bluuebunny/crossref_metadata_2025 huggingface dataset:
Strategies to Reduce Radiation Stress in Open-Field Ginger and Turmeric Production
Authors: Retana-Cordero Marlon , Flores Sofia , Freyre Rosanna , Gómez Celina
Published: August 2022

Excess solar radiation can negatively affect growth and rhizome yield of ginger (Zingiber officinale) and turmeric (Curcuma longa) plants. Thus, the objective of this study was to evaluate the effect of 60% shade nets (Experiment 1) as well as white and red kaolin sprays during two production stages (early establishment vs. entire cycle) (Experiment 2) on field-grown ginger and turmeric plants. In Experiment 1, plants were propagated from seed rhizomes (R) or second-generation rhizomes from tissue-cultured plants (2GR), while only R were used in Experiment 2. There were no differences in rhizome yield in response to shade in Experiment 1, with mean values of 644 and 692 g in ginger and turmeric, respectively. Overall, 2GR ginger plants produced a higher rhizome yield (880 g) than R plants (425 g), but no yield differences were measured in turmeric. In Experiment 2, for both species and regardless of kaolin color, sprays applied during the entire cycle increased photosynthesis and stomatal conductance and reduced leaf temperature and transpiration compared to control. Rhizome yield was also up to 87% higher in ginger and 47% higher in turmeric plants sprayed with kaolin. Spraying plants with white kaolin during the early season establishment of these crops can be an effective strategy to reduce radiation stress for open-field production.
Study on Microbial Community Structure and Soil Nitrogen Accumulation in Greenhouse Vegetable Fields with Different Planting Years
Authors: Li Luzhen , Zhao Changsheng , Chen Qingfeng , Liu Ting , Li Lei , Liu Xuzhen , Wang Xiaokai
Published: August 2022

Soil microbial communities are an important part of the soil ecosystem in greenhouse vegetable fields, where ammonia-oxidising microorganisms play a key role in nitrogen conversion. The health and stability of the ecological environment of greenhouse vegetable fields are affected by the number of years of continuous cultivation. We used real-time PCR amplification and 16S rRNA gene sequencing to analyse the changes in soil microbial community structure and diversity in different planting years (0, 3, 9, and 13). The content of environmental factors increased with the increase of planting year; the NO3−-N content in the 0–20 cm soil layer showed a cumulative trend, peaking to 1290–1390 mg/kg in year 13. The abundance of operational taxonomic units (OTUs) in the microbial community gradually decreased, and the OTUs of 0–20 cm soil layer in year 13 decreased by 52.2% compared to year 0. The Shannon and Simpson indices indicated a substantial decrease in microbial diversity after year 9. The dominant phyla in the soil microbial community mainly included Firmicutes (23.6%), Actinobacteria (23.2%), Proteobacteria (17.6%), Crenarchaeota (83.4%), and Euryarchaeota (2.7%). Nitrosopumilus and Nitrososphaera in the ammonia-oxidising archaeal (AOA) community and Nitrolancea and Nitrospira in the ammonia-oxidising bacterial (AOB) community dominated the ammonia-oxidising microorganisms. With the increase in planting years in greenhouse vegetable fields, the structure of soil microbial community changed significantly, with soil biomass and diversity significantly decreasing in years 9 and 13. Reasonable fertilization and planting year would improve microbial activity and provide a basis for sustainable utilization and high-quality production in greenhouse vegetable fields.
Mapping of the Thermal Microenvironment for Dairy Cows in an Open Compost-Bedded Pack Barn System with Positive-Pressure Ventilation
Authors: Oliveira Carlos Eduardo Alves , Tinôco Ilda de Fátima Ferreira , Damasceno Flávio Alves , Oliveira Victor Crespo de , Ferraz Gabriel Araújo e Silva , Sousa Fernanda Campos de , Andrade Rafaella Resende , Barbari Matteo
Published: August 2022

The objective of this study was to evaluate and characterize the dependence and the spatial and temporal distribution of variables and indices of the thermal environment in an open compost-bedded pack barn system with positive-pressure ventilation (CBPPV) during the winter period. The study was conducted in a CBPPV system located in the Zona da Mata region, Minas Gerais, Brazil. The indoor environment was divided into a mesh composed of 55 equidistant points, where data on dry-bulb air temperature (tdb) and relative humidity (RH) were collected. The collected data were divided into four periods—dawn, morning, afternoon, and night—and mean values were obtained. To evaluate the thermal microenvironment, the temperature and humidity index (THI) and the specific enthalpy of air (h) were used. For spatial dependence analysis, geostatistical techniques were applied. Through the results, a strong spatial dependence was verified for all variables evaluated. Through THI and h maps, conditions of thermal comfort were found for dairy cattle. The highest values of tdb, THI, and h were recorded in the afternoon period in the northwest region of the facility (tdb = 23.2 °C, THI = 69.7, and h = 50.9 kJ∙kg of dry air−1).
Effect of Dietary 4-Phenylbuthyric Acid Supplementation on Acute Heat-Stress-Induced Hyperthermia in Broiler Chickens
Authors: Tokutake Yukako , Takanashi Ryo , Kikusato Motoi , Toyomizu Masaaki , Sato Kan
Published: August 2022

Hot, humid weather causes heat stress (HS) in broiler chickens, which can lead to high mortality. A recent study found that HS causes endoplasmic reticulum (ER) stress. However, the possible involvement of ER stress in HS-induced physiological alterations in broiler chickens is unclear. This study aimed to evaluate the effect of the dietary supplementation of 4-phenylbutyric acid (4-PBA), an alleviator of ER stress, in acute HS-exposed young broiler chickens. Twenty-eight 14-day-old male broiler chickens (ROSS 308) were divided into two groups and fed either a control diet or a diet containing 4-PBA (5.25 g per kg of diet feed) for 10 days. At 24 days old, each group of chickens was kept in thermoneutral (24 ± 0.5 °C) or acute HS (36 ± 0.5 °C) conditions for 2 h. The results showed that thermoneutral birds supplemented with 4-PBA exhibited no negative effects in terms of broiler body weight gain and tissue weight compared to non-supplemental birds. HS increased body temperature in both the control and 4-PBA groups, but the elevation was significantly lower in the 4-PBA group than in the control group. The plasma non-esterified fatty acid concentration was significantly increased by HS treatment in non-supplemental groups, while the increase was partially attenuated in the 4-PBA group. Moreover, 4-PBA prevented HS-induced gene elevation of the ER stress markers GRP78 and GRP94 in the skeletal muscle. These findings suggest that the 4-PBA effect may be specific to the skeletal muscle in HS-exposed birds and that 4-PBA supplementation attenuated HS-induced muscle ER stress, which could be associated with a supplementation of the body temperature elevation and lipolysis.
Cultural and Medicinal Use of Amphibians and Reptiles by Indigenous People in Punjab, Pakistan with Comments on Conservation Implications for Herpetofauna
Authors: Adil Saba , Altaf Muhammad , Hussain Tanveer , Umair Muhammad , Ni Jian , Abbasi Arshad Mehmood , Bussmann Rainer W. , Ashraf Sana
Published: August 2022

Amphibians and reptiles have interacted with humans for millennia. However, humans interact with amphibian and reptile species in different manners, which depend on their culture and traditions. This study was designed to better understand the interactions between amphibian and reptile species and their usage among the native peoples in the vicinity of the Jhelum and Chenab rivers, Pakistan. Information was collected through semi-structured interviews and questionnaires, and was analyzed by using different indices, including the frequency of citation, corrected fidelity level, fidelity level, relative importance level, and informant major ailment. Two amphibians and twenty-six reptile species were used in therapeutic medicine in the study area. Based on the cultural analysis, we found that Naja naja (black cobra) was highly cited across all cultural groups. A 100% Fidelity Level was calculated for the following species: Naja naja (eye infection), Varanus bengalensis (joint pain), Eurylepis taeniolatus (cataract), and Acanthodactylus cantoris (cancer). We found five endangered species in the study area, i.e., Aspideretes gangeticus, A. hurum, Chitra indica, Varanus flavescens, and Geoclemys hamiltonii, that were used to cure joint pain, muscle stretching and pain, backbone pain, paralysis, and psoriasis, respectively. Likewise, Lissemys punctata andersoni, a vulnerable species as labelled by the International Union for Conservation of Nature, was extensively used for the treatment of joint pain, body pain, paralysis, and arthritis in the study area. In terms of conservation, it is critical to protect the highly vulnerable and endangered species that are being used in therapeutic medicines. Our findings may be helpful for the conservation of amphibian and reptile species by helping to make an effective plan to prevent their extinction. The main threats to the diversity of amphibian and reptile species in the area are hunting, trading, and cultural use. These threats could potentially lead to the extinction of these species. Therefore, with the involvement of concerned authorities, e.g., local stakeholders, the Ministry of Climate Change, provincial wildlife departments, academia, and conservation managers, immediate conservation measures should be taken for the protection and sustainable utilization of medicinal species.
Regulation of a High-Iron Diet on Lipid Metabolism and Gut Microbiota in Mice
Authors: Xiong Qingqing , Zhao Jing , Tian Chenying , Ma Wan , Miao Linfeng , Liang Li , Zhang Kang , Du Huahua
Published: August 2022

Iron homeostasis disorder is associated with the imbalance of lipid metabolism, while the specific interaction remains unclear. In the present study, we investigated the effect of a high-iron diet on lipid metabolism in mice. The C57BL/6 mice were fed with a normal diet (WT) or a high-iron diet (WT + Fe) for 12 weeks. We found that mice in the WT + Fe group showed a significant decrease in body weight gain, body fat and lipid accumulation of liver when compared with mice in the WT group. Accordingly, serum total cholesterol and triglyceride levels were both reduced in mice with a high-iron diet. Moreover, mice in the WT + Fe group exhibited a significant decrease in expression of genes regulating adipogenesis and adipocyte differentiation, and a significant increase in expression of fat hydrolysis enzyme genes in both liver and adipose tissues, which was consistent with their dramatic reduction in adipocyte cell size. In addition, a high-iron diet decreased the relative abundance of beneficial bacteria (Akkermansia, Bifidobacterium and Lactobacillus) and increased the relative abundance of pathogenic bacteria (Romboutsia and Erysipelatoclostridium). Thus, our research revealed that a high-iron diet reduced lipid deposition by inhibiting adipogenesis and promoting lipolysis. Altered gut microbial composition induced by a high-iron diet may not play a critical role in regulating lipid metabolism, but might cause unwanted side effects such as intestinal inflammation and damaged villi morphology at the intestinal host–microbe interface. These findings provide new insights into the relationship among iron, lipid metabolism and gut microbiota.
Effects of Dietary Inclusion of Sericea Lespedeza Hay on Feed Intake, Digestion, Nutrient Utilization, Growth Performance, and Ruminal Fermentation and Methane Emission of Alpine Doelings and Katahdin Ewe Lambs
Authors: Wang Wei , Patra Amlan Kumar , Puchala Ryszard , Ribeiro Luana , Gipson Terry Allen , Goetsch Arthur Louis
Published: August 2022

Twenty-four Alpine doelings, initial 25.3 ± 0.55 kg body weight (BW) and 10.4 ± 0.11 mo of age, and 24 Katahdin ewe lambs, 28.3 ± 1.02 kg BW and 9.6 ± 0.04 mo of age, were used to determine effects of dietary inclusion of Sericea lespedeza (Lespedeza cuneata) hay on feed intake, digestion, growth performance, energy metabolism, and ruminal fermentation and methane emission. There were four periods, the first three 42 days in length and the fourth 47 days. Diets consumed ad libitum contained 75% coarsely ground hay with alfalfa (ALF), a 1:1 mixture of ALF and LES (ALF+LES), and LES (10.0% condensed tannins; CT). The intake of dry matter (DM) tended to be greater (p = 0.063) for Katahdin than for Alpine (4.14 vs. 3.84% BW; SEM = 0.110). The dry matter intake was similar among the diets (3.97, 4.10, and 3.89% BW for ALF, ALF+LES, and LES, respectively; SEM = 0.134). The digestion of organic matter (75.3, 69.3, and 65.5%; SEM = 0.86), neutral detergent fiber (61.7, 50.5, and 41.4%; SEM = 1.49), and nitrogen (78.8, 66.9, and 50.8% for ALF, ALF+LES, and LES, respectively; SEM = 0.92) decreased as the dietary concentration of lespedeza increased (p < 0.05). However, there was an interaction (p < 0.05) between the breed and diet in nitrogen digestion, with a greater value for goats vs. sheep with LES (54.4 vs. 47.3%; SEM = 1.30). The digested nitrogen intake decreased markedly with the increasing quantity of lespedeza (38.0, 27.5, and 15.7 g/day for ALF, ALF+LES, and LES, respectively; SEM = 1.26). The average daily gain was greater for Katahdin than for Alpine (p < 0.001; 180 vs. 88 g, SEM = 5.0) and ranked (p < 0.05) ALF > ALF+LES > LES (159, 132, and 111 g, respectively; SEM = 6.1). The ruminal methane emission differed (p < 0.05) between animal types in MJ/day (1.17 and 1.44), kJ/g DM intake (1.39 and 1.23), and kJ/g ADG (18.1 and 9.8 for Alpine and Katahdin, respectively). Regardless of the period and animal type, diet did not impact methane emission in MJ/day or relative to DM intake, BW, or ADG (p > 0.05). The digestible and metabolizable energy intakes, heat production, and retained energy were not affected by diet (p > 0.05). In conclusion, future research should consider the marked potential effect of CT of forages such as lespedeza on nitrogen digestion and associated effects on protein status and other conditions that may be impacted.
Rapid Oxford Nanopore Technologies MinION Sequencing Workflow for Campylobacter jejuni Identification in Broilers on Site—A Proof-of-Concept Study
Authors: Marin Clara , Marco-Jiménez Francisco , Martínez-Priego Llucia , De Marco-Romero Griselda , Soriano-Chirona Vicente , Lorenzo-Rebenaque Laura , D’Auria Giuseppe
Published: August 2022

Campylobacter is recognised as one of the most important foodborne bacteria, with a worldwide health and socioeconomic impact. This bacterium is one of the most important zoonotic players in poultry, where efficient and fast detection methods are required. Current official culture methods for Campylobacter enumeration in poultry usually include >44 h of culture and >72 h for identification, thus requiring at least five working shifts (ISO/TS 10272-2:2017). Here, we have assembled a portable sequencing kit composed of the Bento Lab and the MinION and developed a workflow for on-site farm use that is able to detect and report the presence of Campylobacter from caecal samples in less than five hours from sampling time, as well as the relationship of Campylobacter with other caecal microbes. Beyond that, our workflow may offer a cost-effective and practical method of microbiologically monitoring poultry at the farm. These results would demonstrate the possibility of carrying out rapid on-site screening to monitor the health status of the poultry farm/flock during the production chain.
Diverse Metabolites and Pharmacological Effects from the Basidiomycetes Inonotus hispidus
Authors: Wang Zhen-xin , Feng Xi-long , Liu Chengwei , Gao Jin-ming , Qi Jianzhao
Published: August 2022

Inonotus hispidus mushroom is a popular edible and medicinal mushroom with a long history of use. It is well known as a medicinal fungus with various health benefits for its significant anticancer and immunomodulatory activities. Over the last 60 years, secondary metabolites derived from I. hispidus and their biological activities have been discovered and investigated. Structurally, these compounds are mainly polyphenols and triterpenoids, which have anticancer, anti-inflammatory, antioxidant, antimicrobial, and enzyme inhibitor activities. Here, the secondary metabolites derived from I. hispidus and their activities were systematically and comprehensively classified and summarized, and the biosynthetic pathway of stylylpyrones was deduced and analyzed further. This review contributes to our understanding of I. hispidus and will help with research into natural product chemistry, pharmacology, and the biosynthesis of I. hispidus metabolites. According to this review, I. hispidus could be a promising source of bioactive compounds for health promotion and the development of functional foods.
“ACTIVE VALUES”: An Interdisciplinary Educational Programme to Promote Healthy Lifestyles and Encourage Education in Values—A Rationale and Protocol Study
Authors: Jiménez-Parra José Francisco , Belando-Pedreño Noelia , López-Fernández Jorge , García-Vélez Antonio Joaquín , Valero-Valenzuela Alfonso
Published: August 2022

Numerous investigations show the need to intervene with school children and young students in order to mitigate socio-educational difficulties such as social conflict, and public health problems such as sedentary lifestyles and childhood obesity. This study seeks to explain the rationale and protocol of an educational programme called “ACTIVE VALUES” as an intervention strategy for the reduction of sedentary lifestyles and the promotion of education in values in schools. The present research used a mixed methods approach with a quasi-experimental design of repeated measures (pre-test and post-test), with a non-randomised control group (CG) and an experimental group (EG). The sample was composed of approximately 250 students and 30 teachers from different autonomous communities in Spain, divided into EG and CG. The EG implemented a teaching methodology based on the incorporation of Active Breaks (AB) into the structure of the Teaching Personal and Social Responsibility (TPSR) model, during one academic year, while the CG used conventional teaching based on the direct instruction teaching technique. A specific two-stage professional development procedure was followed: (1) initial training and (2) continuing professional development (CPD). The fidelity of the programme was checked by observational analysis of the sessions which were analysed by two observers with expertise in educational research and active methodologies. Currently, “ACTIVE VALUES” is the first study that examines the effectiveness of an educational programme that integrates into the teaching methodology, elements that foster education in values and promote healthy lifestyle habits through physical-sports activity within the classroom.
Nutritional Composition and Biological Properties of Sixteen Edible Mushroom Species
Authors: Dimopoulou Maria , Kolonas Alexandros , Mourtakos Stamatis , Androutsos Odysseas , Gortzi Olga
Published: August 2022

Mushrooms are considered to be functional foods with high nutritional, culinary, and pharmacological values, and there has been an increase in their consumption, both through the diet and in the form of dietary supplements. The present study aimed to briefly review the nutritional composition and biological properties of sixteen mushroom species, as well as to compare the mushrooms’ proximate composition to the analyses conducted at the University of Thessaly, Greece, in cooperation with the Natural History Museum of Meteora and Mushroom Museum. The macronutrient profile of each mushroom was analyzed according to the methods described in the Association of Official Analytical Chemists International, at the School of Agricultural Sciences of the University of Thessaly. The protein content of the mushrooms was found to range between 13.8 g/100 g and 38.5 g/100 g, carbohydrate content ranged between 32 g/100 g and 61.4 g/100 g, and fat content ranged between 0.4 g/100 g and 5.9 g/100 g. Additionally, a serving of 100 g of most species of mushrooms covers 15 to 30% of the daily recommendation of vitamins and trace elements. Based on their compositions, mushrooms were shown to constitute excellent food sources from a nutritional point of view, containing high amounts of dietary fiber and protein, low fat, and reasonable sources of phosphorus, although they were shown to be poor in vitamin C.
Three-Dimensional Formation Control for Robot Swarms
Authors: Kim Jonghoek
Published: August 2022

This article addresses a distributed 3D algorithm for coordinating a swarm of autonomous robots (ARs) to spatially self-aggregate into an arbitrary shape based on only local interactions. Each AR has local proximity sensors for measuring the relative coordinates of its nearby AR. We assume that only a single AR, called the leader, can localize itself in global coordinate systems, while accessing the arbitrary user-specified 3D shape. We further assume that the leader has a communication ability superior to all other ARs so that the leader can directly send a communication signal to any other AR inside the shape. Our aim is to make the ARs maneuver while maintaining a user-specified 3D formation such that the network connection of all ARs is maintained during the maneuver. Our approach results in a 3D formation shape and does not need the global localization of an AR, except for the leader. To the best of our knowledge, our study is novel in the construction of a 3D formation for covering an arbitrary shape such that network connection is maintained while ARs maneuver based on local communication. We further show that the proposed control yields reliable accuracy against significant AR failures and movement error. Utilizing MATLAB simulations, we demonstrate the outperformance of the proposed formation controls.
WPFD: Active User-Side Detection of Evil Twins
Authors: Hsu Fu-Hau , Wu Min-Hao , Hwang Yan-Ling , Lee Chia-Hao , Wang Chuan-Sheng , Chang Ting-Cheng
Published: August 2022

The bothersome evil twin problem has an active user-side remedy in the form of the Wireless Packet Forwarding Detector (WPFD). The evil twin issue can lead to further security problems, including man-in-the-middle (MITM) attacks. Open public Wi-Fi connections have provided potential answers to this issue, although they often need more data that people either cannot get or are too pricey for regular users. The solution that we created does not require these standards. It allows users’ notebooks to be used to check for evil twins. We have succeeded in developing a user-side detection system that can successfully identify the presence of an evil twin. The packet forwarding behavior generated by the evil twin and the TCP/IP (Transmission Control Protocol/Internet Protocol) protocol are both used by the WPFD. It can identify evil twins without a hitch when we utilize accessible Wi-Fi settings in public spaces or IoT smart homes with unencrypted WLANs (Wireless Local Area Network). However, neither additional data nor a wireless network administrator’s assistance is needed. We compare our work to various publications on popular Rogue Access Points (APs) or IoT (Internet of Things) smart homes. The WPFD does not require any extra setup to install on the host of any end user. According to experimental findings, the WPFD true positive and true negative rates are 100% even when Received Signal Strength Index (RSSI) is 45%.
Assessment of Spatio-Temporal Kinematic Phenomena Observed along the Boundary of Triaxial Sand Specimens
Authors: Zhu Yichuan , Medina-Cetina Zenon
Published: August 2022

This paper follows up on a reference paper that inspired MDPI’s topic “Stochastic Geomechanics: From Experimentation to Forward Modeling”, in which global and local deformation effects on sand specimens were fully described from high-resolution boundary displacement fields. This paper is supported by that study’s experimental database, which is open to the scientific community for further study. This paper focuses on the analysis of this experimental study to investigate strain localization effects on a subset of tests included in this database. Strain localization is defined here as associated with the non-homogeneous deformation process occurring in elastoplastic materials, including sands. Many experimental and numerical studies have been conducted during the last two decades to explore the characteristics of localization effects on sand, and to determine how these contribute to the failure mechanisms of specific sands. Under a triaxial compression condition, localization effects have been studied mainly with regard to particle kinematics and translational strain of the specimen’s displacement fields. However, to the best of the authors’ knowledge, there has been no 3D experimental kinematic analysis performed on sands to study the localization phenomena that can directly relate the impact of a specimen’s initial and boundary conditions to a failure mechanism during a triaxial test. In this paper, we introduce a full set of 3D kinematic operators under cylindrical coordinates to assess the boundary localization effects of deforming sand specimens under triaxial loading conditions. Furthermore, a set of experiments were carried out under varying experimental conditions to study the impact of variability in these localization effects. Results show that patterns of kinematic effects are quantifiable and can be used to assess likely failure-influencing factors, such as confining pressure, initial density, sample geometry, and sample heterogeneity, in the development of specific failure mechanisms. Spatio-temporal interdependencies between localization effects, such as the interactions between shear, expansion, and compaction bands observed during the specimen’s shearing process, were also studied. We therefore hypothesize that the proposed framework will serve as the basis for quantifying the uncertainty associated with the development of localization effects over the boundary of sand-deforming specimens.
Evolution Law of Three-Dimensional Non-Uniform Temperature Field of Tunnel Construction Using Local Horizontal Freezing Technique
Authors: Pang Changqiang , Cai Haibing , Hong Rongbao , Li Mengkai , Yang Zhe
Published: August 2022

The formation quality of a frozen wall is one of the prerequisites for tunnel excavation using artificial ground freezing techniques. However, the non-uniformity of temperature distribution along the length direction of the freezing pipe is often ignored in the actual freezing engineering, which leads to a thin frozen wall at a local position that does not meet the design requirements. Therefore, exploring the evolution law of three-dimensional non-uniform freezing temperature fields is necessary. In this paper, a tunnel horizontal freezing model test system was established based on the similarity criterion of hydro–heat coupling, and the temperatures at three sections were tested using thermocouple temperature sensors. The results show that the temperature drop curves of measurement points suffer from three periods: steep drop, slow drop and tending to be stable. The temperature curves on the main and vice planes of the frozen wall all present a “V” type; specifically, the temperature on the axis plane is the lowest, while the temperature away from the axis plane is higher, and the temperature gradient outside the axis plane is greater than that inside. The frozen wall develops from frozen soil columns to a sector ring, and the average thickness of the frozen wall at three sections is 50.6, 40.7 and 75.1 mm after freezing for 60 min, respectively, which shows an obvious non-uniformity. The temperature distribution along the length of the freezing pipe is T = −0.000045z2 + 0.0205z − 13.5125. The freezing temperature contours calculated by ABAQUS are basically consistent with those calculated by the model test after calling the temperature function of the freezing pipe wall.
Deep Active Learning for Computer Vision Tasks: Methodologies, Applications, and Challenges
Authors: Wu Mingfei , Li Chen , Yao Zehuan
Published: August 2022

Active learning is a label-efficient machine learning method that actively selects the most valuable unlabeled samples to annotate. Active learning focuses on achieving the best possible performance while using as few, high-quality sample annotations as possible. Recently, active learning achieved promotion combined with deep learning-based methods, which are named deep active learning methods in this paper. Deep active learning plays a crucial role in computer vision tasks, especially in label-insensitive scenarios, such as hard-to-label tasks (medical images analysis) and time-consuming tasks (autonomous driving). However, deep active learning still has some challenges, such as unstable performance and dirty data, which are future research trends. Compared with other reviews on deep active learning, our work introduced the deep active learning from computer vision-related methodologies and corresponding applications. The expected audience of this vision-friendly survey are researchers who are working in computer vision but willing to utilize deep active learning methods to solve vision problems. Specifically, this review systematically focuses on the details of methods, applications, and challenges in vision tasks, and we also introduce the classic theories, strategies, and scenarios of active learning in brief.
Multi-Objective Optimization for Outer Rotor Low-Speed Permanent Magnet Motor
Authors: Du Guanghui , Hu Chengshuai , Zhou Qixun , Gao Wentao , Zhang Qizheng
Published: August 2022

For outer rotor low-speed permanent magnet motors (LSPMMs), in the optimization design process, not only is the electromagnetic performance optimized, but the influence of the thermal load and copper loss on the temperature in the electromagnetic parameters should also be considered. However, these optimized designs that comprehensively consider electromagnetic performance and temperature characteristics are rare in the existing literature. Therefore, this paper focuses on a multi-objective optimization process considering efficiency, thermal load and copper loss. Firstly, according to the initial design, the influence of the design parameters on the efficiency and thermal load is analyzed, and the range of optimization parameters is determined. Next, the response surface is built, the response-surface analysis of electromagnetic performance is performed, and the parameter sensitivity is calculated. Then, the multi-objective optimization design is carried out by comprehensively considering the electromagnetic performance and temperature. Finally, compared with the initial scheme, the optimized scheme improves the efficiency and reduces the temperature, and the optimized scheme is verified by experimentation on a 22 kW, 56 rpm LSPMM prototype, which can provide a reference for the multi-objective optimization of LSPMMs by comprehensively considering the electromagnetic performance and temperature.
Motion-Induced Phase Error Compensation Using Three-Stream Neural Networks
Authors: Li Yueyang , Guo Wenbo , Shen Junfei , Wu Zhoujie , Zhang Qican
Published: August 2022

Phase-shifting profilometry (PSP) has been widely used in the measurement of dynamic scenes. However, the object motion will cause a periodical motion-induced error in the phase map, and there is still a challenge to eliminate it. In this paper, we propose a method based on three-stream neural networks to reduce the motion-induced error, while a general dataset establishment method for dynamic scenes is presented to complete three-dimensional (3D) shape measurement in a virtual fringe projection system. The numerous automatically generated data with various motion types is employed to optimize models. Three-step phase-shift fringe patterns captured along a time axis are divided into three groups and processed by trained three-stream neural networks to produce an accurate phase map. The actual experiment’s results demonstrate that the proposed method can significantly perform motion-induced error compensation and achieve about 90% improvement compared with the traditional three-step phase-shifting algorithm. Benefiting from the robust learning-based technique and convenient digital simulation, our method does not require empirical parameters or complex data collection, which are promising for high-speed 3D measurement.
Analysis of Errors and Winners in Men’s and Women’s Professional Padel
Authors: Escudero-Tena Adrián , Muñoz Diego , Sánchez-Alcaraz Bernardino Javier , García-Rubio Javier , Ibáñez Sergio J.
Published: August 2022

The objective was to analyze the effectiveness in men’s and women’s professional padel of errors and winners depending on the type of shot and the importance of the situation during each game. In addition, differences between men and women were identified. The sample was made up of 2759 points corresponding to the games that finished with a golden point from matches played in the 2021 season of the World Padel Tour circuit. The results show men and women make more errors (men: 58.7%; women: 63.2%) than winners (men: 41.3%; women: 36.8%), and this difference increases as the importance of the points increases in men’s padel; however, the opposite happens in women’s padel. Trays and smashes are the most characteristic last shots in men’s and women’s padel (hits with which more winners are achieved), followed by back wall shots (shots where more errors are made) and then drive and backhand volleys. In men’s padel there are more winning shots and fewer errors than in women’s padel, except in the golden points, where men make more errors than women. These considerations are of great importance, as they help the players to know the most effective way to finish points according to the situation of the game.
Optimizing the Layout of Run-of-River Powerplants Using Cubic Hermite Splines and Genetic Algorithms
Authors: Córdoba Alejandro Tapia , Gata Pablo Millán , Reina Daniel Gutiérrez
Published: August 2022

Despite the clear advantages of mini hydropower technology to provide energy access in remote areas of developing countries, the lack of resources and technical training in these contexts usually lead to suboptimal installations that do not exploit the full potential of the environment. To address this drawback, the present work proposes a novel method to optimize the design of mini-hydropower plants with a robust and efficient formulation. The approach does not involve typical 2D simplifications of the terrain penstock layout. On the contrary, the problem is formulated considering arbitrary three-dimensional terrain profiles and realistic penstock layouts taking into account the bending effect. To this end, the plant layout is modeled on a continuous basis through the cubic Hermite interpolation of a set of key points, and the optimization problem is addressed using a genetic algorithm with tailored generation, mutation and crossover operators, especially designed to improve both the exploration and intensification. The approach is successfully applied to a real-case scenario with real topographic data, demonstrating its capability of providing optimal solutions while dealing with arbitrary terrain topography. Finally, a comparison with a previous discrete approach demonstrated that this algorithm can lead to a noticeable cost reduction for the problem studied.
Implementing an Ensemble Learning Model with Feature Selection to Predict Mortality among Patients Who Underwent Three-Vessel Percutaneous Coronary Intervention
Authors: Huang Yen-Chun , Chen Kuan-Yu , Li Shao-Jung , Liu Chih-Kuang , Lin Yang-Chao , Chen Mingchih
Published: August 2022

Coronary artery disease (CAD) is a common major disease. Revascularization with percutaneous coronary intervention (PCI) or coronary artery bypass graft (CABG) could relieve symptoms and myocardial ischemia. As the treatment improves and evolves, the number of aged patients with complex diseases and multiple comorbidities gradually increases. Furthermore, in patients with multivessel disease, 3-vessel PCI may lead to a higher risk of complications during the procedure, leading to further ischemia and higher long-term mortality than PCI for one vessel or two vessels. Nevertheless, the risk factors for accurately predicting patient mortality after 3-vessel PCI are unclear. Thus, a new risk prediction model for primary PCI (PPCI) patients’ needs to be established to help physicians and patients make decisions more quickly and accurately. This research aimed to construct a prediction model and find which risk factors will affect mortality in 3-vessel PPCI patients. This nationwide population-based cohort study crossed multiple hospitals and selected 3-vessel PPCI patients from January 2007 to December 2009. Then five different single machine learning methods were applied to select significant predictors and implement ensemble models to predict the mortality rate. Of the 2337 patients who underwent 3-vessel PPCI, a total of 1188 (50.83%) survived and 1149 (49.17%) died. Age, congestive heart failure (CHF), and chronic renal failure (CRF) are mortality’s most important variables. When CRF patients accept 3-vessel PPCI at ages between 68–75, they will possibly have a 94% death rate; Furthermore, this study used the top 15 variables averaged by each machine learning method to make a prediction model, and the ensemble learning model can accurately predict the long-term survival of 3-vessel PPCI patients, the accurate predictions rate achieved in 88.7%. Prediction models can provide helpful information for the clinical physician and enhance clinical decision-making. Furthermore, it can help physicians quickly identify the risk features, design clinical trials, and allocate hospital resources effectively.
Research on the Reliability of Bridge Structure Construction Process System Based on Copula Theory
Authors: Li Qingfu , Zhang Tianjing
Published: August 2022

Various random factors in the bridge construction process directly affect the safety of the bridge life cycle. The existing theories on the reliability of bridge structure mainly focus on the reliability of components and the reliability of the bridge structure system in the completion and operation stages, while the research on the reliability of the structure system in the construction stage is relatively lacking. Therefore, this paper proposed using the Copula function to calculate the reliability index of the bridge structure construction process system. The basic theory of the Copula function was introduced in detail, and the formula was improved according to the actual situation of bridge construction. Finally, the sensitivity analysis of bridge system reliability was carried out. The research results showed that the method proposed in this paper based on Copula theory to calculate the reliability index of the bridge structure construction process system has strong applicability, simple calculation, and can be used in conjunction with the “interval estimation method”, which is suitable for large and complex bridge structural engineering. At the same time, the conclusion that the influence of failure mode correlation on structural reliability should not be ignored in the actual engineering construction process is confirmed.
A Secure Architecture to Protect the Network from Replay Attacks during Client-to-Client Data Transmission
Authors: Nadeem Muhammad , Arshad Ali , Riaz Saman , Zahra Syeda Wajiha , Dutta Ashit Kumar , Almotairi Sultan
Published: August 2022

Cloud computing is an online data storage system that can be easily accessed anywhere. Various algorithms and techniques have been developed to secure cloud data, which, if used correctly, can detect cloud attacks. These algorithms can only detect cloud data attacks and cannot prevent such attacks. If an attacker gains access to the data, he or she can tamper with the data in any way that could lead to misuse of the data. This paper will design a secure architecture for securing data with various algorithm implementations on the architecture so that cloud data can be saved from replay attacks. First, a text file will be taken, the text file will be encrypted using the encryption mechanism, and this file will be transmitted on the SaaS cloud server platform. Whenever a file is uploaded to a cloud server, it will be broadcast across the network, after which any user can access it, whether it is valid or invalid. Whenever a file is downloaded from a cloud server, it will be necessary to decrypt it to access it. If the file is successfully decrypted, then the file will be verified. A verification mechanism will be used to verify the data, which will be used to check whether a replay attack has been made on the data or not. If the data authentication is successful, this data will be called authentic data. The novelty of this paper is that an algorithm has been developed in this paper to prevent replay attacks so that if the data is retransmitted with slight changes, then the authenticity and inauthenticity of the data will be identified. Recent papers will be compared with the proposed paper in the conclusion, and it will be pointed out how much better the current technique is than the previous one.
Information on Drivers’ Sex Improves EEG-Based Drowsiness Detection Model
Authors: Stancin Igor , Zeba Mirta Zelenika , Friganovic Kresimir , Cifrek Mario , Jovic Alan
Published: August 2022

Objective detection of a driver’s drowsiness is important for improving driving safety, and the most prominent indicator of drowsiness is changes in electroencephalographic (EEG) activity. Despite extensively documented behavioral differences between male and female drivers, previous studies have not differentiated drowsiness detection models based on drivers’ sex. Therefore, the overall aim of this study is to demonstrate that drowsiness detection can be improved with the use of drivers’ sex information, either as a feature or as separate sex-dependent datasets. Additionally, we aim to provide a reliable EEG-based sex classification model. The used dataset consists of 17 male and 17 female drivers which were evaluated during alert and drowsy sessions. Frequency-domain and recurrence quantification analysis EEG features were used. Four classification algorithms and three feature selection methods were applied to build the models. The accuracy of drowsiness detection based on sex-dependent datasets is 84% for male drivers and 88% for female drivers, which is 3% and 7% better, respectively, than the classification without information about driver’s sex (81%). The model for sex classification based on EEG achieved high accuracy: 97% correctly identified participants in alert sessions and 96% in drowsy sessions. All participants were correctly classified after the application of majority voting on five algorithm runs. The results suggest that sex-dependent datasets improve the accuracy of drowsiness models, which may be relevant to a variety of drowsiness detection systems currently being developed in the field.
Towards Design and Development of Security Assessment Framework for Internet of Medical Things
Authors: Alzahrani Fahad A. , Ahmad Masood , Ansari Md Tarique Jamal
Published: August 2022

The majority of medical equipment in use today does not have built-in security features. As a result, whether linked to a hospital system or the cloud, these devices’ built-in weaknesses make them vulnerable to a variety of cyberattacks. In hospitals and clinics, hackers can breach equipment, manipulate data, and disrupt facilities, putting patients’ health as well as their lives in jeopardy. A professional can manage cybersecurity threats by lowering the attack surface of the system. Security analysis, whether as a means to detect possible vulnerabilities that can be exploited by attackers or as a means to prevent cyberattacks, plays an important role in risk mitigation. In addition, throughout the pre-market and post-market phases, security checks are required. This study presents a paradigm for incorporating security check concepts into medical device design and development and healthcare big data security. The security of devices and healthcare data is tested by the integrated fuzzy AHP-TOPSIS method. After the security check of devices, with the parameters security-checked for data, the algorithm is designed and implemented. As a result, the appropriate customized security controls are prompted in order to impede the attack.
Modelling Hourly Particulate Matter (PM10) Concentrations at High Spatial Resolution in Germany Using Land Use Regression and Open Data
Authors: Wallek Stefan , Langner Marcel , Schubert Sebastian , Schneider Christoph
Published: August 2022

Air pollution is a major health risk factor worldwide. Regular short- and long-time exposures to ambient particulate matter (PM) promote various diseases and can lead to premature death. Therefore, in Germany, air quality is assessed continuously at approximately 400 measurement sites. However, knowledge about this intermediate distribution is either unknown or lacks a high spatial–temporal resolution to accurately determine exposure since commonly used chemical transport models are resource intensive. In this study, we present a method that can provide information about the ambient PM concentration for all of Germany at high spatial (100 m × 100 m) and hourly resolutions based on freely available data. To do so we adopted and optimised a method that combined land use regression modelling with a geostatistical interpolation technique using ordinary kriging. The land use regression model was set up based on CORINE (Coordination of Information on the Environment) land cover data and the Germany National Emission Inventory. To test the model’s performance under different conditions, four distinct data sets were used. (1) From a total of 8760 (365 × 24) available h, 1500 were randomly selected. From those, the hourly mean concentrations at all stations (ca. 400) were used to run the model (n = 566,326). The leave-one-out cross-validation resulted in a mean absolute error (MAE) of 7.68μgm−3 and a root mean square error (RMSE) of 11.20μgm−3. (2) For a more detailed analysis of how the model performs when an above-average number of high values are modelled, we selected all hourly means from February 2011 (n = 256,606). In February, measured concentrations were much higher than in any other month, leading to a slightly higher MAE of 9.77μgm−3 and RMSE of 14.36μgm−3, respectively. (3) To enable better comparability with other studies, the annual mean concentration (n = 413) was modelled with a MAE of 4.82μgm−3 and a RMSE of 6.08μgm−3. (4) To verify the model’s capability of predicting the exceedance of the daily mean limit value, daily means were modelled for all days in February (n = 10,845). The exceedances of the daily mean limit value of 50 μgm−3 were predicted correctly in 88.67% of all cases. We show that modelling ambient PM concentrations can be performed at a high spatial–temporal resolution for large areas based on open data, land use regression modelling, and kriging, with overall convincing results. This approach offers new possibilities in the fields of exposure assessment, city planning, and governance since it allows more accurate views of ambient PM concentrations at the spatial–temporal resolution required for such assessments.