bluuebunny/crossref_metadata_2025_split huggingface dataset:
Virtual reality intervention effects on future self-continuity and delayed reward preference in substance use disorder recovery: pilot study results
Authors: Shen Yitong I , Nelson Andrew J , Oberlin Brandon Gregg 
Published: July 2022

Abstract
Sustained remission from substance use disorder (SUD) is challenged by high relapse rates, which provides opportunities for novel clinical interventions. Immersive virtual reality (VR) permits delivering synthetic experiences that feel real and actualizes otherwise impossible scenarios for therapeutic benefit. We report on the feasibility of an immersive VR intervention designed to increase valuation of the future by enhancing future self-continuity and leveraging future self-discrepancy with personalized future selves as SUD recovery support. Twenty-one adults in early SUD recovery (< 1 year) interacted with versions of themselves age-progressed fifteen years from two different behavioral trajectories: an SUD Future Self and a Recovery Future Self. The future selves’ interactive monologs include personalized details and voice for a lifelike interaction within a time travel vignette. Before and following the intervention, participants rated future self-continuity and performed delay discounting. Following the intervention, daily images of the Recovery Future Self were sent to participants’ smartphones for thirty days. The VR intervention generated no adverse events, was well tolerated (presence, liking, and comfort), significantly increased future self-continuity and delayed reward preference (doubling delay tolerance), and reduced craving, ps < .05. Thirty days later, n = 18 remained abstinent; importantly, increased future self-similarity persisted. Abstainers’ future self-similarity increased following VR. All individual participants showing increased future self-similarity post-VR remained abstinent, and all participants who relapsed showed either reduced or zero effect on future self-similarity. Post-intervention semi-structured interviews revealed emotional engagement with the experience. VR simulation of imagined realities reifies novel clinical interventions that are practicable and personalized. The current study demonstrates an implementation readily applied in the clinic and shows promise for facilitating SUD recovery. Creative collaboration between researchers, clinicians, and VR developers has great potential to revolutionize mental health interventions and expand the range of tools for clinicians targeting SUD and other disorders.
Characteristics of rice straw decomposition and succession in the bacterial community during decomposition in paddy field in Southeast China
Authors: Wang Xiya , He Ping , Xu Xinpeng , Qiu Shaojun , Zhao Shicheng 
Published: July 2022

Abstract
Crop straw decomposition in the soil is a complex biochemical process. Microorganisms are the main drivers of straw decomposition, and external environmental conditions and straw composition are known to regulate straw decomposition by influencing the microbial community composition. However, the characteristics of rice straw decomposition and changes in microbial community structure during the straw decomposition in the double-rice system are still unclear. A 2-year straw bag decomposition experiment was used to study the change in nutrient release, enzyme activity, and bacterial community composition during rice straw decomposition in the double-rice system in Southeast China. After burial in soil, the cumulative dry matter loss rates of rice straw were 38.9%, 72.6%, and 82.7% after 2, 12, and 24 months, respectively. The change in the release rate of straw nitrogen and phosphorus was similar to the dry matter loss, but 93.5% of straw potassium was released after 1st month. Bacterial abundance and community diversity in straw increased rapidly, reaching peaks after 7 and 12 months, respectively. Straw extracellular enzyme activities are the highest in the first 2 months, and then gradually decrease over time. Redundancy analysis showed that rice straw decomposition was mainly influenced by straw C/N and K. The dominating bacterial communities at the early stage were classes Bacilli and Flavobacteriia. However, they were succeeded by classes Acidobacteria, Anaerolineae, Deltaproteobacteria, Saccharibacteria, and Sphingobacteriia at the later stage of decomposition. In conclusion, rice straw decomposition was strongly influenced by straw composition, and straw decomposition was dominated by copiotrophic bacteria in the early stages and evolved to be dominated by oligotrophic bacteria in the later stages with the depletion of easily decomposable components.
Phylogeographical analysis on the alpine endemic plant Meconopsis punicea (Papaveraceae) based on chloroplast and nuclear genes
Authors: Ou Zhi , Xiong Jian , Jiang Yuanqi , Dai Yongdong , Qu Yan 
Published: July 2022

Abstract
Meconopsis punicea (Papaveraceae) is only distributed in the alpine areas of the Qinghai Plateau (QHP) and Hengduan Mountains (HDM) in China. As an important ornamental flower and traditional Tibetan medicine, in addition to habitat loss, its higher economic value drives over-exploitation of this resource, which has accelerated the reduction of its distribution. How to make its protection strategy is still unfounded as unclear genetic diversity characteristics of M. punicea. In this study, we analyzed the genetic diversity and phylogeographic structures of M. punicea representing 11 populations 106 individuals using 4-locus dataset (matK, ndhF, rbcL and rpb2, a total of 2576 bp). A total of 76 sequence types were identified (Hd = 0.987, Pi = 0.00447). Six phylogenetic clades were recognized, and 3 clades were restricted to unique geographic distribution (Clade A corresponded to population SD, B to LT, and C to BL). The zoige area was referred as the differentiation center and a glacial refuge of M. punicea. M. punicea most likely originated from the southern HDM in the early Miocene (~ 22 Myr). Two dispersal routes were suggested and the ecological and geographical difference were revealed as the main driving forces for species differentiation of M. punicea. The suitable distribution area was predicted about 158,000 km2 mainly in Sichuan, Gansu and Qinghai. Our current results provide much clear and detailed understanding for the diversity and geographical spatial distribution of the endemic alpine plant M. punicea. It will also be able to provide theoretical guidance for formulating the urgently needed protection strategies of M. punicea.
Pleotropic potential of quorum sensing mediated N-acyl homoserine lactones (AHLs) at the LasR and RhlR receptors of Pseudomonas aeruginosa
Authors: Rex Devasahayam Arokia Balaya , Saptami Kanekar , Chandrasekaran Jaikanth , Rekha Punchappady Devasya 
Published: July 2022

Abstract
Pseudomonas aeruginosa is an opportunistic pathogen, having complicated quorum sensing (QS) system utilizing multiple signals and receptors to coordinate virulence and pathogenicity. N-acyl-homoserine-lactones (AHLs) are the most common autoinducers responsible for regulation of QS mediated virulence gene expression. There are two interrelated QS systems in P. aeruginosa namely, LasI/R and RhlI/R, which are regulated by 3-oxo-C12-HSL and C4-HSL respectively and well explored in host-associated pathogenesis. The LasR and RhlR binding specificity to cognate or non-cognate HSLs influences the QS mediated responses. In the current study, using computational approaches we aimed to consolidate the interaction of different types of HSLs which are produced during P. aeruginosa infection with LasR and RhlR receptors. To explore the binding affinity, fourteen different AHLs were subjected for molecular docking analysis with LasR and RhlR receptors. The RhlR was modelled using MMseqs2 in ColabFold: Alpha fold 2. Further, to validate the stability and interaction mechanism, molecular dynamic simulations was performed with the top docked six HSLs for 100 ns. In docking results, apart from 3-oxo-C12-HSL and C4-HSL, other HSLs such as C16-HSL and C6-HSL showed better binding affinity towards LasR and RhlR respectively. Further validation by molecular dynamic simulations showed that 3-oxo-C10-HSL has a stable complex formation with LasR and 3-oxo-C6-HSL with RhlR. Our comprehensive Insilco study results may provide promising targets for development of anti-QS drugs against Las/Rhl QS systems.
Clinical features, etiology, and prognosis of hand knob stroke: a case series
Authors: Zhang Zhiyong , Sun Xiaoxin , Liu Xinxiu , Wang Lei , Zhu Rui 
Published: July 2022

Abstract
Background
Hand knob stroke is a rare clinical disorder frequently misdiagnosed as peripheral neuropathy. The purpose of this study is to recognize this particular type of stroke by analyzing clinical features, etiology, and prognosis.
Methods
We enrolled 20 patients with acute hand knob stroke in the Department of Neurology of the Beijing Geriatric Hospital from January 2018 to January 2022, and the clinical and imaging data of the patients during hospitalization and follow-up were collected and summarized.
Results
Acute hand knob stroke accounted for 0.9% of all acute stroke, and ischemic stroke (18 cases, 85%) was more than hemorrhagic stroke (2 cases, 15%). All patients presented contralateral hand paresis, 12 (60%) of them had only isolated hand paralysis, and the location of the lesion corresponded to different finger weakness. The cause of hand knob hemorrhage was hypertension, while the causes of hand knob infarction were mainly small-vessel occlusion (SVO) (33.3%) and large-artery atherosclerosis (LAA) (33.3%), and the rare causes include carotid artery dissection, moyamoya disease and carotid body tumor. After a median follow-up 13.8 months, the prognosis of 95% patients was good, and one patient (5%) had recurrent stroke.
Conclusions
Hand knob stroke is a rare stroke with a good prognosis and a low stroke recurrence rate. Ischemic stroke is the predominant type and the main clinical manifestation is hand paresis. The cause of hand knob hemorrhage is hypertensive, while SVO and LAA are the main causes of hand knob infarction, but there are some rare etiologies.
Overburden Strata Movement Mechanism and its Key Control Technologies for Intelligent Backfilling Mining in Deep Coal Seams
Authors: Wang Fangtian , Li Zhe , Ren Shuai , Li Huaizhan , Gao Xiang , Feng Guangming 
Published: July 2022

Abstract
Coordinated development of safety and efficient mining and ecological environment protection in deep coal seams was an important theme of current coal green mining. Based on the geological production conditions in the deep coal seam of Yineng Coal Mine as the engineering background, the intelligent upgrading of backfilling mining equipment has been carried out in field and set the remote-control center in the roadway to realize intelligent backfilling mining; The FLAC3D software was used to simulate the coordinated bearing characteristics of the “backfilling body and the coal pillar”, and the coal pillar width in the reasonable section of the panel was determined to be 30 m. The coordinated load-bearing structure can realize overburden strata stability control. Comparing and simulating the coal energy distribution law with different backfilling ratios, on-site micro-seismic monitoring shows that super-high-water backfilling mining can effectively reduce the degree of coal seam energy accumulation, effectively prevent the occurrence of shock dynamic disasters in deep coal seams, and reveal the mechanism of backfilling mining to prevent rock bursts; In order to further improve the control effect of overburden strata movement in backfilling mining, intelligent mining and backfilling coordinated overburden strata control technologies such as secondary backfilling, and gangue pumping and mining without coal pillars, ‘backfilling body-support-coal body’ coordinated bearing have been proposed; The intelligent monitoring and pre-warning of the backfilling face, the intelligent monitoring and control of the surrounding rock deformation of the roadway and the evaluation strategy of the backfilling effect have been constructed, and the intelligent monitoring and pre-warning control technology system of deep coal seam backfilling and mining has been formed. The research results provide a demonstration for the realization of intelligent and green mining of deep coal seams.
Knowledge of youth regarding HIV prevention in South Africa – A quantitative descriptive and cross-sectional study
Authors: Sedzani Thivhafuni , Rose Tshililo Azwidihwi , Sellina Raliphaswa Ndidzulafhi 
Published: July 2022

Abstract
Background: The human immune deficiency virus is a transmissible retro infection that causes Acquired immune deficiency syndrome in humans. HIV infection gradually affects the immune system of the human body and successively harms the cells. The significant method of transmission of HIV and AIDS worldwide is hetero contacts, especially in developing countries. Most young people do not receive adequate HIV and sex education. The study aimed at investigating the knowledge of youth regarding HIV prevention in TVET campuses within the Vhembe district. Methods: Quantitative approach with a descriptive and cross-sectional design was employed in the study to gather more information on the knowledge of youth regarding HIV prevention in the Vhembe district. 353 self-administered questionnaires were completed by the students from all TVET campuses within the Vhembe district. Results: The study revealed that youths know the following: unprotected sex place’s one at risk of getting HIV/AIDS, condom use is one of the HIV prevention strategies, ABC stands for; is Abstain, be faithful, and Condom use, Abstaining reduces one’s chances of contracting HIV, and being faithful to one sexual partner means one is safe from contracting HIV. Conclusion: It is recommended that school health nurses should gain access to all TVET campuses within the Vhembe district to disseminate information about HIV prevention to the youth to increase their knowledge of HIV and promote the utilization of knowledge that youths must prevent HIV infection.
Integration of the Design Structure Matrix (DSM) and Modular Function Deployment (MFD) methods applied to mass customization aiming product modularization: a case study on heavy vehicle suspension
Authors: Forti Antonio Wagner , Ramos Cesar Coutinho , Muniz Jorge 
Published: July 2022

Abstract
This work presents the integration between the Design Structure Matrix (DSM) and Modular Function Deployment (MFD) methods applied to the modularization process of an air rear suspension system for heavy vehicles with 44 components by a cross-functional team. These two methods possess desired characteristics to process in industries, such as matrix-based data entry and commercial and academic software available. The modularization process started with the DSM method base on a binary square matrix that shows the presence or absence of relationships between pairs of components in a system. A DSM algorithm reordered the binary square matrix elements to generate the preliminary modules. That way, 26 from 44 components were grouped into eight modules that became new components, reducing the initial number of components from 44 to 26 (44-26+8). The reduction of the number of components made easy the application of the MFD method. The MFD method incorporated the customer requirements using the Quality Function Deployment (QFD), the Engineering point of view utilizing the Design Property Matrix (DPM), and the strategies of the company employing the Module Indication Matrix (MIM) in the modularization process. The QFD Matrix, DPM, and MIM union form the Product Management Matrix (PMM). A dendrogram helped the cross-functional team visualize the hierarchical relationship between the DPM and MIM components and analyze the modules' set. The cross-functional team chose seven final suitable modules considering components mounting in the assembly line and the supply chain of components too. This systematic modularization process showed up efficiently and made the work of the cross-functional team easy. Finally, the cross-functional team suggested the company board invest in knowledge management tools to assist the future cross-functional teams in replicating this modularization process in other heavy vehicle systems.
High-Dimensional Aerodynamic Data Modeling Using Machine Learning Method Based on Convolutional Neural Network
Authors: Zan Bo-Wen , Han ZhongHua , Xu Chen-Zhou , Liu Ming-Qi , Wang Wen-Zheng 
Published: July 2022

Abstract
Modeling of high-dimensional aerodynamic data presents a major challenge in the context of aero-loads prediction, aerodynamic shape optimization, flight control and simulation, etc. In this article, a machine learning approach based on convolutional neural network (CNN) is developed to address this problem. CNN is able to implicitly distill features underlying the data, and the number of parameters to be trained can be significantly reduced due to its local connectivity and parameter sharing properties, which is favorable for solving high-dimensional problems in which the training cost can be prohibitive. A hypersonic wing similar to the wing of Sanger aerospace plane carrier is employed as the test case to demonstrate the CNN-based modeling method. First, the wing is parameterized by free-form deformation method and 109 variables incorporating flight status and aerodynamic shape variables are defined as model input. Second, 7431 sample points generated by Latin hypercube sampling method are evaluated by performing computational fluid dynamics simulations based on a Reynolds-Average Navier-Stokes flow solver to finally obtain an aerodynamic database, and a CNN model is built based on the observed data. Finally, the well-trained CNN model considering both flight status and shape variables is applied to aerodynamic shape optimization to demonstrate its capability to achieve fast optimization at multiple flight statuses.
Identification, Prioritization and Management of Biodiversity Hotspecks: A Case Study of Western Ghats of Maharashtra
Authors: Trivedi Shivam , Bharucha Erach 
Published: July 2022

Abstract
The Western Ghats are globally recognized as a hotspot of rich, endemic and threatened biodiversity. Within this hotspot of biological diversity, there are islands of natural landscapes that can be termed as ‘hotspecks’. These hotspecks require careful prioritization and specific management strategies as they vary in objectives and ownership. Conserving hotspecks of biodiversity is of great relevance because creating new protected areas with wildlife corridors between them has become relatively impossible in the present context of intensive land-use change in this rapidly developing region. Management strategies, however, must be based on scientific assessment and using a set of prioritization criteria for selecting the most appropriate forms of management. The conservation action plan for the Western Ghats has become a controversial issue. In the present context of rapidly changing land-use patterns, economic development, forest fragmentation, isolation of habitats, linear intrusion, neo-urbanization and industrial growth are threats to the pristine nature of the ghats. Thus, there is an urgent need to identify, prioritize and manage the smaller fragments of biological importance within the larger ecologically sensitive landscape. A prioritization model for different types of hotspecks is essential so that it can be easily replicated by training frontline forest staff and implementing a strategy and action plans for the sites by using the Biological Diversity Act, 2002. Support of the local Biodiversity Management Committees and the State Biodiversity Board is essential for the conservation management of these biodiversity-rich sites.This study presents an innovative approach to prioritize areas (outside Forest Department jurisdiction) to assess the conservation value of hotspecks of diversity through a Rapid Biodiversity Assessment Technique. This can lead to a rational conservation strategy that conservation planners and practitioners can use.
Orbital b-Metric Spaces and Related Fixed Point Results on Advanced Nashine-Wardowski-Feng-Liu Type Contractions with Applications
Authors: Rasham T. , Shabbir M. S. , Nazam M. , Musatafa A. , Park Choonkil 
Published: July 2022

Abstract
In this article we prove some novel fixed-point results for a pair of multivalued dominated mappings obeying a new generalized Nashine-Wardowski-Feng-Liu- type contraction for orbitally lower semi-continuous functions in complete orbital b-metric space. Furthermore, some new fixed-point theorems for dominated multivalued mappings are established in the scenario of ordered complete orbital b-metric space. Some examples are offered to demonstrate the validity of our new results' premise. To demonstrate the applicability of our findings, applications for a system of nonlinear Volterra type integral equations and fractional differential equations are shown. These results extend the theoretical results of Nashine et al. (Nonlinear Anal. Model. Control. 26(3)(2021), 522–533).2010 Mathematics Subject Classification: 47H04; 47H10; 54H25
Applying the Spherical fuzzy DEMATEL Approach for Identification and Prioritization of the Drone App Issues
Authors: Pandey Mamta , Litoriya Ratnesh , Pandey Prateek 
Published: July 2022

Abstract
During the past few years, the number of drones (Unmanned Aerial Vehicles or UAVs) manufactured and purchased has risen dramatically. It is predicted that it will continue to spread, making its use inevitable in all walks of life. There are two key parts to the UAV: the physical hardware and the software that governs its navigation or performs various duties depending on the area of concern. Manufacturers of drones release a mobile app for operating the drones. Only a small number of drone manufacturers also offer development kits for those who want to create their own unique or more creative apps for their devices. Drone apps are therefore expected to be overrun the app stores in the near future. UAV's software is not being studied/researched despite several active researches and studies being carried out in the UAV's hardware field. A large-scale empirical analysis of Google Play Store Platform apps connected to drones is being done in this direction. There are, however, a number of challenges with drone apps because of the lack of formal and specialized app development procedures. In this paper, eleven drone apps issues have been identified. Then we applied DEMATEL (Decision Making Trial and Evaluation Laboratory) method to analyze the drone apps issues (DIs) and divide these issues into cause and effect groups. Firstly, multiple experts evaluate the direct relations of influential issues in drone apps. The evaluation results are presented in spherical fuzzy numbers (SFN). Secondly, convert the linguistic terms into SFN. Thirdly, based on DEMATEL, the cause-effect classifications of issues are obtained. Finally, the issues in the cause category are identified as DI’s in drone apps. The outcome of the research is compared with the other variants of DEMATEL like rough‐Z‐number‐based DEMATEL and Spherical fuzzy number and the comparative results suggest that Spherical Fuzzy-DEMATEL is the most fitting method to analyze the interrelationship of different issues in drone app. The outcome of this work definitely assists the software industry to successful identification of the critical issues where professionals and project managers could really focus on.