Miracle-dz/UniFAR-FTUs huggingface dataset:
Immediate effects of meditation in college students: A pilot study examining the role of baseline attention performance and trait mindfulness

Abstract Objective Determine feasibility of a procedure to identify relationships between preexisting traits and immediate mindfulness meditation (MM) responses in novice college students. Participants Twenty-four novice college students participated between September 2016 and April 2017. Methods We measured trait mindfulness, attention and executive function performance, and immediate MM-related changes in self-reported state mindfulness and state anxiety following a 13-min MM. Results The procedure appeared to be feasible and acceptable to college students. Preliminary findings included increases in state mindfulness and decreases in state anxiety, which appeared to vary by level of trait mindfulness. Better attention performance correlated with greater increases in state mindfulness of body. Conclusion This pilot study demonstrated feasibility of investigating the relationship between baseline traits and college students’ immediate MM responses. Using these methods, future studies can provide a unique examination of MM effects stratified by validated facets of state mindfulness of body and mind.
High Resolution ADC for Ultrasound Color Doppler Imaging Based on MASH Sigma-Delta Modulator

Objective: A high precision quantization ultrasound imaging system, capable of capturing small variances of the echo signal with a wide dynamic range, is important for producing accurate diagnostic outputs. Commercial ultrasound systems, typically utilizing 12 or 14 bits analog-to-digital converters (ADCs), lack the ability to measure blood flow deep inside the tissue and may be affected by surrounding tissue noise. Methods: In this study, we propose a newly designed ADC with over 20-bit resolution. The superior performance was achieved by shaping the quantization noise with a MASH23b-24b-15b sigma-delta modulator (SDM), and filtering the shaped noise at high frequencies by a digital decimation filter. Results: Designed in a mature 0.35 μm CMOS technology and powered by a 3.3 V voltage supply, the proposed SDM integrated circuits (IC) model achieved a signal to noise and distortion ratio (SNDR) of 109.5 dB, and an effective number of bits (ENOB) of 17.9-bit in an 8 MHz bandwidth. Eight identical SDMs were integrated onto one chip, and the entire layout occupied an area of 4.8 mm×5 mm. A total of sixteen 8-channel SDM IC models were connected to all elements of the array transducer. Conclusion: Simulated performance with blood flow evaluation datasets using 12-bit and 20-bit ADCs demonstrates that the proposed 20-bit ADC provides superior overall performance on image contrast and estimation accuracy of the blood speed. Significance: Owing to these advantages, the 20-bit ADC shows promise for future development of ultrasound imaging systems, especially for color Doppler imaging.
Educational Program for Promoting Collaboration Between Community Care Professionals and Convenience Stores

Convenience stores play an important role in supporting community-dwelling older adults’ lives. This study aimed to describe the development of and to evaluate an educational program to promote collaboration between communities and convenience stores in Japan. We developed the educational program based on interviews of convenience store staff to encourage them to collaborate with health/social care professionals for helping older adults. We conducted pre- and post-program questionnaire surveys of 184 participants to evaluate the program. After the program, the total score for attitudes toward dementia (p = .010) improved significantly among the convenience store staff. On the contrary, the score for “solidarity and proactiveness,” a subscale for sense of community, improved significantly among health/social care professionals (p = .003). This educational program can have a significant effect on the perceptions and attitudes for supporting older adults, depending on the participants’ occupations. This educational program could foster community networks, leading to an age-friendly community.
Structure-Preserving Neural Style Transfer

State-of-the-art neural style transfer methods have demonstrated amazing results by training feed-forward convolutional neural networks or using an iterative optimization strategy. The image representation used in these methods, which contains two components: style representation and content representation, is typically based on high-level features extracted from pre-trained classification networks. Because the classification networks are originally designed for object recognition, the extracted features often focus on the central object and neglect other details. As a result, the style textures tend to scatter over the stylized outputs and disrupt the content structures. To address this issue, we present a novel image stylization method that involves an additional structure representation. Our structure representation, which considers two factors: i) the global structure represented by the depth map and ii) the local structure details represented by the image edges, effectively reflects the spatial distribution of all the components in an image as well as the structure of dominant objects respectively. Experimental results demonstrate that our method achieves an impressive visual effectiveness, which is particularly significant when processing images sensitive to structure distortion, e.g. images containing multiple objects potentially at different depths, or dominant objects with clear structures.
Relationship between granulocyte–macrophage colony-stimulating factor, embryo quality, and pregnancy outcomes in women of different ages in fresh transfer cycles: a retrospective study

Abstract This study aimed to explore the effects of low-concentration (0.6 ng/mL) granulocyte–macrophage colony-stimulating factor (GM-CSF) supplementation on human embryo quality and pregnancy outcomes in patients with fresh transfer cycles. The data were retrospectively collected from 719 hyperstimulation cycles of 631 patients divided into two groups: GM-CSF supplementation (0.6 ng/mL, n = 399) and control (n = 320). The embryo quality and pregnancy outcomes were compared. GM-CSF addition significantly increased the available embryo rate (52.0 vs. 48.1%, p < .05). In patients >38 years, it significantly enhanced cleavage (99.4 vs. 97.8%, p < .05) and blastocyst formation (45.7 vs. 34.9%, p < .05) rates but not pregnancy outcomes, including clinical pregnancy (power = 0.160) and implantation (power = 0.204) rates. The lack of a statistically significant difference could be related to low study power. These results suggest that low-concentration GM-CSF addition contributes to embryo quality improvement, especially in patients >38 years. IMPACT STATEMENT What is already known on this subject? Granulocyte–macrophage colony-stimulating factor (GM-CSF) has a beneficial effect on the development of human embryos in assisted reproductive technology. What do the results of this study add? Adding 0.6 ng/mL GM-CSF significantly increased the available embryo rate. In patients over 38 years of age, it statistically significantly enhanced the cleavage rate (99.4 vs. 97.8%, p < .05) and blastocyst formation rate (45.7 vs. 34.9%, p < .05). What are the implications of these findings for clinical practice and/or further research? GM-CSF benefits embryos with poorer development potential and a randomised clinical trial with a larger sample size should be performed.
Transfusion of Anaerobically or Conventionally Stored Blood After Hemorrhagic Shock

ABSTRACT Background: Resuscitation from hemorrhagic shock (HS) by blood transfusion restores oxygen (O2) delivery and provides hemodynamic stability. Current regulations allow red blood cells (RBCs) to be stored and used for up to 42 days. During storage, RBCs undergo many structural and functional changes. These storage lesions have been associated with adverse events and increased mortality after transfusion, increasing the need for improved RBC storage protocols. This study evaluates the efficacy of anaerobically stored RBCs to resuscitate rats from severe HS compared with conventionally stored RBCs. Methods and results: Rat RBCs were stored under anaerobic, anaerobic/hypercapnic, or conventional conditions for a period of 3 weeks. Hemorrhage was induced by controlled bleeding, shock was maintained for 30 min, and RBCs were transfused to restore and maintain blood pressure near the prhemorrhage level. All storage conditions met current regulatory 24-h posttransfusion recovery requirements. Transfusion of anaerobically stored RBCs required significantly less RBC volume to restore and maintain hemodynamics. Anaerobic or anaerobic/hypercapnic RBCs restored hemodynamics better than conventionally stored RBCs. Resuscitation with conventionally stored RBCs impaired indices of left ventricular cardiac function, increased hypoxic tissue staining and inflammatory markers, and affected organ function compared with anaerobically stored RBCs. Conclusions: Resuscitation from HS via transfusion of anaerobically stored RBCs recovered cardiac function, restored hemodynamic stability, and improved outcomes.
Virtual Nursing: The New Reality in Quality Care

The purpose of this article is to report on an innovative new model of care and the effects this model pilot program had on patient satisfaction, staff satisfaction, physician satisfaction, patient quality metrics, and financial metrics. The Virtually Integrated Care team is a model of care that leverages technology to bring an experienced expert nurse into the patients' room virtually. The advanced technology allows the virtual nurse to direct and monitor patient care, interacting with the patient through 6 core roles: patient education, staff mentoring/education, real-time quality/patient safety surveillance, physician rounding, admission activities, and discharge activities.
Multidisciplinary Concussion Management: A Model for Outpatient Concussion Management in the Acute and Post-Acute Settings

Supplemental Digital Content is Available in the Text. Objective: To describe a model of multidisciplinary concussion management and explore management methods in the acute and post-acute settings. Setting: A multidisciplinary concussion management program within a large health system. Participants: Patients with sports and non–sports-related concussions aged 14 to 18 years with persisting concussion symptoms at 4 weeks postinjury or beyond. Design: Pilot randomized controlled trial comparing a subsymptom threshold exercise program with standard-of-care treatment in the post-acute setting. Main Measures: Beck Depression Inventory-II and the Post-Concussion Scale-Revised. Results: Across groups, 60% improvement in concussion symptoms was noted. After removing the influence of depression, the intervention showed a large effect on symptom reduction, with participants in the intervention group improving more than those in the control group. There was no difference in response to the intervention by the sports and nonsports groups. Conclusion: Results demonstrate that exercise intervention is effective in reducing symptoms in adolescents with persisting symptoms. The finding that participants in the control group who underwent education, light activity, and sophisticated monitoring still had meaningful recovery supports the utility of active engagement in a multidisciplinary management program. Finally, depression had a clinically meaningful effect on recovery, highlighting the need for targeted intervention of noninjury factors relevant to persisting symptoms.
Are Individual patient data meta-analyses still needed today in oncology? A discussion focused on Head and Neck oncology

Head and neck cancers are a leading cause of cancer incidence and mortality, with over 800,000 new cases and 400,000 deaths estimated in 2018 by GLOBOCAN [1]. Over the years, a wide range of randomized controlled trials has been conducted to define the best treatment strategies for each disease site and tumor stage. These trials have evaluated the role of chemotherapy, altered fractionated radiotherapy, targeted therapy or radioprotectants. To help define treatment guidelines, individual patient data metaanalyses were conducted by collaborative groups led by the meta-analysis unit at Gustave Roussy Cancer Center, launched in 1994 by Jean Bourhis and Jean-Pierre Pignon. They have focused on the role of chemotherapy [2,3] or altered fractionation radiotherapy [4] in locally advanced head and neck squamous cell cancers (HNSCC), amifostine [5], and chemotherapy in nasopharyngeal cancer (NPC) [6]. Additional works have studied surrogate endpoints for HNSCC [7] and NPC [8], network meta-analyses for HNSCC [9] and NPC [10]; but also the impact of missing data on trial characteristics [11] or the use of alternative relative efficacy metrics such as the restricted mean survival time difference [12]. The aim of this article is to focus on the relevance of meta-analyses today and tomorrow in a world where patients’ and tumors’ genomic profiling and tailored treatment could become the rule. We will concentrate on individual patient data meta-analyses, which is the gold standard for collecting and synthesizing evidence [13]. The medical literature is currently flooded with metaanalyses based on published data. A quick search on Pubmed performed on 28 December 2018 using the keywords ‘head neck cancer’ and the built-in filter ‘meta-analysis’ retrieved 2080 references, with more than 250 new ‘meta-analyses’ performed each year since 2014. A minority of these is synthesizing comparative data prospectively collected, and only a handful is based on individual patient data. What is the process of an individual patient data meta-analysis?
ASPECTS OF SOCIAL BEHAVIOUR OF THE NATAL CLINGING BAT MINI0PTERUS SCHREIBERSI NATALENSIS (A. SMITH, 1834)

Les chauvcs-souris appartenant ä l'espece Miniopterus schreibersi sont de veritables troglodytes ; clles se groupent en un ou plusicurs essaims tres denses au plafond ou sur les parois. Ces essaims sont de tallies tres variables allant de quelques individus ä plusieurs milliers (jusqu'ä 100000). A Uitkmost, Transvaal, les males arrivent dans les grottes d'hibernation au mois de Janvier, les femelies en avril. II est probable que 1'accouplement ait lieu dans les grottes d'hibernation, juste avant celle-ci, au mois d'avril. 11 a etc trouve des colonies de pre-mise-bas dans une grotte du Bushveld, au Transvaal, ou des milliers tant de males que de femelies (ces dernieres etant generalenient gravides) s'etaient groupcs avant le de*part des femelies vers les lieux de misc-bas. Des colonies de mise-bas ont ete trouvees dans deux grottes situces egalernent au Bushveld, oü des milliers de femelles s'etaient assemblers af in de mettre bas. Les premiers jeunes sont nes vers la fin du printemps : fin octobre et debut novembre
Refinement of the crystal structure of ɑ domeykite, a structure related to the A15 type*

The s t ruc tu re of cubic (or at) domeykite , CU3AS, has been reexamined and refined f rom counter da t a . T h e original (1938) and somewhat discredited model proposed by S T E E N B E R G has been fully confirmed. I n addi t ion to t h e relation, previously pointed out by S T E E N B E R G , between this s t ruc ture and the s t ruc tu re of CU15S14, a relation is described between the a -domeyki te s t ruc ture a n d the ß-W s t ruc ture (A 15) type .
High-commitment HR practices and employee voice behavior-empirical evidence from Chinese millennial generation

Employee voice behavior is a kind of extra-role behavior which refers to employees proactively make suggestions to organizations in order to improve working environment and enhance organizational performance. Therefore, how to encourage employee voice behavior is the important issue in the academic field. This paper explores the relationship between millennial employees' perception of high-commitment HR practices (HCHRPs) on their voice behaviors with data from a sample of 140 subordinate-supervisor dyads based multiple regression analysis method. The results indicate that HCHRPs are positively related to employee voice behavior (EVB) and both organization-based self-esteem (OBSE) and organizational identification (OI) partially mediate the effect of HCHRPs on EVB. The findings of this research are of great guiding importance for enterprises to encourage employee voice behavior.
What if we were twice as close to the sun?: findings from a science summer camp serving underrepresented youth

Diversity has been a prevalent issue in the American STEM workforce for a number of years. Efforts to increase diversification have resulted in alternate learning spaces such as makerspaces, after school programs, and technology integrated curriculums. Our study, hosted at a non-profit organization serving underrepresented youth, leveraged the video game Minecraft (MC) as a way to engage summer campers in scientific concepts and inquiries over one week. Reoccurring themes from interviews include familial rules on technology use at home, engaging with STEM in a novel way, and a love for building and creating within MC. We discuss our insight into the discoveries and challenges of these types of STEM-oriented program that takes place in informal settings.
From Reports to Bug-Fix Commits: A 10 Years Dataset of Bug-Fixing Activity from 55 Apache's Open Source Projects

Bugs appear in almost any software development. Solving all or at least a large part of them requires a great deal of time, effort, and budget. Software projects typically use issue tracking systems as a way to report and monitor bug-fixing tasks. In recent years, several researchers have been conducting bug tracking analysis to better understand the problem and thus provide means to reduce costs and improve the efficiency of the bug-fixing task. In this paper, we introduce a new dataset composed of more than 70,000 bug-fix reports from 10 years of bug-fixing activity of 55 projects from the Apache Software Foundation, distributed in 9 categories. We have mined this information from Jira issue track system concerning two different perspectives of reports with closed/resolved status: static (the latest version of reports) and dynamic (the changes that have occurred in reports over time). We also extract information from the commits (if they exist) that fix such bugs from their respective version-control system (Git). We also provide a change analysis that occurs in the reports as a way of illustrating and characterizing the proposed dataset. Once the data extraction process is an error-prone nontrivial task, we believe such initiatives like this could be useful to support researchers in further more detailed investigations.
A Survey on Scheduling Strategies for Workflows in Cloud Environment and Emerging Trends

Workflow scheduling is one of the challenging issues in emerging trends of the distributed environment that focuses on satisfying various quality of service (QoS) constraints. The cloud receives the applications as a form of a workflow, consisting of a set of interdependent tasks, to solve the large-scale scientific or enterprise problems. Workflow scheduling in the cloud environment has been studied extensively over the years, and this article provides a comprehensive review of the approaches. This article analyses the characteristics of various workflow scheduling techniques and classifies them based on their objectives and execution model. In addition, the recent technological developments and paradigms such as serverless computing and Fog computing are creating new requirements/opportunities for workflow scheduling in a distributed environment. The serverless infrastructures are mainly designed for processing background tasks such as Internet-of-Things (IoT), web applications, or event-driven applications. To address the ever-increasing demands of resources and to overcome the drawbacks of the cloud-centric IoT, the Fog computing paradigm has been developed. This article also discusses workflow scheduling in the context of these emerging trends of cloud computing.
Algorithmic Perception of Vertices in Sketched Drawings of Polyhedral Shapes

In this article, visual perception principles were used to build an artificial perception model aimed at developing an algorithm for detecting junctions in line drawings of polyhedral objects that are vectorized from hand-drawn sketches. The detection is performed in two dimensions (2D), before any 3D model is available and minimal information about the shape depicted by the sketch is used. The goal of this approach is to not only detect junctions in careful sketches created by skilled engineers and designers but also detect junctions when skilled people draw casually to quickly convey rough ideas. Current approaches for extracting junctions from digital images are mostly incomplete, as they simply merge endpoints that are near each other, thus ignoring the fact that different vertices may be represented by different (but close) junctions and that the endpoints of lines that depict edges that share a common vertex may not necessarily be close to each other, particularly in quickly sketched drawings. We describe and validate a new algorithm that uses these perceptual findings to merge tips of line segments into 2D junctions that are assumed to depict 3D vertices.
Personalized Recommendation with User Categories of Different Behavior Modes: A Case in an E-Commerce Platform in China

As resources of E-commerce platform grow exponentially in recent years, how to filter and recommend the items that users are interested in from the massive resources has become an increasingly concerned topic in both academia and industry. This paper, based on the users and sales data of Taobao, the biggest E-commerce platform in China, studies the personalized recommendation in the e-commerce scenario. With users' behavior data, this paper first identifies different user groups with different shopping behavior modes. Secondly, recommendation strategies are established for the user group with a low purchase rate. Thirdly, item-based collaborative filtering and user-based collaborative filtering are applied to user groups with different degrees of personalized requirements. The experimental results show that the recommendation algorithm based on different user categories can better adapt to the users with different shopping behavior modes.
Deep Architectures for Crowd Flow Prediction

Crowd flow prediction is significant in crowd management and public security. However, accurate crowd flow prediction is challenging, for it is influenced by numerous complicated factors, such as traffic accidents and weather impact. In this treatise, we recommend two deep crowd flow prediction architectures: P-GRU and P-DBT by introducing a gated recurrent unit network/a deep Bi-LSTM model, regression layer, precipitation record, dropout training method, and residual network. The proposed models possess a nice capacity to dig up the deeply hidden information of crowd flow. Moreover, they are able to make efficient use of crowd flow data and precipitation recordings. The forecast architectures are assessed on taxi trajectory data and bike trajectory data in Chongqing with additional precipitation recordings collected from China Meteorological Data Service Center. Experiments based on two kinds of datasets demonstrate that the proposed models have a more ideal performance in comparison with other model architectures.