bluuebunny/crossref_metadata_2025 huggingface dataset:
Operational Characteristics of Women Street Food Vendors in Rural South Africa
Authors: Mahopo Tjale Cloupas , Nesamvuni Cebisa Noxolo , Nesamvuni Azwihangwisi Edward , de Bryun Melanie , van Niekerk Johan , Ambikapathi Ramya
Published: July 2022

Objective

To characterize the operations of the street food enterprise in the Vhembe district, focusing on business profile, sold foods, inputs, pricing, record-keeping practices and total running cost.

Methods

A descriptive cross-sectional face-to-face study of 511 vendors was done using a structured researcher-administered questionnaire comprising demographic and operational characteristics. Convenience sampling was used to choose the vending sites. Chi-square tests were conducted between four categorical variables (gender, age, marital status and citizenship) and operational characteristics. P-values were considered significant at p < 0.05. However, a Bonferroni adjustment decreased the significant value to p < 0.013.

Results

The findings highlight the dominance of single middle-aged (35–44) women (63.1%) with some high school education. About 14% migrated from Zimbabwe. Most vendors were owners (86.1%), with 70.0% in business for at least 1–10 years. Food sold included mielie pap (stiff porridge) served with beef or chicken, sometimes with vegetables. Plate prices were R40.00 (2.6 USD) for a full plate and R30.00 (2 USD) for half a plate. The typical street food consumers were government officials, middlemen, and schoolchildren. Social media such as Whatsapp were used to communicate between the street food vendors and customers. The results highlight poor managerial skills as only 15.5% kept records, most of which were sales records (59.5%). On average, street vendors made a monthly profit of R3200.00 (213 USD) while spending R1800.00 (120 USD) on daily running expenses. There were statistically significant variations in some operational characteristics of vendor variables and gender, age, marital status, and citizenship.

Conclusions

There is a need for capital and management for small businesses and food training for rural street food vendors. Therefore, government officials, policymakers, and NGOs could target street vendors to offer training and microfinance to improve their business skills while promoting food safety and consumption of nutritious foods.
The Effect of Mindfulness Yoga in Children With School Refusal: A Study Protocol for an Exploratory, Cluster-Randomized, Open, Standard Care-Controlled, Multicenter Clinical Trial
Authors: Amitani Marie , Amitani Haruka , Owaki Tetsuhiro , Monuki Takako , Adachi Satomi , Kawazu Suguru , Fukumoto Takamasa , Suzuki Hajime , Yoshimura Takuya , Mizuma Kimiko , Nishida Yuko , Watanabe Hiroko , Hirose Masayuki , Funakoshi Kouta , Ota Keiko , Murotani Kenta , Asakawa Akihiro
Published: July 2022

Background

School refusal occurs in about 1–2% of young people. Anxiety and depression are considered to be the most common emotional difficulties for children who do not attend school. However, at present, no definitive treatment has been established for school refusal, although interventions such as cognitive behavioral therapy have been used. This paper reports a protocol for a cluster-randomized controlled trial of a mindfulness yoga intervention for children with school refusal.

Methods

This study is a multicenter, exploratory, open cluster-randomized controlled trial. This study will recruit children aged 10–15 years with school refusal. After a 2-week baseline, participants for each cluster will be randomly assigned to one of two groups: with or without mindfulness yoga for 4 weeks. Mindfulness yoga will be created for schoolchildren for this protocol and distributed to the participants on DVD. The primary outcome is anxiety among children with school refusal using the Spence Children's Anxiety Scale-Children.

Discussion

For this study, we developed a mindfulness yoga program and protocol, and examine whether mindfulness yoga can improve anxiety in children with school refusal. Our mindfulness yoga program was developed based on the opinions of children of the same age, and is a program that children can continue to do every day without getting bored. In this way, we believe that we can contribute to the smooth implementation of support to reduce the anxiety of children with school refusal, and to the reduction of the number of children who refuse to go to school.
Maintaining the Partnership Between a Tribal Breast and Cervical Cancer Program and a University-Based Cancer Prevention Center During COVID-19 Lock-Down Restrictions-A Case Study
Authors: Teufel-Shone Nicolette I. , Goldtooth-Begay Carol , Begay Andria B. , Lazaro Ashley , Yellowhair Janet , Todecheenie Rolanda , Begay Delila , Singer Darlene , Briscoe Curtis
Published: July 2022

To inform women of the Navajo Nation of safety measures implemented to minimize COVID-19 virus exposure during screening and treatment procedures at Navajo Nation based health care facilities, the Navajo Nation Breast and Cervical Cancer Prevention Program (NNBCCPP) and the University-based Partnership for Native American Cancer Prevention Program (NACP) collaborated to develop a podcast to describe the continued availability of services. During the COVID-19 pandemic, women of all ages and ethnicities in the US needing breast and cervical cancer prevention screenings and treatment, have been hesitant to seek services given the advice to avoid crowded spaces and maintain physical distancing. Epidemiological trends indicate that proactive, intensive strategies are needed in Native American communities for early detection and treatment to support early cancer diagnosis and improve cancer survival. The NNBCCPP and Northern Arizona University (NAU) through the National Institute of Health's National Cancer Institute funded NACP had a nascent partnership prior to the onset of COVID-19 pandemic. This partnership relied on face-to-face interaction to allow for informal social interaction, facilitate clear communication and support continued trust building. To adhere to federal, state and tribal recommendations to minimize gatherings and to stay in-place to minimize the spread of the virus, the Navajo Nation and NAU restricted, and in most cases would not approve employee travel for partnership meetings. The plans to develop a podcast necessitated bringing additional members into the collaboration who were unfamiliar to the original partners and due to travel restrictions, required all interactions to be remote. This expanded group met virtually to develop a script, record and edit the podcast. More importantly, group members had to build and maintain trust over months of communicating via a teleconference video platform. This collaborative addressed challenges related to unstable Internet connections and periodic stay-at-home policies; thus, these emerging partners had to modify social and professional communication to respect and accommodate the stress and uncertain circumstances created by the pandemic on the citizens and employees of Navajo Nation. This case study describes strategies used to maintain and respect all members of the partnership.
Male and Female Differences in Homicide Mortality: Results of an Italian Longitudinal Study, 2012–2018
Authors: Ventura Martina , Di Napoli Anteo , Petrelli Alessio , Pappagallo Marilena , Mirisola Concetta , Frova Luisa
Published: July 2022

Introduction

Italy has one of the lowest homicide rates in Europe. However, while it is decreasing overall, the proportion of murdered women is increasing. This study aimed to analyze the demographic and socioeconomic characteristics associated with homicide mortality in Italy, focusing specifically on male and female differences.

Methods

Using a longitudinal design, the Italian 2011 General Census population was followed up to 2018. Deaths from homicide were retrieved by a record linkage with the Causes of Death Register. Age-standardized mortality rates, stratified by sex, citizenship, education, and geographic area of residence were calculated. The association between sociodemographic characteristics and homicide mortality was evaluated using quasi-Poisson regression models.

Results

Between 2012 and 2018, 1,940 homicides were recorded in Italy: 53% were females over age 55, 10% were immigrant females, 34% were males aged 40–54 years, 76% had a medium-low education level, and 57% lived in the South and Islands. Foreign citizenship increased a female's risk of dying from homicide (adjusted rate ratio (RRadj): 1.85; 95% CI: 1.54–2.23), while no differences between Italian and immigrant males were found. An inverse association between education and mortality was observed for both sexes, stronger for males (RRadj: 3.68; 95% CI: 3.10–4.36, low vs. high) than for females (RRadj: 1.38; 95%CI: 1.17–1.62, low vs. high). Moreover, a male residing in the South or the Islands had almost 2.5 times the risk of dying from homicide than a resident in the North-West. Finally, old age (over 75) increased a female's risk of being murdered, whereas the highest risk for males was observed for those aged 25–54 years.

Conclusions

Male and female differences in homicide mortality profiles by age were expected, but the results by residence, citizenship, and education highlight that living in disadvantaged socioeconomic contexts increases the risk of dying from homicide, suggesting the need to implement specific prevention and intervention strategies.
Effects of Factors Related to Shift Work on Depression and Anxiety in Nurses
Authors: Li Yuxin , Wang Yongchao , Lv Xiaoyan , Li Rong , Guan Xiangyun , Li Li , Li Junli , Cao Yingjuan
Published: July 2022

Background

Although shift work is the foundation of the provision of 24-h continuous care in hospitals, it can negatively impact mental health in hospital workers such as nurses. Despite the connection between mental health and overall health, little is known about the effect of shift work-related factors on mental health in this population.

Objectives

We investigated the effect of scheduling practices, physical and psychological characteristics related to shift work, and personal habits during shift work on depression and anxiety among nurses.

Methods

In this multi-center cross-sectional study, 11,061 nurses from 20 hospitals in the Shandong Province of China completed an online survey between December 2020 and February 2022. Multivariate ordered logistic regression analysis was performed to examine shift-related factors associated with depression and anxiety in the study population.

Results

The completion rate of all nurses' questionnaires was 83.00% (n = 9,181). Among the 9,181 respondents, 66.20% (n = 6,078) were shift nurses. Depression and anxiety were found in 58.82 and 62.08% of shift nurses, respectively, and these rates were influenced by fatigue during shift work, psychological stress before/during/after night shifts, feeling of being refreshed after resting before/after night shifts, using sleep medication before/after night shifts, physical discomfort during night shifts, busyness during night shifts, food intake during shift work, working > 40 h/week during shift work, and sleep quality before/after night shifts.

Conclusions

Depression and anxiety in shift nurses may be addressed by reducing their workload, sources of stress during night shifts, and facilitating rest and relaxation.
The Association of Internet Use Intensity and Lifestyle Behaviors During the COVID-19 Pandemic: A Cross-Sectional Study in Chinese Adults
Authors: Wang Yangyang , Xu Jian , Xie Tian
Published: July 2022

The COVID-19 pandemic substantially increased the intensity of internet use in humans, which has made public opinion around health and public perceptions of it more vital, and this phenomenon has had a significant impact on human lifestyle behavior. This study used cross-sectional data during the COVID-19 pandemic to explore how internet use intensity influenced lifestyle behaviors among adults, and compared the differences between samples of different ages. The findings showed that the internet use intensity among adults increased the probability of physical activity, staying up late, and high-quality eating behaviors, and that they had a statistically significant positive association. Such associations were also found in independent younger, middle-aged, and older samples. However, the internet use intensity elevated the probability of body weight gain only in the independent samples of younger, middle-aged, and older adults. Besides, internet use intensity was able to increase the probability of smoking & drinking only among the younger sample. Notably, the effect of internet use intensity on lifestyle behaviors, including body weight gain, physical activity, staying up late, and a high-quality diet, was strongest among the elderly, followed by the middle-aged, and weakest among the younger. In the process of rural and urban governance regarding citizens' health, public health agencies should remind citizens to spend a reasonable amount of time on internet use to reduce the probability of unhealthy lifestyle behaviors and improve their physical health.
Depressive Symptoms and Cognitive Decline Among Chinese Rural Elderly Individuals: A Longitudinal Study With 2-Year Follow-Up
Authors: Zhou Shuai , Wang Qiong , Zhang Jingya , Wang Qing , Hou Fangfang , Han Xiao , Hu Shilian , Shen Guodong , Zhang Yan
Published: July 2022

Background

Depressive symptoms and mild cognitive impairment (MCI) are highly prevalent in rural China. The study aimed to investigate the longitudinal associations between changes in depressive symptoms and cognitive decline and MCI incidence among Chinese rural elderly individuals.

Methods

A 2-year follow-up study was conducted among 1,477 participants from the Anhui Healthy Longevity Survey (AHLS). Depressive symptoms were assessed by the 9-item Patient Health Questionnaire (PHQ-9), and cognitive status was evaluated by the Mini Mental State Examination (MMSE). Multivariable linear regression and logistic regression were employed.

Results

Every 1-unit PHQ-9 score increase was significantly associated with more cognitive decline (β = 0.157, 95% CI: 0.092, 0.221, p < 0.001) and a higher risk of MCI incidence (OR = 1.063, 95% CI: 1.025, 1.103, p = 0.001). The participants who experienced worsening of depression symptoms had a larger decline in the 2-year MMSE score (β = 0.650, 95% CI: 0.039, 1.261, p = 0.037) and elevated risks of incident MCI (OR = 1.573, 95% CI: 1.113, 2.223, p = 0.010).

Limitations

Screening tools rather than standard diagnostic procedures were used in the study. Moreover, the long-term associations still need further exploration since the follow-up time was short.

Conclusions

Increased depressive symptoms were associated with more cognitive decline and higher risks of incident MCI among Chinese rural residents.
Horizon: A Trajectory Optimization Framework for Robotic Systems
Authors: Ruscelli Francesco , Laurenzi Arturo , Tsagarakis Nikos G. , Mingo Hoffman Enrico
Published: July 2022

This paper presents Horizon, an open-source framework for trajectory optimization tailored to robotic systems that implements a set of tools to simplify the process of dynamic motion generation. Its user-friendly Python-based API allows designing the most complex robot motions using a simple and intuitive syntax. At the same time, the modular structure of Horizon allows for easy customization on many levels, providing several recipes to handle fixed and floating-base systems, contact switching, variable time nodes, multiple transcriptions, integrators and solvers to guarantee flexibility towards diverse tasks. The proposed framework relies on direct simultaneous methods to transcribe the optimal problem into a nonlinear programming problem that can be solved by state-of-the-art solvers. In particular, it provides several off-the-shelf solvers, as well as two custom-implemented solvers, i.e. GN-SQP and Iterative Linear-Quadratic Regulator. Solutions of optimized problems can be stored for warm-starting, and re-sampled at a different frequency while enforcing dynamic feasibility. The proposed framework is validated through a number of use-case scenarios involving several robotic platforms. Finally, an in-depth analysis of a specific case study is carried out, where a highly dynamic motion (i.e., a twisting jump using the quadruped robot Spot® from BostonDynamics1) is generated, in order to highlight the main features of the framework and demonstrate its capabilities.
Enhanced Integration of Health, Climate, and Air Quality Management Planning at the Urban Scale
Authors: Kleiman Gary , Anenberg Susan C. , Chafe Zoe A. , Appiah Desmond C. , Assefa Tibebu , Bizberg Andrea , Coombes Toby , Cuestas Doroti , Henze Daven K. , Kessler Alexander , Kheirbek Iyad , Kinney Patrick , Mahlatji Musa , Marshall Julian D. , Naidoo Seneca , Potwana Nwabisa , Rodriguez Adriana , Tessum Christopher W. , Thomas Culley
Published: July 2022

Cities emit the majority of greenhouse gas emissions globally and are increasingly committing to aggressive mitigation actions. Cities are also experiencing poor—and in some cases worsening—air quality, contributing to large disease burdens for adults and children. Integrated planning frameworks can help cities leverage and prioritize measures that achieve climate, air quality, and health benefits simultaneously. We developed and applied an integrated climate action planning process that includes air quality, utilizing Pathways-AQ, a new assessment tool, in six pilot cities: Accra, Ghana; Addis Ababa, Ethiopia; Buenos Aires, Argentina; the metropolitan area of Guadalajara, Mexico; Johannesburg, South Africa; and Lima, Peru. Implementing the “ambitious” greenhouse gas reduction scenarios in these cities' climate action plans would reduce in-city contributions to fine particulate matter (PM2.5) concentrations and would avoid 230–1,040 annual premature deaths per city, by 2050. This new integrated climate action planning process revealed the importance of (i) geographic scales of analysis, (ii) data integration across climate and air quality, (iii) local civic engagement, and (iv) nuanced health messaging. Rapidly scaling up and applying this integrated approach can broaden the group of municipal stakeholders involved in climate-related planning goals, potentially leading to greater ambition by integrating climate, air pollution, and health objectives.
Epigallocatechin Gallate and Isoquercetin Synergize With Remdesivir to Reduce SARS-CoV-2 Replication In Vitro
Authors: Rabezanahary Henintsoa , Badr Ashraf , Checkmahomed Liva , Pageau Kim , Desjardins Yves , Baz Mariana
Published: July 2022

The ongoing pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) urgently needs effective antivirals. After over 2 years since the beginning of the pandemic, only a few FDA approved therapeutic options are available to treat the population. Combination therapies have become a standard for the treatment of other infectious diseases such as HIV and hepatitis C due to their improved efficacy compared to monotherapy, reduced toxicity, the ability to prevent the development of resistant viral strains and their potential to treat co-infection. The interest in identifying molecules displaying bioactivity against SARS-CoV-2 has led to extensive search for promising molecules from the natural pharmacopoeia and polyphenols have been shown to display antiviral activity against a number of viruses including SARS-CoV-2. Here we evaluated the in vitro efficacy of two polyphenols, Epigallocatechin gallate (EGCG) and Isoquercetin, in combination with Remdesivir, the first-approved drug for the treatment of severe COVID-19. We confirmed the inhibitory effects of EGCG and isoquercetin against SARS-CoV-2 and demonstrated their strong antiviral synergistic effects with Remdesivir in vitro. These combinational therapies represent an interesting avenue for the treatment of COVID-19 and grant further studies.
Financial Loss and Depressive Symptoms in University Students During the First Wave of the COVID-19 Pandemic: Comparison Between 23 Countries
Authors: Tancredi Stefano , Burton-Jeangros Claudine , Ruegg René , Righi Elena , Kagstrom Anna , Quesnel Vallee Amelie , Chiolero Arnaud , Bracke Piet , Buffel Veerle , Van De Velde Sarah , Cullati Stéphane
Published: July 2022

Objectives: To assess the association between students’ financial loss and depressive symptoms during the first wave of the coronavirus disease 2019 (COVID-19) pandemic and whether this association varied by countries having different levels of lockdown measures.

Methods: This cross-sectional survey, conducted in spring 2020, included 91,871 students from 23 countries. Depressive symptoms were measured using the shortened Center for Epidemiological Studies Depression Scale and information on lockdowns retrieved from the COVID-19 government response tracker. The association between financial loss and depressive symptoms was investigated estimating prevalence ratios (PR) with multilevel Poisson models.

Results: Some 13% of students suffered financial loss during the lockdown and 52% had a relatively high depression score, with large between-countries differences. Minimally and maximally adjusted models showed a 35% (PR = 1.35, 95% Confidence Interval (CI) = 1.29–1.42) and 31% (PR = 1.31, 95% CI = 1.26–1.37) higher prevalence of depressive symptoms in students who lost economic resources compared to students with stable economic resources. No substantial differences in the association were found across countries.

Conclusion: Depressive symptoms were more frequent among students who suffered financial loss during the pandemic. Policy makers should consider this issue in the implementation of COVID-19 mitigating measures.
IoT Multi-Vector Cyberattack Detection Based on Machine Learning Algorithms: Traffic Features Analysis, Experiments, and Efficiency
Authors: Lysenko Sergii , Bobrovnikova Kira , Kharchenko Vyacheslav , Savenko Oleg
Published: July 2022

Cybersecurity is a common Internet of Things security challenge. The lack of security in IoT devices has led to a great number of devices being compromised, with threats from both inside and outside the IoT infrastructure. Attacks on the IoT infrastructure result in device hacking, data theft, financial loss, instability, or even physical damage to devices. This requires the development of new approaches to ensure high-security levels in IoT infrastructure. To solve this problem, we propose a new approach for IoT cyberattack detection based on machine learning algorithms. The core of the method involves network traffic analyses that IoT devices generate during communication. The proposed approach deals with the set of network traffic features that may indicate the presence of cyberattacks in the IoT infrastructure and compromised IoT devices. Based on the obtained features for each IoT device, the feature vectors are formed. To conclude the possible attack presence, machine learning algorithms were employed. We assessed the complexity and time of machine learning algorithm implementation considering multi-vector cyberattacks on IoT infrastructure. Experiments were conducted to approve the method’s efficiency. The results demonstrated that the network traffic feature-based approach allows the detection of multi-vector cyberattacks with high efficiency.
Path Planning for Multiple Unmanned Vehicles (MUVs) Formation Shape Generation Based on Dual RRT Optimization
Authors: Gong Tianhao , Yu Yang , Song Jianhui
Published: July 2022

In this paper, dual RRT optimization is proposed to solve the formation shape generation problem for a large number of MUVs. Since large numbers of MUVs are prone to collision during formation shape generation, this paper considers the use of path planning algorithms to solve the collision avoidance problem. Additionally, RRT as a commonly used path planning algorithm has non-optimal solutions and strong randomness. Therefore, this paper proposes a dual RRT optimization to improve the drawbacks of RRT, which is applicable to the formation shape generation of MUVs. First, an initial global path can be obtained quickly by taking advantage of RRT-connect. After that, RRT* is used to optimize the initial global path locally. After finding the section that needs to be optimized, RRT* performs a new path search on the section and replaces the original path. Due to its asymptotic optimality, the path obtained by RRT* is shorter and smoother than the initial path. Finally, the algorithm can further optimize the path results by introducing a path evaluation function to determine the results of multiple runs. The experimental results show that the dual RRT operation optimization can greatly reduce the running time while avoiding obstacles and obtaining better path results than the RRT* algorithm. Moreover, multiple runs still ensure stable path results. The formation shape generation of MUVs can be completed in the shortest time using dual RRT optimization.
Changes in Soil Quality through Conservation Agriculture in North-Eastern Italy
Authors: Pittarello Marco , Chiarini Francesca , Menta Cristina , Furlan Lorenzo , Carletti Paolo
Published: July 2022

Conservation Agriculture includes practices focused on the conservation and the restoration of main soil features, such as organic carbon content, structure, and biological diversity and activity. Our study was conducted in three farms in North-Eastern Italy in pairs of closely located fields to compare conservation agriculture (no tillage, cover cropping) with conventional agriculture. Differences in terms of soil enzymatic activity, such as FDA and β-glucosidase through spectrophotometric analyses, microbial biomass carbon and nitrogen contents, total organic carbon, and nitrogen contents with CNS Elemental Analyzer and soil arthropod community via the QBS-ar index were investigated. Enzymatic activities resulted to be readily and positively affected by conservation agriculture whereas total and microbial carbon, nitrogen contents, and microarthropod community seemed to be more dependent on the time factor. The responses to conservation agriculture differed between the three farms, pointing out that differences in soil features may drive the effectiveness of conservation management. N stock, maybe dependent on previous soil management, might be the key characteristic able to influence soil evolution in the studied conditions. The present results could be helpful to predict soil reaction to sustainable agriculture in short periods.
Research on Navigation Path Extraction and Obstacle Avoidance Strategy for Pusher Robot in Dairy Farm
Authors: Tian Fuyang , Wang Xinwei , Yu Sufang , Wang Ruixue , Song Zhanhua , Yan Yinfa , Li Fade , Wang Zhonghua , Yu Zhenwei
Published: July 2022

Existing push robots mainly use magnetic induction technology. These devices are susceptible to external electromagnetic interference and have a low degree of intelligence. To make up for the insufficiency of the existing material pushing robots, and at the same time solve the problems of labor-intensive, labor-intensive, and inability to push material in time at night, etc., in this study, an autonomous navigation pusher robot based on 3D lidar is designed, and an obstacle avoidance strategy based on the improved artificial potential field method is proposed. Firstly, the 3D point cloud data of the barn is collected by the self-designed pushing robot, the point cloud data of the area of interest is extracted using a direct-pass filtering algorithm, and the 3D point cloud of the barn is segmented using a height threshold. Secondly, the Least-Squares Method (LSM) and Random Sample Consensus (RANSAC) were used to extract fence lines, and then the boundary contour features were extracted by projection onto the ground. Finally, a target influence factor is added to the repulsive potential field function to determine the principle of optimal selection of the parameters of the improved artificial potential field method and the repulsive direction, and to clarify the optimal obstacle avoidance strategy for the pusher robot. It can verify the obstacle avoidance effect of the improved algorithm. The experimental results showed that under three different environments: no noise, Gaussian noise, and artificial noise, the fence lines were extracted using RANSAC. Taking the change in the slope as an indicator, the obtained results were about −0.058, 0.058, and −0.061, respectively. The slope obtained by the RANSAC method has less variation compared to the no-noise group. Compared with LSM, the extraction results did not change significantly, indicating that RANSAC has a certain resistance to various noises, but RANSAC performs better in extraction effect and real-time performance. The simulation and actual test results show that the improved artificial potential field method can select reasonable parameters and repulsive force directions. The optimized path increases the shortest distance of the obstacle point cloud from the navigation path from 0.18 to 0.41 m, where the average time is 0.059 s, and the standard deviation is 0.007 s. This shows that the optimization method can optimize the path in real time to avoid obstacles, basically meet the requirements of security and real-time performance, and effectively avoid the local minimum problem. This research will provide corresponding technical references for pusher robots to overcome the problems existing in the process of autonomous navigation and pushing operation in complex open scenarios.
Increasing the Environmental Sustainability of Greenhouse Vegetable Production by Combining Biochar Application and Drip Fertigation—Effects on Soil N2O Emissions and Carbon Sequestrations
Authors: Zhao Yiming , Lin Shan , Lv Haofeng , Wang Yafang , Hu Jing , Li Guoyuan , Butterbach-Bahl Klaus
Published: July 2022

Drip fertigation with reduced fertilizer and water inputs has been widely used in greenhouse vegetable production in China. However, farmers usually do not apply additional organic material with a high carbon content, although soil organic carbon (SOC) concentrations are mostly below the optimum level for vegetable production. Returning straw or biochar to fields is an effective strategy for sustainability and environmental friendliness. We tested whether drip fertigation, (DIF) combined with maize straw (DIF+S) or biochar (DIF+BC), is a suitable option to improve SOC sequestration over eight growing seasons, and how these options affect soil N2O emissions and yields or partial factor productivity of applied N (PFPN) of crops over three growing seasons. During the winter–spring growing season, DIF+BC significantly reduced soil N2O emission by 61.2% and yield-scaled N2O emission by 62.4%, while increasing the tomato yield and PFPN compared with DIF. Straw incorporation had similar trends but without significant effects. Conversely, straw and biochar incorporation increased N2O emission during the autumn–winter season. The structural equation model indicated N2O emission was dominantly driven by soil NH4+-N concentration, temperature and moisture. The N2O emission factor decreased significantly with increased PFPN. Moreover, the contribution of biochar to the increased SOC was approximately 78%, which was four times higher than that of straw incorporation. Overall, the results highlighted the potential of drip fertigation with biochar incorporation to mitigate N2O emissions, improve PFPN and significantly increase SOC storage, which could all contribute to maintaining environmental sustainability and soil quality of greenhouse vegetable production.
Wildlife Photos on Social Media: A Quantitative Content Analysis of Conservation Organisations’ Instagram Images
Authors: Shaw Meghan N. , Borrie William T. , McLeod Emily M. , Miller Kelly K.
Published: July 2022

Wildlife populations are vanishing at alarmingly high rates. This issue is being addressed by organisations around the world and when utilizing social media sites like Instagram, images are potentially more powerful than words at conveying crucial conservation messages and garnering public support. However, different elements of these images have been shown to potentially have either positive or negative effects on viewers’ attitudes and behaviours towards wildlife and towards the organisation posting the image. This study used a quantitative content analysis to assess the most common and engaging elements of wildlife images posted to Instagram in 2020 and 2021, using Australian conservation organisations as a case study. A total of 670 wildlife images from the Instagram accounts of 160 conservation organisation Instagram accounts were coded and analysed. Results highlight that the most common image elements used included natural backgrounds, mammals and birds, and no human presence. In addition, it was found that the taxon of the animal featured in a post and the presence of humans did not impact engagement levels. Our findings highlight the potential for Instagram posts to feature and promote a wide range of currently underrepresented species, and for conservation organisations to be able to confidently share and post images that promote positive perceptions of both the animal and the conservation organisation.
High-Throughput Identification of Epigenetic Compounds to Enhance Chicken Host Defense Peptide Gene Expression
Authors: Deng Zhuo , Lyu Wentao , Zhang Guolong
Published: July 2022

Enhancing the synthesis of endogenous host defense peptides (HDPs) has emerged as a novel antibiotic-free approach to infectious disease control and prevention. A number of epigenetic compounds have been identified as HDP inducers and several have proved beneficial in antimicrobial therapy. However, species-specific regulation of HDP synthesis is evident. In attempt to identify epigenetic compounds with potent HDP-inducing activity for poultry-specific application, we developed a stable luciferase reporter cell line, known as HTC/AvBD10-luc, following our earlier construction of HTC/AvBD9-luc. HTC/AvBD10-luc was developed through permanent integration of a chicken macrophage cell line, HTC, with a lentiviral luciferase reporter vector driven by a 4-Kb AvBD10 gene promoter. Using a high throughput screening assay based on the two stable cell lines, we identified 33 hits, mostly being histone deacetylase (HDAC) inhibitors, from a library of 148 epigenetic compounds. Among them, entinostat and its structural analog, tucidinostat, were particularly effective in promoting multiple HDP gene expression in chicken macrophages and jejunal explants. Desirably, neither compounds triggered an inflammatory response. Moreover, oral gavage of entinostat significantly enhanced HDP gene expression in the chicken intestinal tract. Collectively, the high throughput assay proves to be effective in identifying HDP inducers, and both entinostat and tucidinostat could be potentially useful as alternatives to antibiotics to enhance intestinal immunity and disease resistance.
Chocolate and Cocoa-Derived Biomolecules for Brain Cognition during Ageing
Authors: Zeli Corinna , Lombardo Mauro , Storz Maximilian Andreas , Ottaviani Morena , Rizzo Gianluca
Published: July 2022

Cognitive decline is a common problem in older individuals, often exacerbated by neurocognitive conditions, such as vascular dementia and Alzheimer’s disease, which heavily affect people’s lives and exert a substantial toll on healthcare systems. Currently, no cure is available, and commonly used treatments are aimed at limiting the progressive loss of cognitive functions. The absence of effective pharmacological treatments for the cognitive decline has led to the search for lifestyle interventions, such as diet and the use of nutraceuticals that can prevent and limit the loss of cognition. Cocoa and chocolate are foods derived from cocoa beans, commonly used in the population and with good acceptability. The purpose of this review was to collect current experimental evidence regarding the neuroprotective effect of chocolate and cocoa (or derived molecules) in the elderly. From a systematic review of the literature, 9 observational studies and 10 interventional studies were selected, suggesting that the biomolecules contained in cocoa may offer promising tools for managing cognitive decline, if provided in adequate dosages and duration of treatment. However, the molecular mechanisms of cocoa action on the central nervous system are not completely understood.
A Comprehensive Review of C. capsularis and C. olitorius: A Source of Nutrition, Essential Phytoconstituents and Pharmacological Activities
Authors: Biswas Ashok , Dey Susmita , Huang Siqi , Deng Yong , Birhanie Ziggiju Mesenbet , Zhang Jiangjiang , Akhter Delara , Liu Liangliang , Li Defang
Published: July 2022

Plant bioactive compounds have gained global significance in terms of both medicinal and economic ramifications due to being easily accessible and are believed to be effective with fewer side effects. Growing relevant clinical and scientific evidence has become an important criterion for accepting traditional health claims of medicinal plants and also supports the traditional uses of Corchorus as folk medicine. C. capsularis and C. olitorius have broad applications ranging from textile to biocomposite, and young leaves and shoots are used as healthy vegetables and have long been used as traditional remedies for fever, ascites, algesia, liver disorders, piles, and tumors in many cultures. This review systematically summarized and emphasized the nutritional attributes, mostly available bioactive compounds, and biological and potential pharmaceutical properties of C. capsularis and C. olitorius, disclosed to users and non-users. Results suggest that various phytochemicals such as cardiac glycosides, phenols, flavonoids, sterols, lipids, and fatty acids were found or analytically identified in different plant parts (leaf, stem, seed, and root), and many of them are responsible for pharmacological properties and their antitumor, anticancer, antioxidant, antinociceptive, anti-inflammatory, analgesic, antipyretic, antiviral, antibacterial, anticonvulsant, antidiabetic and antiobesity, and cardiovascular properties help to prevent and cure many chronic diseases. In addition to their use in traditional food and medicine, their leaves have also been developed for skin care products, and some other possible uses are described. From this review, it is clear that the isolated compounds of both species have great potential to prevent and treat various diseases and be used as functional foods. In conclusion, this comprehensive review establishes a significant reference base for future research into various medical and functional food applications.
Analysis of a Nature-Inspired Shape for a Vertical Axis Wind Turbine
Authors: Damota Javier Blanco , García Juan de Dios Rodríguez , Casanova Antonio Couce , Miranda Javier Telmo , Caccia Claudio Giovanni , Galdo María Isabel Lamas
Published: July 2022

Wind energy is gaining special interest worldwide due to the necessity of reducing pollutant emissions and employ renewable resources. Traditionally, horizontal axis wind turbines have been employed but certain situations require vertical axis wind turbines. With a view to improve the efficiency of a vertical axis wind turbine Savonius type, the present work proposes a bioinspired design blade profile relying on the Fibonacci spiral. This shape is repeatedly presented in nature and thus it leads to a bio-inspired blade profile. A numerical model was carried out and it was found that the Fibonacci shape improves the performance of the original Savonius shape, based on semicircular blade profiles. Particularly, the Fibonacci blade profile increases around 14% the power in comparison with the Savonius blade profile. Besides this comparison between Savonius and Fibonacci, a research study was carried out to improve the efficiency of the Fibonacci turbine. To this end, the effect of several parameters was analyzed: number of blades, aspect ratio, overlap, separation gap, and twist angle. Improvements on the average power greater than 30% were obtained.
Biodeterioration Assessment of a Unique Old Pharaonic Kingdom Wooden Statue Using Advanced Diagnostic Techniques
Authors: Atwa Dina M. , Ibrahim Shimaa , Stani Chiaramaria , Birarda Giovanni , Ali Nehal , Abdullah Emam , Vaccari Lisa , Grenni Paola , Visca Andrea , Badr Yehia , Soliman Wafaa
Published: July 2022

A recently discovered Egyptian wooden statue of King Djedefre was studied together with some surrounding burial soil samples for assessing the statue biodeterioration. The wooden morphological characterisation identified the hardwood Acacia nilotica as the wood type. X-ray diffraction, micro-FT-IR spectroscopy, and scanning electron microscopy with an X-ray spectrometer were used to evaluate the wood deterioration degree and the soil contribution in wood biodeterioration. Microbiological analyses (fluorescent in situ hybridisation and polymerase chain reaction) were also performed to detect the microbial attack on the statue. The prolonged interaction of the statue with the burial environment caused a strong wood decay due to biotic (fungi and bacteria) and abiotic factors (e.g., humidity fluctuations of the burial environment), which caused the severe cracking and collapsing of the wood structures. The analyses of the burial soil mineral composition were relevant for obtaining an overall picture of the statue deterioration. The results are useful for planning the right conservation procedures for this very particular and important wooden statue. Furthermore, analysis of the woody cell wall will help in the selection of appropriate consolidation and recovery treatments. Because the statue is a unique single piece of wood, and the morphological observations indicated that it is a bald woman in a sitting position, this statue will provide new and interesting knowledge of Egyptian culture.
Error-Resistant Movement Detection Algorithm for the Elderly with Smart Mirror
Authors: Yang Bo-Seung , Kang Tae-Won , Choi Yong-Sik , Jung Jin-Woo
Published: July 2022

As the elderly population increases globally, the demand for systems and algorithms that target the elderly is increasing. Focusing on the extendibility of smart mirrors, our purpose is to create a motion detection system based on video input by an attached device (an RGB camera). The motion detection system presented in this paper is based on an algorithm that returns a Boolean value indicating the detection of motion based on skeletal information. We analyzed the problems that occur when the adjacent frame subtraction method (AFSM) is used in the motion detection algorithm based on the skeleton-related output of the pose estimation model. We compared and tested the motion recognition rate for slow-motion with the previously used AFSM and the vector sum method (VSM) proposed in this paper. As an experimental result, the slow-motion detection rate showed an increase of 30–70%.
Incorporation of Torsion Springs in a Knee Exoskeleton for Stance Phase Correction of Crouch Gait
Authors: Bumbard Katy Baker , Herrington Harold , Goh Chung-Hyun , Ibrahim Alwathiqbellah
Published: July 2022

Crouch gait is a motor complication that is commonly associated with cerebral palsy, spastic diplegia, stroke, and motor-neurological pathologies, broadly defined as knee flexion in excess of 20° in the gait cycle. Uncorrected crouch gait results in fatigue, joint degradation, and loss of ambulation. Torsion springs have been used in cycling to store energy in the knee flexion to reduce fatigue in the quadriceps during knee extension. SolidWorks was used to design a passive exoskeleton for the knee, incorporating torsion springs of stiffnesses 20,000 N/mm and 30,000 N/mm at the knee joint, to correct four different crouch gaits. OpenSim was used to gather data from the moments produced, and knee angles from each crouch gait and the normal gait. Motion analysis of the exoskeleton was simulated using knee angles for each crouch gait and compared with the moments produced with the normal gait moments in the stance phase of the gait cycle. All crouch gait moments were significantly reduced, and the correction of peak crouch moments was achieved, corresponding to the normal gait cycle during the stance phase. These results offer significant potential for nonsurgical and less invasive options for wearable exoskeletons in crouch gait correction.
Is the Side Bridge Test Valid and Reliable for Assessing Trunk Lateral Flexor Endurance in Recreational Female Athletes?
Authors: Juan-Recio Casto , Prat-Luri Amaya , Galindo Alberto , Manresa-Rocamora Agustín , Barbado David , Vera-Garcia Francisco J.
Published: July 2022

The side bridge test (SBT) is one of the most popular tests to assess isometric trunk lateral flexor endurance. The aim of this study was to assess the validity and reliability of the SBT in healthy females. Twenty-four (24.58 ± 3.92 years) physically active (1–2 h of moderate physical activity, 2–3 times a week) females voluntarily participated in this study. The surface electromyography (EMG) of eight abdominal, back, shoulder and hip muscles was measured during the SBT. Normalized median frequency slopes (NMFslope) were calculated to analyze the muscle fatigue. The EMG amplitudes were normalized to maximum EMG values to assess muscle activity intensity. A one-week test-retest design was performed to evaluate the SBT reliability through the ICC3,1 and typical error. Higher NMFslopes and normalized EMG amplitudes were found in deltoids, abdominal obliques, rectus abdominis, and erector spinae in comparison to latissimus dorsi, gluteus medius, and rectus femoris. However, no significant differences were found between the trunk lateral flexors and the deltoids. Linear regression analysis showed that SBT performance could be significantly predicted by external oblique and deltoid NMFslope (adjusted R2 = 0.673) and by body mass and trunk height (adjusted R2 = 0.223). Consistency analysis showed a high intraclass correlation coefficient (0.81) and a relatively high typical error (10.95 s). Despite the good relative reliability of the SBT, its absolute reliability was low and its validity questionable, as the shoulder muscle activation and fatigue and the individuals’ anthropometric characteristics played an important role in SBT performance.
Biomaterial-Mediated Factor Delivery for Spinal Cord Injury Treatment
Authors: Pinelli Filippo , Pizzetti Fabio , Veneruso Valeria , Petillo Emilia , Raghunath Michael , Perale Giuseppe , Veglianese Pietro , Rossi Filippo
Published: July 2022

Spinal cord injury (SCI) is an injurious process that begins with immediate physical damage to the spinal cord and associated tissues during an acute traumatic event. However, the tissue damage expands in both intensity and volume in the subsequent subacute phase. At this stage, numerous events exacerbate the pathological condition, and therein lies the main cause of post-traumatic neural degeneration, which then ends with the chronic phase. In recent years, therapeutic interventions addressing different neurodegenerative mechanisms have been proposed, but have met with limited success when translated into clinical settings. The underlying reasons for this are that the pathogenesis of SCI is a continued multifactorial disease, and the treatment of only one factor is not sufficient to curb neural degeneration and resulting paralysis. Recent advances have led to the development of biomaterials aiming to promote in situ combinatorial strategies using drugs/biomolecules to achieve a maximized multitarget approach. This review provides an overview of single and combinatorial regenerative-factor-based treatments as well as potential delivery options to treat SCIs.