Miracle-dz/UniFAR-FTUs huggingface dataset:
High-Accuracy Low-Precision Training

Low-precision computation is often used to lower the time and energy cost of machine learning, and recently hardware accelerators have been developed to support it. Still, it has been used primarily for inference - not training. Previous low-precision training algorithms suffered from a fundamental tradeoff: as the number of bits of precision is lowered, quantization noise is added to the model, which limits statistical accuracy. To address this issue, we describe a simple low-precision stochastic gradient descent variant called HALP. HALP converges at the same theoretical rate as full-precision algorithms despite the noise introduced by using low precision throughout execution. The key idea is to use SVRG to reduce gradient variance, and to combine this with a novel technique called bit centering to reduce quantization error. We show that on the CPU, HALP can run up to $4 \times$ faster than full-precision SVRG and can match its convergence trajectory. We implemented HALP in TensorQuant, and show that it exceeds the validation performance of plain low-precision SGD on two deep learning tasks.
Principal angles preserving property of Gaussian random projection for subspaces

With the complexity of solving large-scale problems increasing, dimension reduction appears more and more important. In the early work, we find that with high probability the affinity and distance between two subspaces will be concentrated around their estimates after Gaussian random projection. When the ambient dimension after projection is sufficiently large, the affinity and distance between two subspaces almost remain unchanged after projection. In this paper, we extend the above results to principal angles (or canonical angles) to reveal the relationship between two subspaces from a more fundamental viewpoint. We theoretically prove that each principal angle will also be concentrated around its estimate with high probability. When the ambient dimension after projection is sufficiently large, it also remains almost unchanged. Numerical simulation verifies the theoretical work.
The Impact of BDNF Polymorphisms on Suicidality in Treatment-Resistant Major Depressive Disorder: A European Multicenter Study

Abstract Background Numerous studies have reported associations between the brain-derived neurotrophic factor (BDNF) gene and psychiatric disorders, including suicidal behavior, although with conflicting results. Methods A total of 250 major depressive disorder patients were collected in the context of a European multicenter resistant depression study and treated with antidepressants at adequate doses for at least 4 weeks. Suicidality was assessed using the Mini International Neuropsychiatric Interview and Hamilton Rating Scale for Depression, and treatment response using the HAM-D. Genotyping was performed for the functional Val66Met polymorphism (rs6265) and 7 additional tagging single nucleotide polymorphisms within the BDNF gene. Results Neither BDNF single markers nor haplotypes were found to be associated with suicide risk and lifetime history of suicide attempts. Gender-specific analyses revealed nonsignificant single marker (rs908867) and haplotypic association with suicide risk in males after multiple testing correction. Analyzing treatment response phenotypes, the functional Val66Met polymorphism as well as rs10501087 showed significant genotypic and haplotypic association with suicide risk in remitters (n=34, 13.6%). Conclusions Considering the sample size, the present findings need to be replicated in larger samples to confirm or refute a role of BDNF in the investigated suicidal behavior phenotypes.
Whole-Genome Sequence of the Novel Enterobacter Bacteriophage Arya with an Integrase Pseudogene, Isolated from the Gut of the Formosan Subterranean Termite

ABSTRACT We isolated and sequenced the novel Enterobacter bacteriophage Arya from termite gut. The genome showed synteny to lytic bacteriophage genomes; however, the genome encodes a truncated, putatively nonfunctional integrase pseudogene. Lysogeny-related genes were previously observed in certain lytic phages, but their role and evolution remain unclear.
Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays

Simultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these measurements is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is greatly complicated by electrical stimulation artifacts across the array, which can exhibit complex and nonlinear waveforms, and overlap temporarily with evoked spikes. Here we develop a scalable algorithm based on a structured Gaussian Process model to estimate the artifact and identify evoked spikes. The effectiveness of our methods is demonstrated in both real and simulated 512-electrode recordings in the peripheral primate retina with single-electrode and several types of multi-electrode stimulation. We establish small error rates in the identification of evoked spikes, with a computational complexity that is compatible with real-time data analysis. This technology may be helpful in the design of future high-resolution sensory prostheses based on tailored stimulation (e.g., retinal prostheses), and for closed-loop neural stimulation at a much larger scale than currently possible. Author Summary Simultaneous electrical stimulation and recording using multi-electrode arrays can provide a valuable technique for studying circuit connectivity and engineering neural interfaces. However, interpreting these recordings is challenging because the spike sorting process (identifying and segregating action potentials arising from different neurons) is largely stymied by electrical stimulation artifacts across the array, which are typically larger than the signals of interest. We develop a novel computational framework to estimate and subtract away this contaminating artifact, enabling the large-scale analysis of responses of possibly hundreds of cells to tailored stimulation. Importantly, we suggest that this technology may also be helpful for the development of future high-resolution neural prosthetic devices (e.g., retinal prostheses).
The Wheat Microbiome Under Four Management Strategies, and Potential for Endophytes in Disease Protection

Manipulating plant-associated microbes to reduce disease or improve crop yields requires a thorough understanding of interactions within the phytobiome. Plants were sampled from a wheat/maize/soybean crop rotation site that implements four different crop management strategies. We analyzed the fungal and bacterial communities of leaves, stems, and roots of wheat throughout the growing season using 16S and fungal internal transcribed spacer 2 rRNA gene amplicon sequencing. The most prevalent operational taxonomic units (OTUs) were shared across all samples, although levels of the low-abundance OTUs varied. Endophytes were isolated from plants, and tested for antagonistic activity toward the wheat pathogen Fusarium graminearum. Antagonistic strains were assessed for plant protective activity in seedling assays. Our results suggest that microbial communities were strongly affected by plant organ and plant age, and may be influenced by management strategy.
Study on loaded condition characteristics of piezoelectric actuator

A stacked piezoelectric actuator is used for precision positioning because of high resolution, large generative force and high responsiveness. When piezoelectric actuators are used in the positioning mechanism it is usually used in compressive pre-load because it is weak for tensile load. There are several reports to investigate characteristics of the piezoelectric actuator in loaded condition.However, there are no detail reports which investigate influences of pre-load on the characteristics of both displacement characteristics and relative permittivity under simultaneous measurement. In this paper, it is shown that the behaviors of displacement and relative permittivity of stacked piezoelectric actuators for the pre-load does not agree with each other at all under the same measurement condition, and that these behaviors are dependent on both amplitude and offset value of input voltage. In the experiments, soft and hard type PZT elements are investigated and difference of the behavior is shown. In addition, influences of the input voltage amplitude and the offset voltage on the behaviors of displacement and relative permittivity for pre-load. As a result, in all types of PZT elements, behaviors of displacement and relative permittivity for pre-load do not agree with each other under the same measurement condition, and these behaviors for load are much different between soft and hard types PZT elements.
After-birth abortion: why should the baby live?

Abortion is largely accepted even for reasons that do not have anything to do with the fetus' health. By showing that (1) both fetuses and newborns do not have the same moral status as actual persons, (2) the fact that both are potential persons is morally irrelevant and (3) adoption is not always in the best interest of actual people, the authors argue that what we call ‘after-birth abortion’ (killing a newborn) should be permissible in all the cases where abortion is, including cases where the newborn is not disabled.
Assessment of a Syndromic Surveillance System Based on Morbidity Data: Results from the Oscour® Network during a Heat Wave

Background Syndromic surveillance systems have been developed in recent years and are now increasingly used by stakeholders to quickly answer questions and make important decisions. It is therefore essential to evaluate the quality and utility of such systems. This study was designed to assess a syndromic surveillance system based on emergency departments' (ED) morbidity rates related to the health effects of heat waves. This study uses data collected during the 2006 heat wave in France. Methods Data recorded from 15 EDs in the Ile-de-France (Paris and surrounding area) from June to August, 2006, were transmitted daily via the Internet to the French Institute for Public Health Surveillance. Items collected included diagnosis (ICD10), outcome, and age. Several aspects of the system have been evaluated (data quality, cost, flexibility, stability, and performance). Periods of heat wave are considered the most suitable time to evaluate the system. Results Data quality did not vary significantly during the period. Age, gender and outcome were completed in a comprehensive manner. Diagnoses were missing or uninformative for 37.5% of patients. Stability was recorded as being 99.49% for the period overall. The average cost per day over the study period was estimated to be €287. Diagnoses of hyperthermia, malaise, dehydration, hyponatremia were correlated with increased temperatures. Malaise was most sensitive in younger and elderly adults but also the less specific. However, overall syndrome groups were more sensitive with comparable specificity than individual diagnoses. Conclusion This system satisfactorily detected the health impact of hot days (observed values were higher than expected on more than 90% of days on which a heat alert was issued). Our findings should reassure stakeholders about the reliability of health impact assessments during or following such an event. These evaluations are essential to establish the validity of the results of syndromic surveillance systems.
Aedes albopictus Mosquito: The Main Vector of the 2007 Chikungunya Outbreak in Gabon

The primary vector at the origin of the 2007 outbreak in Libreville, Gabon is identified as Aedes albopictus, trapped around the nearby French military camp. The Chikungunya virus was isolated from mosquitoes and found to be identical to the A226V circulating human strain. This is the first field study showing the role of the recently arrived species Aedes albopictus in Chikungunya virus transmission in Central Africa, and it demonstrates this species' role in modifying the epidemiological presentation of Chikungunya in Gabon.
Survival advantage of planned haemodialysis over peritoneal dialysis: a cohort study

Background Previous studies comparing the outcomes in haemodialysis (HD) with those in peritoneal dialysis (PD) have yielded conflicting results. Methods The aim of the study was to compare the survival of planned HD versus PD patients in a cohort of adult incident patients who started renal replacement therapy (RRT) between 2006 and 2008 in the nationwide REIN registry (Réseau Epidémiologie et Information en Néphrologie). Patients who started RRT in emergency or stopped RRT within 2 months were excluded. Adjusted Cox models, propensity score matching and marginal structural models (MSMs) were used to compensate for the lack of randomization and provide causal inference from longitudinal data with time-dependent treatments and confounders including transplant censorship, modality change over time and time-varying covariates. Results Among a total of 13 767 dialysis patients, 13% were on PD at initiation of RRT and 87% were on HD. The median survival times were 53.5 months or 4.45 years and 38.6 months or 3.21 years for patients starting on HD and PD, respectively. Regardless of the model used, there was a consistent advantage in terms of survival for HD patients: hazard ratio (HR) 0.76 [95% confidence interval (95% CI) 0.69-0.84] with the Cox model using propensity score; HR 0.67 (95% CI 0.62-0.73) in the Cox model with censorship for each treatment change; and HR 0.82 (95% CI 0.69-0.97) with MSMs. However, MSMs tended to reduce the survival gap between PD and HD patients. Conclusion This large cohort study using various statistical methods to minimize the bias appears to demonstrate a better survival in planned HD than in PD.
Development and psychometric evaluation of a Persian version of the Death Depression Scale-Revised: a cross-cultural adaptation for patients with advanced cancer

Objective The surfacing of thoughts and depressive affect associated with the prospect of death are prevalent among patients with advanced cancer. Because death cognitions and associated negative affect occur along an adaptive-less adaptive continuum, it is essential that valid and reliable instruments are available to measure death depression. The present study aimed to determine the psychometric properties of the Death Depression Scale among Iranian patients with advanced cancer. Methods About 497 cancer patients completed a Persian version of the 21-item Death Depression Scale-Revised. The face, content and construct validity of the scale were ascertained. Reliability was also assessed using internal consistency, construct reliability and intra-class correlation coefficient (ICC). Results Construct validity determined one factor with an eigenvalue greater than 1. The model had a good fit (χ2 (179, N = 248) = 520.345, P < 0.001; χ2/df = 2.907, CFI = 0.916, TLI = 0.902, IFI = 0.917, SRMR = 0.049 and RMSEA = 0.088 (90% confidence interval = 0.079-0.097)) with all factors loadings greater than 0.5 and statistically significant. The internal consistency, construct reliability and ICC were greater than 0.70. Convergent validity of the scale was demonstrated. Conclusions Findings revealed that the Persian version of the Death Depression Scale-Revised is valid and reliable, and may be used to assess and evaluate death depression in Iranian patients with advanced cancer.
A Randomized Controlled Pilot Study on Mindfulness-Based Cognitive Therapy for Unipolar Depression in Patients With Chronic Pain.

OBJECTIVE Chronic pain is a disabling illness, often comorbid with depression. We performed a randomized controlled pilot study on mindfulness-based cognitive therapy (MBCT) targeting depression in a chronic pain population. METHOD Participants with chronic pain lasting ≥ 3 months; DSM-IV major depressive disorder (MDD), dysthymic disorder, or depressive disorder not otherwise specified; and a 16-item Quick Inventory of Depressive Symptomatology-Clinician Rated (QIDS-C₁₆) score ≥ 6 were randomly assigned to MBCT (n = 26) or waitlist (n = 14). We adapted the original MBCT intervention for depression relapse prevention by modifying the psychoeducation and cognitive-behavioral therapy elements to an actively depressed chronic pain population. We analyzed an intent-to-treat (ITT) and a per-protocol sample; the per-protocol sample included participants in the MBCT group who completed at least 4 of 8 sessions. Changes in scores on the QIDS-C₁₆ and 17-item Hamilton Depression Rating Sale (HDRS₁₇) were the primary outcome measures. Pain, quality of life, and anxiety were secondary outcome measures. Data collection took place between January 2012 and July 2013. RESULTS Nineteen participants (73%) completed the MBCT program. No significant adverse events were reported in either treatment group. ITT analysis (n = 40) revealed no significant differences. Repeated-measures analyses of variance for the per-protocol sample (n = 33) revealed a significant treatment × time interaction (F₁,₃₁ = 4.67, P = .039, η²p = 0.13) for QIDS-C₁₆ score, driven by a significant decrease in the MBCT group (t₁₈ = 5.15, P < .001, d = >1.6), but not in the control group (t₁₃ = 2.01, P = .066). The HDRS₁₇ scores did not differ significantly between groups. The study ended before the projected sample size was obtained, which might have prevented effect detection in some outcome measures. CONCLUSIONS MBCT shows potential as a treatment for depression in individuals with chronic pain, but larger controlled trials are needed. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT01473615.
Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation

Commonly used evaluation measures including Recall, Precision, F-Factor and Rand Accuracy are biased and should not be used without clear understanding of the biases, and corresponding identification of chance or base case levels of the statistic. Using these measures a system that performs worse in the objective sense of Informedness, can appear to perform better under any of these commonly used measures. We discuss several concepts and measures that reflect the probability that prediction is informed versus chance. Informedness and introduce Markedness as a dual measure for the probability that prediction is marked versus chance. Finally we demonstrate elegant connections between the concepts of Informedness, Markedness, Correlation and Significance as well as their intuitive relationships with Recall and Precision, and outline the extension from the dichotomous case to the general multi-class case.
An Effective Deferentially Private Data Releasing Algorithm for Decision Tree

Differential privacy is a strong definition for protecting individual privacy in data releasing and mining. However, it is a rigid definition introducing a large amount of noise to the original dataset, which significantly decreases the quality of data mining results. Recently, how to design a suitable data releasing algorithm for data mining purpose is a hot research area. In this paper, we propose a differential private data releasing algorithm for decision tree construction. The proposed algorithm provides a non-interactive data releasing method through which miner can obtain the complete dataset for data mining purpose. With a given privacy budget, the proposed algorithm generalizes the original dataset, and then specializes it in a differential privacy constrain to construct decision trees. As the designed novel scheme selection operation can fully utilize the allocated privacy budget, the data set released by the proposed algorithm can yield better decision tree models than other method. Experimental results demonstrate that the proposed algorithm outperforms existing methods for private decision tree construction.
Narcolepsy with cataplexy and pregnancy: a case–control study

This was a retrospective case–control study in 25 patients with narcolepsy with cataplexy and 75 women in the control group. Patients completed the questionnaire by Maurovich‐Horvat et al. (J. Sleep Res., 2013, 22: 496–512). We personally interviewed 25 patients with narcolepsy with cataplexy using the administered questionnaire regarding conception, pregnancy, delivery, perinatal and breastfeeding periods. Patients with narcolepsy with cataplexy reported 59 pregnancies versus 164 in the control group. In 16 cases (27.1%), a disease before pregnancy was present compared with eight cases (4.9%) in the control group (P < 0.001); among them, extrinsic asthma was reported 11 times in the narcolepsy with cataplexy group (P < 0.005). Patients with narcolepsy with cataplexy more often had a single pregnancy compared with controls (P < 0.05). Gestational diabetes was more frequent in patients with narcolepsy with cataplexy (P < 0.05). Induced deliveries were higher in controls (P < 0.009). No differences were found between the groups in terms of duration of pregnancies and complications during and after delivery, as during the puerperium. Neonates from patients had heavier birth weight (P < 0.015). The breastfeeding period was longer in patients (P < 0.01). Modafinil and methylphenidate were the drugs administered in six pregnancies. No significant differences in depression during pregnancy and during puerperium were found between patients and controls. This is the first case–control study in women with narcolepsy with cataplexy related to pregnancy, delivery, childbirth and puerperium. Data suggest that patients have pregnancy outcomes similar to controls. The prevalence of gestational diabetes was higher in women with narcolepsy with cataplexy. Caesarean sections, complications during delivery and normal perinatal period for infants were similar in both groups. Breastfeeding was longer in patients.
Fecal Microbiota Transplantation in Patients With Blood Disorders Inhibits Gut Colonization With Antibiotic-Resistant Bacteria: Results of a Prospective, Single-Center Study

Background Patients with blood disorders colonized with antibiotic-resistant bacteria (ARB) are prone to systemic infections that are difficult to treat. Reintroduction of commensal bacteria in a murine model of enterococcal colonization of the gut can lead to eradication of enterococci. We hypothesized that fecal microbiota transplantation (FMT) could be used to eradicate ARB in humans. Methods Participants colonized with ARB were treated with intraduodenal FMT according to a prospective protocol (NCT02461199). The primary endpoint was complete ARB decolonization at 1 month after FMT. Secondary endpoints included safety assessment and partial ARB decolonization. Microbiome sequencing was performed to investigate the influence of microbial composition of the transplanted material on the outcome of FMT. Results Twenty-five FMTs were performed in 20 participants (including 40% who had neutropenia) who were colonized by a median of 2 (range, 1-4) strains of ARB. The primary endpoint was reached in 15/25 (60%) of the FMTs and more frequently in cases in which there was no periprocedural use of antibiotics (79% vs 36%, P < .05). Among participants, 15/20 (75%) experienced complete ARB decolonization. There were no severe adverse events, and partial ARB decolonization was observed in 20/25 (80%) of the FMTs. The microbiota composition analysis revealed higher abundance of Barnesiella spp. , Bacteroides, and Butyricimonas and greater bacterial richness in the fecal material, resulting in eradication of Klebsiella pneumoniae compared with nonresponders. Conclusions FMT in patients with blood disorders is safe and promotes eradication of ARB from the gastrointestinal tract. Clinical Trials Registration NCT02461199.