bluuebunny/crossref_metadata_2025 huggingface dataset:
Trajectories of physical functioning and its predictors in older adults: A 16-year longitudinal study in China
Authors: Zhao Yinan , Duan Yunzhu , Feng Hui , Nan Jiahui , Li Xiaoyang , Zhang Hongyu , Xiao Lily Dongxia
Published: August 2022

Objective

Maintaining and delaying a decline in physical function in older adults is critical for healthy aging. This study aimed to explore trajectories, critical points of the trajectory changes, and predictors among older people in the Chinese community.

Design

This study was one with a longitudinal design performed in China.

Setting and participants

The target population was community-dwelling older adults aged over 65 years. A total of 2,503 older adults from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) were included in this study.

Methods

Physical functioning was measured by instrumental activities of daily living (IADL). Population-based trajectory models were used to identify potential heterogeneity in longitudinal changes over 16 years and to investigate associations between baseline predictors and different trajectories for different cohort members using LASSO regression and logistic regression.

Results

Four trajectories of physical function were identified: slow decline (33.0%), poor function and moderate decline (8.1%), rapid decline (23.5%), and stable function (35.4%). Older age, male sex, worse self-reported health status, worse vision status, more chronic diseases, worse cognitive function, and a decreased frequency of leisure activity influenced changes in the trajectory of physical function. Having fewer teeth, stronger depressive symptoms, a lack of exercise, and reduced hearing may increase the rate of decline.

Conclusion and implications

Four trajectories of physical function were identified in the Chinese elderly population. Early prevention or intervention of the determinants of these trajectories can maintain or delay the rate of decline in physical function and improve healthy aging.
Network meta-analysis of deaths from various underlying diseases after COVID-19 infection
Authors: Yang Jinqiang , Li Ming , Zhang Renmin
Published: August 2022

Network meta-analysis of deaths from various underlying diseases after COVID-19 infection. This study included more than 10 research centers with the same level of care. In total, 1,676 subjects were included in our study, including 1,122 men and 554 women, patients diagnosed with COVID-19, and combined with underlying diseases; provided data on the number of deaths from related diseases, such as hypertension, diabetes, heart disease, cerebrovascular disease, malignant tumor, chronic kidney disease, chronic liver disease, and respiratory disease. The comparison RR between hypertension and different diseases shows that it is (RR = 2.35, 95% CI: 1.47, 3.98) compared with diabetes, compared with coronary heart disease (RR = 2.57, 95% CI: 1.5, 4.4), compared with cerebrovascular disease (RR = 3.68, 95% CI: 1.87, 7.29), compared with malignant tumor (RR = 6.35, 95% CI: 3.45, 11.97), and compared with chronic kidney disease (RR = 5.53 95% CI: 3.04, 10.34), compared with chronic liver disease (RR = 15.51, 95% CI: 5.26, 50.98), compared with respiratory diseases (RR = 4.35, 95% CI: 2.37, 7.65), RR values are >1, which is statistically significant. The surface under the cumulative ranking curve (SUCRA) showed that the ranking of disease mortality from high to low was hypertension> diabetes> heart disease> cerebrovascular disease> respiratory disease> chronic kidney disease> malignant tumor> chronic liver disease. The study that hypertension, diabetes, and heart disease are the top three risk factors for patients infected with COVID-19, and management of these patients should be strengthened to improve the prognosis of patients. Ethical approval and patient consent are not required as this study is a meta-analysis based on published studies. The results of this network meta-analysis will be submitted to a peer-reviewed journal for the publication.
Can information infrastructure development improve the health care environment? Evidence from China
Authors: Tu Chenglin , Zang Chuanxiang , Tan Yuanfang , Zhou Yu , Yu Chenyang
Published: August 2022

Existing studies ignore the importance of information infrastructure development in improving regional health care environment. This paper adopts a spatial difference-in-difference (DID) model to assess the impact of information infrastructure development on urban health care environment based on a quasi-natural experiment of the “Broadband China” city pilots (BCCP). A balanced panel of 259 cities from 2010 to 2019 is selected for empirical analysis in this paper. Our findings show that the implementation of BCCP resulted in a 4.1 and 2.9% improvement in local medical workforce and medical infrastructure. In addition, there is significant spatial spillover effects of the implementation of BCCP, with 7.2 and 12.5% improvement in medical workforce and medical infrastructure in the surrounding areas. Our findings also suggest that information infrastructure development enhances the health care environment by driving industrial upgrading and education levels. Further analysis shows that BCCP has the strongest improvement on medical workforce in the eastern region and non-ordinary prefecture-level cities. For medical infrastructure, BCCP has stronger improvement in central region, western region, and non-ordinary prefecture-level cities. Finally, the paper conducts a series of robustness tests to ensure the reliability of the analysis results, including parallel trend tests, placebo tests, and re-estimation with different methods. Policies to improve the health care environment through information infrastructure development are proposed.
Distributed cognition for collaboration between human drivers and self-driving cars
Authors: Plebe Alice , Rosati Papini Gastone Pietro , Cherubini Antonello , Da Lio Mauro
Published: August 2022

This paper focuses on the collaboration between human drivers and intelligent vehicles. We propose a collaboration mechanism grounded on the concept of distributed cognition. With distributed cognition, intelligence does not lie just in the single entity but also in the interaction with the other cognitive components in a system. We apply this idea to vehicle intelligence, proposing a system distributed into two cognitive entities—the human and the autonomous agent—that together contribute to drive the vehicle. This account of vehicle intelligence differs from the mainstream research effort on highly autonomous cars. The proposed mechanism follows one of the paradigm derived from distributed cognition, the rider-horse metaphor: just like the rider communicates their intention to the horse through the reins, the human influences the agent using the pedals and the steering wheel. We use a driving simulator to demonstrate the collaboration in action, showing how the human can communicate and interact with the agent in various ways with safe outcomes.
Menstrual health and period poverty in Lebanon during economic crisis: A qualitative analysis of the challenges and recommendations
Authors: Elhage Hassan Malika , Doumat George , Daher Darine , Al Tannir Abdul Hafiz , Hassan Bashar , Chidiac Charbel , Hariri Hussein , Hatab Taha , Abou Daher Alaa , Ezzedin Omar , Fouad Fouad M.
Published: August 2022

Objective

Recently, severe period poverty has had a dramatic spread throughout Lebanon as a result of several crises: the COVID-19 pandemic, the Beirut explosion, and the economic collapse. Period poverty is the lack of access to menstrual hygiene materials, comfortable environments, and adequate education about menstrual health. Due to the great implications of period poverty on Lebanese women's health, our study aims to explore stakeholder's perspective on the Lebanese public health policy regarding menstrual health, the evolving challenges it faces in the context of the current economic collapse, and to suggest recommendations for solutions.

Methods

Our study is qualitative in nature, where data collection was done via online semi-structured interviews with stakeholders from the public and private sectors of the Lebanese healthcare system in addition to non-governmental organizations (NGOs) and physicians. Data were then analyzed based on themes and subthemes that emerged from the interviews.

Results

Nine stakeholders were interviewed: five from NGOs, two obstetrics and gynecology physicians, and two public sector representatives. The challenges to menstrual health were subcategorized into previously existing and new ones. The consequences of poor menstrual health were tackled on the mental, physical, and social levels. Stakeholders suggested both short-term and long-term recommendations. Short-term recommendations included decreasing the monetary burden by subsidizing menstrual products or via a coupon system. Long-term recommendations included proper education on multiple levels, cooperation between key players in the private and public sectors, and encouragement of local production to ensure future sustainability.

Conclusion

Menstrual health is a neglected public health issue in Lebanon, causing detrimental effects on girls and women residing in the country. Proper planning and collaboration between the private and public sectors are required to address this human rights issue.
Grain yield and food security evaluation in the yellow river basin under climate change and water resources constraints
Authors: Niu Chen , Qi Yafei , Guo Aijun , Chang Jianxia
Published: August 2022

With climate change, the amount of global water resources is decreasing and crop growth patterns are changing. Global food security will face severe challenges in future. Hence, it is of great significance to study the change in grain production under climate change and the water resources constraint to ensure national and regional food security. In this study, a complex system coupled with the hydrological model, crop model, and optimal regulation model of water resources has been constructed to explore the changes in future grain yield in the Yellow River Basin (YRB) under climate change and the water resources constraint, and further evaluate the future food security of the basin. The models show good adaptability. The results show that the precipitation and temperature in the YRB will be higher than the historical level and show an upward trend in future. On the contrary, runoff and irrigation water demand in the basin are lower than historical levels. Although the grain yield would decrease in future, the food security of YRB would be well-guaranteed. However, the level of food security in different provinces would be quite different. And some provinces will face serious food security problems without grain trade. This study will help relevant institutions in the YRB to deal with possible food security problems in future, and can also provide a reference for other countries and institutions in the world.
Development of anti-Crimean-Congo hemorrhagic fever virus Gc and NP-specific ELISA for detection of antibodies in domestic animal sera
Authors: Belij-Rammerstorfer Sandra , Limon Georgina , Maze Emmanuel A. , Hannant Kayleigh , Hughes Ellen , Tchakarova Simona R. , Alexandrov Tsviatko , Mmbaga Blandina T. , Willett Brian , Booth George , Lyons Nicholas A. , Baker Natalie , Thomas Kelly M. , Wright Daniel , Saunders Jack , Browning Clare , Wilsden Ginette , Carroll Miles , Hewson Roger , Charleston Bryan , Lambe Teresa , Ludi Anna B.
Published: August 2022

Crimean-Congo hemorrhagic fever (CCHF) is a priority emerging disease. CCHF, caused by the CCHF virus (CCHFV), can lead to hemorrhagic fever in humans with severe cases often having fatal outcomes. CCHFV is maintained within a tick-vertebrate-tick cycle, which includes domestic animals. Domestic animals infected with CCHFV do not show clinical signs of the disease and the presence of antibodies in the serum can provide evidence of their exposure to the virus. Current serological tests are specific to either one CCHFV antigen or the whole virus antigen. Here, we present the development of two in-house ELISAs for the detection of serum IgG that is specific for two different CCHFV antigens: glycoprotein Gc (CCHFV Gc) and nucleoprotein (CCHFV NP). We demonstrate that these two assays were able to detect anti-CCHFV Gc-specific and anti-CCHFV NP-specific IgG in sheep from endemic CCHFV areas with high specificity, providing new insight into the heterogeneity of the immune response induced by natural infection with CCHFV in domestic animals.
Advances in vaccine development and the immune response against toxoplasmosis in sheep and goats
Authors: Hasan Tanjila , Nishikawa Yoshifumi
Published: August 2022

Toxoplasmosis is a zoonotic, parasitic infection caused by the intracellular, apicomplexan parasiteToxoplasma gondii, which infects all homeothermic animals including humans. The parasite has a major economic impact on the livestock industry. This is especially true for small ruminants (sheep, goats) as it is one of the most likely reasons for reproductive disorders in these animals. Primary infection in sheep and goats can result in a fetus that is mummified or macerated, fetal embryonic death, abortion, stillbirth, or the postnatal death of neonates, all of which threaten sheep and goat rearing globally. Humans can also become infected by ingesting bradyzoite-containing chevon or mutton, or the contaminated milk of sheep or goats, highlighting the zoonotic significance of this parasite. This article reviews the advances in vaccine development over recent decades and our current understanding of the immune response to toxoplasmosis in small ruminants (sheep, and goats).
The Parental and Children Report of the Prevalence of Depressive Symptoms in Children and Adolescents Amid the COVID-19 Pandemic: A Cross-Sectional Study From Oman
Authors: Zadjali Fahad , Al-Futaisi Amna , Al-Hosni Amira , Al-Huseini Salim , Crommelin Maarten , Mirza Hassan
Published: August 2022

Objective: Studies from the past decades have shown that mood disorders are common during childhood and adolescence. This study aimed to estimate the point prevalence of depression in Omani children and adolescents during social distancing and lockdown and identify the risk factors for developing depressive symptoms during the COVID-19 pandemic.

Methods: This is an analytical cross-sectional study conducted in May 2020, in which all young Omani people attending a mainstream school aged 8–18 years old were eligible to participate. Parents were asked to complete the online survey, which consisted of the parent version of the Mood and Feelings Questionnaire (MFQ-Parent). In addition, the option of a self-reported version (MFQ-Self) was provided in cases where children preferred to fill out the survey themselves. Logistic regression was used to identify the contributing socio-demographic variables associated with depressive symptoms.

Results: A total of 445 participants completed the MFQ, out of which 72.1% were parents, and 27.9% were children, adolescents and young people. 13.9% of children and adolescents exhibited depressive symptoms during the COVID-19 pandemic in Oman. The presence of depressive symptoms was associated with increased food intake (OR 1.81, 95% CI 1.00–3.29, p-value <0.05), longer use of smartphones (OR 2.72, 95% CI 1.56–4.73, p-value <0.001), whereas additional entertainment activities during lockdown were protective against depression (OR 0.35 95% CI 0.19–0.64, p-value <0.001).

Conclusion: This study from Oman concurs with recent reports of depression being common during the COVID-19 pandemic. Concerted efforts are needed to mitigate this trend and identify high-risk groups during the lockdown period.
Physical and Chemical Characteristics of Native Maize from the Jalisco Highlands and Their Influence on the Nixtamalization Process
Authors: Ramírez-Vega Humberto , Vázquez-Carrillo Gricelda , Muñóz-Rosales Gabriela Minerva , Martínez-Loperena Raquel , Heredia-Nava Darwin , Martínez-Sifuentes José Ángel , Anaya-Esparza Luis Miguel , Gómez-Rodríguez Víctor Manuel
Published: August 2022

From a cultural point of view, Maize is the most important crop in Mexico, and is also an essential food in the Mexican diet. This study aimed to evaluate the physical and chemical characteristics of maize grain and their influence on the quality of dough and tortillas produced with three native maize cultivars from western Mexico. Physical, structural, and chemical characteristics of the grain were evaluated, including hectolitric weight, 100-grain weight, flotation index, grain structure, grain color, pedicel, pericarp, germ, and floury endosperm, vitreous endosperm, ethereal extract, and protein. Nixtamal and tortilla quality include nixtamal moisture, dough moisture, freshly made tortilla moisture, total soluble solids, pericarp remnant, dough yield, and hot tortilla yield. In general, statistical differences (p ≤ 0.05) were found in almost all variables analyzed. The principal component analysis (PCA) showed that two principal components (PCs), described approximately 79% of the variation, and a positive correlation between the characteristics of freshly made tortilla moisture (FMTM), dough yield (DY), and nixtamal moisture (NM), as well as dough moisture (DM) and hot tortilla yield (HTY). Future studies on these and other native maize cultivars of western Mexico must be conducted to assess the physicochemical and phytochemical characteristics of maize grains that may be useful for food and pharmaceutical applications, contributing to the conservation, propagation, and use of natural and ancient resources.
Numerical Simulation and Wind Tunnel Test on the Wind-Induced Response of Three Typical Types of Greenhouse Main Structures
Authors: Xie Simeng , Zheng Jianhong , Xiao Bengui , Hu Huiyue , Cao Xinyi , Wang Xuepeng , Zhang Luling
Published: August 2022

Investigating the wind-induced vibration response of the greenhouse structure, and the wind pressure distribution on its surface takes on a critical significance when the main structure is under large wind loads. A computational fluid dynamics-based study was conducted, and wind tunnel tests were performed to study the wind pressure distribution on the surface of the greenhouse structure. First, three types of greenhouses, including Venlo, Round-arch, and Saw-tooth type greenhouses, were selected as the design models for the study. In addition, the double-span, four-room structure model was built to explore the wind pressure distribution and the extreme wind pressure coefficient on the greenhouse surface for 13 (0°–180°, every 15°) directions of the wind direction to obtain the wind load characteristics in the greenhouse surface under different conditions. The results of the wind tunnel tests were consistent with those of the simulations, with the maximum wind pressure in the X-direction occurring at 30°-wind and the maximum wind pressure in the Y-direction at 75°-wind. The maximum negative wind pressure acting locally on the roof of the greenhouse was twice the maximum positive pressure acting on the windward side of the greenhouse. Accordingly, it is necessary to strengthen the structure in regions sensitive to wind direction with significant response to wind.
Establishment and Validation of a Structural Dynamics Model with Power Take-Off Driveline for Agricultural Tractors
Authors: Shao Xuedong , Zheng Bowen , Luo Zhenhao , Song Zhenghe
Published: August 2022

As off-road vehicles, in addition to field transportation, another vital function of agricultural tractors is to provide power for field machinery. Therefore, the dynamic performance of the power take-off (PTO) driveline directly affects the field reliability of tractors. Firstly, a torsional vibration coupled spatial dynamics model of the power take-off driveline is proposed according to the classical machine driveline dynamics and gear dynamics theory. In the dynamics model, the interactions among the vertical, lateral, and rotational motions of the driveline parts are fully included. The coupling vibrations from internal excitations (such as tooth surface friction, gear time-varying mesh, and engine pulse) and external excitations (such as field machinery load) are also considered. Secondly, the simulation results of the model are obtained using the numerical solving algorithm ode15s. The actual experiment is carried out on the indoor Tractor PTO Test Bench. Then, the model is verified by comparing the test results with the simulation results. Finally, the dynamic characteristics of the whole driveline are revealed under different drive modes, especially strong interactions between the driveline and field machinery in low-speed and heavy-load mode. The gear mesh forces and the root mean square (RMS) values of the acceleration amplitude for the main parts generally decrease gradually with the increase in the PTO rotation speed and the decrease in PTO torque. Furthermore, the model can be applied to reliability assessment, for instance, vibration, damage, and fatigue of off-road vehicles considering gear transmissions, particularly in a field working environment.
Effect of Row Spacing on Quinoa (Chenopodium quinoa) Growth, Yield, and Grain Quality under a Mediterranean Climate
Authors: Asher Aviv , Dagan Reut , Galili Shmuel , Rubinovich Lior
Published: August 2022

Quinoa (Chenopodium quinoa Willd., Amaranthaceae) is an environmental stress-resilient crop of increasing global importance. Sowing density is a critical factor in the quinoa cultivation protocol. We evaluated the row-spacing effect on quinoa growth, yield, and grain quality under Mediterranean conditions. We hypothesized that lower row spacing would reduce quinoa stem diameter and increase yield but may reduce grain quality. Two quinoa accessions were sown in northern Israel with 16, 26, or 80 cm between rows during two consecutive years, in November and January each year. Plant density at harvest ranged from 22 to 260 plants m−2. Plant height and stem diameter ranged from 77 to 126 and 6.3 to 10.5 cm, respectively. Hay, grain, and straw yield ranged from 2259 to 17,979, 1604 to 4266, and 1212 to 3660 kg DM ha−1, respectively. Grain protein content (PC) ranged from 5.2 to 14.2 and thousand grain weight (TGW) from 2033 to 3446 mg. Plant density, hay, grain, and straw yield were negatively correlated to row spacing. Stem diameter was positively correlated to row spacing, while there were no correlations between this parameter and plant height, grain PC, or TGW. Results indicated that 16 cm between rows may be optimal, as this produced the greatest yields with no effect on grain quality. However, as it may result in plant lodging, 26 cm row spacing should also be considered. The effects of additional management-related parameters on quinoa production should be examined.
A Study of Application and Comparison of Thermal Drying and Freeze Drying of Fresh Edamame Seeds in the Analysis of Seed Composition
Authors: Jiang Guo-Liang , Townsend William , Sismour Edward , Xu Yixiang
Published: August 2022

Edamame is a vegetable soybean (Glycine max) with high nutritional and market value. It is mainly grown in Asia and has expanded to North America and Africa. Freeze and low- and high-heat drying methods were used to dry fresh edamame seeds of 20 soybean lines and cultivars for analysis of their composition using near-infrared reflectance (NIR) technology. The results indicated that significant differences existed between years of samplings for all seed composition traits investigated. Differences between drying methods were significant for all the traits with whole-seed samples, while they were not significant in protein, raffinose and linoleic acid for flour samples. Ground flour and whole-seed samples were similar or comparable in most cases for freeze and low-heat drying methods, but differences in seed composition between sample types were observed for high-heat drying. Among the traits investigated, protein content was the most consistent for all three drying methods, with an over 91% estimate of repeatability, showing high stability during drying. Oil content also showed a repeatability estimate of over 86% for all three drying methods. Low-heat drying generated results more comparable to freeze drying, while high-heat drying exhibited larger differences in most cases. Estimates of repeatability and correlation coefficients further confirmed that, low-heat drying, similar to freeze drying, was appropriate for drying fresh edamame seeds, but high-heat drying was not. Therefore, low-heat drying is a suitable method for drying fresh edamame and rapid analysis of seed composition, and it can be used as an alternative of freeze-drying method.
Increasing Agricultural Resilience through Combined Supply and Demand Management (Case Study: Karaj Reservoir Dam, Iran)
Authors: Yoosefdoost Icen , Basirifard Milad , Álvarez-García José , del Río-Rama María de la Cruz
Published: August 2022

Among the solutions to climate change’s harmful effects, AS (Adaptation Strategies) are more feasible. In this study, four AS, Changing Cultivation Dates (CCD), Deficit Irrigation (DI), Improving Irrigation Performance (IIP), and Optimizing the Crop Pattern (OCP), were investigated. The results showed that the WUE (Water Use Efficiency) was declined when the cultivation date was changed for all crops in the baseline and increased after the cultivation date was brought forward to 7, 14, 14, 28, 28 days for tomato, wheat, corn, barley and cucumber, respectively, in the future period. Deficit irrigation of 30% increased the WUE in all crops. A 48% increase in irrigation performance reduced demand by 10%. Following the OCP and diminishing the cultivation area by 30% increased farmers’ total profit and reduced the water consumption volume by 9% and 11%, respectively, in the baseline and future periods. To study the effect of these AS on crop yield and allocated volume, a combination of crop model programming and the MOEPO (Multi-Objective Emperor Penguin Optimizer) was employed to minimize Vulnerability and maximize Reliability Indexes (Performance Indexes). In the supply section, three scenarios were examined. The results showed that DI, IIP, CCD and OCP were classified from the most to the least option based on improving the Performance Indexes.
Protective Effects of Systiva® Seed Treatment Fungicide for the Control of Winter Wheat Foliar Diseases Caused at Early Stages Due to Climate Change
Authors: Vagelas Ioannis , Cavalaris Chris , Karapetsi Lefkothea , Koukidis Charalambos , Servis Dimitris , Madesis Panagiotis
Published: August 2022

Foliar fungal diseases are a serious threat to winter wheat production and climate change appears to favor pathogens associated with leaf blotch and tan spot symptoms in the Mediterranean area. The present work aimed to highlight these risks and propose appropriate disease management strategies by evaluating the seed treatment with the Systiva® (BASF) fungicide as a means to protect the crop against foliar fungal infections during the early growing stages. Towards that aim, plant tissue symptoms affected by the pathogens Pyrenophora tritici-repentis and Septoria spp. were systematically recorded in a study field in the region of Larissa, central Greece for three years (2016–2018), and the findings were associated with the monthly weather anomalies. Consequently, for the growing period of 2021–2022, a field experiment was established in the same disease prone field, comparing different doses of the seed treatment with Systiva® fungicide against leaf blotch and tan spot diseases. The evaluation was made by visual disease assessments, remote sensing with an unmanned aerial vehicle (UAV) and metagenomics analysis. Parallel measurements on straw residues were also made to characterize the plant residues perithecia (pseudothecia). Visual leaf disease assessments and UAV remote sensing data showed that Systiva® treatments at doses of 125 cc and 150 cc per 100 kg of wheat seed can reduce the percentage of infected wheat plants caused by foliar fungal pathogens at wheat growth stages GS23-25 and GS30-31. Moreover, the metagenomics analyses performed on the microbial communities revealed that Systiva® can decrease the degree of infection by P. tritici-repentis and Z. tritici but do not provide sufficient protection against P. nodorum. Foliar diseases were influenced by the soil surface area covered with straw residue with a high proportion of natural inoculum (pseudothecia/ascospores).
Cat Foster Program Outcomes: Behavior, Stress, and Cat–Human Interaction
Authors: Vitale Kristyn R. , Frank Delaney H. , Conroy Jocelyn , Udell Monique A. R.
Published: August 2022

Recent research has demonstrated that cats (Felis catus) have greater social potential and flexibility than was previously assumed. However, many traditional cat care practices have been influenced by the misconception that cats are socially aloof. This can result in less support or guidance for cat-focused programs that may promote improved success or welfare. For example, while dog fostering programs—even overnight programs—are considered highly beneficial, with research to back these claims, relatively little research has been dedicated to understanding the potential risks and benefits of cat fostering programs. Therefore, the aim of this study was to empirically evaluate the social, behavioral, and stress response outcomes associated with placing shelter cats in an overnight or short-term foster environment. While neither overnight nor 1-week fostering lead to a statistically significant improvement in human-directed social behavior or stress levels, foster cats also did not display increased fear or aggression in the foster home and did not have higher cortisol levels. Therefore, cat fostering—even short-term fostering—does not appear to be more stressful or problematic for this species than remaining in a shelter. This information could contribute to life-saving efforts by providing empirical evidence that cats can be safely moved into foster homes, even for short durations, when shelter space is limited. More research is needed to evaluate the potential effects of longer-term fostering in cats, as well as cat fostering practices that could lead to greater welfare benefits.
Expression of CSF1, AR, and SRD5A2 during Postnatal Development of the Boar Reproductive Tract
Authors: Katleba Kimberley , Legacki Erin , Berger Trish
Published: August 2022

The male reproductive system develops from a minimally functioning gonad and nonfunctioning accessory sex glands in the neonate; sex steroids, presumed to be primary influencers of these changes, have been characterized in multiple species. This study focused on the expression of the androgen receptor as the principal mediator of androgen-induced signaling; the 5α reductase enzyme that converts testosterone to the more active dihydrotestosterone; and colony stimulating factor 1, a mediator of macrophage influence on organ development in the pig. The time points chosen to evaluate normal developmental changes during the juvenile and prepubertal intervals included the inflection time points of 6.5 weeks of age at the nadir of circulating estradiol and testosterone concentrations in juveniles, and 11 weeks of age, when these concentrations begin to increase. The role of sex steroid signaling in the regulation of gene expression was evaluated by the blockade of androgen and estrogen receptors and reduction in endogenous estrogens. Expression of colony stimulating factor 1 in the testes gradually decreased during development; developmental profiles in the prostate and seminal vesicles were clearly different. Interference with sex steroid signaling had no effect on the expression of these three genes in testicular tissue and minimal and transient effects in prostate and seminal vesicles.
Correction: Chen et al. Computational Fluid Dynamics Analysis of Alternative Ventilation Schemes in Cage-Free Poultry Housing. Animals 2021, 11, 2352
Authors: Chen Long , Fabian-Wheeler Eileen E. , Cimbala John M. , Hofstetter Dan , Patterson Paul
Published: August 2022

There was an error in the original publication [...]
Antibiotic De-Escalation in Emergency General Surgery
Authors: Vallicelli Carlo , Minghetti Margherita , Sartelli Massimo , Coccolini Federico , Ansaloni Luca , Agnoletti Vanni , Bravi Francesca , Catena Fausto
Published: August 2022

Background. Antibiotic treatment in emergency general surgery (EGS) is a major challenge for surgeons, and a multidisciplinary approach is necessary in order to improve outcomes. Intra-abdominal infections are at high risk of increased morbidity and mortality, and prolonged hospitalization. An increase in multi-drug resistance bacterial infections and a tendency to an antibiotic overuse has been described in surgical settings. In this clinical scenario, antibiotic de-escalation (ADE) is emerging as a strategy to improve the management of antibiotic therapy. The objective of this article is to summarize the available evidence, current strategies and unsolved problems for the optimization of ADE in EGS. Methods. A literature search was performed on PubMed and Cochrane using “de-escalation”, “antibiotic therapy” and “antibiotic treatment” as research terms. Results. There is no universally accepted definition for ADE. Current evidence shows that ADE is a feasible strategy in the EGS setting, with the ability to optimize antibiotic use, to reduce hospitalization and health care costs, without compromising clinical outcome. Many studies focus on Intensive Care Unit patients, and a call for further studies is required in the EGS community. Current guidelines already recommend ADE when surgery for uncomplicated appendicitis and cholecystitis reaches a complete source control. Conclusions. ADE in an effective and feasible strategy in EGS patients, in order to optimize antibiotic management without compromising clinical outcomes. A collaborative effort between surgeons, intensivists and infectious disease specialists is mandatory. There is a strong need for further studies selectively focusing in the EGS ward setting.
Deregulation of Mitochondrial Calcium Handling Due to Presenilin Loss Disrupts Redox Homeostasis and Promotes Neuronal Dysfunction
Authors: Ryan Kerry C. , Laboy Jocelyn T. , Norman Kenneth R.
Published: August 2022

Mitochondrial dysfunction and oxidative stress are major contributors to the pathophysiology of neurodegenerative diseases, including Alzheimer’s disease (AD). However, the mechanisms driving mitochondrial dysfunction and oxidative stress are unclear. Familial AD (fAD) is an early onset form of AD caused primarily by mutations in the presenilin-encoding genes. Previously, using Caenorhabditis elegans as a model system to study presenilin function, we found that loss of C. elegans presenilin orthologue SEL-12 results in elevated mitochondrial and cytosolic calcium levels. Here, we provide evidence that elevated neuronal mitochondrial generated reactive oxygen species (ROS) and subsequent neurodegeneration in sel-12 mutants are a consequence of the increase of mitochondrial calcium levels and not cytosolic calcium levels. We also identify mTORC1 signaling as a critical factor in sustaining high ROS in sel-12 mutants in part through its repression of the ROS scavenging system SKN-1/Nrf. Our study reveals that SEL-12/presenilin loss disrupts neuronal ROS homeostasis by increasing mitochondrial ROS generation and elevating mTORC1 signaling, which exacerbates this imbalance by suppressing SKN-1/Nrf antioxidant activity.
Holistic Interpretation of Public Scenes Using Computer Vision and Temporal Graphs to Identify Social Distancing Violations
Authors: Jayatilaka Gihan , Hassan Jameel , Sritharan Suren , Senanayaka Janith Bandara , Weligampola Harshana , Godaliyadda Roshan , Ekanayake Parakrama , Herath Vijitha , Ekanayake Janaka , Dharmaratne Samath
Published: August 2022

Social distancing measures are proposed as the primary strategy to curb the spread of the COVID-19 pandemic. Therefore, identifying situations where these protocols are violated has implications for curtailing the spread of the disease and promoting a sustainable lifestyle. This paper proposes a novel computer vision-based system to analyze CCTV footage to provide a threat level assessment of COVID-19 spread. The system strives to holistically interpret the information in CCTV footage spanning multiple frames to recognize instances of various violations of social distancing protocols, across time and space, as well as identification of group behaviors. This functionality is achieved primarily by utilizing a temporal graph-based structure to represent the information of the CCTV footage and a strategy to holistically interpret the graph and quantify the threat level of the given scene. The individual components are evaluated in a range of scenarios, and the complete system is tested against human expert opinion. The results reflect the dependence of the threat level on people, their physical proximity, interactions, protective clothing, and group dynamics, with a system performance of 76% accuracy.
Analysis of a Stochastic SICR Epidemic Model Associated with the Lévy Jump
Authors: Srivastava Hari M. , Danane Jaouad
Published: August 2022

We propose and study a Susceptible-Infected-Confined-Recovered (SICR) epidemic model. For the proposed model, the driving forces include (for example) the Brownian motion processes and the jump Lévy noise. Usually, in the existing literature involving epidemiology models, the Lévy noise perturbations are ignored. However, in view of the presence of strong fluctuations in the SICR dynamics, it is worth including these perturbations in SICR epidemic models. Quite frequently, this results in several discontinuities in the processes under investigation. In our present study, we consider our SICR model after justifying its used form, namely, the component related to the Lévy noise. The existence and uniqueness of a global positive solution is established. Under some assumptions, we show the extinction and the persistence of the infection. In order to give some numerical simulations, we illustrate a new numerical method to validate our theoretical findings.
Spatiotemporal Joint Cleaning of Distribution Network Measurement Data Based on Correntropy Criterion with Variable Center Unscented Kalman Filter
Authors: Sun Zhenglong , Liu Chuanlin , Liu Baihan , Zhou Jun , Chen Chen , Song Qipeng
Published: August 2022

Measurement data cleaning is a key step of edge computing in a distribution network; it is beneficial to improve the state perception and regional autonomy level of a distribution network. According to the temporal and spatial correlation of measurement data in the distribution network, a joint cleaning method of measurement data in a distribution network is proposed based on the correntropy criterion with variable center unscented Kalman filter (CC-VC-UKF). Initially, the mean square error (MSE) in the original unscented Kalman filter (UKF) is replaced by the correntropy criterion with variable center (CC-VC) to improve the accuracy of filtering the measurement data in the distribution network with a non-Gaussian non-zero mean measurement deviation. Then, the measured data of different measuring devices located on the same section of the line are filtered based on the CC-VC-UKF algorithm according to their respective reference time series to improve the signal-to-noise ratio of the measured data. Then, the filtered measured data are filtered and cleaned based on the CC-VC-UKF algorithm according to the space–time joint filtering and cleaning technology. Finally, the method is used to test the measurement data of the distribution network obtained by a power supply company in a city in north China to solve the problem of measurement deviation caused by the existence of space distance. Results show that this method can obtain FTU measurement data with higher precision from network topology based on the filtered TTU measurement data through the media of filtered spatial measurement deviation.
Research on the Distribution Characteristics of Transformer Axial Vibration under Short-Circuit Conditions Considering Damping Parameters
Authors: Gao Shuguo , Sun Lu , Tian Yuan , Liu Hongliang
Published: August 2022

The existing research on the distribution characteristics of displacement and acceleration of the transformer axial vibration under short-circuit conditions is based on ignoring the damping parameters. An accurate description of the axial distribution characteristics of the windings, especially for the axial vibration of the winding under short-circuit conditions, has a poor effect. In this paper, the damping, stiffness, and mass parameters between windings are comprehensively considered, and the classical “mass-spring-damping” axial vibration mathematical model of transformer windings is established. After solving, the natural frequency, main mode shape, displacement, and acceleration of each wire cake of the multi-degree-of-freedom (multi-DOF) vibration system were quickly obtained. The relationship between the axial displacement and acceleration of the wire cake and the axial deformation of the transformer winding was discussed, and the transformer winding axis was summarized as well as characteristics of the vibration distribution.
Research on Image Matching of Improved SIFT Algorithm Based on Stability Factor and Feature Descriptor Simplification
Authors: Tang Liang , Ma Shuhua , Ma Xianchun , You Hairong
Published: August 2022

In view of the problems of long matching time and the high-dimension and high-matching rate errors of traditional scale-invariant feature transformation (SIFT) feature descriptors, this paper proposes an improved SIFT algorithm with an added stability factor for image feature matching. First of all, the stability factor was increased during construction of the scale space to eliminate matching points of unstable points, speed up image processing and reduce the dimension and the amount of calculation. Finally, the algorithm was experimentally verified and showed excellent results in experiments on two data sets. Compared to other algorithms, the results showed that the algorithm proposed in this paper improved SIFT algorithm efficiency, shortened image-processing time, and reduced algorithm error.
Volatile Freight Rates in Maritime Container Industry in Times of Crises
Authors: Rožić Tomislav , Naletina Dora , Zając Mateusz
Published: August 2022

In recent years, the stability of supply chains has been undermined due to many disruptions. Although it is normal for the disruptions in supply chains to occur periodically, they have great impact on the rise of the costs and they create strong imbalances in business. For years, most world trade has been performed by maritime transport due its cost-effectiveness. The COVID-19 pandemic has disrupted the global supply chain like nothing before, and the Russian invasion of Ukraine has only deepened the crisis that is affecting the global supply chain. The focus of this paper has been placed on volatile freight rates in the maritime container industry due to the COVID-19 pandemic and the Russian invasion of Ukraine and the consequences of these crises on the changes of the prices of consumer goods in the European Union.
Global Local Fusion Neural Network for Multimodal Sentiment Analysis
Authors: Hu Xiaoran , Yamamura Masayuki
Published: August 2022

With the popularity of social networking services, people are increasingly inclined to share their opinions and feelings on social networks, leading to the rapid increase in multimodal posts on various platforms. Therefore, multimodal sentiment analysis has become a crucial research field for exploring users’ emotions. The complex and complementary interactions between images and text greatly heighten the difficulty of sentiment analysis. Previous works conducted rough fusion operations and ignored the study for fine fusion features for the sentiment task, which did not obtain sufficient interactive information for sentiment analysis. This paper proposes a global local fusion neural network (GLFN), which comprehensively considers global and local fusion features, aggregating these features to analyze user sentiment. The model first extracts overall fusion features by attention modules as modality-based global features. Then, coarse-to-fine fusion learning is applied to build local fusion features effectively. Specifically, the cross-modal module is used for rough fusion, and fine-grained fusion is applied to capture the interaction information between objects and words. Finally, we integrate all features to achieve a more reliable prediction. Extensive experimental results, comparisons, and visualization of public datasets demonstrate the effectiveness of the proposed model for multimodal sentiment classification.
Generating Activity-Based Mobility Plans from Trip-Based Models and Mobility Surveys
Authors: Adenaw Lennart , Bachmeier Quirin
Published: August 2022

Manifold applications in transportation system engineering rely on accurate modeling of human mobility demand. This demand is often represented by so-called mobility plans. Distinguished by their levels of aggregation, activity-based and trip-based models are the most prominent types of demand models in the literature. Macroscopic trip-based models are widely available but do not model mobility at the person level. In contrast, activity-based approaches simulate mobility microscopically but are complex and thus rarely available. The goal of this article is to present, apply, and validate an approach to generate activity-based mobility plans which microscopically reproduce real-world mobility demand but circumvent the complexity of activity-based approaches. To achieve this, existing trip-based models and mobility surveys are employed. Application results for car mobility in the city of Munich show that the obtained mobility plans are realistic on both a microscopic and a macroscopic level with regard to time, space, and activities. The presented approach can thus be considered appropriate for generating activity-based mobility plans whenever the development of a full-scale activity-based demand model is infeasible.
Autonomous Vehicle with Emergency Braking Algorithm Based on Multi-Sensor Fusion and Super Twisting Speed Controller
Authors: Alsuwian Turki , Saeed Rana Basharat , Amin Arslan Ahmed
Published: August 2022

The automobile revolution and growth in the number of cars produced several issues, and vehicle accidents remain one of the most serious road-related issues. Human mistakes and a failure to brake quickly are the main causes of accidents. There may be serious outcomes to driving when distracted. To address the aforementioned issues, an autonomous emergency braking system (AEBS) was developed. To support such an AEBS, scalable, reliable, secure, fault-tolerant, and interoperable technologies are required. An advanced emergency braking system (EBS) with sensor fusion is proposed in this paper that can autonomously identify a probable forward collision and activate the vehicle braking system to brake the vehicle to avoid or mitigate a collision. Additionally, it provides a non-linear speed controller that facilitates the AEBS to apply the brakes in an emergency. Sensor fusion using lidar, radar, and vision sensors makes the AEBS more efficient and more reliable to detect vehicles or obstacles and decreases the chance of collision to a minimum level. A MATLAB/Simulink environment was used for simulation experiments and the results demonstrated the stable operation of the AEBS to avoid forward collisions in the event of an error in the measurement of any one sensor while any vehicle is detected. The presented work establishes that the EBS sensor fusion unit is a highly reliable solution for detecting the leading vehicle at the proper time and the AEBS controller can apply the brake in the situation of forwarding obstacle detection.