bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sex Difference in Female and Male Ice Swimmers for Different Strokes and Water Categories Over Short and Middle Distances: A Descriptive Study
Authors: Oppermann Janne , Knechtle Beat , Seffrin Aldo , Vancini Rodrigo Luiz , de Lira Claudio Andre Barbosa , Hill Lee , Andrade Marilia Santos 
Published: May 2022

Abstract
Background
Winter swimming developed from a national tradition into a health-improving sport with international competitions. The difference in performance between women and men was thoroughly examined in various sporting disciplines; however, there is little data on winter swimming events. Therefore, this study aims to compare the sex differences in female and male winter swimmers for a distinct stroke over distances of 25 m and 200 m in ice water, freezing water and cold water in the multiple stages of the Winter Swimming World Cup, hosted by the International Winter Swimming Association (IWSA) since 2016.

Methods
All data included in this study were obtained from the official results of the Winter Swimming World Cup, published on the “International Winter Swimming Association” (IWSA) website. The Mann–Whitney U test was used to compare race time between sexes in different swimming strokes and categories of water. In contrast, the Kruskal–Wallis H test was used to compare differences between swimming strokes or water categories for the same sex.

Results
For 25 m and 200 m events of the “IWSA World Cup,” male athletes were faster than female athletes, regardless of stroke and water temperature category. However, the effect size of the difference between the sexes was greater in 25 m than in 200 m for all strokes and water temperatures. Swimming speed for the same-sex differed between the swimming stroke in relation to the water temperature category. Head-up breaststroke was found to be the slowest stroke (p < 0.05).

Conclusion
In water temperatures between − 2° and + 9 °C, men were faster than women in all stages of the “IWSA World Cup,” regardless of the swimming stroke, but the effect size of the difference between the sexes was greater in shorter than in longer events.
The more the better? Comparing two SQD-based learning designs in a teacher training on augmented and virtual reality
Authors: Buchner Josef , Hofmann Martin 
Published: May 2022

AbstractThe purpose of this study was to investigate whether a learning design based entirely on the micro level strategies of the Synthesis of Qualitative Data (SQD) model is better suited to promote teachers augmented and virtual reality-related Will, Skill, and Tool (WST) compared to a learning design based less on the SQD model. To this end, we first developed two learning designs that were randomly distributed across two teacher professional development courses. In one course (n = 23), teachers learned according to our developed and fully SQD-based Tell–Show–Enact–Do (TSED) learning design; in the other course, teachers (n = 22) followed a Tell–Show–Enact (TSE) learning design that was less SQD-based. The results of the quasi-experimental field study show that the developed fully SQD-based TSED learning design is better able to promote the elements WST in teachers regarding the integration of augmented and virtual reality in the classroom. The results of the study have implications for theory and practice. For example, the developed TSED learning design can serve as a blueprint for other teacher educators, and the empirical findings support the micro level strategies recommended in the SQD model. Additional findings are discussed.
Effects of mattress support on sleeping position and low-back pain
Authors: Bolton Roman , Hulshof Hidde , Daanen Hein A. M. , van Dieën Jaap H. 
Published: May 2022

Abstract
Purpose
To determine the efficacy of decreasing spinal curvature – when sleeping laterally – in reducing low-back pain (LBP) and improving sleep quality in people with chronic LBP. Secondly, to investigate whether sleeping positions, nocturnal movements, and skin temperature are related to pain in people with chronic LBP.

Methods
Sixteen subjects with chronic LBP (50% female, mean age 45.6 ± 13.1 years) slept for one night on their own mattress, followed by three nights on an experimental mattress – designed to reduce spinal curvature in lateral sleeping positions – and then a final night again on their own mattress. Sleep positions, nocturnal movements, skin temperature, and room temperature were measured throughout the five nights. Numerical pain ratings for pain while lying, pain on rising, stiffness on rising, sleep quality, and mattress comfort were recorded for both mattresses.

Results
The experimental mattress was associated with 18% (p<.05) lower pain scores while lying and a 25% (p<.01) higher comfort rating. Pain on rising, stiffness on rising, and sleep quality were not different between own and experimental mattress. The relationship between sleep positions and pain scores was non-significant, but pain when rising was positively correlated with nocturnal movement (p<.05) and skin temperature was negatively correlated with pain while lying (p<0.05).

Conclusion
Pain while lying in bed decreased and comfort was higher for the experimental mattress compared to the participants’ own mattresses.
Pocket-sized, wireless-Bluetooth ultrasound system to perform diagnostic and low-complexity interventional procedures in bedridden patients during the COVID-19 pandemic: from intensive care unit to domiciliary service?
Authors: Ossola Christian , Piacentino Filippo , Fontana Federico , Curti Marco , Zorzetto Giada , Coppola Andrea , Carcano Giulio , Venturini Massimo 
Published: May 2022

AbstractThe use of a pocked-sized, wireless-Bluetooth ultrasound portable system with display images presented on a tablet facilitated the work of our radiologists during the first wave of coronavirus disease 2019 (COVID-19) to perform diagnostic and interventional procedures in bedridden patients. The device is equipped with a battery-powered probe without cables that transmits images to a tablet (or a cell phone) through a dedicated App. We hypothesise in future to extend diagnostic and low-complexity interventional procedures from hospitalised patients to at-home patients who are not able to mobilise out of bed or are difficult to transport. This domiciliary service might also reduce the overhead of hospital accesses.
Analytical study of two feature extraction methods in comparison with deep learning methods for classification of small metal objects
Authors: Amraee Somaieh , Chinipardaz Maryam , Charoosaei Mohammadali 
Published: May 2022

AbstractThis paper addresses the efficiency of two feature extraction methods for classifying small metal objects including screws, nuts, keys, and coins: the histogram of oriented gradients (HOG) and local binary pattern (LBP). The desired features for the labeled images are first extracted and saved in the form of a feature matrix. Using three different classification methods (non-parametric K-nearest neighbors algorithm, support vector machine, and naïve Bayesian method), the images are classified into four different classes. Then, by examining the resulting confusion matrix, the performances of the HOG and LBP approaches are compared for these four classes. The effectiveness of these two methods is also compared with the “You Only Look Once” and faster region-based convolutional neural network approaches, which are based on deep learning. The collected image set in this paper includes 800 labeled training images and 180 test images. The results show that the use of the HOG is more efficient than the use of the LBP. Moreover, a combination of the HOG and LBP provides better results than either alone.
Estimation of lifetime attributable risk incidence and mortality for breast cancer attributed to computed tomography of the head in the Niger Delta Region of Nigeria
Authors: Ikubor Joyce Ekeme , Tobi Anwuli Christiana 
Published: May 2022

Abstract
Background
The rising increase in the incidence of breast cancer among women is worrisome and a great concern to all. More disturbing is that the incidence of breast cancer and death has been attributed to exposure to imaging modalities that utilize ionizing radiation such as computed tomography. The aim of this study was to estimate the lifetime attributable risk (LAR) incidence and mortality for breast cancer for female patients who had head computed tomography in two imaging facilities (centres) in the Niger Delta region of Nigeria.

Result
The overall estimated mean effective dose in centres G1 and G2 is 5.76 mSv and 1.54 mSv, respectively. There was a statistical significant difference in the mean effective dose between centres G1 and G2 (P < 0.001). The LAR breast cancer incidence obtained in this study ranged between 0.5 and 26.45 per 100,000 population in centre G1, while in centre G2, it ranged between 0.14 and 6.56 per 100,000 population. The LAR breast cancer mortality obtained in this study ranged between 0.07 and 6.25 per 100,000 population in centre G1, while in centre G2, it ranged between 0.03 and 1.55 per 100,000 population.

Conclusion
The estimated mean LAR of breast cancer incidence and mortality for the women who had head CT examination in the two study centres was found to be minimal to negligible among the female patients of the different age groups in the study population. The overall mean risk of breast cancer incidence was very low in centre G1 and minimal in centre G2. The obtained risk values can be used to optimize the dose delivered to patients and also ensure that CT examinations are justified.
Polar flocks with discretized directions: The active clock model approaching the Vicsek model
Authors: Chatterjee Swarnajit , Mangeat Matthieu , Rieger Heiko 
Published: May 2022

AbstractWe consider the off-lattice two-dimensionalq-state active clock model (ACM) as a natural discretization of the Vicsek model (VM) describing flocking. The ACM consists of particles able to move in the plane in a discrete set ofqequidistant angular directions, as in the active Potts model (APM), with an alignment interaction inspired by the ferromagnetic equilibrium clock model. We find that for a small number of directions, the flocking transition of the ACM has the same phenomenology as the APM, including macrophase separation and reorientation transition. For a larger number of directions, the flocking transition in the ACM becomes equivalent to the one of the VM and displays microphase separation and only transverse bands,i.e., no re-orientation transition. Concomitantly also the transition of theq → ∞limit of the ACM, the active XY model (AXYM), is in the same universality class as the VM. We also construct a coarse-grained hydrodynamic description for the ACM and AXYM akin to the VM.
Legal Spectatorship
Authors: Moore Kelli 
Published: May 2022

In Legal Spectatorship Kelli Moore traces the political origins of the concept of domestic violence through visual culture in the United States. Tracing its appearance in Article IV of the Constitution, slave narratives, police notation, cybernetic theories of affect, criminal trials, and the “look” of the battered woman, Moore contends that domestic violence refers to more than violence between intimate partners—it denotes the mechanisms of racial hierarchy and oppression that undergird republican government in the United States. Moore connects the use of photographic evidence of domestic violence in courtrooms, which often stands in for women’s testimony, to slaves’ silent experience and witnessing of domestic abuse. Drawing on Harriet Jacobs’s Incidents in the Life of a Slave Girl, abolitionist print culture, courtroom witness testimony, and the work of Hortense Spillers, Moore shows how the logic of slavery and antiblack racism also dictates the silencing techniques of the contemporary domestic violence courtroom. By positioning testimony on contemporary domestic violence prosecution within the archive of slavery, Moore demonstrates that domestic violence and its image are haunted by black bodies, black flesh, and black freedom.
Duke University Press Scholars of Color First Book Award recipient
Lactuca virosa Leaf-mediated Biosynthesis of Zinc Oxide Nanoparticles and Estimation of Antimicrobial and Anticancer Activities
Authors: Gharpure Saee , Yadwade Rachana , Ankamwar Balaprasad 
Published: May 2022

Abstract
The antimicrobial potential of zinc oxide nanoparticles biosynthesized from Lactuca virosa leaves was investigated, but they were found to have no antimicrobial effects. Different parameters of nanoparticles and microorganisms influence these antimicrobial capabilities. Because of their inert nature, ZnO nanoparticles displayed no cytotoxicity when tested on HCT-116 cancer cells and can be employed for drug administration. These ZnO nanoparticles can thus be used as a bio-stable vehicle for various biological uses.
Structure of Heme-binding Pocket in Heme Protein is Generally Rigid and can be Predicted by AlphaFold2
Authors: Kondo Hiroko X , Kanematsu Yusuke , Takano Yu 
Published: May 2022

Abstract
AlphaFold2 is a deep-learning algorithm used to predict the tertiary structures of proteins based on their amino acid sequences. We examined whether AlphaFold2 could predict the heme-binding pocket by comparing the structures of heme proteins from the Protein Data Bank and AlphaFold Protein Structure Database. In most cases, the structures showed only minor differences. We also investigated the impact of heme binding on the protein conformation, showing the pocket rigidity. Therefore, AlphaFold2 can predict the structure of the heme-binding pocket.
Evidence synthesis summary formats for clinical guideline development group members: a mixed-methods systematic review protocol
Authors: Sharp Melissa K. , Tyner Barrie , Awang Baki Dayang Anis Binti , Farrell Cormac , Devane Declan , Mahtani Kamal R. , Smith Susan M. , O'Neill Michelle , Ryan Máirín , Clyne Barbara 
Published: May 2022

Introduction: Evidence syntheses, often in the form of systematic reviews, are essential for clinical guideline development and informing changes to health policies. However, clinical guideline development groups (CGDG) are multidisciplinary, and participants such as policymakers, healthcare professionals and patient representatives can face obstacles when trying to understand and use evidence synthesis findings. Summary formats to communicate the results of evidence syntheses have become increasingly common, but it is currently unclear which format is most effective for different stakeholders. This mixed-methods systematic review (MMSR) evaluates the effectiveness and acceptability of different evidence synthesis summary formats for CGDG members. Methods: This protocol follows guidance from the Joanna Briggs Institute on MMSRs and is reported according to the Preferred Reporting Items for Systematic Reviews (PRISMA)-P guideline. A comprehensive search of six databases will be performed with no language restrictions. Primary outcomes are those relating to the effectiveness and preferences for and attitudes towards the different summary formats. We will include qualitative research and randomised controlled trials. Two reviewers will perform title, abstract, and full-text screening. Independent double-extraction of study characteristics and critical appraisal items will be undertaken using a standardised form. We will use a convergent segregated approach to analyse quantitative and qualitative data separately; results will then be integrated. Discussion: The results of this systematic review will provide an overview of the effectiveness and acceptability of different summary formats for evidence synthesis findings. These findings can be helpful for those in or communicating to guideline development groups. The results can also inform the development and pilot-testing of summary formats for evidence summaries.
Optimal Frameworks for Detecting Anomalies in Sensor-Intensive Heterogeneous Networks
Authors: Moghaddass Ramin , Guan Yongtao 
Published: May 2022

Many network/graph structures are continuously monitored by various sensors that are placed at a subset of nodes and edges. The multidimensional data collected from these sensors over time create large-scale graph data in which the data points are highly dependent. Monitoring large-scale attributed networks with thousands of nodes and heterogeneous sensor data to detect anomalies and unusual events is a complex and computationally expensive process. This paper introduces a new generic approach inspired by state-space models for network anomaly detection that can utilize the information from the network topology, the node attributes (sensor data), and the anomaly propagation sets in an integrated manner to analyze the entire network all at once. This article presents how heterogeneous network sensor data can be analyzed to locate the sources of anomalies as well as the anomalous regions in a network, which can be impacted by one or multiple anomalies at any time instance. Experimental results demonstrate the superior performance of our proposed framework in detecting anomalies in attributed graphs. Summary of Contribution: With the increasing availability of large-scale network sensors and rapid advances in artificial intelligence methods, fundamentally new analytical tools are needed that can integrate data collected from sensors across the networks for decision making while taking into account the stochastic and topological dependencies between nodes, sensors, and anomalies. This paper develops a framework to intelligently and efficiently analyze complex and highly dependent data collected from disparate sensors across large-scale network/graph structures to detect anomalies and abnormal behavior in real time. Unlike general purpose (often black-box) machine learning models, this paper proposes a unique framework for network/graph structures that incorporates the complexities of networks and interdependencies between network entities and sensors. Because of the multidisciplinary nature of the paper that involves optimization, machine learning, and system monitoring and control, it can help researchers in both operations research and computer science domains to develop new network-specific computing tools and machine learning frameworks to efficiently manage large-scale network data.
Parallelism measurement method for nontransparent flat parts
Authors: Zhang Juntao , Pan Bo , Liu Huan , Zhu Xu , Kang Renke , Du Dongxing , Guo Jiang 
Published: May 2022

Nontransparent flat parts with weak rigidity are widely used in precision physics experiments, aerospace, and other fields in which parallelism is required. However, existing methods cannot meet requirements due to the limitation of measurement size and accuracy. This paper proposes a new method for measuring parallelism of nontransparent flat parts with high accuracy and then builds a submicrometer-level parallelism measuring system. The 3D model of the whole part is reconstructed by thickness and flatness, which are measured respectively. Subsequently, parallelism is evaluated by the principle of minimum directional zone. The method is verified by an experiment with a thin copper substrate sized

⊘

200

m
m

×

2.48

m
m

on the parallelism measuring system. The experiment result shows that the part’s parallelism is 7.41 µm, and the expanded uncertainty of parallelism measurement system is 0.34 µm,

k
=

2

.
Foundational ingredients of robotic gait training for people with incomplete spinal cord injury during inpatient rehabilitation (FIRST): A randomized controlled trial protocol
Authors: Swank Chad , Holden Alexandria , McDonald Lacy , Driver Simon , Callender Librada , Bennett Monica , Sikka Seema 
Published: May 2022

Introduction
As technological advances allow the use of robotic exoskeleton devices with gait training, there is a critical need to establish a robotic gait training (RGT) program to meet the needs of people with spinal cord injury (SCI) during inpatient rehabilitation. The purposes of this study are to prospectively examine the efficacy of a stakeholder informed RGT program compared to usual care gait training (UC) during inpatient rehabilitation in people with incomplete SCI and compare the intensity of RGT and UC gait training during inpatient rehabilitation.

Study design
128 patients with incomplete SCI admitted to our inpatient rehabilitation facility will be screened for eligibility and randomized to either the RGT or UC group. RGT sessions will use the Ekso robotic exoskeleton [class II medical device (United States FDA)]. UC sessions will use traditional gait training approaches such as manually assisted overground gait training with walkers and orthotics and body weight–supported treadmill training (BWSTT). Our primary outcome is gait function as characterized by the Walking Index for Spinal Cord Injury–II (WISCI-II). Secondary outcomes are gait speed, Spinal Cord Independence Measure (SCIM), Numeric Pain Rating Scale (NPRS), Fatigue Severity Scale (FSS), Penn Spasm Frequency Scale (PSFS), Patient Health Questionnaire-9 (PHQ-9), General Anxiety Disorder– 7 (GAD-7), International Spinal Cord Injury Quality of Life Basic Data Set, and a Qualitative Questionnaire. Assessments of primary and secondary outcomes will occur at admission and discharge from inpatient rehabilitation. General or generalized linear models will be used to analyze differences between groups for all measures.

Clinical impact
Successful completion of this study will provide a usable, replicable, stakeholder informed RGT intervention for use with individuals with incomplete SCI during inpatient rehabilitation.
Acceptance and commitment therapy versus mindfulness-based stress reduction for newly diagnosed head and neck cancer patients: A randomized controlled trial assessing efficacy for positive psychology, depression, anxiety, and quality of life
Authors: Zhang Zheng , Leong Bin Abdullah Mohammad Farris Iman , Shari Nurul Izzah , Lu Ping 
Published: May 2022

Background and aimHead and neck cancer patients are vulnerable to various psychological complications due to the effects of both cancer itself and cancer treatment on patients’ appearance and physical well-being. Nevertheless, few data have been obtained on effective psychosocial interventions that could protect this group of cancer patients’ psychological well-being. Therefore, this three-armed, parallel-group, double-blind, randomized control trial (RCT) aims to evaluate and compare the effects of acceptance and commitment therapy (ACT) and mindfulness-based stress reduction (MBSR) on positive psychology (such as posttraumatic growth [PTG], hope, and optimism), quality of life (QoL), and psychological complications (depression, anxiety, and experiential avoidance) among newly diagnosed head and neck cancer patients.Methods and analysisThis RCT will target newly diagnosed head and neck cancer patients who have been treated only with surgery or who have not yet received any treatment. In total, 120 patients who meet all of the study’s inclusion criteria and none of its exclusion criteria will be randomly assigned into three groups—an ACT group, an MBSR group, and a treatment-as-usual control group—at a 1:1:1 allocation ratio. Participants in the two intervention groups (the ACT and MBSR groups) will undergo an eight-week group intervention program. During this program, each intervention will comprise eight modules based on ACT and MBSR, respectively. Outcome assessments will be performed across a three-point timeline, including before the intervention (t0), immediately after the psychosocial intervention at eight weeks (t1), and six months after the intervention (t2). The primary outcome that will be assessed during this RCT is PTG. Meanwhile, the secondary outcomes that will be evaluated in this study are such as QoL, hope, optimism, depression, anxiety, and experiential avoidance.Trial registration numberNCT04800419(ClinicalTrials.gov). Registered on March 16, 2021.