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Copyright of Canadian Journal of Dental Hygiene is the property of Canadian Dental Hygienists Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background Since the outbreak of COVID-19, how to reduce the risk of spreading viruses and other microorganisms while performing aerosol generating procedures (AGPs) has become a challenging question within the dental and dental hygiene communities. The purpose of this position paper is to summarize the existing evidence about the effectiveness of various mitigation methods used to reduce the risk of infection transmission during AGPs in dentistry. Methods The authors searched six databases, MEDLINE, EMBASE, Scopus, Web of Science, Cochrane Library, and Google Scholar, for relevant scientific evidence published in the last ten years (January 2012 to December 2022) to answer six research questions about the the aspects of risk of transmission, methods, devices, and personal protective equipment (PPE) used to reduce contact with microbial pathogens and limit the spread of aerosols. Results A total of 78 studies fulfilled the eligibility criteria. There was limited literature to indicate the risk of infection transmission of SARS-CoV-2 between dental hygienists and their patients. A number of mouthrinses are effective in reducing bacterial contaminations in aerosols; however, their effectiveness against SARS-CoV-2 was limited. The combined use of eyewear, masks, and face shields are effective for the prevention of contamination of the facial and nasal region, while performing AGPs. High volume evacuation with or without an intraoral suction, low volume evacuation, saliva ejector, and rubber dam (when appropriate) have shown effectiveness in reducing aerosol transmission beyond the generation site. Finally, the appropriate combination of ventilation and filtration in dental operatories are effective in limiting the spread of aerosols. Conclusion Aerosols produced during clinical procedures can potentially pose a risk of infection transmission between dental hygienists and their patients. The implementation of practices supported by available evidence are best practices to ensure patient and provider safety in oral health settings. More studies in dental clinical environment would shape future practices and protocols, ultimately to ensure safe clinical care delivery. [ABSTRACT FROM AUTHOR]

Reducing examination table paper (ETP) use may help curb carbon emissions from health care. Six participants applied Glo Germ (DMA International) to their hands before a common physical examination (abdominal, cardiorespiratory, hip and knee) both with and without ETP. After each exam, UV light was shined on the exam table and photographs were taken. The number of hand touches on ETP-covered areas and uncovered areas were tallied and compared using t tests. Despite covering more surface area, participants touched areas without ETP significantly more than ETP-covered areas (P <.05). Despite its continued use, patients do not have much hand contact with ETP during common clinical examinations. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Soil Sciences & Agricultural Engineering is the property of Egyptian National Agricultural Library (ENAL) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Microfluidic paper‐based analytical devices (μPADs) are commonly used in point‐of‐care testing (POCT) due to their advantages of low cost and easy operation. However, the fabrication and potential environmental pollution of μPADs are the universal and pendent concerns. In this respect, a simple and novel method is developed for preparing photo‐adjustable μPADs using the photocatalytic properties of TiO2. A superhydrophobic TiO2‐paper substrate with unique photoactivity is fabricated. The flow channels on the superhydrophobic TiO2‐paper substrate can be quickly generated and on‐demand edited by a simple UV irradiation process, to fabricate various 2D and 3D μPADs for specific applications. After usage, the residual organics and biological specimens on μPADs can be easily bleached via TiO2‐assited degradation under UV or sunlight, avoiding the risk of potential environment pollution and disease transmission. The successful application of such novel substrate in the fabrication of smart and safe μPADs for sweat analysis and motion monitoring is shown. [ABSTRACT FROM AUTHOR]

This article reports on the first record of wilt and gummosis disease in subabul trees caused by Fusarium equiseti in India. Subabul trees are economically important for the paper and pulp industry in India. The affected trees exhibited symptoms of yellowing, wilting, and gummosis. Isolates of Fusarium equiseti were obtained from the diseased tissue and were found to be identical in their genetic sequences. Pathogenicity tests confirmed that the Fusarium isolates caused similar symptoms in healthy subabul plants. The rapid spread of this disease poses a threat to subabul plantations, and the development of management strategies is necessary. [Extracted from the article]

We study a three-species cyclic game system where organisms face a contagious disease whose virulence may change by a pathogen mutation. As a responsive defence strategy, organisms' mobility is restricted to reduce disease dissemination in the system. The impact of the collective self-preservation strategy on the disease infection risk is investigated by performing stochastic simulations of the spatial version of the rock–paper–scissors game. Our outcomes show that the mobility control strategy induces plasticity in the spatial patterns with groups of organisms of the same species inhabiting spatial domains whose characteristic length scales depend on the level of dispersal restrictions. The spatial organisation plasticity allows the ecosystems to adapt to minimise the individuals' disease contamination risk if an eventual pathogen alters the disease virulence. We discover that if a pathogen mutation makes the disease more transmissible or less lethal, the organisms benefit more if the mobility is not strongly restricted, thus forming large spatial domains. Conversely, the benefits of protecting against a pathogen causing a less contagious or deadlier disease are maximised if the average size of groups of individuals of the same species is significantly limited, reducing the dimensions of groups of organisms significantly. Our findings may help biologists understand the effects of dispersal control as a conservation strategy in ecosystems affected by epidemic outbreaks. • Stochastic simulations of the rock–paper–scissors model with organisms facing a disease spreading are performed. • The effects of individuals' mobility restrictions on the spatial organisation scale are quantified. • The impact of changes in the disease virulence on population dynamics is studied. • The benefits of the spatial organisation plasticity induced by the adaptation of the mobility restrictions in response to changes in the disease virulence are calculated. [ABSTRACT FROM AUTHOR]

Paper products are widely used in daily life, while the lack of antibacterial activity has made them become some disease transmission media. Herein, we introduced NIR-responsive molybdenum disulfide nanosheets (MoS 2) to endow nanocellulose paper antibacterial activity by electrostatic self-assembly with quaternized chitosan (QCS). Firstly, the MoS 2 nanosheets were exfoliated and stabilized with QCS under ultrasonication. The strong coordination between QCS and MoS 2 as well as the electrostatic attraction between QCS and cellulose nanofiber (CNF) helped to fabricate the MoS 2 @QCS/CNF composite paper. The MoS 2 @QCS/CNF composite paper exhibited excellent photothermal and photodynamic activity, achieving over 99.9% antibacterial efficacy against both E. coli and S. aureus , respectively. The hyperthermia induced by MoS 2 accelerated the glutathione (GSH) consumption and the reactive oxygen species (ROS)-independent oxidative stress destroyed the bacteria membranes integrity, synergistically leading to the malondialdehyde (MDA) oxidation and protein leakage to inhibit the bacteria growth. Importantly, the self-assembled fibrous network incorporating with the photo-stable antibacterial MoS 2 enabled the flexible composite paper with excellent mechanical strength and recyclability for long-term antimicrobial, possessing over 99.9% inhibition even after five cycles. No cell cytotoxicity was observed for the MoS 2 @QCS/CNF composite paper, suggesting the potential of composite paper for bacterial infection control. [Display omitted] • The MoS 2 nanosheets were exfoliated and stabilized with quaternized chitosan (QCS). • QCS acted as glue to fabricate the electrostatic self-assembled MoS 2 @QCS/CNF paper. • The NIR-responsive paper had a strong killing effect on pathogenic bacteria. • The composite paper showed excellent mechanical stability and cytocompatibility. • The composite paper had > 99% sterilization efficacy after five antibacterial cycles. [ABSTRACT FROM AUTHOR]

The mathematical modeling of infectious diseases has become of paramount importance in recent years. Since 2019, with the worldwide spread of the Covid-19 pandemic, many already existing mathematical models have been improved. This paper focuses on the digital analysis of a model of transmission of the Covid-19 disease by means of Chebyshev wavelets. The analysis of the results obtained makes it possible to make a very good forecast of positive Covid-19 cases according to the parameters studied. [ABSTRACT FROM AUTHOR]

Under the dual pressure of energy consumption and environmental pollution, mankind hopes to develop clean and renewable alternative energy, and the rapid development of fuel cells meets people's demand for energy-efficient power systems. The emergence of portable micro energy systems represented by microfluidic fuel cells, such as paper-based microfluidic fuel cells, has greatly enriched the means of medical detection to better cope with the threat of disease transmission. In this work, the numerical simulation method is innovatively introduced to study the paper-based microfluidic fuel cells. Both transient and steady-state modes are employed to demonstrate the whole operation process of the paper-based microfluidic fuel cell. In addition, the different structural parameters, including electrode spacing, the distance between electrode and inlet, channel thickness, and electrode length, are also investigated their influence mechanisms on cell performance. Results show that the increase of most structural parameters decreases cell output power in different degrees. Even on the premise that increasing channel thickness has a positive impact on the output power, the fuel utilization still shows a downward trend. These conclusions provide theoretical support and reference for future optimization work and accelerate the development of microfluidic fuel cells. • Numerical simulation is employed to study paper-based microfluidic fuel cell. • The effects of structure parameters on cell performance are discussed. • Through fuel concentration distribution to reveal cell performance mechanism. • Fuel utilization is used to evaluate energy efficiency. [ABSTRACT FROM AUTHOR]

But this reliance on an inherent transmission assumption can lead to challenges in interpretation, particularly in rapidly changing epidemics that take several generations of infection to settle to equilibrium. Understanding the extent of disease transmission - and how it changes over time - is a deceptively difficult problem, and these papers highlight some key considerations in how we should estimate and interpret COVID transmission dynamics. Even if we were to be omniscient, and see every contact and every transmission event, we would still have to make conceptual decisions about whether we are looking back at transmission that has already occurred, or predicting ongoing transmission from current infectious individuals, which is subject to right truncation. [Extracted from the article]

Background: Access to correct information can influence the formation of the right attitude towards mitigating the spread of the COVID-19. Many individuals in Nigeria have taken up non-scientifically approved practices in a bid to protect themselves from the virus. The aim of this study was to assess the source of information, and knowledge of the cause and mode of transmission of the COIVD-19 among local traders in Ibadan, Oyo State, Nigeria. Methods: A cross-sectional study of local traders from two densely populated markets in Ibadan was conducted using an interviewer-administered semi-structured questionnaire. Data were analyzed using SPSS software v. 25 and Microsoft Excel 2016 and were presented in frequency tables and charts. The Chi-square test was used to test the associations. The level of significance was set at P<0.05. Results: A total of 321 traders (27.4% were males and 72.6% were females) were recruited with a Mean±SD age of 39.4±11.8 years. Radio (93.5%) and television (75.7%) were the most commonly used sources of information, 65.8% believed that COVID-19 was a result of divine punishment for sins and the majority (95.3%) reported that COVID-19 was spread through personal contact with infected persons. There was a statistically significant association between knowledge of cause and age (P=0.004), as well as between knowledge of cause and marital status (P=0.001). Additionally, a statistically significant association was observed between knowledge of transmission and level of education (P=0.012). Conclusion: Even though they have access to adequate information, people may not take proper actions to protect themselves and others from contracting the COVID-19. Reinforced health promotion strategies that pay attention to the local contexts and perspectives of community members should be taken across the board. Background: Access to correct information can influence the formation of the right attitude towards mitigating the spread of the COVID-19. Many individuals in Nigeria have taken up non-scientifically approved practices in a bid to protect themselves from the virus. The aim of this study was to assess the source of information, and knowledge of the cause and mode of transmission of the COIVD-19 among local traders in Ibadan, Oyo State, Nigeria. Methods: A cross-sectional study of local traders from two densely populated markets in Ibadan was conducted using an interviewer-administered semi-structured questionnaire. Data were analyzed using SPSS software v. 25 and Microsoft Excel 2016 and were presented in frequency tables and charts. The Chi-square test was used to test the associations. The level of significance was set at P<0.05. Results: A total of 321 traders (27.4% were males and 72.6% were females) were recruited with a Mean±SD age of 39.4±11.8 years. Radio (93.5%) and television (75.7%) were the most commonly used sources of information, 65.8% believed that COVID-19 was a result of divine punishment for sins and the majority (95.3%) reported that COVID-19 was spread through personal contact with infected persons. There was a statistically significant association between knowledge of cause and age (P=0.004), as well as between knowledge of cause and marital status (P=0.001). Additionally, a statistically significant association was observed between knowledge of transmission and level of education (P=0.012). Conclusion: Even though they have access to adequate information, people may not take proper actions to protect themselves and others from contracting the COVID-19. Reinforced health promotion strategies that pay attention to the local contexts and perspectives of community members should be taken across the board. [ABSTRACT FROM AUTHOR]

Identifying influential spreaders in complex networks is a crucial issue that can help control the propagation process in complex networks. An aviation network is a typical complex network, and accurately identifying the key city nodes in the aviation network can help us better prevent network attacks and control the spread of diseases. In this paper, a method for identifying key nodes in undirected weighted networks, called weighted Laplacian energy centrality, was proposed and applied to an aviation network constructed from real flight data. Based on the analysis of the topological structure of the network, the paper recognized critical cities in this network, then simulation experiments were conducted on key city nodes from the perspectives of network dynamics and robustness. The results indicated that, compared with other methods, weighted Laplacian energy centrality can identify the city nodes with the most spreading influence in the network. From the perspective of network robustness, the identified key nodes also have the characteristics of accurately and quickly destroying network robustness. [ABSTRACT FROM AUTHOR]

Objective: To end the AIDS epidemic by 2030, despite the increasing poverty and inequalities, policies should be designed to deal with population heterogeneity and environmental changes. Bottom-up designs, such as the Agent-Based Model (ABM), can model these features, dealing with such complexity. HIV/AIDS has a complex dynamic of structural factors, risk behaviors, biomedical characteristics and interventions. All embedded in unequal, stigmatized and heterogeneous social structure. To understand how ABMs can model this complexity, we performed a scoping review of HIV applications, highlighting their potentialities. Methods: We searched on PubMed, Web of Science, and Scopus repositories following the PRISMA extension for scoping reviews. Our inclusion criteria were HIV/AIDS studies with an ABM application. We identified the main articles using a local co-citation analysis and categorized the overall literature aims, (sub)populations, regions, and if the papers declared the use of ODD protocol and limitations. Results: We found 154 articles. We identified eleven main papers, and discussed them using the overall category results. Most studies model Transmission Dynamics (37/154), about Men who have sex with Men (MSM) (41/154), or individuals living in the US or South Africa (84/154). Recent studies applied ABM to model PrEP interventions (17/154) and Racial Disparities (12/154). Only six papers declared the use of ODD Protocol (6/154), and 34/154 didn't mention the study limitations. Conclusions: While ABM is among the most sophisticated techniques available to model HIV/AIDS complexity. Their applications are still restricted to some realities. However, researchers are challenged to think about social structure due model characteristics, the inclusion of these features is still restricted to case-specific. Data and computational power availability can enhance this feature providing insightful results. [ABSTRACT FROM AUTHOR]

This paper examines Russia's propaganda discourse on Twitter during the 2022 invasion of Ukraine. The study employs network analysis, natural language processing (NLP) techniques, and qualitative analysis to identify key communities and narratives associated with the prevalent and damaging narrative of "fascism/Nazism" in discussions related to the invasion. The paper implements a methodological pipeline to identify the main topics, and influential actors, as well as to examine the most impactful messages in spreading this disinformation narrative. Overall, this research contributes to the understanding of propaganda dissemination on social media platforms and provides insights into the narratives and communities involved in spreading disinformation during the invasion. [ABSTRACT FROM AUTHOR]

In this paper, a new delayed fractional-order model including susceptible migratory birds, infected migratory birds and predators is proposed to discuss the spread of diseases among migratory birds. Fear of predators is considered in the model, as fear can reduce the reproduction rate and disease transmission rate among prey. First, some basic mathematical results of the proposed model are discussed. Then, time delay is regarded as a bifurcation parameter, and the delay-induced bifurcation conditions for such an uncontrolled system are established. A novel periodic pulse feedback controller is proposed to suppress the bifurcation phenomenon. It is found that the control scheme can successfully suppress the bifurcation behavior of the system, and the pulse width can be arbitrarily selected on the premise of ensuring the control effect. Compared with the traditional time-delay feedback controller, the control scheme proposed in this paper has more advantages in practical application, which not only embodies the advantages of low control cost and easy operation but also caters to the periodic changes of the environment. The proposed control scheme, in particular, remains effective even after the system has been disrupted by a constant. Numerical simulation verifies the correctness of the theoretical results. [ABSTRACT FROM AUTHOR]

Harvesting usable and meaningful disaster-related, spatio-temporal data at a highly granular level poses major challenges in its cleaning and aggregation. This paper presents a strategy related to those challenges with respect to individual behavior near COVID-19 laden healthcare facilities. This is done to enable the visualizing of egress behavior data as interactive, three-dimensional (3D) scenes to investigate human behavior patterns regarding touch-based, disease transmission. Therefore, the aim is to demonstrate how this concept of 3D epidemiology may provide new mechanisms to understand the relative risk and exposure prevalence for data analysis. This paper demonstrates 3D enablement of disaster-related field data through use of first-hand observations of 1,936 individuals egressing New York City healthcare facilities during the onset of COVID-19 in the Spring of 2020. The observations capture egress behavior in terms of where people go (e.g. coffee shop, Subway) and how they physically interact with the surroundings (i.e. what they touch and how long they remain). This paper introduces a mechanism for automated extraction and 3D visualization of such data in Potree, an open-source Web Graphics Library (WebGL) point cloud viewer. Distinctive vertex shaders are used to distinguish specific destination selection and behavioral patterns (e.g. personal protective equipment usage). Two-dimensional heatmaps are paired with 3D scenes to demonstrate the potential of using 3D visualization of spatio-temporal patterns for visualizing disease transmission potential. [ABSTRACT FROM AUTHOR]

Background: A larger percentage of social housing tenants have poorer physical and mental health outcomes compared to private renters and homeowners. They are also at a greater risk of respiratory conditions, cardiovascular disease, communicable disease transmission and mortality. One approach that aims to reduce health inequalities is to create research partnerships with underserved local communities. Our primary aim was to develop a research partnership with social housing tenants in Nottingham and our secondary aim was to explore the health priorities of these social housing tenants to inform future research applications. We also hope to provide a descriptive process of PPI within a social housing context for other researchers to learn from. Methods: We used Public and Patient Involvement (PPI) as the foundation of this work, as we believed that people with lived experience of social housing, also end-users of the research, were best placed to inform us of the areas with the greatest research need. Through online and in-person focus groups, we discussed with tenants, collectively named a Social Advisory Group (SAG), their health concerns and priorities. Together they raised 26 health issues, which were combined with 22 funding opportunity themes being offered by the NIHR (National Institute for Health and Care Research). This was with the purpose of investigating whether there was alignment between the health needs of Nottingham's social housing tenants and the NIHR's research priorities. A prioritisation technique (Diamond Nine) was used to sort in total, 48 areas of health and wellbeing, into three top priorities. Tenants were provided the opportunity to be involved in public health research in other ways too, such as reviewing this paper and also an NIHR Programme Development Grant application to expand and continue this work. One was also offered the opportunity to be a public co-applicant. Results: The group prioritised improvements in the quality of social housing, mental health and healthcare services. There was only some alignment between these and the NIHR funding themes. Other factors, such as age and race, also determined individual health priorities.. The diversity and reach of the current project were limited, however this is something we hope to improve in the future with more funding. We learned that tenants have varying degrees of mobility and technological abilities, requiring both online and in-person meetings. Plain English summary: Social housing is offered to people who cannot afford to buy or rent in the open market, and a larger percentage of social housing tenants have poorer physical and mental health outcomes compared to the general population. One approach that aims to reduce health inequalities is to create sustainable research partnerships with underserved local communities. Our primary aim was to involve social housing tenants in public health research, as they are best placed to tell us the type of research they would benefit from. The secondary aim was to explore the health priorities of social housing tenants to inform future research applications. We also hope to describe the process of PPI within a social housing context for other researchers to learn from. To achieve these aims, we established a research partnership with a group of social housing tenants in Nottingham and spoke to them about the areas of their health they wanted to improve (i.e., their priorities). The topics that were discussed the most were the need for improved mental health, quality of social housing and healthcare services, however this varied between individuals according to race and age. We learned several things throughout this process. Firstly, the combination of mobility and technological abilities amongst tenants meant that meetings must be held both in-person and online. This ensured they remained accessible and convenient. Secondly, we learnt that in-person meetings should be held in a neutral space to encourage different members of the group to attend. Finally, in general, people were very enthusiastic about this partnership and were committed to seeing improvements in public health. We therefore provided more opportunities for the group to be involved in research. For example, they were offered the opportunity to write and edit a lay summary for a future research application, which was based on the priorities identified in this paper. One member of the group was nominated to be the public co-applicant , which would allow us to increase the reach of this housing work across the East Midlands. It would also allow us to increase the diversity of the group, as currently it is made up of mostly retired females of British origin. Involving the public in health research has been central to this process and continues to be important in the production of accessible and relevant research. [ABSTRACT FROM AUTHOR]

Cholera, as an endemic disease around the world, has imposed great harmful effects on human health. In addition, from a microscopic viewpoint, the interference of random factors exists in the process of virus replication. However, there are few theoretical studies of viral infection models with biologically reasonable stochastic effects. This paper studied a stochastic cholera model used to describe transmission dynamics in China. In this paper, we adopted a special method to simulate the effect of environmental perturbations to the system instead of using linear functions of white noise, i.e., the transmission rate of environment to human was satisfied Ornstein-Uhlenbeck processes, which is a more practical and interesting. First, it was theoretically proved that the solution to the stochastic model is unique and global, with an ergodic stationary distribution. Moreover, by solving the corresponding Fokker-Planck equation and using our developed algebraic equation theory, we obtain the exact expression of probability density function around the quasi-equilibrium of the stochastic model. Finally, several numerical simulations are provided to confirm our analytical results. [ABSTRACT FROM AUTHOR]

During COVID and lockdown, many prisoners have not only been affected by infection transmission in crowded and ill-equipped institutions, they have also been separated from a range of supports, including loss of family and professional supports and support for prisoners with addiction and/or mental health problems has been disrupted. This paper reports on evidence of how peer-based recovery organizations have attempted to mitigate these adverse effects, based on a case study of one prison in the North-West of England, using a range of routine reporting data and original research data. The paper shows how prison-based peer recovery support has not only continued through lockdown but grown both in the prison and in continuing care on release. The key conclusion is that Lived Experience Recovery Organizations (LEROs) have a vital role to play in offering continuing care to prison populations both to support early recovery and to sustain change around release back into the community, in COVID but also more generally. [ABSTRACT FROM AUTHOR]

Background: As the global community begins recovering from the COVID-19 pandemic, the challenges due to its aftermath remain. This health crisis has highlighted challenges associated with airborne pathogens and their capacity for rapid transmission. While many solutions have emerged to tackle this challenge, very few devices exist that are inexpensive, easy to manufacture, and versatile enough for various settings. Methods: This paper presents a novel suction device designed to counteract the spread of aerosols and droplets and be cost-effective and adaptable to diverse environments. We also conducted an experimental study to evaluate the device's effectiveness using an artificial cough generator, a particle counter, and a mannequin in an isolated system. We measured droplet removal rates with simulated single and repeated cough incidents. Also, measurements were taken at four distinct areas to compare its effectiveness on direct plume versus indirect particle removal. Results: The device reduced airborne disease transmission risk, as evidenced by its capacity to decrease the half-life of aerosol volume from 23.6 minutes to 15.6 minutes, effectively capturing aerosol-sized droplets known for their extended airborne persistence. The suction device lessened the peak total droplet volume from peak counts. At 22 minutes post peak droplet count, the count had dropped 24% without the suction device and 43% with the suction device. Conclusions: The experiment's findings confirm the suction device's capability to effectively remove droplets from the environment, making it a vital tool in enhancing indoor air quality. Given the sustained performance of the suction device irrespective of single or multiple cough events, this demonstrates its potential utility in reducing the risk of airborne disease transmission. 3D printing for fabrication opens the possibility of a rapid iterative design process, flexibility for different configurations, and rapid global deployment for future pandemics. [ABSTRACT FROM AUTHOR]

The occurrence and spread of infectious diseases pose considerable challenges to public health. While the relationship between the built environment and the spread of infectious diseases is well-documented, there is a dearth of urban planning tools specifically designed for conducting Health Impact Assessments (HIAs) targeted at infectious diseases. To bridge this gap, this paper develops a comprehensive framework of an HIA for Urban Planning and Epidemic (HIA4UPE), formulated by considering the progression of public health incidents and the distinct transmission patterns of infectious diseases. This framework is designed to provide a comprehensive assessment by including a health risk-overlay assessment, health resource-quality assessment, health resource-equality assessment, and health outcome-impact prediction, enabling a multidimensional evaluation of the potential impacts of current environmental conditions or planning proposals on the incidence of infectious diseases. Furthermore, this paper advances the application of spatial analysis and computation, comprehensive assessment methodologies, and predictive analytics to conduct specific assessments. The theoretical framework and analytical tools presented in this paper contribute to the academic discourse and offer practical utility in urban planning and policymaking on epidemic prevention and control. [ABSTRACT FROM AUTHOR]

This paper focuses on the discovery of unusual spatiotemporal associations across multiple phenomena from distinct application domains in a spatial neighborhood where each phenomenon is represented by anomalies from the domain. Such an approach can facilitate the discovery of interesting links between distinct domains, such as links between traffic accidents and environmental factors or road conditions, environmental impacts and human factors, disease spread, and hydrological trajectory, to name a few. This paper proposes techniques to discover spatiotemporal associations across distinct phenomena using a series of anomalous windows from each domain that represent a phenomenon. We propose a novel metric called influence score to quantify the associated influence between the phenomena. In addition, we also propose spatiotemporal confidence, support, and lift measures to quantify these associations. Two novel algorithms for finding multi-domain spatiotemporal associations across phenomena are proposed. We present experimental results across real-world phenomena that are linked and discuss the efficacy of our approach. [ABSTRACT FROM AUTHOR]

Understanding and modeling individuals' behaviors during epidemics is crucial for effective epidemic control. However, existing research ignores the impact of users' irrationality on decision-making in the epidemic. Meanwhile, existing disease control methods often assume users' full compliance with measures like mandatory isolation, which does not align with the actual situation. To address these issues, this paper proposes a prospect theorybased framework to model users' decision-making process in epidemics and analyzes how irrationality affects individuals' behaviors and epidemic dynamics. According to the analysis results, irrationality tends to prompt conservative behaviors when the infection risk is low but encourages risk-seeking behaviors when the risk is high. Then, this paper proposes a behavior inducement algorithm to guide individuals' behaviors and control the spread of disease. Simulations and real user tests validate our analysis, and simulation results show that the proposed behavior inducement algorithm can effectively guide individuals' behavior. [ABSTRACT FROM AUTHOR]

For example, in recruiting participants randomly from those registered for healthcare in England, the REACT-1 design attempts to reduce the impact of temporal variation when making growth rate estimates (Riley et al., [4]). REACT is a program of studies separated into REACT-1 (Riley et al., [4]) that collects self-administered nose and throat swabs (Riley et al., [4]) and REACT-2 that collects self-administered lateral-flow antibody tests (Ward et al., [6]). In addition to growth rates, population surveys of infection provide estimates of prevalence at national and regional scales that can be easily understood as measures of individual risk: measured swab-positivity is easily translated into odds of infection. [Extracted from the article]

This paper estimates the state transition of COVID-19 positive cases by analyzing the data about confirmed positive cases in Tokyo, Japan. The prediction of the number of newly infected persons is one of the active research topics for the COVID-19 pandemic. Although such a prediction is important for recognizing the future risk of spreading infectious diseases, understanding the state transition after they are confirmed to be positive is also important for estimating the number of required ICUs, hotel rooms for isolation, etc. This paper classifies the state after being positive into "in hotel/home for isolation," "in hospital with a mild state," "in hospital with a severe state," "recovered," and "dead" and estimates the transition probabilities among those states from the data about confirmed positive cases in Tokyo, Japan. This paper shows the parameters estimated from different periods and discusses the difference considering the pandemic situation. An agent simulation using the estimated transition probabilities as its parameters is also proposed. The result of the simulation from August to November 2020 shows the predicted number of agents is close to the actual data. As one of the possible applications to the proposed agent simulation, this paper shows the simulation result from December 2020 to January 2021 under a hypothetical situation. [ABSTRACT FROM AUTHOR]

Background: During dental procedures, critical parameters, such as cooling condition, speed of the rotary dental turbine (handpiece), and distance and angle from pollution sources, were evaluated for transmission risk of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), simulated by spiking in a plasmid encoding a modified viral spike protein, HexaPro (S6P), in droplets and aerosols. Methods: To simulate routine operation in dental clinics, dental procedures were conducted on a dental manikin within a digital dental unit, incorporating different dental handpiece speeds and cooling conditions. The tooth model was immersed in Coomassie brilliant blue dye and was pre-coated with 100 μL water spiked-in with S6P-encoding plasmid. Furthermore, the manikin was surrounded by filter papers and Petri dishes positioned at different distances and angles. Subsequently, the filter papers and Petri dishes were collected to evaluate the aerosol splash points and the viral load of S6P-encoding plasmid in aerosols and splatters generated during the dental procedure. Results: Aerosol splashing generated a localized pollution area extended up to 60 cm, with heightened contamination risks concentrated within a 30 cm radius. Significant differences in aerosol splash points and viral load by different turbine handpiece speeds under any cooling condition (P < 0.05) were detected. The highest level of aerosol splash points and viral load were observed when the handpiece speed was set at 40,000 rpm. Conversely, the lowest level of aerosol splash point and viral load were found at a handpiece speed of 10,000 rpm. Moreover, the aerosol splash points with higher viral load were more prominent in the positions of the operator and assistant compared to other positions. Additionally, the position of the operator exhibited the highest viral load among all positions. Conclusions: To minimize the spread of aerosol and virus in clinics, dentists are supposed to adopt the minimal viable speed of a dental handpiece with limited cooling water during dental procedures. In addition, comprehensive personal protective equipment is necessary for both dental providers and dental assistants. [ABSTRACT FROM AUTHOR]

Purpose: This paper explores the reasons why Indonesia must have legal regulations to provide protection and guarantees for health workers in carrying out the profession in overcoming corona virus disease (COVID-19). This paper also explains the legal regulations as the foundation for today's medical workers' protection. This paper also aims at providing an ideal legal construction that safeguards the rights and obligations of health workers in overcoming COVID-19. Design/methodology/approach: In this paper, the author used qualitative research methods with a socio-legal approach. The data were obtained through literature study and analysis of laws and regulations through the socio-legal method. Findings: Various challenges and professional risks taken by health workers in dealing with COVID-19 derive from several factors, such as shortage of personal protective equipment, ineffective implementation of informed consent from the patients and the negative stigma spreading in the community. Moreover, the current legal regulation has not particularly modulated the protection of health workers, relying only on available articles that are actually irrelevant to be applied in the COVID-19 pandemic. Research limitations/implications: This research is focused on problems faced by health workers in combating COVID-19 and law concessions to ensure their protection. Practical implications: The final results of this research will be useful for The House of Representatives (DPR), the Ministry of Health of the Republic of Indonesia (Kemenkes RI) and the Indonesian Medical Association (IDI) in establishing legal and regulatory construction for the protection of health workers in tackling COVID-19. Social implications: This research aims at strengthening legal protections for the health workers so that their rights and obligations are well guaranteed. Originality/value: This paper proposes an ideal legal construction for the protection of health workers during the COVID-19 pandemic, which is currently still not specifically and rigidly regulated, to realize a guaranteed and sustainable life for health workers. [ABSTRACT FROM AUTHOR]

A stochastic network simulation is verified when its distribution of outputs is aligned with the ground truth, while tolerating deviations due to variability in real-world measurements and the randomness of a stochastic simulation. However, comparing distributions may yield false positives, as erroneous simulations may have the expected distribution yet present aberrations in low-level patterns. For instance, the number of sick individuals may present the right trend over time, but the wrong individuals were infected. We previously proposed an approach that transforms simulation traces into images verified by machine learning algorithms that account for low-level patterns. We demonstrated the viability of this approach when many simulation traces are compared with a large ground truth data set. However, ground truth data are often limited. For example, a publication may include few images of their simulation as illustrations; hence, teams that independently re-implement the model can only compare low-level patterns with few cases. In this paper, we examine whether our approach can be utilized with very small data sets (e.g., 5–10 images), as provided in publications. Depending on the network simulation model (e.g., rumor spread, cascading failure, and disease spread), we show that results obtained with little data can even surpass results obtained with moderate amounts of data at the cost of variability. Although a good accuracy is obtained in detecting several forms of errors, this paper is only a first step in the use of this technique for verification; hence, future works should assess the applicability of our approach to other types of network simulations. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has exposed several chinks in the armour of public health infrastructure across the world. However, the impact of the pandemic has been assessed primarily from the perspective of the 'privileged' members of society. The experiences of the 'other' world inhabited by the marginalised communities, who have had their livelihoods crushed under the weight of the pandemic, have been scarcely documented. As thousands of migrant workers were more scared of death caused by hunger rather than the disease itself, the various steps taken by different countries to curb community transmission have unveiled the ugly side of these measures. For example, as several states such as the US, the UK, Singapore, Hong Kong, and India/Bharat imposed lockdowns, border closures, quarantines, inter alia, the most vulnerable section of the human population has been the migrant workers, especially those individuals who were employed in the unorganised sector. Thus, the global health crisis has unravelled deep-rooted deficiencies, racial biases, and an overall lack of concern and empathy for the lesser privileged, apart from the growing socio-economic divide between the rich and the poor. This research paper aims to explore the impact of the COVID-19 pandemic on migrant workers in the informal sector by exploring the measures imposed by the US, the UK, Singapore, Hong Kong, and India/Bharat and analyse how their fundamental rights, including the right to development, were compromised. Through this paper, the author provides a five-point strategic framework that can be adopted globally to prevent such instances in the future. [ABSTRACT FROM AUTHOR]

Zoonotic diseases represent a significant societal challenge in terms of their health and economic impacts. One Health approaches to managing zoonotic diseases are becoming more prevalent, but require novel thinking, tools and cross-disciplinary collaboration. Bovine tuberculosis (bTB) is one example of a costly One Health challenge with a complex epidemiology involving humans, domestic animals, wildlife and environmental factors, which require sophisticated collaborative approaches. We undertook a scoping review of multi-host bTB epidemiology to identify trends in species publication focus, methodologies, and One Health approaches. We aimed to identify knowledge gaps where novel research could provide insights to inform control policy, for bTB and other zoonoses. The review included 532 articles. We found different levels of research attention across episystems, with a significant proportion of the literature focusing on the badger-cattle-TB episystem, with far less attention given to tropical multi-host episystems. We found a limited number of studies focusing on management solutions and their efficacy, with very few studies looking at modelling exit strategies. Only a small number of studies looked at the effect of human disturbances on the spread of bTB involving wildlife hosts. Most of the studies we reviewed focused on the effect of badger vaccination and culling on bTB dynamics with few looking at how roads, human perturbations and habitat change may affect wildlife movement and disease spread. Finally, we observed a lack of studies considering the effect of weather variables on bTB spread, which is particularly relevant when studying zoonoses under climate change scenarios. Significant technological and methodological advances have been applied to bTB episystems, providing explicit insights into its spread and maintenance across populations. We identified a prominent bias towards certain species and locations. Generating more high-quality empirical data on wildlife host distribution and abundance, high-resolution individual behaviours and greater use of mathematical models and simulations are key areas for future research. Integrating data sources across disciplines, and a "virtuous cycle" of well-designed empirical data collection linked with mathematical and simulation modelling could provide additional gains for policy-makers and managers, enabling optimised bTB management with broader insights for other zoonoses. [ABSTRACT FROM AUTHOR]

Background: The prolonged presence of Syrian refugees in Jordan has highlighted the need for sustainable health service delivery models for refugees. In 2012, the Jordanian government adopted a policy that granted Syrian refugees access, free of charge, to the national health system. However since 2012, successive policy revisions have limited refugee access. This paper seeks to understand factors that initially put refugee integration into the health system on the policy agenda, as well as how these same factors later affected commitment to sustain the policy. Methods: This paper draws on data from a document review of 197 peer-reviewed and grey literature publications, a media analysis of newspaper articles retrieved from four officially recognized newspapers in Jordan, and 33 semi-structured key informant interviews. We used Kingdon's Multiple Streams Model – a well-established tool for analyzing policy adoption – to understand how political priority developed for integration of refugees into the health system. Results: We find that several factors helped bring attention to the issue, namely concerns over infectious disease transmission to host communities, high rates of chronic conditions among the refugee population and the increasingly urban and dispersed nature of refugees. At the outset of the conflict, the national mood was receptive to refugees. Politicians and government officials quickly recognized the crisis as an opportunity to secure material and technical support from the international humanitarian community. At the same time, global pressures for integrating refugees into national health systems helped move the integration agenda forward in Jordan and the region more broadly. Since 2012, there were several modifications to the policy that signal profound changes in national views around the continued presence of Syrian refugees in the country, as well as reduced external financial support which has undermined the sustainability of the policy. Conclusion: This case study underscores the dynamic nature of policymaking and the challenge of sustaining government commitment to the right to health among refugees. Our analysis has important implications for advocates seeking to advance and maintain momentum for the integration of refugees into national health systems. [ABSTRACT FROM AUTHOR]

Human distance estimation is essential in many vital applications, specifically, in human localisation-based systems, such as independent living for older adults applications, and making places safe through preventing the transmission of contagious diseases through social distancing alert systems. Previous approaches to estimate the distance between a reference sensing device and human subject relied on visual or high-resolution thermal cameras. However, regular visual cameras have serious concerns about people's privacy in indoor environments, and high-resolution thermal cameras are costly. This paper proposes a novel approach to estimate the distance for indoor human-centred applications using a low-resolution thermal sensor array. The proposed system presents a discrete and adaptive sensor placement continuous distance estimators using classification techniques and artificial neural network, respectively. It also proposes a real-time distance-based field of view classification through a novel image-based feature. Besides, the paper proposes a transfer application to the proposed continuous distance estimator to measure human height. The proposed approach is evaluated in different indoor environments, sensor placements with different participants. This paper shows a median overall error of ± 0.2 m in continuous-based estimation and 96.8 % achieved-accuracy in discrete distance estimation. [ABSTRACT FROM AUTHOR]

Background: There is an increase in number of Human Papillomavirus related head and neck squamous cell carcinoma (HPV-related HNSCC) High risk HPV(HR-HPV) types can be cleared by an infected person, however, some can persist and develop HN cancer. There is a broad knowledge gap regarding HPV and related cancers. Main text: The aim of this review is to assess existing published knowledge on oral-genital HPV transmission, concordance of HPV genotypes and risk of oral or/and genital lesions among spouses/partners of patients diagnosed with HPV-related HNSCC, identify gaps in the current research and highlight areas that requires further inquiry. Method: Database like Pub med, Google Scholar, Scopus, Puplon, Wiley online library were used for search strategy. Published papers on transmission, concordance of HPV genotypes and genital lesions among spouses/partners of patients diagnosed with HPV-related HNSCC were included. Papers published from January1,2000 to October 31, 2022 were included. The published papers included are 8 Case reports, 2 cross-sectional studies, 3 Cohort studies and 2 systematic reviews. Results: A total of 2125 citations were retrieved from the five sources. 15papers were included. Case reports reported concurrent HPV-related oropharyngeal, tonsillar, unspecified HNSCC, laryngeal and nasopharyngeal carcinoma among couples. The two cross-sectional studies were done. Almost all the tumors taken from patients with HPV-related oropharyngeal carcinoma (HPV-related OPC) and their spouses were positive for identical HPV 16 type. The three cohort studies showed an increase risk of upper aero-digestive tract cancer among male spouses of females with cervical cancer. Two systematic reviews reviewed literature studies which evaluated concurrent cases of HPV-related Oropharyngeal cancers. Examination of these papers showed that the majority of the studies suggested that there is HPV transmission, concordance and risk of HNSCC cancer among spouses with HPV-related oral-genital cancer. No studies evaluated the risk of developing genital cancer in spouses of patients with HNSCC. Conclusion: The findings of this review highlighted big need of further research on oral-genital HPV infection among spouses of patients diagnosed with HPV-related HNSCC. Studies are needed to evaluate the risk of getting genital and upper aero-digestive tract HPV-related cancer among spouses with HPV-related HNC. [ABSTRACT FROM AUTHOR]

As COVID-19 has spread rapidly, detection of the COVID-19 infection from radiology and radiography images is probably one of the quickest ways to diagnose the patients. Many researchers found the necessity to utilize chest X-ray and chest computed tomography imaging to diagnose COVID-19 infection. In this paper, our objective is to minimize the false negatives and false positives in the detection process. Reduction in the number of false negatives minimizes community spread of the COVID-19 pandemic. Reducing false positives help people avoid mental trauma and wasteful expenses. This paper proposes a novel weighted consensus model to minimize the number of false negatives and false positives without compromising accuracy. In the proposed novel weighted consensus model, the accuracy of individual classification models is normalized. While predicting, different models predict different classes, and the sum of the normalized accuracy for a particular class is then considered based on a predefined threshold value. We used traditional Machine Learning classification algorithms like Linear Regression, Support Vector Machine, k-Nearest Neighbours, Decision Tree, and Random Forest for the weighted consensus experimental evaluation. We predicted the classes, which provided better insights into the condition. The proposed model can perform as well as the existing state-of-the-art technique in terms of accuracy (99.64%) and reduce false negatives and false positives. [ABSTRACT FROM AUTHOR]

The prevention and control of communicable diseases such as COVID-19 has been a worldwide problem, especially in terms of mining towards latent spreading paths. Although some communication models have been proposed from the perspective of spreading mechanism, it remains hard to describe spreading mechanism anytime. Because real-world communication scenarios of disease spreading are always dynamic, which cannot be described by time-invariant model parameters, to remedy such gap, this paper explores the utilization of big data analysis into this area, so as to replace mechanism-driven methods with big data-driven methods. In modern society with high digital level, the increasingly growing amount of data in various fields also provide much convenience for this purpose. Therefore, this paper proposes an intelligent knowledge discovery method for critical spreading paths based on epidemic big data. For the major roadmap, a directional acyclic graph of epidemic spread was constructed with each province and city in mainland China as nodes, all features of the same node are dimension-reduced, and a composite score is evaluated for each city per day by processing the features after principal component analysis. Then, the typical machine learning model named XGBoost carries out processing of feature importance ranking to discriminate latent candidate spreading paths. Finally, the shortest path algorithm is used as the basis to find the critical path of epidemic spreading between two nodes. Besides, some simulative experiments are implemented with use of realistic social network data. [ABSTRACT FROM AUTHOR]

The COVID-19 epidemic has required countries to implement different containment strategies to limit its spread, like strict or weakened national lockdown rules and the application of age-stratified vaccine prioritization strategies. These interventions have in turn modified the age-dependent patterns of social contacts. In our recent paper, starting from the available age-structured real data at the national level, we identified, for the Italian case, specific virulence parameters for a two-age-structured COVID-19 epidemic compartmental model (under 60, and 60 years and over) in six different diseases transmission scenarios under concurrently adopted feedback interventions. An interpretation of how each external scenario modifies the age-dependent patterns of social contacts and the spread of COVID-19 disease has been accordingly provided. In this paper, which can be viewed as a sequel to the previous one, we mainly apply the same general methodology therein (involving the same dynamic model) to new data covering the three subsequent additional scenarios: (i) a mitigated coordinated intermittent regional action in conjunction with the II vaccination phase; (ii) a super-attenuated coordinated intermittent regional action in conjunction with the II vaccination phase; and (iii) a last step towards normality in conjunction with the start of the III vaccination phase. As a new contribution, we show how meaningful updated information can be drawn out, once the identification of virulence parameters, characterizing the two age groups within the latest three different phases, is successfully carried out. Nevertheless, differently from our previous paper, the global optimization procedure is carried out here with the number of susceptible individuals in each scenario being left free to change, to account for reinfection and immunity due to vaccination. Not only do the slightly different estimates we obtain for the previous scenarios not impact any of the previous considerations (and thus illustrate the robustness of the procedure), but also, and mainly, the new results provide a meaningful picture of the evolution of social behaviors, along with the goodness of strategic interventions. [ABSTRACT FROM AUTHOR]

The development of antimicrobial polymeric materials has evolved into one of the more promising methods for preventing the growth of microbes and mitigating the spread of infectious diseases in several applications including the health and food packaging sectors. The outbreak of global pandemics, and particularly the recent COVID-19 pandemic, further strengthen the importance of developing such solutions. This review paper presents a fundamental understanding of how antimicrobial polymers are developed, describes the possible surface modification approaches to render polymers with antimicrobial properties, highlights the potential mechanism of action against a range of microorganisms (bacterial, viral, and fungal), and details some of the international standard protocols and procedures to evaluate the antimicrobial properties of modified materials (such as plastics and textiles). In addition, this review paper discusses the toxicity of antimicrobial additives when used in healthcare and food packaging applications. [ABSTRACT FROM AUTHOR]

In this paper, with the method of epidemic dynamics, we assess the spread and prevalence of COVID-19 after the policy adjustment of prevention and control measure in December 2022 in Taiyuan City in China, and estimate the excess population deaths caused by COVID-19. Based on the transmission mechanism of COVID-19 among individuals, a dynamic model with heterogeneous contacts is established to describe the change of control measures and the population's social behavior in Taiyuan city. The model is verified and simulated by basing on reported case data from November 8th to December 5th, 2022 in Taiyuan city and the statistical data of the questionnaire survey from December 1st to 23rd, 2022 in Neijiang city. Combining with reported numbers of permanent residents and deaths from 2017 to 2021 in Taiyuan city, we apply the dynamic model to estimate theoretical population of 2022 under the assumption that there is no effect of COVID-19. In addition, we carry out sensitivity analysis to determine the propagation character of the Omicron strain and the effect of the control measures. As a result of the study, it is concluded that after adjusting the epidemic policy on December 6th, 2022, three peaks of infection in Taiyuan are estimated to be from December 22nd to 31st, 2022, from May 10th to June 1st, 2023, and from September 5th to October 13th, 2023, and the corresponding daily peaks of new cases can reach 400 000, 44 000 and 22 000, respectively. By the end of 2022, excess deaths can range from 887 to 4887, and excess mortality rate can range from 3.06% to 14.82%. The threshold of the infectivity of the COVID-19 variant is estimated 0.0353, that is if the strain infectivity is above it, the epidemic cannot be control with the previous normalization measures. [ABSTRACT FROM AUTHOR]

Asymmetry plays a significant role in the transmission dynamics in novel discrete fractional calculus. Few studies have mathematically modeled such asymmetry properties, and none have developed discrete models that incorporate different symmetry developmental stages. This paper introduces a Taylor monomial falling function and presents some properties of this function in a delta fractional model with Green's function kernel. In the deterministic case, Green's function will be non-negative, and this shows that the function has an upper bound for its maximum point. More precisely, in this paper, based on the properties of the Taylor monomial falling function, we investigate Lyapunov-type inequalities for a delta fractional boundary value problem of Riemann–Liouville type. [ABSTRACT FROM AUTHOR]

The automation of hand hygiene monitoring is critical in healthcare for ensuring clean hands and preventing infectious disease spread. While advancements have been made, existing methods have limitations in accurately detecting and classifying handwashing actions. This paper addresses these limitations and introduces the Residual-Based Multilevel Fused Network (ResMFuse-Net) as a novel approach to automate the quality assurance of hand hygiene procedures. Our model integrates advanced techniques, including feature fusion, model compression, a feature fusion block (FFB), and a modified separable residual block (SE-ResB). The proposed model fused two networks into one trainable feature extraction pipeline, and applies model compression to retain the core blocks that are crucial for propagating strong and robust features while conserving a significant fraction of the computing resources. Additionally, we introduce a FFB that includes ConvLSTM and alpha dropout to learn spatial dependencies, establish correlations between frames in a video, and mitigate overfitting. This paper introduces a SE-ResB, which is a customized residual component composed of separable convolutions and LeakyReLU activation. The SE-ResB is incorporated to handle the fused features and generate a more diverse set of features, leading to considerable performance enhancements. This study also includes an ablation analysis that highlights the importance of each component. The proposed ResMFuse-Net is evaluated on two datasets: a newly created handwashing dataset (451 videos) and a publicly available dataset (656 videos). Achieving a recognition accuracy of 97.61% on the handwashing dataset and 98.69% on the other dataset, the ResMFuse-Net outperforms previous methods with fewer parameters and FLOPs, demonstrating its efficiency and cost-effectiveness. [ABSTRACT FROM AUTHOR]

This paper presents the design and development of a new type of planetary traction drive bearing-type reducer. In this design, the transmission outer ring is replaced with an elastic ring. The design constructs a circular arc at the axial end of the rolling body's contour line. This ensures that the contact point of this arc with the reducer's outer ring and the inner ring's axial end face is maintained on the radial traction contact line. As a result, it can replace the thrust bearing and provide an axial support function. It has the advantages of simple structure, easy processing, smooth transmission, and low noise. This paper first introduces the design and development process of this bearing-type reducer and presents systematic research on its transmission principle and dynamics. Subsequently, in response to the edge effect phenomenon of the outer ring contact line, the contour line of the outer ring is refined by adopting the shaping method used for bearing rollers, establishing a full circular arc profile shaping method, which significantly improves its edge effect. Finally, in our investigations, combined with experimental tests, a prototype of the bearing-type reducer was fabricated, and the speed ratio, torque, and transmission efficiency of the reducer were studied. The results demonstrate that the bearing-type reducer can achieve high transmission accuracy and efficiency. The transmission performance varies significantly under different lubrication conditions, with the peak efficiency reaching as high as 99.97% when using Santotrac 50 traction oil. The results verify the feasibility of the proposed design method and have the potential to be applied in wheel hub motors and robot joints. [ABSTRACT FROM AUTHOR]

This paper studies a delayed rumor propagation model with logistic growth and saturation incidence. The next generation matrix method, some inequality techniques, the Lyapunov-LaSalle invariance principle, and the Lyapunov method are used in this paper. Our results indicate that if the basic regeneration number (which is analogous to the basic reproduction number in disease transmission models) is less than 1, the rumor-free equilibrium point (which is analogous to the disease-free equilibrium point in disease transmission models) is globally stable. If the basic regeneration number is greater than 1, then the rumor is permanent, and some sufficient conditions are obtained for local and global asymptotic stability of the rumor prevailing equilibrium point (which is analogous to the endemic equilibrium point in disease transmission models). Finally, three examples with numerical simulations are presented to illustrate the obtained theoretical results. [ABSTRACT FROM AUTHOR]

This paper presents the study of the effectiveness of horizontal transfer of local isolates of the pathogenic fungus Beauveria bassiana (Balsamo) on adults of olive fruit fly Bactrocera oleae (Rossi) at a concentration of 106 spores/ml in laboratory conditions (this work was carried out in specialized scientific laboratories). In addition, it is not possible to reach the desired results in such experiments effectively when the data and observations of the study are not clear and accurate. For this reason, in this paper, experimental data will be presented with inaccurate or uncertain observations using neutrosophic statistics. The purpose is to know the success of males contaminated with pathogenic isolates in the transmission of infection to females. In laboratory conditions through a neutrosophic reading of the study data. This proposed presentation provides greater accuracy, flexibility, and applicability than the classic experimental design in the case of uncertainty. [ABSTRACT FROM AUTHOR]