bluuebunny/crossref_metadata_2025 huggingface dataset:
Andean rain shadow effect drives phenotypic variation in a widely distributed Austral rodent
Authors: Teta Pablo , de la Sancha Noé U. , D'Elía Guillermo , Patterson Bruce D.
Published: September 2022

Aim

Mountains cover approximately 22% of the planet's terrestrial surface and have dramatic effects on climate and biodiversity. The rain shadow effect is a common feature on mountain ranges worldwide and its effects on ecology and evolution of species, particularly morphology, are incompletely known. Our aim is to identify the correlates that best describe morphological variation along a pronounced rain shadow gradient.

Location

Patagonia and Tierra del Fuego (southern South America), including Valdivian and Magellanic forests and steppes.

Taxa

Shaggy soft‐haired mouse Abrothrix hirta (Order Rodentia, Family Cricetidae).

Methods

We measured 450 skulls of A. hirta from 67 localities between 35°S and 54°S, from the Pacific to the Atlantic coasts. We analysed geographic differences in skull morphology using 17 linear skull measurements. Discriminant function analysis revealed clear evidence for sexual dimorphism; thus, analyses were conducted for the entire dataset, and separately by sex. We implemented regression tree analysis to test the environmental correlates that best describe morphological variation along this gradient.

Results

Skull size variation in shaggy soft‐haired mice does not follow Bergmann's rule; however, latitude was the second node for PC1 of all samples. Regression tree analyses showed that the variables that best explained size for the various datasets were longitude, precipitation of the coldest quarter and temperature seasonality. Longitude appeared in eight of the nine regression tree analyses. We find that organisms attain greater sizes in the western Andes where there is no rain shadow effect, below 500 m of elevation.

Main Conclusions

Morphological variation and size of A. hirta is highly structured along a longitudinal gradient, which mirrors patterns of primary productivity and the Andean rain shadow effect in this region, best described by the “resource rule”. Mountains are a formidable land feature that clearly affects the morphology of species distributed at both sides of them.
“We're in this together”: Attachment insecurities, dyadic coping strategies, and relationship satisfaction in couples involved in medically assisted reproduction
Authors: Péloquin Katherine , Boucher Stéphanie , Benoit Zoé , Jean Mireille , Beauvilliers Laurie , Carranza‐Mamane Belina , Brassard Audrey
Published: September 2022

Attachment is an important predictor of relationship satisfaction and attachment insecurities are a risk factor for couples under stress. Drawing from the Vulnerability–Stress–Adaptation model, we investigated whether dyadic coping strategies (DCS) would explain the links between attachment insecurities and relationship satisfaction in 97 couples involved in medically assisted reproduction (MAR). Path analyses revealed that for women and men, attachment insecurities (anxiety, avoidance) were associated with their own lower relationship satisfaction through their lower use of positive DCS. Attachment avoidance was also associated with participants' own lower relationship satisfaction through their own lower use of negative DCS. Men's attachment avoidance was also related to their partner's lower relationship satisfaction via their own and their partner's lower use of positive DCS. The findings suggest that promoting the use of positive DCS may be important to preserve relationship satisfaction in couples involved in MAR.
Caudal pulmonary artery to vein ratio on radiography can predict pulmonary hypertension in dogs with mitral regurgitation
Authors: Lee Sang‐Kwon , Choi Jihye
Published: September 2022

Pulmonary hypertension (PH) is an important predictor of poor outcomes in dogs with mitral regurgitation (MR). The feasibility of radiography to predict PH in dogs with MR is unknown. This retrospective, observational, and analytic study aimed to identify a radiographic parameter to predict PH in dogs with MR. A total of 302 dogs diagnosed with MR on echocardiography were enrolled. Medical record and radiographic findings such as the size of the main pulmonary artery, left atrium, left ventricle, and right chamber, and cranial and caudal pulmonary arteries and veins were evaluated according to the presence of PH. The diameters of the cranial and caudal pulmonary vessels were compared to the fourth rib and the ninth rib, respectively, and the ratio of the pulmonary artery to the corresponding vein (CdPA/CdPV) was calculated. Pulmonary hypertension was diagnosed in 77 dogs (25.5%) and the prevalence of PH increased with MR grade. The CdPA/CdPV was significantly higher (P < 0.001) in the presence of PH. Multivariate analysis showed that the CdPA/CdPV was the only independent radiographic parameter that had a significant association with PH in dogs with MR (P = 0.028). The cut‐off value of the CdPA/CdPV = 1.10 showed 90.6% specificity and 31.1% sensitivity for detecting PH in dogs with MR. In dogs with MR, PH can be predicted with high specificity when the caudal pulmonary artery is 1.1 times larger than the corresponding vein on radiographs.
Building Scenarios on the Regional Integration in Eurasia along the New Silk Road
Authors: Thees Hannes , Erschbamer Greta
Published: September 2022

Regions are gaining importance as globalization struggles with local sustainable implementation. Thus, regional integration assumes economic development based on transnational cooperation, including regionalization and regionalism. The New Silk Road (NSR) offers a set of policies (including the Belt and Road Initiative) for regional integration that faces challenges in geopolitics and geoeconomics with problems at the local and regional scale, especially along its core corridor, namely, the Eurasian Land Bridge. Therefore, we focus on the NSR implementation by examining the scenarios for future regional integration along the NSR in Eurasia. Using a stepwise scenario building method, including a literature review and qualitative interviews, four scenarios are outlined to explore regional cooperation and the impacts: from (1) withdrawal/reduction of the NSR towards (2) solo efforts by Chinese shareholders, (3) corridorintegration and finally, (4) deep regional integration. This study examines the interface between economic geography and international relations.
ESG Performance of Multinational Companies and Stock Price Crash: Evidence from Korea
Authors: Lee Jeong Hwan , Cho Jin Hyung , Kim Bong Joon
Published: September 2022

Our research focuses on the relationship between the ESG performance of South Korean multinational companies and stock price crash in next year. For our study, we divide samples into three different categories - namely, all companies, multinational companies (MNC) and non-multinational companies(non-MNC). Our major findings are as following. First, we find the negative relationship between the social (S) score of multinational companies and future price crash, indicating that their social performance prevents price crash risk. Second, when individual ESG performance is considered, there exists negative relationship between environmental (E) and social (S) score, and future price crash for multinational companies. Lastly, we find negative relationship between the ESG score and future price crash, which is due to the high environmental (E) and social (S) score of MNCs, which, in turn, raise each respective score for all companies, which has high correlation with their ESG scores. In this research, focusing on features of ESG on price crash in Korean MNCs, we identify the mitigating effect of social (S) factor for the MNC, which is in consistence with previous researches.
Strategic perceptual weighting of acoustic cues for word stress in listeners with cochlear implants, acoustic hearing, or simulated bimodal hearing
Authors: Fleming Justin T. , Winn Matthew B.
Published: September 2022

Perception of word stress is an important aspect of recognizing speech, guiding the listener toward candidate words based on the perceived stress pattern. Cochlear implant (CI) signal processing is likely to disrupt some of the available cues for word stress, particularly vowel quality and pitch contour changes. In this study, we used a cue weighting paradigm to investigate differences in stress cue weighting patterns between participants listening with CIs and those with normal hearing (NH). We found that participants with CIs gave less weight to frequency-based pitch and vowel quality cues than NH listeners but compensated by upweighting vowel duration and intensity cues. Nonetheless, CI listeners' stress judgments were also significantly influenced by vowel quality and pitch, and they modulated their usage of these cues depending on the specific word pair in a manner similar to NH participants. In a series of separate online experiments with NH listeners, we simulated aspects of bimodal hearing by combining low-pass filtered speech with a vocoded signal. In these conditions, participants upweighted pitch and vowel quality cues relative to a fully vocoded control condition, suggesting that bimodal listening holds promise for restoring the stress cue weighting patterns exhibited by listeners with NH.
A coalition to heal—the impact of the cardiac microenvironment
Authors: Tzahor Eldad , Dimmeler Stefanie
Published: September 2022

Heart regenerative medicine has been gradually evolving from a view of the heart as a nonregenerative organ with terminally differentiated cardiac muscle cells. Understanding the biology of the heart during homeostasis and in response to injuries has led to the realization that cellular communication between all cardiac cell types holds great promise for treatments. Indeed, recent studies highlight new disease-reversion concepts in addition to cardiomyocyte renewal, such as matrix- and vascular-targeted therapies, and immunotherapy with a focus on inflammation and fibrosis. In this review, we will discuss the cross-talk within the cardiac microenvironment and how specific therapies aim to target the hostile cardiac milieu under pathological conditions.
Cell-type profiling in salamanders identifies innovations in vertebrate forebrain evolution
Authors: Woych Jamie , Ortega Gurrola Alonso , Deryckere Astrid , Jaeger Eliza C. B. , Gumnit Elias , Merello Gianluca , Gu Jiacheng , Joven Araus Alberto , Leigh Nicholas D. , Yun Maximina , Simon András , Tosches Maria Antonietta
Published: September 2022

The evolution of advanced cognition in vertebrates is associated with two independent innovations in the forebrain: the six-layered neocortex in mammals and the dorsal ventricular ridge (DVR) in sauropsids (reptiles and birds). How these innovations arose in vertebrate ancestors remains unclear. To reconstruct forebrain evolution in tetrapods, we built a cell-type atlas of the telencephalon of the salamander
Pleurodeles waltl
. Our molecular, developmental, and connectivity data indicate that parts of the sauropsid DVR trace back to tetrapod ancestors. By contrast, the salamander dorsal pallium is devoid of cellular and molecular characteristics of the mammalian neocortex yet shares similarities with the entorhinal cortex and subiculum. Our findings chart the series of innovations that resulted in the emergence of the mammalian six-layered neocortex and the sauropsid DVR.
Single-cell Stereo-seq reveals induced progenitor cells involved in axolotl brain regeneration
Authors: Wei Xiaoyu , Fu Sulei , Li Hanbo , Liu Yang , Wang Shuai , Feng Weimin , Yang Yunzhi , Liu Xiawei , Zeng Yan-Yun , Cheng Mengnan , Lai Yiwei , Qiu Xiaojie , Wu Liang , Zhang Nannan , Jiang Yujia , Xu Jiangshan , Su Xiaoshan , Peng Cheng , Han Lei , Lou Wilson Pak-Kin , Liu Chuanyu , Yuan Yue , Ma Kailong , Yang Tao , Pan Xiangyu , Gao Shang , Chen Ao , Esteban Miguel A. , Yang Huanming , Wang Jian , Fan Guangyi , Liu Longqi , Chen Liang , Xu Xun , Fei Ji-Feng , Gu Ying
Published: September 2022

The molecular mechanism underlying brain regeneration in vertebrates remains elusive. We performed spatial enhanced resolution omics sequencing (Stereo-seq) to capture spatially resolved single-cell transcriptomes of axolotl telencephalon sections during development and regeneration. Annotated cell types exhibited distinct spatial distribution, molecular features, and functions. We identified an injury-induced ependymoglial cell cluster at the wound site as a progenitor cell population for the potential replenishment of lost neurons, through a cell state transition process resembling neurogenesis during development. Transcriptome comparisons indicated that these induced cells may originate from local resident ependymoglial cells. We further uncovered spatially defined neurons at the lesion site that may regress to an immature neuron–like state. Our work establishes spatial transcriptome profiles of an anamniote tetrapod brain and decodes potential neurogenesis from ependymoglial cells for development and regeneration, thus providing mechanistic insights into vertebrate brain regeneration.
Boosting cognition with a hormone
Authors: Hoffmann Hanne M.
Published: September 2022

A hormone enhances cognition in mouse models of Alzheimer’s disease and Down syndrome
Complete Genome Sequence of Campylobacter coli Strain P4581, a Hybrid Carrying Campylobacter jejuni Genomic Content, Isolated from Rhesus Monkey, Macaca mulatta
Authors: Kim Sung Guk , Summage-West Christine V. , Sims Lillie M. , Wu Leihong , Kim JaeHyun , Nho Seongwon , Foley Steven L.
Published: September 2022

Campylobacter coli
is a leading bacterial cause of human gastroenteritis. We reported the circularized 1.8-Mbp complete genome of MLST type 1055
C. coli
strain P4581 isolated from a rhesus monkey,
Macaca mulatta
, hybridizing Illumina short- and Nanopore long-reads.
Genomic Characterization of Antimicrobial-Resistant Salmonella enterica in Duck, Chicken, and Pig Farms and Retail Markets in Eastern China
Authors: Tang Biao , Elbediwi Mohammed , Nambiar Reshma B. , Yang Hua , Lin Jiahui , Yue Min
Published: September 2022

Public health is a significant concern in China, and the foodborne pathogen
Salmonella
, which is spread via the animal-borne food chain, plays an important role in the overall disease burden in China annually. The development of advanced sequencing technologies has introduced a new way of understanding emerging pathogens.
Effect of oats and oat ß-glucan on glycemic control in diabetes: a systematic review and meta-analysis of randomized controlled trials
Authors: Chen Victoria , Zurbau Andreea , Ahmed Amna , Khan Tauseef A , Au-Yeung Fei , Chiavaroli Laura , Blanco Mejia Sonia , Leiter Lawrence A , Jenkins David J A , Kendall Cyril W C , Sievenpiper John L
Published: September 2022

Introduction

Current health claims recognize the ability of oat ß-glucan to lower blood cholesterol; however, its ability to improve glycemic control is less certain. We undertook a systematic review and meta-analysis of randomized controlled trials (RCTs) to update the evidence on the effect of oats and oat ß-glucan on glycemic control in individuals with diabetes.

Research design and methods

MEDLINE, EMBASE and Cochrane were searched (June 2021) for RCTs of ≥2 weeks investigating the effect of oat ß-glucan on glycemic control in diabetes. The outcomes were hemoglobin A1c (HbA1c), fasting glucose, 2-hour postprandial glucose (2h-PG) from a 75 g oral glucose tolerance test, homeostatic model assessment of insulin resistance (HOMA-IR) and fasting insulin. Independent reviewers extracted the data and assessed the risk of bias. Data were pooled using the generic inverse variance method. Heterogeneity was assessed (Cochran Q) and quantified (I2). Pooled estimates were expressed as mean difference (MD) with 95% CI. The certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development and Evaluations approach.

Results

Eight trial comparisons (n=407) met the eligibility criteria. All trials were in adults with type 2 diabetes who were predominantly middle-aged, overweight and treated by antihyperglycemic medications or insulin. A median dose of 3.25 g of oat ß-glucan for a median duration of 4.5 weeks improved HbA1c (MD, −0.47% (95% CI −0.80 to −0.13), pMD=0.006), fasting glucose (−0.75 mmol/L (−1.20 to –0.31), pMD<0.001), 2h-PG (−0.42 mmol/L (−0.70 to –0.14), pMD=0.003) and HOMA-IR (−0.88 (−1.55 to –0.20), pMD=0.011). There was a non-significant reduction in fasting insulin (−4.30 pmol/L (−11.96 to 3.35), pMD=0.271). The certainty of evidence was high for fasting glucose, moderate for HOMA-IR and fasting insulin (downgraded for imprecision), and low for HbA1c and 2h-PG (downgraded for imprecision and inconsistency).

Conclusions

Consumption of oats and oat ß-glucan results in generally small improvements in established markers of fasting and postprandial glycemic control beyond concurrent therapy in adults with type 2 diabetes. The current evidence provides a very good indication for reductions in fasting glucose and less of an indication for reductions in HbA1c, 2h-PG, fasting insulin and HOMA-IR in this population.

Trial registration number

NCT04631913.
Commercial business and partnership aspects of general practice: the learning needs of First5 general practitioners in NHS Scotland–a qualitative study
Authors: Lindemann Roberta F , Robson Gordon , Cunningham David Edward
Published: September 2022

Objectives

To identify the learning needs of recently qualified general practitioners (GPs) (First5) in National Health Service (NHS) Scotland concerning GP partnership and the commercial business aspects of general practice. It aimed to identify learning opportunities during General Practice Specialty Training and the first 5 years of work, and to explore their suggestions of additional resources that would improve their sense of preparedness for partnership. A secondary aim was to explore what influenced their current choice of employment model and place of work.

Design

Qualitative research study using grounded theory methods. Recruitment was stratified to include First5 GPs from a range of NHS boards in Scotland including remote and rural areas. Participants were interviewed in small focus groups or individual interviews in person, or over the telephone depending on their preference. Interviews were audio-recorded and transcribed. Transcriptions were coded and codes developed into themes using Charmazian grounded theory methods. Data saturation was achieved and verified by the researchers.

Setting

General practice in NHS Scotland. Participant GPs, within the first 5 years of completion of General Practice Specialty Training, who were working in NHS Scotland.

Results

Twenty-seven recently qualified GPs participated in the study. Three main themes were constructed: preparedness for partnership from experiential learning in General Practice Specialty Training; perceived commercial business learning needs and preferred learning styles (with learning needs arranged into five topic areas); considerations that inform decision-making about choice of employment model and of practice. Factors that influenced the decision to enter into specific employment models were identified.

Conclusion

Lengthening the time spent in specialty training may help GP trainees gain more knowledge, skills and confidence about the commercial business aspects of general practice and of GP partnership.
Women’s priorities towards ovarian cancer testing: a best–worst scaling study
Authors: Hall Rebekah , Medina-Lara Antonieta , Hamilton Willie , Spencer Anne
Published: September 2022

Objective

To investigate the importance of key characteristics relating to diagnostic testing for ovarian cancer and to understand how previous test experience influences priorities.

Design

Case 1 best–worst scaling embedded in an online survey.

Setting

Primary care diagnostic testing in England and Wales.

Participants

150 women with ovaries over 40 years old living in England and Wales.

Methods

We used best–worst scaling, a preference-based survey method, to elicit the relative importance of 25 characteristics relating to ovarian cancer testing following a systematic review. Responses were modelled using conditional logit regression. Subgroup analysis investigated variations based on testing history.

Main outcome measures

Relative importance scores.

Results

‘Chance of dying from ovarian cancer’ (0.380, 95% CI 0.26 to 0.49) was the most important factor to respondents, closely followed by ‘test sensitivity’ (0.308, 95% CI 0.21 to 0.40). In contrast, ‘time away from usual activities’ (−0.244, 95% CI −0.33 to −0.15) and ‘gender of healthcare provider’ (−0.243, 95% CI −0.35 to −0.14) were least important to respondents overall. Women who had previously undergone testing placed higher importance on certain characteristics including ‘openness of healthcare providers’ and ‘chance of diagnosing another condition’ at the expense of reduced emphasis on characteristics such as ‘pain and discomfort’ and ‘time away from usual activities’.

Conclusions

The results clearly demonstrated items at the extreme, which were most and least important to women considering ovarian cancer testing. Differences in priorities by testing history demonstrate an experience effect, whereby preferences adapt over time based on evidence and experience. Acknowledging these differences helps to identify underlying barriers and facilitators for women with no test experience as well as shortcomings of current service based on women with experience.
Rationale and design for efficacy and safety evaluation of Bone-Anchored Maxillary Protraction (BAMP) for patients with unilateral cleft lip and palate with skeletal anterior crossbite: a single-arm, open-label, non-randomised prospective study protocol
Authors: Shimada Eriya , Kanetaka Hiroyasu , Yamauchi Kensuke , Takahashi Tetsu , Nochioka Kotaro , Igarashi Kaoru
Published: September 2022

Introduction

Bone-anchored maxillary protraction (BAMP) was devised recently as a method of direct maxillary protraction using anchor plates implanted in the maxilla and mandible without involving the teeth. Although several reports have described orthognathic effects of BAMP on patients with cleft lip and palate (CLP) with skeletal crossbite, none has described a study of Japanese patients with CLP or of BAMP treatment effects on speech in patients with CLP. This study, by performing BAMP treatment, and by evaluating speech function and skeletal and soft tissues, is intended to clarify BAMP efficacy and safety for patients with unilateral CLP (UCLP) who have skeletal crossbite.

Methods and analysis

This single-arm, open-label, non-randomised prospective study examines 20 patients with UCLP with skeletal crossbite (Wits appraisal ≤−5.0 mm). These 10–15 year-old participants had already undergone cheiloplasty, palatoplasty and bone grafting. The anchor plates are implanted in the zygomatic process in the maxilla and in the anterior part of the mandible. Two weeks after anchor plate implantation, maxillary protraction is started using elastics. Protraction is performed at 150 g per side at the start of protraction, 200 g per side from 1 month after the start of protraction and 250 g per side from 3 months after the start of protraction. The treatment period will be approximately 1½ years. Pretreatment and post-treatment, cephalometric analysis, speech evaluation, nasopharyngeal closure function evaluation and facial soft tissue evaluation will be performed to ascertain the effects of BAMP on patients with UCLP.

Ethics and dissemination

Ethical approval for this study has been received from Tohoku Certificated Review Board of Tohoku University, Japan, CRB2200003. The approval number is 2021-34-2. The results of this research shall be presented at domestic and international academic conferences, and be published to peer-reviewed journals.

Trial registration number

jRCTs022210007.
Predicting arrhythmias in primary prevention heart failure patients: picking up the fragments
Authors: Engstrom Nathan , Letson Hayley Louise , Ng Kevin , Dobson Geoffrey Phillip
Published: September 2022

Identifying patients with high-risk heart failure (HF) who would benefit from an implantable cardioverter-defibrillator (ICD) remains controversial. A potential marker for arrhythmic sudden death is fragmented QRS (fQRS). fQRS is the notching and slurring of the QRS complex in a 12-lead ECG and it indicates abnormal ventricular depolarisation and myocardial scarring and fibrosis. However, before fQRS complex can be included into selection criteria for ICD therapy, more complete reporting is required on their association with malignant arrhythmias, left ventricular remodelling and myocardial scarring/fibrosis in patients with HF. The molecular basis of the fQRS-arrhythmia-fibrosis connection in HF also needs to be explored. It is not widely appreciated that changes in the QRS complex and phases 0 and 1 of the ventricular action potential occurbefore contractionand predetermine Ca2+releaseduring contractionand later Ca2+sparks. It is currently not known whether the different zig-zag patterns of the QRS are associated with aberrant Ca2+cycling and arrhythmogenic sparks in patients with HF.
Deep Learning-Enabled Road Segmentation and Edge-Centerline Extraction from High-Resolution Remote Sensing Images
Authors: Patel Miral Jerambhai , Kothari Ashish M.
Published: September 2022

Nowadays, precise and up-to-date maps of road are of great significance in an extensive series of applications. However, it automatically extracts the road surfaces from high-resolution remote sensed images which will remain as a demanding issue owing to the occlusion of buildings, trees, and intricate backgrounds. In order to address these issues, a robust Gradient Descent Sea Lion Optimization-based U-Net (GDSLO-based U-Net) is developed in this research work for road outward extraction from High Resolution (HR) sensing images. The developed GDSLO algorithm is newly devised by the incorporation of Stochastic Gradient Descent (SGD) and Sea Lion Optimization Algorithm (SLnO) algorithm. Input image is pre-processed and U-Net is employed in road segmentation phase for extracting the road surfaces. Meanwhile, training data of U-Net has to be done by using the GDSLO optimization algorithm. Once road segmentation is done, road edge detection and road centerline detection is performed using Fully Convolutional Network (FCN). However, the developed GDSLO-based U-Net method achieved superior performance by containing the estimation criteria, including precision, recall, and F1-measure through highest rate of 0.887, 0.930, and 0.809, respectively.
Autonomous Traffic-Aware Scheduling for Industrial Wireless Sensor-Actuator Networks
Authors: Cheng Xia , Sha Mo
Published: September 2022

Recent years have witnessed rapid adoption of low-power Wireless Sensor-Actuator Networks (WSANs) in process industries. To meet the critical demand for reliable and real-time communication in harsh industrial environments, the industrial WSAN standards make a set of specific design choices, such as employing the
Time-Slotted Channel Hopping (TSCH)
technique. Such design choices distinguish industrial WSANs from traditional Wireless Sensor Networks, which were designed for best-effort services. Recently, there has been increasing interest in developing new methods to enable autonomous transmission scheduling for industrial WSANs that run TSCH and the Routing Protocol for Low-Power and Lossy Networks (RPL). Our study shows that the current approaches fail to consider the traffic loads of different devices when assigning time slots and channels, which significantly compromises network performance when facing high data rates. In this article, we introduce a novel Autonomous Traffic-Aware transmission scheduling method for industrial WSANs. The device that runs ATRIA can detect its traffic load based on its local routing information and then schedule its transmissions accordingly without the need to exchange information with neighboring devices. Experimental results show that ATRIA provides significantly higher end-to-end network reliability and lower end-to-end latency without introducing additional overhead compared with a state-of-the-art baseline.
Effect of Forest-Based Health and Wellness on Sleep Quality of Middle-Aged People
Authors: Quan Wei , Yu Shaona , Xia Lizhi , Ying Miaomiao
Published: September 2022

To explore the effect of forest-based health and wellness experiences on sleep quality for middle-aged people, we observed 12 healthy volunteers, aged 35–39 years, for three days and two nights during “forest bathing.” Huawei honor-4 bracelets were used to continuously monitor their exercise and sleep patterns. After the forest-based health and wellness experience, the average sleep score of the volunteers increased by 6 points, and the length of night sleep increased by 1.6 hours. The proportion of deep sleep increased by 3%, the proportion of rapid eye movement increased by 1%, and the proportion of shallow sleep decreased by 4%. Overall, sleep quality was improved; however, this was not sustained. The effects of forest-based health and wellness experience on the sleep indicators showed both individual and gender differences; sleep quality generally improved better for females than males.
Unique Fixed Point Results and Its Applications in Complex-Valued Fuzzy
b
-Metric Spaces
Authors: Humaira  , Sarwar Muhammad , Mlaiki Nabil
Published: September 2022

The goal of this paper is to extend the concept of complex-valued fuzzy metric space to complex-valued fuzzy

b

-metric spaces and to discuss various existence results for fixed points to ensure their existence and uniqueness. To demonstrate the viability of the proposed strategies, a nontrivial example is used. Finally, applications to integral equations and initial value problems in mechanical engineering are discussed to demonstrate the superiority of the obtained results.
Evidence and Potential Mechanisms of Traditional Chinese Medicine for the Adjuvant Treatment of Coronary Heart Disease in Patients with Diabetes Mellitus: A Systematic Review and Meta-Analysis with Trial Sequential Analysis
Authors: Wei Yu , Ding Qi-You , Yeung Chak , Huang Yi-shan , Zhang Bo-xun , Zhang Li-li , Miao Run-Yu , Di Sha , Zhao Lin-Hua , Tong Xiao-Lin
Published: September 2022

Traditional Chinese medicine (TCM) has long been used to treat diabetes mellitus and angina. It has also gained widespread clinical applications in China as a common adjuvant treatment. Although there is high-quality evidence that TCM is effective in regulating glucose and lipid metabolism, the cardiovascular protective effect of TCM in the treatment of diabetes mellitus has not been fully elucidated, especially in patients with both diabetes mellitus and coronary heart disease (CHD). We systematically assessed the efficacy and safety of TCM for the adjuvant treatment of patients with CHD and diabetes mellitus and examined the pharmacological effects and potential mechanisms of TCM medication/herbs on diabetes mellitus with CHD. We found that TCM could improve the control effect of conventional treatment on cardiac function, hemorheology, blood glucose, blood lipid, and inflammation, thus reducing the frequency of angina and the incidence of cardiovascular events and all-cause mortality. These findings indicate that TCM may be used as a complementary approach for patients with diabetes mellitus and CHD. Nevertheless, more rigorously designed randomized controlled trials and long-term evaluations are needed to support these findings.
A New Approach for Target Capability Assessment and Selection in Complex Situations
Authors: Wang Yuan , Liang Jun , Wang Shicheng
Published: September 2022

In modern information warfare, medium and long-range weapons with high strike precision are often used to ensure stable, accurate, and ruthless conditions. However, the target system often has multiple target units and which target units to specifically attack becomes the primary issue. This study constructs a target combat system network based on the complex network theory and maximum entropy principle, establishes a key target selection model based on this network, and then determines the use of medium and long-range weapons to strike the key target unit in the enemy combat system network. The key target selection model consists of four parts. The first is a value model of the node itself constructed by comprehensively considering the relationship between the target and the war, the importance of the target in the system, and the threat of the target. The second is a node network value model based on the potential field theory. The third is to construct a cascading failure model of the target system through the definition of triples (results of strike action, target unit status, and failure influence relationship between target units). Fourth, with the optimal cost-effectiveness ratio as the objective function, the evaluation criterion function model is established. Case scenarios and simulation experiments illustrate the rationality and effectiveness of the method which can provide effective solutions for commanders to select key targets.
The Effects of Vestibular Rehabilitation on Poststroke Fatigue: A Randomized Controlled Trial Study
Authors: Ghaffari Amin , Asadi Bahador , Zareian Armin , Akbarfahimi Malahat , Raissi Gholam Reza , Fathali Lavasani Fahimeh
Published: September 2022

Background. A major complication caused by stroke is poststroke fatigue (PSF), and by causing limitations in doing activities of daily living (ADL), it can lower the quality of life. Objective. The present study is an attempt to examine the effects of vestibular rehabilitation on BADL (Basic Activities of Daily Living), fatigue, depression, and Lawton Instrumental Activities of Daily Living (IADL) in patients with stroke. Method. Patients with a history of stroke took part voluntarily in a single-blind clinical trial. The participants were allocated to control and experimental groups randomly. The experimental group attended 24 sessions of vestibular rehabilitation protocol, while the control group received the standard rehabilitation (including three sessions per week each for around 60 min). To measure fatigue, the Fatigue Impact Scale (FIS) and the Fatigue Assessment Scale (FAS) were used. Depression, BADL, and IADL were measured using the Beck Depression Inventory-II (BDI-II), Barthel Index (BI), and Lawton Instrumental Activities of Daily Living, respectively. All changes were measured from the baseline after the intervention. Results. Significant improvement was found in the experimental group compared to the control group (

p
<
0.05

) in FIS (physical, cognition, and social subscales), FAS, BDI-II, BADL, and IADL. Moreover, the results showed small to medium and large effect sizes for the physical subscale of FIS and FAS scores based on Cohen’s

d

, respectively; however, no significant difference was found in terms of cognition and social subscales of FIS, BDI-II, BADL, and IADL scores. Conclusion. It is possible to improve fatigue, depression, and independence in BADL and IADL using vestibular rehabilitation. Thus, it is an effective intervention in case of stroke, which is also well tolerated.
Properties in Stage-Structured Population Models with Deterministic and Stochastic Resource Growth
Authors: Aye Tin Nwe , Carlsson Linus
Published: September 2022

Modelling population dynamics in ecological systems reveals properties that are difficult to find by empirical means, such as the probability that a population will go extinct when it is exposed to harvesting. To study these properties, we use an aquatic ecological system containing one fish species and an underlying resource as our models. In particular, we study a class of stage-structured population systems with and without starvation. In these models, we study the resilience, the recovery potential, and the probability of extinction and show how these properties are affected by different harvesting rates, both in a deterministic and stochastic setting. In the stochastic setting, we develop methods for deriving estimates of these properties. We estimate the expected outcome of emergent population properties in our models, as well as measures of dispersion. In particular, two different approaches for estimating the probability of extinction are developed. We also construct a method to determine the recovery potential of a species that is introduced in a virgin environment.
Analysis of Vegetable Waste Pollution Risk and Resource Potential Based on Geographical Information System and Remote Sensing
Authors: Li Pingheng
Published: September 2022

Land resources are an important foundation for human survival and development. In recent years, land resources have experienced rapid industrialization and urbanization. With the expansion of urban construction land and the sharp decline of natural and agricultural landscapes, ecological and social problems have gradually surfaced. Based on the intuitive interpretation of LandsatTM/ETM +/OLI image data from 2016 to 2020, this work created an annual land use reference database. The use of resources and the recovery of nutrients from vegetable waste are necessary measures to achieve sustainable and environmentally friendly agriculture. Collecting and analyzing data from the literature are to determine the risk of vegetable waste pollution and the possibility of resource utilization. The amount of vegetable waste produced and the total amount of nitrogen, total phosphorus, and total potassium pollution in the study area are estimated, and ArcGIS is used to characterize TN (total nitrogen) and TP (total phosphorus). The spatial distribution of TK (total potassium) pollution intensity and pollution risk comprehensive index determines the key areas of vegetable waste nonpoint source pollution control in the region and compares the resource utilization potential of vegetable waste based on the demand for fertilizer. This paper combines the research of the subject; takes cultivated land as the research object; clarifies the main pollutants, contaminated area, content, and distribution of cultivated land; uses factor analysis method to conduct a preliminary study on the causes of heavy metal contaminated soil in the study area; and adopts a source-sink balance model, analyze the cumulative characteristics of soil pollution. Based on geographical information system (GIS) and remote sensing technology, this paper investigates the risk assessment of vegetable waste pollution and discusses the analysis of resource potential.
Concept Tree-Based Event Matching Algorithm in Publish/Subscribe Systems
Authors: Zhang Zhi Yuan , Wang Yu Jie , Huang Xue Hu , Yung Kai Leung
Published: September 2022

Semantic-based publish/subscribe system has attracted a lot of attention in recent years due to its powerful description ability in message dissemination scenarios. As a key part of semantic-based publish/subscribe systems, event matching needs to understand the semantic meaning of subscriptions, especially the hierarchy of concepts. However, existing event matching algorithms are severely affected by the complexity of concept hierarchy trees, some even cannot run due to high memory occupation. This article proposes an event matching algorithm called CTPS (concept tree-based publish/subscribe system) to address it; specifically, we build subscription indexes on concept hierarchy trees for the first time, employ bit arrays to avoid unnecessary matches, and use faster bit operations to accelerate the matching speed. Experiments show that, compared with previous algorithms, CTPS has less memory occupation and shorter event matching time, and its performance is not sensitive to the height of the concept hierarchy tree.
Real-Time Recognition Method of Video Basketball Technical Action Based on Target Detection Algorithm
Authors: Zhu Daqing
Published: September 2022

Aiming at the problems of poor real-time recognition efficiency and low recognition accuracy of video basketball technical movements, a real-time recognition method of video basketball technical movements based on the target detection algorithm is proposed. This study firstly collects video basketball technical action images and detects their edge contour features. Through machine vision block template matching processing, the video basketball technology motion capture results are output. Then, according to the target probability of video basketball technical action detection, the basketball video sample set is estimated and constructed, the sequence of basketball video is obtained, and the basketball video target detection algorithm is designed. Finally, the similarity between the two vectors of video basketball technical action targets is measured to realize real-time recognition of video basketball technical actions. The experimental results show that the method in this study has high accuracy in extracting feature points of basketball video image decomposition, the real-time recognition time of video basketball technical action is up to 4s, and the recognition error of basketball rotation projection technology is small, which is close to the actual value.
Exploring the Flora of South Sulawesi, Forest Vegetation, and Karst Areas as Bundle Dyeing on Silk Fabrics
Authors: Nuraeni Sitti , Nasri Nasri , Hamzah Andi Siady , Wahyudi Wahyudi
Published: September 2022

The development of dyeing frm natural substances for silk fabrics has been rapidly growing in recent years. This study aimed to explore the plant species prodsucing unique dyes and patterns on silk fabrics. The flowers and leaves of some plant species found at the research sites were assayed for their color and shape expression on the fabrics. The dyeing technique applied was the bundle dyeing or ecoprinting technique on the fabric’s surface with mordant alum and myrobalan. We obtained 297 plants consisting of 95 families and 181 genera. The plant species producing colors were trees (48.4%), shrubs (30.5%), and herbs, vines, ferns, and lycopods (21.1%). The plant species samples obtained were 213 (71.7%) producing color and 84 (28.3%) species not expressing color. The leaves and flowers producing colors and patterns on the fabrics suitable for bundle dyeing were 126 species and 19 species, respectively. The leaves produce colors without shape patterns; thus, they have potential roles as dyes for the dipping technique.
Early Warning of Financial and Business Management Based on Three Improved BP-NN Algorithms
Authors: Zhang Gengquan , Hu Pan
Published: September 2022

To address the issue of early warning in financial management and economics, this article presents a study based on our improved BP-NN algorithms. This approach improves the benefits of early warning systems in financial and business management based on BP neural network algorithm technology and improves BP neural network algorithms. Based on the analysis and calculation of the results, the inconsistency of the financial model industry estimates is 66.3% and 72.7% for CT and non-CT companies. The actual discrimination rate of the hedge fund model is 81.3% and 83.9% for ST and ST companies, respectively. Compared with the net structure of the financial index, the general guidance model improved the ability of ST companies and non-ST companies to withstand risks by 14.27% and 8.76%, respectively. It can be concluded that the integration of nonfinancial indicators into the estimation model can improve the accuracy of the estimation of the model. Experiments have shown that research based on our improved BP-NN algorithms can not only eliminate BP network inadequacies but also improve the accuracy of early warning in financial markets.
Default Risk Prediction of Enterprises Based on Convolutional Neural Network in the Age of Big Data: Analysis from the Viewpoint of Different Balance Ratios
Authors: Li Zhe , Jiang Zhenhao , Pan Xianyou
Published: September 2022

In the age of big data, machine learning models are globally used to execute default risk prediction. Imbalanced datasets and redundant features are two main problems that can reduce the performance of machine learning models. To address these issues, this study conducts an analysis from the viewpoint of different balance ratios as well as the selection order of feature selection. Accordingly, we first use data rebalancing and feature selection to obtain 32 derived datasets with varying ratios of balance and feature combinations for each dataset. Second, we propose a comprehensive metric model based on multimachine learning algorithms (CMM‐MLA) to select the best‐derived dataset with the optimal balance ratio and feature combination. Finally, the convolutional neural network (CNN) is trained on the selected derived dataset to evaluate the performance of our approach in terms of type‐II error, accuracy, G‐mean, and AUC. There are two contributions in this study. First, the optimal balance ratio is found through the classification accuracy, which changes the deficiency of the existing research that samples are imbalanced or the balance ratio is 1 : 1 and ensures the accuracy of the classification model. Second, a comprehensive metric model based on the machine learning algorithm is proposed, which can simultaneously find the best balance ratio and the optimal feature selection. The experimental results show that our method can noticeably improve the performance of CNN, and CNN outperforms the other four commonly used machine learning models in the task of default risk prediction on four benchmark datasets.
A Double Random Matrix Design Model for Fractal Art Patterns Based on Visual Characteristics
Authors: Xing Qiang , Chen Jie , Liu Jieyu , Song Baifeng
Published: September 2022

This paper adopts the method of visual characteristics of the double random matrix to conduct in-depth research and analysis on the design of fractal art patterns. For the practical application needs in fractal graphic design, a method is proposed to automatically extract the core base pattern based on fractal graphic content and generate a four-sided continuous pattern. The method first uses the Canny operator for edge detection to analyze the area of the main pattern. Then, it uses a grayscale cogeneration matrix to extract and analyze the graphic texture features, based on which the best splicing method is selected to splice the extracted pattern, and then, it achieves two splicing methods of flat row and staggered four-sided continuous pattern. The method has good practicality with low complexity and high versatility under the premise of ensuring the beauty of the generated four-sided continuous pattern. It can assist designers to design patterns, improve efficiency, and save design costs. In this paper, we improve the existing image segmentation methods, adopt two segmentation methods, namely quadratic tree segmentation and HV segmentation, propose a new local codebook selection strategy, and study the degree of self-adaptation of different methods to images in terms of segmentation methods and local codebook selection strategies. It makes the network unable to train efficiently on long text prediction problems. Finally, the improved algorithm of this paper is tested on the standard and living image libraries, and the experimental results show that the use of local codebooks makes the image coding speed significantly improved compared with the fixed fractal. In the face of the image to be retrieved, it is only necessary to perform the coding operation to obtain the fractal code to perform similarity matching, which can meet the requirement of real-time retrieval. Applying the improved distance formula, the search accuracy obtained on the test gallery is significantly better than that of the grayscale histogram algorithm.