bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementation stages for integrating behavioral health and primary care: A participatory Delphi study to refine a determinant framework
Authors: Domlyn Ariel M , Wandersman Abraham , Palinkas Lawrence A , Zarrett Nicole , Weist Mark D 
Published: December 2022

Abstract
Background: The integration of behavioral health and primary care is a best practice to improve patient outcomes and achieve health equity. However, the process of integrating is complex, requiring organizational change and sometimes a complete system overhaul. Implementation science offers useful ideas for helping healthcare organizations to implement effective care, including recognition that change occurs incrementally and is stymied by specific barriers and facilitators. Although determinants (i.e., barriers and facilitators) of successful care integration have been identified their relevance to organizations seeking to integrate care remains unknown. This study sought to understand which implementation determinants (defined by the R=MC2 framework, where Readiness is conceptualized as Motivation, Innovation-specific Capacity, and General Capacity) are most important in the process of integrating care across four implementation stages: Exploration, Installation, Initial Implementation, and Full Implementation.
Methods: A participatory Delphi study design was used to gather practice-based evidence from ten integrated care practitioners, researchers, and technical assistance providers. Qualitative and quantitative data were collected across four rounds. Qualitative summaries were presented back to participants between rounds for reaction and recalibration. The Framework Method guided initial qualitative analyses, which were then triangulated with descriptive statistics from a process survey. Coders used fuzzy set theory to create the final results on perceived relevance of each determinant across stages of implementation.
Results: Determinants most relevant across implementation stages are Leadership, Priority, a Champion, Supportive Climate, Culture, Innovativeness, and Staff Capacities. Determinant strength is most critical during active implementation stages.
Conclusions: The present study is one of only a few that apply implementation science frameworks to the integration of behavioral health and primary care. Results provide a structure for assessing determinants by phase and could be used to determine precision and timing of resource allocation to facilitate integration.
Synthesis of Activated Carbon Composited With Egyptian Black Sand for Enhanced Adsorption Performance toward Methylene Blue Dye
Authors: Elkholy Ahmed Salah , Yahia Mohamed Saber , Elnwawy Mohamed Abdelsamei , Gomaa Hosny Anwar , Elzaref Ahmed Shafek 
Published: December 2022

Abstract
The present study reports the feasibility of the synthesis of a novel porous activated carbon (OS400) composite adsorbent prepared from olive stone and impregnated with garnet (GA) types of black sand minerals. The Activated Carbon/ garnet composite (OSMG) was applied for the sorption of macromolecular organic dye. The structural characteristics of the synthesized composite were evaluated by Brunauer–Emmett–Teller (BET), N2 adsorption/desorption measurements, Scanning Electron Microscopy equipped with Energy Dispersive X-ray spectroscopy (SEM-EDX), X-ray diffraction (XRD), and a Fourier transform infrared spectrometer (FT-IR). The specific surface area of (GA), (OS400), and (OSMG) were 5.157 m2.g− 1, 1489.598 m2.g− 1, and 546.392 m2.g− 1, respectively. The high specific surface area and effective active centers of the new composite promoted the adsorption of methylene blue (MB). The experiments were carried out under various conditions such as contact time, initial concentration of adsorbate, adsorbent dosage, pH, and temperatures. The equilibrium adsorption data were evaluated using the Langmuir and Freundlich isotherm models. The results display that, the adsorption isotherm had an excellent fitting to the Freundlich model. Furthermore, the data obtained from adsorption kinetic models showed that the pseudo-second-order model more agreeing for describing the (MB) adsorption reaction, suggesting a chemisorption mechanism. The values of thermodynamic parameters indicate that methylene blue dye adsorption onto the (GA) adsorbents through an endothermic reaction, while exothermic sorption of MB onto (OS400) and (OSMG), with a non-spontaneous process.
Structural analysis, in vitro antioxidant and lipid-lowering activities of purified Tremella fuciformis polysaccharide fractions
Authors: Li Xige , Zhang Fengyi , Jiang Chaoxian , Jiang Jun , Hou Yanhui 
Published: December 2022

Abstract

In order to study the composition, structure and physicochemical properties of Tremella fuciformis polysaccharide (TFPS), four new polysaccharide fractions (TFPS1, TFPS2, TFPS3 and TFPS4) were successfully isolated from the hot-water extracted crude polysaccharides by DEAE-52 cellulose column. Their structures were analyzed by FT-IR, SEM, HPGPC, monosaccharide composition, Congo red and I2-KI experiments. TFPS1 was a heteropolysaccharide with a molecular weight of 742 Da for the major polysaccharide fragment. TFPS2, TFPS3 and TFPS4 were single component homogeneous polysaccharides with 350774 Da, 622675 Da and 624724 Da, respectively. Glucose was the major monosaccharide of TFPS1 and TFPS2, while Mannose was the major monosaccharide of TFPS3 and TFPS4. TFPS1 and TFPS2 displayed a stable triple helix structure at aqueous solution, while TFPS3 and TFPS4 presented longer side chains and more branched chains. TFPS1, TFPS2, TFPS3 and TFPS4 all possessed in vitro antioxidant activities. Moreover, the four polysaccharide fractions all demonstrated significant cholesterol binding ability, as well as obvious sodium taurocholate binding ability. The results of this study may provide some guidance on the medicinal value of TFPS.
Assessing the protection of Key Biodiversity Areas in mountains at conservation-relevant scales
Authors: Ly Amina , Geschke Jonas , Snethlage Mark A. , Stauffer Kerrie L. , Nussbaumer Jasmine , Schweizer Dominic , Diffenbaugh Noah S. , Fischer Markus , Urbach Davnah 
Published: December 2022

Abstract
Indicators of biodiversity protection at the national level are used to assess progress toward global goals. However, they provide little information at scales relevant for conservation and management. Hence we provide an area-based alternative to the current indicator calculated at the level of individual mountain ranges, which is directly relevant for assessing progress toward SDG 15.4.1. This allows identifying mountain areas in need of enhanced conservation efforts, within and across countries.
A New Molecular (P)Layer in Pseudomyxoma Peritonei: The Splicing Machinery is Dysregulated and Linked to Low Survival
Authors: Moreno-Montilla María Trinidad , Alors-Pérez Emilia , Martínez-López Ana , Blázquez-Encinas Ricardo , García-Vioque Víctor , Rodríguez-Ortiz Lidia , Valenzuela-Molina Francisca , Rufián-Andújar Blanca , Granados-Rodríguez Melissa , Ortega-Salas Rosa , Vázquez-Borrego Mari C. , Romero-Ruiz Antonio , Castaño Justo P. , Arjona-Sánchez Álvaro , Ibáñez-Costa Alejandro 
Published: December 2022

Abstract
Purpose:
Pseudomyxoma peritonei (PMP) is a rare cancer that causes chronic and uncontrollable mucus accumulation, gradually leading to intraperitoneal organ adhesion, bowel obstruction, malnutrition, and eventually cachexia and death. Aggressive cytoreductive surgery and hyperthermic intraperitoneal chemotherapy offer the best results; but the probability of relapse remains high. The study of the distinct molecular layers underlying PMP is essential to understand its genesis and progression. Alternative splicing is emerging as a new player in all cancers, but its role in PMP is unknown. The aim of this work was to assess the splicing machinery status in PMP and determine its potential contribution to disease prognosis.
Methods:
A set of 62 splicing-related genes were evaluated in a cohort of 29 patients using a microfluidic array, and their levels were compared between tumor and non-tumor tissue and correlated to relevant clinical parameters. Selected components were validated by immunohistochemistry and subsequently studied in detail by enrichment analyses.
Results:
Results revealed a profound dysregulation of the splicing machinery at RNA/protein level, which allowed to distinguish between tumor and control tissues. Particularly, the splicing factors HNRNPK, MBNL1, PTBP1 and RAVER1were associated with poor prognosis and their expression was linked to TP53regulation and inflammation processes.
Conclusions:
These findings provide the first evidence for the dysregulation of the splicing machinery in PMP, suggesting that it could be functionally altered and play a role in this rare malignant disease. Therefore, its detailed understanding could help to identify novel prognostic biomarkers and therapeutic targets in PMP.
Implementation of Resource Allocation Technique for DVB-RCS Compliant Satellite Terminals in Test-bed Scenario
Authors: Roy Abhishek Kumar , Singhal Rajneesh , Saini Trilok K. , Kumar Satyendra , Dhaka Manoj K. 
Published: December 2022

Abstract
Satellite communication is advantageous for several reasons such as broad coverage, small installation time of remote user sites, and network services in inhospitable terrains, where installing terrestrial infrastructure is costly. With the advent of broadband multimedia satellites such as Ku and Ka band satellites, multimedia services to the satellite terminals are gaining momentum. Digital Video Broadcast Return Channel via Satellite (DVB-RCS) is an open standard developed by ETSI which has further standardized, commercialized and solved the problem of inter-operability of Ku Band satellite terminals. Satellite bandwidth is scarce therefore treated as precious resource. In the present paper, authors aim to develop and realize the resource allocation techniques in return link channel for DVB-RCS compliant satellite terminals. The paper provides method for giving preference to real time application in terms of early processing of allocation request generated against the real time traffic to reduce delay and also provides method to avoid parallel connection arises due to transmission of terminal on more than one frequency at a time. Authors have realised DVB-RCS resource allocation technique and have given simulation results.
3D-DCNN Classification of Retinal Diseases Using Artificial Intelligence Deep Patterns Generated from 3D-OCT Hyperspectral Images
Authors: Krishnan M. Mukesh , Ramya S. Thanga , Ramar K. 
Published: December 2022

Abstract
The automatic and exact classification of 3D Optical Coherence Tomography (3D-OCT) images is crucial for retinal machine diagnostics. We propose a novel hybrid computer-aided 3D-OCT analytical approach (HCAD3D-OCT) for discriminating Diabetic Macular Edema (DME), Choroidal Neovascularization (CNV), and drusen illnesses from normal Optical Coherence Tomography (OCT) imaging. The proposed hybrid learning method combines Region of Interest (RoI) segmentation based on central severe chorioretinopathy images with deep neural networks for retinal condition diagnosis. The suggested strategy includes location, segmentation, extraction, diagnosis, and classification. Effective feature fusion for merging OCT image data obtained using a 3D Deep Convolution Neural Network (3D-DCNN) with RoI segmentation phase characteristics is provided. These combined extracted characteristics predict OCT retina disorders. Fragmentation of retinal RoI sections helps concentrate attention on diagnostically important regions. Norm-VGG19 is a hybrid supervised neural network with regularized kernels. Norm-VGG19 is trained on a large testing set for RoI localization and classification. The system's efficacy has been tested. The Large Database of Annotated 3D-OCT v3 is used to test the model's competence. The research outcome illustrates with the intention of the proposed model has good efficiency, sensitivity, and specificity. Overall, we see a 98.8% accuracy rate, 99.4% sensitivity, and 98.2% specificity.
Identification of a pyroptosis-related prognostic signature in bladder cancer and RT-qPCR validation
Authors: Wang Wei , Yang Ke , Wang Shuang , Zhang Wei , Guo Qiang , Wu Bo , Chen Qian , Zhang Yanlong , Wang Jingqi 
Published: December 2022

Abstract
Bladder carcinoma (BC) remains one of the commonly occurring cancers worldwide. Pyroptosis promotes the development of various tumors, but its role in the progression of bladder cancer as well as its effect on prognosis remain unclear. TCGA dataset was used as training set, GSE32894 as well as GSE48276 were used as test sets. We identified 19 DEGs related to pyroptosis between bladder cancer tissues and normal bladder tissues, 6 genes were further clarified as prognosis-associated genes. Through stepwise K-M analyses and stepwise multiCox analyses, we established a prognostic model, and the model had high specificity and sensitivity in predicting the patients’ prognosis. Independence analysis suggested that the survival of bladder cancer patients could be independently predicted by the risk signature. Further, we found differences in tumor immune cells infiltration, tumor mutation burden (TMB), immune checkpoints, and drug sensitivity among different risk groups. Our study confirmed the critical prognosis role of pyroptosis-related genes in bladder cancer. Our prognostic model may offer a new perspective for the therapy of bladder cancer.
State of the art review on automatic sorting system for industrial robots using Internet of Robotic Things
Authors: Gueye Thierno , Wang Yanen , Mushtaq Ray Tahir , Rehman Mudassar , Ahmed Ammar , Ali Haider 
Published: December 2022

Abstract

The idea for the Internet of Robotic Things (IoRT) comes from activities. IoRT allows smart devices to combine sensor information from multiple sources, use broader nearby insights to determine the best reason for the activity and display events on-screen. The Internet of Things can connect web applications to other gadgets to make them smarter. Automated engineers combine the two and arm themselves with sensors that can analyze the current situation. Mechanical improvements such as ordinary voice links (PC) vision sensor innovations and artificial intelligence (AI) have resulted in a turn of events and programmed placement frameworks under advanced machinery. This article examines frameworks for arranging programmed objects to assemble robots and innovative patterns in ordinary language programmed programming, and three-dimensional (3D) visual insight. The relevant statement "regulation scene" should describe the combination of all three modules. This computation enables people to relate through a three-tiered information scene and guides managers to use discourse to provide reasonable criteria whenever an order is legitimate. After receiving precise criteria, the robot can use this diary's planned execution calculations and programmed programming to direct the placement of programmed items. The play area provides a context for the natural product, while the landscape design provides a valuable part of the framework.
Contextually Intelligent Decisions: A Co-designed Approach for Commercial Driving Assessment
Authors: Mase Jimiama Mosima Mafeni , Pekaslan Direnc , Agrawal Utkarsh , Chapman Peter , Wagner Christian , Figueredo Grazziela 
Published: December 2022

Abstract
Commercial driving is a complex multifaceted task influenced by drivers' personal traits and external contextual factors, such as weather, traffic, and road conditions. Current intelligent commercial driving assessment systems only focus on the manner by which drivers operate vehicle controls when analysing driving performance and the impact of driver behaviour on road safety, potentially producing incomplete and unfair assessments. In this paper, we introduce a stakeholder co-designed approach to complement current driver-assessment systems and provide more context-aware, comprehensive and we hope--fairer assessments of commercial driving. The approach engages key stakeholders in the commercial driving sector to capture the impact of personal traits and external contextual factors on driving performance and provides a systematic approach to embed this knowledge into the assessment of commercial drivers. We demonstrate the effectiveness and utility of the approach by illustrating its end-to-end deployment in the context of heavy goods vehicle driving assessment.
Fast Ethics - Making Ethical Decisions in Mental Health During Covid – a case study
Authors: Beale Russell , Leitao Filipe 
Published: December 2022

Abstract
We report on the structure set up within Birmingham & Solihull Mental Health Foundation Trust in the UK to give advice and guidance on a range of ethical challenges arising as a result of the Covid-19 pandemic. The principles behind the group, its approach to decision making and a summary of the issues referred to it are represented, as well as our reflections on the potential usefulness of the group outside of the pandemic.
Data fusion using neural networks for intelligent multilevel control of artificial and natural objects: a survey
Authors: Tianxing Man , Osipov Vasiliy , Zhukova Nataly , Subbotin Alexey 
Published: December 2022

Abstract
In the modern world, data fusion (DF) technique has been playing an increasingly important role for effective and efficient data transformation in subject domains. DF aims to solve the problem of control of artificial and natural objects. Although DF has been intensively studied, neither unified problem statements of the fusion of the heterogeneous, multimodal, complex, imperfect data nor in-depth elaboration of characteristics and challenges about the application of DF on such specific situations are available. It is also unclear to what extent DF challenges have been addressed and what the overall research landscape of DF is. We define the requirements for DF in the interests of intelligent control of artificial and natural objects and look at the applications, reveal the capabilities of traditional DF methods and analyze the advantages that neural networks (NN) have over them. We show that despite of the evident advantages, none of the existing NNs satisfy all the requirements of DF. Based on the analysis of NN architectures, we determine the requirements for advanced NN architectures and discuss future research directions.
EGCG inhibits atrial fibrosis and reduces the occurrence and maintenance of atrial fibrillation and its possible mechanisms
Authors: Li Tao , Tong Qi , Wang Zhengjie , Yang Ziqi , Sun Yiren , Cai Jie , Xu Qiyue , Lu Yuan , Liu Xuemei , Lin Ke , Qian Yongjun 
Published: December 2022

Abstract
Purpose The aim of this study was to investigate the effect and mechanism of epigallocatechin-3-gallate (EGCG) on atrial fibrillation (AF) in rats.
Methods A rat AF model was established by angiotensin-II (Ang-II) induction, to verify the relationship between atrial fibrosis and the AF. The expression levels of TGF-β/Smad3 pathway molecules and lysyl oxidase (LOX) in AF were detected. Subsequently, EGCG was used to intervene Ang-Ⅱ-induced atrial fibrosis, to explore the role of EGCG in the treatment of AF and its inhibitory mechanism on fibrosis. It was further verified that EGCG inhibited the production of collagen and the expression of LOX through the TGF-β/Smad3 pathway at the cellular level.
Results The results showed that the induction rate and maintenance time of AF in rats increased with the increase of the degree of atrial fibrosis. Meanwhile, the expressions of Col I, Col III, molecules related to TGF-β/Smad3 pathway, and LOX increasedsignificantly in the atrial tissues of rats in the Ang-II induced group. EGCG could reduce the occurrence and maintenance time of AF by inhibiting the degree of Ang-induced rat atrial fibrosis. Cell experiments confirmed that EGCG could reduce the synthesis of collagen and the expression of LOX in cardiac fibroblast induced by Ang-II. The possible mechanism is to down-regulate the expression of genes and proteins related to TGF-βSmad3 pathway.
Conclusion EGCG could downregulate the expression levels of collagen and LOX by inhibiting the TGF-β/Smad3 signaling pathway, alleviating Ang-II-induced atrial fibrosis, which in turn inhibited the occurrence and curtailed the duration of AF.
Effect of GNSS RO on prediction of the 2021 Henan Rainstorm
Authors: Wang Yu , Jin Shuanggen 
Published: December 2022

Abstract
Precise prediction of the extremely heavy rainstorm is still challenging due to less or low spatial-temporal measurements. Nowadays, space-borne Global Navigation Satellite System (GNSS) radio occultation (RO) provides high spatial-resolution atmospheric parameters, which may improve the prediction precision of heavy rainfalls. In this paper, the impact of GNSS radio occultation on forecasting the heavy precipitation event is assessed for the extremely massive rainfall in Henan, China, on July 20, 2021. The GNSS radio occultation data from Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2), MetOp-A/B/C, Fengyun (FY)-3C GNOS are applied for assimilation in Weather Research and Forecasting Model Data Assimilation (WRFDA) of three-dimensional framework (3DVAR) system using the local refractivity operator. Control Experiment (CNTL) and RO are designed to examine the roles of GNSS radio occultation, and RO+GNOS is conducted to further evaluate the impact of GNSS RO data onboard FY-3C on this extreme rainfall. The fractions skill score (FSS) is used to quantify the accuracy of predicted precipitation at given thresholds. The 24-h forecast result shows that the experiments with assimilating GNSS radio occultation data produce better precipitation forecasts with regard to the distribution and the amount due to more precise initial conditions of the moisture field. In general, RO and RO+GNOS have similar increments for a more accurate humidity field near Henan and more explicit water vapor channels, and thus their predictions outperform CNTL. Compared with RO and CNTL, RO+GNOS exhibits the higher marked FSSs for heavy rainfall forecast at 50 mm and 100 mm thresholds, with average advancements of 7.76% and 32.55% for the 50 mm threshold, and 10.50% and 47.39% for 100 mm threshold, respectively. For the 48-h and 72-h forecasts, three experiments exhibit similar results that RO+GNOS gives the best performance in rainfall predictions, followed by RO and then CNTL. Overall results imply that GNSS radio occultation data has a noticeable enhancement for the prediction of this record-breaking rainfall, and data from GNOS onboard FY-3C plays an indispensable role.