Miracle-dz/UniFAR-FTUs huggingface dataset:
Interrupting Prolonged Sitting with Intermittent Walking Increases Postprandial Gut Hormone Responses

ABSTRACT Introduction Continuous exercise can increase postprandial gut hormone such as glucagon-like peptide 1 (GLP-1) and peptide YY (PYY) responses, but it is unknown whether interrupting prolonged sitting with intermittent walking elicits this effect. Method Ten participants with central overweight/obesity (7 men and 3 postmenopausal women, 51 ± 5 yr; mean ± SD) completed a randomized crossover study in which they consumed breakfast and lunch in the laboratory while either sitting continuously for the entire 5.5-h period (SIT) or the prolonged sitting interrupted every 20 min by walking briskly (6.4 km·h−1) for 2 min (BREAKS). Blood samples were collected at regular intervals to examine postprandial plasma GLP-1, PYY, and glucose-dependent insulinotropic polypeptide concentrations. Adipose tissue samples were collected at baseline and at the end of the trials to examine changes in net dipeptidyl peptidase 4 secretion from primary explants. Results Mean (95% confidence interval) postprandial GLP-1 and PYY incremental area under curve values were elevated by 26% and 31% in the BREAKS trial versus SIT (8.4 [0.7, 16.1] vs 6.7 [−0.8, 14.2], P = 0.001, and 26.9 [8.1, 45.6] vs 20.4 [5.1, 35.8] nmol·330 min·L−1, P = 0.024, respectively) but without any such effect on glucose-dependent insulinotropic polypeptide (P = 0.076) or net adipose tissue dipeptidyl peptidase 4 secretion (P > 0.05). Conclusions Interrupting prolonged sitting with regular short bouts of brisk walking increases postprandial GLP-1 and PYY concentrations in healthy middle-age men and women with central adiposity.
Understanding the surgeon’s behaviour during robot-assisted surgery: protocol for the qualitative Behav’Robot study

Introduction Robot-assisted surgery is spreading worldwide, accounting for more than 1.2 million procedures in 2019. Data are sparse in the literature regarding the surgeon’s mechanisms that mediate risk-taking during a procedure, especially robot-assisted. This study aims to describe and understand the behaviour of the surgeons during robot-assisted surgery and the change in their behaviour with increasing experience in using the robot. Methods and analysis This is a qualitative study using semistructured interviews with surgeons who perform robot-assisted surgery. An interview guide comprising open questions will be used to ensure that the points to be discussed are systematically addressed during each interview (ie, (1) difference in behaviour and preparation of the surgeon between a standard procedure and a robot-assisted procedure; (2) the influence of proprioceptive modifications, gain in stability and cognitive biases, inherent in the use of a surgical robot and (3) the intrinsic effect of the learning curve on the behaviour of the surgeons. After transcription, interviews will be analysed with the help of NVivo software, using thematic analysis. Ethics and dissemination Since this project examines professional practices in the field of social and human sciences, ethics committee was not required in accordance with current French legislation (Decree no 2017-884, 9 May 2017). Consent from the surgeons is implied by the fact that the interviews are voluntary. Surgeons will nonetheless be informed that they are free to interrupt the interview at any time. Results will be presented in peer-reviewed national and international congresses and submitted to peer-reviewed journals for publication. The communication and publication of the results will be placed under the responsibility of the principal investigator and publications will be prepared in compliance with the ICMJE uniform requirements for manuscripts. Trial registration number NCT04869995.
Characterization of Genetic Diversity and Variation in Pathogenicity of the Rice False Smut Pathogen Ustilaginoidea virens from a Single Source.

Rice false smut, caused by Ustilaginoidea virens, is one of the most destructive fungal diseases in rice-growing countries. Studies of the genetic diversity, evolution, and pathogenicity of U. virens can provide more information for disease control and cultivar breeding. Contrary to previous studies on the genetic diversity of different geographical populations of U. virens, in this study the genetic variation of U. virens from different panicles of the same rice cultivar in a field in Yunnan province was analyzed using SNP molecular markers. A total of 183 polymorphic loci and five haplotypes, hap_1 to hap_5, were identified based on the 1350-bp combined DNA fragment of 127 isolates, showing some genetic diversity. Hap_1 and hap_3 had the highest occurrence, indicating they were the dominant haplotypes in the field. Further analysis showed that most rice panicles could be co-infected by different haplotypes, and even a few spikelets could be co-infected by multiple haplotypes. The phylogeny indicated that all isolates were divided into five genetic groups. Groups Ⅰ, II, and Ⅲ clustered together and distinguished from Groups Ⅳ and Ⅴ. Significant genetic variations in five pairwise comparisons of panicle populations, accounting for 72.45% of the total variation, were found according to FST values. This variation might be caused by different field microenvironments and the uneven distribution of inoculum sources. A UPGMA dendrogram and the population structure revealed that the genetic composition of the isolates collected from YN1, YN2, and YN4, which were dominated by the same genetic subgroup, was different from that collected from YN3. Finally, genetic recombination was found in 11 isolates; hap_2 and hap_5, probably as genetic recombination progenies produced by sexual hybridization between hap_1 and hap_3, acquired a greater virulence than their ancestors according to population structure and pathogenicity analyses. These results will help us understand the genetic diversity, evolution, and infection process of U. virens, aiding in the development of more effective management strategies for rice false smut, including new cultivars with improved resistance.
Clinical Characteristics of Non-Smoking Chronic Obstructive Pulmonary Disease Patients: Findings from the KOCOSS Cohort

ABSTRACT Chronic obstructive pulmonary disease (COPD) has been regarded as a disease of smokers, but the prevalence of non-smoking COPD patients have been reported to be considerable. We investigated differences in clinical characteristics between smoking and non-smoking COPD patients. We used data from the Korea COPD Subgroup Study (KOCOSS) database, which is a multicenter cohort that recruits patients from 54 medical centres in Korea. Comprehensive comparisons of smoking and non-smoking COPD patients were performed based on general characteristics, exacerbations, symptom scores, radiological findings, and lung-function tests. Of the 2477 patients included in the study, 8.1% were non-smokers and 91.9% were smokers. Non-smoking COPD patients were more likely to be female and to have a higher body mass index and lower level of education. Non-smoking COPD patients had more comorbidities, including hypertension, osteoporosis, and gastroesophageal reflux disease, and experienced more respiratory and allergic diseases. No significant differences in exacerbation rates, symptom scores, or exercise capacity scores were observed between the two groups. Smoking COPD patients had more emphysematous lung according to the radiological findings, and non-smoking patients had more tuberculosis-destroyed lung and bronchiectasis. Lung-function testing revealed no significant difference in the forced expiratory capacity in 1 sec between the two groups, but smokers had more rapid lung-function decline in the 5 years of follow-up data. We found differences in general characteristics and radiological findings between smoking and non-smoking COPD patients. No significant differences in exacerbation or symptom scores were observed, but decline in lung function was less steep in non-smoking patients. Supplemental data for this article is available online at https://doi.org/10.1080/15412555.2022. 2053088 .
The Impact of an Electronic Health Record Intervention on Spirometry Completion in Patients with Chronic Obstructive Pulmonary Disease

Abstract Spirometry is necessary to diagnose chronic obstructive pulmonary disease (COPD), yet a large proportion of patients are diagnosed and treated without having received testing. This study explored whether the effects of interventions using the electronic health record (EHR) to target patients diagnosed with COPD without confirmatory spirometry impacted the incidence rates of spirometry referrals and completions. This retrospective before and after study assessed the impact of provider-facing clinical decision support that identified patients who had a diagnosis of COPD but had not received spirometry. Spirometry referrals, completions, and results were ascertained 1.5 years prior to and 1.5 years after the interventions were initiated. Inhaler prescriptions by class were also tallied. There were 10,949 unique patients with a diagnosis of COPD who were eligible for inclusion. 4,895 patients (44.7%) were excluded because they had completed spirometry prior to the cohort start dates. The pre-intervention cohort consisted of 2,622 patients, while the post-intervention cohort had 3,392. Spirometry referral rates pre-intervention were 20.2% compared to 31.6% post-intervention (p < 0.001). Spirometry completion rates rose from 13.2% pre-intervention to 19.3% afterwards (p < 0.001). 61.7% (585 of 948) had no evidence of airflow obstruction. After excluding patients with a diagnosis of asthma, 25.8% (126 of 488) patients who had no evidence of airflow obstruction had prescriptions for long-acting bronchodilators or inhaled steroids. A concerted EHR intervention modestly increased spirometry referral and completion rates in patients with a diagnosis of COPD without prior spirometry and decreased misclassification of disease.
Predictors of postoperative pain, opioid consumption, and functionality after arthroscopic shoulder surgery: A prospective observational study

Purpose This study aims to identify predictors of postoperative pain and opioid consumption after shoulder surgery to help optimize postoperative pain protocols. Study Design Observational cohort study. Methods One thirty-four patients undergoing arthroscopic shoulder repair were included. Variables related to the patient, surgery and anesthesia were collected and correlated with postoperative pain intensity, analgesic consumption, and functionality up to 1-month post-surgery. We used mixed-effect linear models to estimate the association of gender, interscalene block (ISB), preoperative shoulder pain, non-steroidal anti-inflammatory drugs (NSAIDs) consumption before surgery, and type of surgery with each of the following outcomes: postoperative pain scores, opioid consumption, and functionality. We further analyzed the data for pain scores and opioid consumption per body weight using the multiple linear regression analysis to demonstrate the aforementioned associations specifically at 1 h, 6 h, 12 h, 24 h, 72 h, 1 week and 1 month after surgery. Results Omitting the ISB was associated with higher postoperative pain and cumulative opioid consumption over the first 24 h after surgery. Rotator cuff repair and stabilization surgeries were found to be predictive of higher postoperative pain at 24 h, 72 h, and 1 week and lower functionality at 1 week after surgery. Preoperative shoulder pain and NSAIDs consumption were also predictive of postoperative pain and cumulative opioid consumption. Conclusion Omitting a single shot ISB is a strong predictor of postoperative pain and opioid consumption in the early postoperative phase, beyond which the type of surgery, particularly rotator cuff repair and stabilization surgery, emerges as the most important predictor of postoperative pain and functionality.
Arrow Flight

Moving structured data between diﬀerent big data frameworks and/or data warehouses/storage systems often cause signiﬁcant overhead. Most of the time more than 80% of the total time spent in accessing data is elapsed in serialization/de-serialization step. Columnar data formats are gaining popularity in both analytics and transactional databases. Apache Arrow, a uniﬁed columnar in-memory data format promises to provide ef-ﬁcient data storage, access, manipulation and transport. In addition, with the introduction of the Arrow Flight communication capabilities, which is built on top of gRPC, Arrow enables high performance data transfer over TCP networks. Arrow Flight allows parallel Arrow RecordBatch transfer over networks in a platform and language-independent way, and oﬀers high performance, parallelism and security based on open-source standards. In this paper, we bring together some recently implemented use cases of Ar-row Flight with their benchmarking results. These use cases include bulk Arrow data transfer, querying subsystems and Flight as a microservice integration into diﬀerent frameworks to show the throughput and scalability results of this protocol. We show that Flight is able to achieve up to 6000 MB/s and 4800 MB/s throughput for DoGet() and DoPut() operations respectively. On Mellanox ConnectX-3 or Connect-IB interconnect nodes Flight can utilize upto 95% of the total available bandwidth. Flight is scalable and can use upto half of the available system cores eﬃciently for a bidirectional communication. For query systems like Dremio, Flight is order of magnitude faster than ODBC and turbodbc protocols. Arrow Flight based implementation on Dremio performs 20x and 30x better as compared to turbodbc and ODBC connections respectively. We brieﬂy outline some recent Flight based use cases both in big data frameworks like Apache Spark and Dask and remote Arrow data processing tools. We also discuss some limitations and future outlook of Apache Arrow and Arrow Flight as a whole.
Balancing Information with Observation Costs in Deep Reinforcement Learning

The use of reinforcement learning (RL) in scientific applications, such as materials design and automated chemistry, is increasing. A major challenge, however, lies in fact that measuring the state of the system is often costly and time consuming in scientific applications, whereas policy learning with RL requires a measurement after each time step. In this work, we make the measurement costs explicit in the form of a costed reward and propose a framework that enables off-the-shelf deep RL algorithms to learn a policy for both selecting actions and determining whether or not to measure the current state of the system at each time step. In this way, the agents learn to balance the need for information with the cost of information. Our results show that when trained under this regime, the Dueling DQN and PPO agents can learn optimal action policies whilst making up to 50\% fewer state measurements, and recurrent neural networks can produce a greater than 50\% reduction in measurements. We postulate the these reduction can help to lower the barrier to applying RL to real-world scientific applications.
Targeted Advertising Technologies in the ICT Space: A Use Case Driven Analysis

In recent years, the field of information and communication technology has started to change dramatically. Carriers are threatened by high revenue losses requiring them to identify new revenue potentials beyond their core business. Targeted advertising can be one of these revenue opportunities. Christian Schlee provides a broad overview of the latest developments and trends in targeted advertising in the ICT space. The author focuses on the technological aspects of targeted advertising, but also covers business and legal aspects. He analyzes the most interesting use cases in the Web, IPTV, the mobile environment, and in converged scenarios and examines important technological key building blocks.
Simulating Brittle Fracture with Material Points

Large-scale topological changes play a key role in capturing the fine debris of fracturing virtual brittle material. Real-world, tough brittle fractures have dynamic branching behaviour but numerical simulation of this phenomena is notoriously challenging. In order to robustly capture these visual characteristics, we simulate brittle fracture by combining elastodynamic continuum mechanical models with rigid-body methods: A continuum damage mechanics (CDM) problem is solved, following rigid-body impact, to simulate crack propagation by tracking a damage field. We combine the result of this elastostatic continuum model with a novel technique to approximate cracks as a non-manifold mid-surface, which enables accurate and robust modelling of material fragment volumes to compliment fast-and-rigid shatter effects. For enhanced realism, we add fracture detail, incorporating particle damage-time to inform localised perturbation of the crack surface with artistic control. We evaluate our method with numerous examples and comparisons, showing that it produces a breadth of brittle material fracture effects and with low simulation resolution to require much less time compared to fully elastodynamic simulations.
Students’ reflective thinking pattern changes and characteristics of problem solving

ABSTRACT Problem-solving is an action that requires a thinking process to solve a mathematical problem. Reflective thinking is a mental activity that begins with confusion and repeatedly evaluation for problem-solving. The confusion is a doubt experience or mistakes conducted by individuals in determining a solution for problem-solving. The reflective thinkers categorized into productive, connective, and clarification. It distinguishes how problem-solvers overcome confusion. This study reveals the pattern-change and characteristics of analytical geometry problem-solving. The research urgency focuses on identifying characteristics of students’ reflective thinking pattern-change as well as contributing theories in determining indicators of reflective thinking. Research stages include administering analytical geometry problems to students that are solved by think-aloud techniques, making observations on observation and answer sheets, conducting interviews, reducing data, coding processes, analysing data, and concluding. The data include students’ answer sheets, think-aloud transcripts, observation sheets, and interview transcripts. Researchers administered the analytical geometry problems to mathematics education students in some universities in Indonesia. Based on data analysis and discussion, the study successfully concluded that the pattern-changes found are complete, incomplete, consistent, and inconsistent. Further research may focus on the development of an infused learning model in defragmenting students’ reflective thinking.
The Structure of the Dharmadharmatāvibhāga-kārikā as Revealed by Vasubandhu’s Method Presented in the Vyākhyāyukti

This study1 aims to review the ideas that we carry, as a community of thinkers, about the content of the Dharmadharmatāvibhāga and its versified version (kārikās). 2 This reexamination also contributes to the discussion of method and hermeneutics within the field of Buddhist studies. To date, the studies and annotated translations on this particular philosophical text have mostly focused on certain topics (e.g., āśrayaparivr.tti, nirvikalpajñāna) as they relate to Yogācāra and/or Madhyamaka, or as they relate to Mahāmudrā and Dzogchen within the Tibetan and Chinese traditions. They have not yet clearly shown how these notions are developed within the text itself. In order to look at the text itself, Vasubandhu’s five steps presented in the Vyākhyāyukti are used here as a method of analysis. If Vasubandhu’s vr.tti, the Sanskrit fragments, Mipham’s commentary, and works of scholars like Mathes are essential to this research, then the literary work of authors like Riffaterre (1979) or Jauss (2005) has put it in perspective.
Color classification of solid wood floor based on LGBM

With the development of economy, solid wood flooring has become a new favorite of indoor decoration. The color of solid wood floor plays an important role in interior decoration quality. For 108 three types of solid wood floors provided by enterprises, the statistical characteristics of different color spaces of solid wood floor were extracted, and the LGBM model was used to classify and sort the importance of different characteristics to the classification results. Finally, 94.44% accuracy was obtained in 36 images of the test set, and find the effective characteristics of color feature representation of solid wood floor were the first-order moment of a, b channel in Lab color space and the first moment and second moment of H channel in HSV color space. (Abstract)
The Effect of Dual Sensory Impairment and Multimorbidity Patterns on Functional Impairment: A Longitudinal Cohort of Middle-Aged and Older Adults in China

Objective There is an urgent need to evaluate the contribution of several co-existing diseases on health. This study aims to explore the combined effect of dual sensory impairment (DSI) and multimorbidity patterns on functional impairment among middle-aged and older adults in China. Methods Data were from 10,217 adults aged 45 or older from four waves of the China Health and Retirement Longitudinal Study (CHARLS). Sensory impairments were self-reported measures. Multimorbidity patterns were identified by using k-means cluster analyses. Functional impairment was defined using activities of daily living (ADL) scale and instrumental activities of daily living (IADL) scale. Generalized estimating equation models were estimated to assess the effect of co-occurring DSI and multimorbidity on functional impairment. Results DSI prevalence was 50.4%, and multimorbidity prevalence was 37.7% at the baseline. The simultaneous presence of DSI and multimorbidity was associated with increased odds of ADL limitations (OR = 2.27, 95% CI: 2.11–2.43) and IADL limitations (OR = 1.89, 95% CI: 1.77–2.02). Five multimorbidity patterns were identified: the cardio-cerebrovascular pattern, the stomach-arthritis pattern, the respiratory pattern, the hepatorenal pattern, and the unspecified pattern. Compared to DSI only, DSI plus the hepatorenal pattern was most strongly associated with functional impairment (for ADL: OR = 2.70, 95% CI: 2.34–3.12; for IADL: OR = 2.04, 95% CI: 1.77–2.36). Conclusion Middle-aged and older adults with co-occurrence of DSI and multimorbidity are at increased risk of functional impairment, especially those with multimorbidity characterized by the hepatorenal pattern. These findings imply that integrated care for DSI and multimorbidity may be a potent pathway in improving functional status.
Epigenetic Regulation of Nucleotide Excision Repair

Genomic DNA is constantly attacked by a plethora of DNA damaging agents both from endogenous and exogenous sources. Nucleotide excision repair (NER) is the most versatile repair pathway that recognizes and removes a wide range of bulky and/or helix-distorting DNA lesions. Even though the molecular mechanism of NER is well studied through in vitro system, the NER process inside the cell is more complicated because the genomic DNA in eukaryotes is tightly packaged into chromosomes and compacted into a nucleus. Epigenetic modifications regulate gene activity and expression without changing the DNA sequence. The dynamics of epigenetic regulation play a crucial role during the in vivo NER process. In this review, we summarize recent advances in our understanding of the epigenetic regulation of NER.