bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel Fractional Accumulative Grey Model with GA-PSO Optimizer and Its Application
Authors: Huang Ruixiao , Fu Xiaofeng , Pu Yifei
Published: January 2023

The prediction of cyber security situation plays an important role in early warning against cyber security attacks. The first-order accumulative grey model has achieved remarkable results in many prediction scenarios. Since recent events have a greater impact on future decisions, new information should be given more weight. The disadvantage of first-order accumulative grey models is that with the first-order accumulative method, equal weight is given to the original data. In this paper, a fractional-order cumulative grey model (FAGM) is used to establish the prediction model, and an intelligent optimization algorithm known as particle swarm optimization (PSO) combined with a genetic algorithm (GA) is used to determine the optimal order. The model discussed in this paper is used for the prediction of Internet cyber security situations. The results of a comparison with the traditional grey model GM(1,1), the grey model GM(1,n), and the fractional discrete grey seasonal model FDGSM(1,1) show that our model is suitable for cases with insufficient data and irregular sample sizes, and the prediction accuracy and stability of the model are better than those of the other three models.
Degradation Feature Extraction Method for Prognostics of an Extruder Screw Using Multi-Source Monitoring Data
Authors: Park Jun-Kyu , Lee Howon , Kim Woojin , Kim Gyu-Man , An Dawn
Published: January 2023

Laboratory-scale data on a component level are frequently used for prognostics because acquiring them is time and cost efficient. However, they do not reflect actual field conditions. As prognostics is for an in-service system, the developed prognostic methods must be validated using real operational data obtained from an actual system. Because obtaining real operational data is much more expensive than obtaining test-level data, studies employing field data are scarce. In this study, a prognostic method for screws was presented by employing multi-source real operational data obtained from a micro-extrusion system. The analysis of real operational data is more challenging than that of test-level data because the mutual effect of each component in the system is chaotically reflected in the former. This paper presents a degradation feature extraction method for interpreting complex signals for a real extrusion system based on the physical and mechanical properties of the system as well as operational data. The data were analyzed based on general physical properties and the inferred interpretation was verified using the data. The extracted feature exhibits valid degradation behavior and is used to predict the remaining useful life of the screw in a real extrusion system.
Development of Magnetocardiograph without Magnetically Shielded Room Using High-Detectivity TMR Sensors
Authors: Kurashima Koshi , Kataoka Makoto , Nakano Takafumi , Fujiwara Kosuke , Kato Seiichi , Nakamura Takenobu , Yuzawa Masaki , Masuda Masanori , Ichimura Kakeru , Okatake Shigeki , Moriyasu Yoshitaka , Sugiyama Kazuhiro , Oogane Mikihiko , Ando Yasuo , Kumagai Seiji , Matsuzaki Hitoshi , Mochizuki Hidenori
Published: January 2023

A magnetocardiograph that enables the clear observation of heart magnetic field mappings without magnetically shielded rooms at room temperatures has been successfully manufactured. Compared to widespread electrocardiographs, magnetocardiographs commonly have a higher spatial resolution, which is expected to lead to early diagnoses of ischemic heart disease and high diagnostic accuracy of ventricular arrhythmia, which involves the risk of sudden death. However, as the conventional superconducting quantum interference device (SQUID) magnetocardiographs require large magnetically shielded rooms and huge running costs to cool the SQUID sensors, magnetocardiography is still unfamiliar technology. Here, in order to achieve the heart field detectivity of 1.0 pT without magnetically shielded rooms and enough magnetocardiography accuracy, we aimed to improve the detectivity of tunneling magnetoresistance (TMR) sensors and to decrease the environmental and sensor noises with a mathematical algorithm. The magnetic detectivity of the TMR sensors was confirmed to be 14.1 pTrms on average in the frequency band between 0.2 and 100 Hz in uncooled states, thanks to the original multilayer structure and the innovative pattern of free layers. By constructing a sensor array using 288 TMR sensors and applying the mathematical magnetic shield technology of signal space separation (SSS), we confirmed that SSS reduces the environmental magnetic noise by −73 dB, which overtakes the general triple magnetically shielded rooms. Moreover, applying digital processing that combined the signal average of heart magnetic fields for one minute and the projection operation, we succeeded in reducing the sensor noise by about −23 dB. The heart magnetic field resolution measured on a subject in a laboratory in an office building was 0.99 pTrms and obtained magnetocardiograms and current arrow maps as clear as the SQUID magnetocardiograph does in the QRS and ST segments. Upon utilizing its superior spatial resolution, this magnetocardiograph has the potential to be an important tool for the early diagnosis of ischemic heart disease and the risk management of sudden death triggered by ventricular arrhythmia.
Microdosing Sprint Distribution as an Alternative to Achieve Better Sprint Performance in Field Hockey Players
Authors: Cuadrado-Peñafiel Víctor , Castaño-Zambudio Adrián , Martínez-Aranda Luis Manuel , González-Hernández Jorge Miguel , Martín-Acero Rafael , Jiménez-Reyes Pedro
Published: January 2023

Introduction: The implementation of optimal sprint training volume is a relevant component of team sport performance. This study aimed to compare the efficiency and effectiveness of two different configurations of within-season training load distribution on sprint performance over 6 weeks. Methods: Twenty male professional FH players participated in the study. Players were conveniently assigned to two groups: the experimental group (MG; n = 11; applying the microdosing training methodology) and the control group (TG; n = 9; traditional training, with players being selected by the national team). Sprint performance was evaluated through 20 m sprint time (T20) m and horizontal force–velocity profile (HFVP) tests before (Pre) and after (Post) intervention. Both measurements were separated by a period of 6 weeks. The specific sprint training program was performed for each group (for vs. two weekly sessions for MG and TG, respectively) attempting to influence the full spectrum of the F-V relationship. Results: Conditional demands analysis (matches and training sessions) showed no significant differences between the groups during the intervention period (p > 0.05). No significant between-group differences were found at Pre or Post for any sprint-related performance (p > 0.05). Nevertheless, intra-group analysis revealed significant differences in F0, Pmax, RFmean at 10 m and every achieved time for distances ranging from 5 to 25 m for MG (p < 0.05). Such changes in mechanical capabilities and sprint performance were characterized by an increase in stride length and a decrease in stride frequency during the maximal velocity phase (p < 0.05). Conclusion: Implementing strategies such as microdosed training load distribution appears to be an effective and efficient alternative for sprint training in team sports such as hockey.
A Machine Learning Approach for the NLP-Based Analysis of Cyber Threats and Vulnerabilities of the Healthcare Ecosystem
Authors: Silvestri Stefano , Islam Shareeful , Papastergiou Spyridon , Tzagkarakis Christos , Ciampi Mario
Published: January 2023

Digitization in healthcare systems, with the wid adoption of Electronic Health Records, connected medical devices, software and systems providing efficient healthcare service delivery and management. On the other hand, the use of these systems has significantly increased cyber threats in the healthcare sector. Vulnerabilities in the existing and legacy systems are one of the key causes for the threats and related risks. Understanding and addressing the threats from the connected medical devices and other parts of the ICT health infrastructure are of paramount importance for ensuring security within the overall healthcare ecosystem. Threat and vulnerability analysis provides an effective way to lower the impact of risks relating to the existing vulnerabilities. However, this is a challenging task due to the availability of massive data which makes it difficult to identify potential patterns of security issues. This paper contributes towards an effective threats and vulnerabilities analysis by adopting Machine Learning models, such as the BERT neural language model and XGBoost, to extract updated information from the Natural Language documents largely available on the web, evaluating at the same time the level of the identified threats and vulnerabilities that can impact on the healthcare system, providing the required information for the most appropriate management of the risk. Experiments were performed based on CS news extracted from the Hacker News website and on Common Vulnerabilities and Exposures (CVE) vulnerability reports. The results demonstrate the effectiveness of the proposed approach, which provides a realistic manner to assess the threats and vulnerabilities from Natural Language texts, allowing adopting it in real-world Healthcare ecosystems.
Lectin Purification through Affinity Chromatography Exploiting Macroporous Monolithic Adsorbents
Authors: Silva Josiane F. da , Lima Clara M. G. , da Silva Débora L. , do Nascimento Ivonea S. , Rodrigues Sarah de O. , Gonçalves Letícia A. , Santana Renata F. , Khalid Waseem , Verruck Silvani , Emran Talha Bin , de Menezes Irwin R. A. , Coutinho Henrique D. M. , Khandaker Mayeen U. , Faruque Mohammad R. I. , Fontan Rafael da C. I.
Published: January 2023

Growing medical, engineering, biochemical, and biological interest has led to a steady pace of research and development into polymeric monolithic structures with densely interconnected pores for purifying bio compounds. Cryogels, which are generated by freezing a reactive polymerization mixture, are highlighted due to their versatility and low relative cost as macroporous, polymeric, monolithic adsorbents. The conversion of cryogels into affinity adsorbents is one possible alternative to their optimal application. Some of the most often utilized supports for immobilizing particular ligands are monolithic columns manufactured with epoxy radicals on their surfaces. The purification of biomolecules with a high degree of specificity, such as lectins and glycoproteins with an affinity for glycosylated groups, has garnered interest in the use of fixed non-traditional beds functionalized with ligands of particular interest. The interaction is both robust enough to permit the adsorption of glycoproteins and reversible enough to permit the dissociation of molecules in response to changes in the solution’s pH. When compared to other protein A-based approaches, this one has been shown to be more advantageous than its counterparts in terms of specificity, ease of use, and cost-effectiveness. Information on polymeric, macroporous, monolithic adsorbents used in the affinity chromatographic purification of lectins has been published and explored.
Can Policy Promote Agricultural Service Outsourcing? Quasi-Natural Experimental Evidence from China
Authors: Li Xiang , Guo Xiaoqin
Published: January 2023

This paper emphasizes the key role of policy in the development of agricultural services outsourcing. In this paper, a theoretical framework is constructed to analyze the role of government policies on agricultural service outsourcing under the assumption of the separability of agricultural production processes. The article constructs a quasi-natural experiment using the China-targeted poverty alleviation program and nationally representative microdata, and the PSM-DID model is chosen to estimate the policy effects. We also discuss regional heterogeneity, aiming to identify the ways in which policy affects agricultural service outsourcing. Based on a comprehensive household-level dataset and econometric analysis, we find that targeted poverty alleviation programs significantly promote the use of agricultural service outsourcing by low-income farmers, and the effects of the policies are more pronounced for the central and western regions. These findings suggest that targeted poverty alleviation programs improve the income of farm households in poor areas and encourage the use of agricultural service outsourcing, which can save agricultural labor, reduce the opportunity cost of agricultural production, and contribute to the sustainable development of the poor.
Application of Probabilistic Seismic Hazard Assessment to Understand the Earthquake Hazard in Attock City, Pakistan: A Step towards Linking Hazards and Sustainability
Authors: Qadri S. M. Talha , Mirza M. Qasim , Raja Afia , Yaghmaei-Sabegh Saman , Hakimi Mohammed Hail , Ali Syed Haroon , Khan Mohammad Younis
Published: January 2023

Within the last three decades, twelve major earthquakes (Mw > 6.0) have jolted Pakistan and contributed to a heavy death toll and an economic loss of billions of dollars, which is immense for any underdeveloped country. Despite the generalized description of seismic hazards in various regions of Pakistan, densely populated cities still require a detailed and integrated vulnerability analysis to overcome the impact of a significant earthquake. This study aims to integrate seismic hazard assessment schemes to understand the vulnerability of Attock city against an earthquake. It initially evaluates the threat from an earthquake due to tectonic activity in the region, splits the region (about 200 km radius) into six seismic zones and uses area source parameters. The ground motion prediction equations compatible with the study area’s seismotectonic environment are also used in this study. Peak horizontal ground acceleration (PGA) and 5% damped spectral acceleration are critical features of ground motions. The site classification is carried within Attock city, indicating the presence of SB (foundation condition with Vs30 = 760 m/s), SC (foundation condition with Vs30 = 400 m/s) and SD (foundation condition with Vs30 = 300 m/s). The peak ground accelerations for a return period of 475 years at the SB, SC and SD sites are estimated as 0.23 g, 0.28 g and 0.30 g, respectively. Uniform hazard spectra are obtained for each site classification at three return periods (475, 975 and 2475 years). Another possible threat can be the local site conditions of the study area, as Attock city exists on the unlithified sediments of upper Pleistocene to Recent alluvial deposits. That is why microtremor recordings are conducted at 20 sites within Attock city to understand the fundamental frequency (f0), horizontal to vertical spectral amplitude (A0) and Kg parameter, a seismic vulnerability index. The values of f0 are found between 0.6 and 9 Hz and A0 is observed between 2.1 and 5 Hz, whereas the Kg is estimated between 0.24 and 20 Hz. Despite evidence of the seismic vulnerability of Attock city, the current building designs and infrastructure development are not synchronized with the uniform hazard response spectra and the soil amplification, thus enhancing the exposure of the study area to disaster during a major earthquake. This study will be instrumental in pre-disaster mitigation strategies for urban planners and policymakers.
Regulatory Obstacles in Municipal Solid Waste Management in Kazakhstan in Comparison with the EU
Authors: Nukusheva Aigul , Rustembekova Dinara , Abdizhami Aitugan , Au Tatyana , Kozhantayeva Zhaukhar
Published: January 2023

In the context of achieving the goals of the modern environmental agenda, the issue of effective management of household waste is a complex problem, being one of the highest priorities on a global scale. Regional features and the lack of effective international instruments often hinder the solution of this problem, complicating the development and application of common mechanisms. For Kazakhstan, which is the largest country in Central Asia and the state that produces the largest amount of household waste in the region, the issue of managing household waste is of particular relevance. This study is on the prospects for political and legal regulation in matters of municipal waste management in Kazakhstan within the framework of the use of foreign legal instruments and practices. Besides that, the study examines the prospects for the management of solid domestic waste in the country. Based on the study of foreign experience in the management of domestic waste, we identified the shortcomings of the existing legislative regulation in this area in the Republic of Kazakhstan. The analysis showed that the legislation of the Republic of Kazakhstan in the relevant area is at the stage of formation. At the same time, the existing problems require a comprehensive solution related to the development of an integrated approach, which implies the effective interaction of political and legal instruments. In particular, the use of national strategies and programs, integrated waste management programs, and the development of an appropriate regulatory framework for them. A review of political initiatives that directly affect the prospects for the formation of legal regulation indicated the commitment of the subjects of policy making in the field of environmental protection of the Republic of Kazakhstan to approaches based on the preference for minimizing or preventing waste generation and for the waste-to-energy principles. These initiatives are in line with the environmental policies in the EU.
The Effect of Corporate Social Responsibility on Customer Trust and Loyalty
Authors: Barlas Achilleas , Valakosta Aggeliki , Katsionis Christos , Oikonomou Anastasios , Brinia Vasiliki
Published: January 2023

The concept of Corporate Social Responsibility (CSR) has been the subject of various studies in recent decades. The purpose of this research was to study the Corporate Social Responsibility of companies, in combination with customers’ perspectives, in terms of their trends regarding their trust and loyalty. In this study, the business sector of the Greek mobile telecommunications’ companies was selected, where research on issues related to CSR is not considered extensive, to analyze customers’ attitudes towards a company that emphasizes its social responsibility. To complete the theoretical framework, questionnaires were collected to empirically investigate correlations and highlight, ultimately, the importance of having socially responsible companies in the mobile telecommunications sector in Greece. The present research proved that both at the bibliographic and practical level, successful companies are the ones that are concerned not only with increasing their sales and profitability, but also with enhancing and emphasizing their social impact and returning value to society.
How Italian Fashion Brands Beat COVID-19: Manufacturing, Sustainability, and Digitalization
Authors: Di Maria Eleonora , Bettiol Marco , Capestro Mauro
Published: January 2023

COVID-19 has had a dramatic impact on the fashion industry. Fashion brands had to restructure their value chains and refine their strategies to overcome the negative consequences of the lockdown. An analysis of the Italian fashion industry is used to examine how companies responded to the challenges of the pandemic and how they were able to find competitive solutions. Qualitative analysis is used to discuss the case of Italy, a country that was particularly affected by COVID-19. The research shows that companies invested in three different directions to overcome the obstacles posed by the COVID-19 emergency: refocusing on manufacturing, investing in sustainability (especially social), and relying on digital technologies (e.g., e-commerce and videoconferencing) to interact with remote customers. The theoretical and practical contributions of this study are discussed.
Psychological Research of College Students Based on Online Education under COVID-19
Authors: Wang Xi , Zou Yuntao
Published: January 2023

As a socially sensitive group, college students have a higher risk of mental health problems. However, because of the COVID-19 pandemic, many nonlocal college students were isolated locally and were not able to attend classes as usual. This series of protective measures to avoid the spread of the disease may bring an additional mental impact on college students’ lives. As an important aspect of the sustainable development goals of quality education, education plays a central role in shaping personal and social change towards sustainability. The COVID-19 environment poses a great challenge to the education of university students. The purpose of this study is to propose a strategy to use an intelligent online learning system based on content recommendation and electronic questionnaires in the field of education. We invited 3000 isolated college students (47.6% male and 52.4% female) to participate in an internet trial. It proved to be effective in helping us intervene quickly, objectively, effectively, and in real-time in students’ psychological problems. In addition, according to the data analysis collected by the intelligent online learning system, we found that the degree of isolation regarding college students’ psychological problems was closely related to their grade, family background, professional category, and computer proficiency. This study shows that, during the period of isolation, the mental health of college students should be well monitored. Targeted psychosocial guidance is more needed for students with higher grades, those with low-income families, liberal arts majors, and those with weak computer skills in order to reduce the emotional impact of isolation on students.
Unsafe Mining Behavior Identification Method Based on an Improved ST-GCN
Authors: Cao Xiangang , Zhang Chiyu , Wang Peng , Wei Hengyang , Huang Shikai , Li Hu
Published: January 2023

Aiming to solve the problems of large environmental interference and complex types of personnel behavior that are difficult to identify in the current identification of unsafe behavior in mining areas, an improved spatial temporal graph convolutional network (ST-GCN) for miners’ unsafe behavior identification network in a transportation roadway (NP-AGCN) was proposed. First, the skeleton spatial-temporal map constructed using multi-frame human key points was used for behavior recognition to reduce the interference caused by the complex environment of the coal mine. Second, aiming to solve the problem that the original graph structure cannot learn the association relationship between the non-naturally connected nodes, which leads to the low recognition rate of climbing belts, fighting and other behaviors, the graph structure was reconstructed and the original partitioning strategy was changed to improve the recognition ability of the model for multi-joint interaction behaviors. Finally, in order to alleviate the problem that the graph convolution network has difficulty learning global information due to the small receptive field, multiple self-attention mechanisms were introduced into the graph convolution to improve the recognition ability of the model for unsafe behaviors. In order to verify the detection ability of the model regarding identifying unsafe behaviors of personnel in a coal mine belt area, our model was tested on the public datasets NTU-RGB + D and the self-built datasets of unsafe behaviors in a coal mine belt area. The recognition accuracies of the proposed model in the above datasets were 94.7% and 94.1%, respectively, which were 6.4% and 7.4% higher than the original model, which verified that the proposed model had excellent recognition accuracies.
Correction: Yang, J.; Yu, M. The Influence of Institutional Support on the Innovation Performance of New Ventures: The Mediating Mechanism of Entrepreneurial Orientation. Sustainability 2022, 14, 2212
Authors: Yang Jie , Yu Mingxing
Published: January 2023

In the original publication [...]
Analysis of Vertical Temperature Gradients and Their Effects on Hybrid Girder Cable-Stayed Bridges
Authors: Tan Hongmei , Qian Dacheng , Xu Yan , Yuan Mofang , Zhao Hanbing
Published: January 2023

The real temperature distribution within 24 h of the main beam in a single-tower hybrid beam cable-stayed bridge is analysed according to its actual section and material parameters, as well as other factors of local atmospheric temperature, geographical environment, and solar intensity. The results show that the internal temperature distribution in the steel–concrete composite beam is uneven, and the temperature of the steel is higher than that at the surface of the concrete slab. Then, a finite element model of the whole bridge is established using the thermal–mechanical sequential coupling function in ABAQUS to acquire the structural response under the action of a 24-h temperature field. The results show that the vertical temperature gradients have a great influence on the longitudinal stress in the lower flange of the steel I-beam, with a maximum compressive stress of 11.9 MPa in the daytime and a maximum tensile stress of 13.36 MPa at midnight. The temperature rise leads to a downward deflection of the main span, and the maximum deflection occurs at the 1/4 main span. There was an obvious temperature gradient in the concrete slab, with a difference between the maximum and minimum value of 14 °C. Similarly, the longitudinal compressive stress of the concrete slab increases with increasing temperature in the daytime, but the peak time is obviously inconsistent with that of the steel beam.
Performance Enhancement of an Upflow Anaerobic Dynamic Membrane Bioreactor via Granular Activated Carbon Addition for Domestic Wastewater Treatment
Authors: Liu Le , Hu Yisong , Qu Yi , Cheng Dongxing , Yang Yuan , Chen Rong , Ji Jiayuan
Published: January 2023

Developing low-carbon advanced processes for sustainable wastewater treatment is of great importance to increase bioenergy recovery and to reduce the greenhouse gas effect. In this study, the influence of adding 25 g/L of granular activated carbon (GAC) on the process performance was studied with a lab-scale GAC amended anaerobic dynamic membrane (G-AnDMBR) used to treat real domestic wastewater, which was compared to a control bioreactor without the GAC addition (C-AnDMBR). Due to the initial adsorption effect of GAC and the high microbial activity of the attached biomass of GAC, the G-AnDMBR achieved a better removal of the total chemical oxygen demand (TCOD) and turbidity compared to the C-AnDMBR, with the average removal rate increasing from 82.1% to 86.7% and from 88.7% to 93.2%. The gaseous methane production increased from 0.08 ± 0.05 to 0.14 ± 0.04 L/d, and the total methane production rate was enhanced from 0.21 ± 0.11 to 0.23 ± 0.09 LCH4/gCOD. Thus, the treatment performance of the G-AnDMBR was superior to that of the C-AnDMBR, and the addition of GAC could improve the effluent quality during the initial dynamic membrane formation process. In addition, the buffering effect of GAC made the G-AnDMBR maintain a relatively stable solution environment. The G-AnDMBR showed a transmembrane pressure (TMP) increasing rate of 0.045 kPa/d, which was obviously lower than that of the C-AnDMBR (0.057 kPa/d) because the nonfluidized GAC could trap fine sludge particles and adsorb soluble extracellular polymer substances (SEPSs), thus inhibiting the over formation of the dynamic membrane layer. A microbial property analysis indicated that GAC induced a change in the microbial community and enhanced the gene abundance of type IV pili and that it also potentially accelerated the direct interspecific electron transfer (DIET) among syntrophic bacteria and methanogens by enriching specific functional microorganisms. The results indicated that the integration of GAC and the AnDMBR process can be a cost-effective and promising alternative for domestic wastewater treatment and bioenergy recovery.
Joint Impacts of Pricing Strategies and Persuasive Information on Habitual Automobile Commuters’ Travel Mode Shift Responses
Authors: Li Yaping , Liu Zheng , Zhang Shiqing
Published: January 2023

Persuasive information developed by smartphone applications is a potential tool that can be utilized in order to increase the effectiveness of the impact of pricing strategies on triggering sustainable travel mode choice behavior. In order to address the joint impacts of pricing strategies and persuasive information on habitual automobile commuters’ travel mode shift responses, a stated-preference survey was conducted in Beijing’s inner district, from which over 1000 responses were collected. Four separate multivariable multilevel logistic regression models were estimated for more and less habitual automobile commuters when subjected to congestion pricing and reward strategies. The model estimation results showed that the influence of persuasive information was more effective in promoting travel mode shifts among more habitual automobile commuters with regard to reward strategies compared to congestion pricing. The results also showed that the impact of sociodemographic characteristics, commuter travel characteristics, the amount of congestion pricing or monetary award, and types of persuasive information on travel mode shift decisions under these strategies were deemed to be significantly different between more and less habitual automobile commuters. These findings suggest that more effective reward strategies can be explored by providing personalized and differentiated travel feedback information (e.g., pollution emission information and physical activity information), particularly for less habitual automobile commuters. This study also provides some degree of insight regarding the question as to how to design future congestion pricing, i.e., with respect to formulating differentiated charge rates according to the travel characteristics of habitual automobile commuters, as well as in developing complementary persuasive information that focuses on addressing public acceptability and fairness rather than travel feedback information.
Fault Prediction Recommender Model for IoT Enabled Sensors Based Workplace
Authors: Uppal Mudita , Gupta Deepali , Mahmoud Amena , Elmagzoub M. A. , Sulaiman Adel , Reshan Mana Saleh Al , Shaikh Asadullah , Juneja Sapna
Published: January 2023

Industry 5.0 benefits from advancements being made in the field of machine learning and the Internet of Things. Different sensors have been installed in a variety of IoT devices present in different industries such as transportation, healthcare, manufacturing, agriculture, etc. The sensors present in these devices should automatically predict errors due to the extensive use of sensors in urban living. To ensure the integrity, precision, security, dependability and fidelity of sensor nodes, it is, therefore, necessary to foresee faults before they occur. Additionally, as more data is being collected by these devices every day, cloud computing becomes more necessary for sustainable urban living. The proposed model emphasizes solution recommendations for faults that occurred in real-life smart devices to mitigate faults at an early stage, which is a key requirement in today’s smart offices. The proposed model monitors the real-time health of IoT devices through an ML algorithm to make devices more efficient and increase the quality of life. Through the use of K-Nearest Neighbor, Decision Tree, Gaussian Naive Bayes and Random Forest approach, the proposed fault prediction recommender model has been evaluated and Random Forest shows the highest accuracy compared to other classifiers. Several performance indicators such as recall, accuracy, F1 score and precision were utilized to examine the performance of the model. The results have demonstrated the effectiveness of ML techniques applied to sensors in predicting faults in smart offices with Random Forest being observed as the best technique with a maximum accuracy of 94.27%. In future, deep learning can also be applied to bigger datasets to provide more accurate results.
Control Functions in G-Metric Spaces: Novel Methods for θ-Fixed Points and θ-Fixed Circles with an Application
Authors: Hammad Hasanen A. , Alshehri Maryam G. , Shehata Ayman
Published: January 2023

The purpose of this paper is to present some new contraction mappings via control functions. In addition, some fixed point results for Θ,α,θ,Ψ contraction, rational Θ,α,θ,Ψ contraction and almost Θ,α,θ,Ψ contraction mappings are obtained. Moreover, under contraction mappings of types (I), (II), and (III) of Θ,θ,Ψυ0, several fixed circle solutions are provided in the setting of a G-Metric space. Our results extend, unify, and generalize many previously published papers in this direction. In addition, some examples to show the reliability of our results are presented. Finally, a supporting application that discusses the possibility of a solution to a nonlinear integral equation is incorporated.
Public Knowledge and Perceptions about the Emerging Human Mpox in Jordan: A Cross-Sectional Study
Authors: Abu-Farha Rana K. , Alzoubi Karem H. , Mukattash Tareq L. , Alkhawaldeh Rama , Barakat Muna , Thiab Samar
Published: January 2023

Hundreds of human mpox cases are spreading outside of Western and Central Africa, which could be considered a significant world health problem. In this study, we sought to assess public knowledge and perceptions of human mpox. The study was a cross-sectional survey conducted in Jordan in September–October 2022. All participants were approached through social media portals. A total of 1195 participants agreed to participate in this study. The participants showed a low median knowledge score about human mpox (4.0 out of 15.0, IQR = 5.0), with only 27.9% of the participants (n = 334) correctly identifying that human mpox is not a bacterial disease, and around half of them (n = 589, 49.3%) knowing that this disease affects both genders. Higher monthly income (≥400 JD/month) was significantly associated with better knowledge about the disease. Social media was the most comprehensive source of information about mpox (n = 1018, 85.2%). Finally, 57.3% of the participants (n = 685) believed that mpox would affect social and economic life, like the COVID-19 pandemic. These findings highlight the urgent need for systematic strategies that should be promoted to increase public knowledge of mpox, which will be critical in improving the capacity to respond to the disease.
A Detailed Overview of SARS-CoV-2 Omicron: Its Sub-Variants, Mutations and Pathophysiology, Clinical Characteristics, Immunological Landscape, Immune Escape, and Therapies
Authors: Chatterjee Srijan , Bhattacharya Manojit , Nag Sagnik , Dhama Kuldeep , Chakraborty Chiranjib
Published: January 2023

The COVID-19 pandemic has created significant concern for everyone. Recent data from many worldwide reports suggest that most infections are caused by the Omicron variant and its sub-lineages, dominating all the previously emerged variants. The numerous mutations in Omicron’s viral genome and its sub-lineages attribute it a larger amount of viral fitness, owing to the alteration of the transmission and pathophysiology of the virus. With a rapid change to the viral structure, Omicron and its sub-variants, namely BA.1, BA.2, BA.3, BA.4, and BA.5, dominate the community with an ability to escape the neutralization efficiency induced by prior vaccination or infections. Similarly, several recombinant sub-variants of Omicron, namely XBB, XBD, and XBF, etc., have emerged, which a better understanding. This review mainly entails the changes to Omicron and its sub-lineages due to it having a higher number of mutations. The binding affinity, cellular entry, disease severity, infection rates, and most importantly, the immune evading potential of them are discussed in this review. A comparative analysis of the Delta variant and the other dominating variants that evolved before Omicron gives the readers an in-depth understanding of the landscape of Omicron’s transmission and infection. Furthermore, this review discusses the range of neutralization abilities possessed by several approved antiviral therapeutic molecules and neutralizing antibodies which are functional against Omicron and its sub-variants. The rapid evolution of the sub-variants is causing infections, but the broader aspect of their transmission and neutralization has not been explored. Thus, the scientific community should adopt an elucidative approach to obtain a clear idea about the recently emerged sub-variants, including the recombinant variants, so that effective neutralization with vaccines and drugs can be achieved. This, in turn, will lead to a drop in the number of cases and, finally, an end to the pandemic.
ERVWE1 Reduces Hippocampal Neuron Density and Impairs Dendritic Spine Morphology through Inhibiting Wnt/JNK Non-Canonical Pathway via miR-141-3p in Schizophrenia
Authors: Yao Wei , Zhou Ping , Yan Qiujin , Wu Xiulin , Xia Yaru , Li Wenshi , Li Xuhang , Zhu Fan
Published: January 2023

Human endogenous retroviruses (HERVs) are remnants of ancestral germline infections by exogenous retroviruses. Human endogenous retroviruses W family envelope gene (HERV-W env, also called ERVWE1), located on chromosome 7q21-22, encodes an envelope glycoprotein from the HERV-W family. Mounting evidence suggests that aberrant expression of ERVWE1 involves the etiology of schizophrenia. Moreover, the genetic and morphological studies indicate that dendritic spine deficits may contribute to the onset of schizophrenia. Here, we reported that ERVWE1 changed the density and morphology of the dendritic spine through inhibiting Wingless-type (Wnt)/c-Jun N-terminal kinases (JNK) non-canonical pathway via miR-141-3p in schizophrenia. In this paper, we found elevated levels of miR-141-3p and a significant positive correlation with ERVWE1 in schizophrenia. Moreover, serum Wnt5a and actin-related protein 2 (Arp2) levels decreased and demonstrated a significant negative correlation with ERVWE1 in schizophrenia. In vitro experiments disclosed that ERVWE1 up-regulated miR-141-3p expression by interacting with transcription factor (TF) Yin Yang 1 (YY1). YY1 modulated miR-141-3p expression by binding to its promoter. The luciferase assay revealed that YY1 enhanced the promoter activity of miR-141-3p. Using the miRNA target prediction databases and luciferase reporter assays, we demonstrated that miR-141-3p targeted Wnt5a at its 3’ untranslated region (3′ UTR). Furthermore, ERVWE1 suppressed the expression of Arp2 through non-canonical pathway, Wnt5a/JNK signaling pathway. In addition, ERVWE1 inhibited Wnt5a/JNK/Arp2 signal pathway through miR-141-3p. Finally, functional assays showed that ERVWE1 induced the abnormalities in hippocampal neuron morphology and spine density through inhibiting Wnt/JNK non-canonical pathway via miR-141-3p in schizophrenia. Our findings indicated that miR-141-3p, Wnt5a, and Arp2 might be potential clinical blood-based biomarkers or therapeutic targets for schizophrenia. Our work also provided new insight into the role of ERVWE1 in schizophrenia pathogenesis.
Development of Dot-ELISA and Colloidal Gold Immunochromatographic Strip for Rapid and Super-Sensitive Detection of Plum Pox Virus in Apricot Trees
Authors: Guo Mengmeng , Qi Duo , Dong Jinxi , Dong Saiyu , Yang Xiuling , Qian Yajuan , Zhou Xueping , Wu Jianxiang
Published: January 2023

Plum pox virus (PPV) is a causal agent of the stone fruit tree sharka disease that often causes enormous economic losses. Due to its worldwide distribution and economic importance, rapid and reliable diagnostic technologies are becoming increasingly important for successful management of sharka disease. In this study, we have produced two super-sensitive and specific anti-PPV monoclonal antibodies (i.e., MAbs 13H4 and 4A11). Using these two MAbs, we have now developed a dot enzyme-linked immunosorbent assay (dot-ELISA) and a colloidal gold immunochromatographic strip (CGICS) assay. These two technologies can be used to quickly and reliably detect PPV. The results of these sensitivity assays confirmed that the dot-ELISA and CGICS assays could detect PPV infection in apricot tree leaf crude extracts diluted up to 1:5120 and 1:6400 (w/v), respectively. Further analyses using field-collected apricot tree leaf samples showed that the detection endpoint of the dot-ELISA was ~26 times above that obtained through RT-PCR, and the CGICS was as sensitive as RT-PCR. This present study is to broaden the knowledge about detection limits of dot-ELISA and CGICS for PPV monitoring. We consider that these newly developed dot-ELISA and CGICS are particularly useful for large scale PPV surveys in fields.
Coagulation Abnormalities in Dogs with Parvoviral Enteritis
Authors: Corda Francesca , Ballocco Isabella , Corda Andrea , Mollica Alessandra , Cilano Anna , Polinas Marta , Pinna Parpaglia Maria Luisa
Published: January 2023

Hemostatic alterations have been documented in dogs with canine parvoviral enteritis. This study’s aims were to measure the standard coagulation parameters, and to assess the relationship between them and the clinical variables in dogs with canine parvoviral enteritis. Nine client-owned dogs with a canine parvoviral infection were included in a prospective, observational clinical study. Clinical score and coagulation status were assessed at admission. All nine dogs showed alterations of three or more standard coagulation variables. A correlation analysis evidenced a significantly high positive correlation between the activated partial thromboplastin time and clinical score. The present study concurs that dogs with canine parvoviral enteritis have coagulation disorders that are detectable by measuring the standard coagulation parameters.
Analyzing the Soil Microbial Characteristics of Poa alpigena Lindm. on Bird Island in Qinghai Lake Based on Metagenomics Analysis
Authors: Li Lingling , Che Zihan , Cao Yanhong , Qi Lulu , Chen Kelong , Wang Hengsheng
Published: January 2023

Poa alpigena Lindm. is a dominant forage grass that is widely distributed on the Qinghai-Tibetan Plateau and is often used in the restoration of degraded grasslands. Soil microorganisms are major players in the cycling of materials in terrestrial ecosystems. In this study, based on high-throughput sequencing, the rhizosphere and non-rhizosphere soils of Poa alpigena L. on Bird Island, Qinghai Lake, were used to investigate the effects of Poa alpigena L. on the composition and structure of soil microbial communities, and to establish associated soil microbial gene pools. Results revealed that microorganisms in the soil of Poa alpigena L. on Bird Island belonged to 62 phyla, 112 classes, 245 orders, 518 families, 1610 genera, and 5704 species. The dominant soil bacteria in rhizosphere and non-rhizosphere soils were Proteobacteria (49.62%, 47.13%) and Actinobacteria (30.31% and 31.67%), whereas the dominant fungi were Ascomycota (3.15% and 3.37%) and Basidiomycota (0.98% and 1.06%). Alpha diversity analysis revealed that the microbial richness and diversity in non-rhizosphere soil were significantly higher than those in rhizosphere soil, mainly influenced by soil water content and total nitrogen content. Furthermore, on the basis of LEfSe analysis, Alphaproteobacteria and Betaproteobacteria were identified as prominent differential taxa for rhizosphere and non-rhizosphere soils, respectively. The key differential metabolic pathways of rhizosphere soil microorganisms were those associated with the ATP-binding cassette (ABC) transporter, basal metabolism, and cytochrome P450 metabolism, whereas those of non-rhizosphere soil microorganisms included the gene expression-related pathways, methane metabolism, and pathway associated with degradation of aromatic compounds. These findings indicated that the rhizosphere soil of Poa alpigena L. is selective for microorganisms that play important roles in the oxidation of methane and regulation of the greenhouse effect on Bird Island, and that the soil environment on this island may be subject to contamination with aromatic compounds.
Carotenogenic Activity of Two Hypersaline Greek Dunaliella salina Strains under Nitrogen Deprivation and Salinity Stress
Authors: Chantzistrountsiou Xanthi , Ntzouvaras Alexandros , Papadaki Sofia , Tsirigoti Amersa , Tzovenis Ioannis , Economou-Amilli Athena
Published: January 2023

The culture growth and carotenogenic activity of two Greek Dunaliella salina strains (AthU-Al D30 and AthU-Al D31) under stress conditions are investigated herein, with emphasis on β-carotene production as well as on lutein and zeaxanthin. In particular, the strains were cultivated in “standard” conditions (60 ‰ salinity and 1.18 M of NaNO3), under salinity stress conditions (160 ‰ salinity and 1.18 M of NaNO3) and under nitrogen deprivation conditions (60 ‰ salinity and 0 M of NaNO3). In addition to the two Greek strains, the D. salina CCAP 19/18 strain, which has been extensively studied regarding carotenogenesis, is included in this study as a reference. All three strains were found to produce increased amounts of β-carotene when cultivated under nitrogen deprivation conditions, while the AthU-Al D31 strain also produced high amounts of carotenoids under salt stress. The HPLC carotenoid profiles of the strains revealed reduced production of lutein in nitrogen deprivation conditions, coupled with a high production of β-carotene. The strains exhibited various responses in terms of carotenogenic activity, indicating an intraspecific variation in the metabolic reactions related to carotenogenesis.
Determination of Seasonal Indices for the Regionalization of Low Flows in the Upper Vistula River Basin
Authors: Cupak Agnieszka , Kaczor Grzegorz
Published: January 2023

Low flow is a parameter that is used for many purposes in water management. It is particularly important in terms of the needs of small water supply systems, which usually are located in ungauged catchment areas. The aim of this study is to determine the values of seasonality indices for the regionalization of low flow characteristics in the Upper Vistula river basin. This study analyzed three seasonality indicators (seasonality index—SI; seasonality histograms—SHs; and seasonality ratio—SR) in 32 selected catchments differentiated in terms of selected physiographic and meteorological characteristics. Daily flows, from the years 1951–2016, were used in the study. On the basis of the analysis, regions characterized by similar values of seasonality indicators were delineated. The non-hierarchical method of cluster analysis, i.e., the K-means method, was used for this purpose. For each region, obtained by this method, regression models were determined using stepwise regression analysis. Three groups of low flow occurrences were determined: winter, summer and mixed. The delineation of an additional mixed group for the Upper Vistula river basin resulted in a much better fit of calculated flows to observed values than in the case when only two groups of low flow seasonality were determined (winter and summer).