bluuebunny/crossref_metadata_2025 huggingface dataset:
Sensors, Students, and Self: Exploring Knowledge, Self-Efficacy, and Interest Impact of Ocean Sensor Learning on High School Marine Science Students
Authors: Windleharth Travis W. , Katagiri Colin
Published: February 2022

This study examined the effect of online technical lessons of how ocean sensors function on student interest in ocean science technology, as well as knowledge gain outcomes. Additionally, the study contributes novel findings to sensor-based learning literature by measuring changes to self-efficacy and confidence gains stemming from sensor-based learning, as well as changes in interest in ocean careers. The area of educational focus was also novel—focusing on how the sensors themselves function, not just what they do. Precipitated by COVID-19 pandemic constraints, the team used a remote learning approach to provide lessons on sensors at a distance, providing an additional opportunity to contrast this approach with previously studied hands-on learning modes. A sample of students from four high school marine science classes completed two assessments both before and after a series of lessons on ocean sensors. This included a self-reported survey (N = 48), and an open-ended knowledge assessment (N = 40). Results showed modest gains in knowledge assessments, and students experienced statistically significant gains in confidence in their ability to explain what sensors are, confidence in their ability to use sensors and understand resulting data, and confidence in accuracy of sensor data (p < 0.05). No changes were observed for several measures of interest in ocean technology, nor were there changes in an already high belief that understanding these sensors is important to marine science careers. Notably, these findings measure a positive shift in several measures of self-efficacy and confidence, which is a new finding for sensor-based learning. The findings also contrast with prior related work that included hands-on activities with sensors, which reported an increase in interest after working with sensors, whereas this intervention did not. This suggests a hands-on component is key to increasing interest in ocean technology.
Finding the Optimal Pose of 2D LLT Sensors to Improve Object Pose Estimation
Authors: Heczko Dominik , Oščádal Petr , Kot Tomáš , Boleslavský Adam , Krys Václav , Bém Jan , Virgala Ivan , Bobovský Zdenko
Published: February 2022

In this paper, we examine a method for improving pose estimation by correctly positioning the sensors relative to the scanned object. Three objects made of different materials and using different manufacturing technologies were selected for the experiment. To collect input data for orientation estimation, a simulation environment was created where each object was scanned at different poses. A simulation model of the laser line triangulation sensor was created for scanning, and the optical surface properties of the scanned objects were set to simulate real scanning conditions. The simulation was verified on a real system using the UR10e robot to rotate and move the object. The presented results show that the simulation matches the real measurements and that the appropriate placement of the sensors has improved the orientation estimation.
A New Digital Platform for Collecting Measurement Data from the Novel Imaging Sensors in Urology
Authors: Rybak Grzegorz , Strzecha Krzysztof , Krakós Marek
Published: February 2022

The use of UT and EIT technologies gives the opportunity to develop new, effective, minimally invasive diagnostic methods for urology. The introduction of new diagnostic methods into medicine requires the development of new tools for collecting, processing and analysing the data obtained from them. Such system might be seen as a part of the electronic health record EHR system. The digital medical data management platform must provide the infrastructure that will make medical activity possible and effective in the presented scope. The solution presented in this article was implemented using the newest computer technologies to obtain advantages such as mobility, versatility, flexibility and scalability. The architecture of the developed platform, technological stack proposals, database structure and user interface are presented. In the course of this study, an analysis of known and available standards such as Hl7, RIM, DICOM, and tools for collecting medical data was performed, and the results obtained using them are also presented. The developed digital platform also falls into an innovative path of creating a network of sensors communicating with each other in the digital space, resulting in the implementation of the IoT (Internet of Things) vision. The issues of building software based on the architecture of microservices were discussed emphasizing the role of message brokers. The selected message brokers were also analysed in terms of available features and message transmission time.
Enabling Green Crowdsourced Social Delivery Networks in Urban Communities
Authors: Choi Kevin , Bedogni Luca , Levorato Marco
Published: February 2022

With the ever-increasing popularity of wearable devices, data on the time and location of popular walking, running, and bicycling routes is expansive and growing rapidly. These data are currently used primarily for route discovery and mobile context awareness, as it provides precise and updated information about urban dynamics. We leverage these data to build ad hoc transportation flows, and we present a novel model that creates delivery networks from these zero-emission transportation flows. We evaluate the model using data from two popular datasets, and our results indicate that such networks are indeed possible, and can help reduce traffic, emissions, and delivery times. Moreover, we demonstrate how our results can be consistently reproduced in different cities with different subsets of carriers. We then extend our work into predicting routes of vehicles, hence possible delivery flows, based on the traces history. We conclude this paper by laying the groundwork for a future real-world study.
Intelligent Transportation Logistics Optimal Warehouse Location Method Based on Internet of Things and Blockchain Technology
Authors: Chen Jun , Xu Shiyan , Liu Kaikai , Yao Shuqi , Luo Xiao , Wu Huan
Published: February 2022

In order to cut down on costs to the greatest possible extent, enterprises hope to distribute goods to different customers at the lowest costs possible. Based on this, this paper proposes an optimal location method for an intelligent transportation logistics warehouse. This scheme combines a variety of complex mechanisms to allow IoT devices to provide input. The scheme makes full use of the irreducibility of a blockchain system to promote the development and design of blockchain logistics applications. This method is aimed at tracking the progress of transportation of products in the whole supply chain. Experimental results show that, compared with traditional methods, the optimal positioning method has the advantages of fewer calculations, a high positioning accuracy, and a low overall cost, and it obtains the best warehouse positioning results. Based on the Internet of Things and blockchain technology, the application of intelligent logistics systems enables enterprises to intuitively understand their current inventory and the transportation status of goods, thus better controlling changes in enterprise resources.
Graph Representation Learning-Based Early Depression Detection Framework in Smart Home Environments
Authors: Kim Jongmo , Sohn Mye
Published: February 2022

Although the diagnosis and treatment of depression is a medical field, ICTs and AI technologies are used widely to detect depression earlier in the elderly. These technologies are used to identify behavioral changes in the physical world or sentiment changes in cyberspace, known as symptoms of depression. However, although sentiment and physical changes, which are signs of depression in the elderly, are usually revealed simultaneously, there is no research on them at the same time. To solve the problem, this paper proposes knowledge graph-based cyber–physical view (CPV)-based activity pattern recognition for the early detection of depression, also known as KARE. In the KARE framework, the knowledge graph (KG) plays key roles in providing cross-domain knowledge as well as resolving issues of grammatical and semantic heterogeneity required in order to integrate cyberspace and the physical world. In addition, it can flexibly express the patterns of different activities for each elderly. To achieve this, the KARE framework implements a set of new machine learning techniques. The first is 1D-CNN for attribute representation in relation to learning to connect the attributes of physical and cyber worlds and the KG. The second is the entity alignment with embedding vectors extracted by the CNN and GNN. The third is a graph extraction method to construct the CPV from KG with the graph representation learning and wrapper-based feature selection in the unsupervised manner. The last one is a method of activity-pattern graph representation based on a Gaussian Mixture Model and KL divergence for training the GAT model to detect depression early. To demonstrate the superiority of the KARE framework, we performed the experiments using real-world datasets with five state-of-the-art models in knowledge graph entity alignment.
Deep-Learning-Based Resource Allocation for Time-Sensitive Device-to-Device Networks
Authors: Zheng Zhe , Chi Yingying , Ding Guangyao , Yu Guanding
Published: February 2022

Ultra-reliable and low-latency communication (URLLC) is considered as one of the major use cases in 5G networks to support the emerging mission-critical applications. One of the possible tools to achieve URLLC is the device-to-device (D2D) network. Due to the physical proximity of communicating devices, D2D networks can significantly improve the latency and reliability performance of wireless communication. However, the resource management of D2D networks is usually a non-convex combinatorial problem that is difficult to solve. Traditional methods usually optimize the resource allocation in an iterative way, which leads to high computational complexity. In this paper, we investigate the resource allocation problem in the time-sensitive D2D network where the latency and reliability performance is modeled by the achievable rate in the short blocklength regime. We first design a game theory-based algorithm as the baseline. Then, we propose a deep learning (DL)-based resource management framework using deep neural network (DNN). The simulation results show that the proposed DL-based method achieves almost the same performance as the baseline algorithm, while it is more time-efficient due to the end-to-end structure.
Signal Source Positioning Based on Angle-Only Measurements in Passive Sensor Networks
Authors: Chen Yidi , Wang Linhai , Zhou Shenghua , Chen Renwen
Published: February 2022

Some passive sensors can measure only directions of arrival of signals, but the real positions of signal sources are often desirable, which can be estimated by combining distributed passive sensors as a network. However, passive observations should be correctly associated first. This paper studies the multi-target data association and signal localization problem in distributed passive sensor networks. With angle-only measurements from distributed passive sensors, multiple lines in a 3-dimensional (3D) scenario can be built and then those that will intersect in a small volume in 3D are classified into the same source. The center of the small volume is taken as an estimate of the signal source position, whose statistical distributions are formulated. If the minimum distance is less than an association threshold, then two lines are considered to be from the same signal source. In numerical results, the impacts of angle measurement accuracy and platform self-positioning accuracy are analyzed, indicating that this method can achieve a prescribed data association rate and a high positioning performance with a low computation cost.
Unified Accurate Attitude Control for Dual-Tiltrotor UAV with Cyclic Pitch Using Actuator Dynamics Compensated LADRC
Authors: Wang Zexin , Wang Yingxun , Cai Zhihao , Zhao Jiang , Liu Ningjun , Zhao Yanqi
Published: February 2022

This paper proposes a unified attitude controller based on the modified linear active disturbance rejection control (LADRC) for a dual-tiltrotor unmanned aerial vehicle (UAV) with cyclic pitch to achieve accurate attitude control despite its nonlinear and time-varying characteristics during flight mode transitions. The proposed control algorithm has higher robustness against model mismatch compared with the model-based control algorithms. The modified LADRC utilizes the state feedbacks from the onboard sensors like IMU and Pitot tube instead of the mathematical model of the plane. It has less dependency on the accurate dynamics model of the dual-tiltrotor UAV, which can hardly be built. In contrast to the original LADRC, an actuator model is integrated into the modified LADRC to compensate for the non-negligible slow rotor flapping dynamics and servo dynamics. This modification eliminates the oscillation of the original LADRC when applied on the plant with slow-response actuators, such as propeller and rotors of the helicopter. In this way, the stability and performance of the controller are improved. The controller replaces the gain-scheduling or the control logic switching by a unified controller structure, which simplifies the design approach of the controller for different flight modes. The effectiveness of the modified LADRC and the performance of the unified attitude controller are demonstrated in both simulation and flight tests using a dual-tiltrotor UAV. The attitude control error is less than ±4° during the conversion flight. The control rising time in different flight modes is all about 0.5 s, despite the variations in the airspeed and tilt angle. The flight results show that the controller guarantees high control accuracy and uniform control quality in different flight modes.
Ensemble-Based Bounding Box Regression for Enhanced Knuckle Localization
Authors: Vyas Ritesh , Williams Bryan M. , Rahmani Hossein , Boswell-Challand Ricki , Jiang Zheheng , Angelov Plamen , Black Sue
Published: February 2022

The knuckle creases present on the dorsal side of the human hand can play significant role in identifying the offenders of serious crime, especially when evidence images of more recognizable biometric traits, such as the face, are not available. These knuckle creases, if localized appropriately, can result in improved identification ability. This is attributed to ambient inclusion of the creases and minimal effect of background, which lead to quality and discerning feature extraction. This paper presents an ensemble approach, utilizing multiple object detector frameworks, to localize the knuckle regions in a functionally appropriate way. The approach leverages from the individual capabilities of the popular object detectors and provide a more comprehensive knuckle region localization. The investigations are completed with two large-scale public hand databases which consist of hand-dorsal images with varying backgrounds and finger positioning. In addition to that, effectiveness of the proposed approach is also tested with a novel proprietary unconstrained multi-ethnic hand dorsal dataset to evaluate its generalizability. Several novel performance metrics are tailored to evaluate the efficacy of the proposed knuckle localization approach. These metrics aim to measure the veracity of the detected knuckle regions in terms of their relation with the ground truth. The comparison of the proposed approach with individual object detectors and a state-of-the-art hand keypoint detector clearly establishes the outperforming nature of the proposed approach. The generalization of the proposed approach is also corroborated through the cross-dataset framework.
Loss of Visual Reference in U.S. Aviation: An Analysis of 129 Accidents
Authors: Kalagher Hilary , de Voogt Alex
Published: February 2022

A “loss of visual reference” is a term used by the National Transportation and Safety Board investigators to describe a situation in which the pilot has lost reference to the horizon or ground. Previous research has largely focused on the conditions that are often associated with a loss of visual reference (e.g., spatial disorientation) instead of the term itself. The purpose of the present study is to examine the accident and pilot characteristics that are associated with a loss of visual reference and the extent to which both are associated with fatalities. A total of 129 accident reports from 2008 through 2020 were extracted from the NTSB online database in which the term loss of visual reference appeared in the event category. Fatal accidents, which made up more than half of the dataset, were more likely to have occurred during the en-route phase of flight compared to all of the other phases of flight combined. The reports in which “decision making” or “decision making/judgment” was present were more likely to be for fatal accidents compared to reports in which the terms were not listed. It is the pilot’s decision and lack of attention that are most commonly associated with accidents in which a loss of visual reference occurred. Decisions that are likely to cause a loss of visual reference include initiating or continuing in adverse weather or light conditions. The dangers of loss of visual reference need to be part of ongoing training of pilots as opposed to their initial training only.
Influence of National Culture in Companies with Different Ownership on Employees’ CSR Perception in a Developing Country: The Case of Serbia
Authors: Radovanović Goran , Miletić Ljiljana , Karović Samed , Mijatović Marijana Dukić , Bubulj Milan
Published: February 2022

Starting from the fact that perceptions of employees might be related to national culture and our previous finding that CSR perception by employees depends on company ownership, in the present research, we aim at the investigation of relations between CSR and national culture perception by employees’ dependence on company ownership in the specific context of Serbia as a developing post-socialist country. Questionnaire-based research was conducted among employees in public and private companies in Serbia with domestic and foreign ownership. The results pointed out that both CSR and national culture perceptions are highly dependent on company ownership with the dependence of CSR perception on national culture perception by employees in public but not private companies. The obtained results point out that in private companies, excessive adoption of managerial practices not aligned with national culture resulted in shifts in perception of national culture, as well as in divergence between national culture and perceptions of CSR activities.
Strengthening Agroecology with the Political Pedagogy of Peasant Organisations: A Case Study of Baserritik Mundura in the Basque Country
Authors: Casado Beatriz , Urretabizkaia Leticia , Begiristain-Zubillaga Mirene , Martinez Zesar
Published: February 2022

La Vía Campesina organisations have identified the area of education and training as a strategic and priority arena of intervention to bring about change in the political-pedagogical perspective. This involves rethinking and redesigning the conventional training processes towards the collective experiences of learning, organisation, exchange and living. With this approach in mind, and based on the experiences and educational contributions made by peasant organisations, this paper presents the systematisation of the Baserritik Mundura experience, analysing and sharing the learning derived from this case study and establishing the integral role of the pedagogic proposal as an axis for systematisation. This analysis, from the logic of the systematisation of processes, promulgates the learnings of this agroecological training experience while exposing both its strengths and weaknesses. We present the learning linked to the pedagogic dimensions that, through a cross-over method, aim to create a multidimensional educational environment which transforms our subjectivities, practices and the beliefs that sustain them. This learning is presented in eight main areas related to: (1) organicity, (2) alternation, (3) the mystical and ludic-cultural dimension, (4) the contents, subjects and teaching team, (5) the proposal as a whole and its perspective of popular education and action research, (6) the transversality of the feminist perspective, (7) linguistic plurality and (8) the pedagogic political support of the process. In addition, we present considerations related to the learning identified in the systematisation itself. On the one hand, we look at the lack of training processes in the official university context related to an alternation system with an organicity linked to the territory, and the need for the practical development of a dynamic of the collective construction of knowledge with a view toward transforming the logics that underpin the existing hegemonic ideologies. On the other hand, we point out the need for a debate regarding the epistemological perspective and integral, experiential and emancipatory pedagogical perspectives. Even with their limitations and challenges, these proposals have great potential to train, organise, politicise, excite and connect people from different fields towards the construction of a fairer, healthier and more sustainable agroecological agri-food system, based on food sovereignty and the everyday lives of people
The Impact of COVID-19 on Public/Third-Sector Collaboration in the Italian Context
Authors: Corvo Luigi , Pastore Lavinia , Mastrodascio Marco , Tricarico Luca
Published: February 2022

The extent of the effects produced by the ongoing COVID-19 pandemic on the collaboration between public administrations and the third sector is currently unclear. Undoubtedly, as in any other organizations, social enterprises and non-profit organizations have been severely affected by the spread of COVID-19, especially regarding their relationship with the public sector. Based on an analysis of 563 Italian third sector entities (ETSs) that responded to an online survey launched in March 2020, this study aims to explore the current state and extent of the potential change in the collaboration between organizations belonging to the third sector and the Italian public administration system in response to the COVID-19 emergency. The results have shown that only approximately one-third of the organizations have been asked to jointly contribute with the public sector to contain the negative effects of the pandemic. In other cases, spontaneous support initiatives have been undertaken to manage the crisis. The findings have also revealed that the COVID-19 pandemic has affected the internal operating and functioning mechanisms of the organizations operating in the third sector. The study concludes with a forecast of the potential exacerbation of the difficulties currently faced by the third sector and with the provision of future strategic paths to contain the health, social and economic effects of the pandemic.
Assessment of Power System Sustainability and Compromises between the Development Goals
Authors: Wang Diankai , Gryshova Inna , Balian Anush , Kyzym Mykola , Salashenko Tetiana , Khaustova Viktoriia , Davidyuk Olexandr
Published: February 2022

Ensuring the sustainability of the European power system is one of the key priorities in the implementation of the EU’s ambitious plans to become climate-neutral by 2050. The uniqueness of the power systems of the EU member states necessitates their assessment and comparison. The article offers a composite indicator, namely, the power system sustainability index (PSS index), to assess the current level of the development of the power systems via three dimensions (social, economic, and environmental) and eight local indicators: the household electricity consumption per capita; the commercial electricity consumption per GDP; the external dependency of the power system; the energy efficiency of the generation; the capacity utilization factor; the share of organic fossil fuels; the share of renewable energy resources; and the greenhouse gas (GHG) emissions per unit of primary energy source. The “energy mix” is defined as the key impact factor, which has a contradictory effect on the local power system sustainability (LPSS) indicators, which can be represented as a set of regression models. The data of the regression analysis can be used for performing a multiobjective optimization by the local indicators, and they can determine the vectors of change required to ensure the sustainability of the power system. The research results prove that it is possible to minimize the GHG emissions per unit of primary energy source and maximize the energy efficiency of generation, while reducing the capacity utilization and increasing the external dependency of the power system.
Provincial Allocation of Energy Consumption, Air Pollutant and CO2 Emission Quotas in China: Based on a Weighted Environment ZSG-DEA Model
Authors: Song Jiekun , Chen Rui , Ma Xiaoping
Published: February 2022

Air pollutants and CO2 emissions have a common important source, namely energy consumption. Considering fairness and efficiency, the provincial coordinated allocation of energy consumption, air pollutant emission, and carbon emission (EAC) quotas is of great significance to promote provincial development and achieve national energy conservation and emission reduction targets. A weighted environment zero-sum-gains data envelopment analysis (ZSG-DEA) model is constructed to optimize the efficiency of the initial provincial quotas under the fairness principle, so as to realize the fairness and efficiency of allocation. The empirical analysis in 2020 shows that the optimal allocation scheme proposed in this study is better than the national planning scheme in terms of fairness and efficiency, and the optimal scheme based on the initial allocation of priority order of “capacity to pay egalitarianism > historical egalitarianism > population egalitarianism” is the fairest. The optimal allocation scheme in 2025 can achieve absolute fairness. In this scheme, the pressures of energy conservation and emission reduction undertaken by different provinces vary greatly. The implementation of regional coordinated development strategies can narrow this gap and improve the enforceability of this scheme. Combined with the analysis of energy conservation and emission reduction in seven categories and three major national strategic regions, we put forward corresponding measures to provide decision support for China’s energy conservation and emission reduction.
Road Network Vulnerability Based on Diversion Routes to Reconnect Disrupted Road Segments
Authors: Redzuan Amir Al Hamdi , Zakaria Rozana , Anuar Aznah Nor , Aminudin Eeydzah , Yusof Norbazlan Mohd
Published: February 2022

The reliance on roads to provide fluent mobilization has raised great concern when facing functional degradation. Disruption of the critical segments of a road network may significantly increase the distance traveled by a community. This paper proposes a method for measuring road network vulnerability when facing disruption by assessing all road segments within a network. The assessment is based on two of the shortest disjointed diversion routes from one end of the segment to the other, supporting the strategy of reaching equilibrium flow in an emergency condition. To generate diversion routes for the purpose of reconnecting a disrupted segment, the shortest path patterns are generated through the formation of adjacent polygons using GIS. Accordingly, this paper proposes a segment vulnerability index based on the support of diversion routes. Additionally, the model introduces supporting vulnerability, a parameter for measuring the potential of a road segment becoming a supporting diversion route when its surrounding segments are disrupted. By adopting the Malaysian Peninsular road network as a case study, the developed index can assist transportation agencies in planning and maintaining road assets while prioritizing vulnerable road segments relative to the entire road network.
Contaminant Flushing in Water Distribution Networks Incorporating Customer Faucet Control
Authors: Marlim Malvin S. , Kang Doosun
Published: February 2022

Contamination events in water distribution networks (WDNs) begin with contaminant inception in the network. WDNs respond to events according to the detection, stopping service, and recovery phases. The recovery phase aims to remove hazardous substances by flushing them out so that the network can return to normal conditions. Flushing must be conducted efficiently and safely. The contaminated water is removed by allowing it to flow from outlet points in the network, which is enabled by displacing it with clean water from the source. Conventionally, a hydrant was used as the outlet point. Recent advancements in information and communication technology allow the use of electronic media to broadcast warnings and guidance rapidly. Water utilities can convey information to customers as part of the flushing scheme by notifying them to open and close their faucets at designated times. In this study, the viability of customer involvement in decontamination was examined. The proposed method was tested by evaluating its effectiveness in terms of the time and volume of water needed for decontamination, and the change in hydraulics to drain a fully contaminated district metered area (DMA). A comparable performance to hydrant flushing was found after testing in two actual DMA-sized WDNs.
Seasonal Abundance and Distribution Patterns of Microplastics in the Lis River, Portugal
Authors: Sá Bárbara , Pais Joana , Antunes Joana , Pequeno João , Pires Ana , Sobral Paula
Published: February 2022

The majority of microplastics (MP) found in the marine environment have land-based sources and rivers are known as carriers of these particles to the ocean. This work is the first to study MP in the Lis River Basin and coastal shoreline (total nine sampling sites) and the potential relationship with inputs from 105 companies/units. We report the seasonal abundance, typology, colour, size, and polymer distribution of MP in surface water and sediment. To the collected samples, a digestion protocol was applied, followed by filtration. For sediment, an MP density separation was performed prior to filtration. MP were mostly fibres (0.02 to 1111.11 items.m−3 in water and 10.66 to 1609.64 items.kg−1 in sediment) and fragments (0.02 to 2311.11 items.m−3 in water and 10.66 to 501.01 items.kg−1 in sediment). The most frequent colours were transparent and blue, and MP were mostly smaller than 1 mm in water and 2 mm in sediment samples. The most abundant polymers in water were polyethylene (37%), polyacrylate (18%) and polystyrene (18%), and in sediment, polyethylene terephthalate (29%) and polyacrylate (23%). Population density, plastic processing companies and meteorological factors were found to be associated with seasonal MP abundance and distribution patterns in the Lis River Basin.
Toward High-Quality Adult Online Learning: A Systematic Review of Empirical Studies
Authors: Lu Yefeng , Hong Xiaocui , Xiao Longhai
Published: February 2022

Adult education is a key policy to achieve the sustainable development goals. Large-scale open online courses are gradually increasing with the continued spread of COVID-19 all around the world, which has also attracted more and more adults to participate in such courses. However, despite the fact that the research on adult online learning is abundant, there is still a lack of systematic summaries that can guide the design and selection of course content and instructional methods. Therefore, the purpose of this study is to systematically examine the factors and related strategies that influence adult online learning, and to some extent also provide directions for future research. Using a systematic literature review, with the help of literature visualization software CiteSpace, this study summarized and analyzed 124 SSCI literature of empirical studies. The findings show that although some conclusions of adult online learning research are controversial, there is still some consensus, which is worthy of our attention. First, adult learners have time constraints and more responsibilities, hence life oriented, structured, and flexible online courses are more suitable for them. Secondly, adult learners have less scholastic aptitude and are less ICT skilled than normal students, so preparatory learning is necessary. Finally, in terms of an online instructional approach, integrated online discussions are recommended, as adults are prone to inefficient and superficial discussions in open discussions. This study contributes to theory and practice by expanding the systematic understanding of online learning for adults.
The Effect of Air Purifier on Smoke Detector Revealed by Fire Dynamics Simulation
Authors: Kim Taehoon , Kim Yongjoo , Rie Dongho
Published: February 2022

In the present study, the relevance of the airflow to the response time of the smoke detector has been investigated regarding the different air purifier locations by Fire Dynamics Simulator (FDS). Particular attention has been devoted to the impact on the smoke detector response with different device types, i.e., top-discharge and front-discharge air purifiers. Additionally, the response delay rate regarding the fire sizes (200 kW and 550 kW) was also evaluated with the top-discharge type purifier. The obscuration plots suggest that the response delay rate generally increases when the air purifier and the smoke detector are in a straight line. The change in the delay rate of the detector was distinct for the top-discharge type device due to the formation of a current barrier by the ceiling jet flow, and a nearby physical barrier (e.g., wall) can further suppress the flow diffusion during a fire event. The delay rate tends to decrease with the increment of the fire intensity.
Emotional Labor Mediates the Relationship between Clan Culture and Teacher Burnout: An Examination on Gender Difference
Authors: Zhang Ying , Tsang Kwok Kuen , Wang Li , Liu Dian
Published: February 2022

Teacher burnout is a psychological syndrome affecting many teachers across the globe. Therefore, numerous studies have investigated antecedents of teacher burnout in order to provide recommendations to alleviate it. Although the studies pay attention to either the role of environmental factors, such as school culture, or individual factors, such as gender, in contributing to teacher burnout, they less frequently examine how teacher burnout is concurrently influenced by both factors. Thus, this study aims to understand the relationship between clan culture and burnout by examining the mediation effect of emotional labor and the moderating effect of gender. A sample of 467 primary and secondary schoolteachers from China participated in this study. The result demonstrated the following: (1) clan culture was negatively related to teacher burnout; (2) deep acting mediated the relationship between clan culture and teacher burnout, while surface acting did not; (3) the mediating effect of deep acting was only significant in the female group of teachers, not the male group.
How Farmers Conceive and Cope with Megatrends: The Case of Finnish Dairy Farmers
Authors: Lahnamäki-Kivelä Susanna , Kuhmonen Tuomas
Published: February 2022

Megatrends (urbanization, digitalization, globalization, climate change, etc.) are mainstream developments that affect most economic activities. These megatrends have varying incidences and impacts on individual entrepreneurs and enterprises, also in farming sector. A farmer can either ignore or try to adapt to or benefit from megatrends. This reaction depends on many things: individuals’ futures orientation, management practices, business strategy, sunk costs, the life cycle and type of business, for example. The study explores the association between eight common megatrends and business strategies among a sample of Finnish dairy producers. The analysis is based on survey data from the year 2019 (n = 135) collected among a major Finnish dairy industry co-operative’s contract producers. The respondents evaluated the expected impact of the megatrends on their own business within the next 10 years with 5-point Likert-type scale (−2 … +2). K-means cluster analysis was utilized to uncover a few basic settings in the association between megatrends and farmers behaviours. After trying out several numbers of clusters, a distinctive three cluster solution was found. Additionally, cluster member profiles were framed with farmers’ Likert -scale responses. The analysis indicates that dairy farmers differ in their observation of megatrends. The results confirm that some of the farmers more or less ignore the common megatrends, whereas some other farmers adapt to or benefit from the common megatrends. Supporting farmers’ futures consciousness will strengthen their capacities of coping in the changing business environment.
Existence of Attractive Solutions for Hilfer Fractional Evolution Equations with Almost Sectorial Operators
Authors: Zhou Mian , Ahmad Bashir , Zhou Yong
Published: February 2022

The purpose of this paper is to investigate the existence of attractive solutions for a Cauchy problem of fractional evolution equations with Hilfer fractional derivative, which is a generalization of both the Riemann–Liuoville and Caputo fractional derivatives. Our methods are based on the generalized Ascoli–Arzela theorem, Schauder’s fixed point theorem, the Wright function and Kuratowski’s measure of noncompactness. The symmetric structure of the spaces and the operators defined by us plays a crucial role in showing the existence of fixed points. We obtain the global existence and attractivity results of mild solutions when the semigroup associated with an almost sectorial operator is compact as well as noncompact.
Lamellar Tetragonal Symmetry of Amphiphilic Thermotropic Ionic Liquid Crystals in the Framework of Other Closely Related Highly Ordered Structures
Authors: Arkas Michael , Douloudi Marilina , Vardavoulias Michail , Katsika Theodora
Published: February 2022

An overview of the chemical compounds forming the rare smectic T phases is presented with references to the historical context. Thermodynamics (transition temperatures, enthalpies) along with the factors (stereochemical constraints, electrostatic interactions, aliphatic chain stacking, intermolecular forces) contributing to the adoption of tetragonal scaffolds are also discussed. Characteristic optical microscopy textures and X-ray diffraction patterns are presented. In parallel, a comparison of the geometrical parameters such as distances between atoms, molecular areas, volumes, and lattice parameters with the closest two-dimensional and three-dimensional organizations, is performed.
Verifying the Smart Contracts of the Port Supply Chain System Based on Probabilistic Model Checking
Authors: Liu Yang , Zhou Ziyu , Yang Yongsheng , Ma Yan
Published: February 2022

Port supply chains play a very important role in the process of economic globalization. Lack of trust of the mechanism is the main factor in restricting the development of port supply chains. Blockchains have great potential to solve the trust problem among all participants using port supply chains, which can reduce costs and improve efficiency. As the bridge between blockchains and port supply chains, smart contracts reconstruct the business process of blockchain-empowered port supply chains. In this article, we present an architecture of a consortium blockchain-empowered port supply chain system, and propose a system verification framework for the smart contracts of port supply chains with probabilistic behaviors. The smart contracts are modeled as DTMCs (Discrete-Time Markov Chains), which are automatically transformed through the BPMN (Business Process Model and Notation) description of the smart contracts. The requirements are specified by PCTL (Probabilistic Computation Tree Logic). Moreover, we implement the customs clearance process of the Shanghai Yangshan Port based on blockchain Hyperledger Fabric, and reconstruct the clearance process with smart contracts. We use it to demonstrate the effectiveness of this framework, and identify the smart contracts that do not meet the expected needs of users.
The Decision of Production Systems with Quality-Contingent Demand and Condition-Based Maintenance
Authors: Gao Zhenhua , Wang Hongjun , Zhang Hongliang
Published: February 2022

To make a production plan fit with the actual situation better, we focus on the production system with equipment, and design a joint optimization strategy combining the economic production quantity (EPQ) model with condition-based maintenance. In this strategy, different maintenance operations are carried out when the state of the equipment exceeds different thresholds. The numerical relationship between product demand rate and equipment state is established, and the average cost rate is calculated by using the renewal reward theory. An optimization model is proposed, which takes the lowest average cost rate as the objective function with the economic production quantity and condition-based maintenance threshold are taken as the decision variables. An improved genetic algorithm with an elite strategy is used to solve the model. The results shows that the cost of the proposed model is lower and the sensitivity analysis can describe the relationship between the various elements of the production system clearly, understand the system state quickly, and demonstrate the proposed model.
Male Lower Urinary Tract Dysfunction: An Underrepresented Endpoint in Toxicology Research
Authors: Peterson Nelson T. , Vezina Chad M.
Published: February 2022

Lower urinary tract dysfunction (LUTD) is nearly ubiquitous in men of advancing age and exerts substantial physical, mental, social, and financial costs to society. While a large body of research is focused on the molecular, genetic, and epigenetic underpinnings of the disease, little research has been dedicated to the influence of environmental chemicals on disease initiation, progression, or severity. Despite a few recent studies indicating a potential developmental origin of male LUTD linked to chemical exposures in the womb, it remains a grossly understudied endpoint in toxicology research. Therefore, we direct this review to toxicologists who are considering male LUTD as a new aspect of chemical toxicity studies. We focus on the LUTD disease process in men, as well as in the male mouse as a leading research model. To introduce the disease process, we describe the physiology of the male lower urinary tract and the cellular composition of lower urinary tract tissues. We discuss known and suspected mechanisms of male LUTD and examples of environmental chemicals acting through these mechanisms to contribute to LUTD. We also describe mouse models of LUTD and endpoints to diagnose, characterize, and quantify LUTD in men and mice.
HIV Infection and Spread between Th17 Cells
Authors: Zayas Janet P. , Mamede João I.
Published: February 2022

HIV mainly targets CD4+ T cells, from which Th17 cells represent a major cell type, permissive, and are capable of supporting intracellular replication at mucosal sites. Th17 cells possess well-described dual roles, while being central to maintaining gut integrity, these may induce inflammation and contribute to autoimmune disorders; however, Th17 cells’ antiviral function in HIV infection is not completely understood. Th17 cells are star players to HIV-1 pathogenesis and a potential target to prevent or decrease HIV transmission. HIV-1 can be spread among permissive cells via direct cell-to-cell and/or cell-free infection. The debate on which mode of transmission is more efficient is still ongoing without a concrete conclusion yet. Most assessments of virus transmission analyzing either cell-to-cell or cell-free modes use in vitro systems; however, the actual interactions and conditions in vivo are not fully understood. The fact that infected breast milk, semen, and vaginal secretions contain a mix of both cell-free viral particles and infected cells presents an argument for the probability of HIV taking advantage of both modes of transmission to spread. Here, we review important insights and recent findings about the role of Th17 cells during HIV pathogenesis in mucosal surfaces, and the mechanisms of HIV-1 infection spread among T cells in tissues.
Induction of Broadly Cross-Reactive Antibodies by Displaying Receptor Binding Domains of SARS-CoV-2 on Virus-like Particles
Authors: Chang Xinyue , Liu Xuelan , Mohsen Mona O. , Zeltins Andris , Martina Byron , Vogel Monique , Bachmann Martin F.
Published: February 2022

The impact of the COVID-19 pandemic has been reduced since the application of vaccination programs, mostly shown in the reduction of hospitalized patients. However, the emerging variants, in particular Omicron, have caused a steep increase in the number of infections; this increase is, nevertheless, not matched by an increase in hospitalization. Therefore, a vaccine that induces cross-reactive antibodies against most or all variants is a potential solution for the issue of emerging new variants. Here, we present a vaccine candidate which displays receptor-binding domain (RBD) of SARS-CoV-2 on virus-like particles (VLP) that, in mice, not only induce strong antibody responses against RBD but also bind RBDs from other variants of concern (VOCs). The antibodies induced by wild-type (wt) RBD displayed on immunologically optimized Cucumber mosaic virus incorporated tetanus toxin (CuMVTT) VLPs bind to wt as well as RBDs of VOCs with high avidities, indicating induction of strongly cross-reactive IgG antibodies. Interestingly, similar cross-reactive IgA antibodies were induced in immunized mice. Furthermore, these cross-reactive antibodies demonstrated efficacy in neutralizing wt (Wuhan) as well as SARS-CoV-2 VOCs (Beta, Delta, and Gamma). In summary, RBDs displayed on VLPs are capable of inducing protective cross-reactive IgG and IgA antibodies in mice, indicating that it may be possible to cover emerging VOCs with a single vaccine based on wt RBD.
Leptospira interrogans Serogroup Pomona in a Dairy Cattle Farm in a Multi-Host Zootechnical System
Authors: Aliberti Antonino , Blanda Valeria , Di Marco Lo Presti Vincenzo , Macaluso Giusi , Galluzzo Paola , Bertasio Cristina , Sciacca Carmela , Arcuri Francesca , D’Agostino Rosalia , Ippolito Dorotea , Pruiti Ciarello Flavia , Torina Alessandra , Grippi Francesca
Published: February 2022

Bovine leptospirosis is an infectious zoonotic disease causing reproductive problems and economic losses in livestock. This work reports, for the first time in Sicily (South Italy), an outbreak of Leptospira interrogans serogroup Pomona that occurred in cattle farms within the Nebrodi Park and was mainly characterized by full-term abortion. Blood and urine samples were collected at different time points from animals of six different farms (Farms A–F) sharing the same grazing area. Research of antibodies against pathogenic Leptospira species in serum samples was carried out via Micro Agglutination Test (MAT). Urine samples were subjected to pathogen isolation and molecular analyses via TaqMan Real Time-PCR. Genotyping of Leptospira species was obtained by Multi-locus sequence typing. MAT detected antibodies against Leptospira interrogans serogroup Pomona in serum samples of all the farms. Pathogenic Leptospira spp. DNA and culture isolation was obtained from urine samples. Genotyping confirmed the excretion of L. interrogans serogroup Pomona. This study describes clinical manifestations, diagnostic implications and epidemiological characteristics of an outbreak in cattle due to L. interrogans Pomona in a protected multi-host area, where domestic and wild animals share the same habitat, suggesting a role of wild species in transmission and persistence of Pomona serogroup among cattle.