bluuebunny/crossref_metadata_2025 huggingface dataset:
Molecular survey of Zika virus in the animal-human interface in traditional farming
Authors: Lopez-Apodaca Laura Ivone , Zarza Heliot , Zamudio-Moreno Emily , Nuñez-Avellaneda Daniel , Baak-Baak Carlos Marcial , Reyes-Solis Guadalupe del Carmen , Oswaldo Margarito Torres-Chablé , Peláez-Ballestas Ingris , Roiz David , Suzán Gerardo , Roche Benjamin , Machain-Williams Carlos Ignacio
Published: November 2022

Backyard animal husbandry is common in rural communities in developing countries and, given the conditions in which it occurs, it can increase the risk of disease transmission, such as arboviruses. To determine the presence of the Zika virus (ZIKV) and abundance of its arthropod vectors we evaluated the socioeconomic implications involved in its transmission in two highly vulnerable Mayan communities in the state of Yucatan that practice backyard farming. An analytical cross-sectional study was carried out throughout 2016 to understand socioeconomic variables and seasonal patterns in mosquito populations. We selected 20 households from each community. Social exclusion indicators were analyzed, human and domestic animals were sampled, and mosquitoes were collected and identified. Four out of eight indicators of social exclusion were higher than the reported national averages. We captured 5,825 mosquitoes from 16 species being Culex quinquefasciatus and Aedes aegypti the most abundant. The presence of chickens and human overcrowding in dwellings were the most significant factors (P = 0.026) associated with the presence of Ae. aegypti. Septic tanks (odds ratio = 6.64) and chickens (odds ratio = 27.41) in backyards were the main risk factors associated with the presence of immature states of Ae. aegypti in both communities. Molecular analysis to detect ZIKV was performed in blood samples from 416 humans, 1,068 backyard animals and 381 mosquito pools. Eighteen humans and 10 pig pools tested positive for ZIKV. Forty-three mosquito pools tested positive for flavivirus. Ten of the 43 pools of positive mosquitoes were sequenced, corresponding 3/10 to ZIKV and 1/10 to Dengue virus type 2. The findings obtained indicate the continuous circulation of Flavivirus (including ZIKV) in backyard environments in vulnerable communities, highlighting the importance of studying their transmission and maintenance in these systems, due that backyard animal husbandry is a common practice in these vulnerable communities with limited access to health services.
A Review on Computer Vision Technology for Physical Exercise Monitoring
Authors: Khanal Salik Ram , Paulino Dennis , Sampaio Jaime , Barroso Joao , Reis Arsénio , Filipe Vitor
Published: November 2022

Physical activity is movement of the body or part of the body to make muscles more active and to lose the energy from the body. Regular physical activity in the daily routine is very important to maintain good physical and mental health. It can be performed at home, a rehabilitation center, gym, etc., with a regular monitoring system. How long and which physical activity is essential for specific people is very important to know because it depends on age, sex, time, people that have specific diseases, etc. Therefore, it is essential to monitor physical activity either at a physical activity center or even at home. Physiological parameter monitoring using contact sensor technology has been practiced for a long time, however, it has a lot of limitations. In the last decades, a lot of inexpensive and accurate non-contact sensors became available on the market that can be used for vital sign monitoring. In this study, the existing research studies related to the non-contact and video-based technologies for various physiological parameters during exercise are reviewed. It covers mainly Heart Rate, Respiratory Rate, Heart Rate Variability, Blood Pressure, etc., using various technologies including PPG, Video analysis using deep learning, etc. This article covers all the technologies using non-contact methods to detect any of the physiological parameters and discusses how technology has been extended over the years. The paper presents some introductory parts of the corresponding topic and state of art review in that area.
Influence of Supplemental Feeding on Body Condition Score and Reproductive Performance Dynamics in Botosani Karakul Sheep
Authors: Nechifor Ionică , Florea Marian Alexandru , Radu-Rusu Răzvan-Mihail , Pascal Constantin
Published: November 2022

The aim of this research was to study the impact of supplementary feeding on reproductive traits in sheep. Two groups, L1 (control) and L2 (experimental treatment), of adult females aged between two and six years belonging to the Botosani Karakul sheep breed were formed. The experimental treatment group (L2) received supplementary feeding 25 days prior to mating. Improvements in body condition and significant increases in live weight occurred by the time of mating in those ewes that had been flushed (L2) (p < 0.01 vs. L1). The number of lambs per individual parturition was influenced by the body condition score (BCS), especially in females with a BCS of 2.0. The total number of weaned lambs in females with a BCS of 2.0 differed in comparison to that of females with a BCS of 2.5 or 3.0. All results highlighted that supplementary feeding applied to ewes prior to mating affected their reproductive and economic performance, translating to an increased live weight of the litter at weaning in the L2 group (p < 0.01 in lambs from BCS 2.0 ewes and p < 0.001 in lambs from BCS 2.5 to 3.5 ewes).
Impact of Press Mud and Animal Manure in Comparison with NPK on the Growth and Yield of Triticale (Triticosecale wittmack) Genotypes Cultivated under Various Irrigation Regimes
Authors: Sher Ahmad , Nawaz Muhammad , Hasnain Zuhair , Mehmood Kashf , Chattha Muhammad Bilal , Ijaz Muhammad , Sattar Abdul , Ibrar Danish , Bashir Saqib , Khan Muhammad Musawir , Gul Safia , Irshad Sohail , Fahad Shah , Ahmed Niaz , Habibullah  , Rais Afroz , Khan Shahbaz
Published: November 2022

It is needful to have alternative nutritious cereal crops to feed the ever increasing population and meet food security in the long run. Triticale (Triticosecale wittmack) is used for both livestock feed and human consumption as it contains higher protein and lysine contents than other cereals. Synthetic fertilizers applied in combination with organic amendments can play a pivotal role in increasing crop yields. Field experiments were designed to explore the impact of chemical fertilizers (NPK), press mud and animal manure on growth and yield of triticale genotypes cultivated under different irrigation regimes. Experiments were laid out by using randomized complete block design (RCBD) with split-split plot arrangements having three replicates and comprised of different treatments such as chemical fertilizers (T1 = control, T2 = NPK, T3 = press mud and T4 = animal manure), genotypes (G1 and G2), and irrigation regimes (I1 = full irrigation, I2 = irrigation was skipped at heading stage, and I3 = irrigation was skipped at heading and grain filling stages). Statistical analyses of collected data depicted the significant effect of chemical fertilizers, organic amendments, genotypes and irrigation regimes on various yield and yield related attributes of triticale. The highest increment in various observed attributes like plant height, leaves per plant, spike length, spikelets per spike, grains per spike, leaf area, 1000-grain weight, biological yield and grain yield was recorded in I1, followed by I2 and I3; in case of varieties, G1 performed better than G2 while T3 had maximum values in the aforementioned parameters as compared to other treatments. The application of NPK in combination with press mud and animal manure improved the growth and yield of triticale genotypes cultivated under different irrigation regimes. Thus, NPK along with organic amendments and irrigation practices can successfully be used to improve the growth and yield of triticale.
Molecular Characterization of Diverse Wheat Genetic Resources for Resistance to Yellow Rust Pathogen (Puccinia striiformis)
Authors: Saeed Muhammad , Ibrahim Muhammad , Ahmad Waqas , Tayyab Muhammad , Attacha Safira , Khan Mudassar Nawaz , Jadoon Sultan Akbar , Shah Syed Jehangir , Zeb Shaista , Shah Liaqat , Munsif Fazal , Zubair Ahmad , Lu Jie , Si Hongqi , Ma Chuanxi
Published: November 2022

Yellow rust (YR) epidemics have affected wheat productivity worldwide. YR resistance (Yr) is eminent in wheat; however, it is continuously invaded by evolving YR pathogen Puccinia striiformis (Pst.). Understanding the Yr genes’ diversity among the available germplasm is paramount to developing YR-resistant cultivars. In this study, 14 wheat genotypes were screened for their relative resistance index (RRI) and Yr genes/QTL via linked microsatellite markers. RRI screening categorized the studied genotypes into susceptible (<5; 4.44 ± 0.75), moderate (5–7; 6.11 ± 0.64), and resistant (>7; 8.45 ± 0.25) bulks (p < 0.001). Genetic analysis using 19 polymorphic microsatellite markers revealed 256 alleles, which were divergent among the three resistance bulks. Markers Xbarc7 and Xgwm429 showed the highest allelic diversity in comparison to Xbarc181, Xwmc419, SCAR1400, and Xgwm130. Resistant bulk showed associated alleles at Yr18 gene-linked markers Xgwm295, cssfr6, and csLV34. Other RRI-associated alleles at markers Xbarc7 and Xbarc101 showed weak and moderate linkages, respectively, with the Yr5 gene; whereas, a moderate association was noted for the Yr15 gene-linked marker Xgwm11. Marker Xwe173 linked with the Yr26 gene showed associated alleles among the susceptible bulk. Cross combinations of the parental lines forming recombinant inbred lines (RILs) demonstrated net higher RRI implying favorable allelic recombination. These results support reports and field observations on novel Pst. races that triggered Yr26, Yr5, and Yr15 busts in recent past. This study further implies that pyramiding all stage resistance genes (Yr5, Yr10, Yr15, and Yr26) with adult plant resistance genes (Yr18 and Yr62) should provide sustained YR resistance. The associated alleles at Yr genes-linked markers provide a basis for marker-assisted YR resistance breeding in wheat.
Climate Change Promotes the Large-Scale Population Growth of Grapholita molesta (Busck) (Lepidoptera: Tortricidae) within Peach Orchards in China
Authors: Li Hongchen , Peng Qiulian , Wang Su , Zhang Fan , Guo Xiaojun , Jiang Quan , Huang Ningxing , Li Hu
Published: November 2022

Cosmopolitan agricultural herbivorous pests are provided with a wide range of potential hosts. Therefore, they have high carrying capacity, and can cause extremely severe damage in agroecosystems. Understanding the ecological mechanisms of their population dynamics, especially as they relate to large-scale meteorological variations and geographical landscape influences, can help us to reveal how they became such important pests. The oriental fruit moth, Grapholita molesta, is a typical example of a significant pest distributed on a large scale, which is capable of damaging fruit trees of economic value such as peach, apple, pear, etc. This pest not only occurs in China, but exists on all continents except Antarctica. In order to prevent major pests and diseases, a system of plant protection has been established gradually in peach orchards within the Modern Agro-industry Technology Research System in China (CARS) since 2009. In the system, we collected the monitoring data of G. molesta by using pheromone traps at 17 experimental stations, and then used the corresponding climate data (temperature and precipitation) to explore the link between climate factors using mixed models. The results show that both monthly mean temperature and precipitation had a significant positive correlation with the occurrence of G. molesta. Therefore, global warming with higher levels of precipitation may favor G. molesta, allowing it to outperform other potential pests at the population level in peach orchards, on a large scale.
Associations between Pet Care Responsibility, Companion Animal Interactions, and Family Relationships during COVID-19
Authors: Charmaraman Linda , Kiel Elizabeth , Richer Amanda M. , Gramajo Alyssa , Mueller Megan K.
Published: November 2022

For families with children during the COVID-19 pandemic, it is crucial to explore how both youth and parents view their roles with regard to the shared caretaking of pets. While most human–animal interaction studies examine adult or early childhood samples, our focus was on adolescent development. We present findings from a U.S. based mixed-method study of adolescent surveys and parent interviews regarding pet care responsibility. As part of an ongoing longitudinal study, we analyzed survey data from 567 pet-owning adolescents and a subset of 356 dog owning adolescents aged 10–17 as well as 31 in-depth interviews with parents of adolescents from the same study. Higher reported pet caretaking responsibilities was significantly associated with a preference for spending time with pets when stressed and improved family relationships during the COVID-19 pandemic for both pet owners and dog owners. For dog owners only, increased levels of responsibility for the pet was significantly associated with a higher likelihood of identifying as a pet owner. Qualitative findings showcase the range of parental expectations and adolescent initiative around pet caretaking. Our study highlights the continued importance of pet companionship during the adolescent years as they develop their identities as responsible pet owners.
Valuation of Goat and Sheep By-Products: Challenges and Opportunities for Their Use
Authors: Cordeiro Ana Rita Ribeiro de Araújo , Bezerra Taliana Kênia Alencar , Madruga Marta Suely
Published: November 2022

Goat and sheep meat production is a challenge for the meat industry as well as for environmental management. Yet within cultures, certain by-products, such as liver, the lungs, heart, brain, spleen, blood, tail and ears, are traditionally used in the production of typical dishes for regional or local cuisine. These by-products are a rich source of lipids, proteins, essential amino acids, B-complex vitamins, and minerals. They can be effectively exploited for higher (value-added) applications, including functional foods or feed ingredients, food supplements, enzymes and other chemical products such as hydrolyzed proteins and flavorings. This review article gathers data on: (i) the production of by-products obtained from slaughter and available for processing, and (ii) potential strategies for using and applying these by-products in obtaining new value-added ingredients. Other than proteins, the review discusses other macromolecules and possible uses of these by-products in culinary dishes, as hydrolyzed enzymes, and as food additives. Even though these by-products undoubtedly present themselves as rich in nutrients, there remains an unfortunate lack of documented information on the potential use of these by-products for their bioactive components, peptides that have various biological and technological properties, and the use of hydrolyzed versions of these by-products as precursors for the production of flavorings.
The Importance of Dietary Antioxidants on Oxidative Stress, Meat and Milk Production, and Their Preservative Aspects in Farm Animals: Antioxidant Action, Animal Health, and Product Quality—Invited Review
Authors: Ponnampalam Eric N. , Kiani Ali , Santhiravel Sarusha , Holman Benjamin W. B. , Lauridsen Charlotte , Dunshea Frank R.
Published: November 2022

The biological effects of oxidative stress and associated free radicals on farm animal performance, productivity, and product quality may be managed via dietary interventions—specifically, the provision of feeds, supplements, and forages rich in antioxidants. To optimize this approach, it is important first to understand the development of free radicals and their contributions to oxidative stress in tissue systems of farm animals or the human body. The interactions between prooxidants and antioxidants will impact redox homeostasis and, therefore, the well-being of farm animals. The impact of free radical formation on the oxidation of lipids, proteins, DNA, and biologically important macromolecules will likewise impact animal performance, meat and milk quality, nutritional value, and longevity. Dietary antioxidants, endogenous antioxidants, and metal-binding proteins contribute to the ‘antioxidant defenses’ that control free radical formation within the biological systems. Different bioactive compounds of varying antioxidant potential and bio-accessibility may be sourced from tailored feeding systems. Informed and successful provision of dietary antioxidants can help alleviate oxidative stress. However, knowledge pertaining to farm animals, their unique biological systems, and the applications of novel feeds, specialized forages, bioactive compounds, etc., must be established. This review summarized current research to direct future studies towards more effective controls for free radical formation/oxidative stress in farm animals so that productivity and quality of meat and milk can be optimized.
Trends in Reproductive Indicators of Green and Hawksbill Sea Turtles over a 30-Year Monitoring Period in the Southern Gulf of Mexico and Their Conservation Implications
Authors: López-Castro Melania C. , Cuevas Eduardo , Guzmán Hernández Vicente , Raymundo Sánchez Ángeles , Martínez-Portugal Rosa C. , Reyes Diana J. Lira , Chio Jorge Ángel Berzunza
Published: November 2022

Long-term monitoring programs of species at risk are efficacious tools to assess population changes, evaluate conservation strategies, and improve management practices to ensure populations reach levels at which they can fulfill their ecological roles. For sea turtles, annual nesting beach surveys are the most accessible method to estimating the population abundance and reproductive output, especially when these are done in primary nesting sites. However, little data exist on the long-term assessment of these parameters. Here, we present the trends of the nest abundance, female size, hatching, and emergence success of hawksbill (Eretmochelys imbricata) and green (Chelonia mydas) turtles at key nesting beaches in the southern Gulf of Mexico over 31 years (from 1990 to 2021). The nest abundance showed an increasing trend in both species as a result of the sustained protection and conservation effort, but there was no significant temporal trend in the annual female size, clutch size, hatching, and emergence success. However, these indicators showed decreasing mean values over the last decade and should be closely monitored. We suggest these decreases link to the combined effects of ocean warming and anthropogenic pressures affecting the sea turtle foraging grounds. Aside from protecting key nesting sites, protecting and restoring crucial foraging habitats should be an immediate priority requiring international cooperation.
Gastroprotective Effect of Anisomeles indica on Aspirin-Induced Gastric Ulcer in Mice
Authors: Lien Hsiu-Man , Wang Yu-Yen , Huang Mei-Zi , Wu Hui-Yu , Huang Chao-Lu , Chen Chia-Chi , Hung Shao-Wen , Chen Chia-Chang , Chiu Cheng-Hsun , Lai Chih-Ho
Published: November 2022

Gastric ulcers are commonly seen in the upper gastrointestinal tract and may be related to the Helicobacter pylori infection and the use of aspirin, a nonsteroidal anti-inflammatory drug (NSAID). Typically, proton-pump inhibitors (PPIs) are used to treat gastric ulcers; however, adverse effects have emerged following long-term treatment. Natural medicines are used as alternative therapeutic agents in the treatment of gastric ulcers, with few side effects. Despite various reports on the anti-H. pylori and anti-gastric cancer activities of Anisomeles indica, its gastroprotective effect on ulcers remains undetermined. This study investigated the protective effect of A. indica on aspirin-induced gastric ulcers in murine models. Our results show that three fractions of ethanol-extracted A. indica inhibited aspirin-induced gastric injury. Among these, A. indica Fraction 1 was observed to enrich ovatodiolide, which effectively diminished gastric acidity and alleviated aspirin-induced inflammation in the stomach. Our results provide evidence that A. indica could be developed as an effective therapeutic agent for gastroprotective purposes.
Optimization of Discrete Wavelet Transform Feature Representation and Hierarchical Classification of G-Protein Coupled Receptor Using Firefly Algorithm and Particle Swarm Optimization
Authors: Kamal Nor Ashikin Mohamad , Bakar Azuraliza Abu , Zainudin Suhaila
Published: November 2022

Ineffective protein feature representation poses problems in protein classification in hierarchical structures. Discrete wavelet transform (DWT) is a feature representation method which generates global and local features based on different wavelet families and decomposition levels. To represent protein sequences, the proper wavelet family and decomposition level must be selected. This paper proposed a hybrid optimization method using particle swarm optimization and the firefly algorithm (FAPSO) to choose the suitable wavelet family and decomposition level of wavelet transformation for protein feature representation. The suggested approach improved on the work of earlier researchers who, in most cases, manually selected the wavelet family and level of decomposition based solely on experience and not on data. The paper also applied the virtual class methods to overcome the error propagation problems in hierarchical classification. The effectiveness of the proposed method was tested on a G-Protein Coupled Receptor (GPCR) protein data set consisting of 5 classes at the family level, 38 classes at the subfamily level, and 87 classes at the sub-subfamily level. Based on the result obtained, the most selected wavelet family and decomposition level chosen to represent GPCR classes by FAPSO are Biorthogonal wavelets and decomposition level 1, respectively. The experimental results show that the representation of GPCR protein using the FAPSO algorithm with virtual classes can yield 97.9%, 86.9%, and 81.3% classification accuracy at the family, subfamily, and sub-subfamily levels, respectively. In conclusion, the result shows that the selection of optimized wavelet family and decomposition level by the FAPSO algorithm, and the virtual class method can be potentially used as the feature representation method and a hierarchical classification method for GPCR protein.
Biomedical Text NER Tagging Tool with Web Interface for Generating BERT-Based Fine-Tuning Dataset
Authors: Park Yeon-Ji , Lee Min-a , Yang Geun-Je , Park Soo Jun , Sohn Chae-Bong
Published: November 2022

In this paper, a tagging tool is developed to streamline the process of locating tags for each term and manually selecting the target term. It directly extracts the terms to be tagged from sentences and displays it to the user. It also increases tagging efficiency by allowing users to reflect candidate categories in untagged terms. It is based on annotations automatically generated using machine learning. Subsequently, this architecture is fine-tuned using Bidirectional Encoder Representations from Transformers (BERT) to enable the tagging of terms that cannot be captured using Named-Entity Recognition (NER). The tagged text data extracted using the proposed tagging tool can be used as an additional training dataset. The tagging tool, which receives and saves new NE annotation input online, is added to the NER and RE web interfaces using BERT. Annotation information downloaded by the user includes the category (e.g., diseases, genes/proteins) and the list of words associated to the named entity selected by the user. The results reveal that the RE and NER results are improved using the proposed web service by collecting more NE annotation data and fine-tuning the model using generated datasets. Our application programming interfaces and demonstrations are available to the public at via the website link provided in this paper.
Design of a Structural Health Monitoring System and Performance Evaluation for a Jacket Offshore Platform in East China Sea
Authors: Ye Hailin , Jiang Chuwei , Zu Feng , Li Suzhen
Published: November 2022

Offshore platform plays an important role in ocean strategy, and the construction of structural health monitoring (SHM) system could significantly improve the safety of the platform. In this paper, complete SHM system architecture design for offshore platform is presented, including the sensor subsystem, data reading and transferring subsystem, data administration subsystem, and assessment subsystem. First, the sensor subsystem is determined to include the structure information, component information, and vibration information monitoring of the offshore platform. Based on the monitoring target, three sensor types including incline sensor, acceleration sensor, and strain sensor are initially selected. Second, the assessment subsystem is determined to include safety monitoring and early warning evaluation using static measurements, overall performance evaluation based on frequency variation, and damage identification based on strain modal using strain monitoring. Overall performance evaluation based on frequency variation and damage identification based on Strain modal are illustrated. Finally, an offshore platform in the East China Sea is selected to establish a finite-element model to discuss the application and feasibility of the SHM system, the frequency variation due to scouring, corrosion, the growth of marine organisms, and temperature variation was investigated, and the overall performance of the platform was also evaluated. This work can provide a reference for installation and implementation of SHM system for offshore platform.
CAR-Tourist: An Integrity-Preserved Collaborative Augmented Reality Framework-Tourism as a Use-Case
Authors: Syed Toqeer Ali , Jan Salman , Siddiqui Muhammad Shoaib , Alzahrani Ali , Nadeem Adnan , Ali Arshad , Ullah Ali
Published: November 2022

The unprecedented growth in Augmented Reality (AR) has captured the focus of researchers and the industrial sector. The development of AR applications and their implementation in various domains is broadening. One of the advancements in the field of AR is Collaborative AR, which provides ample opportunities for the members of a team to work on a particular project remotely. The various activities carried out remotely, in a collaborative fashion, are based on the active interaction and transmission of data and applications across a communication channel that constitutes a mesh of frequently interacting applications, thus providing a real feeling of working together physically in the purportedly same demographic area. However, in the integration of different roles, remotely working in collaborative AR has a great chance of being intruded upon and manipulated. Consequently, the intrusion may explore novel vulnerabilities to various sensitive collaborative projects. One of the security concerns for collaborative and interconnected remote applications is to have pristine environments, where the participants of the collaborative AR can reliably trust each other during the execution of the various processes. This paper presents an integrity-aware CAR-Tourist (Collaborative Augmented reality for Tourism) framework wherein the unauthorized user’s access is denied and the remote participants of the network are provided with a secure environment through the state-of-the-art Blockchain architecture. This study further provides a use-case implementation of a tourism application. Each tourist has the chance to hire a remote guide for collaborative guidance over a blockchain-trusted network. Moreover, the proposed framework is lightweight, as the only necessary communication between the tourist and guide is recorded in the blockchain network. Each user has to register on a permission blockchain to be allowed to perform certain activities on our proposed CAR-Tourist framework. The decentralized Blockchain approach provides a consensus mechanism based on which not every participant is free to intrude on ongoing communication. Thus, through the proposed framework, all the participants in the collaborative Augmented Reality will have the essential trust of working remotely without external intrusion.
A Study on the Identification of Delayed Delivery Risk Transmission Paths in Multi-Variety and Low-Volume Enterprises Based on Bayesian Network
Authors: Yang Linchao , Zhang Fan , Liu Anying , Zhou Shenghan , Wu Xiangwei , Wei Fajie
Published: November 2022

Due to the prevalence of the order production mode, multi-variety, small-batch manufacturing enterprises frequently delay deliveries to downstream customers. To date, most existing studies on delayed delivery risk have focused on the response to the risk after it occurs, ignoring how the risk arises. For multi-variety, low-volume production companies, any part of the production process could lead to the ultimate risk of delayed delivery, and the risk is transmissible. Therefore, the path of risk transmission needs to be identified to effectively control the risk of late delivery at key production stages. In this paper, from the perspective of risk transmission, a recognition method based on association rules and the Bayesian network was proposed to identify the risk conduction path. This method firstly determined the strong association rules among the risk factors based on historical data stored in the ERP system and determined the Bayesian network topology structures of the risk transmission path by combining the business process and expert experience. Secondly, the prior and conditional probabilities of each node were determined using data statistics, and the risk transmission path of delayed delivery was identified using the forward and backward reasoning of the Bayesian network. Finally, this paper provided a case study to verify the method, and the following conclusions were obtained: (1) the delay in delivery to downstream customers is mainly due to the delayed delivery of upstream suppliers and the sudden change in customer demand, and (2) the adjustment of enterprise production plans is the key node of the delayed delivery risk transmission path. Through the research in this paper, production companies can identify the target of risk management more scientifically and mitigate the risk through the adjustment of key links.
Classification of Malicious URLs by CNN Model Based on Genetic Algorithm
Authors: Wu Tiefeng , Xi Yunfang , Wang Miao , Zhao Zhichao
Published: November 2022

Researchers have proposed many models for the identification of malicious URLs in network security, but they have not achieved good results. In order to improve this defect, the current popular machine learning algorithm is combined to train the model, thus improving the accuracy of malicious URL classification. This paper proposes a model of a convolutional neural network based on genetic algorithm optimization. Firstly, the genetic algorithm was used to reduce the data dimension of the grammatical features, structural features, and probabilistic features in the extracted malicious URL text, and then the convolutional neural network was used to establish the model and classify the malicious URL. Through experimental verification, the model has achieved good results. Compared with the traditional machine learning model, it improves the accuracy of malicious URL recognition and provides a reference for malicious URL recognition.
A Collection of Best Practices for the Collection and Analysis of Bioacoustic Data
Authors: Oswald Julie N. , Van Cise Amy M. , Dassow Angela , Elliott Taffeta , Johnson Michael T. , Ravignani Andrea , Podos Jeffrey
Published: November 2022

The field of bioacoustics is rapidly developing and characterized by diverse methodologies, approaches and aims. For instance, bioacoustics encompasses studies on the perception of pure tones in meticulously controlled laboratory settings, documentation of species’ presence and activities using recordings from the field, and analyses of circadian calling patterns in animal choruses. Newcomers to the field are confronted with a vast and fragmented literature, and a lack of accessible reference papers or textbooks. In this paper we contribute towards filling this gap. Instead of a classical list of “dos” and “don’ts”, we review some key papers which, we believe, embody best practices in several bioacoustic subfields. In the first three case studies, we discuss how bioacoustics can help identify the ‘who’, ‘where’ and ‘how many’ of animals within a given ecosystem. Specifically, we review cases in which bioacoustic methods have been applied with success to draw inferences regarding species identification, population structure, and biodiversity. In fourth and fifth case studies, we highlight how structural properties in signal evolution can emerge via ecological constraints or cultural transmission. Finally, in a sixth example, we discuss acoustic methods that have been used to infer predator–prey dynamics in cases where direct observation was not feasible. Across all these examples, we emphasize the importance of appropriate recording parameters and experimental design. We conclude by highlighting common best practices across studies as well as caveats about our own overview. We hope our efforts spur a more general effort in standardizing best practices across the subareas we’ve highlighted in order to increase compatibility among bioacoustic studies and inspire cross-pollination across the discipline.
Compressing BERT for Binary Text Classification via Adaptive Truncation before Fine-Tuning
Authors: Zhang Xin , Fan Jing , Hei Mengzhe
Published: November 2022

Large-scale pre-trained language models such as BERT have brought much better performance to text classification. However, their large sizes can lead to sometimes prohibitively slow fine-tuning and inference. To alleviate this, various compression methods have been proposed; however, most of these methods solely consider reducing inference time, often ignoring significant increases in training time, and thus are even more resource consuming. In this article, we focus on lottery ticket extraction for the BERT architecture. Inspired by observations that representations at lower layers are often more useful for text classification, we propose that we can identify the winning ticket of BERT for binary text classification through adaptive truncation, i.e., a process that drops the top-k layers of the pre-trained model based on simple, fast computations. In this way, the cost for compressing and fine-tuning, as well as inference, can be vastly reduced. We present experiments on eight mainstream binary text classification datasets covering different input styles (i.e., single-text and text-pair), as well as different typical tasks (e.g., sentiment analysis, acceptability judgement, textual entailment, semantic similarity analysis and natural language inference). Compared with some strong baselines, our method saved 78.1% time and 31.7% memory on average, and up to 86.7 and 48% in extreme cases, respectively. We also saw good performance, often outperforming the original language model.
Model Predictive Control and Its Role in Biomedical Therapeutic Automation: A Brief Review
Authors: Parihar Sushma , Shah Pritesh , Sekhar Ravi , Lagoo Jui
Published: November 2022

The reliable and effective automation of biomedical therapies is the need of the hour for medical professionals. A model predictive controller (MPC) has the ability to handle complex and dynamic systems involving multiple inputs/outputs, such as biomedical systems. This article firstly presents a literature review of MPCs followed by a survey of research reporting the MPC-enabled automation of some biomedical therapies. The review of MPCs includes their evolution, architectures, methodologies, advantages, limitations, categories and implementation software. The review of biomedical conditions (and the applications of MPC in some of the associated therapies) includes type 1 diabetes (including artificial pancreas), anaesthesia, fibromyalgia, HIV, oncolytic viral treatment (for cancer) and hyperthermia (for cancer). Closed-loop and hybrid cyber-physical healthcare systems involving MPC-led automated anaesthesia have been discussed in relatively greater detail. This study finds that much more research attention is required in the MPC-led automation of biomedical therapies to reduce the workload of medical personnel. In particular, many more investigations are required to explore the MPC-based automation of hyperthermia (cancer) and fibromyalgia therapies.
A Possible Reconciliation between Eddy Covariance Fluxes and Surface Energy Balance Closure
Authors: Durand Pierre
Published: November 2022

At the surface of the earth, the available radiative energy Rn is distributed between the ground heat flux and the sensible and latent heat fluxes according to the surface energy balance (SEB) equation. In the past decades, most attempts to measure the individual terms of this equation have revealed a non-closure problem, regardless of the site of observation or period of the year. Today, no definitive answer has been provided to this question. In general, it is suspected that the sensible and latent heat fluxes (H and LvE, respectively) that are calculated with the eddy-covariance technique are underestimated. This paper suggests two additional terms that should be considered in the SEB equation, which are based on thermodynamic considerations. They are directly related to H and LvE and appear to be interesting candidates for explaining (at least in part) the non-closure of the SEB. The distribution of the correction between H and LvE varies as a function of the Bowen ratio B. The correction relative to H is dominant for values of B that are greater than 0.2 and represents more than 80% of the total correction for values greater than unity. The impact of these corrections on the SEB closure was tested on a large set of observations from 24 FLUXNET sites around the world with different vegetation types. The closure defect, which is about 17% in the original dataset, is reduced to about 3% with the proposed corrections.
Neutral Beams for Neutron Generation in Fusion Neutron Sources
Authors: Dlougach Eugenia , Shlenskii Mikhail , Kuteev Boris
Published: November 2022

Neutral beam injection is supposed to be the main source of high-energy particles, driving non-inductive current and generating primary neutrons in fusion neutron sources design based on tokamaks. Numerical simulation of high-energy particles’ thermalization in plasma and fusion neutron emission is calculated by novel dedicated software (NESTOR code). The neutral beam is reproduced statistically by up to 109 injected particles. The beam efficiency and contribution to primary neutron generation is shown to be dependent on the injection energy, input current, and plasma temperature profile. A beam-driven plasma operation scenario, specific for FNS design, enables the fusion rate and neutron generation in plasma volume to be controlled by the beam parameters; the resultant primary neutron yield can be efficiently boosted in plasma maintained at a relatively low temperature when compared to ‘pure’ fusion reactors. NESTOR results are applicable to high-precision nuclear and power balance estimations, neutron power loads distribution among tokamak components, tritium generation in hybrid reactors, and for many other tasks critical for FNS design.
Extending Normality: A Case of Unit Distribution Generated from the Moments of the Standard Normal Distribution
Authors: Concha-Aracena Miguel S. , Barrios-Blanco Leonardo , Elal-Olivero David , Ferreira da Silva Paulo Henrique , Nascimento Diego Carvalho do
Published: November 2022

This paper presents an important theorem, which shows that, heading from the moments of the standard normal distribution, one can generate density functions originating a family of models. Additionally, we discussed that different random variable domains are achieved with transformations. For instance, we adopted the moment of order two, from the proposed theorem, and transformed it, which enabled us to exemplify this class as a unit distribution. We named it as Alpha-Unit (AU) distribution, which contains a single positive parameter α (AU(α)∈[0,1]). We presented its properties and demonstrated two estimation methods for the α parameter, the maximum likelihood estimator (MLE) and uniformly minimum-variance unbiased estimator (UMVUE) methods. In order to analyze the statistical consistency of the estimators, a Monte Carlo simulation study was carried out, in which the robustness was demonstrated. As a real-world application, we adopted two sets of unit data, the first regarding the dynamics of Chilean inflation in the post-military period, and the other one regarding the daily maximum relative humidity of the air in the Atacama Desert. In both cases presented, the AU model is competitive, whenever the data present a range greater than 0.4 and extremely heavy asymmetric tail. We compared our model with other commonly used unit models, such as the beta, Kumaraswamy, logit-normal, simplex, unit-half-normal, and unit-Lindley distributions.
Bilateral Sensorimotor Cortical Communication Modulated by Multiple Hand Training in Stroke Participants: A Single Training Session Pilot Study
Authors: Huang Jian-Jia , Pei Yu-Cheng , Chen Yi-Yu , Tseng Shen-Shiou , Hung Jen-Wen
Published: November 2022

Bi-manual therapy (BT), mirror therapy (MT), and robot-assisted rehabilitation have been conducted in hand training in a wide range of stages in stroke patients; however, the mechanisms of action during training remain unclear. In the present study, participants performed hand tasks under different intervention conditions to study bilateral sensorimotor cortical communication, and EEG was recorded. A multifactorial design of the experiment was used with the factors of manipulating objects (O), robot-assisted bimanual training (RT), and MT. The sum of spectral coherence was applied to analyze the C3 and C4 signals to measure the level of bilateral corticocortical communication. We included stroke patients with onset <6 months (n = 6), between 6 months and 1 year (n = 14), and onset >1 year (n = 20), and their Brunnstrom recovery stage ranged from 2 to 4. The results showed that stroke duration might influence the effects of hand rehabilitation in bilateral cortical corticocortical communication with significant main effects under different conditions in the alpha and beta bands. Therefore, stroke duration may influence the effects of hand rehabilitation on interhemispheric coherence.
Combination of Pembrolizumab and Stereotactic Body Radiation Therapy in Recurrent Metastatic Penile Squamous Cell Carcinoma: A Case Study
Authors: Kaakour Dalia , Seyedin Steven , Houshyar Roozbeh , Mar Nataliya
Published: November 2022

The prognosis for patients with penile squamous cell carcinoma metastatic to regional lymph nodes or distant sites remains poor with limited treatment options, especially after the failure of first-line chemotherapy. Clinical trials evaluating the use of checkpoint inhibitor therapy, or the use of checkpoint inhibitor therapy with stereotactic body radiation therapy for the treatment of metastatic penile squamous cell carcinoma, are currently unavailable. In this case report, we present a patient with relapsed advanced penile squamous cell carcinoma and an unknown (human papilloma virus) HPV status and borderline programmed death-ligand 1 (PD-L)1 status who was treated with pembrolizumab and stereotactic body radiation therapy. This patient achieved a complete durable treatment response despite having genomic features of an immunologically “cold” tumor. This case highlights the importance of investigating more into the treatment of these tumors that lack genomic features that classically have been observed to be susceptible to treatment with immunotherapy or immunotherapy augmented with stereotactic body radiation therapy in solid tumors, particularly in metastatic penile squamous cell carcinoma.
Immune Response after COVID-19 mRNA Vaccination in Multiple Sclerosis Patients Treated with DMTs
Authors: Mazziotti Valentina , Crescenzo Francesco , Tamanti Agnese , Dapor Caterina , Ziccardi Stefano , Guandalini Maddalena , Colombi Annalisa , Camera Valentina , Peloso Angela , Pezzini Francesco , Turano Ermanna , Marastoni Damiano , Calabrese Massimiliano
Published: November 2022

The impact of disease-modifying therapies (DMTs) on the immune response to coronavirus disease-2019 (COVID-19) vaccines in persons with multiple sclerosis (pwMS) needs further elucidation. We investigated BNT162b2 mRNA COVID-19 vaccine effects concerning antibody seroconversion, inflammatory mediators’ level and immunophenotype assessment in pwMS treated with cladribine (c-pwMS, n = 29), fingolimod (f-pwMS, n = 15) and ocrelizumab (o-pwMS, n = 54). Anti-spike immunoglobulin (Ig)-G detection was performed by an enzyme immunoassay; molecular mediators (GrB, IFN-γ and TNF-α) were quantified using the ELLA platform, and immunophenotype was assessed by flow cytometry. ANCOVA, Student’s t-test and Pearson correlation analyses were applied. Only one o-pwMS showed a mild COVID-19 infection despite most o-pwMS lacking seroconversion and showing lower anti-spike IgG titers than c-pwMS and f-pwMS. No significant difference in cytokine production and lymphocyte count was observed in c-pwMS and f-pwMS. In contrast, in o-pwMS, a significant increase in GrB levels was detected after vaccination. Considering non-seroconverted o-pwMS, a significant increase in GrB serum levels and CD4+ T lymphocyte count was found after vaccination, and a negative correlation was observed between anti-spike IgG production and CD4+ T cells count. Differences in inflammatory mediators’ production after BNT162b2 vaccination in o-pwMS, specifically in those lacking anti-spike IgG, suggest a protective cellular immune response.
Novel Mucoadhesive Wafers for Treating Local Vaginal Infections
Authors: Alzainy Ahmed , Boateng Joshua
Published: November 2022

Current vaginal formulations, such as gels and pessaries, have limitations, including poor retention. Therefore, the use of mucoadhesive formulations that adhere to the vaginal wall would allow prolonged retention and controlled drug release while reducing the required dose and the potential toxicity associated with high drug loading. The aim of the current research was to develop, characterize, and optimize freeze-dried wafers loaded with metronidazole (MTz) to treat vaginal bacterial infections. Blank (BLK) composite wafers comprising carrageenan (CARR) and sodium alginate (SA) were initially formulated; however, due to poor physico-chemical properties, Carbopol (CARB), hydroxypropylmethylcellulose (HPMC), and polyethylene glycol 200 (PEG) were included. The MTz-loaded formulations were obtained by loading optimized composite CARB:CARR- or CARB:SA-based gels (modified with HPMC and/or PEG) with 0.75% of MTz prior to freeze-drying. The physico-chemical properties were investigated using texture analysis (resistance to compressive deformation and adhesion), scanning electron microscopy (SEM), X-ray diffractometry (XRD), and attenuated total reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy. Functional properties were investigated by examining the swelling, porosity, drug release, and in vitro antimicrobial activity using E. coli as a model infection-causative agent. The results showed that HPMC and PEG generally improved the wafer’s appearance, with smoother surfaces for easy insertion. From the physico-chemical characterization studies, only two composite wafers prepared from 8% CARB:SA 1:4 and 8% CARB:SA 1:9 gels were deemed optimal and loaded with MTz. Both formulations showed sustained drug release and achieved almost 100% cumulative release within 72 h in simulated vaginal fluid. The data obtained from the drug dissolution (release) experiments were fitted to various mathematical equations and showed the highest correlation coefficient with the Higuchi equation, suggesting a drug release based on diffusion from a swollen matrix; this was confirmed by the Korsmeyer–Peppas equation. The released MTz inhibited the growth of the E. coli used as a model bacterial organism.