bluuebunny/crossref_metadata_2025 huggingface dataset:
Deep Learning for Diabetic Retinopathy Analysis: A Review, Research Challenges, and Future Directions
Authors: Nadeem Muhammad Waqas , Goh Hock Guan , Hussain Muzammil , Liew Soung-Yue , Andonovic Ivan , Khan Muhammad Adnan
Published: September 2022

Deep learning (DL) enables the creation of computational models comprising multiple processing layers that learn data representations at multiple levels of abstraction. In the recent past, the use of deep learning has been proliferating, yielding promising results in applications across a growing number of fields, most notably in image processing, medical image analysis, data analysis, and bioinformatics. DL algorithms have also had a significant positive impact through yielding improvements in screening, recognition, segmentation, prediction, and classification applications across different domains of healthcare, such as those concerning the abdomen, cardiac, pathology, and retina. Given the extensive body of recent scientific contributions in this discipline, a comprehensive review of deep learning developments in the domain of diabetic retinopathy (DR) analysis, viz., screening, segmentation, prediction, classification, and validation, is presented here. A critical analysis of the relevant reported techniques is carried out, and the associated advantages and limitations highlighted, culminating in the identification of research gaps and future challenges that help to inform the research community to develop more efficient, robust, and accurate DL models for the various challenges in the monitoring and diagnosis of DR.
HT-Net: A Hybrid Transformer Network for Fundus Vessel Segmentation
Authors: Hu Xiaolong , Wang Liejun , Li Yongming
Published: September 2022

Doctors usually diagnose a disease by evaluating the pattern of abnormal blood vessels in the fundus. At present, the segmentation of fundus blood vessels based on deep learning has achieved great success, but it still faces the problems of low accuracy and capillary rupture. A good vessel segmentation method can guide the early diagnosis of eye diseases, so we propose a novel hybrid Transformer network (HT-Net) for fundus imaging analysis. HT-Net can improve the vessel segmentation quality by capturing detailed local information and implementing long-range information interactions, and it mainly consists of the following blocks. The feature fusion block (FFB) is embedded in the shallow levels, and FFB enriches the feature space. In addition, the feature refinement block (FRB) is added to the shallow position of the network, which solves the problem of vessel scale change by fusing multi-scale feature information to improve the accuracy of segmentation. Finally, HT-Net’s bottom-level position can capture remote dependencies by combining the Transformer and CNN. We prove the performance of HT-Net on the DRIVE, CHASE_DB1, and STARE datasets. The experiment shows that FFB and FRB can effectively improve the quality of microvessel segmentation by extracting multi-scale information. Embedding efficient self-attention mechanisms in the network can effectively improve the vessel segmentation accuracy. The HT-Net exceeds most existing methods, indicating that it can perform the task of vessel segmentation competently.
High Performance Broadcast Receiver Based on Obsolete Technology
Authors: Teodorescu Laurenţiu , Dima Gabriel
Published: September 2022

Since its inception, the electronics industry has mass-produced equipment. The fast evolution of electronic technologies made obsolete the entire generation of products and even technologies. Until the government issued regulations and guidelines on how to address the issue of reuse of obsolete electronic equipment, with special regard to the ones still operating (e.g., give it to family/friends, donate to charity, or sell to individuals or recycling companies), most of it was thrown out with usual rubbish, with a destructive effect on the environment. This paper presents the design techniques and methods for revaluation of obsolete vacuum tube analog receivers, with a focus on the manufacturing steps of a high-performance receiver. The choice of receiver type is not accidental at all, since tube technology is still a real success among audiophiles many providers offer vacuum tube amplifiers at considerably high prices. The redesign implied the original FM unit replacement with a DSP-based AM/FM tuner while the AM RF vacuum tube section has been preserved with the original architecture to allow the reception of the broadcast stations for the long-wave band and the alternative operation with the silicon tuner for the medium-wave and short-wave bands. The electrical performances of the modified receiver in terms of reliability, sensitivity, selectivity, and distortions on the reception chain are clearly superior to the original one, while the power consumption of the RF section is reduced more than 10 times from 11.5 W–15.5 W to 1 W. Last, but not least important, the proposed solution implied the use of few additional parts and resources and extended significantly the lifetime of the original vacuum tubes receiver. The work has been developed to serve as an example of how obsolete electronic equipment can be redesigned and reused avoiding its complete recycling or even worse, its disposal with usual rubbish. It has been imagined and performed as the initial step in launching a professional student contest on the reuse/redesign of obsolete equipment aimed at raising awareness regarding the issue of pollution with e-waste amongst students from the electronic departments of Romanian technical universities.
Exploratory Research on Sweetness Perception: Decision Trees to Study Electroencephalographic Data and Its Relationship with the Explicit Response to Sweet Odor, Taste, and Flavor
Authors: Romeo-Arroyo Elena , Soria Javier , Mora María , Laport Francisco , Moreno-Fernandez-de-Leceta Aitor , Vázquez-Araújo Laura
Published: September 2022

Using implicit responses to determine consumers’ response to different stimuli is becoming a popular approach, but research is still needed to understand the outputs of the different technologies used to collect data. During the present research, electroencephalography (EEG) responses and self-reported liking and emotions were collected on different stimuli (odor, taste, flavor samples) to better understand sweetness perception. Artificial intelligence analytics were used to classify the implicit responses, identifying decision trees to discriminate the stimuli by activated sensory system (odor/taste/flavor) and by nature of the stimuli (‘sweet’ vs. ‘non-sweet’ odors; ‘sweet-taste’, ‘sweet-flavor’, and ‘non-sweet flavor’; and ‘sweet stimuli’ vs. ‘non-sweet stimuli’). Significant differences were found among self-reported-liking of the stimuli and the emotions elicited by the stimuli, but no clear relationship was identified between explicit and implicit data. The present research sums interesting data for the EEG-linked research as well as for EEG data analysis, although much is still unknown about how to properly exploit implicit measurement technologies and their data.
Security Analysis and Improvement of Vehicle Ethernet SOME/IP Protocol
Authors: Du Jinze , Tang Rui , Feng Tao
Published: September 2022

The combination of in-vehicle networks and smart car devices has gradually developed into Intelligent Connected Vehicles (ICVs). Through the vehicle security protocol, ICVs can quickly realize communication transmission. However, with the more frequent connections between smart in-vehicle devices and the network, the relationship between intelligent cars and external systems is becoming more and more complicated, and in-vehicle networks are gradually facing many security issues. Strengthening the security of in-vehicle protocols has become particularly important. This paper uses the model building method based on the Colored Petri Net (CPN) theory to model the Scalable service-Oriented MiddlewarE over IP (SOME/IP) protocol of the vehicle Ethernet. The security protocol is formally verified and analyzed by combining it with the Dolev–Yao adversary model detection method. After verification, the protocol is subject to three attack vulnerabilities: replay, tampering, and deception. We introduce timestamps and random numbers to strengthen the protocol security. After the final analysis and verification, the improved scheme in this paper can effectively improve the security performance of the protocol.
Precise Two-Dimensional Tilt Measurement Sensor with Double-Cylindrical Mirror Structure and Modified Mean-Shift Algorithm for a Confocal Microscopy System
Authors: Wang Zhiyi , Wang Tingyu , Yang Yongqiang , Yang Yukai , Mi Xiaotao , Wang Jianli
Published: September 2022

To improve the accuracy of three-dimensional (3D) surface contour measurements of freeform optics, a two-dimensional (2D) tilt measurement sensor for confocal microscopy (CM) systems is proposed based on a double-cylindrical mirror structure. First, the proposed system is accurately modeled. Second, we introduce a modified mean–shift-based peak-extraction algorithm with a novel kernel function (MSN) because the reflectivity of the measured object and fluctuation of the light source affect the measurement accuracy. Third, a partition fitting (PF) strategy is proposed to reduce the fitting error and improve the measurement accuracy. Simulations and experiments reveal that the robustness, speed, and angular prediction accuracy of the system effectively improved as a function of MSN and PF. The developed sensor can measure the 2D tilt, where each tilt is a composition of two separate dimensions, and the mean prediction errors in the 2D plane from −10°–+10° are 0.0134° (0.067% full scale (F.S)) and 0.0142° (0.071% F.S). The sensor enables the optical probe of a traditional CM to obtain accurate and simultaneous estimates of the 2D inclination angle and spatial position coordinates of the measured surface. The proposed sensor has potential in 3D topographic reconstruction and dynamic sampling rate optimization for 3D contour detection.
Shape Memory Alloy-Based Wearables: A Review, and Conceptual Frameworks on HCI and HRI in Industry 4.0
Authors: Srivastava Rupal , Alsamhi Saeed Hamood , Murray Niall , Devine Declan
Published: September 2022

Ever since its discovery, the applications of Shape Memory Alloys (SMA) can be found across a range of application domains, from structural design to medical technology. This is based upon the unique and inherent characteristics such as thermal Shape Memory Effect (SME) and Superelasticity (or Pseudoelasticity). While thermal SME is used for shape morphing applications wherein temperature change can govern the shape and dimension of the SMA, Superelasticity allows the alloy to withstand a comparatively very high magnitude of loads without undergoing plastic deformation at higher temperatures. These unique properties in wearables have revolutionized the field, and from fabrics to exoskeletons, SMA has found its place in robotics and cobotics. This review article focuses on the most recent research work in the field of SMA-based smart wearables paired with robotic applications for human-robot interaction. The literature is categorized based on SMA property incorporated and on actuator or sensor-based concept. Further, use-cases or conceptual frameworks for SMA fiber in fabric for ‘Smart Jacket’ and SMA springs in the shoe soles for ‘Smart Shoes’ are proposed. The conceptual frameworks are built upon existing technologies; however, their utility in a smart factory concept is emphasized, and algorithms to achieve the same are proposed. The integration of the two concepts with the Industrial Internet of Things (IIoT) is discussed, specifically regarding minimizing hazards for the worker/user in Industry 5.0. The article aims to propel a discussion regarding the multi-faceted applications of SMAs in human-robot interaction and Industry 5.0. Furthermore, the challenges and the limitations of the smart alloy and the technological barriers restricting the growth of SMA applications in the field of smart wearables are observed and elaborated.
DDoS Attack Prevention for Internet of Thing Devices Using Ethereum Blockchain Technology
Authors: Ibrahim Rahmeh Fawaz , Abu Al-Haija Qasem , Ahmad Ashraf
Published: September 2022

The Internet of Things (IoT) has widely expanded due to its advantages in enhancing the business, industrial, and social ecosystems. Nevertheless, IoT infrastructure is susceptible to several cyber-attacks due to the endpoint devices’ restrictions in computation, storage, and communication capacity. As such, distributed denial-of-service (DDoS) attacks pose a serious threat to the security of the IoT. Attackers can easily utilize IoT devices as part of botnets to launch DDoS attacks by taking advantage of their flaws. This paper proposes an Ethereum blockchain model to detect and prevent DDoS attacks against IoT systems. Additionally, the proposed system can be used to resolve the single points of failure (dependencies on third parties) and privacy and security in IoT systems. First, we propose implementing a decentralized platform in place of current centralized system solutions to prevent DDoS attacks on IoT devices at the application layer by authenticating and verifying these devices. Second, we suggest tracing and recording the IP address of malicious devices inside the blockchain to prevent them from connecting and communicating with the IoT networks. The system performance has been evaluated by performing 100 experiments to evaluate the time taken by the authentication process. The proposed system highlights two messages with a time of 0.012 ms: the first is the request transmitted from the IoT follower device to join the blockchain, and the second is the blockchain response. The experimental evaluation demonstrated the superiority of our system because there are fewer I/O operations in the proposed system than in other related works, and thus it runs substantially faster.
Correction: Schiboni et al. DynDSE: Automated Multi-Objective Design Space Exploration for Context-Adaptive Wearable IoT Edge Devices. Sensors 2020, 20, 6104
Authors: Schiboni Giovanni , Suarez Juan Carlos , Zhang Rui , Amft Oliver
Published: September 2022

Due to formal academic regulations, the affiliation of the university has been amended, and an “Acknowledgements” section has been added to the original publication [...]
Wireless Sensor Network-Based Rigid Body Localization for NLOS Parameter Estimation
Authors: Wan Pengwu , Wei Jian , Wang Jin , Huang Qiongdan
Published: September 2022

In wireless sensor network (WSN)-based rigid body localization (RBL) systems, the non-line-of-sight (NLOS) propagation of the wireless signals leads to severe performance deterioration. This paper focuses on the RBL problem under the NLOS environment based on the time of arrival (TOA) measurement between the sensors fixed on the rigid body and the anchors, where the NLOS parameters are estimated to improve the RBL performance. Without any prior information about the NLOS environment, the highly non-linear and non-convex RBL problem is transformed into a difference of convex (DC) programming, which can be solved by using the concave–convex procedure (CCCP) to determine the position of the rigid body sensors and the NLOS parameters. To avoid error accumulation, the obtained NLOS parameters are utilized to refine the localization performance of the rigid body sensors. Then, the accurate position and the orientation of the rigid body in two-Dimensional space are obtained according to the relative deflection angle method. To reduce the computational complexity, the singular value decomposition (SVD) method is employed to solve the problem in three-Dimensional space. Simulation results show that the proposed method can effectively improve the performance of the rigid body localization based on the wireless sensor network in NLOS environment.
Dairy Cattle Rumen Bolus Developments with Special Regard to the Applicable Artificial Intelligence (AI) Methods
Authors: Hajnal Éva , Kovács Levente , Vakulya Gergely
Published: September 2022

It is a well-known worldwide trend to increase the number of animals on dairy farms and to reduce human labor costs. At the same time, there is a growing need to ensure economical animal husbandry and animal welfare. One way to resolve the two conflicting demands is to continuously monitor the animals. In this article, rumen bolus sensor techniques are reviewed, as they can provide lifelong monitoring due to their implementation. The applied sensory modalities are reviewed also using data transmission and data-processing techniques. During the processing of the literature, we have given priority to artificial intelligence methods, the application of which can represent a significant development in this field. Recommendations are also given regarding the applicable hardware and data analysis technologies. Data processing is executed on at least four levels from measurement to integrated analysis. We concluded that significant results can be achieved in this field only if the modern tools of computer science and intelligent data analysis are used at all levels.
Accelerating 3D Convolutional Neural Network with Channel Bottleneck Module for EEG-Based Emotion Recognition
Authors: Kim Sungkyu , Kim Tae-Seong , Lee Won Hee
Published: September 2022

Deep learning-based emotion recognition using EEG has received increasing attention in recent years. The existing studies on emotion recognition show great variability in their employed methods including the choice of deep learning approaches and the type of input features. Although deep learning models for EEG-based emotion recognition can deliver superior accuracy, it comes at the cost of high computational complexity. Here, we propose a novel 3D convolutional neural network with a channel bottleneck module (CNN-BN) model for EEG-based emotion recognition, with the aim of accelerating the CNN computation without a significant loss in classification accuracy. To this end, we constructed a 3D spatiotemporal representation of EEG signals as the input of our proposed model. Our CNN-BN model extracts spatiotemporal EEG features, which effectively utilize the spatial and temporal information in EEG. We evaluated the performance of the CNN-BN model in the valence and arousal classification tasks. Our proposed CNN-BN model achieved an average accuracy of 99.1% and 99.5% for valence and arousal, respectively, on the DEAP dataset, while significantly reducing the number of parameters by 93.08% and FLOPs by 94.94%. The CNN-BN model with fewer parameters based on 3D EEG spatiotemporal representation outperforms the state-of-the-art models. Our proposed CNN-BN model with a better parameter efficiency has excellent potential for accelerating CNN-based emotion recognition without losing classification performance.
A Review of Multi-Modal Learning from the Text-Guided Visual Processing Viewpoint
Authors: Ullah Ubaid , Lee Jeong-Sik , An Chang-Hyeon , Lee Hyeonjin , Park Su-Yeong , Baek Rock-Hyun , Choi Hyun-Chul
Published: September 2022

For decades, co-relating different data domains to attain the maximum potential of machines has driven research, especially in neural networks. Similarly, text and visual data (images and videos) are two distinct data domains with extensive research in the past. Recently, using natural language to process 2D or 3D images and videos with the immense power of neural nets has witnessed a promising future. Despite the diverse range of remarkable work in this field, notably in the past few years, rapid improvements have also solved future challenges for researchers. Moreover, the connection between these two domains is mainly subjected to GAN, thus limiting the horizons of this field. This review analyzes Text-to-Image (T2I) synthesis as a broader picture, Text-guided Visual-output (T2Vo), with the primary goal being to highlight the gaps by proposing a more comprehensive taxonomy. We broadly categorize text-guided visual output into three main divisions and meaningful subdivisions by critically examining an extensive body of literature from top-tier computer vision venues and closely related fields, such as machine learning and human–computer interaction, aiming at state-of-the-art models with a comparative analysis. This study successively follows previous surveys on T2I, adding value by analogously evaluating the diverse range of existing methods, including different generative models, several types of visual output, critical examination of various approaches, and highlighting the shortcomings, suggesting the future direction of research.
Myconoside Affects the Viability of Polarized Epithelial MDCKII Cell Line by Interacting with the Plasma Membrane and the Apical Junctional Complexes
Authors: Kostadinova Aneliya , Staneva Galya , Topouzova-Hristova Tanya , Moyankova Daniela , Yordanova Vesela , Veleva Ralitsa , Nikolova Biliana , Momchilova Albena , Djilianov Dimitar , Hazarosova Rusina
Published: September 2022

The phenyl glycoside myconoside, extracted from Balkan endemic Haberlea rhodopensis, has a positive effect on human health, but the exact molecular mechanism of its action is still unknown. The cell membrane and its associated junctional complex are the first targets of exogenous compound action. We aimed to study the effect of myconoside on membrane organization and cytoskeleton components involved in the maintenance of cell polarity in the MDCKII cell line. By fluorescent spectroscopy and microscopy, we found that at low concentrations, myconoside increases the cell viability by enhancing membrane lipid order and adherent junctions. The opposite effect is observed in high myconoside doses. We hypothesized that the cell morphological and physicochemical changes of the analyzed cell compartments are directly related to cell viability and cell apical-basal polarity. Our finding contributes to a better understanding of the beneficial application of phytochemical myconoside in pharmacology and medicine.
A Resolved Simulation Approach to Investigate the Separation Behavior in Solid Bowl Centrifuges Using Material Functions
Authors: Baust Helene Katharina , Hammerich Simon , König Hartmut , Nirschl Hermann , Gleiß Marco
Published: September 2022

The separation of finely dispersed particles from liquids is a basic operation in mechanical process engineering. On an industrial scale, continuously operating decanter centrifuges are often used, whose separation principle is based on the density difference between the solid and the liquid phase due to high g-forces acting on both phases. The design of centrifuges is based on the experience on the individual manufacturer or simplified black box models, which only consider a stationary state. Neither the physical behavior of the separation process nor the sediment formation and its transport is considered. In this work, a computationally-efficient approach is proposed to simulate the separation process in decanter centrifuges. Thereby, the open-source computation software OpenFOAM was used to simulate the multiphase flow within the centrifuge. Sedimentation, consolidation of the sediment, and its transport are described by material functions which are derived from experiments. The interactions between the particles and the fluid are considered by locally defined viscosity functions. This work shows that the simulation method is suitable for describing the solid-liquid separation in a simplified test geometry of a decanter centrifuge. In addition, the influence of the rheological behavior on the flow in the test geometry can be observed for the first time.
Sexualization and Dehumanization of Women by Social Media Users in Namibia
Authors: Venditto Bruno , Set Beatha , Amaambo Rachel Ndinelao
Published: September 2022

The advancements in current sources of information and technology have resulted in our ‘real lives’ becoming inundated with and entangled with new media and ‘virtual’ environments. Social media promotes freedom of expression, and remains a largely unregulated interactive space, despite the various monitoring mechanisms introduced by social platform hosts and owners to control hate speech and other forms of abuse. It is becoming increasingly evident that the protection of anonymity on social media platforms promotes the proliferation of new forms of misogyny and offensive language directed towards women and individuals belonging to marginalised groups. This proliferation of online misogynistic hate speech ultimately exhibits oppressing mechanisms that aim to disempower, dehumanise and perpetuate gender-based violence against women. This paper discusses the results of exploring the use of dehumanising and abusive language expressed online, that targets prominent Namibian women in politics and business. The feminist theory, especially sexualization and objectification framework was employed to conceptually analyse depictions of dehumanisation of women in Namibia. Narratives from social media, such as Facebook and Twitter of public figures of Namibian women, were presented to justify cases of insulting and derogatory language. They expose the implications of sexualisation and dehumanisation of women’s human rights and freedom to participate actively in both public and social media spaces, and its potential to perpetuate gender-based violence in Namibia. The paper argues that contemporary social media has failed to create a conducive environment for critical and meaningful participation, which is free from sexualization, genderisation and dehumanisation, providing recommendations for the Namibian environment.
Stability Analysis and Prediction of Traffic Flow of Trucks at Road Intersections Based on Heterogenous Optimal Velocity and Artificial Neural Network Model
Authors: Olayode Isaac Oyeyemi , Tartibu Lagouge Kwanda , Campisi Tiziana
Published: September 2022

The evolution of traffic-related accidents caused by long, short, and medium trucks at signalized road intersections have been underemphasized in the last few years. Far, little attention has been paid to the modelling of trucks traffic flow using an artificial neural network model and evaluating the stability analysis of trucks depending on the heterogenous optimal velocity. This research evaluates the effect of trucks on some specific traffic flow features. Over the years, it has been deduced that trucks, irrespective of their sizes, significantly impact their surrounding traffic flow due to their body sizes and operational features. In this study, we focused on modelling the traffic flow of trucks at signalized road intersections using traffic flow variables such as speed, traffic volume, traffic density, and time as our inputs and outputs. The truck traffic data was collected using up-to-date equipment such as video cameras and inductive loop detectors from the South Africa transportation network. During the ANN modelling of the truck traffic flow, we used 956 traffic datasets divided into 70% for training and 15% each for testing and validation. The ANN model results show testing regression values of R2 (0.99901). This shows that the inputs and output are well correlated and the ANN model’s superiority in predicting truck traffic flow at signalized road intersections. Based on the HEOV model results, the result of the research indicates that in the mixed traffic flow of trucks in real-life scenarios, the proportion of different trucks on the signalized road intersections rather than the proportions of types of trucks can be used in the determination of traffic flow stability of each truck. This research extends our knowledge of truck traffic flow modelling and provides a blueprint for examining the stability analysis of long, short, and medium trucks in their immediate driving environment.
Development Agencies and Local Governments—Coexistence within the Same Territory
Authors: Garat de Marin Mirtha Silvana , Soriano Flores Emmanuel , Rodríguez Velasco Carmen Lili , Silva Alvarado Eduardo , Calderon Iglesias Ruben , Álvarez Roberto Marcelo , Gracia Villar Santos
Published: September 2022

This article proposes a discussion on the form of coexistence of local Development Agencies in Uruguay, with local governments in the face of the new scenarios marked by the decentralization process, initiated in the country with the Constitutional Reform of 1996 and culminating in February 2009, with the Law of Political Decentralization and Citizen Participation. The discussion applies in particular to the local development agency of the city of Rivera (ADR), located in the northeast of the country. A descriptive, mixed, bibliographic, documentary investigation was carried out with primary data collection to internal and external references to ADR. The results show that the coexistence of both institutions has been difficult, without defining clear roles. Promoting dialogue to define the role of each seems to be the great challenge facing the sustainability of the agency.
Earning Housing: Removing Barriers to Housing to Improve the Health and Wellbeing of Chronically Homeless Sex Workers
Authors: Macon Claire , Tai Eden
Published: September 2022

For many sex workers, accessing and maintaining housing is one of the central reasons for engaging in sex work. Simultaneously, one of the most stringent barriers to accessible and affordable housing is the stigma and discrimination against sex work as a livelihood. This paper explores the relationship between barriers to accessing housing for sex workers and the systems that hold the barriers in place. This paper is based on qualitative research conducted by Ocean State Advocacy’s research team. Using quantitative analysis of 100 surveys and qualitative analysis of 35 interviews conducted with sex workers living in Rhode Island, this paper discusses the ways housing improves the physical health, mental health, and overall wellbeing of sex workers. By including sex workers and centering their human rights in movements around housing equity and access, sex workers’ needs are prioritized while increasing understanding of stigma and systemic disenfranchisement within the field of housing justice.
The Social and Cultural Dimensions Associated with Death in Muslim Communities, a Case Study Khartoum City
Authors: Ahmed Osman Sirajeldeen , Abdalrahman Elsayed , Al Rawashdeh Alaa Zuhir , Al Arab Asma Rebhi
Published: September 2022

In Arab universities, sociologists rarely discuss the sociology of death. By studying social and cultural variables along with subjective and objective meanings of death, this paper contributes to filling this gap in research on death in a Sudanese urban area. Furthermore, the study examines the relationship between the burial of the dead and the time and place of their burial, social status, relatives, and religious affiliation as they relate to their burial. A major objective of the research is to explore the social and cultural dimensions of death in Sudanese communities. Data were collected using interviews and observations in the field using the descriptive method. Death is more of a social than a biological fact; therefore, the general findings of this research are about declaration of death, and what it implies about social cohesion. Burial and social acts following death are acts that express social meanings, and further, indicate how biological death has occurred. Based on variables such as social status, family relationship, and religious affiliation, it can be seen that the deceased person and/or family holds these beliefs.
Comparative Study of Trehalose and Trehalose 6-Phosphate to Improve Antioxidant Defense Mechanisms in Wheat and Mustard Seedlings under Salt and Water Deficit Stresses
Authors: Mohsin Sayed Mohammad , Fardus Jannatul , Nagata Atsushi , Tamano Nobuhisa , Mitani Hirofumi , Fujita Masayuki
Published: September 2022

Trehalose 6-phosphate (T6P) regulates sugar levels and starch metabolism in a plant cell and thus interacts with various signaling pathways, and after converting T6P into trehalose (Tre), it acts as a vital osmoprotectant under stress conditions. This study was conducted using wheat (Triticum aestivum L. cv. Norin 61) and mustard (Brassica juncea L. cv. BARI sharisha 13) seedlings to investigate the role of Tre and T6P in improving salt and water deficit stress tolerance. The seedlings were grown hydroponically using Hyponex solution and exposed to salt (300 and 200 mM NaCl for wheat and mustard, respectively) and water deficit (20 and 12% PEG 6000 for wheat and mustard, respectively) stresses with or without Tre and T6P. The study demonstrated that salt and water deficit stress negatively influenced plant growth by destroying photosynthetic pigments and increasing oxidative damage. In response to salt and water deficit stresses, the generation of H2O2 increased by 114 and 67%, respectively, in wheat seedlings, while in mustard, it increased by 86 and 50%, respectively. Antioxidant defense systems were also altered by salt and water deficit stresses due to higher oxidative damage. The AsA content was reduced by 65 and 38% in wheat and 61 and 45% in mustard under salt and water deficit stresses, respectively. The subsequent negative results of salinity and water deficit can be overcome by exogenous application of Tre and T6P; these agents reduced the oxidative stress by decreasing H2O2 and TBARS levels and increasing enzymatic and non-enzymatic antioxidants. Moreover, the application of Tre and T6P decreased the accumulation of Na in the shoots and roots of wheat and mustard seedlings. Therefore, the results suggest that the use of Tre and T6P is apromising strategy to alleviate osmotic and ionic toxicity in plants under salt and water deficit stresses.
Team Leader’s Conflict Management Style and Team Innovation Performance in Remote R&D Teams—With Team Climate Perspective
Authors: Yin Jielin , Qu Meng , Li Miaomiao , Liao Ganli
Published: September 2022

Remote work has become a new way of working due to the influence of the COVID-19 pandemic, which inevitably aggravates team conflicts caused by cognitive differences given the lack of face-to-face communication. With a team climate perspective, this paper investigates the impact of the team leader’s conflict management style on team innovation performance in remote R&D teams in China based on social cognition theory and two-dimension theory. A theoretical model is constructed which describes the mediating effect of team psychological safety and the moderating impact of team trust. Paired data from 118 remote R&D teams in China including 118 leaders and 446 members were collected. The results show that team leader’s cooperative conflict management style is conducive to enhancing team psychological safety and further effectively improves team innovation performance. Therefore, team psychological safety has a mediating effect between team leader’s cooperative conflict management style and team innovation performance. In addition, team trust has a negative moderating effect between team leader’s cooperative conflict management style and team psychological safety. Besides, this study obtains some valuable culture-related insights and provides more views for conflict management research in the cross-cultural context since the samples in this study are from China, a society with high collectivism, which is different from the western cultural context from which many conflict management theories develop.
Policy Cognition, Household Income and Farmers’ Satisfaction: Evidence from a Wetland Ecological Compensation Project in the Poyang Lake Area at the Micro Level
Authors: Pang Jie , Jin Leshan , Yang Yujie , Li Heng , Chu Zongling , Ding Fei
Published: September 2022

The paper follows a field survey of 773 rural households in 14 towns in five prefectures (cities and districts) around the Poyang Lake, and uses a multivariate ordered logistic model to explore the factors influencing satisfaction with wetland ecological compensation policies (WECPs) from the perspective of rural households’ subjective cognition of WECPs and income factors. The research shows the following. (1) the overall score for satisfaction of farmers with WECPs is 3.56, which indicates satisfaction between “fair” and “fairly satisfied,” and there is room for policy optimization. (2) The subjective cognition of policies and the income-related factors have significant impacts on the satisfaction of farmers with WECPs. Among them, cognition of policy objectives, evaluation of compensation rates, timely distribution of compensations, government supervision, changes in household incomes and importance of compensation on households all have significant positive influences on policy satisfaction. (3) The degree of education, the proportion of household labor forces and the proportion of household non-agricultural incomes have a significant positive impact on the policy satisfaction of farmers. Therefore, in future policy implementation, we should strengthen publicity and guidance of the policy, raise compensation rates appropriately, strengthen government supervision, pay attention to rural livelihood, and establish an ecological compensation mechanism featuring fairness and long-term effectiveness.
Assessing Spatial and Temporal Changes of Natural Capital in a Typical Semi-Arid Protected Area Based on an Ecological Footprint Model
Authors: Sobhani Parvaneh , Esmaeilzadeh Hassan , Sadeghi Seyed Mohammad Moein , Wolf Isabelle D. , Esmaeilzadeh Yaghoub , Deljouei Azade
Published: September 2022

Exploring spatial and temporal changes in protected areas (PAs) is essential for protecting natural capital and creating a harmonious relationship between humans and nature. This study has assessed land use/land cover (LULC) changes in the Jajrud, a Protected Area with a semi-arid climate zone in Iran (covers an area of 18,814 km2), to assess the sustainability of the use of natural resources using Landsat imagery from 1989 to 2018. Likewise, Ecological Footprint accounts (including the sum of biological, freshwater, energy, and pollution) and changes in the per-capita Ecological Carrying Capacity were investigated to uncover Ecological Deficits. The Ecological Pressure Index was used to explore driving factors of natural capital utilization in each of the various identified zones. Between 1989 and 2018, high-density pastures decreased the most in Jajrud, while built-up land increased the most. Likewise, the Ecological Footprint increased while the Ecological Carrying Capacity decreased, increasing Ecological Deficit quantities. Driving factors for the use of natural capital differs among the various zones due to differing management goals, type of uses, and human activity development. As supply and demand for natural resources were clearly out of an imbalance between the supply and demand of natural resources and exceeded the maximum tolerable limits in Jajrud, a change in production and consumption patterns is necessary. This case study has practical importance for establishing mathematical models to reveal the patterns of LULC, ecological footprint, ecological deficit, and ecological pressure indices in a typical PA in a semi-arid region of Iran. Our approach is advisable for semi-arid PAs in Iran and regions with similar attributes in other countries.
A Reflection on the Response to Sudden-Onset Disasters in the Post-Pandemic Era: A Graded Assessment of Urban Transportation Resilience Taking Wuhan, China as an Example
Authors: Wang Jingzhao , Yan Jincheng , Ding Keyuan , Li Qian , Liu Yehao , Liu Xueliang , Peng Ran
Published: September 2022

The COVID-19 pandemic has led to thinking about the response to sudden-onset disasters, for which the transportation resilience of urban areas is crucial. The purpose of paper is to provide a graded assessment of urban transportation resilience to help city managers target policies and plans. Wuhan, the first city in China to be severely hit by COVID-19, was selected as the case study for this research. Based on an extensive survey of the travel characteristics of residents in central urban areas, the concept of “travel mode shift” was combined to classify residents into four modes, including non-motorized conventional travel, non-motorized over-distance travel, motorized adaptable travel and motorized non-substitutable travel. The potential transportation stoppages in different levels of epidemic impact were then divided into three scenarios, corresponding to each of the city’s three levels of transportation resilience. The concept of MWD (Maximum Willingness Distance) in active travel mode was further developed, which was divided into WMWD (Walking Maximum Willingness Distance) and RMWD (Riding Maximum Willingness Distance). Finally, a hierarchical assessment model of urban transportation resilience is developed based on the MWD distance threshold. Besides, the average income level of urban residents was also included in the assessment system. The following research conclusions were drawn: (1) The degree of transportation resilience in Wuhan showed an “S-curve” relationship with RMWD, with thresholds at RMWD = 2.5 km, 11 km and 23 km respectively. (2) The resilience of transportation in the suburbs of the city was weaker than in the city center, and the gap between the two increases as the RMWD increases, but the share of motorized transportation in short distance trips in the city center was still higher than desirable. (3) The upper-income groups in the city had more flexible travel options, while the lower income groups were less resilient to travel. Based on the results of the study, it is recommended that city managers can identify areas of low resilience and critical distance thresholds that may lead to sudden changes in transportation resilience in the event of a sudden disaster. This will lead to the development of improved policies. The special needs of socially disadvantaged groups should also be taken more into account in this process.
Rural Application of a Low-Pressure Reverse Osmosis Desalination System Powered by Solar–Photovoltaic Energy for Mexican Arid Zones
Authors: Cervantes-Rendón Esmeralda , Ibarra-Bahena Jonathan , Cervera-Gómez Luis E. , Romero Rosenberg J. , Cerezo Jesús , Rodríguez-Martínez Antonio , Dehesa-Carrasco Ulises
Published: September 2022

A reverse osmosis system driven by photovoltaic energy is an eco-friendly and sustainable way to produce freshwater in rural areas without connection to a power grid and with available brackish water sources. This paper describes a project where a photovoltaic-driven low-pressure reverse osmosis system (LPRO-PV) was designed, tested under laboratory conditions, and installed in Samalayuca, Chihuahua, Mexico, to evaluate the technical feasibility and social impact of this technology. The LPRO-PV system was tested with synthetic water with a salinity of 2921 ± 62.3 mg/L; the maximum freshwater volume produced was 1.8 ± 0.06 m3/day with a salinity value of 91 ± 1.9 mg/L. The LPRO-PV system satisfied the basic freshwater requirements for a local family of three members for one year, including the mobility-restriction period due to the COVID-19 pandemic. The social evaluation analysis reflects the importance of considering the technical aspects derived from the experimental tests, as well as the users’ perception of the performance and operation of the system. As a result of the implementation of this technology and the benefits described by the users, they committed to the maintenance activities required for the LPRO-PV system’s operation. This technology has great potential to produce fresh water in arid and isolated regions with high-salinity groundwater sources, thus fulfilling the human right to safe and clean drinking water.
Blind Spot for Pioneering Farmers? Reflections on Dutch Dairy Sustainability Transition
Authors: Hoes Anne-Charlotte , Aramyan Lusine
Published: September 2022

This study explores the questions of how to govern the transition towards sustainable farming in a responsible and inclusive manner by exploring the Dutch dairy case. Sustainability transition is about fundamental social–technical changes to address the grand challenges that society faces today. It includes breaking down and phasing out unsustainable practice as well as scaling up sustainable alternatives. Transition literature argues that governments should implement a mix of transition tasks to give direction, support the new and destabilase the unsustainable. In addition, market-based instruments (MBIs) and policy interventions rewarding sustainable farming stimulate transition. This study illustrates that strong and prolonged pressure of not meeting international environmental agreements triggered the implementation of stronger policy interventions that destabilize the unsustainable. However, less policy attention seems to be given to supporting the “new”, such as pioneering alternative farmers who develop sustainable alternatives to mainstream farming. To achieve more responsible and inclusive sustainability transitions, it is important to implement tailor-made policies that support pioneering alternative farmers who are already taking steps in developing sustainable farms which, in addition to food, provide ecological and other benefits to community.
Titania Thin Film Coated Glass for Simultaneous Ammonia Degradation and UV Light Blocking Layer in Photovoltaics
Authors: Juraić Krunoslav , Bohač Mario , Plaisier Jasper Rikkert , Hodzic Aden , Dubček Pavo , Gracin Davor , Grčić Ivana , Marčec Jan , Čižmar Tihana , Gajović Andreja
Published: September 2022

In this work, we have investigated the potential dual application of TiO2 thin films as a photocatalyst for ammonia degradation, and as a UV light blocking layer in c-Si photovoltaics. For this purpose, we deposited a series of TiO2 thin films on a glass substrate by reactive magnetron sputtering and analysed the influence of the deposition parameters (O2/Ar working gas content and pressure) on the structural, optical and photocatalytic properties. All samples are nanocrystalline anatase TiO2 and have a uniform surface (RMS roughness < 5 nm) in a wide range of magnetron sputtering deposition parameters. They are transparent in the Vis/NIR spectral range and strongly absorb light in the UV range above the optical bandgap energy (3.3 eV), which makes them suitable for the use as UV blocking layers and photocatalysts. The photocatalytic properties were studied in a mini-photocatalytic wind tunnel reactor by examining ammonia degradation. A kinetic study was performed to estimate the reaction rate constants for all samples. The intrinsic reaction rate constant confirmed the crucial role of surface morphology in ammonia decomposition efficiency.
The Impact of Knowledge Power on Enterprise Breakthrough Innovation: From the Perspective of Boundary-Spanning Dual Search
Authors: Wang Jianjun , Cao Ning , Wang Yulu , Wang Yu
Published: September 2022

Breakthrough innovation is key for enterprises to achieve extraordinary development, transformation and upgrading. In the open innovation environment, breakthrough innovation activities are considered to be closely related to enterprise knowledge power and external search strategies. However, there has been no systematic empirical study to explore the internal relationships among the three factors mentioned above. Based on resource dependence theory, this paper explored the impact of knowledge power on enterprise breakthrough innovation from the perspective of boundary-spanning dual search, and examined the moderating effect of absorptive capacity. Using the sample data of 239 knowledge intensive enterprises from China, this paper empirically tested the research hypothesis. The results showed that: (1) the two dimensions of knowledge power (including knowledge control and knowledge influence) have a significant positive impact on enterprise breakthrough innovation; (2) the breadth and depth of boundary-spanning search play a mediating role between knowledge power and enterprise breakthrough innovation; (3) enterprise absorptive capacity significantly strengthens the positive effect of boundary-spanning search on enterprise breakthrough innovation. This study clarified the relationship between knowledge power and breakthrough innovation and provided theoretical support for enterprises to actively take advantage of knowledge power to improve their breakthrough innovation performance.