Miracle-dz/UniFAR-FTUs huggingface dataset:
C-NAP1 and rootletin restrain DNA damage-induced centriole splitting and facilitate ciliogenesis

Cilia are found on most human cells and exist as motile cilia or non-motile primary cilia. Primary cilia play sensory roles in transducing various extracellular signals, and defective ciliary functions are involved in a wide range of human diseases. Centrosomes are the principal microtubule-organizing centers of animal cells and contain two centrioles. We observed that DNA damage causes centriole splitting in non-transformed human cells, with isolated centrioles carrying the mother centriole markers CEP170 and ninein but not kizuna or cenexin. Loss of centriole cohesion through siRNA depletion of C-NAP1 or rootletin increased radiation-induced centriole splitting, with C-NAP1-depleted isolated centrioles losing mother markers. As the mother centriole forms the basal body in primary cilia, we tested whether centriole splitting affected ciliogenesis. While irradiated cells formed apparently normal primary cilia, most cilia arose from centriolar clusters, not from isolated centrioles. Furthermore, C-NAP1 or rootletin knockdown reduced primary cilium formation. Therefore, the centriole cohesion apparatus at the proximal end of centrioles may provide a target that can affect primary cilium formation as part of the DNA damage response.
The training—injury prevention paradox: should athletes be training smarter and harder?

Background There is dogma that higher training load causes higher injury rates. However, there is also evidence that training has a protective effect against injury. For example, team sport athletes who performed more than 18 weeks of training before sustaining their initial injuries were at reduced risk of sustaining a subsequent injury, while high chronic workloads have been shown to decrease the risk of injury. Second, across a wide range of sports, well-developed physical qualities are associated with a reduced risk of injury. Clearly, for athletes to develop the physical capacities required to provide a protective effect against injury, they must be prepared to train hard. Finally, there is also evidence that under-training may increase injury risk. Collectively, these results emphasise that reductions in workloads may not always be the best approach to protect against injury. Main thesis This paper describes the ‘Training-Injury Prevention Paradox’ model; a phenomenon whereby athletes accustomed to high training loads have fewer injuries than athletes training at lower workloads. The Model is based on evidence that non-contact injuries are not caused by training per se, but more likely by an inappropriate training programme. Excessive and rapid increases in training loads are likely responsible for a large proportion of non-contact, soft-tissue injuries. If training load is an important determinant of injury, it must be accurately measured up to twice daily and over periods of weeks and months (a season). This paper outlines ways of monitoring training load (‘internal’ and ‘external’ loads) and suggests capturing both recent (‘acute’) training loads and more medium-term (‘chronic’) training loads to best capture the player's training burden. I describe the critical variable—acute:chronic workload ratio—as a best practice predictor of training-related injuries. This provides the foundation for interventions to reduce players risk, and thus, time-loss injuries. Summary The appropriately graded prescription of high training loads should improve players’ fitness, which in turn may protect against injury, ultimately leading to (1) greater physical outputs and resilience in competition, and (2) a greater proportion of the squad available for selection each week.
Toward automation of thin optical-fiber submarine cable installation

This paper describes a ROV-based automated cable-laying system that can automatically payout a thin optical-fiber submarine cable while keeping balance with the ground speed and adjusting the degree of cable tautness. This system has been developed to reduce the physical and mental burdens on the ROV operator(s) and to speed up the construction of DONET (Dense Oceanfloor Network System for Earthquakes and Tsunamis). Through several field experiments and the first mission, we became convinced that the automated cable-laying system can accomplish these purposes. In this paper, we first overview the automated cable-laying system and then present some results of the experiments and the first mission. Lastly, we touch the issue associated with the complete automation of the cable-laying operation: from the starting point to the installation of the cable bobbin at the destination.
Cryptochrome 2 variants, chronicity, and seasonality of mood disorders

Departments of Psychiatry and Internal Medicine, Roy J. and Lucille A. Carver College of Medicine, University of Iowa Hospitals and Clinics, Department of Epidemiology, College of Public Health, University of Iowa, Iowa City, Iowa and College of Pharmacy, University of Michigan, Ann Arbor, Michigan, USA Correspondence to Jess G. Fiedorowicz, MD, PhD, University of Iowa Hospitals and Clinics, 200 Hawkins Drive W278GH, Iowa City, IA 52242, USA Tel: + 1 319 384 9267; fax: + 1 319 353 8656; e-mail: jess-fiedorowicz@uiowa.edu
Eating pattern and some factors effective on Body Mass Index in Erzurum province of Turkey

ABSTRACT Normal range of Body Mass Index (BMI) is highly important for a healthy and quality life. BMI has shown increase at significant rate worldwide in recent years. Within this context, a survey was administered to 400 individuals in Erzurum province in order to determine the factors affecting BMI. Regression analysis was employed in the evaluation of the data. According to the results, it was determined that BMI increased with age. In addition, the consumption of butter, bread, and chicken was found to have a significant positive affect on BMI. It was concluded that public awareness should be raised using programs in mass media for a healthy lifestyle through encouraging sports activities and clanging eating habits towards keeping BMI within normal ranges.
A New Kind of Pso: Predator Particle Swarm Optimization

Abstract Today, swarm intelligence is widely used in optimization problems. PSO is one the best swarm intelligence methods. In the method, each particle moves toward the direction in which the best individual and group experience has happened. The most important disadvantage of this method is that it falls in local optima. To fix the problem, a metaheuristic method is proposed in this paper. There has always been a competition between prey and predator in the nature. Little birds often fly in a colony form to run away from birds of prey. Being inspired by the phenomenon, a new particle is added to PSO algorithm known as predator, also a new behavior called “Take flight from predator” is defined. This particle is responsible for attacking the colony of particles so as to prevent the premature convergence. With the predator attack to the colony, particles run away and again the chance rises for a Global optimum to be gained. The attack just caused particles dispersion and no particle dies. It can be repeated for m times and the optimal point is saved each time. To test the method, 12 benchmark functions were employed and the results were compared to OPSO, VPSO, LPSO, and GPSO methods. Regarding the results, the proposed method had a better performance.
Reproducibility of a Parkinsonism‐related metabolic brain network in non‐human primates: A descriptive pilot study with FDG PET

We have previously defined a parkinsonism‐related metabolic brain network in rhesus macaques using a high‐resolution research positron emission tomography camera. This brief article reports a descriptive pilot study to assess the reproducibility of network activity and regional glucose metabolism in independent parkinsonian macaques using a clinical positron emission tomography/CT camera.
Factors Affecting Students' Adoption of ICT Tools in Higher Education Institutions: An Indian Context

In the recent years, technology has been an important component in teaching and learning. The literature has highlighted many studies investigations on the students' intention to use technology in many Western, African and South East Asian countries. This article brings in the factors influencing students' adoption of ICT tools in higher education institutions in India. The Unified Theory of Acceptance and Use of Technology UTAUT model was used to determine the predictors of ICT adoption in learning their coursework in colleges. The results were obtained by structural equation modelling, using the data collected from 398 students doing their undergraduate engineering programs. The findings show that performance expectancy, effort expectancy and social influence has a positive significant relationship on behavioral intention to use ICT tools and facilitating conditions has a direct relationship with usage behaviour. The findings have led to relevant theoretical and practical implications and future researches are suggested.
Autotuning multigrid with PetaBricks

Algorithmic choice is essential in any problem domain to realizing optimal computational performance. Multigrid is a prime example: not only is it possible to make choices at the highest grid resolution, but a program can switch techniques as the problem is recursively attacked on coarser grid levels to take advantage of algorithms with different scaling behaviors. Additionally, users with different convergence criteria must experiment with parameters to yield a tuned algorithm that meets their accuracy requirements. Even after a tuned algorithm has been found, users often have to start all over when migrating from one machine to another. We present an algorithm and autotuning methodology that address these issues in a near-optimal and efficient manner. The freedom of independently tuning both the algorithm and the number of iterations at each recursion level results in an exponential search space of tuned algorithms that have different accuracies and performances. To search this space efficiently, our autotuner utilizes a novel dynamic programming method to build efficient tuned algorithms from the bottom up. The results are customized multigrid algorithms that invest targeted computational power to yield the accuracy required by the user. The techniques we describe allow the user to automatically generate tuned multigrid cycles of different shapes targeted to the user's specific combination of problem, hardware, and accuracy requirements. These cycle shapes dictate the order in which grid coarsening and grid refinement are interleaved with both iterative methods, such as Jacobi or Successive Over-Relaxation, as well as direct methods, which tend to have superior performance for small problem sizes. The need to make choices between all of these methods brings the issue of variable accuracy to the forefront. Not only must the autotuning framework compare different possible multigrid cycle shapes against each other, but it also needs the ability to compare tuned cycles against both direct and (non-multigrid) iterative methods. We address this problem by using an accuracy metric for measuring the effectiveness of tuned cycle shapes and making comparisons over all algorithmic types based on this common yardstick. In our results, we find that the flexibility to trade performance versus accuracy at all levels of recursive computation enables us to achieve excellent performance on a variety of platforms compared to algorithmically static implementations of multigrid. Our implementation uses PetaBricks, an implicitly parallel programming language where algorithmic choices are exposed in the language. The PetaBricks compiler uses these choices to analyze, autotune, and verify the PetaBricks program. These language features, most notably the autotuner, were key in enabling our implementation to be clear, correct, and fast.
High-performance work systems in health care management, Part 1: Development of an evidence-informed model

Background: Although management practices are recognized as important factors in improving health care quality and efficiency, most research thus far has focused on individual practices, ignoring or underspecifying the contexts within which these practices are operating. Research from other industries, which has increasingly focused on systems rather than individual practices, has yielded results that may benefit health services management. Purpose: Our goal was to develop a conceptual model on the basis of prior research from health care as well as other industries that could be used to inform important contextual considerations within health care. Methodology/Approach: Using theoretical frameworks from A. Donabedian (1966), P. M. Wright, T. M. Gardner, and L. M. Moynihan (2003), and B. Schneider, D. B. Smith, and H. W. Goldstein (2000) and review methods adapted from R. Pawson (2006b), we reviewed relevant research from peer-reviewed and other industry-relevant sources to inform our model. The model we developed was then reviewed with a panel of practitioners, including experts in quality and human resource management, to assess the applicability of the model to health care settings. Findings: The resulting conceptual model identified four practice bundles, comprising 14 management practices as well as nine factors influencing adoption and perceived sustainability of these practices. The mechanisms by which these practices influence care outcomes are illustrated using the example of hospital-acquired infections. In addition, limitations of the current evidence base are discussed, and an agenda for future research in health care settings is outlined. Practice Implications: Results may help practitioners better conceptualize management practices as part of a broader system of work practices. This may, in turn, help practitioners to prioritize management improvement efforts more systematically.
Learning Likely Invariants to Explain Why a Program Fails

Debugging is difficult. Recent studies show that automatic bug localization techniques have limited usefulness. One of the reasons is that programmers typically have to understand why the program fails before fixing it. In this work, we aim to help programmers understand a bug by automatically generating likely invariants which are violated in the failed tests. Given a program with an initial assertion and at least one test case failing the assertion, we first generate random test cases, identify potential bug locations through bug localization, and then generate program state mutation based on active learning techniques to identify a predicate "explaining" the cause of the bug. The predicate is a classifier for the passed test cases and failed test cases. Our main contribution is the application of invariant learning for bug explanation, as well as a novel approach to overcome the problem of lack of test cases in practice. We apply our method to real-world bugs and show the generated invariants are often correlated to the actual bug fixes.
Co-Integration of an RF Energy Harvester Into a 2.4 GHz Transceiver

This paper presents an RF energy harvester embedded in a low-power transceiver (TRX) front-end. Both the harvester and the TRX use the same antenna and operate at the same frequency of 2.4 GHz. To decouple the harvester from the TRX, different concepts are proposed regarding the transmitter (TX) and receiver (RX). To avoid loading the TX, the harvester is decoupled with an nMOS switch that can be enabled with a start-up rectifier. Concerning the RX, the decoupling mechanism relies on the nonlinear input impedance of the main RF-DC converter. The harvester also includes a supply management circuit for over-voltage protection and charging energy storage devices with a constant current or voltage. The energy harvester has been co-integrated with the low power TRX in a 130 nm CMOS process and achieves a measured peak power conversion efficiency of 15.9%. For input power levels of at least -9 dBm, it is able to charge up a supply capacitor to a regulated voltage of 1.34 V. The impact of the harvester on the TRX performance is measured with respect to an identical TRX front-end without harvester, showing little impact on the TRX performance. Both TX output power and RX noise figure are degraded by less than 0.5 dB. As an additional feature, the start-up rectifier is also used for demodulation of On-Off-Keying (OOK) signaling, which can be used as a secondary wake-up channel. Since the required area for the harvester is only 0.019 mm2 (≈ 2% of the total active TRX area), it can be added to the TRX at almost no cost.
Anodal tDCS over the Motor Cortex on Prepared and Unprepared Responses in Young Adults

Anodal transcranial direct current stimulation (tDCS) over the primary motor cortex (M1) has been proposed as a possible therapeutic rehabilitation technique for motor impairment. However, despite extensive investigation into the effects of anodal tDCS on motor output, there is little information on how anodal tDCS affects response processes. In this study, we used a cued go/nogo task with both directional and non-directional cues to assess the effects of anodal tDCS over the dominant (left) primary motor cortex on prepared and unprepared motor responses. Three experiments explored whether the effectiveness of tDCS varied with timing between stimulation and test. Healthy, right-handed young adults participated in a double-blind randomised controlled design with crossover of anodal tDCS and sham stimulation. In Experiment 1, twenty-four healthy young adults received anodal tDCS over dominant M1 at least 40 mins before task performance. In Experiment 2, eight participants received anodal tDCS directly before task performance. In Experiment 3, twenty participants received anodal tDCS during task performance. In all three experiments, participants responded faster to directional compared to non-directional cues and with their right hand. However, anodal tDCS had no effect on go/nogo task performance at any stimulation – test interval. Bayesian analysis confirmed that anodal stimulation had no effect on response speed. We conclude that anodal tDCS over M1 does not improve response speed of prepared or unprepared responses of young adults in a go/nogo task.
Estimating directional epistasis

Epistasis, i.e., the fact that gene effects depend on the genetic background, is a direct consequence of the complexity of genetic architectures. Despite this, most of the models used in evolutionary and quantitative genetics pay scant attention to genetic interactions. For instance, the traditional decomposition of genetic effects models epistasis as noise around the evolutionarily-relevant additive effects. Such an approach is only valid if it is assumed that there is no general pattern among interactions—a highly speculative scenario. Systematic interactions generate directional epistasis, which has major evolutionary consequences. In spite of its importance, directional epistasis is rarely measured or reported by quantitative geneticists, not only because its relevance is generally ignored, but also due to the lack of simple, operational, and accessible methods for its estimation. This paper describes conceptual and statistical tools that can be used to estimate directional epistasis from various kinds of data, including QTL mapping results, phenotype measurements in mutants, and artificial selection responses. As an illustration, I measured directional epistasis from a real-life example. I then discuss the interpretation of the estimates, showing how they can be used to draw meaningful biological inferences.
Impact of advanced autonomous non-medical practitioners in emergency care: protocol for a scoping study

Introduction Emergency care services are looking for new models of care delivery to deal with changing patient demographics and increased pressures. It has been suggested that advanced non-medical practitioners might be valuable for delivering such new models of care. However, it is not clear what the impact of the deployment of advanced non-medical practitioners in emergency care is. This scoping study addresses the following research question: What is known from the literature about the different types of impact of the deployment of advanced (autonomous) non-medical practitioners in emergency care? Methods and analysis A scoping study will be undertaken to examine and map the impact of the deployment of advanced non-medical practitioners in emergency care. The scoping study follows the methodology proposed by Arksey and O'Malley. Searches will be carried out on databases of peer-reviewed literature and other sources to systematically identify and characterise the literature. Papers will be screened using a 2-stage process to identify the most relevant literature. Papers will be screened by title and abstract, followed by full-text review. Data abstraction and synthesis will be performed using a narrative thematic analysis. Ethics and dissemination We will communicate the findings to Health Education England, NHS Improvement and the Royal College of Emergency Medicine through existing links provided by members of the project team. We anticipate that the findings will also be of interest to other similar organisations internationally. By identifying gaps in the research literature, we anticipate that the study will generate recommendations for informing future high-quality research studies about the impact of advanced non-medical practitioners in emergency care as well as in other settings. The research findings will be submitted for publication to relevant peer-reviewed journals as well as professional magazines. The scoping study uses only previously published material, and does not require ethical review.
Application of carbon nanoparticles in laparoscopic sentinel lymph node detection in patients with early-stage cervical cancer

Objective To investigate the value of carbon nanoparticles in identifying sentinel lymph nodes in early-stage cervical cancer. Methods From January 2014 to January 2016, 40 patients with cervical cancer stage IA2–IIA, based on the International Federation of Gynecology and Obstetrics (FIGO) 2009 criteria, were included in this study. The normal cervix around the tumor was injected with a total of 1 mL of carbon nanoparticles (CNP)at 3 and 9 o'clock. All patients then underwent laparoscopic pelvic lymph node dissection and radical hysterectomy. The black-dyed sentinel lymph nodes were removed for routine pathological examination and immunohistochemical staining. Results Among the 40 patients, 38 patients had at least one sentinel lymph node (SLN). The detection rate was 95% (38/40). One hundred seventy-three SLNs were detected with an average of 3.9 SLNs per side. 25 positive lymph nodes, which included 21 positive SLNs, were detected in 8 (20%) patients. Sentinel lymph nodes were localized in the obturator (47.97%), internal lilac (13.87%), external lilac (26.59%), parametrial (1.16%), and common iliac (8.67%) regions. The sensitivity of the SLN detection was 100% (5/5), the accuracy was 97.37% (37/38), and the negative predictive value was 100. 0% and the false negative rate was 0%. Conclusions Sentinel lymph nodes can be used to accurately predict the pathological state of pelvic lymph nodes in early cervical cancer. The detection rates and accuracy of sentinel lymph node were high. Carbon nanoparticles can be used to trace the sentinel lymph node in early cervical cancer.