bluuebunny/crossref_metadata_2025 huggingface dataset:
Optimized Convolutional Neural Network Recognition for Athletes’ Pneumonia Image Based on Attention Mechanism
Authors: Zhang Hui , Ma Ruipu , Zhao Yingao , Zhang Qianqian , Sun Quandang , Ma Yuanyuan
Published: October 2022

After high-intensity exercise, athletes have a greatly increased possibility of pneumonia infection due to the immune function of athletes decreasing. Diseases caused by pulmonary bacterial or viral infections can have serious consequences on the health of athletes in a short period of time, and can even lead to their early retirement. Therefore, early diagnosis is the key to athletes’ early recovery from pneumonia. Existing identification methods rely too much on professional medical knowledge, which leads to inefficient diagnosis due to the shortage of medical staff. To solve this problem, this paper presents an optimized convolutional neural network recognition method based on an attention mechanism after image enhancement. For the collected images of athlete pneumonia, we first use contrast boost to adjust the coefficient distribution. Then, the edge coefficient is extracted and enhanced to highlight the edge information, and enhanced images of the athlete lungs are obtained by using the inverse curvelet transformation. Finally, an optimized convolutional neural network with an attention mechanism is used to identify the athlete lung images. A series of experimental results show that, compared with the typical image recognition methods based on DecisionTree and RandomForest, the proposed method has higher recognition accuracy for lung images.
The Impact of a Digital Escape Room Focused On HTML and Computer Networks on Vocational High School Students
Authors: Huraj Ladislav , Hrmo Roman , Sejutová Hudáková Marianna
Published: October 2022

Today, students live in a world surrounded by technology and traditional education methods are no longer very attractive to them. Applying the concept of a digital educational escape room to teaching can help increase students’ interest in the subject. In an escape room, the players search for clues, complete tasks, and solve polymorphic puzzles, working together to escape the room within a certain time limit. This article presents the use of a digital escape room on third-year students in the field of computer network mechanics at a secondary vocational school. The aim of this study was to determine the effects of implementing an escape room focused on HTML and computer networks on third-year computer network mechanics students and to assess the students’ levels of perception of the game. Although the experiment did not confirm an increase in students’ cognitive abilities, the quantitative analysis confirms a significant increase in the motivation, engagement, and satisfaction of students in secondary vocational schools focusing on technical vocational subjects. Qualitative analysis provides a better understanding of these results and supports the conclusion that using a digital educational escape room is enjoyable for students, and leads to problem-solving skills and teamwork.
Keeping the Parents outside the School Gate—A Critical Review
Authors: Kent Carmel , du Boulay Benedict , Cukurova Mutlu
Published: October 2022

The existing evidence shows that parental engagement is one of the most effective educational interventions. Most parents, carers, and teachers are aware of that and wish to engage with their children’s education. However, most parents are still only peripherally involved through parent–teacher evenings, school activities, or by helping their children keep up with their homework. In this review paper, we summarize the evidence about the impact of parental engagement, as opposed to involvement, on the learning of children. Via that, we critically look at the design choice of most western mainstream public education systems to distance parents from their children’s education, which, as the review results indicate, can be detrimental to children’s learning. Based on these results, we reframe parental engagement in the light of two global shifts: (1) the implications of the school closures during the COVID-19 pandemic for the role of parents in their children’s learning; and (2) the increased use of educational technologies for learning, and specifically, the rise of artificial intelligence (AI) technologies. We conclude by calling for a renewed conversation about parents’ and families’ roles in their children’s learning and their interface with schools and teachers.
Experimental Validation of an Active Fault Tolerant Control Strategy Applied to a Proton Exchange Membrane Fuel Cell
Authors: Dijoux Etienne , Steiner Nadia Yousfi , Benne Michel , Péra Marie-Cécile , Grondin-Perez Brigitte
Published: October 2022

Reliability of proton exchange membrane fuel cells (PEMFCs) is a major issue for large industrialization and commercialization. Indeed, performance can be degraded due to abnormal operating conditions, namely, faults, which lead either to a transient decay of the fuel cell performance or to permanent damage that cannot be recovered. The literature shows that long-time exposure to faults leads to fuel cell degradation. Therefore, it is necessary to use tools that can not only diagnose these faulty conditions, but also modify the fuel cell operations to recover a healthy operating point. For that purpose, one approach is the Active Fault Tolerant Control (AFTC) strategy which is composed of three functions. First, a diagnosis part allows fault detection and identification. Then a decision part, which is an algorithm aiming at finding a new operating point that mitigates the occurring fault. Finally, a control part applies the mitigation strategy established by the decision algorithm. The present work focuses on the decision part. and aims to bring a new contribution to PEMFCs reliability improvement and address water management issues, namely, the cell flooding and membrane drying out with the developed AFTC tool. The strategy is tested and validated on a single PEMFC cell and results are presented, analyzed, and discussed.
Forensic Analysis of IoT File Systems for Linux-Compatible Platforms
Authors: Lee Jino , Shon Taeshik
Published: October 2022

Due to recent developments in IT technology, various IoT devices have been developed for use in various environments, such as card smart TVs, and smartphones Communication between IoT devices has become possible. Various IoT devices are found in homes and in daily life, and IoT technologies are being combined with vehicles, power, and wearables, amongst others. Although the usage of IoT devices has increased, the level of security technology applied to IoT devices is still insufficient. There is sensitive information stored inside IoT devices, such as personal information and usage history, so if security accidents happen, such as data leakage, it can be very damaging for users. Since research on data storage and acquisition in IoT devices is very important, in this paper we conducted a security analysis, from a forensic perspective, on IoT platform file systems used in various environments. The analysis was conducted on two mechanical platforms: Tizen (VDFS) and Linux (JFFS2 and UBIFS). Through file system metadata analysis, file system type, size, list of files and folders, deleted file information were obtained so that we could analyze file system structure with the obtained information. We also used the obtained information to check the recoverability of deleted data to investigate the recovery plan. In this study, we explain the characteristics of platforms used in various environments, and the characteristics of data stored in each platform. By analyzing the security issues of data stored during platform communications, we aimed to help in solving the problems affecting devices. In addition, we explain the analysis method for file system forensics so that it can be referred to in other platform forensics.
A Systematic Literature Review of Enabling IoT in Healthcare: Motivations, Challenges, and Recommendations
Authors: Mohamad Jawad Huda Hussein , Bin Hassan Zainuddin , Zaidan Bilal Bahaa , Mohammed Jawad Farah Hussein , Mohamed Jawad Duha Husein , Alredany Wajdi Hamza Dawod
Published: October 2022

Internet of things (IoT) has revolutionized how we utilize technology over the past decade. IoT’s rapid growth affects several fields, including the healthcare sector. As a result, the concept of smart healthcare or electronic healthcare (e-healthcare) has emerged. Smart healthcare promises to enhance people’s lives and wellbeing by monitoring them, offering an efficient connection, improving mobility, gathering medical data, and decreasing hospital and patient costs. IoT in healthcare is still one of the hot and trendy topics that needs in-depth investigation. No recent review has been conducted to elucidate the extent of research in the area, features of published papers, motives, and challenges in enabling IoT in healthcare systems. This study presents a comprehensive systematic review of the screened articles published between 2015 and 2022 pertaining to enabling IoT in healthcare services and applications. A total of 106 papers fulfilled the final inclusion criteria and were analyzed using systematic literature review (SLR). Two procedures were used to review the final articles: First, publications are examined in terms of study designs, publishing journals, and topics/study objectives. In the second approach, motives, challenges, and recommendations for enabling IoT in healthcare systems are explored. This article summarizes published studies on IoT in healthcare systems and its usage in smart healthcare service delivery. Based on the reviewed studies, recommendations for future research to enable the effective application of IoT in healthcare and service delivery are proposed.
Spatial-Temporal Value-of-Information Maximization for Mobile Crowdsensing in Wireless Sensor Networks
Authors: Luo Xiaoling , Chen Che , Zhang Wenjie , Zeng Chunnian , Li Chengtao , Xu Jing
Published: October 2022

Mobile crowdsensing is considered as a promising technology to exploit the computing and sensing capabilities of the decentralized wireless sensor nodes. Typically, the quality of information obtained from crowdsensing is largely affected by various factors, such as the diverse requirements of crowdsensing tasks, the varying quality of information across different crowd workers, and the dynamic changes of channels conditions and the sensing environment. In this paper, considering the dynamics’ of the crowd workers, we focus on a spatial-temporal crowdsensing model and aim to maximize the value of information at the point of interest, by optimizing the recruiting range and time duration for the crowd workers. In particular, the crowdsensing system includes a mobile access point (MAP) and a set of wireless sensor nodes. As the information requester, the MAP can broadcast its crowdsensing task and then estimate the value of information by collecting the responses from the sensing nodes. Each sensing node in the crowdsensing task will receive a payment from the MAP. We aim to maximize the utility of the information requester by optimizing the recruiting range and waiting time for the sensing nodes. We firstly define a set of value metrics to characterize the MAP’s value of information. The optimal recruiting range can be obtained in closed-form expressions. Furthermore, considering the aging effect, we propose a gradient-based method to maximize the spatial-temporal value of information. Specifically, we first determine the optimal recruiting time for the requester and then choose the optimal recruiting range within each time slot. Via simulation, we first compare the sum, max, and min values of information at the requester, and then verify the effectiveness of the gradient-based method to optimize the recruiting time and range to maximize the value of information.
CSI-Impaired Beamforming Optimization for Dense MIMO Communication Networks
Authors: Yu Bencheng , Ren Zihui , Tang Shoufeng
Published: October 2022

This paper studied the robust beamforming for dense transmission systems with imperfect channel state information (CSI). The objective was to maximize the minimum signal to interference plus noise ratio (SINR) in the constraint of the per base station (BS) power. By performing the uplink–downlink duality theory, the referred non-convex optimization problem can be changed into the equivalent uplink decoupling optimization problem. Then, we proposed the instantaneous updating uplink–downlink power algorithm, which relies on instantaneous CSI for the finite system. For the massive MIMO system, to obtain the solution to the problem required for power to instantaneously update, we proposed the updating uplink–downlink power algorithm, which only requires statistical CSI, by applying the random matrix theory. The simulation results show the feasibility and effectiveness of our proposed algorithms.
Electronically Adjustable Multiphase Sinusoidal Oscillator with High-Output Impedance at Output Current Nodes Using VDCCs
Authors: Pitaksuttayaprot Koson , Phanrattanachai Kritphon , Jaikla Winai
Published: October 2022

This paper presents the high-output-impedance current-mode multiphase sinusoidal oscillators (MSO) using voltage differencing current conveyor (VDCC)-based lossy integrators, which consist of one VDCC, one grounded capacitor, and two grounded resistors. The proposed oscillator can provide an odd-phase and even-phase system without the use of an additional amplifier. The frequency of oscillation (FO) is electronically tuned via the bias current without affecting the condition of oscillation (CO). The proposed oscillator is designed to obtain three-phase sinusoidal waveforms (n = 3). The effect of non-idealities of VDCC on the lossy integrator section is also investigated. The validity of the proposed circuit is demonstrated by PSPICE simulation using 0.18 µm TSMC CMOS process parameters with ±0.9V power supply. The frequency of oscillation obtained from the simulation is 1.43 MHz. The total harmonic distortions of the sinusoidal output currents IO1, IO2, and IO2 are 1.22%, 1.18%, and 0.57%. The IO1–IO2 and IO2–IO3 phase differences are approximately 121 and 119 degrees, respectively. The feasibility of the proposed MSO is also verified with experimental results using the VDCC constructed from the commercially available ICs (LT1288 and AD844) with ±5 V power supply. The results of PSPICE simulations and experiments are closely consistent with the theoretical expectation.
MediaPipe’s Landmarks with RNN for Dynamic Sign Language Recognition
Authors: Samaan Gerges H. , Wadie Abanoub R. , Attia Abanoub K. , Asaad Abanoub M. , Kamel Andrew E. , Slim Salwa O. , Abdallah Mohamed S. , Cho Young-Im
Published: October 2022

Communication for hearing-impaired communities is an exceedingly challenging task, which is why dynamic sign language was developed. Hand gestures and body movements are used to represent vocabulary in dynamic sign language. However, dynamic sign language faces some challenges, such as recognizing complicated hand gestures and low recognition accuracy, in addition to each vocabulary’s reliance on a series of frames. This paper used MediaPipe in conjunction with RNN models to address dynamic sign language recognition issues. MediaPipe was used to determine the location, shape, and orientation by extracting keypoints of the hands, body, and face. RNN models such as GRU, LSTM, and Bi-directional LSTM address the issue of frame dependency in sign movement. Due to the lack of video-based datasets for sign language, the DSL10-Dataset was created. DSL10-Dataset contains ten vocabularies that were repeated 75 times by five signers providing the guiding steps for creating such one. Two experiments are carried out on our dataset (DSL10-Dataset) using RNN models to compare the accuracy of dynamic sign language recognition with and without the use of face keypoints. Experiments revealed that our model had an accuracy of more than 99%.
Deep-Learning-Based System for Assisting People with Alzheimer’s Disease
Authors: Munteanu Dan , Bejan Catalina , Munteanu Nicoleta , Zamfir Cristina , Vasić Mile , Petrea Stefan-Mihai , Cristea Dragos
Published: October 2022

People with Alzheimer’s disease are at risk of malnutrition, overeating, and dehydration because short-term memory loss can lead to confusion. They need a caregiver to ensure they adhere to the main meals of the day and are properly hydrated. The purpose of this paper is to present an artificial intelligence system prototype based on deep learning algorithms aiming to help Alzheimer’s disease patients regain part of the normal individual comfort and independence. The proposed system uses artificial intelligence to recognize human activity in video, being able to identify the times when the monitored person is feeding or hydrating, reminding them using audio messages that they forgot to eat or drink or that they ate too much. It also allows for the remote supervision and management of the nutrition program by a caregiver. The paper includes the study, search, training, and use of models and algorithms specific to the field of deep learning applied to computer vision to classify images, detect objects in images, and recognize human activity video streams. This research shows that, even using standard computational hardware, neural networks’ training provided good predictive capabilities for the models (image classification 96%, object detection 74%, and activity analysis 78%), with the training performed in less than 48 h, while the resulting model deployed on the portable development board offered fast response times—that is, two seconds. Thus, the current study emphasizes the importance of artificial intelligence used in helping both people with Alzheimer’s disease and their caregivers, filling an empty slot in the smart assistance software domain.
DFSGraph: Data Flow Semantic Model for Intermediate Representation Programs Based on Graph Network
Authors: Tang Ke , Shan Zheng , Zhang Chunyan , Xu Lianqiu , Qiao Meng , Liu Fudong
Published: October 2022

With the improvement of software copyright protection awareness, code obfuscation technology plays a crucial role in protecting key code segments. As the obfuscation technology becomes more and more complex and diverse, it has spawned a large number of malware variants, which make it easy to evade the detection of anti-virus software. Malicious code detection mainly depends on binary code similarity analysis. However, the existing software analysis technologies are difficult to deal with the growing complex obfuscation technologies. To solve this problem, this paper proposes a new obfuscation-resilient program analysis method, which is based on the data flow transformation relationship of the intermediate representation and the graph network model. In our approach, we first construct the data transformation graph based on LLVM IR. Then, we design a novel intermediate language representation model based on graph networks, named DFSGraph, to learn the data flow semantics from DTG. DFSGraph can detect the similarity of obfuscated code by extracting the semantic information of program data flow without deobfuscation. Extensive experiments prove that our approach is more accurate than existing deobfuscation tools when searching for similar functions from obfuscated code.
Electromagnetic Effective-Degree-of-Freedom Limit of a MIMO System in 2-D Inhomogeneous Environment
Authors: Yuan Shuai S. A. , He Zi , Sun Sheng , Chen Xiaoming , Huang Chongwen , Sha Wei E. I.
Published: October 2022

Compared with a single-input-single-output (SISO) wireless communication system, the benefit of multiple-input-multiple-output (MIMO) technology originates from its extra degree of freedom (DOF), also referred to as scattering channels or spatial electromagnetic (EM) modes, brought by spatial multiplexing. When the physical sizes of transmitting and receiving arrays are fixed and there are sufficient antennas (typically with half-wavelength spacings), the DOF limit is only dependent on the propagating environment. Analytical methods can be used to estimate this limit in free space, and some approximate models are adopted in stochastic environments, such as Clarke’s model and Ray-tracing methods. However, this DOF limit in a certain inhomogeneous environment has not been well discussed with rigorous full-wave numerical methods. In this work, volume integral equation (VIE) is implemented for investigating the limit of MIMO effective degree of freedom (EDOF) in three representative two-dimensional (2-D) inhomogeneous environments. Moreover, we clarify the relation between the performance of a MIMO system and the scattering characteristics of its propagating environment.
Penetration Estimation in SEM, EDAX Dental Imaging Systems for Desensitization Application
Authors: Michael Prawin Angel , Dharmaraj Pamela , Meenal Rajasekaran , Josh Francisxavier Thomas , Joseph Jeyaraj Jency , Nigel Kulandaisamy Gerard Joe , Hemanth Jude
Published: October 2022

Background: In the dental field, many people undergo an extreme fear of injections, which is referred to as trypanophobia. The medical procedures that involve injections in the dental field to create numbness raises a certain level of discomfort to all of the patients to an extent that the patients avoid treating their teeth or show an anxious or avoidance behavior. Hence, needle phobia is one of the more common phobias amongst people but was not officially recognized as a phobia in dentistry for a long time. In rural areas, some patients, mainly elderly people, might go away without treating their damaged tooth due to fear of injections. Aim: Thus, setting this as the major point of consideration, the researchers have put forth a new concept of dental treatment of creating desensitization without injections rather by adopting a new concept as “iontophoresis”, which causes the ions of specific charges to penetrate the semipermeable membrane, which helps in performing surgeries in the dental field. In the present manuscript, the ‘iontophoresis’ method, along with the imaging systems, was adopted and 45 tooth samples were taken and tested with four different ionic gels that are used in the dental field, and the results were analyzed using the imaging systems of SEM and EDAX for clear analysis. Results: The results through these imaging systems show that the ions have penetrated the tooth, which causes a desensitizing effect in the tooth and makes it numb, so that dental operations can be performed easier and with more perfection. The process of performing dental surgery with a needless process is that the patient to be treated by the dentist is exposed to a gel with electrodes wherein the ions penetrate the tooth, which causes numbness. Conclusion: The incorporation of needle-free injection through the concept of iontophoresis and imaging systems in the dental field introduces a new era in the field of dentistry, making the process simple.
Characterization of Ground Thermal Conditions for Shallow Geothermal Exploitation in the Central North China Plain (NCP) Area
Authors: Wang Wanli , Wang Guiling , Liu Feng , Liu Chunlei
Published: October 2022

The central North China Plain (NCP) is one of the rapidly developing regions in China which has a great potential for ground source heat pump (GSHP) system applications. However, the ground thermal property, which is a prerequisite for GSHP system design, has been insufficiently investigated. In this paper, the ground thermal conditions including ground temperature and thermal conductivity are characterized in three representative hydrogeological regions in the NCP area: the piedmont alluvial plain, the central alluvial plain, and the coastal plain. Results show that the geothermal gradient below 40 m in depth in this area ranges from 0.018 °C/m to 0.029 °C/m. Although the thermal conductivity measured by soil samples differs slightly among the three regions, parameters in the piedmont plain have a larger variability than in the central and coastal plain due to the significant heterogeneity of the lithology. Thermal conductivity measured by the thermal response test (TRT) ranges between 2.37 and 2.68 W/(m·K) in the piedmont plain and varies between 1.35 and 1.94 W/(m·K) in the central and coastal plain, indicating that the piedmont plain has a higher potential for shallow geothermal exploitation than other two sub-areas. Comparing the TRT with laboratory measurements, the thermal conductivity obtained by the TRT is greater than that of the lab measurements in the piedmont plain due to the TRT outputs including the effects of groundwater flow. Therefore, the TRT is highly recommended to estimate the effective thermal conductivity of the ground in the piedmont plain, while laboratory and field tests are both suitable methods for the determination of thermal conductivity in the central and coastal plains.
Equilibrium Optimization with Multi-Energy-Efficiency-Grade Products: Government and Market Perspective
Authors: Zhu Qiuyun , Zhou Xiaoyang , Liu Aijun , Gao Chong , Xu Lei , Zhao Fan , Zhang Ding , Lev Benjamin
Published: October 2022

This paper studies the multi-level supply chain network equilibrium optimization problem of multi-energy-efficiency products under different government subsidies and demand scales. In the equilibrium optimization problem, manufacturers determine the production volume of the energy-saving products; retailers decide the transaction volume with manufacturers, distribution volume for markets, and marketing efforts of energy-saving products; markets determine the transaction price. Firstly, the optimal decision-making behaviors of manufacturers, retailers, and markets are described. Simultaneously, the global optimization problem is transformed into a finite-dimensional variational inequality formulation. Then, the equilibrium conditions of the whole supply chain network are derived by the Euler method. Finally, a case study verifies the effectiveness of the proposed method. Interestingly, we found that energy-saving subsidies and demand scales were negatively correlated with the marketing efforts of the subsidized retailers for high energy-efficient products and positively correlated with the marketing efforts of non-subsidized retailers for high energy-efficient products in the same market; the development of retailers in the same market tended to be consistent, and the differentiation of the demand scale eliminated the retailers without a competitive advantage.
Solar-Powered Plant Protection Equipment: Perspective and Prospects
Authors: Ramesh Desikan , Chandrasekaran Mohanrangan , Soundararajan Raga Palanisamy , Subramanian Paravaikkarasu Pillai , Palled Vijayakumar , Kumar Deivasigamani Praveen
Published: October 2022

The major challenges in sustainable and profitable agriculture are developing high-yielding crop varieties and reducing crop losses. Presently, there are significant crop losses due to weed/bird/insect/animal attacks. Among the various renewable energy sources, solar energy is utilized for different agricultural operations, especially in plant protection applications. Solar photovoltaic (PV) devices present a positive approach to sustainable crop production by reducing crop loss in various ways. This might result in the extensive use of PV devices in the near future. PV-based plant protection equipment/devices are primarily utilized in protecting crops from birds, weeds, or insects. Solar-powered plant protection equipment such as light traps, bird scarers, sprayers, weeders, and fencing are gaining interest due to their lower operational costs, simple design, no fuel requirements, and zero carbon emissions. Most of these PV devices require 12 V rechargeable batteries with different currents to meet the load, which varies from 2 to 1500 W. This paper briefly discusses the applications of solar-powered plant protection devices in sustainable agriculture and their future prospects.
Isolation and Purification of Actinides Using N,O-Hybrid Donor Ligands for Closing the Nuclear Fuel Cycle
Authors: Alyapyshev Mikhail , Babain Vasiliy , Kirsanov Dmitry
Published: October 2022

Despite the fact that in the mass consciousness nuclear power is associated with increased environmental risks, this type of energy today remains one of the cleanest, most efficient and carbon neutral. Further development of nuclear energy is hampered by the problem of appropriate handling of spent nuclear fuel (SNF). A very attractive concept of the closed nuclear cycle has been developed to solve it. A real-life implementation of this concept requires the development of technological processes for the efficient separation of minor actinides from the rest of the SNF components. Recent progress in this area has been closely associated with N,O-hybrid donor ligands for liquid–liquid extraction. This work systematically reviews the available literature on the topic and provides detailed explanations on the behavior of the most perspective ligands. Notably, another important aspect of the application of N,O-hybrid donor ligands in nuclear cycle analytics through their incorporation in chemical sensors is also discussed.
IK-SPSA-Based Performance Optimization Strategy for Steam Generator Level Control System of Nuclear Power Plant
Authors: Geng Pengcheng , Kong Xiangsong , Shi Changqing , Liu Hang , Liu Jiabin
Published: October 2022

The steam generator (SG) is a critical component of the steam supply system in the nuclear power plant (NPP). Hence, it is necessary to control the SG level well to ensure the stable operation of the NPPs. However, its dynamic level response process has significant nonlinearity (such as the ‘swell and shrinks’ effect) and time-varying properties. As most of the SG level control systems (SGLCS) are constructed based on the Proportional-Integral-Derivative (PID) controllers with fixed parameters, the controller parameters should be optimized to improve the performance of the SGLCS. However, traditional parameters tuning methods are generally experience-based, cumbersome, and time-consuming, and it is difficult to obtain the optimal parameters. To address the challenge, this study adopts a knowledge-informed simultaneous perturbation stochastic approximation (IK-SPSA) based on adjacent iteration points information to improve the performance of the SGLCS. Rather than the traditional controller parameter tuning method, the IK-SPSA method optimizes the control system directly by using measurements of control performance. The method’s efficiency lies in the following aspects. Firstly, with the help of historical information during the optimization process, the IK-SPSA can dynamically sense the current status of the optimization process. Secondly, it can accomplish the iteration step size tuning adaptively according to the optimization process’s current status, reducing the optimization cost. Thirdly, it has the stochastic characteristic of simultaneous perturbation, which gives it high optimization efficiency to optimize high dimensional controller parameters. Fourthly, it incorporates an intelligent termination control mechanism to accomplish optimization progress control. This mechanism could terminate the optimization process intelligently through historical iterative process information, avoiding unnecessary iterations. The optimization method can improve the stability, safety, and economy of SGLCS. The simulation results demonstrated the effectiveness and efficiency of the method.
Micro-Channel Oscillating Heat Pipe Energy Conversion Approach of Battery Heat Dissipation Improvement: A Review
Authors: Zhao Xiaohuan , Zhu Yue , Li Hailiang
Published: October 2022

The application of batteries has become more and more extensive, and the heat dissipation problem cannot be ignored. Oscillating Heat Pipe (OHP) is a good means of heat dissipation. In this paper, the methods to improve the energy conversion and flow thermal performance of micro-channel OHP are studied and summarized. The working principle, heat transfer mechanism, advantages and applications of PHP are also introduced in detail in this study. Proper adjustment of the micro-channel layout can increase the heat transfer limit of PHP by 44%. The thermal resistance of two-diameter channel PHP is 45% lower than that of conventional PHP. The thermal resistance of PHP under uneven heating can be reduced to 50% of the original. PHP pulse heating can alleviate the phenomenon of dryness. Different working fluids have different effects on PHP. The use of graphene nano-fluids as the work medium can reduce the thermal resistance of PHP by 83.6%. The work medium obtained by the mixture of different fluids has the potential to compensate for the defects while inheriting the advantages of a single fluid.
Investigating The Impact of Roadway Characteristics on Intersection Crash Severity
Authors: Sharafeldin Mostafa , Farid Ahmed , Ksaibati Khaled
Published: October 2022

Intersections are commonly recognized as crash hot spots on roadway networks. Therefore, intersection safety is a major concern for transportation professionals. Identifying and quantifying the impact of crash contributing factors is crucial to planning and implementing the appropriate countermeasures. This study covered the analysis of nine years of intersection crash records in the State of Wyoming to identify the contributing factors to crash injury severity at intersections. The study involved the investigation of the influence of roadway (intersection) and environmental characteristics on crash injury severity. The results demonstrated that several parameters related to intersection attributes (pavement friction; urban location; roadway functional classification; guardrails; right shoulder width) and two environmental conditions (road surface condition and lighting) influence the injury severity of intersection crashes. This study identified the significant roadway characteristics influencing crash severity and explored the key role of pavement friction, which is a commonly omitted variable.
Rainfall Physical Partitioning and Chemical Characteristics in Evergreen Coniferous and Deciduous Broadleaved Forest Stands in a High Nitrogen Deposition Region, China
Authors: Yang Tao , Li Yong , Ouyang Xueying , Wang Bo , Ge Xiaomin , Tang Luozhong
Published: October 2022

Atmospheric rainfall is one of the major sources of water and nutrient inputs in forest stands. Understanding the atmospheric rainfall partitioning and hydrochemical fluxes of forest stands is critical for forest management and monitoring regional atmospheric pollution, especially in high N deposition regions. In this study, annual rainfall collections were implemented to investigate rainfall partitioning, element concentrations, and element fluxes in an evergreen coniferous forest (ECF) stand, a deciduous broadleaved forest (DBF) stand, and open area field (OAF) in a high N deposition region, China. Rainfall in the ECF and DBF was partitioned into throughfall, stemflow, and interception loss, which accounted for 74.7%, 4.8%, and 20.5% of the gross annual rainfall in the ECF stand, respectively; and 79.8%, 5.8%, and 14.4% of the gross annual rainfall in the DBF stand, respectively. Rainfall physical partitioning chemical characteristics varied with forest stand type. The amount of throughfall and stemflow in the ECF stand was lower than that in the DBF stand; the interception loss in the ECF stand was higher than that in the DBF stand. Element concentrations and element fluxes increased as rainfall passed through forest canopies in the high N deposition region. The stemflow pH in the ECF was lower than that in the DBF stand, the concentrations of NO3−-N, Cl−, and SO42−-S in stemflow in the ECF stand were higher than those in the DBF stand, and the concentrations of K+, Na+, Ca2+, Mg2+ and NH4+-N in stemflow in the ECF stand were lower than those in the DBF stand. The inorganic N deposition was 52.7 kg ha−1 year−1 for the OAF, 110.9 kg ha−1 year−1 for the ECF stand, and 99.6 kg ha−1 year−1 for the DBF stand; stemflow accounted for 15.1% and 19.2% of inorganic N deposition in the ECF stand and the DBF stand, respectively. In the present study, given the similar rainfall characteristics and meteorological conditions, the differences in rainfall partitioning and chemical characteristics between the ECF stand and the DBF stand could largely be attributed to their differences in stand characteristics. The results of the study will facilitate a greater understanding of the atmospheric rainfall partitioning and hydrochemical fluxes of forest stands in a high nitrogen deposition region.
Production of Enzymatic Extract with High Cellulolytic and Oxidative Activities by Co-Culture of Trichoderma reesei and Panus lecomtei
Authors: Peláez Rubén Darío Romero , Wischral Daiana , Cunha Joice Raísa Barbosa , Mendes Thais Demarchi , Pacheco Thályta Fraga , Siqueira Félix Gonçalves de , Almeida João Ricardo Moreira de
Published: October 2022

This work aimed to produce enzymatic fungi extracts with hydrolytic and oxidative activities to hydrolyze lignocellulosic biomasses efficiently. For this, the fungi Trichoderma reesei and Panus lecomtei were co-cultured using the vegetable biomasses oil palm decanter cake, wheat bran, and cottonseed cake as substrates in submerged fermentation. T. reesei and P. lecomtei showed partially compatible positive interaction on plates. The co-cultures respond positively to variations of temperature and inoculum interval, generating extracts responsible for higher hydrolysis yield when grown at 25 °C, and P. lecomtei is inoculated 24 h after T. reesei. The enzymatic extract production of co-cultures was also improved by modifying the components of the initial media and evaluating enzymatic activities, hydrolysis of sugarcane bagasse pretreated by autohydrolysis and ethanol production as a response. Five culture media were evaluated with variations in the composition of nutritional elements, minerals and substrates. The best extract showed a maximum cellulose hydrolysis efficiency of 68.7% compared with 44.8% of the initial medium. The ethanolic fermentation of hydrolysates obtained by co-culture extracts showed higher ethanol yields than monocultures. This work demonstrates the use of fungi co-cultures to produce enzymatic extracts composed of cellulolytic, hemicellulolytic, and ligninolytic enzymes complexes, which allow hydrolyzing pretreated lignocellulosic biomass with high efficiency, generating hydrolysates that are easier fermented by yeast.
Changes of γ-Aminobutyric Acid, Phytoestrogens, and Biofunctional Properties of the Isoflavone-Enriched Soybean (Glycine max) Leaves during Solid Lactic Acid Fermentation
Authors: Lee Hee Yul , Cho Du Yong , Jang Kyeong Jin , Lee Jin Hwan , Jung Jea Gack , Kim Min Ju , Jeong Jong Bin , Haque Md. Azizul , Cho Kye Man
Published: October 2022

The present study documents the changes in the γ-aminobutyric acid (GABA), the total phenolic (TP), total flavonoid (TF), and isoflavone contents, the antioxidant activities and the digestive enzyme inhibition during the solid lactic acid fermentation of isoflavone-enriched soybean leaves (IESLs) with starters Lactiplantibacillus plantarum P1201 and Levilactobacillus brevis BMK184. The contents of glutamic acid (GA) and GABA remained almost unchanged during fermentation with P1201. In contrast, the contents of GABA increased from 144.24 to 173.09 and 175.59 mg/100 g, and the contents of GA decreased from 43.68 to 18.26 and 11.25 mg/100 g during the IESLs’ fermentation with BMK184 and the combined use of P1201 + BMK184, respectively. The total isoflavone content decreased during fermentation, but the isoflavone aglycone levels increased; in fact, the levels of daidzein and genistein were the highest after the use of P1201 + BMK184 (2265.57 μg/g) and BMK184 (1055.27 μg/g), respectively, at 72 h of fermentation. Correspondingly, the DPPH (90.90%), the ABTS (91.09%), and the hydroxyl (74.88%) radical scavenging activities, the ferric reducing/antioxidant power (2.45), as well as the α-glucosidase (49.86%) and pancreatic lipase (37.30%) inhibition activities exhibited their highest levels after fragmentation with P1201 + BMK184.
Valorization of Potential Post-Consumer Polyethylene (PE) Plastics Waste and Ethiopian Indigenous Highland Bamboo (EHB) for Wood Plastic Composite (WPC): Experimental Evaluation and Characterization
Authors: Ayana Keresa Defa , De Angelis Marco , Schmidt Goran , Krause Andreas , Ali Abubeker Yimam
Published: October 2022

The best approaches to minimizing resource scarcity, removing valuable waste streams, and re-establishing a circular economic chain of recycled thermoplastics are to cascade them into product life cycles and their valorization combined with sustainable raw materials. As one part of this goal, WPC was formulated from three recycled PE plastic wastes: linear low-density polyethylene (LLDPE), medium-density polyethylene (MDPE), high-density polyethylene (HDPE), and underutilized EHB. The chemical composition of EHD, chemical structure, crystallinity, melting and crystallization points, residual metal additives, and polycyclic aromatic hydrocarbons (PAHs) of recycled PE were investigated using standard chromatographic and spectroscopic methods such as HPAEC-UV/VIS, FTIR, DSC, GC/MSD, and XPS. The properties of WPC formulations from different compositions of bamboo particles (BP) as dispersed phase, individual recycled PE plastics, and equal melt blend (EM) as polymer matrix were investigated extensively and measured with a known standard. These comprised tensile strength (TS), modulus of elasticity (TM), flexural strength (FS), modulus of rupture (FM), and unnotched impact strength (UIS). It also included the effect of various alkaline surface treatment ranges on the interface surface interaction. The results show improved mechanical properties for all blending ratios of surface-treated BP, which resulted from better encapsulation in the polymer matrix. Despite its inherent immiscibility, WPC formulation from equal melt blending revealed unusual properties compared to separate phase blends, which is attributed to thermally induced cross-linking. This implies that melt blending of the weakest and cheapest recycled LLDPE with relatively cheap recycled MDPE and HDPE improves the properties of the blend, particularly toughness, while simultaneously retaining some of their properties.
Mixed Mulberry Fruit and Mulberry Leaf Fermented Alcoholic Beverages: Assessment of Chemical Composition, Antioxidant Capacity In Vitro and Sensory Evaluation
Authors: Gao Tengqi , Chen Jinling , Xu Feng , Wang Yilin , Zhao Pengpeng , Ding Yunfei , Han Yongbin , Yang Jie , Tao Yang
Published: October 2022

The fruit and leaves of mulberry (Morus alba L.) contain a variety of health-beneficial components. At present, although both alcoholic and non-alcoholic mulberry beverages are commercially available, studies on fermented alcoholic beverages mixed with both mulberry fruit and mulberry leaf are rare. In this study, different amounts (1, 2 and 3%, g/mL dry weight) of mulberry leaves were added during the alcoholic fermentation of mulberry juice. After 9 days of fermentation, the 1-deoxynojirimycin (DNJ) content increased from 61.12 ± 3.10 to 153.39 ± 3.98 μg/mL, and the quercetin content increased from 0.45 ± 0.01 to 20.14 ± 0.08 mg/L in the mulberry alcoholic beverages with the addition of mulberry leaves at 2%. Moreover, the ABTS+ scavenging capacity at the end of fermentation for the same sample was enhanced by 40.9%. In addition, the total sugar, total phenols, total anthocyanins, and γ-aminobutyric acid (GABA) contents of the fermented samples all decreased significantly at the end of fermentation. A total of 33 volatile compounds and 17 free amino acids were detected in the fermented alcoholic beverages with mulberry leaves added. The total free amino acid content increased with the increase in mulberry leaf addition. Principal component analysis showed that the addition of mulberry leaves during fermentation increased the contents of GABA, DNJ, total flavonols and protocatechuic acid in mulberry alcoholic beverages. All these studies revealed the dynamic changes in functional components in the alcoholic fermentation of mulberry juices with the addition of mulberry leaves. Overall, the addition of mulberry leaf powder at 2% was selected as the appropriate addition for producing mulberry alcoholic beverages with enhanced nutritional value.
Development of a Sensitive and Fast Determination Method for Trace Carbaryl Residues in Food Samples Based on Magnetic COF (TpPa-NH2)@Fe3O4 Nanoparticles and Fluorescence Detection
Authors: Du Juanli , Wu Hao , Jing Xu , Yu Yonghe , Yan Zhisheng , Zhang Jianhai
Published: October 2022

Developing a simple and effective method for measuring carbaryl residues in food is urgent due to its widespread use and the associated health risks in agriculture, as well as various defects in existing detection techniques. The COF (TpPa-NH2)@Fe3O4 nanocomposite (amino modification) was synthesized via a two-step method and used as an adsorbent for the extraction of carbaryl from food samples in this study. The results indicated that COF (TpPa-NH2)@Fe3O4 can rapidly and successfully capture carbaryl directly from samples via π–π stacking and hydrophobic interactions, achieving maximum adsorption within 5 min under a small adsorbent quantity using a fluorescence spectrophotometer. Under the optimized conditions, carbaryl exhibited good linearity in the range of 0.2–120 µg·kg−1, and the limit of detection was 0.012 µg·kg−1. The recoveries of the samples were 96.0–107.4%. This method has broad application prospects for the monitoring of carbaryl in food.
Identification and Structure–Activity Relationship of Recovered Phenolics with Antioxidant and Antihyperglycemic Potential from Sugarcane Molasses Vinasse
Authors: Huang Zhe , Chen Yinning , Huang Riming , Zhao Zhengang
Published: October 2022

Sugarcane molasses vinasse is the residue of the fermentation of molasses and the water and soil environmental pollutants from distilleries. However, its recycling value has been neglected. The chemical analysis of the molasses vinasse led to the isolation of a new benzoyl chloride called 2,3,4-trihydroxy-5-methoxy benzoyl chloride, as well as thirteen known compounds, including six benzoic acids. The structure of the new benzoyl chloride was elucidated on the basis of extensive spectroscopic analysis. The antioxidant activity of all isolated compounds was measured using the ORAC assay. Moreover, we compared the cellular antioxidant activity (CAA) and inhibitory activity against α-amylase and α-glucosidase for structure–activity analysis. The results showed that only vanillic acid had CAA (8.64 μmol QE/100 μmol in the no PBS wash protocol and 6.18 μmol QE/100 μmol in the PBS wash protocol), although other benzoic acid derivatives had high ORAC values ranging between 1879.9 and 32,648.1 μmol TE/g. Additional methoxy groups at the ortho-positions of the p-hydroxy group of benzoic acids enhanced the inhibition of α-glucosidase but reduced the ORAC activity unless at the para-position. This work indicated that phenolics, especially phenolic acids in the sugarcane molasses vinasse, possessed potential antioxidant and antihyperglycemic activity, which improved the utilization rate of resources and reduced the discharge of pollutants.