bluuebunny/crossref_metadata_2025 huggingface dataset:
A Week of Sleep Restriction Does Not Affect Nighttime Glucose Concentration in Healthy Adult Males When Slow-Wave Sleep Is Maintained
Authors: Kontou Thomas G. , Sargent Charli , Roach Gregory D.
Published: September 2022

The aim of this laboratory-based study was to examine the effect of sleep restriction on glucose regulation during nighttime sleep. Healthy males were randomly assigned to one of two conditions: 9 h in bed (n = 23, age = 24.0 year) or 5 h in bed (n = 18, age = 21.9 year). Participants had a baseline night with 9 h in bed (23:00–08:00 h), then seven nights of 9 h (23:00–08:00 h) or 5 h (03:00–08:00 h) in bed. Participants were mostly seated during the daytime but had three bouts of treadmill walking (4 km·h−1 for 10 min) at ~14:40 h, ~17:40 h, and ~20:40 h each day. On the baseline night and night seven, glucose concentration in interstitial fluid was assessed by using continuous glucose monitors, and sleep was assessed by using polysomnography. On night seven, compared to the 9 h group, the 5 h group obtained less total sleep (292 min vs. 465 min) and less REM sleep (81 min vs. 118 min), but their slow-wave sleep did not differ (119 min vs. 120 min), and their glucose concentration during sleep did not differ (5.1 mmol·L−1 vs. 5.1 mmol·L−1). These data indicate that sleep restriction does not cause elevated levels of circulating glucose during nighttime sleep when slow-wave sleep is maintained. In the future, it will be important to determine whether increased insulin is required to maintain circulating glucose at a normal level when sleep is restricted.
3D-Printable Piezoelectric Composite Sensors for Acoustically Adapted Guided Ultrasonic Wave Detection
Authors: Roloff Thomas , Mitkus Rytis , Lion Jann Niklas , Sinapius Michael
Published: September 2022

Commercially available photopolymer resins can be combined with lead zirconate titanate (PZT) micrometer size piezoelectric particles to form 3D-printable suspensions that solidify under UV light. This in turn makes it possible to realize various non-standard sensor geometries which might bring benefits, such as increased piezoelectric output in specific conditions and less interference with incoming waves due to better acoustical adaptation compared to solid PZT ceramics. However, it is unclear whether piezoelectric composite materials are suitable for guided ultrasonic wave (GUW) detection, which is crucial for structural health monitoring (SHM) in different applications. In this study, thin piezoelectric composite sensors are tape casted, solidified under UV light, covered with electrodes, polarized in a high electric field and adhesively bonded onto an isotropic aluminum waveguide. This approach helps to demonstrate the capabilities of tape casting’s freedom to manufacture geometrically differently shaped, thin piezoelectric composite sensors for GUW detection. In an experimental study, thin two-dimensional piezoelectric composite sensors demonstrate successful detection of GUW for frequency-thickness products of up to 0.5 MHz mm. An analytical calculation of the maximum and minimum amplitudes for the ratio of the wavelength and the sensor length in wave propagation direction shows good agreement with the sensor-recorded signals. The output of the piezoelectric composite sensors and occurring reflections as measure for wave interactions are compared to commercial piezoelectric discs to evaluate their performance.
PATROL: Participatory Activity Tracking and Risk Assessment for Anonymous Elderly Monitoring
Authors: Dawadi Research , Mizumoto Teruhiro , Matsuda Yuki , Yasumoto Keiichi
Published: September 2022

There has been a subsequent increase in the number of elderly people living alone, with contribution from advancement in medicine and technology. However, hospitals and nursing homes are crowded, expensive, and uncomfortable, while personal caretakers are expensive and few in number. Home monitoring technologies are therefore on the rise. In this study, we propose an anonymous elderly monitoring system to track potential risks in everyday activities such as sleep, medication, shower, and food intake using a smartphone application. We design and implement an activity visualization and notification strategy method to identify risks easily and quickly. For evaluation, we added risky situations in an activity dataset from a real-life experiment with the elderly and conducted a user study using the proposed method and two other methods varying in visualization and notification techniques. With our proposed method, 75.2% of the risks were successfully identified, while 68.5% and 65.8% were identified with other methods. The average time taken to respond to notification was 176.46 min with the proposed method, compared to 201.42 and 176.9 min with other methods. Moreover, the interface analyzing and reporting time was also lower (28 s) in the proposed method compared to 38 and 54 s in other methods.
Monitoring Wheat Lodging at Various Growth Stages
Authors: Jiang Shuangshuai , Hao Jinyu , Li Han , Zuo Changzhen , Geng Xia , Sun Xiaoyong
Published: September 2022

Lodging is one of the primary factors that reduce wheat yield; therefore, rapid and accurate monitoring of wheat lodging helps to provide data support for crop loss and damage response and the subsequent settlement of agricultural insurance claims. In this study, we aimed to address two problems: (1) calculating the wheat lodging area. Through comparative experiments, the SegFormer-B1 model can achieve a better segmentation effect of wheat lodging plots with a higher prediction rate and a stronger generalization ability. This model has an accuracy of 96.56%, which realizes the accurate extraction of wheat lodging plots and the relatively precise calculation of the wheat lodging area. (2) Analyzing wheat lodging areas from various growth stages. The model established, based on the mixed-stage dataset, generally outperforms those set up based on the single-stage datasets in terms of the segmentation effect. The SegFormer-B1 model established based on the mixed-stage dataset, with its mIoU reaching 89.64%, was applicable to wheat lodging monitoring throughout the whole growth cycle of wheat.
Coarse-to-Fine Localization of Underwater Acoustic Communication Receivers
Authors: He Pan , Shen Lu , Henson Benjamin , Zakharov Yuriy V.
Published: September 2022

For underwater acoustic (UWA) communication in sensor networks, the sensing information can only be interpreted meaningfully when the location of the sensor node is known. However, node localization is a challenging problem. Global Navigation Satellite Systems (GNSS) used in terrestrial applications do not work underwater. In this paper, we propose and investigate techniques based on matched field processing for localization of a single-antenna UWA communication receiver relative to one or more transmit antennas. Firstly, we demonstrate that a non-coherent ambiguity function (AF) allows significant improvement in the localization performance compared to the coherent AF previously used for this purpose, especially at high frequencies typically used in communication systems. Secondly, we propose a two-step (coarse-to-fine) localization technique. The second step provides a refined spatial sampling of the AF in the vicinity of its maximum found on the coarse space grid covering an area of interest (in range and depth), computed at the first step. This technique allows high localization accuracy and reduction in complexity and memory storage, compared to single step localization. Thirdly, we propose a joint refinement of the AF around several maxima to reduce outliers. Numerical experiments are run for validation of the proposed techniques.
Deep Ensemble Fake News Detection Model Using Sequential Deep Learning Technique
Authors: Ali Abdullah Marish , Ghaleb Fuad A. , Al-Rimy Bander Ali Saleh , Alsolami Fawaz Jaber , Khan Asif Irshad
Published: September 2022

Recently, fake news has been widely spread through the Internet due to the increased use of social media for communication. Fake news has become a significant concern due to its harmful impact on individual attitudes and the community’s behavior. Researchers and social media service providers have commonly utilized artificial intelligence techniques in the recent few years to rein in fake news propagation. However, fake news detection is challenging due to the use of political language and the high linguistic similarities between real and fake news. In addition, most news sentences are short, therefore finding valuable representative features that machine learning classifiers can use to distinguish between fake and authentic news is difficult because both false and legitimate news have comparable language traits. Existing fake news solutions suffer from low detection performance due to improper representation and model design. This study aims at improving the detection accuracy by proposing a deep ensemble fake news detection model using the sequential deep learning technique. The proposed model was constructed in three phases. In the first phase, features were extracted from news contents, preprocessed using natural language processing techniques, enriched using n-gram, and represented using the term frequency–inverse term frequency technique. In the second phase, an ensemble model based on deep learning was constructed as follows. Multiple binary classifiers were trained using sequential deep learning networks to extract the representative hidden features that could accurately classify news types. In the third phase, a multi-class classifier was constructed based on multilayer perceptron (MLP) and trained using the features extracted from the aggregated outputs of the deep learning-based binary classifiers for final classification. The two popular and well-known datasets (LIAR and ISOT) were used with different classifiers to benchmark the proposed model. Compared with the state-of-the-art models, which use deep contextualized representation with convolutional neural network (CNN), the proposed model shows significant improvements (2.41%) in the overall performance in terms of the F1score for the LIAR dataset, which is more challenging than other datasets. Meanwhile, the proposed model achieves 100% accuracy with ISOT. The study demonstrates that traditional features extracted from news content with proper model design outperform the existing models that were constructed based on text embedding techniques.
The Method of Trajectory Selection Based on Bayesian Game Model
Authors: Tian Wen , Fang Qin , Zhou Xuefang , Yang Fan
Published: September 2022

To cope with the problem that most of the en-route spatial-temporal resource allocation in the collaborative trajectory options program (CTOP) only considers the air traffic control system command center (ATCSCC) while ignoring the needs of the airlines, which results in the loss of fairness, this study explores resource allocation methods oriented to airline trajectory preferences with optional trajectory and entry slots of flights over the flow constrained area (FCA) as the research object. Using game theory to analyze airline trajectory preference information and a Bayesian game model based on mixed strategies is constructed, the process of incomplete information game among airlines is studied. The equilibrium theory is used to solve the guarantee strategy of airline trajectory selection, which makes the airline trajectory selection strategy robust and provides a basis for the selection of schemes for ATCSCC to implement en-route network resource allocation under the CTOP. Experimental analysis was carried out to verify the feasibility of the method based on the actual operation data of high-altitude sectors of Shanghai. The results show that the solution obtained by the game can provide airlines with flight trajectory and entry slots over the FCA that are more in line with their actual operational needs and which provide data reference for the ATCSCC to select the final plan in multiple global Pareto optimal solutions in the subsequent process of the CTOP so as to better play the decision-making role of airlines in the CTOP while improving the fairness of en-route resource allocation.
Mapping Digital Storytelling in Interactive Learning Environments
Authors: Chang Ching-Yi , Chu Hui-Chun
Published: September 2022

This study used bibliographic analysis to validate the research trends of technology-enhanced digital storytelling (DS) in education and educational research published from 2005 to 2022, reviewing the literature found in the Web of Science (WoS) databases. The study investigated trends in learning domains in DS by primarily analyzing the top published journals and the most frequently cited DS-related articles, countries, publishing authors, occurring keywords, research methods, and application domains in the field. This paper mainly used bibliometric analysis and examined the relationship between keywords using the VOSviewer software. Four thematic clusters were identified: DS, education, technology, and literacy. The results show that Robin’s study is the most frequently cited DS-related work in the education and educational research field. Important findings in the literature about the main application domains in DS research are that activity is dominant, there is no specific domain, followed by the application of language, and next by position studies. The results highlight the research trend of technology-enhanced storytelling education, and recommendations are provided for future research. For field researchers, the analysis serves as a map to explore the indiscernible relationships among DS research trends, providing new avenues for DS researchers to investigate further.
The Influence of Multilingualism and Professional Development Activities on Teacher Reflection Levels
Authors: Almusharraf Asma , Almusharraf Norah , Bailey Daniel
Published: September 2022

Reflection occurs as a learning process in which thoughts are consequential and continuously improved upon. The current research examined teacher reflection by examining the influence of multilingualism and professional development activities on teacher reflection levels. Data were analyzed using IBM SPSS employing 226 male and 207 female EFL instructors teaching in Saudi Arabia. Variables were grouped into languages spoken and professional development activities. Inferential statistics (i.e., descriptive statistics, independent sample t-test, and one-way ANOVA) were utilized. The findings revealed that reflective practices varied significantly due to the languages spoken. The mean of the total English Language Teaching Reflection Inventory (ELTRI) for participants who performed the professional development activity is higher than for those who did not. Further, participants who collaborated with colleagues were mentored, self-studied, and took courses illustrated a significantly higher total score on the ELTRI. When designing professional development curricula, a greater focus on particular reflection training should be more appropriate depending on completed professional benchmarks. These implications and the future direction of this study highlight the dynamic influence of multilingualism in reflective practices. Henceforward, the study suggests the imperative need to provide teachers with professional development programs for training them and elevate their awareness of the effectiveness of reflective teaching practices.
Sense of Place and Sound: Revisiting from Multidisciplinary Outlook
Authors: Yildirim Yalcin , Arefi Mahyar
Published: September 2022

This study revisits the sense of place and sound nexus in the literature. Along with that, it seeks to explore the approaches that influential urban theorists, landscape architects, and planners have recommended. How these concepts converge within the allied disciplines of urban planning, urban design, geography, and landscape architecture remains at the forefront of this investigation. This research proposes a conceptual framework by identifying sounds in three key categories—auditory experience, sound, and silence—to address the gap between sound and urban studies. The study reveals decisive patterns in urban studies’ interface between the sense of place and the sound context.
SDG Performance in Local Organic Food Systems and the Role of Sustainable Public Procurement
Authors: Stefanovic Lilliana
Published: September 2022

Alternative food systems have occupied a steady niche in the food systems transformation discourse as one of the transformative pathways capable of addressing many of the United Nations Sustainable Development Goals (SDGs). Being one of the alternative approaches, organic food systems are often in the spotlight of transformation discussion. While their outcomes and, to a lesser extent, potential to address the SDGs have been documented, the attempts to provide empirical evidence for the latter contribution are largely lacking. The study aimed to close this gap by assessing the performance of SDGs in local organic food systems with the territorial approach. For this purpose, a mixed methods research design and actor-oriented approach have been used. The research employed a multiple-case study design to examine three European territorial organic food systems to uncover their contribution to SDGs and thereby their role in food systems transformation towards enhanced sustainability. Analysis at the target level revealed the central role of SDG 12, responsible consumption and production, addressed by the highest number of targets manifested through corresponding outcomes of all three analyzed case studies. The analyzed systems uncovered a leverage potential of sustainable public procurement to unfold other SDG targets through synergetic interactions of the respective outcomes.
Research on Bearing Capacity of Secant Piled-Bucket Foundation in Saturated Clay
Authors: Xu Ying , Wang Haijun , Zhang Liying , Deng Mingji , Jiang Hechuan , Guo Yaohua , Yang Xu
Published: September 2022

The secant piled-bucket foundation (SPBF) is innovatively proposed to suit the large-capacity mainstream, which is optimized from a traditional foundation and consists of an upper pile cap and a lower bucket skirt. Compared with the pile foundation, the SPBF has great advantages and deserves further study. In this research, the bearing mode, bearing capacity and failure mode under various loads of SPBF in saturated clay have been fully studied. First, the small-scale model test in saturated clay is carried out to verify the finite element (FE) method; the deviation between the FE results and the test results under vertical load and horizontal–moment load is 10.65% and 10.25%, respectively. Next, the bearing mode of SPBF in engineering scales is investigated via FE method, the results indicating that the bearing mode of SPBF is similar to that of a prestressed tubular foundation. Finally, the bearing capacity and failure mode of SPBF are studied and the findings show that the vertical bearing capacity and horizontal–moment bearing capacity of SPBF is 96.53 MN and 1.62 MN, and the weak parts of SPBF are concrete of the pile cap and the anchor bolts, respectively. This paper provides support for design and further optimization in the future.
Analysis of the Characteristics of Real-World Emission Factors and VSP Distributions—A Case Study in Beijing
Authors: He Weinan , Duan Lei , Zhang Zhuoyuan , Zhao Xu , Cheng Ying
Published: September 2022

Vehicle emissions intensity at a given travel speed is well known among the public since travel speed is the key parameter in both the traffic model and the emission model. Yet, several problems still remain in traditional approaches of measuring the emission intensity. To establish accurate and high-resolution emission factors, an established method of emission factors is proposed based on the real-time monitoring operation conditions data, which can reflect the effect of dynamic traffic changes on emissions. The speed-specific vehicle-specific power (VSP) distributions of different months, as well as those in different vehicles in Beijing were developed and compared. Statistical analyses such as Coefficient of Variation (CV) and Root Mean Square Error (RMSE) were used to quantify the differences in the VSP distribution. The results showed the significant correlation between the distribution of VSP, velocity, and operating patterns at time intervals within the annual range. Driving conditions in 2021 are more eco-friendly because of the improvement of digital development and driving habits. Furthermore, research on CO, HC, and NOx emission factor situations in different cycles revealed that the emission factors of NOx and HC are always underestimated in typical operating modes, while sometimes the emissions of CO are overvalued.
Does Farmland Transfer Contribute to Reduction of Chemical Fertilizer Use? Evidence from Heilongjiang Province, China
Authors: Cui Ningbo , Ba Xuezhen , Dong Jin , Fan Xiaofan
Published: September 2022

Promoting the reduction of chemical fertilizers is an important measure to promote the green and sustainable development of agriculture. Farmland transfer is a new way to minimize the need of chemical fertilizers. However, there is debate over this causality. This paper examines the relationship between farmland transfer and chemical fertilizer reduction. After the theoretical analysis, based on the data of 442 corn farmers in Heilongjiang Province, the study employed the endogenous switching probit model to empirically test the effect of farmland transfer on the reduction of chemical fertilizer. The study finds that in the survey area, the overall actual chemical fertilizer application rate was 12.12 kg/mu higher than the economic optimal application rate, which had more room for chemical fertilizer reduction. Moreover, farmland transfer-in reduced the chemical fertilizer application during corn production. If farmland transfer-in farmers decided not to transfer into the farmland, the chemical fertilizer reduction treatment effect would decrease, while it would increase if farmland non-transfer-in farmers decided to transfer into the farmland. Finally, the chemical fertilizer reduction treatment effect would decrease if farmers who had transferred into farmland concentratedly chose to transfer into farmland dispersedly, while it would increase if farmers who had transferred into farmland dispersedly chose to transfer into farmland concentratedly. These findings can provide experience for achieving more effective farmland transfer and chemical fertilizer reduction.
Minimizing Waste in the Food Supply Chain: Role of Information System, Supply Chain Strategy, and Network Design
Authors: Tan Ying , Hai Feng , Popp József , Oláh Judit
Published: September 2022

A continuous increase in the world population and reduction in quantity and quality of resources is putting enormous pressure on nations to ensure a balance between food demand and supply. The same is highlighted at number two in the United Nations’ sustainable development goals as the Zero Hunger goal. However, a significant portion of produced food worldwide is damaged or wasted in the food supply chain. This study focuses on minimizing waste in the food supply chain by highlighting the importance of strategy, information systems, and network design in the food supply chain. The authors collected data from 211 respondents from 48 firms and analyzed it through structural equation modeling. It has been found that information system has great potential to minimize waste in the food supply chain. Moreover, strategy and network design significantly improve organizational capabilities to minimize waste in the food supply chain. The finding provides constructive insights to food companies to incorporate and operationalize recommended measures to minimize waste in the food supply chain so that the world can counter the food shortage and waste/damage problem and the Zero Hunger goal can successfully be achieved.
Increasing Transparency in Global Supply Chains: The Case of the Fast Fashion Industry
Authors: Fraser Eve , van der Ven Hamish
Published: September 2022

The fast fashion industry is subject to growing calls for transparency, from civil society groups as well as consumers. Despite universal pressure on retailers to disclose information on supply chain practices, uptake of transparency policies and practices has been heterogenous amongst large fast fashion companies. In this paper, we explain variation in transparency practices through a comparison of the four largest fast fashion retailers: H&M, Inditex, Gap, and Fast Retailing. Drawing on cross-case comparison and within-case process tracing, we offer insights into why some retailers are more transparent than others. Our findings suggest that sustainability scandals are a necessary but insufficient condition for motivating firms to increase transparency in their supply chains. Scandals can be an important driver of increased transparency, but only when accompanied by support from senior management and alignment with domestic norms about appropriate corporate conduct. These findings contribute to the literature on transnational business governance, corporate transparency, and sustainable supply-chain management.
The Effect of Economic Policy Uncertainty on Green Technology Innovation: Evidence from China’s Enterprises
Authors: Yang Xuan , Mao Shihao , Sun Luxuan , Feng Chao , Xia Yinshuang
Published: September 2022

In some cases, enterprise fears uncertainty more than the policy itself, and this fear can impede innovation. However, this study finds that uncertainty is the source of enterprise’s innovation. We took Chinese A-share listed companies from 2010 to 2018 as the research sample and studied the impact of economic policy uncertainty (EPU) on green technology innovation (GTI). Based on China’s EPU index and green patent-application data of Chinese-listed enterprises, this study adopted a panel fixed regression model and found that EPU has a slightly promoting effect on GTI of Chinese-listed enterprises. This effect is also affected by enterprise ownership and industry characteristics. Among them, EPU has a stronger promoting effect on GTI activities of state-owned enterprises and high-tech enterprises than common enterprises. In particular, if EPU increases, the GTI of high-polluting enterprises is not as great as the incentive effect of ordinary enterprises. The reasons may be that state-owned enterprises have more implicit capital guarantees, high-tech enterprises have higher innovation motivation, and high-polluting enterprises have stronger dependence on traditional production equipment. These results can provide a reference for the debate on “uncertainty.” The conclusions of this paper contain unique policy implications.
The Procurement Agenda for the Transition to a Circular Economy
Authors: Al-Sinan Mazen A. , Bubshait Abdulaziz A.
Published: September 2022

The circular economy (CE) has emerged as an upcoming promising solution to global sustainability. Some policymakers have issued legislations to encourage the adoption of CE, and academics have published studies addressing CE from different approaches. However, adopting CE entails a disruptive shift from a linear economy to a closed-loop economy, where economic growth is decoupled from consumption growth. Though it is difficult to develop a uniform, structured approach for incorporating CE into procurement, this paper attempts to fill the current knowledge gap by proposing a holistic framework to embed CE into the procurement process. The procurement ecosystem is very complex, and this study accordingly dismantles the ecosystem into basic components. The integration of CE for each component is addressed separately. Propositions have then been developed for each element within the procurement ecosystem to embrace CE. The research findings suggest that governments can play an important role in promulgating laws and regulations that encourage CE within procurement. The buyer should be willing to pay a premium for circular products or services; training is needed to address CE when drafting the agreement and during the technical and proposal evaluation. In regard to the bidders’ prequalification evaluation, a certain weight should be assigned to the adoption of CE. Furthermore, the bid–award system should give preferential treatment to circular materials or services.
Factors Affecting Organisations’ Adoption Behaviour toward Blockchain-Based Distributed Identity Management: The Sustainability of Self-Sovereign Identity in Organisations
Authors: Mulaji Sarah Mulombo , Roodt Sumarie
Published: September 2022

Blockchain-based Distributed Identity Management (BDIDM) can enhance sustainable identification and authentication of users on organisations’ digital systems. But there is not a clear consensus on how organisations perceive the value proposition of such technology, nor what might affect their adoption behaviour toward it. This research explains how technological, organisational and environmental (TOE) factors affect organisations’ adoption behaviour toward BDIDM. This study aims to determine the most critical factors affecting the behaviour while assessing the effectiveness and appropriateness of the model involved, i.e., TOE-BDIDM. Online questionnaires are used to survey 111 information and cybersecurity practitioners within South African organisations. The analysis combines binary logistic regression modelling, Structural Equation Modelling of the measurement model, and chi-squared tests. The results suggest TOE factors positively or negatively affect adoption behaviour. The behaviour is significantly affected by technology characteristics, i.e., BDIDM’s disruptive nature, and is associated with Blockchain type. Indeed, the majority of participants intended to recommend BDIDM to their organisations yet paradoxically preferred private-permissioned blockchain the most, revealing resistance to decentralised and privacy-preserving BDIDM models like Self-Sovereign Identity (SSI). The latter might be utopian or unsustainable for organisations. TOE-BDIDM was found relatively appropriate and effective but arguably ‘incomplete’ for explaining the adoption of disruptive technologies like SSI in organisations. TOE should extend to TOEU by including the User factors.
Talent Retention of New Generations for Sustainable Employment Relationships in Work 4.0 Era—Assessment by Fuzzy Delphi Method
Authors: Lin Lung-Hsin , Wang Kung-Jeng
Published: September 2022

The transformation in Industry 4.0 has impacted not only manufacturing systems but also work, essentially changing the nature of work. “Work 4.0” is referred to as “Industry 4.0”, but with a focus on sustainable employment relationships and the forms of work. However, the issue of talent retention (TR) in the Work 4.0 context remains unsolved. The purpose of this study was to identify factors influencing TR among different generations for the development of sustainable employment relationships from a Work 4.0 perspective. Accordingly, we put forward propositions concerning TR and generational effects in Work 4.0 scenarios. By evaluating the influencing factors using the fuzzy Delphi method, 19 TR determinants were eventually extracted. Furthermore, considering generational effects, our results indicate that Work 4.0 has a higher impact on TR for Gen Y than for Gen X and Baby Boomers. The talents of the new generation seem to pay more attention to autonomy and digitalization at work (e.g., flexible work arrangements and knowledge management through digitalization) but are tired of bureaucracies. The results provided in this study may offer organizations a reference for better meeting the preferences of talents, regarding work in the context of Work 4.0, allowing them to fine-tune their strategies for sustainable talent management, thus enhancing TR in the digital era.
Population Dynamics of Methanogenic Archea in Co-Digestion Systems Operating Different Industrial Residues for Biogas Production
Authors: da Motta Isabela Gomes Barreto , Santana Larice Aparecida Rezende , Pereira Hyago Passe , de Paula Vanessa Romário , Martins Marta Fonseca , da Costa Carneiro Jailton , Otenio Marcelo Henrique
Published: September 2022

This study aimed to analyze the population dynamics of methanogenic archaea in co-digestion systems operated under different concentrations of industrial waste such as ricotta whey and brewery waste sludge in association with bovine manure. It was believed that the association of these residues from the food industry combined with bovine manure can contribute to improve the production of biogas. To identify the archaea, DNA extractions and the sequencing of the 16s rRNA gene were performed from 38 samples of influents and effluents. The results indicated that Methanosaeta and Methanosarcina were predominant in the co-digestion of ricotta cheese whey and that Methanosaeta, Methanocorpusculum, and Methanobrevibacter prevailed in the co-digestion of residual brewery sludge. The three ricotta cheese whey biodigesters demonstrated efficiency in methane production; in contrast, residual sludge of brewery biodigesters only showed efficiency in the system operated with 20% co-substrate.
HVAC Control Systems for a Negative Air Pressure Isolation Room and Its Performance
Authors: Hamdani Hamdani , Sabri Fajar Salamul , Harapan Harapan , Syukri Maimun , Razali Razali , Kurniawan Rudi , Irwansyah Irwansyah , Sofyan Sarwo Edhy , Mahlia Teuku Meurah Indra , Rizal Samsul
Published: September 2022

The controlled environment room, called an isolation room, has become a must have for medical facilities, due to the spreading of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), to isolate the high risk infected patients. To avoid the transmission of the virus through airborne routes, guidelines were published by the government and the association. A medical facility must comply with this document for high-risk patient treatment. A full-scale N class isolation room was built at Syiah Kuala University to investigate the performance in terms of the controller, temperature, pressure, humidity, and energy consumption. The isolation room was equipped with a proper capacity heating, ventilating, and air conditioning (HVAC) system, which consisted of an air conditioning compressor and a negative pressure generator (NPG), and its installation was ensured to fulfil the guidelines. Since the current NPG was controlled manually, a computer-based control system was designed, implemented, and compared with the manual control. The results showed that the computer-based control outputs better stability of pressure and electric power. For that reason, a computer-based control was chosen in the real case. To investigate the performance of the isolation room, a 24 h experiment was carried out under different parameter setups. The results showed that improvement of the control strategy for temperature and humidity is still necessary. The energy consumption during the activation of the NPG for the recommended negative pressure was slightly different. An additional piece of equipment to absorb the heat from the exhaust air would be promising to improve the energy efficiency.
COVID-19’s Impact on the Restaurant Industry
Authors: Gomes Conceição , Malheiros Cátia , Campos Filipa , Lima Santos Luís
Published: September 2022

The restaurant industry contributed to the creation of wealth and employment until the end of 2019, when it reached maximum values. However, with the COVID-19 pandemic in early 2020, this sector suffered a very serious economic and employment crisis. The analysis of this situation is imperative to mitigate the consequences for the restaurant industry and to prevent impacts in future crises. The main purpose of the present study is to compare the years 2019 and 2020, analyzing the profitability, payroll costs, headcount, and indebtedness of the restaurants, to verify the COVID-19 pandemic’s impact in Spain and Portugal. Quantitative research was applied, where a descriptive analysis and hypothesis testing were conducted. SABI database was the secondary data source used in this research. The results show that the COVID-19 pandemic has had an impact on profitability, efficiency, and indebtedness in the restaurant industry, being a generalized situation in both countries, in all regions except for Ceuta. The results also confirm the importance of this study for managers and academics since all the variables under study worsened with the COVID-19 pandemic. This study represents a contribution to managers and stakeholders in the restaurant sector by allowing the comparative evaluation of each restaurant with the average of the variables by location and the definition of proactive strategies. Practical implications are proposed to mitigate the effect not only of COVID-19 but also of other pandemics or economic crises that may arise in the future, preparing managers and stakeholders to adapt to change and promoting the financial sustainability of the restaurant industry. It is recommended to increase the disclosure of statistical indicators and financial ratios of free access, which allows the improvement of the analysis of different variables that are important for professionals in the restaurant industry.
Molecular Epidemiological Characterisation of ESBL- and Plasmid-Mediated AmpC-Producing Escherichia coli and Klebsiella pneumoniae at Kamuzu Central Hospital, Lilongwe, Malawi
Authors: Choonara Faheema Ebrahim , Haldorsen Bjørg Christina , Janice Jessin , Mbanga Joshua , Ndhlovu Isaac , Saulosi Osborne , Maida Tarsizio , Lampiao Fanuel , Simonsen Gunnar Skov , Essack Sabiha Yusuf , Sundsfjord Arnfinn
Published: September 2022

The global rise in infections caused by multidrug resistant (MDR) Enterobacterales poses a public health problem. We have performed a molecular epidemiological characterisation of representative plasmid-mediated AmpC (pAmpC) and ESBL-positive clinical isolates of Escherichia coli (n = 38) and Klebsiella pneumoniae (n = 17) from a tertiary hospital in Malawi collected in 2017. BlaCTX-M-15 was the most prevalent ESBL-determinant in E. coli (n = 30/38) and K. pneumoniae (n = 17/17), whereas blaCMY-2 was detected in nearly all AmpC-phenotype E. coli (n = 15/17). Whole genome sequencing revealed dominant globally disseminated E. coli sequence types (STs); ST410 (n = 16), ST131 (n = 7), and ST617 (n = 6). The ST distribution in K. pneumoniae was more diverse but included ST101 (n = 2), ST14 (n = 2), and ST340 (n = 2), all considered high-risk MDR clones. The isolates expressed an MDR profile, including resistance against commonly used antibiotics, such as fluoroquinolones, aminoglycosides, and/or trimethoprim-sulfamethoxazole, and harboured corresponding resistance determinants. Clonal analyses of the major STs of E. coli revealed closely related genetic clusters within ST410, ST131, and ST617 supporting within-hospital transmission between patients and/or via a common reservoir. The overall findings add to the limited knowledge on the molecular epidemiology of MDR E. coli and K. pneumoniae in Malawi and may help health policy makers to identify areas to target when addressing this major threat of antibiotic resistance.
A Risk Prediction Model and Risk Score of SARS-CoV-2 Infection Following Healthcare-Related Exposure
Authors: Sripanidkulchai Kantarida , Rattanaumpawan Pinyo , Ratanasuwan Winai , Angkasekwinai Nasikarn , Assanasen Susan , Werarak Peerawong , Navanukroh Oranich , Phatharodom Phatharajit , Tocharoenchok Teerapong
Published: September 2022

Hospital workers are at high risk of contact with COVID-19 patients. Currently, there is no evidence-based, comprehensive risk assessment tool for healthcare-related exposure; so, we aimed to identify independent factors related to COVID-19 infection in hospital workers following workplace exposure(s) and construct a risk prediction model. We analyzed the COVID-19 contact tracing dataset from 15 July to 31 December 2021 using multiple logistic regression analysis, considering exposure details, demographics, and vaccination history. Of 7146 included exposures to confirmed COVID-19 patients, 229 (4.2%) had subsequently tested positive via RT-PCR. Independent risk factors for a positive test were having symptoms (adjusted odds ratio 4.94, 95%CI 3.83–6.39), participating in an unprotected aerosol-generating procedure (aOR 2.87, 1.66–4.96), duration of exposure >15 min (aOR 2.52, 1.82–3.49), personnel who did not wear a mask (aOR 2.49, 1.75–3.54), exposure to aerodigestive secretion (aOR 1.5, 1.03–2.17), index patient not wearing a mask (aOR 1.44, 1.01–2.07), and exposure distance <1 m without eye protection (aOR 1.39, 1.02–1.89). High-potency vaccines and high levels of education protected against infection. A risk model and scoring system with good discrimination power were built. Having symptoms, unprotected exposure, lower education level, and receiving low potency vaccines increased the risk of laboratory-confirmed COVID-19 following healthcare-related exposure events.
Genomic and Epidemiological Features of COVID-19 in the Novosibirsk Region during the Beginning of the Pandemic
Authors: Palyanova Natalia , Sobolev Ivan , Alekseev Alexander , Glushenko Alexandra , Kazachkova Evgeniya , Markhaev Alexander , Kononova Yulia , Gulyaeva Marina , Adamenko Lubov , Kurskaya Olga , Bi Yuhai , Xin Yuhua , Sharshov Kirill , Shestopalov Alexander
Published: September 2022

In this retrospective, single-center study, we conducted an analysis of 13,699 samples from different individuals obtained from the Federal Research Center of Fundamental and Translational Medicine, from 1 April to 30 May 2020 in Novosibirsk region (population 2.8 million people). We identified 6.49% positive for SARS-CoV-2 cases out of the total number of diagnostic tests, and 42% of them were from asymptomatic people. We also detected two asymptomatic people, who had no confirmed contact with patients with COVID-19. The highest percentage of positive samples was observed in the 80+ group (16.3%), while among the children and adults it did not exceed 8%. Among all the people tested, 2423 came from a total of 80 different destinations and only 27 of them were positive for SARS-CoV-2. Out of all the positive samples, 15 were taken for SARS-CoV-2 sequencing. According to the analysis of the genome sequences, the SARS-CoV-2 variants isolated in the Novosibirsk region at the beginning of the pandemic belonged to three phylogenetic lineages according to the Pangolin classification: B.1, B.1.1, and B.1.1.129. All Novosibirsk isolates contained the D614G substitution in the Spike protein, two isolates werecharacterized by an additional M153T mutation, and one isolate wascharacterized by the L5F mutation.
Co-Infection and Cancer: Host–Pathogen Interaction between Dendritic Cells and HIV-1, HTLV-1, and Other Oncogenic Viruses
Authors: Mulherkar Tania H. , Gómez Daniel Joseph , Sandel Grace , Jain Pooja
Published: September 2022

Dendritic cells (DCs) function as a link between innate and adaptive immune responses. Retroviruses HIV-1 and HTLV-1 modulate DCs to their advantage and utilize them to propagate infection. Coinfection of HTLV-1 and HIV-1 has implications for cancer malignancies. Both viruses initially infect DCs and propagate the infection to CD4+ T cells through cell-to-cell transmission using mechanisms including the formation of virologic synapses, viral biofilms, and conduits. These retroviruses are both neurotrophic with neurovirulence determinants. The neuropathogenesis of HIV-1 and HTLV-1 results in neurodegenerative diseases such as HIV-associated neurocognitive disorders (HAND) and HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP). Infected DCs are known to traffic to the brain (CNS) and periphery (PNS, lymphatics) to induce neurodegeneration in HAND and HAM/TSP patients. Elevated levels of neuroinflammation have been correlated with cognitive decline and impairment of motor control performance. Current vaccinations and therapeutics for HIV-1 and HTLV-1 are assessed and can be applied to patients with HIV-1-associated cancers and adult T cell leukemia/lymphoma (ATL). These diseases caused by co-infections can result in both neurodegeneration and cancer. There are associations with cancer malignancies and HIV-1 and HTLV-1 as well as other human oncogenic viruses (EBV, HBV, HCV, HDV, and HPV). This review contains current knowledge on DC sensing of HIV-1 and HTLV-1 including DC-SIGN, Tat, Tax, and current viral therapies. An overview of DC interaction with oncogenic viruses including EBV, Hepatitis viruses, and HPV is also provided. Vaccines and therapeutics targeting host–pathogen interactions can provide a solution to co-infections, neurodegeneration, and cancer.
Evaluation of UVC Excimer Lamp (222 nm) Efficacy for Coronavirus Inactivation in an Animal Model
Authors: Tucciarone Claudia Maria , Cecchinato Mattia , Vianello Lucrezia , Simi Gabriele , Borsato Enrico , Silvestrin Luca , Giorato Michele , Salata Cristiano , Morandin Mauro , Greggio Elisa , Drigo Michele
Published: September 2022

The current pandemic caused by severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) has encouraged the evaluation of novel instruments for disinfection and lowering infectious pressure. Ultraviolet subtype C (UVC) excimer lamps with 222 nm wavelength have been tested on airborne pathogens on surfaces and the exposure to this wavelength has been considered safer than conventional UVC. To test the efficacy of UVC excimer lamps on coronaviruses, an animal model mimicking the infection dynamics was implemented. An attenuated vaccine based on infectious bronchitis virus (IBV) was nebulized and irradiated by 222 nm UVC rays before the exposure of a group of day-old chicks to evaluate the virus inactivation. A control group of chicks was exposed to the nebulized vaccine produced in the same conditions but not irradiated by the lamps. The animals of both groups were sampled daily and individually by choanal cleft swabs and tested usign a strain specific real time RT-PCR to evaluate the vaccine replication. Only the birds in the control group were positive, showing an active replication of the vaccine, revealing the efficacy of the lamps in inactivating the vaccine below the infectious dose in the other group.
Cross-Reactivity of SARS-CoV-2 Nucleocapsid-Binding Antibodies and Its Implication for COVID-19 Serology Tests
Authors: Rak Alexandra , Donina Svetlana , Zabrodskaya Yana , Rudenko Larisa , Isakova-Sivak Irina
Published: September 2022

The emergence of the new coronavirus SARS-CoV-2 in late 2019 led to the global pandemic COVID-19, causing a profound socioeconomic crisis. Adequate diagnostic tools need to be developed to control the ongoing spread of infection. Virus-specific humoral immunity in COVID-19 patients and those vaccinated with specific vaccines has been characterized in numerous studies, mainly using Spike protein-based serology tests. However, Spike protein and specifically its receptor-binding domain (RBD) are mutation-prone, suggesting the reduced sensitivity of the validated serology tests in detecting antibodies raised to variants of concern (VOC). The viral nucleocapsid (N) protein is more conserved compared to Spike, but little is known about cross-reactivity of the N-specific antibodies between the ancestral B.1 virus and different VOCs. Here, we generated recombinant N phosphoproteins from different SARS-CoV-2 strains and analyzed the magnitude of N-specific antibodies in COVID-19 convalescent sera using an in-house N-based ELISA test system. We found a strong positive correlation in the magnitude of anti-N (B.1) antibodies and antibodies specific to various VOCs in COVID-19-recovered patients, suggesting that the N-binding antibodies are highly cross-reactive, and the most immunogenic epitopes within this protein are not under selective pressure. Overall, our study suggests that the RBD-based serology tests should be timely updated to reflect the constantly evolving nature of the SARS-CoV-2 Spike protein, whereas the validated N-based test systems can be used for the analysis of sera from COVID-19 patients regardless of the strain that caused the infection.