bluuebunny/crossref_metadata_2025_split huggingface dataset:
Functional and effective connectivity underlying semantic verbal fluency
Authors: Arrigo Isabella Velloso , Silva Pedro Henrique Rodrigues , Leoni Renata Ferranti 
Published: February 2023

Abstract
Semantic verbal fluency (SVF) impairment is present in several neurological disorders. Although activation in SVF-related areas has been reported, how these regions are connected and their functional roles in the network remain divergent. We assessed SVF static and dynamic functional connectivity (FC) and effective connectivity using functional magnetic resonance imaging in healthy participants. We observed activation in the inferior frontal (IFG), middle temporal (pMTG) and angular gyri (AG), anterior cingulate (AC), insular cortex, and regions of the superior, middle, and medial frontal gyri (SFG, MFG, MidFG). Our static FC analysis showed a highly interconnected network for task and resting state. Increased connectivity of AC with the pMTG and AG was observed for the task. The dynamic FC analysis provided circuits with connections similarly modulated across time and regions related to category identification, language comprehension, word selection and recovery, word generation, inhibition of speaking, speech planning, and articulatory planning of orofacial movements. Finally, the effective connectivity analysis provided a network that best explained our data, starting at the AG and going to the pMTG, from which there was a division between the ventral and dorsal routes. The SFG and MFG regions were connected and modulated by the MidFG, while the inferior regions formed the ventral route. Therefore, we successfully assessed the SVF network exploring regions associated with the entire processing, from category identification to word generation. The methodological approach can be helpful for further investigation of the SVF network in neurological disorders.
Study on wear resistance of implant abutment using different surface treatment methods
Authors: Wang Fang , Gu Hongzheng , Yang Bin , Zhu Zhen , Li Yongjian 
Published: February 2023

Abstract
Abrasion often happened in abutment screw during the operation of dental implant, and it often resulted in reduction of tightness between the abutment and the implant, which always caused the connection failure at last. The purpose of this in vitro study was to research the wear resistance of implant abutment screw under different surface treatment methods, and to find appropriate method to increase the wear resistance of implant abutment screw. Titanium abutments which were treated by low-temperature surface nitriding and low-temperature magnetron sputtering with TiN coating respectively were the experimental groups, and the untreated titanium implants and related abutments were used as the control groups. Wear resistance was obviously increased after low-temperature surface nitriding and low-temperature magnetron sputtering.
CAE-VLAD-Net: A Loop Closure Detection System for Mobile Robots Using Convolutional Auto-Encoders Network with VLAD
Authors: Liu Yanli , Li Yawei , Zhang Heng , Xiong Neal 
Published: February 2023

Abstract
A critical part of visual SLAM is visual loop closure detection. It can solve the problem of trajectory drift caused by long time movement of mobile robots. The traditional loop closure detection system can not accurately detect the real closed loop. Factors such as different viewpoints, different lighting conditions and dynamic feature occlusion can seriously affect the positioning accuracy of mobile robots. Deep learning is made significant strides in computer visual in recent years, offering a fresh approach to the closing loop detection challenge. In this paper, We build a loop closure algorithm based on CAE-VLAD-Net (Convolutional Auto-Encoder-Vector of Locally Aggregated Descriptors-Network) model, which can solve these problems. This algorithm combines the characteristics of convolutional neural networks and stacked auto-encoders in deep learning, extracts features of continuous dense data collected by sensors, and applies them in loop closure based on key frames. We conduct comprehensive tests on various datasets, demonstrating that our method performs better than the state-of-the-art approach.
Muscle Dysmorphic Disorder Inventory (MDDI): Translation and Validation of an Arabic-language version
Authors: AlGhareeb Muneera , Almutawa Yaser Mansoor , Karaidi Noor , Albalawi Rima , Aldwsri Alreem , Helmy Mai , Alenezi Ahmad F. , Trabelsi Khaled , Ghazzawi Hadeel Ali , Jahrami Haitham 
Published: February 2023

Abstract
Purpose
The term muscle dysmorphia (MD) refers to the pathological desire to increase lean muscle mass coupled with a persistent belief that one is not muscular enough. The disorder was recently classified under the umbrella of obsessive-compulsive disorder in DSM-5. The individuals social view and sense of self-worth are impacted by MD. Consequently, functional impairment occurs. The assessment of MD is made with the muscle dysmorphia Disorder Inventory (MDDI). The purpose of the study is to validate the Arabic version of the MDDI ensuring the availability of the instrument in Arabic-speaking nations.
Methods
1118 participants (58% female, average age 28 years) participated in the translation of MDDI through an internet-based survey.
Results
Based on multigroup confirmatory factor analysis (CFA), the three-factor structure of the English MDDI was replicated, independent of gender (TLI = 0.85, CFI = 0.90, RMSEA = 0.09). The reliability was evaluated via Cronbach's α and McDonald's ω for the total MDDI scale and the sub-scales. Cronbach´s alpha was 0.71 for DFS, 0.71 for AI and 0.82 for FI, and 0.70 for the MDDI total score. Men and women showed differences in three subscales of the MDDI (DFS, AI, FI). McDonald's Omega showed an Al of (0 .72) DFS (0.72) FI (0.83) and total MDDI (0.82).
Conclusion
The MDDI-13 Arabic translation proved to be valid. Thus, the results are consistent with using the measure in Arabic-speaking nations.
Level of evidence:
Level V descriptive cross-sectional study.
Big Data and Personal Information Privacy in Developing Countries: A Case of Kenya
Authors: Wambiri Daniel , Masinde Johnson , Mugambi Frankline 
Published: February 2023

Abstract
This study investigated the relationship between big data and personal information privacy in Kenya, a developing country where the use of big data has grown rapidly in recent years. The study aimed to assess the effectiveness of current data protection laws and policies, identify challenges faced by individuals and organizations in protecting their data privacy, and suggest ways to strengthen data protection frameworks and enhance public awareness of data privacy issues. The study used a mixed-methods approach, including a survey of 500 participants, 20 interviews with key stakeholders, and a review of 50 relevant documents.Based on the findings from the survey, interviews, and document review, the study found that there was a lack of awareness about the risks associated with sharing personal information online, and a need for greater public education and awareness-raising campaigns. The study also found that while individuals may be willing to trade their personal information for tangible benefits, they are also concerned about how their data is being used and by whom. Additionally, the legal and regulatory frameworks related to data privacy in Kenya were weak and fragmented, highlighting the need for stronger legal and regulatory frameworks and greater education and training for stakeholders. The study identified the need for cross-sectoral collaboration among government institutions, legal experts, industry representatives, and citizens to develop more nuanced and balanced policies and practices. The study has important implications for policymakers, industry representatives, and civil society organizations in Kenya and beyond, including the need for greater public education, stronger legal and regulatory frameworks, and greater dialogue and collaboration among stakeholders in the field.
A Deep Learning Method for Automatic Reliability Prediction of CR-VANETs
Authors: Bahramnejad Somayeh , Movahhedinia Naser , Naseri Amineh 
Published: February 2023

Abstract
Reliability is a critical issue in vehicular networks. A Deep Learning (DL) method is proposed in this study to automatically predict the reliability of Cognitive Radio Vehicular Networks (CR-VANETs) ignored in the previous research. First, a dataset is generated based on a previously proposed method for the reliability assessment of CR-VANETs. Then, a model is proposed to predict the networks' reliability using the DL method and compared with other machine learning methods. While machine learning methods have been applied in vehicular networks, they have not been used for reliability prediction. The proposed DL model is utilized in this research to predict CR-VANETs' reliability. Based on the results, the DL model outperforms other machine learning methods for reliability prediction. The correlation coefficient and root mean square error of the test data for the DL model are 0.9862 and 0.0381. These results indicate the CR-VANETs' reliability prediction accurately using the proposed method.
Environmental Risk Factors Contributing to the Transmission of COVID-19 in Zambia: A Cross-sectional study in Lusaka district
Authors: Chishimba Kennedy , Libonda Liyali , Velu Rachel Milomba , Kamboyi Harvey K. , Hakoonde Titus , Bumbangi Flavien Nsoni 
Published: February 2023

Abstract
Background: A propagative increase in SARS-CoV-2 transmission has been witnessed in Zambia since the index case was reported in March 2020. Although sociocultural factors including movement patterns, people’s livelihood, and way of life have been demonstrated to influence SARS-CoV-2 transmission dynamics, the role of environmental risk factors has not been adequately documented. The aim of the study was to investigate environmental risk factors contributing to the transmission dynamics of SARS-CoV-2 in Zambia using a cross-sectional study
Results: The positivity rates were 10.5 % cell phones, 5.3% door knobs, 2.7% remote controls and 2.6% beddings. All the other surfaces came out negative. The sex proportion of the respondents was 55% and 45% males and females respectively. Regarding occupancy density, 37.5% (15/40) resided in a 2 to 3-roomed house, 32.5% (13/40) resided in a 4 to 7 roomed house and 30% (12/40) resided in > 7-roomed house. Of the 40 respondents, 75% (30/40) used recyclable face masks while 25% (10/40) used non-recyclable face masks. For the non-recyclable face masks, 30% of the respondents indicated incineration as a disposal method. A correlation coefficient of 0.25 was documented for the association between occupancy density and surface contamination.
Conclusions: The study revealed that most environmental surfaces particularly mobile phones were rarely disinfected and were most likely to contribute to the transmission of SARS-CoV-2 in the community. Furthermore, the majority of the respondents used recyclable face masks which are easily washable. However, those who used non-recyclable face masks disposed of them indiscriminately which has the potential of contaminating the environment and further lead to the transmission of SARS-CoV-2.
The effect of exercise on breast cancer-related lymphedema
Authors: Yanxue Lian , Sandhu Simran , Yamikani Asefa , Gupta Ananya 
Published: February 2023

Abstract
Purpose: This review will provide an overview of the current state of knowledge by 1) evaluating the feasibility and safety of exercise as a treatment for patients with breast cancer-related lymphedema (BCRL), and 2) exploring the effects of different exercises on patients with BCRL.
Method: A systematic literature review of relevant studies published before 30 June 2022 was performed using three scientific databases PubMed, Embase, and Scopus.
Result: A total of 611 articles were found. Eventually, 15 articles fulfilled the inclusion criteria and were used for this literature review. A total of 5 different exercises, consisting of yoga, Pilates, resistance exercise, aquatic-based exercise, and complex exercise of aerobic and resistance training are included.
Conclusion: The review shows that these exercises are safe for patients with BCRL. Some measurable effects of exercises on lymphedema and some possible reasons/theories are shown.
Implications for Cancer Survivors: Although only yoga, Pilates, and resistance exercise may improve the severity of lymphedema based on the measurement of limb volume, all 5 exercise modes can help improve lymphedema symptoms to some extent. The improvement of symptoms may cause the increased quality of life (QoL) in symptom and physical functioning domains, leading to increased emotional and social function.
The Basic Elements of Devices Resource Consumption Decreasing Metodology for Distributed Systems on the Basis of Fog- and Edge-Computing
Authors: Klimenko A. B. 
Published: February 2023

Purpose of research.The purpose of this study is to form a set of basic elements of the methodology for reducing the consumption of the residual resource of computing devices operating as part of distributed computing systems based on the concepts of fog and edge computing. The concepts of fog and edge computing are relatively new and, despite the large volume of publications on this topic, the issue of resource consumption of computing devices in terms of FBG values has not been considered in the literature. At the same time, extending the service life of devices is currently highly desirable, which makes this study relevant.Methods.The main scientific methods used in this study are analysis (of subject areas), numerical simulation and natural experiment, confirming the feasibility of the main aspects of the developed methodology.Within the framework of the concepts of fog and edge computing, it is considered appropriate to shift the computing load to data sources, which, as a rule, are located at the edge of the network. However, modern studies do not affect the estimates of the impact of such a strategy in the placement of functional tasks on the estimated values of the probability of non-failure operation of devices, which characterizes the state of the residual resource of the device. Meanwhile, an increase in the load on devices with less computing power than, say, a device within a data center leads to an acceleration of their wear, which, in turn, translates into economic costs for maintaining a functioning computing infrastructure. At the same time, the load on the intermediate network devices is reduced, since they transmit reduced amounts of data, and the time that can be used for data processing, if the latter is performed at the edge devices, increases. The developed methodology offers an integrated approach to the placement of functional tasks of distributed information systems, taking into account the listed features of using the concepts of fog and edge computing.Results.The main results of this study are the description of a set of basic methods that make up the methodology for reducing the consumption of the residual resource of computing devices of distributed computing systems based on fog and edge computing. The resulting complex is based on the developed models and the results of experimental studies.Conclusion.Currently, despite the massive use of the concepts of fog and edge computing in the implementation of distributed information systems, there has not been developed a unified methodology that would reduce the consumption of resources of computing devices and thereby extend their service life. Within the framework of this work, a set of methods is proposed, the further development of which will increase the service life of devices that make up the computing infrastructure of distributed computing systems.
High-fibre analog rice made from beneng taro flour
Authors: Fajriaty Deannisa , Setiawan Budi , Sinaga Tiurma , Sulaeman Ahmad 
Published: February 2023

<div class="WordSection1"><p align="center"><strong>ABSTRACT</strong></p><p><strong><em>Background: </em></strong>In 2019, the average national rice consumption was 114,3 kg/cap/year, exceeding the recommended ideal 100,4 kg/cap/year by approximately 82,98%. The staple food in Indonesia is dominated by rice. Indonesian cuisine is known to have cultural diversity and uniqueness and is rich in taste. Besides that, it is closely related to culture and customs, so it has been part of the eating culture of various ethnic cultures in Indonesia for a long time. Therefore, strategic efforts are needed in using local tubers, namely alternative staple foods, by developing friendly products as part of the realization of national food security by means of food diversification.<strong><em></em></strong></p><p><strong><em>Objectives: </em></strong>To analyze the effect of the formulation of taro beneng flour as the primary raw material for analog rice on the analysis of nutritional content (water, ash, fat, protein, and carbohydrates) and dietary fiber content.<strong><em></em></strong></p><p><strong><em>Methods: </em></strong>This type of research was experimental with a completely randomized design (CRD). The level of rice treatment is analogous to the ratio of taro beneng flour, yellow corn flour, and yellow soybean flour, namely F1 (75:25:5), F2(50:50:5), and F3 (25:75:5).<strong><em></em></strong></p><p><strong><em>Results: </em></strong>The F1 formulation (75:50:5) was the best treatment level because it had a high content of nutrients and dietary fiber (76,0% carbohydrates; 18,6% dietary fiber). Therefore, analog rice made from taro beneng flour can be used as a staple food to maintain the health of specific groups.<strong><em></em></strong></p><p><strong><em>Conclusions: </em></strong>Analog rice made from taro beneng flour can be used as an alternative to staple food and meets BPOM standard (2022) as a high-fiber products (18,6 g &gt; 6 g/100 g).<strong><em> </em></strong></p><p><strong> </strong></p><p><strong>KEYWORDS: </strong>analog rice; beneng taro flour; carbohydrate; dietary fiber; local tubers.<strong><em></em></strong></p></div><strong><em><br clear="all" /></em></strong>
A “Good” Samaritan? The Geopolitics of Russia’s Covid-19 Assistance
Authors: Omelicheva Mariya 
Published: February 2023

Between March and December of 2020, more than three dozen states received various types of COVID-19 assistance from Moscow. The Russian government emphasized a humanitarian character of what has become the largest package of emergency aid since Russia’s independence. The Western governments and commentators cautioned that Moscow had strategic and nefarious motives in choosing the recipients of its coronavirus aid. This study theorizes humanitarian aid allocations by authoritarian states and tests theoretical expectations using novel data on Russia’s COVID-19 aid allocations. Far from being driven by humanitarian concerns, Russia has used humanitarian assistance for projecting power on the global stage and supporting diverse political objectives. Moscow’s use of humanitarian aid for geopolitical benefits has not been a critical disruptor in the humanitarian system by itself. However, jointly with other instruments of foreign policy, Russia’s approaches to humanitarianism can be detrimental to the future of the international humanitarian system.
Taxonomic diversity assessment across the tree of life from extracellular environmental DNA in aquatic ecosystems
Authors: Manu Shivakumara , Umapathy Govindhaswamy 
Published: February 2023

Global biodiversity is declining at an alarming pace due to
anthropogenic factors. It is
imperative to monitor the health of ecosystems through biodiversity
assessments. But
existing biodiversity assessment approaches are not scalable to assess
the complete
diversity of all the life forms in large ecosystems. We hypothesized
that the extracellular
environmental DNA (eDNA) released by natural cell lysis of biological
matter in aquatic
ecosystems is a repertoire of genetic material from all the inhabiting
organisms and
deep sequencing of extracellular eDNA could enable the detection of taxa
across the
tree of life. We developed a lysis-free and PCR-free workflow to
directly enrich and
sequence extracellular eDNA from environmental water samples and
demonstrate its
utility for taxonomic diversity assessment across the tree of life in a
large biodiverse
model aquatic ecosystem (Ramsar wetland: Chilika lagoon). Using
incidence-based
asymptotic richness analysis, we estimated that Chilika harbors about
1071 families
across the tree of life comprising approximately 799 families of
Eukaryotes, 230 families
of Bacteria, 27 families of Archaea, and 13 families of DNA Viruses. We
also quantified
the compositional changes in the relative abundance of families across
the tree of life
and detected a higher temporal variation (46%) across the seasons than
the spatial
variation (37%) across the lagoon. With the increasing genomic
resources and
decreasing sequencing costs, we envision the wide adoption of
extracellular eDNA-
based taxonomic diversity assessment across the tree of life to track
the future
biodiversity loss and aid the conservation, restoration, and management
efforts in the
Anthropocene.
A coupled-lines system to determine the anteroposterior position of maxillary central incisors for smiling profile esthetics
Authors: Li Bin , Xiang Xiang , Huang Gao , Wang Peiqi , Xue Chaoran , Han Xianglong , Bai Ding , Xu Hui 
Published: February 2023

ABSTRACT

Objectives
To develop a coupled-lines system to determine the anteroposterior position of maxillary central incisors (U1) for smiling profile esthetics.

Materials and Methods
Thirty Asian females with ordinary and good facial harmony were selected as the study sample and the control sample, respectively. Three-dimensional facial images and 45°- and 90°-angled profiles were collected. The anteroposterior relationships between U1 and upper- and mid-facial soft tissue landmarks were measured. By morphing photos of the study sample, two artificial images were created to represent the well-balanced 45°- and 90°-angled profiles and were further processed with combined variations of soft tissue subnasale (SSn)–Glabella and the mid-point of facial axial points of the bilateral central incisor (mFA)–SSn distances. Esthetic assessments were performed on these images by layperson (n = 94) and orthodontist (n = 94) raters.

Results
Both upper- and mid-facial soft tissue landmarks were indispensable in assessing anteroposterior positions of U1 for well-balanced smiling profiles. As assessed in 45°- and 90°-angled profiles, the most esthetically sensitive parameters were mFA-Glabella and mFA-SSn distances. A coupled-lines system was constructed, comprising the Glabella and SSn vertical lines. In smiling profiles with optimal esthetics, the mFA point was at 2 to 5 mm posterior to the Glabella vertical and concomitantly 4 to 7 mm posterior to the SSn vertical, as perceived by orthodontists. Laypersons gave a wider range for mFA-Glabella distances, at 2 to 6 mm.

Conclusions
The coupled-lines system could serve as a reliable reference for determining esthetically optimal anteroposterior positions of U1 for female facial profiles.