Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Tilt-correction of Anteversion on Anteroposterior Pelvic Radiographs in Total Hip Arthroplasty

Despite inaccuracies due to artifact and variations in patient positioning, anteroposterior (AP) radiographs remain the clinical standard for post-operative evaluation of component placement following total hip arthroplasty (THA). However, cup position, specifically anteversion, can be significantly affected by variations in patient positioning on an X-ray. A major cause of such artifact is unaccounted for pelvic tilt. Several methods for correcting the effects of pelvic tilt on radiographic anteversion have been proposed, with varying degrees of accuracy. The purpose of this study was to evaluate the accuracy and reliability of a commonly referenced method for correcting acetabular cup anteversion in a cohort undergoing total hip arthroplasty and determine its appropriateness for use in this population of patients. Radiographs from patients who underwent primary or revision hip arthroplasty between February 2016 and February 2017 were retrospectively reviewed. Corrected anteversion was calculated by measuring the vertical distance between the symphysis pubis and the sacrococcygeal joint, per the method outlined by Tannast et al. This symphococcygeal distance was then applied to Tannast’s nomograms to calculate the magnitude of pelvic tilt. Corrected and uncorrected anteversion values were compared to anteversion values collected intraoperatively using an imageless computer-assisted navigation device. A total of 71 cases were initially eligible for inclusion in the study. The correction method could not be applied in 44% (31/71) of the cases, chiefly due to difficulties in visualizing the required landmarks. In cases where it could be applied, corrected values correlated very poorly with navigation measurements (r = -0.07). Mean corrected anteversion (36.9°, SD: 7.4°) differed from uncorrected anteversion (25.2°, SD: 7.6°) by an average of 13.5° (p<0.001). Mean navigated anteversion (27.4°, SD: 5.7°) differed from corrected values by an average of 10.8° (p=0.16). The evaluated correction method could not be consistently applied to radiographs and did not reliably correct anteversion due to pelvic tilt in this population of patients undergoing hip arthroplasty. This correction method does not appear to be appropriate for use in this patient population.
A Fast, Principled Working Set Algorithm for Exploiting Piecewise Linear Structure in Convex Problems

By reducing optimization to a sequence of smaller subproblems, working set algorithms achieve fast convergence times for many machine learning problems. Despite such performance, working set implementations often resort to heuristics to determine subproblem size, makeup, and stopping criteria. We propose BlitzWS, a working set algorithm with useful theoretical guarantees. Our theory relates subproblem size and stopping criteria to the amount of progress during each iteration. This result motivates strategies for optimizing algorithmic parameters and discarding irrelevant components as BlitzWS progresses toward a solution. BlitzWS applies to many convex problems, including training L1-regularized models and support vector machines. We showcase this versatility with empirical comparisons, which demonstrate BlitzWS is indeed a fast algorithm.
Dynamic Modeling of Streptococcus pneumoniae Competence Provides Regulatory Mechanistic Insights Into Its Tight Temporal Regulation

In the human pathogen Streptococcus pneumoniae, the gene regulatory circuit leading to the transient state of competence for natural transformation is based on production of an auto-inducer that activates a positive feedback loop. About one hundred genes are activated in two successive waves linked by a central alternative sigma factor ComX. This mechanism appears to be fundamental to the biological fitness of S. pneumoniae. We have developed a knowledge-based model of the competence cycle that describes average cell behavior. It reveals that the expression rates of the two competence operon, comAB and comCDE, involved in the positive feedback loop must be coordinated to elicit spontaneous competence. Simulations revealed the requirement for an unknown late com gene product that shuts of competence by impairing ComX activity. Further simulations led to the predictions that the membrane protein ComD bound to CSP reacts directly to pH change of the medium and that blindness to CSP during the post-competence phase is controlled by late DprA protein. Both predictions were confirmed experimentally.
Predicting Purchasing Intent: Automatic Feature Learning using Recurrent Neural Networks

We present a neural network for predicting purchasing intent in an Ecommerce setting. Our main contribution is to address the significant investment in feature engineering that is usually associated with state-of-the-art methods such as Gradient Boosted Machines. We use trainable vector spaces to model varied, semi-structured input data comprising categoricals, quantities and unique instances. Multi-layer recurrent neural networks capture both session-local and dataset-global event dependencies and relationships for user sessions of any length. An exploration of model design decisions including parameter sharing and skip connections further increase model accuracy. Results on benchmark datasets deliver classification accuracy within 98% of state-of-the-art on one and exceed state-of-the-art on the second without the need for any domain / dataset-specific feature engineering on both short and long event sequences.
Antibiotic‐induced effects on scaling relationships and on plant element contents in herbs and grasses

Abstract Plant performance is correlated with element concentrations in plant tissue, which may be impacted by adverse chemical soil conditions. Antibiotics of veterinary origin can adversely affect plant performance. They are released to agricultural fields via grazing animals or manure, taken up by plants and may be stored, transformed or sequestered by plant metabolic processes. We studied the potential effects of three antibiotics (penicillin, sulfadiazine, and tetracycline) on plant element contents (macro‐ and microelements). Plant species included two herb species (Brassica napus and Capsella bursa‐pastoris) and two grass species (Triticum aestivum and Apera spica‐venti), representing two crop species and two noncrop species commonly found in field margins, respectively. Antibiotic concentrations were chosen as to reflect in vivo situations, that is, relatively low concentrations similar to those detected in soils. In a greenhouse experiment, plants were raised in soil spiked with antibiotics. After harvest, macro‐ and microelements in plant leaves, stems, and roots were determined (mg/g). Results indicate that antibiotics can affect element contents in plants. Penicillin exerted the greatest effect both on element contents and on scaling relationships of elements between plant organs. Roots responded strongest to antibiotics compared to stems and leaves. We conclude that antibiotics in the soil, even in low concentrations, lead to low‐element homeostasis, altering the scaling relationships between roots and other plant organs, which may affect metabolic processes and ultimately the performance of a plant.
Statistical Structural Analysis of Familial Spontaneous Epileptic Cats Using Voxel-Based Morphometry

Voxel-based morphometry (VBM) based on high resolution three-dimensional data of magnetic resonance imaging has been developed as a statistical morphometric imaging analysis method to locate brain abnormalities in humans. Recently, VBM has been used for human patients with psychological or neurological disorders such as Alzheimer's disease, Parkinson's disease, and epilepsy. Traditional volumetry using region of interest (ROI) is performed manually and the observer needs detailed knowledge of the neuroanatomy having to trace objects of interest on many slices which can cause artificial errors. In contrast, VBM is an automatic technique that has less observer biases compared to the ROI method. In humans, VBM analysis is performed in patients with epilepsy to detect accurately structural abnormalities. Familial spontaneous epileptic cats (FSECs) have been developed as an animal model of mesial temporal lobe epilepsy. In FSECs, hippocampal asymmetry had been detected using three-dimensional magnetic resonance (MR) volumetry based on the ROI method. In this study, we produced a standard template of the feline brain and compared FSECs and healthy cats using standard VBM analysis. The feline standard template and tissue probability maps were created using 38 scans from 14 healthy cats. Subsequently, the gray matter was compared between FSECs (n = 25) and healthy controls (n = 12) as group analysis and between each FSEC and controls as individual analysis. The feline standard template and tissue probability maps could be created using the VBM tools for humans. There was no significant reduction of GM in the FSEC group compared to the control group. However, 5/25 (20%) FSECs showed significant decreases in the hippocampal and/or amygdaloid regions in individual analysis. Here, we established the feline standard templates of the brain that can be used to determine accurately abnormal zones. Furthermore, like MR volumetry, VBM identified morphometric changes in the hippocampus and/or amygdala in some FSECs.
Rivers shape population genetic structure in Mauritia flexuosa (Arecaceae)

Abstract The Mauritia flexuosa L.f. palm is known as the “tree of life” given its importance as fundamental food and construction resources for humans. The species is broadly distributed in wet habitats of Amazonia and dry habitats of the Amazon and Orinoco river basins and in the Cerrado savanna. We collected 179 individuals from eight different localities throughout these habitats and used microsatellites to characterize their population structure and patterns of gene flow. Overall, we found high genetic variation, except in one savanna locality. Gene flow between populations is largely congruent with river basins and the direction of water flow within and among them, suggesting their importance for seed dispersal. Further, rivers have had a higher frequency of human settlements than forested sites, contributing to population diversity and structure through increased human use and consumption of M. flexuosa along rivers. Gene flow patterns revealed that migrants are sourced primarily from within the same river basin, such as those from Madeira and Tapajós basins. Our work suggests that rivers and their inhabitants are a critical element of the landscape in Amazonia and have impacted the dispersal and subsequent distribution of tropical palm species, as shown by the patterns of genetic variation in M. flexuosa.
Question-Aware Sentence Gating Networks for Question and Answering

Machine comprehension question answering, which finds an answer to the question given a passage, involves high-level reasoning processes of understanding and tracking the relevant contents across various semantic units such as words, phrases, and sentences in a document. This paper proposes the novel question-aware sentence gating networks that directly incorporate the sentence-level information into word-level encoding processes. To this end, our model first learns question-aware sentence representations and then dynamically combines them with word-level representations, resulting in semantically meaningful word representations for QA tasks. Experimental results demonstrate that our approach consistently improves the accuracy over existing baseline approaches on various QA datasets and bears the wide applicability to other neural network-based QA models.
Sexual cannibalism and population viability

Abstract Some behaviours that typically increase fitness at the individual level may reduce population persistence, particularly in the face of environmental changes. Sexual cannibalism is an extreme mating behaviour which typically involves a male being devoured by the female immediately before, during or after copulation, and is widespread amongst predatory invertebrates. Although the individual‐level effects of sexual cannibalism are reasonably well understood, very little is known about the population‐level effects. We constructed both a mathematical model and an individual‐based model to predict how sexual cannibalism might affect population growth rate and extinction risk. We found that in the absence of any cannibalism‐derived fecundity benefit, sexual cannibalism is always detrimental to population growth rate and leads to a higher population extinction risk. Increasing the fecundity benefits of sexual cannibalism leads to a consistently higher population growth rate and likely a lower extinction risk. However, even if cannibalism‐derived fecundity benefits are large, very high rates of sexual cannibalism (>70%) can still drive the population to negative growth and potential extinction. Pre‐copulatory cannibalism was particularly damaging for population growth rates and was the main predictor of growth declining below the replacement rate. Surprisingly, post‐copulatory cannibalism had a largely positive effect on population growth rate when fecundity benefits were present. This study is the first to formally estimate the population‐level effects of sexual cannibalism. We highlight the detrimental effect sexual cannibalism may have on population viability if (1) cannibalism rates become high, and/or (2) cannibalism‐derived fecundity benefits become low. Decreased food availability could plausibly both increase the frequency of cannibalism, and reduce the fecundity benefit of cannibalism, suggesting that sexual cannibalism may increase the risk of population collapse in the face of environmental change.
Criterion-related validity and reliability of the Urdu version of the patient health questionnaire in a sample of community-based pregnant women in Pakistan

Background Depression is one of the most prevalent, yet unrecognized but treatable mental disorders in low and middle income countries (LMICs). In such locations, screening tools that are easy-to-administer, valid, and reliable are needed to assist in detecting symptoms of depression. The Patient Health Questionnaire (PHQ-9) is one of the most widely used depression screeners. However, its applicability to community-based settings of Pakistan is limited by the lack of studies examining its validity and reliability in such settings. The current study aimed to demonstrate the criterion-related validity and internal reliability of the Urdu version of the PHQ-9 in a sample of community-based pregnant women in Pakistan compared to a diagnostic clinical interview, the Structured Clinical Interview for DSM disorders (SCID), using data from a depression treatment cluster randomized trial in rural Pakistan. Methods Pregnant women in a rural, low income sub-district in Pakistan were approached between October 2014 and February 2016 and, after providing informed consent, screened for depression using the Urdu version of the PHQ-9, with a cutoff of ≥10 used to indicate significant depressive symptoms. Following the PHQ-9, the diagnostic module for current major depressive episode of the SCID was administered. We examined the psychometric properties of PHQ-9 compared to SCID as a gold standard, using sensitivity, specificity, and negative and positive predictive value to measure the criterion-related validity of the PHQ-9 as an indicator of symptoms of depression. We computed area under the receiver operating characteristic curve to determine diagnostic accuracy, and used Cronbach’s alpha to assess internal reliability. Results A total of 1,731 women in their third trimester of pregnancy were assessed for major depressive disorder. Of these women, 572 (33%) met the cutoff for significant depressive symptoms on PHQ-9, and 454 (26%) were assessed positive for depression using the SCID. The sensitivity and specificity of PHQ-9 at a cutoff of ≥10 was 94.7% and 88.9%, respectively. The positive and negative predictive values were 75.2% and 97.9%, respectively; and the area under the curve was 0.959. Internal reliability, as measured by Cronbach’s alpha, was 0.844. Discussion Valid and reliable screening tools to assist in detecting symptoms of depressive disorder are needed in low income settings where depressive disorders are highly prevalent. The Urdu version of the PHQ-9 has not been previously validated against a well-known assessment of depression in a community setting among pregnant women in Pakistan. This study demonstrates that the Urdu version of the PHQ-9 has acceptable criterion-related validity and reliability for screening for depressive symptoms in Pakistan among community-based pregnant women; and when the recommended cut-off score of ≥10 is used it can also serve as an accurate screening tool for major depressive disorder.
Safe option-critic: learning safety in the option-critic architecture

Abstract Designing hierarchical reinforcement learning algorithms that exhibit safe behaviour is not only vital for practical applications but also facilitates a better understanding of an agent’s decisions. We tackle this problem in the options framework (Sutton, Precup & Singh, 1999), a particular way to specify temporally abstract actions which allow an agent to use sub-policies with start and end conditions. We consider a behaviour as safe that avoids regions of state space with high uncertainty in the outcomes of actions. We propose an optimization objective that learns safe options by encouraging the agent to visit states with higher behavioural consistency. The proposed objective results in a trade-off between maximizing the standard expected return and minimizing the effect of model uncertainty in the return. We propose a policy gradient algorithm to optimize the constrained objective function. We examine the quantitative and qualitative behaviours of the proposed approach in a tabular grid world, continuous-state puddle world, and three games from the Arcade Learning Environment: Ms. Pacman, Amidar, and Q*Bert. Our approach achieves a reduction in the variance of return, boosts performance in environments with intrinsic variability in the reward structure, and compares favourably both with primitive actions and with risk-neutral options.
Elasticity detection: a building block for internet congestion control

This paper introduces a new metric, "elasticity," which characterizes the nature of cross-traffic competing with a flow. Elasticity captures whether the cross traffic reacts to changes in available bandwidth. We show that it is possible to robustly detect the elasticity of cross traffic at a sender without router support, and that elasticity detection can reduce delays in the Internet by enabling delay-controlling congestion control protocols to be deployed without hurting flow throughput. Our results show that the proposed method achieves more than 85% accuracy under a variety of network conditions, and that congestion control using elasticity detection achieves throughput comparable to Cubic but with delays that are 50--70 ms lower when cross traffic is inelastic.
Phonetic-and-Semantic Embedding of Spoken words with Applications in Spoken Content Retrieval

Word embedding or Word2Vec has been successful in offering semantics for text words learned from the context of words. Audio Word2Vec was shown to offer phonetic structures for spoken words (signal segments for words) learned from signals within spoken words. This paper proposes a two-stage framework to perform phonetic-and-semantic embedding on spoken words considering the context of the spoken words. Stage 1 performs phonetic embedding with speaker characteristics disentangled. Stage 2 then performs semantic embedding in addition. We further propose to evaluate the phonetic-and-semantic nature of the audio embeddings obtained in Stage 2 by parallelizing with text embeddings.In general, phonetic structure and semantics inevitably disturb each other. For example the words “brother” and “sister” are close in semantics but very different in phonetic structure, while the words “brother” and “bother” are in the other way around. But phonetic-and-semantic embedding is attractive, as shown in the initial experiments on spoken document retrieval. Not only spoken documents including the spoken query can be retrieved based on the phonetic structures, but spoken documents semantically related to the query but not including the query can also be retrieved based on the semantics.
ScoutBot: A Dialogue System for Collaborative Navigation

ScoutBot is a dialogue interface to physical and simulated robots that supports collaborative exploration of environments. The demonstration will allow users to issue unconstrained spoken language commands to ScoutBot. ScoutBot will prompt for clarification if the user’s instruction needs additional input. It is trained on human-robot dialogue collected from Wizard-of-Oz experiments, where robot responses were initiated by a human wizard in previous interactions. The demonstration will show a simulated ground robot (Clearpath Jackal) in a simulated environment supported by ROS (Robot Operating System).
Image Super-resolution

Super-resolution is the task of obtaining a high-resolution image of a scene given low resolution image(s) of the scene. Applications of super-resolution include forensic, satellite, medical imaging, surveillance, displaying video on large screens, etc [1]. Obtaining high-resolution images directly via better hardware (better image sensors, larger chip size) is quite costly. Furthermore, most of the smart-phones today would be hard-pressed to incorporate hardware enhancements for achieving high resolution images. Hence, a signal processing approach to increase the resolution of images obtained from the phone camera is desirable.
Comprehension's Role in Persuasion: The Case of Its Moderating Effect on the Persuasive Impact of Source Cues

A study of reactions to a novel product attributed the invention to either an expert or a novice. Comprehension of the product description was manipulated by varying information exposure time (Study 1) and contextual prior knowledge (Study 2). As predicted by the heuristic-systematic model comprehensibility moderated the persuasive impact of source expertise. When comprehension was low, subjects relied on the inventor's expertise in forming their attitudes toward the product, but when comprehension and hence, systematic processing were higher, source expertise had no impact on subjects' attitudes. In a pilot study, however, subjects attributed comprehensibility to the source and derogated incomprehensible communications. Copyright 1991 by the University of Chicago.
La normalisation de l'électricité

Definir les obligations respectives du distributeur d'electricite, du fabricant de materiel et de l'installateur, telle est la tâche a laquelle s'est attelee la normalisation internationale. Il est primordial pour ces trois intervenants d'intervenir au bon moment et au bon niveau afin de faire valoir leurs vues. Les auteurs presentent les travaux majeurs des organismes de normalisalion, et detaillent le contenu de la publication 1000 de la CEI et EN 50160 du CENELEC
Forward-backward truncated Newton methods for convex composite optimization

This paper proposes two proximal Newton-CG methods for convex nonsmooth optimization problems in composite form. The algorithms are based on a a reformulation of the original nonsmooth problem as the unconstrained minimization of a continuously differentiable function, namely the forward-backward envelope (FBE). The first algorithm is based on a standard line search strategy, whereas the second one combines the global efficiency estimates of the corresponding first-order methods, while achieving fast asymptotic convergence rates. Furthermore, they are computationally attractive since each Newton iteration requires the approximate solution of a linear system of usually small dimension.