are assigned to the same operator, the walking time between the locations has to be considered when estimating the cycle time. The proposed problem is first formulated using an integer programming formulation, which is then solved by commercial software, LINGO, to minimize the cycle time and performance of the U-shaped production line. The empirical results show that U-shaped production lines outperform traditional straight production lines. In addition, the U-shaped production line balancing problem with consideration of walking time provides an opportunity to further reduce cycle time.
Bone: An Outstanding Composite Material
Authors: Rosa Natacha , Moura Marcelo F. S. F. , Olhero Susana , Simoes Ricardo , Magalhães Fernão D. , Marques António Torres , Ferreira João P. S. , Reis Ana Rita , Carvalho Mariana , Parente Marco
Published: March 2022

Bone is an outstanding, well-designed composite. It is constituted by a multi-level structure wherein its properties and behavior are dependent on its composition and structural organization at different length scales. The combination of unique mechanical properties with adaptive and self-healing abilities makes bone an innovative model for the future design of synthetic biomimetic composites with improved performance in bone repair and regeneration. However, the relation between structure and properties in bone is very complex. In this review article, we intend to describe the hierarchical organization of bone on progressively greater scales and present the basic concepts that are fundamental to understanding the arrangement-based mechanical properties at each length scale and their influence on bone’s overall structural behavior. The need for a better understanding of bone’s intricate composite structure is also highlighted.
Predictive Fraud Analysis Applying the Fraud Triangle Theory through Data Mining Techniques
Authors: Sánchez-Aguayo Marco , Urquiza-Aguiar Luis , Estrada-Jiménez José
Published: March 2022

Fraud is increasingly common, and so are the losses caused by this phenomenon. There is, thus, an essential economic incentive to study this problem, particularly fraud prevention. One barrier complicating the research in this direction is the lack of public data sets that embed fraudulent activities. In addition, although efforts have been made to detect fraud using machine learning, such actions have not considered the component of human behavior when detecting fraud. We propose a mechanism to detect potential fraud by analyzing human behavior within a data set in this work. This approach combines a predefined topic model and a supervised classifier to generate an alert from the possible fraud-related text. Potential fraud would be detected based on a model built from such a classifier. As a result of this work, a synthetic fraud-related data set is made. Four topics associated with the vertices of the fraud triangle theory are unveiled when assessing different topic modeling techniques. After benchmarking topic modeling techniques and supervised and deep learning classifiers, we find that LDA, random forest, and CNN have the best performance in this scenario. The results of our work suggest that our approach is feasible in practice since several such models obtain an average AUC higher than 0.8. Namely, the fraud triangle theory combined with topic modeling and linear classifiers could provide a promising framework for predictive fraud analysis.
Design and Analysis of Artificial Neural Network (ANN) Models for Achieving Self-Sustainability in Sanitation
Authors: Ganesapillai Mahesh , Sinha Aritro , Mehta Rishabh , Tiwari Aditya , Chellappa Vijayalakshmi , Drewnowski Jakub
Published: March 2022

The present study investigates the potential of using fecal ash as an adsorbent and demonstrates a self-sustaining, optimized approach for urea recovery from wastewater streams. Fecal ash was prepared by heating synthetic feces to 500 °C and then processing it as an adsorbent for urea adsorption from synthetic urine. Since this adsorption approach based on fecal ash is a promising alternative for wastewater treatment, it increases the process’ self- sustainability. Adsorption experiments with varying fecal ash loadings, initial urine concentrations, and adsorption temperatures were conducted, and the acquired data were applied to determine the adsorption kinetics. These three process parameters and their interactions served as the input vectors for the artificial neural network model, with the percentage urea adsorption onto fecal ash serving as the output. The Levenberg–Marquardt (TRAINLM) and Bayesian regularization (TRAINBR) techniques with mean square error (MSE) were trained and tested for predicting percentage adsorption. TRAINBR was demonstrated in our study to be an ideal match for improving urea adsorption, with an accuracy of R = 0.9982 and a convergence time of seven seconds. The ideal conditions for maximum urea adsorption were determined to be a high starting concentration of 13.5 g.L−1; a low temperature of 30 °C, and a loading of 1.0 g of adsorbent. For urea, the improved settings resulted in maximum adsorption of 92.8%.
Energy Centers in a Smart City as a Platform for the Application of Artificial Intelligence and the Internet of Things
Authors: Garlik Bohumir
Published: March 2022

A fundamental strategy of addressing the energy performance of buildings (EPB) and creating conditions for energy sustainability in applying renewable energy sources (RES) is the effective management of building technical equipment. The buildings in question are buildings within a cluster of buildings. The building cluster can be considered as a unit that is, in the sense of the system concept, a part of a subdivision of the city and subsequently of the whole urban agglomeration. We are talking about smart cities. The control system of a building and, subsequently, smart cities is a process management system using artificial intelligence (AI). In order to achieve the desired effects, such as “near-zero energy buildings”, as required by the European Energy Performance of Buildings Directive (EPBD 3), the application of AI needs to be shifted towards wireless network connection, i.e., “Internet of Things” (IoT) application. The aim is to create conditions for reducing energy consumption, improving environmental comfort in buildings and reducing CO2 emissions. This paper further analyzes the current state of IoT and the implementation thereof in the process management of sustainable energy at the smart city level as a basic element of a smart city system applied to building management.
Methodology for Designing an Electricity Demand System in the Context of IoT Household
Authors: Perez-Camacho Blanca Nydia , Rodriguez Gomez Gustavo , Gonzalez-Calleros Juan Manuel , Martinez-López Francisco J.
Published: March 2022

Many efforts have been made to create scenarios whereby interconnecting IoT can be used. The primary objective of these efforts has been to centralize its access as a single list and to monitor its use and trigger its different functionalities from apps. However, few efforts have addressed the problem of electricity consumption from those devices in the context of a residence. Existing datasets for machine predictive systems are focused on data analytics for global consumption but neglect the use of such solutions by the common citizen as a means of re-educating our citizens and optimizing electricity consumption. Without considering the environmental impact and the urgent need to address this growing global emergency, ordinary citizens require systems that help them be aware of what they consume and thus aspire to make a change. In this work, we propose a methodology that builds on the formal mathematical modeling and development of a simulator to substitute the need to collect real data from real world context of use, as well as an interactive system that integrates the whole process. By adding this module to the architecture our prior work, this work is ready for use in real-life scenarios where electrical consumption could be significantly reduced.
Predictors of Analgesic Consumption in Orthodontic Patients
Authors: Juloski Jovana , Vasovic Dina , Vucic Ljiljana , Pajevic Tina , Gligoric Nevena , Mirkovic Mladen , Glisic Branislav
Published: March 2022

During orthodontic treatment, pain is a subjective experience influenced by several factors. Orthodontic patients consume analgesics at different rates to alleviate this pain. Correlations between orthodontic pain and analgesic consumption were analyzed. Predictive factors to analgesics consumption were not statistically analyzed. This study was conducted to identify the predictive factors for analgesic consumption after initiation of orthodontic treatment with fixed appliances. Two hundred and eighty-six patients involved in this study kept a seven-day diary in which they recorded pain intensity (using a 0–10 numerical rating scale), analgesic consumption, localization of pain, pain triggers, and pain characteristics. Univariable analyses identified potential predictive factors: age, gender, pain intensity, pain localization, pain while chewing, pain at rest, night pain, headache, pulsating pain, sharp pain, dull pain, and tingling. Logistic regression was conducted to create a model that could predict analgesic consumption. Multivariate analyses demonstrated that analgesic consumption was increased by increased age, increased intensity of pain, and presence of a headache. Overall, the model explained 33% of analgesic requirement variability. Age, intensity of pain, and headache proved to be predictors of analgesic consumption. Knowledge of such factors may help clinicians identify orthodontic patients who will consume analgesics on their own.
Using Fluorescence Spectroscopy to Detect Rot in Fruit and Vegetable Crops
Authors: Matveyeva Tatiana A. , Sarimov Ruslan M. , Simakin Alexander V. , Astashev Maxim E. , Burmistrov Dmitriy E. , Lednev Vasily N. , Sdvizhenskii Pavel A. , Grishin Mikhail Ya. , Pershin Sergey M. , Chilingaryan Narek O. , Semenova Natalya A. , Dorokhov Alexey S. , Gudkov Sergey V.
Published: March 2022

The potential of the method of fluorescence spectroscopy for the detection of damage and diseases of fruits and vegetables was studied. For this purpose, the spectra of fluorescence of healthy and rotten apples and potatoes have been investigated. Excitation of samples was carried out using a continuous semiconductor laser with a wavelength of 405 nm and a pulsed solid-state laser with a wavelength of 527 nm. Peaks in the region of 600–700 nm in rotten samples were shifted towards shorter wavelengths for most samples in both modes of spectroscopy. The differences in the fluorescence spectra of a healthy and rotten apple surface have been revealed to be in the spectral range of 550–650 nm for 405 nm continuous excitation. When exposed to a laser in a pulsed mode (527 nm), the contribution of the 630 nm peak in the spectrum increases in rotten samples. The observed differences make it possible to use this method for separating samples of healthy and rotten fruits and vegetables. The article paid attention to the influence of many factors such as sample thickness, time after excitation, contamination by soil and dust, cultivar, and location of the probing on fluorescence spectra.
Adaptive, Observer-Based Synchronization of Different Chaotic Systems
Authors: Kabziński Jacek , Mosiołek Przemysław
Published: March 2022

In this study, the problem of master–slave synchronization of two different chaotic systems is considered and solved under a novel set of assumptions. The mathematical model of each of them contains unknown, constant parameters. Only a single output of the master system is available, and only a single input of the slave system is a control input. The proposed, novel approach is based on the active cooperation of the adaptive observer of the master system and adaptive controller of the slave. The tuning function technique is included in the observer–controller design to avoid overparameterization. Complexity explosion and unacceptable increases in adaptive parameters are prevented by proper adaptive techniques application. Due to the selected observer type, the derivation is restricted to the defined class of master systems—output-nonlinear parametric (ONP) systems. Linear transformation of several popular chaotic systems (e.g., Arneodo, Arneodo–Coullet, Genesio–Tesi, Lur’e) into the ONP form is discussed. The stability of the whole, closed-loop system is derived using Lyapunov techniques and examples of implementation (synchronization of Arneodo and 3D jerk systems) are provided.
Study on Effects of Energy Deposition and Thermal Shock Wave by Electron Beam Irradiation
Authors: Wang Dengwang , Ying Ruomeng , Chen Wei , Wang Sheng
Published: March 2022

The electron beam is an important way to effectively simulate the thermodynamic effects of an intense pulsed X-ray and the materials for electron beam irradiation are of great significance to study the effects of energy deposition and thermal shock waves. Based on the input conditions like the actual current, voltage, and energy spectrum of an electron beam device (REB), the analytic method and the Monte Carlo method were used to calculate the energy deposition of a multi-energy-spectrum electron beam in materials of hard aluminum and carbon phenolic, the differences of the two methods were analyzed, the energy deposition profiles of different incident angles and energies were obtained, and the energy deposition of electron beam irradiation of a multilayer target was calculated as well. Through the numerical simulation and experimental study of thermal shock waves of electron beam irradiation materials, the calculation error was less than 10% by comparing the stress changes of thermal shock waves with different energies. This is helpful for studying the protective structure of spacecraft.
Comparative Evaluation of NLP-Based Approaches for Linking CAPEC Attack Patterns from CVE Vulnerability Information
Authors: Kanakogi Kenta , Washizaki Hironori , Fukazawa Yoshiaki , Ogata Shinpei , Okubo Takao , Kato Takehisa , Kanuka Hideyuki , Hazeyama Atsuo , Yoshioka Nobukazu
Published: March 2022

Vulnerability and attack information must be collected to assess the severity of vulnerabilities and prioritize countermeasures against cyberattacks quickly and accurately. Common Vulnerabilities and Exposures is a dictionary that lists vulnerabilities and incidents, while Common Attack Pattern Enumeration and Classification is a dictionary of attack patterns. Direct identification of common attack pattern enumeration and classification from common vulnerabilities and exposures is difficult, as they are not always directly linked. Here, an approach to directly find common links between these dictionaries is proposed. Then, several patterns, which are combinations of similarity measures and popular algorithms such as term frequency–inverse document frequency, universal sentence encoder, and sentence BERT, are evaluated experimentally using the proposed approach. Specifically, two metrics, recall and mean reciprocal rank, are used to assess the traceability of the common attack pattern enumeration and classification identifiers associated with 61 identifiers for common vulnerabilities and exposures. The experiment confirms that the term frequency–inverse document frequency algorithm provides the best overall performance.
Design Approach and Mechanism Analysis for Cavitation-Tolerant Torque Converter Blades
Authors: Ran Zilin , Ma Wenxing , Liu Chunbao
Published: March 2022

As the development of hydrodynamic torque converters (HTCs) points toward increasing the pump input power and pump rotation speed, the negative effects of cavitation are worsening. Most studies focus on suppressing fluid machinery cavitation to attenuate the negative effects of cavitation, such as noise, vibration, and blade damage. Therefore, we proposed two stator cavitation suppression slotting methods to suppress stator cavitation in HTCs: (1) slotting both sides of the pressure and suction sides and (2) slotting one side of the suction side. The key design parameters are analyzed, including the slot width and slot position of the stator blade. Findings show that a wider slot enlarges the mass flow rate ventilation through the slot, thus reducing the cavitation risk but decreasing the hydrodynamic performance. The most effective slot position for the second proposed method (slotting one side of the suction side) is between S0.15 (stator suction side dimensionless distance 0.15 location) and S0.6 (stator blade suction side); here, the stator cavitation can be suppressed completely. The capacity factor (Tbg) and torque ratio (K) are decreased by 6.81% and 3.23%, respectively, under the stalling speed ratio, whereas the stator cavitation almost completely disappears. Therefore, the new method of slotting one side of the stator suction side completely suppresses the stator cavitation and significantly shortens the cavitation duration. The new method of slotting one side of the blade suction side can serve as a reference for turbomachinery design.
Vulnerability of Barley, Maize, and Wheat Yields to Variations in Growing Season Precipitation in Morocco
Authors: Achli Soumia , Epule Terence Epule , Dhiba Driss , Chehbouni Abdelghani , Er-Raki Salah
Published: March 2022

Climate change continues to have adverse effects on crop yields in Africa and globally. In Morocco, rising temperatures and declining precipitation are having daunting effects on the vulnerability of crops. This study examines the vulnerability of barley, maize, and wheat to variations in growing season precipitation and socio-economic proxies of adaptive capacity such as literacy and poverty rates at both national and sub-national scales in Morocco. The methodology is based on a composite vulnerability index (vulnerability is a function of exposure, sensitivity, and adaptive capacity). National and sub-national crop yield data used to compute the sensitivity index were downloaded from FAOSTAT and the global crop yield gaps Atlas. The mean annual growing season precipitation data at both the national and sub-national scales used to compute the exposure index were downloaded from the world bank climate portal. Proxy data for adaptive capacity in the form of literacy and poverty rates were downloaded from the world bank, figshare, and MPR archives. The CANESM model was used to validate the crop yield observations. The results show that wheat shows the lowest vulnerability and the highest adaptive capacity, while maize has the highest vulnerability and lowest adaptive capacity. Sub-nationally, vulnerability indexes decrease northwards while adaptive capacity and normalized growing season precipitation increase northwards. Wheat also shows the lowest vulnerability and highest adaptive capacity and normalized growing season precipitation at each latitude northward. Model validation shows that the models used here reproduce most of the spatial patterns of the crops concerned. These findings have implications for climate change adaptation and climate policy in Morocco, as it becomes evident which of these most cultivated crops are more vulnerable nationally and spatially. These results have implications for future research, as it might be important to understand how these crops perform under growing season temperature as well as what future projections and yield gaps can be observed.
A New Deep Learning Model for the Classification of Poisonous and Edible Mushrooms Based on Improved AlexNet Convolutional Neural Network
Authors: Ketwongsa Wacharaphol , Boonlue Sophon , Kokaew Urachart
Published: March 2022

The difficulty involved in distinguishing between edible and poisonous mushrooms stems from their similar appearances. In this study, we attempted to classify five common species of poisonous and edible mushrooms found in Thailand, Inocybe rimosa, Amanita phalloides, Amanita citrina, Russula delica, and Phaeogyroporus portentosus, using the convolutional neural network (CNN) and region convolutional neural network (R-CNN). This study was motivated by the yearly death toll from eating poisonous mushrooms in Thailand. In this research, a method for the classification of edible and poisonous mushrooms was proposed and the testing time and accuracy of three pretrained models, AlexNet, ResNet-50, and GoogLeNet, were compared. The proposed model was found to reduce the duration required for training and testing while retaining a high level of accuracy. In the mushroom classification experiments using CNN and R-CNN, the proposed model demonstrated accuracy levels of 98.50% and 95.50%, respectively.
Fabrication of Low-Twist and High-Strength Metallic Fibre Hybrid Spun Yarns
Authors: Shahzad Amir , Bilal Qadir Muhammad , Ali Zulfiqar , Khaliq Zubair , Qamar Khan Muhammad , Kim Ick-Soo
Published: March 2022

Stainless-steel fibre hybrid spun yarns are becoming increasingly popular due to their wide range of applications. In this aspect, the cost-effective and scalable processing of such yarns is highly important. Stainless-steel staple fibres are relatively heavier and weaker compared to conventional textile fibres. As a result, the staple spinning processing of these fibres showing higher tensile strength and productivity both at the same time is quite challenging. In this manuscript, we explored a number of spinning techniques to find the optimised method of producing low-twist and high-strength stainless-steel fibre hybrid spun yarns offering the advantage of both quality and productivity. Conventional ring spinning, folding and twisting, and advanced ring spinning techniques (ARSTs) such as pneumatic compact ring spinning and pneumatic compact SIRO spinning were employed in this study. Additionally, the plain and SIRO yarns were produced in two forms using the compact spinning method, one with pneumatic suction active (compact plain, compact SIRO) and other with pneumatic suction inactive (noncompact plain, noncompact SIRO). The tensile properties of yarns were tested and analysed. The results reveal that the tensile properties of conventional ring-spun and plied yarns can be enhanced to some extent by increasing the twist coefficient (TC) and the number of yarn plies, respectively. In contrast, by finding optimised spinning parameters, a substantially higher tensile strength (up to 16%) of yarns, produced at ARSTs, was observed even at the minimum level of TC used in experiments. The findings of the study are extremely valuable in terms of scaling up the production of high-quality metallic fibre hybrid spun yarns at a higher productivity level.
Formalism-Driven Development: Concepts, Taxonomy, and Practice
Authors: Ding Yepeng , Sato Hiroyuki
Published: March 2022

Formal methods are crucial in program specification and verification. Instead of building cases to test functionalities, formal methods specify functionalities as properties and mathematically prove them. Nevertheless, the applicability of formal methods is limited in most development processes due to the requirement of mathematical knowledge for developers. To promote the application of formal methods, we formulate formalism-driven development (FDD), which is an iterative and incremental development process that guides developers to adopt proper formal methods throughout the whole development lifespan. In FDD, system graphs, a variant of transition systems optimized for usability, are designed to model system structures and behaviors with representative properties. System graphs are built iteratively and incrementally via refinement. Properties of system graphs are specified in propositional and temporal logics and verified by model-checking techniques with interpretation over transition system. In addition, skeleton programs are generated based on system graphs and expose implementable interfaces for executing external algorithms and emitting observable effects. Furthermore, we present Seniz, a framework that practicalizes and automates FDD. In this paper, we explicate the concepts and taxonomy of FDD and discuss its practice.
Comparison of the Wrist Range of Motion Measurement between Inertial Measurement Unit Glove, Smartphone Device and Standard Goniometer
Authors: Surangsrirat Decho , Bualuangngam Tapiya , Sri-iesaranusorn Panyawut , Chaiyaroj Attawit , Buekban Chatchai , Thanawattano Chusak , Poopitaya Sompob
Published: March 2022

A goniometer is currently the gold standard for range of motion (ROM) measurements. However, trained staff are required for accurate measurements. The objective of this study is to assess an agreement between the proposed standalone inertial measurement unit glove, smartphone device, and a standard goniometer for the measurement of wrist range of motion. Twenty participants performed wrist flexion, wrist extension, pronation, supination, ulnar deviation, and radial deviation movements with three operators measuring the movements with three devices. Average measurements from the three approaches had within 1.5 degrees of difference from each other for all of the movements. Both the proposed IMU glove and smartphone showed a strong correlation to the goniometer in most of the movements, with an intraclass correlation coefficient (ICC) between 0.914 and 0.961, and between 0.929 and 0.951, respectively. Only wrist supination using the smartphone has an ICC of 0.828. In comparison with a standard goniometer, a smartphone device is a more convenient method and readily available. The proposed IMU glove requires additional hardware but is easier to use and is more suitable for measuring and monitoring dynamic motion than a smartphone or a goniometer. These patient-friendly approaches could be used by the patients at home and provide remote quantitative monitoring during the wrist rehabilitation process.
Seasonal Variations in the Concentration of Particulate Matter in the Air of Cracow Affect the Magnitude of CD4+ T Cell Subsets Cytokine Production in Patients with Inflammatory and Autoimmune Disorders
Authors: Gałuszka-Bulaga Adrianna , Węglarczyk Kazimierz , Latacz Paweł , Jodłowska-Cicio Katarzyna , Korkosz Mariusz , Pera Joanna , Słowik Agnieszka , Siedlar Maciej , Baran Jarek
Published: March 2022

Recently, the increased prevalence of chronic civilization diseases triggered by environmental pollution has been observed. In this context, the role of air pollution in the pathogenesis of autoimmune and/or inflammatory disorders is poorly elucidated. Here, we asked whether seasonal changes in the air quality of the city of Cracow affect the polarization of T cell subsets in healthy donors (HD) and patients with rheumatoid arthritis (RA), multiple sclerosis (MS), and atherosclerosis (AS). Peripheral blood mononuclear cells (PBMCs) from HD and patients were exposed in vitro to particulate matter isolated from the air of Cracow (PM CRC). Blood samples were collected in two seasons (winter and summer), with differences in air concentration of particulate matter of 10 μm (PM10) (below or above a daily limit of 50 µg/m3). The obtained data showed a significantly elevated frequency of CD4+ lymphocytes specific for IFN-γ and IL-17A after the exposure of PBMCs to PM CRC. This was observed for all patients’ groups and HD. In the case of patients, this effect was dependent on the seasonal concentration of PM in the air, paradoxically being less pronounced in the season with a higher concentration of air pollution. These observations may suggest the role of air pollution on the course of inflammatory and autoimmune disorders.
Comparative Draft Genomes of Leishmania orientalis Isolate PCM2 (Formerly Named Leishmania siamensis) and Leishmania martiniquensis Isolate PCM3 from the Southern Province of Thailand
Authors: Anuntasomboon Pornchai , Siripattanapipong Suradej , Unajak Sasimanas , Choowongkomon Kiattawee , Burchmore Richard , Leelayoova Saovanee , Mungthin Mathirut , E-kobon Teerasak
Published: March 2022

(1) Background: Autochthonous leishmaniasis, a sandfly-borne disease caused by the protozoan parasites Leishmania orientalis (formerly named Leishmania siamensis) and Leishmania martiniquensis, has been reported for immunocompromised and immunocompetent patients in the southern province of Thailand. Apart from the recent genomes of the northern isolates, limited information is known on the emergence and genetics of these parasites. (2) Methods: This study sequenced and compared the genomes of L. orientalis isolate PCM2 and L. martiniquensis isolate PCM3 with those of the northern isolates and other 14 Leishmania species using short-read whole-genome sequencing methods and comparative bioinformatic analyses. (3) Results: The genomes of the southern isolates of L. orientalis and L. martiniquensis were 30.01 Mbp and 32.39 Mbp, and the comparison with the genomes of the northern isolates revealed species-level similarity with a level of genome and proteome variation, suggesting the different strains. Comparative proteome analysis showed six protein groups with 53 unique proteins for the strain PCM2 and 97 for the strain PCM3. Certain proteins were related to virulence, drug resistance, and stress response. (4) Conclusion: Therefore, the findings could indicate the need for more genetic and population genomic investigation, and the close monitoring of L. orientalis and L. martiniquensis in Thailand and neighboring regions.
Tau Protein Modulates Perineuronal Extracellular Matrix Expression in the TauP301L-acan Mouse Model
Authors: Schmidt Sophie , Holzer Max , Arendt Thomas , Sonntag Mandy , Morawski Markus
Published: March 2022

Tau mutations promote the formation of tau oligomers and filaments, which are neuropathological signs of several tau-associated dementias. Types of neurons in the CNS are spared of tau pathology and are surrounded by a specialized form of extracellular matrix; called perineuronal nets (PNs). Aggrecan, the major PN proteoglycans, is suggested to mediate PNs neuroprotective function by forming an external shield preventing the internalization of misfolded tau. We recently demonstrated a correlation between aggrecan amount and the expression and phosphorylation of tau in a TauP310L-acan mouse model, generated by crossbreeding heterozygous aggrecan mice with a significant reduction of aggrecan and homozygous TauP301L mice. Neurodegenerative processes have been associated with changes of PN structure and protein signature. In this study, we hypothesized that the structure and protein expression of PNs in this TauP310L-acan mouse is regulated by tau. Immunohistochemical and biochemical analyses demonstrate that protein levels of PN components differ between TauP301LHET-acanWT and TauP301LHET-acanHET mice, accompanied by changes in the expression of protein phosphatase 2 A. In addition, tau can modulate PN components such as brevican. Co-immunoprecipitation experiments revealed a physical connection between PN components and tau. These data demonstrate a complex, mutual interrelation of tau and the proteoglycans of the PN.
The Novel Analogue of Modafinil CE-158 Protects Social Memory against Interference and Triggers the Release of Dopamine in the Nucleus Accumbens of Mice
Authors: Ebner Karl , Sartori Simone B. , Murau Rita , Kopel Fabian , Kalaba Predrag , Dragačević Vladimir , Leban Johann J. , Singewald Nicolas , Engelmann Mario , Lubec Gert
Published: March 2022

Previous studies have shown that atypical dopamine-transporter-inhibitors such as modafinil and its analogues modify behavioral and cognitive functions in rodents. Here, we tested potential promnestic effects of the novel, more dopamine-transporter selective modafinil analogue CE-158 in the social discrimination memory task in male mice. Systemic administration of CE-158 1 h before the social learning event prevented the impairment of social-recognition memory following retroactive interference 3 h after the learning session of a juvenile conspecific. This effect was dose-dependent, as mice treated with 10 mg/kg, but not with 1 mg/kg CE-158, were able to discriminate between the novel and familiar conspecific despite the presentation of an interference stimulus, both 3 h and 6 h post learning. However, when 10 mg/kg of the drug was administered after learning, CE-158 failed to prevent social memory from interference. Paralleling these behavioral effects, the systemic administration of 10 mg/kg CE-158 caused a rapid and sustained elevation of extracellular dopamine in the nucleus accumbens, a brain area where dopaminergic signaling plays a key role in learning and memory function, of freely moving mice, while 1 mg/kg was not sufficient for altering dopamine levels. Taken together, our findings suggest promnestic effects of the novel dopamine-transporter-inhibitor CE-158 in a social recognition memory test that may be in part mediated via increased dopamine-neurotransmission in the nucleus accumbens. Thus, selective-dopamine-transporter-inhibitors such as CE-158 may represent interesting drug candidates for the treatment of memory complaints observed in humans with cognitive impairments and dementia.
Supporting Relatives Prior to Caregiver Burden—Preventive E-Mental Health Short Intervention for Family Members of Individuals with Parkinsonism in an Early Phase of the Disease: Protocol for a Feasibility Study
Authors: Muente Catharina , Folkerts Ann-Kristin , Kalbe Elke , Thieken Franziska , Assmann Laura-Elisa , Widritzki Maria , Eggers Carsten , Pedrosa David , Wilhelm Marcel
Published: March 2022

Research on support for relatives of patients with Parkinsonism has mainly focused on caregivers, while preventive offers for non-caregiving relatives are lacking. Thus, the aim of this multicenter pilot study is to develop and assess the feasibility of a preventive psychosocial support program for relatives of patients with Parkinsonism. It specifically focuses on family members of patients who are in an early phase of the disease, are not currently caregiving, and have not yet developed distress symptoms. It includes a telemedicine-based, 6-week preventive psychological short intervention (PPSI). The main objective of this feasibility mixed-methods study is to specify the demand for an early, low-threshold, and low-cost short intervention and to collect feedback based on qualitative and quantitative data of N = 20 relatives. Secondary objectives are an evaluation of the effects of the intervention and an analysis of the study design. Future directions are to further develop the PPSI using these data. This study can serve as a basis for future randomized controlled studies on this intervention, which might fill an important gap in clinical supply.