bluuebunny/crossref_metadata_2025 huggingface dataset:
Unfulfilled psychosocial needs of the adolescent siblings of patients with cancer and the identification of the related factors
Authors: Masoudifar Zeynab , Rassouli Maryam , Ashrafizadeh Hadis , Fathollah Zadeh Ensieh , Dadashi Nasrin , Khanali Mojen Leila
Published: September 2022

Background

The diagnosis of cancer in a child is a stressful experience for the entire family, particularly for adolescent or young adult siblings and their psychosocial needs (PSNs) may remain unfulfilled. The aim of the study was to assess the unfulfilled PSNs of the adolescent siblings of patients with cancer in Iran and examine the relationships between demographic and medical variables and PSNs.

Methods

This descriptive analytical study was conducted in 2019 in seven teaching hospitals in Tehran, Iran. Participants were 188 adolescent siblings of patients with cancer. Sampling was performed consecutively. Data were collected using a demographic and clinical characteristics questionnaire and the Sibling Cancer Needs Instrument (SCNI). To investigate the relationship between demographic variables and the mean score of PSNs subscales, first, the correlation was determined, and afterward, the significant variables were analyzed using multiple linear regression.

Results

In total, 180 adolescent siblings completed the study. Their mean age was 15.66 ± 2.55 years and the mean summary score of their PSNs was 121.15 ± 32.73. Around 80.60% of adolescents indicated at least one unmet need related to each question. The most common unfulfilled needs of participants were related to the information about sibling’s cancer dimension (INFO) (mean: 2.94 ± 0.79) and the less common unfulfilled needs were related to the practical assistance dimension (UFAM) (mean: 2.38 ± 0.93). Based on the regression coefficients, a significant relationship was observed between the mean summary score of PSNs with the duration of cancer (β = –2.199, p = 0.006) and mother’s age (β = –2.805, p = 0.029).

Conclusion

The adolescent siblings of patients with cancer have different unfulfilled PSNs, particularly respecting information about their siblings’ cancer and support for emotional coping. Family members and healthcare providers should provide these adolescents with strong informational support and fulfill their needs in order to promote their health and their emotional coping.
Prevalence and correlates of cannabis abuse among residents in the community of Fort McMurray, a city in Northern Alberta which had endured multiple natural disasters
Authors: Obuobi-Donkor Gloria , Eboreime Ejemai , Shalaby Reham , Agyapong Belinda , Agyapong Vincent I. O.
Published: September 2022

Background

Cannabis is one of the widely used drugs for relaxation and may be abuse among users. Researchers have given attention to cannabis use among the general population while vulnerable populations who have experience multiple traumas may be at risk of cannabis abuse. Other factors may influence cannabis abuse among people exposed to traumas.

Objective

The study aims to determine the prevalence and correlates of self-reported cannabis abuse among residents of Fort McMurray, a city in Northern Alberta, Canada.

Methods

A cross-sectional survey was conducted using an online questionnaire. Sociodemographic data, trauma exposure, and clinical characteristics were collected to identify the possible risk factor of cannabis abuse. Data were analyzed with SPSS version 25 using a chi-square test and binary logistic regression analysis. Correlation analysis was also performed to ascertain likely cannabis abuse and the association with other mental health conditions.

Results

Overall, participants who completed the survey were one hundred and eighty-sixed out of the two hundred and forty-nine residents who accessed the online survey, giving a response rate of 74.7%. The prevalence of self-reported cannabis abuse among participants was 14%. Most of the participants were females (159, 85.5%), more than 40 years of age (98, 52.7%), employed (175, 94.1%), owned their house (145, 78.0%), and 103 (60.6%) reported being exposed to at least a trauma (COVID-19, flooding, or wildfire). Regarding regression analysis results, participants living in a rented accommodation were nearly four times more likely to abuse cannabis (OR = 3.86; 95% CI: 1.34–11.14) than those owning their houses. Similarly, male participants were more than 6-folds more likely to abuse cannabis than the female gender (OR= 6.25; 95% CI: 1.89–20), and participants in a relationship were six times more likely to abuse cannabis than participants not in a relationship (OR = 6.33; 95% CI: 1.67–24.39). The study also found significant association of depressive symptoms (X2 = 4.561; p = 0.033) and anxiety symptoms (X2 = 4.700; p = 0.030) with likely cannabis abuse.

Conclusion

Demographic factors significantly predicted likely cannabis abuse in the Fort McMurray population, and cannabis abuse significantly correlated with presence of moderate to high anxiety and depression symptoms. It is essential to mobilized resources to support vulnerable communities and manage cannabis abuse.
Development of a deep learning algorithm for myopic maculopathy classification based on OCT images using transfer learning
Authors: He Xiaoying , Ren Peifang , Lu Li , Tang Xuyuan , Wang Jun , Yang Zixuan , Han Wei
Published: September 2022

Purpose

To apply deep learning (DL) techniques to develop an automatic intelligent classification system identifying the specific types of myopic maculopathy (MM) based on macular optical coherence tomography (OCT) images using transfer learning (TL).

Method

In this retrospective study, a total of 3,945 macular OCT images from 2,866 myopic patients were recruited from the ophthalmic outpatients of three hospitals. After culling out 545 images with poor quality, a dataset containing 3,400 macular OCT images was manually classified according to the ATN system, containing four types of MM with high OCT diagnostic values. Two DL classification algorithms were trained to identify the targeted lesion categories: Algorithm A was trained from scratch, and algorithm B using the TL approach initiated from the classification algorithm developed in our previous study. After comparing the training process, the algorithm with better performance was tested and validated. The performance of the classification algorithm in the test and validation sets was evaluated using metrics including sensitivity, specificity, accuracy, quadratic-weighted kappa score, and the area under the receiver operating characteristic curve (AUC). Moreover, the human-machine comparison was conducted. To better evaluate the algorithm and clarify the optimization direction, the dimensionality reduction analysis and heat map analysis were also used to visually analyze the algorithm.

Results

Algorithm B showed better performance in the training process. In the test set, the algorithm B achieved relatively robust performance with macro AUC, accuracy, and quadratic-weighted kappa of 0.986, 96.04% (95% CI: 0.951, 0.969), and 0.940 (95% CI: 0.909–0.971), respectively. In the external validation set, the performance of algorithm B was slightly inferior to that in the test set. In human-machine comparison test, the algorithm indicators were inferior to the retinal specialists but were the same as the ordinary ophthalmologists. In addition, dimensionality reduction visualization and heatmap visualization analysis showed excellent performance of the algorithm.

Conclusion

Our macular OCT image classification algorithm developed using the TL approach exhibited excellent performance. The automatic diagnosis system for macular OCT images of MM based on DL showed potential application prospects.
Work climate in emergency health services during COVID-19 pandemic—An international multicenter study
Authors: Kosydar-Bochenek Justyna , Krupa Sabina , Religa Dorota , Friganovic Adriano , Oomen Ber , Williams Ged , Vollman Kathleen M. , Rogado Maria Isabelita C. , Goldsworthy Sandra , Lopez Violeta , Brioni Elena , Medrzycka-Dabrowska Wioletta
Published: September 2022

Introduction

A good working climate increases the chances of adequate care. The employees of Emergency in Hospitals are particularly exposed to work-related stress. Support from management is very important in order to avoid stressful situations and conflicts that are not conducive to good work organization. The aim of the study was to assess the work climate of Emergency Health Services during COVID-19 Pandemic using the Abridged Version of the Work Climate Scale in Emergency Health Services.

Design

A prospective descriptive international study was conducted.

Methods

The 24-item Abridged Version of the Work Climate Scale in Emergency Health Services was used for the study. The questionnaire was posted on the internet portal of scientific societies. In the study participated 217 women (74.5%) and 74 men (25.4%). The age of the respondents ranged from 23 to 60 years (SD = 8.62). Among the re-spondents, the largest group were Emergency technicians (85.57%), followed by nurses (9.62%), doctors (2.75%) and Service assistants (2.06%). The study was conducted in 14 countries.

Results

The study of the climate at work shows that countries have different priorities at work, but not all of them. By answering the research questions one by one, we can say that the average climate score at work was 33.41 min 27.0 and max 36.0 (SD = 1.52).

Conclusion

The working climate depends on many factors such as interpersonal relationships, remuneration or the will to achieve the same selector. In the absence of any of the elements, a proper working climate is not possible.
Cost analysis of implementing a vial-sharing strategy for chemotherapy drugs using intelligent dispensing robots in a tertiary Chinese hospital in Sichuan
Authors: Liu Hui , Zou Linke , Song Yujie , Yan Junfeng
Published: September 2022

Introduction

Chemotherapy drug wasting is a huge problem in oncology that not only results in excessive expenses on chemotherapy drugs but also increases the cost of disposing of chemotherapy waste and the risk of occupational exposure in the environment. The main objective of this study was to evaluate the potential for hospitals in China to employ a real-time vial-sharing strategy that can save drug costs.

Method

This study was conducted retrospectively at Pharmacy Intravenous Admixture Services (PIVAS), People's Hospital of Sichuan Province, China, from September to November 2021. Data on prescription drugs wasted were collected from the Hospital Information System (HIS). To assess the real-time vial-sharing strategy, we estimated drug wastage and drug waste costs using intelligent robots that dispense multiple prescriptions simultaneously.

Results

24 of the 46 wasted drugs were cost-saved. The vial-sharing strategy saved 186,067 mg of drugs, or ~59.08% of the total amount wasted, resulting in savings of 150,073.53 China Yuan (CNY), or 47.51% of the cost of the total waste.

Conclusion

Our investigation established that employing a real-time vial-sharing strategy using an intelligent robot to dispense multiple prescriptions simultaneously is cost-effective. Additionally, this approach presented no safety issue concerns, such as the introduction of impurities to sterile compounding via repeated interspersing or the incorrect registration of information during drug storage, often encountered with traditional vial-sharing strategies.
Quality of online video resources concerning patient education for neck pain: A YouTube-based quality-control study
Authors: Zhang Xiang , Yang Yi , Shen Yi-Wei , Zhang Ke-Rui , Ma Li-Tai , Ding Chen , Wang Bei-Yu , Meng Yang , Liu Hao
Published: September 2022

Background

More than 70 percent of the world's population is tortured with neck pain more than once in their vast life, of which 50–85% recur within 1–5 years of the initial episode. With medical resources affected by the epidemic, more and more people seek health-related knowledge via YouTube. This article aims to assess the quality and reliability of the medical information shared on YouTube regarding neck pain.

Methods

We searched on YouTube using the keyword “neck pain” to include the top 50 videos by relevance, then divided them into five and seven categories based on their content and source. Each video was quantitatively assessed using the Journal of American Medical Association (JAMA), DISCERN, Global Quality Score (GQS), Neck Pain-Specific Score (NPSS), and video power index (VPI). Spearman correlation analysis was used to evaluate the correlation between JAMA, GQS, DISCERN, NPSS and VPI. A multiple linear regression analysis was applied to identify video features affecting JAMA, GQS, DISCERN, and NPSS.

Results

The videos had a mean JAMA score of 2.56 (SD = 0.43), DISCERN of 2.55 (SD = 0.44), GQS of 2.86 (SD = 0.72), and NPSS of 2.90 (SD = 2.23). Classification by video upload source, non-physician videos had the greatest share at 38%, and sorted by video content, exercise training comprised 40% of the videos. Significant differences between the uploading sources were observed for VPI (P = 0.012), JAMA (P < 0.001), DISCERN (P < 0.001), GQS (P = 0.001), and NPSS (P = 0.007). Spearman correlation analysis showed that JAMA, DISCERN, GQS, and NPSS significantly correlated with each other (JAMA vs. DISCERN, p < 0.001, JAMA vs. GQS, p < 0.001, JAMA vs. NPSS, p < 0.001, DISCERN vs. GQS, p < 0.001, DISCERN vs. NPSS, p < 0.001, GQS vs. NPSS, p < 0.001). Multiple linear regression analysis suggested that a higher JAMA score, DISCERN, or GQS score were closely related to a higher probability of an academic, physician, non-physician or medical upload source (P < 0.005), and a higher NPSS score was associated with a higher probability of an academic source (P = 0.001) than of an individual upload source.

Conclusions

YouTube videos pertaining to neck pain contain low quality, low reliability, and incomplete information. Patients may be put at risk for health complications due to inaccurate, and incomplete information, particularly during the COVID-19 crisis. Academic groups should be committed to high-quality video production and promotion to YouTube users.
How smart senior care can achieve value co-creation: Evidence from China
Authors: Fu Liping , Pei Tong , Yang Jie , Han Jiarui
Published: September 2022

With the rapid rise of artificial intelligence, smart senior care has become a new trend for future development. The collection of “Typical Cases of Chinese Elderly Service Industry Development” is selected by the script materials. The main purpose of this article is to investigate how smart senior care can achieve value co-creation by grounded theory. This study explores the phenomenon of value co-creation in the participation of multiple actors in smart senior care services. Findings show that institutional guarantee, technical intake, market empowerment, emotional support, service interaction, and reciprocity norm are identified as the driving factors for value co-creation. In addition, the behavioral processes of value co-creation include multi-actor value consensus, co-creation environment establishment, practical value co-creation, public value sharing, and diffusion of service added value in smart senior care. Finally, this study constructs a practical logic model of achieving value co-creation. It extends and enriches the scope of the value co-creation theory. This study confirms that value co-creation can be effectively achieved in smart senior care by the above-mentioned ways, revealing its driving factors and behavioral processes. The article expands on the application of value co-creation in the field of public healthcare. The results have important theoretical and practical significance for narrowing the public service equalization gap.
Training and intrinsic evaluation of lightweight word embeddings for the clinical domain in Spanish
Authors: Chiu Carolina , Villena Fabián , Martin Kinan , Núñez Fredy , Besa Cecilia , Dunstan Jocelyn
Published: September 2022

Resources for Natural Language Processing (NLP) are less numerous for languages different from English. In the clinical domain, where these resources are vital for obtaining new knowledge about human health and diseases, creating new resources for the Spanish language is imperative. One of the most common approaches in NLP is word embeddings, which are dense vector representations of a word, considering the word's context. This vector representation is usually the first step in various NLP tasks, such as text classification or information extraction. Therefore, in order to enrich Spanish language NLP tools, we built a Spanish clinical corpus from waiting list diagnostic suspicions, a biomedical corpus from medical journals, and term sequences sampled from the Unified Medical Language System (UMLS). These three corpora can be used to compute word embeddings models from scratch using Word2vec and fastText algorithms. Furthermore, to validate the quality of the calculated embeddings, we adapted several evaluation datasets in English, including some tests that have not been used in Spanish to the best of our knowledge. These translations were validated by two bilingual clinicians following an ad hoc validation standard for the translation. Even though contextualized word embeddings nowadays receive enormous attention, their calculation and deployment require specialized hardware and giant training corpora. Our static embeddings can be used in clinical applications with limited computational resources. The validation of the intrinsic test we present here can help groups working on static and contextualized word embeddings. We are releasing the training corpus and the embeddings within this publication1.
Yes we care!-Certification for machine learning methods through the care label framework
Authors: Morik Katharina J. , Kotthaus Helena , Fischer Raphael , Mücke Sascha , Jakobs Matthias , Piatkowski Nico , Pauly Andreas , Heppe Lukas , Heinrich Danny
Published: September 2022

Machine learning applications have become ubiquitous. Their applications range from embedded control in production machines over process optimization in diverse areas (e.g., traffic, finance, sciences) to direct user interactions like advertising and recommendations. This has led to an increased effort of making machine learning trustworthy. Explainable and fair AI have already matured. They address the knowledgeable user and the application engineer. However, there are users that want to deploy a learned model in a similar way as their washing machine. These stakeholders do not want to spend time in understanding the model, but want to rely on guaranteed properties. What are the relevant properties? How can they be expressed to the stake- holder without presupposing machine learning knowledge? How can they be guaranteed for a certain implementation of a machine learning model? These questions move far beyond the current state of the art and we want to address them here. We propose a unified framework that certifies learning methodsviacare labels. They are easy to understand and draw inspiration from well-known certificates like textile labels or property cards of electronic devices. Our framework considers both, the machine learning theory and a given implementation. We test the implementation's compliance with theoretical properties and bounds.
Case Report: A case of IgD lambda/lambda Multiple Myeloma in patient with acute renal failure and without monoclonal spike in serum electrophoresis
Authors: Troiano Teresa , Brescia Vincenzo , De Marinis Lucia , Marinaccio Anna , Lovero Roberto , Rizzi Rita , Di Serio Francesca
Published: September 2022

Background

IgD Multiple Myeloma is a rare form of plasma cell dyscrasia and accounts for approximately 1-2% of all cases of Multiple Myeloma. It mainly affects young, male subjects; it is characterized by an aggressive course, a high production of Bence Jones protein, acute renal failure and an often unfortunate outcome compared to the other isotypes of MM. A distinctive feature is the lack of a monoclonal peak on serum protein electrophoresis (SPE).

Case report

a 57-year-old man with pain in his left lower limb and weight loss goes to the Emergency Department (Emergency Department). Laboratory tests performed showed normocytic normochromic anemia (Hemoglobin 9.4 g/dL), acute renal failure (s-creatinine 2.85 mg/dL, e-GFR 23 mL/min/1.73 m². serum protein electrophoresis (SPE) detected only mild polyclonal in the gamma zone with no evidence of any monoclonal peak.

Results

serum immunofixation (s-IFE) showed a monoclonal IgD λ band and a monoclonal λ band. The Free Light Chains (s-FLC) measurement showed a ratio of 0.04. The bone marrow biopsy confirmed an infiltration of> 20% of clonal plasma cells; renal biopsy diagnosed “cast nephropathy”.

Conclusion

IgD λ/λ Multiple Myeloma is a rare form of this disease with a poor prognosis; an early and correct laboratory diagnosis is crucial for appropriate treatment and effective monitoring in order to improve patient outcome.
“After the floods, he says he is an environmentalist”: Understanding blended roles and organizational boundaries in decision-making under uncertainty during unprecedented floods in Wayanad, India
Authors: Koshy Mrudhula
Published: September 2022

An increase in unprecedented environmental crises as a result of climate change and human influence has amplified calls for recognizing the complexity of decision-making under uncertainty (DMUU). How decision-makers act in institutional settings under uncertainty has, however, received limited attention in decision-making in planning practice. This article investigates DMUU in the context of Wayanad, a peri urban hill district in Kerala, India through two decision settings; the response to unprecedented heavy monsoon floods in 2018 and 2019 as a case of short-term uncertainty, and policy and plan making regarding quarrying in ecologically sensitive areas as a case of long-term uncertainty. Through empirical findings from semi-structured interviews of 58 decision-makers from state and non-state actors, the article discusses individual and collective actions made before, during and after the floods by combining insights on DMUU from spatial planning and governance literature underpinned by spatial-temporal and political ecology narratives. The article argues that factors such as community resourcefulness and decentralized governance appeared to facilitate effective decision-making under short-term uncertainty. However, the same factors did not have an intrinsic influence on decision-making under long-term uncertainty with current ways of decision-making regarding quarrying in ecologically sensitive areas likely obstructing sustainable long-term planning and land use transformation in Wayanad. The article concludes with recommendations for potential improvements in decision-making under long-term uncertainty in contexts with weak institutional mechanisms, chronic vulnerabilities and resource scarcity, through structural organizational change, cross-sectoral decision-making arenas, and decision-making frameworks that foregrounds heuristic, flexible, incremental, and cumulative actions across scales over time.
Female influencers: Analyzing the social media representation of female subjectivity in Italy
Authors: Roberti Geraldina
Published: September 2022

The paper addresses the representation of female subjectivity on social media, highlighting how such women's images have a significant impact on the gendered narratives and discourses that populate the public sphere. The article analyzes specifically the pattern of femininity represented by female influencers and the bond they are able to establish with their followers. Starting from the notion of post-feminism sensitivity, it highlights how these celebrities embody its ideals in terms of self-realization, independence and empowerment. Finally, the figures of two of the most popular social media influencers in Italy, Chiara Ferragni and Benedetta Rossi, are analyzed, highlighting their ability to represent a successful model of female digital entrepreneurship. The analysis aims to point out how these media personae provide an ambivalent model of female subjectivity, because on one hand they emphasize women's ability to assert themselves as ambitious, professionally autonomous and free-choosing subjects (as postfeminist culture prescribes), but on the other hand they exploit the spur to female self-fulfillment for marketing aims, turning it into a self-branding tool.
Gender differences in climate-smart adaptation practices amongst bean-producing farmers in Malawi: The case of Linthipe Extension Planning Area
Authors: Nchanji Eileen Bogweh , Kabuli Hilda , Nyamolo Victor Onyango , Cosmas Lutomia , Chisale Virginia , Matumba Anne
Published: September 2022

Agriculture is amongst the vulnerable sectors to climate change and its associated impacts. Most women are more vulnerable to the impacts of climate change than men. Climate Smart Agriculture ensures increased productivity thereby enabling food security, income security and wealth creation amongst the farming households. A study was carried out to understand the gender differences in access and use of climate-smart agriculture, challenges and solutions that men and women farmers use to adapt to climate change. Data was collected from 246 randomly sampled households from 14 villages at Linthipe Extension Planning in Dedza district in Malawi. The multivariate probit model was employed to understand the influence of sociodemographic, farm-level, and institutional factors in the application of climate-smart agriculture in the study area. Findings from this study indicate that there are differences in the adoption and use of climate-smart agriculture technologies in bean production amongst different gender categories. More women compared to men and youths tend to use fertilizer, use improved seeds and plant early in order to mitigate and adapt to climate change. Most men adopt and use irrigation, whilst the youth mostly adopted and used pesticides and conservation agriculture practices. The study recommends policies that would ensure the promotion of gender-responsive climate-smart agriculture technologies, improved access to inputs, and capacity building through training.
Porcine reproductive and respiratory syndrome virus RNA detection in tongue tips from dead animals
Authors: Machado Isadora F. , Magalhães Edison S. , Poeta Silva Ana Paula S. , Moraes Daniel C. A. , Cezar Guilherme , Mil-Homens Mafalda P. , Osemeke Onyekachukwu H. , Paiva Rodrigo , Moura Cesar A. A. , Gauger Phillip , Trevisan Giovani , Silva Gustavo S. , Linhares Daniel C. L.
Published: September 2022

The control of porcine reproductive and respiratory syndrome virus (PRRSV) hinges on monitoring and surveillance. The objective of this study was to assess PRRSV RNA detection by RT-PCR in tongue tips from dead suckling piglets compared to serum samples, processing fluids, and family oral fluids. Tongue tips and serum samples were collected from three PRRSV-positive breeding herd farms (farms A, B, and C) of three different age groups: newborns (<24 h), processing (2 to 7 days of age), and weaning (18 to 22 days of age). Additionally, processing fluids and family oral fluids were collected from 2–7 days of age and weaning age, respectively. In farms A and B, PRRSV RNA was detected in tongue tips from all age groups (100 and 95%, respectively). In addition, PRRSV RNA was detected in pooled serum samples (42 and 27%), processing fluids (100 and 50%), and family oral fluids (11 and 22%). Interestingly, the average Ct value from tongue tips was numerically lower than the average Ct value from serum samples in the newborn age. In farm C, PRRSV RNA was only detected in serum samples (60%) and family oral fluids (43%), both from the weaning age. Further, no PRRSV RNA was detected in tongue tips when pooled serum samples from the same age group tested PRRSV RNA-negative. Taken together, these results demonstrate the potential value of tongue tips for PRRSV monitoring and surveillance.
Sustainable Cotton Production through Increased Competitiveness: Analysis of Comparative Advantage and Influencing Factors of Cotton Production in Xinjiang, China
Authors: Yang Zhongna , Tang Jijun , Yu Mark , Zhang Yong , Abbas Azhar , Wang Shengde , Bagadeem Salim
Published: September 2022

Cotton production makes an important contribution to the income of rural residents and the economy in Xinjiang province, which leads other provinces in terms of planted area, total production, and average yield of cotton in China. This study analyzed the competitiveness of cotton production in the study area using the efficiency advantage index (EAI), scale advantage index (SAI), and aggregated advantage index (AAI). Moreover, the factors influencing the productivity of cotton have been investigated by the use of ridge regression and correlation matrix using a dataset for the period 2005 to 2018. The results showed that cotton production had a large comparative advantage in Xinjiang from 2005 to 2018. The average of efficiency advantage index (EAI), scale advantage index (SAI), and aggregated advantage index (AAI) are 1.50, 12.96, and 4.35, respectively. Overall, Xinjiang cotton production has a higher planting scale advantage and productivity. By using ridge regression to calculate the impact of cotton production on agricultural output value in Xinjiang, the results showed that total cotton production, fiscal expenditure on agricultural support, total agricultural machinery power, and fertilizer use had significant positive effects, whereas cotton sown area, average cotton yield, and the proportion of affected area by insects and diseases had negative impact agricultural output value. The study implies the need for a implementing a well-thought and empirically backed plan to support cotton production based on comparative advantage for a specific area, building a cotton production standard system, reducing the cost of cotton production, and building a cotton risk-protection system to protect the interests of cotton farmers and promote the sustainable development of the cotton industry.
Comparison of Hyperspectral Imagery and Physiological Characteristics of Bentazone-Tolerant and -Susceptible Soybean Cultivars
Authors: Ali Liakat , Jo Hyun , Choi Seung Min , Kim Yoonha , Song Jong Tae , Lee Jeong-Dong
Published: September 2022

Bentazone is a broadleaf post-emergence herbicide widely used for crop production that inhibits photosynthetic activity, resulting in phytotoxicity and injury in plants. Evaluating and identifying herbicide-tolerant genotypes is a critical step in plant breeding programs. In this study, we determined the reaction of 138 Korean soybean cultivars to bentazone using visual evaluation, and selected cultivars were further evaluated to determine the effects of bentazone on physiological parameters. For physiological parameters, we measured the normalized difference vegetation index (NDVI) from hyperspectral reflectance images. From 2 to 4 DAT, the NDVI for two sensitive cultivars was between 0.60 and 0.69, while the NDVI for tolerant cultivars was between 0.70 and 0.86. Photosynthesis rate (A), transpiration (E), stomatal conductance (gsw), and total conductance of CO2 (gtc) were measured using chlorophyll fluorescence. Visual score evaluation showed that moderate bentazone-tolerant cultivars were predominant among the Korean cultivars. For physiological measurements, differences in NDVI were detected between bentazone-tolerant and -sensitive cultivars 2 days after treatment (DAT). However, the A, E, gsw, and gtc levels dramatically decreased 1 DAT in the sensitive cultivars. This study provides insights into the tolerance and sensitivity of soybeans to bentazone.
Rhizospheric Microbiome Responses to Cover Crop Suppression Methods
Authors: Morales Marianela E. , Allegrini Marco , Iocoli Gastón A. , Basualdo Jessica , Villamil María B. , Zabaloy María C.
Published: September 2022

Although winter cover crops (WCCs) have demonstrated positive effects on soil properties, relatively little is known about the responses of the soil and plant microbiomes to the introduction of WCCs and their associated management. Our objective was to evaluate the effects of WCC suppression methods on the rhizosphere microbiome of oats under field conditions. Rhizospheric soil was extracted to quantify the abundances of amoA gene of ammonia-oxidizing bacteria and archaea, and nitrite reductase genes (nirK and nirS), and to determine potential nitrification activity. The bacterial 16S rRNA V4 region and fungal ITS regions were sequenced with the Illumina MiSeq system. Overall, our results indicated that the composition of the bacterial and fungal communities of the rhizosphere were sensitive to the WCC suppression methods. Some bacterial genera, including fungal antagonists and chitin degraders, and two fungi associated with plant potential pathogens, were favored by both suppression methods, yet both methods negatively affected other genera associated with plant growth promotion characteristics. Our work contributes to a more complete understanding of the interactions between WCC management practices, soil properties, and microbial communities in the rhizosphere, which is essential for choosing management strategies that maintain soil health and promote environmental sustainability.
Reducing Anxiety and Stress among Youth in a CBT-Based Equine-Assisted Adaptive Riding Program
Authors: Hoagwood Kimberly , Vincent Aviva , Acri Mary , Morrissey Meghan , Seibel Lauren , Guo Fei , Flores Chelsea , Seag Dana , Peth Pierce Robin , Horwitz Sarah
Published: September 2022

Reining in Anxiety (RiA) is a therapeutic program for youth with mild to moderate anxiety delivered in a therapeutic riding setting by Certified Therapeutic Riding Instructors. RiA was developed after a review of the evidence base for youth anxiety, is manualized, and includes five core CBT components: in vivo exposure, cognitive restructuring, youth psychoeducation, relaxation, and caregiver psychoeducation about anxiety. This study extended findings from a prior RCT that examined (1) the feasibility of collecting saliva samples from horses and children to measure stress (cortisol) and relaxation (oxytocin); (2) whether changes in stress and relaxation occurred both during each lesson and over the course of the 10-week intervention for horses and youth; (3) whether changes in anxiety symptoms, emotional regulation, and self-efficacy found in the first trial were comparable; and (4) if fidelity to the program was reliable. Youth participants (n = 39) ages 6–17 with caregiver-identified mild-to-moderate anxiety participated in a ten-week therapeutic intervention (RiA), which combined adaptive riding and components of CBT. Physiological data and self-report measures were taken at weeks one, four, seven, and ten for the youth and horses. Saliva assays assessed cortisol as a physiological marker of stress and anxiety, and oxytocin as a measure of relaxation. Fidelity data were recorded per session. Anxiety, as measured by caregiver self-reporting, significantly decreased from pre- to post-test, while emotional regulation scores increased. No significant changes in self-efficacy from pre- to post-test were observed. Saliva samples obtained from participants before and after riding sessions showed a consistent decrease in cortisol and a significant increase in oxytocin at two of the four timepoints (Week 1 and Week 7), but no overall pre- to post-test changes. Horse saliva data were collected using a modified bit; there were no significant changes in oxytocin or cortisol, suggesting that the horses did not have an increase in stress from the intervention. RiA may be a promising approach for reducing anxiety and stress among youth, as measured both by self-reported and by physiological measures. Collection of salivary assays for both youth and horses is feasible, and the intervention does not increase stress in the horses. Importantly, RiA can be delivered by adaptive/therapeutic horseback riding instructors in naturalistic (e.g., non-clinic-based) settings. As youth anxiety is a growing public health problem, novel interventions, such as RiA, that can be delivered naturalistically may have the potential to reach more youth and thus improve their quality of life. Further research is needed to examine the comparative value of RiA with other animal-assisted interventions and to assess its cost-effectiveness.
Killing Kira, Letting Tom Go?—An Empirical Study on Intuitions Regarding End-of-Life Decisions in Companion Animals and Humans
Authors: Persson Kirsten , Selter Felicitas , Kunzmann Peter , Neitzke Gerald
Published: September 2022

Veterinary and human medicine share the challenges of end-of-life decisions. While there are legal and practical differences, there might be parallels and convergences regarding decision-making criteria and reasoning patterns in the two disciplines. In this online survey, six variants of a fictitious thought experiment aimed at pointing out crucial criteria relevant for decision-making within and across both professional fields. The six variants introduced four human and two animal patients with the same disease but differing in age, gender and, in case of the human patients, in terms of their state of consciousness. Participants could choose between four different treatment options: euthanasia, continuous sedation, a potentially curative treatment with severe side effects and no intervention. Study participants were human and veterinary medical professionals and an additional control group of lay people. Decisions and justifications for the six variants differed but the three groups of participants answered rather homogeneously. Besides the patient’s “suffering” as a main criterion, “age”, “autonomy” and, to a lesser extent, “species” were identified as important criteria for decision-making in all three groups. The unexpected convergences as well as subtle differences in argumentation patterns give rise to more in-depth research in this cross-disciplinary field.
Characterizing the Pathogenesis and Immune Response of Equine Herpesvirus 8 Infection in Lung of Mice
Authors: Hu Leyu , Wang Tongtong , Ren Huiying , Liu Wenqiang , Li Yubao , Wang Changfa , Li Liangliang
Published: September 2022

Equine herpesvirus type 8 (EHV-8), associated with abortion and severe respiratory disease in donkeys and horses, causes significant economic losses in the global equine industry. However, the pathogenicity of EHV-8 is still unknown. Mice are widely used as an animal model to evaluate virus replication and virulence. The present study aimed to evaluate the pathogenicity of the EHV-8 SDLC66 strain in BALB/c mice. Mice were used to test for infection-associated parameters (such as clinical signs, body weights, virus replication in tissues, viremia, and cytokines) and sacrificed at 0, 2, 4, and 6 days post-infection (dpi). The mice inoculated with EHV-8 exhibited lethargy, dyspnea signs, loss in body weight, and viremia. EHV-8 was detected in the liver, spleen, brain, and lung by PCR at 4 dpi and 6 dpi, effectively replicating these tissues detected by TCID50 at 6 dpi. Proinflammatory cytokines, including IL-6, IL-1β, and TNF-α, were significantly increased at the 4 dpi and 6 dpi in the lung than in the control group. However, IFN-γ was only increased at 6 dpi in the EHV-8-infected group. These data showed that EHV-8 could enter the lungs of mice and cause respiratory disease in the mouse model, which helps reveal the pathogenicity of EHV-8.
Molecular Detection and Genetic Characterization of Ehrlichia ruminantium Harbored by Amblyomma hebraeum Ticks of Domestic Ruminants in North West Province, South Africa
Authors: Mnisi Sifiso S. , Mphuthi Malekoba B. N. , Ramatla Tsepo , Mofokeng Lehlohonolo S. , Thekisoe Oriel , Syakalima Michelo
Published: September 2022

Ehrlichia ruminantium (E. ruminantium) is the causative agent of heartwater disease and it is mainly transmitted to livestock by Amblyomma hebraeum (A. hebraeum) tick in South Africa. This study investigated the occurrence of E. ruminantium and its genetic diversity in ticks within Ngaka Modiri Molema district of North West Province in South Africa. Genomic DNA was extracted from whole A. hebraeum ticks totaling 876 and resulted in a total of 292 pooled DNA samples. Firstly, conventional PCR was used to detect Ehrlichia spp. targeting the dsbA gene, followed by nested PCR targeting the Map1 gene performed on DNA pool samples that were positive from the first PCR. One hundred and six tick DNA pool samples were positive by dsbA gene PCR for the presence of Ehrlichia spp. with minimum infection rate (MIR) of 121, while 13/106 were positive by Map1 PCR with MIR of 15. Different E. ruminantium Map1 genotypes (NWUe1, NWUe2, NWUe3, NWUe5, and NWUe6) were detected from tick samples and were closely related to more than 13 gene sequences of E. ruminantium from the NCBI GenBank database. These findings suggest that there is a significant diversity of E. ruminantium infecting ticks in the study area.
A Multifaceted Deep Generative Adversarial Networks Model for Mobile Malware Detection
Authors: Mazaed Alotaibi Fahad , Fawad
Published: September 2022

Malware’s structural transformation to withstand the detection frameworks encourages hackers to steal the public’s confidential content. Researchers are developing a protective shield against the intrusion of malicious malware in mobile devices. The deep learning-based android malware detection frameworks have ensured public safety; however, their dependency on diverse training samples has constrained their utilization. The handcrafted malware detection mechanisms have achieved remarkable performance, but their computational overheads are a major hurdle in their utilization. In this work, Multifaceted Deep Generative Adversarial Networks Model (MDGAN) has been developed to detect malware in mobile devices. The hybrid GoogleNet and LSTM features of the grayscale and API sequence have been processed in a pixel-by-pixel pattern through conditional GAN for the robust representation of APK files. The generator produces syntactic malicious features for differentiation in the discriminator network. Experimental validation on the combined AndroZoo and Drebin database has shown 96.2% classification accuracy and a 94.7% F-score, which remain superior to the recently reported frameworks.
Multiple Object Tracking in Robotic Applications: Trends and Challenges
Authors: Gad Abdalla , Basmaji Tasnim , Yaghi Maha , Alheeh Huda , Alkhedher Mohammad , Ghazal Mohammed
Published: September 2022

The recent advancement in autonomous robotics is directed toward designing a reliable system that can detect and track multiple objects in the surrounding environment for navigation and guidance purposes. This paper aims to survey the recent development in this area and present the latest trends that tackle the challenges of multiple object tracking, such as heavy occlusion, dynamic background, and illumination changes. Our research includes Multiple Object Tracking (MOT) methods incorporating the multiple inputs that can be perceived from sensors such as cameras and Light Detection and Ranging (LIDAR). In addition, a summary of the tracking techniques, such as data association and occlusion handling, is detailed to define the general framework that the literature employs. We also provide an overview of the metrics and the most common benchmark datasets, including Karlsruhe Institute of Technology and Toyota Technological Institute (KITTI), MOTChallenges, and University at Albany DEtection and TRACking (UA-DETRAC), that are used to train and evaluate the performance of MOT. At the end of this paper, we discuss the results gathered from the articles that introduced the methods. Based on our analysis, deep learning has introduced significant value to the MOT techniques in recent research, resulting in high accuracy while maintaining real-time processing.
A New Method for Evaluating the Homogeneity and Structure of Remolded Loess Samples with the Air Permeability Coefficient
Authors: Hao Zhitao , Li Xi’an , Gao Rongrong , An Mingxiao , Zhang Jing , Wen Feng , Zhou Bingquan , Xue Quan
Published: September 2022

The uniformity of remolded loess samples prepared in the laboratory directly determines the reliability of various test results. While many tests have been designed to reflect the properties of undisturbed loess, there are obvious structural differences between remolded and undisturbed loess. Therefore, it is of great theoretical and practical significance to explore a non-destructive evaluation index of the uniformity and structure of loess samples for indoor geotechnical tests. In this study, the loess from the Malan loess section of the Chanhe River in Xi’an, China, was used as the experimental material to analyze the uniformity of remolded loess samples in terms of the stress distribution, stratification range, and sample variance. Based on the test results, the feasibility of using the air permeability coefficient as an index by which to evaluate the uniformity and structure of loess samples is investigated for the first time. The results demonstrate that when the overall height of the sample is fixed, the higher the designed dry density of the sample and the lower the air permeability of the sample. Moreover, when the designed dry density of the sample is constant, with the increase in the overall height of the sample, the range of the stratified dry density of the sample gradually decreases, as does the sample variance. The more uniform the sample, the greater the air permeability, and under the same conditions, the air permeability of remolded soil is lower than that of undisturbed loess. SEM images reveal that there is a considerable difference between the structures of undisturbed and remolded loess samples. Remolded loess is characterized by the greatly reduced effectiveness of cementation between skeleton particles, which causes its structure to be weaker than that of undisturbed loess. In this paper, a quantitative index of loess structure based on air permeability is proposed, and the test results show that the index can adequately reflect the loess structure. Due to its obvious advantages of non-destructiveness, high efficiency, economy, convenience, and high speed, it has a unique advantage for the evaluation of the uniformity and structure of remolded soil samples.
A Review of Road Surface Anomaly Detection and Classification Systems Based on Vibration-Based Techniques
Authors: Martinez-Ríos Erick Axel , Bustamante-Bello Martin Rogelio , Arce-Sáenz Luis Alejandro
Published: September 2022

Road surfaces suffer from sources of deterioration, such as weather conditions, constant usage, loads, and the age of the infrastructure. These sources of decay generate anomalies that could cause harm to vehicle users and pedestrians and also develop a high cost to repair the irregularities. These drawbacks have motivated the development of systems that automatically detect and classify road anomalies. This study presents a narrative review focused on road surface anomaly detection and classification based on vibration-based techniques. Three methodologies were surveyed: threshold-based methods, feature extraction techniques, and deep learning techniques. Furthermore, datasets, signals, preprocessing steps, and feature extraction techniques are also presented. The results of this review show that road surface anomaly detection and classification performed through vibration-based methods have achieved relatively high performance. However, there are challenges related to the reproduction and heterogeneity of the results that have been reported that are influenced by the limited testing conditions, sample size, and lack of publicly available datasets. Finally, there is potential to standardize the features computed through the time or frequency domains and evaluate and compare the diverse set of settings of time-frequency methods used for feature extraction and signal representation.