Miracle-dz/UniFAR-FTUs huggingface dataset:
FPGA-based high-performance time-to-digital converters by utilizing multi-channels looped carry chains

Time-to-digital converters (TDCs) are core components in many applications and numerous works on this theme have been conducted in recent years. For field programmable gate array (FPGA) based TDCs, their overall performance are still not satisfying when compared with application specific integrated circuit (ASIC) based TDCs. We propose multi-channels looped carry chain TDC architecture in this paper in order to narrow down the performance gap between FPGAs and ASICs. An example TDC prototype implemented on a Stratix III FPGA chip by using the proposed method achieves the resolution below 20 ps, the precision root mean square (RMS) below 15 ps, and the differential non-linearity (DNL) and integral non-linearity (INL) within the range of 2 least significant bit (LSB) peak-to-peak value. This performance is very competitive among all existing FPGA-based designs and close to some ASIC-based TDCs.
Data-Driven Subspace Predictive Control of a Nuclear Reactor

This paper introduces a methodology of designing subspace predictive reactor core power control during load-following mode of operation. The central idea is to implement predictive control law directly from the preprocessed input–output data set without using any explicit process model. The controller is designed to include design constraints, feedforward control, and integral control action effectively. Furthermore, time variations in the process are taken into account by recursively updating control parameters with the arrival of new data set. The efficacy of the proposed technique is demonstrated for tracking various load rejection as well as load-following transients for a pressurized water nuclear reactor. A detailed parameter sensitivity analysis is carried out to analyze the controller performance.
Relationship between positive and negative symptoms and neuropsychological scores in frontotemporal dementia and Alzheimer's disease

Patients with dementia, particularly those with frontotemporal dementia (FTD), are reported to display marked negative symptoms, including apathy, lack of initiative, and flattened affect, similar to those observed in schizophrenic patients. However, negative symptoms have yet to be formally quantified in an FTD population. Twenty-seven patients with FTD (11 primarily right-sided, 8 primarily left-sided, and 4 symmetric) and 7 patients with Alzheimer's disease were rated on the Scale for the Assessment of Negative Symptoms, the Positive and Negative Syndrome Scale, and the Emotional Blunting scale. The FTD patients registered significantly more negative symptoms than the Alzheimer's patients, averaging a threefold increase; groups did not significantly differ in positive symptoms. Negative symptom scale scores were negatively correlated with nonverbal executive skills (23–44% shared variance), verbal executive skills (up to 25% shared variance) and verbal memory (up to 20% shared variance), but were unrelated to measures of attention, verbal and nonverbal information processing, nonverbal memory, language, and constructional skill. In contrast, positive symptoms were positively correlated with constructional skill (19% shared variance) and attentional scores (15% shared variance). These findings add to the existing literature relating negative symptoms to anterior cerebral hypofunction, and suggest that positive symptoms, at least in this population, may be tied to increased posterior activation. (JINS, 2003, 9, 698–709.)
Sleep in a comparative context: Investigating how human sleep differs from sleep in other primates.

OBJECTIVES Primates vary in their sleep durations and, remarkably, humans sleep the least per 24-hr period of the 30 primates that have been studied. Using phylogenetic methods that quantitatively situate human phenotypes within a broader primate comparative context, we investigated the evolution of human sleep architecture, focusing on: total sleep duration, rapid eye movement (REM) sleep duration, non-rapid eye movement (NREM) sleep duration, and proportion of sleep in REM. MATERIALS AND METHODS We used two different Bayesian methods: phylogenetic prediction based on phylogenetic generalized least squares and a multistate Onrstein-Uhlenbeck (OU) evolutionary model of random drift and stabilizing selection. RESULTS Phylogenetic prediction confirmed that humans sleep less than predicted for a primate of our body mass, predation risk, brain size, foraging needs, sexual selection, and diet. These analyses further revealed that humans pack an unexpectedly higher proportion of REM sleep within a shorter overall sleep duration, and do so by reducing NREM sleep (rather than increasing REM). The OU model generally confirmed these findings, with shifts along the human lineage inferred for TST, NREM, and proportion of REM, but not for REM. DISCUSSION We propose that the risks and opportunity costs of sleep are responsible for shorter sleep durations in humans, with risks arising from terrestrial sleep involving threats from predators and conspecifics, and opportunity costs because time spent sleeping could be used for learning, creating material objects, and socializing.
Hyper‐CVAD plus nelarabine in newly diagnosed adult T‐cell acute lymphoblastic leukemia and T‐lymphoblastic lymphoma

Nelarabine, a water soluble prodrug of 9‐β‐D‐arabinofuranosylguanine (ara‐G), is a T‐cell specific purine nucleoside analogue. Given its activity in relapsed and refractory T acute lymphoblastic leukemia (T‐ALL) and T lymphoblastic lymphoma (T‐LBL), we sought to define its role in the frontline treatment of adult patients. Therefore, we conducted a single arm phase 2 study to determine the safety and efficacy of nelarabine in combination with hyper‐CVAD in newly diagnosed patients. For induction/consolidation, patients received eight cycles of hyper‐CVAD alternating with high‐dose methotrexate and cytarabine plus two cycles of nelarabine given at a dose of 650 mg/m2 intravenously daily for 5 days. This was followed by thirty months of POMP maintenance chemotherapy with two additional cycles of nelarabine given instead of cycles 6 and 7 of POMP maintenance. Sixty‐seven patients, including 40 with T‐ALL and 26 with T‐LBL, were enrolled. Complete response rates in both T‐ALL and T‐LBL were 87% and 100% respectively. Grade 3 to 4 neurotoxic adverse events were reported in 5 patients. There were 21 relapses (31%) including 2 after allogeneic stem cell transplantation. Median duration of follow‐up was 42.5 months. The 3‐year complete remission duration (CRD) and overall survival (OS) rates were 66% and 65%, respectively. Compared to our historic hyper‐CVAD data, there was no survival benefit with the addition of nelarabine. In conclusion, hyper‐CVAD plus nelarabine was well tolerated and active in the frontline treatment of adult T‐ALL/LBL patients.
An Interactive Adaptive Learning System Based on Agile Learner-Centered Design

Adaptive and interactive Learning concepts has apprehended the interest of educational actors and partners, especially in higher education. However, the implementation of those concepts has faced many challenges, particularly in Interactive Adaptive Learning Systems (IALS). The present paper aims to give the foundation of a framework for an IALS that gives extensive attention at each stage of the design process to the end-user: learners. The system proposed is based on balanced combination of Agile Learning Design and Learner-Centred Design to improve teaching effectiveness, facilitate learning among learners, encourage long life learning and maximize motivation as well as reducing the dropout rate.
Mitochondrial genome of the Neotropical trans-Andean fish Ichthyoelephas longirostris, Steindachner 1879 (Characiformes, Prochilodontidae)

Abstract Ichthyoelephas longirostris is a trans-Andean migratory species belonging to Prochilodontidae family. In this work, the mitochondrial genome of I. longirostris was sequenced by Illumina technology. The 16,840 bp mitogenome encodes 13 proteins, 22 tRNAs, 2 ribosomal RNAs and present a conserved synteny with others species of the Order Characiformes.
Vocational pedagogy among technical vocational education and training teachers

This concept paper discusses selected factors that affect vocational pedagogy among Technical Vocational Education and Training (TVET) teachers. In the process of teaching and learning, teachers have a very important role. To understand the scope of the vocational pedagogy teachers, all components of vocational pedagogy in the Note for the UNESCO-UNEVOC e-Forum have been used in the study as the basic theory. Documents analysis is used in this research such as scientific journals, previous studies and scientific books. Therefore, this concept paper will elaborate on the selected factors that affect vocational pedagogy i.e., teaching and learning strategies, pedagogical decisions and the padagogy wheel.
High resolution SPM imaging of organic molecules with functionalized tips

One of the most remarkable and exciting achievements in the field of scanning probe microscopy (SPM) in the last years is the unprecedented sub-molecular resolution of both atomic and electronic structures of single molecules deposited on solid state surfaces. Despite its youth, the technique has already brought many new possibilities to perform different kinds of measurements, which cannot be accomplished by other techniques. This opens new perspectives in advanced characterization of physical and chemical processes and properties of molecular structures on surfaces. Here, we discuss the history and recent progress of the high resolution imaging with a functionalized probe by means of atomic force microscopy (AFM), scanning tunnelling microscopy (STM) and inelastic electron tunneling spectroscopy (IETS). We describe the mechanisms responsible for the high-resolution AFM, STM and IETS–STM contrast. The complexity of this technique requires new theoretical approaches, where a relaxation of the functionalized probe is considered. We emphasise the similarities of the mechanism driving high-resolution SPM with other imaging methods. We also summarise briefly significant achievements and progress in different branches. Finally we provide brief perspectives and remaining challenges of the further refinement of these high-resolution methods.
Acoustic modeling with a shared phoneme set for multilingual speech recognition without code-switching

This paper proposes a new acoustic modeling method for the automatic speech recognition (ASR) of data, in which multilingual utterances are mixed, without using any language identification technologies. To perform ASR of unknown-language utterance, first, language identification is performed to determine the language. Then, a language-specific ASR system is used to recognize the utterance. Our proposed method does not train language-specific acoustic models but trains an acoustic model that can speech-recognize utterances spoken by some sort of language. To realize multilingual acoustic modeling, we create a new phoneme set by sharing a part of language-specific phonemes with other languages. The shared phoneme set enables the amount of training data to increase on appearance. Therefore, the acoustic model with the shared phoneme set can perform ASR for a minor language (low-resource language) utterance. The experimental result showed that the acoustic model with the shared phoneme set improved ASR performance for a few languages in comparison with the language-specific ASR system in which language identification was perfectly performed.
Relationships between maximal strength of lower limb, anthropometric characteristics and fundamental explosive performance in handball players

Abstract Background The purpose of this study was to examine relationships between lower body muscular strength, anthropometric characteristics and several measures of explosive performance in elite team-handball players. Methods 22 male elite team-handball players (age: 19.1 ± 1.7 years) were studied during the competitive season. Standard anthropometric and body composition measures included body mass index, lower limb and thigh muscle volume, and body fat percentage. Maximal leg strength was determined by a one-repetition maximum (1-RM) half back-squat. Vertical jump performance was assessed using a squat jump (SJ) and a counter movement jump (CMJ). Repeated shuttle-sprint ability (RSA) was tested by 6 (2 × 15 m) shuttle sprints with 20 s of active recovery intervals. The best time in a single shuttle sprint (30m; RSAbest), fastest total time (RSATT) and RSA test performance decrement (RSAdec) were recorded. Agility was measured using a modified T-half test (MAT). Throwing velocities of jump shooting and 3-step throwing were recorded by digital video camera. Results The explained variance of 1-RM half-back-squats ranged from 0.2 % (RSA% Fatigue Index) to 70.1 % (CMJ). Four out of 8 variables (RSA Best Time, CMJ, SJ, throwing velocity of jump shoot) demonstrated an r2 > 0.5. Jump performances seemed closely related to 1-RM half-back-squats. Furthermore, 1-RM half-back-squats were positively correlated with leg and thigh muscle volumes (r = 0.652, r = 0.768). Conclusion The anthropometric characteristics and some physical performance tests are closely related to the maximal strength performance of handball players. Coaches should focus on maximal strength training programs for the lower limbs when seeking improvements in the throwing velocity and jump performance of handball players.
Biasness identification of talk show's host by using twitter data

Biasness is defined as the inclined feelings of a person about any event. It can be positive or negative. Biasness identification of TV talk show's host is an attractive topic to look into due to the influence of these media groups upon the opinion making. We are using twitter tweets upon different TV hosts's talk shows to find biasness. Twitter is a widely used microblog service and social network, where people tweet mostly about current events. Here, we use sentiments analysis to judge the biasness of talk show's host. The nature of the tweets can be judged by the sentiments analysis. We use Support Vector Machine and Naïve Bayes over user's tweets for biasness identification of the host. Furthermore, emoticons are widely used in sentiments over social media. Therefore, we study the frequency of emoticons from the recent Twitter data set. Then, we carry out analysis to examine the biasness through emoticons and sentiment polarity.
Empirical study on variational inference methods for topic models

Abstract In topic modelling, the main computational problem is to approximate the posterior distribution given an observed collection. Commonly, we must resort to variational methods for approximations; however, we do not know which variational variant is the best choice under certain settings. In this paper, we focus on four topic modelling inference methods, including mean-field variation Bayesian, collapsed variational Bayesian, hybrid variational-Gibbs and expectation propagation, and aim to systematically compare them. We analyse them from two perspectives, i.e. the approximate posterior distribution and the type of -divergence; and then empirically compare them on various data-sets by two popular metrics. The empirical results are almost matching our analysis, where they indicate that CVB0 may be the best variational variant for topic models.
Comparative prognostic value of postprocedural creatine kinase myocardial band and high‐sensitivity troponin T in patients with non‐ST‐segment elevation myocardial infarction undergoing percutaneous coronary intervention

We aimed to assess the prognostic value of postprocedural creatine kinase myocardial band (CK‐MB) and cardiac troponin (cTn) in patients with non‐ST‐segment elevation myocardial infarction (NSTEMI). Background: Whether postprocedural CK‐MB or cTn is a better biomarker to stratify the risk after percutaneous coronary intervention (PCI) remains unknown. Methods: This study included 2,077 patients with NSTEMI undergoing early PCI. Peak postprocedural values of CK‐MB and high‐sensitivity cTn T (hs‐cTnT) were analyzed. The primary outcome was 3‐year mortality. Results: The median values of peak postprocedural CK‐MB and hs‐cTnT were 18.3 U L−1 and 0.140 µg L−1, respectively. Overall, 211 patients died during follow‐up. There were 129 deaths in patients with CK‐MB >the median value and 82 deaths in those with CK‐MB ≤the median value (Kaplan–Meier estimates of 3‐year mortality, 18.9% and 14.0%, respectively; hazard ratio [HR] = 1.52, 95% confidence interval [CI] 1.16–2.01; P < 0.001). There were 134 deaths in patients with hs‐cTnT >the median value and 77 deaths in patients with hs‐cTnT ≤the median value (Kaplan–Meier estimates of 3‐year mortality, 19.9% and 13.2%, respectively; HR = 1.90 [1.44–2.52]; P < 0.001). After adjustment, peak postprocedural CK‐MB (adjusted HR = 1.05 [1.02–1.07], P < 0.001 for each 24 U L−1 increment) and hs‐cTnT (adjusted HR = 1.12 [1.01–1.25], P = 0.037 for each unit higher log hs‐cTnT) remained independently associated with the risk of 3‐year mortality. The C‐statistic(s) of the model with CK‐MB and hs‐cTnT were 0.789 [0.757–0.817] and 0.793 [0.762–0.821], respectively (P = 0.585). Conclusion: In patients with NSTEMI undergoing early PCI, peak postprocedural CK‐MB and hs‐cTnT are independently associated with the risk of 3‐year mortality. © 2017 Wiley Periodicals, Inc.
Realistic models of apparent dynamic changes in resting‐state connectivity in somatosensory cortex

Variations over time in resting‐state correlations in blood oxygenation level‐dependent (BOLD) signals from different cortical areas may indicate changes in brain functional connectivity. However, apparent variations over time may also arise from stationary signals when the sample duration is finite. Recently, a vector autoregressive (VAR) null model has been proposed to simulate real functional magnetic resonance imaging (fMRI) data, which provides a robust stationary model for identifying possible temporal dynamic changes in functional connectivity. In this work, we propose a simpler model that uses a filtered stationary dataset. The filtered stationary model generates statistically stationary time series from random data with a single prescribed correlation coefficient that is calculated as the average over the entire time series. In addition, we propose a dynamic model, which is better able to replicate real fMRI connectivity, estimated from monkey brain studies, than the two stationary models. We compare simulated results using these three models with the behavior of primary somatosensory cortex (S1) networks in anesthetized squirrel monkeys at high field (9.4 T), using a sliding window correlation analysis. We found that at short window sizes, both stationary models reproduced the distribution of correlations of real signals well, but at longer window sizes, a dynamic model reproduced the distribution of correlations of real signals better than the stationary models. While stationary models replicate several features of real data, a close representation of the behavior of resting‐state data acquired from somatosensory cortex of non‐human primates is obtained only when a dynamic correlation is introduced, suggesting dynamic variations in connectivity are real. Hum Brain Mapp 37:3897–3910, 2016. © 2016 Wiley Periodicals, Inc.
Ensemble of binary tree structured deep convolutional network for image classification

In this paper, we propose an ensemble of tree- structured learning architecture to improve the discriminative capability of deep convolutional neural network (DCNN) for image classification. In the proposed technique, the path from the root node to a leaf node represents a classification rule. Thus, to maximize the classification accuracy, each internal node needs to make an optimal binary decision to the left or the right child node. To this aim, we develop a tree-CNN as a randomized tree to embed a DCNN into each internal node and train the model to determine the best traversing path to predict a class. Classification of some images with similar statistical properties yet belonging to different classes are difficult with the conventional DCNN architecture. Thus, to resolve the problem, we use a coarse-to-fine approach where subsequent networks in children nodes are hierarchically and randomly organized to discriminate smaller sets of classes than those in a parent node. The results from all the individual tree-CNNs are ensembled to make the final decision in classification. The proposed technique is implemented with the state-of-the-art deep network model, i.e., Wide Residual Network DCNN model [19], and is demonstrated with experimental results to outperform the classification performance over the anchor.
Pure Squamous Cell Carcinoma of the Bladder in Western Countries

Introduction: Pure squamous carcinoma (SCC) is a rare entity in western regions. The management of SCC still remains similar to that of transitional carcinoma, although it is a different entity. A retrospective review can be helpful in understanding the biological behavior of this uncommon vesical tumour.Material and Methods: Nineteen consecutive cases of pure SCC of the bladder, not related to bilharziasis or spinal cord injury, are herein reported. Fifteen patients were submitted to radical cystectomy, combined with emasculation in 1 case and unilateral nephroureterectomy in another. Partial cystectomy was performed in 1 patient and transurethral resection followed by radiotherapy in 3 more cases. Involvement of prostatic urethra and upper urinary tract was evident in 9 (47.3%) and 5 patients (26.3%), respectively. Four patients were submitted to neoadjuvant chemotherapy and 1 to presurgical radiotherapy without any objective response. Adjuvant chemotherapy was performed in 3 patients. At a mean follow–up of 52 months, 6 patients (31.5%) are alive without any evidence of disease. SCC antigen was monitored in 5 patients. The possible role of this marker in bladder SCC is discussed.Conclusions: Invasion of the upper urinary tract and prostatic urethra seems more common in SCC than in transitional cell carcinoma. Distant metastases are rare. Most patients die after attempts of locoregional control of the tumor have failed. Extensive surgery is recommended. Preoperative radiotherapy should be considered since pelvic recurrences are the leading cause of progression in squamous cell carcinoma.
Data Collection and Management in Community Engaged Research: Lessons Learned From Two Community-Based Participatory Research Partnerships

Background: Data collection and data management (DCDM) within community-engaged research (CEnR) requires special considerations that differ from those of traditional research. To date, little guidance exists to preemptively help community–academic partnerships anticipate and resolve DCDM issues that may arise.Objective: We sought to provide recommendations for DCDM based on two CEnR research projects.Methods: We used a case study design to describe the DCDM process and lessons learned that were generated through formal and informal discussions between community and academic partners.Lessons Learned: We identified 4 key lessons: 1) CEnR requires a flexible, iterative approach to DCDM, 2) there are trade-offs to having a flexible DCDM approach, 3) responsibilities for DCDM should consider the skill sets and priorities of all partners, and 4) nuances of DC within CEnR has important implications for human subjects and ethics training.Conclusions: Based on our lessons learned, we provide recommendations for how to approach DCDM within CEnR.