Miracle-dz/UniFAR-FTUs huggingface dataset:
Significance of the position of the proximal tip of the tibial nail: An important factor related to anterior knee pain

Background: Intramedullary nailing is the treatment of choice for the majority of tibial shaft fractures and anterior knee pain is the most common complication of this surgery; however, its etiology is still unknown. The purpose of this study was to assess the predicting factors related to anterior knee pain following tibial nailing. Materials and Methods: Patients with isolated, unilateral tibial shaft fracture who had undergone tibial nailing were identified retrospectively. Data including age, sex, type of fracture, technique of surgery and location of the nail were collected and finally the association between the above variables and knee pain were analyzed via SPSS software. Results: A total of 95 patients participated in the study. The mean age of the participants was 33.52 ± 1.62, 87 (91.6%) of whom were male and 74 (77.9%) had close fractures respectively. The method of surgery in 60 (63.2%) patients was paratendinous approach and in 35 (36.8%) was transtendinous. Twenty six (27.4%) of the patients had anterior knee pain. There were no significant differences between the two groups of patients with and without knee pain by age, sex, type of fracture and type of surgery (P = 0.952, 0.502, 0.212 and 0.745, respectively). Patients with protrusion of the nail from the anterior cortex had higher risk of developing knee pain after surgery (odds ratio: 2.76, confidence interval: 1.08, 7.08, P = 0.031). Conclusion: The results revealed a higher risk of developing anterior knee pain after tibial nailing in patients with protrusion of the nail from the anterior cortex.
Deep Learning Models for Biomedical Image Analysis

Biomedical image analysis has become critically important to the public health and welfare. However, analyzing biomedical images is time-consuming and labor-intensive, and has long been performed manually by highly trained human experts. As a result, there has been an increasing interest in applying machine learning to automate biomedical image analysis. Recent progress in deep learning research has catalyzed the development of machine learning in learning discriminative features from data with minimum human intervention. Many deep learning models have been designed and achieved superior performance in various data analysis applications. This chapter starts with the basic of deep learning models and some practical strategies for handling biomedical image applications with limited data. After that, case studies of deep feature extraction for gene expression pattern image annotations, imaging data completion for brain disease diagnosis, and segmentation of infant brain tissue images are discussed to demonstrate the effectiveness of deep learning in biomedical image analysis.
DspA/E Contributes to Apoplastic Accumulation of ROS in Non-host A. thaliana

The bacterium Erwinia amylovora is responsible for the fire blight disease of Maleae, which provokes necrotic symptoms on aerial parts. The pathogenicity of this bacterium in hosts relies on its type three-secretion system (T3SS), a molecular syringe that allows the bacterium to inject effectors into the plant cell. E. amylovora-triggered disease in host plants is associated with the T3SS-dependent production of reactive oxygen species (ROS), although ROS are generally associated with resistance in other pathosystems. We showed previously that E. amylovora can multiply transiently in the non-host plant Arabidopsis thaliana and that a T3SS-dependent production of intracellular ROS occurs during this interaction. In the present work we characterize the localization and source of hydrogen peroxide accumulation following E. amylovora infection. Transmission electron microscope (TEM) analysis of infected tissues showed that hydrogen peroxide accumulation occurs in the cytosol, plastids, peroxisomes, and mitochondria as well as in the apoplast. Furthermore, TEM analysis showed that an E. amylovora dspA/E-deficient strain does not induce hydrogen peroxide accumulation in the apoplast. Consistently, a transgenic line expressing DspA/E accumulated ROS in the apoplast. The NADPH oxidase-deficient rbohD mutant showed a very strong reduction in hydrogen peroxide accumulation in response to E. amylovora inoculation. However, we did not find an increase in bacterial titers of E. amylovora in the rbohD mutant and the rbohD mutation did not suppress the toxicity of DspA/E when introgressed into a DspA/E-expressing transgenic line. Co-inoculation of E. amylovora with cycloheximide (CHX), which we found previously to suppress callose deposition and allow strong multiplication of E. amylovora in A. thaliana leaves, led to a strong reduction of apoplastic ROS accumulation but did not affect intracellular ROS. Our data strongly suggest that apoplastic ROS accumulation is one layer of the non-host defense response triggered by the type three effector (T3E) DspA/E, together with callose deposition.
Tomographic Node Placement Strategies and the Impact of the Routing Model

Tomographic techniques can be used for the fast detection of link failures at low cost. Our paper studies the impact of the routing model on tomographic node placement costs. We present a taxonomy of path routing models and provide optimal and near-optimal algorithms to deploy a minimal number of asymmetric and symmetric tomography nodes for basic network topologies under different routing model classes. Intriguingly, we find that in many cases routing according to a more restrictive routing model gives better results: compared to a more general routing model, computing a good placement is algorithmically more tractable and does not entail high monitoring costs, a desirable trade-off in practice.
Peromyscus levipes (Rodentia: Cricetidae)

Abstract Peromyscus levipes Merriam, 1898, commonly called the nimbled-footed deermouse, is 1 of 56 species of Peromyscus. It is often confused with other members of the boylii group; therefore, researchers may need to rely on craniometric and karyotypic data to make a positive identification. P. levipes is found in Mexico on both sides of the Sierra Madre Oriental from central Nuevo Leon and western Tamaulipas to central Veracruz and into the northern slopes of the Transversal Neo volcanic area from Queretaro through Morelos. It has a preference for rocky areas in mixed forest associations, cloud forest, tall sacaton grass, and mixed grasses.
Codebook Design for Memory-Based Quantization of Precoder Matrix in Low-Rate Feedback MIMO Systems with Temporally Correlated Fading

An important transmitter adaptation technique used in multiple-input multiple-output (MIMO) communication systems is precoding based on the dominant right-singular vectors of the channel matrix. These vectors are typically estimated at the receiver, quantized, and fed-back to the transmitter via a low-rate feedback channel. We present a method for designing an efficient low-rate quantizer for the dominant right singular vectors of a MIMO channel matrix, which exploits the memory in the slow-varying channel fading process. A memory-based (recursive) quantizer is considered which quantizes the time-trajectory of points representing the channel subs-spaces on a Grassmannian manifold. The quantizer codebook is optimized with respect to an objective functions which can be directly related to MIMO channel capacity. The main contribution of this paper is the derivation of a stochastic gradient-based algorithm for codebook optimization. Numerical results obtained with channel simulations are presented, which demonstrate the MIMO channel capacity improvement achieved by using the codebooks optimized as proposed in this paper.
Child-Care History, Classroom Composition, and Children's Functioning in Kindergarten

Previous research indicates that exposure to nonparental child care at an earlier age and for more hours predicts, at the individual level, more aggressive and disobedient behavior and greater school preparedness. The present study extended child-care research by investigating classroom-composition effects, that is, effects of the combined child-care histories of all the children in the classroom. Analyses showed that effects at the individual level aggregate at the classroom level: Kindergarten children with limited or no child-care history exhibited more externalizing behavior (e.g., fighting and arguing) and higher academic achievement when schooled in classrooms with more peers who had extensive child-care histories.
Instructing a Reinforcement Learner

In reinforcement learning (RL), rewards have been considered the most important feedback in understanding the environment. However, recently there have been interesting forays into other modes such as using sporadic supervisory inputs. This brings into the learning process richer information about the world of interest. In this paper, we model these supervisory inputs as specific types of instructions that provide information in the form of an expert’s control decision and certain structural regularities in the state space. We further provide a mathematical formulation for the same and propose a framework to incorporate them into the learning process.
Applicability of line outage distribution factors to evaluate distribution network expansion options

Distribution network operators require more advanced planning tools to deal with the challenges of future network planning. An appropriate planning and optimization tool can identify which option for network extension should be selected from available alternatives. However, the evaluation part in these optimization approaches results in many power flow calculations, especially in case of networks which need evaluation of reconfigurability capacity. An iterative approach like the generally accepted AC power flow is a relatively computational expensive evaluation method. Therefore, it is investigated if a linear power flow method with line outage distribution factors (LODFs) can be applied. This paper identifies the trade-off in speed and accuracy of LODFs regarding the evaluation of reconfigurable medium voltage distribution networks.
Vitamin E and nonalcoholic fatty liver disease

Purpose of reviewOxidative stress plays a central role in the transition from simple steatosis to nonalcoholic steatohepatitis (NASH). An effective therapeutic strategy is to target reduction in oxidative stress in NASH patients. The aim of this review is to discuss the role of oxidative stress in NASH and biological activities of vitamin E and present available evidence on the therapeutic efficacy of vitamin E in NASH. Recent findingsIn Pioglitazone versus Vitamin E versus Placebo for the Treatment of Nondiabetic Patients with Nonalcoholic Steatohepatitis (PIVENS) trial, vitamin E therapy demonstrated a significant improvement in steatosis, inflammation, ballooning, and resolution of steatohepatitis in adult patients with aggressive NASH, who do not have diabetes or cirrhosis. Although vitamin E showed a significant resolution of NASH in children, a sustained reduction of alanine aminotransferase was not attained in The Treatment of nonalcoholic fatty liver disease (NAFLD) in Children (TONIC) trial. SummaryThe prevalence of NAFLD is likely to increase over time due to the epidemics of obesity and diabetes. Presently, there is no definitive treatment for NAFLD. Based on available evidence, vitamin E (RRR-&agr;-tocopherol) is only recommended in NASH adults without diabetes or cirrhosis and with aggressive histology. Validation is needed in children before its use can be recommended. Longer follow-up of randomized controlled trials are needed to assess long-term vitamin E safety.
Predicting an Author's Demographics from Text using Topic Modeling Approach

The paper presents an approach to predict personality traits of a writer for the author profiling task of the PAN CLEF 2015. The task aimed at predicting authors’ demographics based on the written tweets of an author. These demographics included traditional authorship attributes of age, gender and various personality traits of an author. We applied topic modeling using LDA as baseline approach and used the generated topic to get hierarchical probabilities of the topics. J48 decision tree was used for training classification model. The trained models were then used to successfully predict the demographics of training and test datasets
A distributed model predictive control (D-MPC) for modular robots in chain configuration

This paper shows the design of a distributed predictive control, applied to a robotic chain of six modules. The dynamic model is obtained for a single module which is validated through the SimMechanics blockset of MATLAB. With the obtained model, a controller is designed using different predictive control strategies to choose the one that shows a better performance in terms of overshoot and settling time. Finally, the predictive control is distributed up to six modules, and its performance is evaluated by varying typical parameters of the predictive control such as the horizons of prediction, the control horizon, and the weights among others.
The Role of Brain-Derived Neurotrophic Factor in Bone Marrow Stromal Cell-Mediated Spinal Cord Repair

The ability of intraspinal bone marrow stromal cell (BMSC) transplants to elicit repair is thought to result from paracrine effects by secreted trophic factors including brain-derived neurotrophic factor (BDNF). Here we used gene therapy to increase or silence BDNF production in BMSCs to investigate the role of BDNF in BMSC-mediated neuroprotection. In a spinal cord organotypic culture, BMSC-conditioned medium significantly enhanced spinal motoneuron survival by 64% compared with culture medium only. Only conditioned medium of BDNF-hypersecreting BMSCs sustained this neuroprotective effect. In a rat model of spinal cord contusion, a BDNF-dependent neuroprotective effect was confirmed; only with a subacute transplant of BDNF-hypersecreting BMSCs were significantly more spared motoneurons found at 4 weeks postinjury compared with vehicle controls. Spared nervous tissue volume was improved by 68% with both control BMSCs and BDNF-hypersecreting BMSCs. In addition, blood vessel density in the contusion with BDNF-hypersecreting BMSCs was 35% higher compared with BMSC controls and sixfold higher compared with vehicle controls. BDNF-silenced BMSCs did not survive the first week of transplantation, and no neuroprotective effect was found at 4 weeks after transplantation. Together, our data broaden our understanding of the role of BDNF in BMSC-mediated neuroprotection and successfully exploit BDNF dependency to enhance anatomical spinal cord repair.
Composition, Abundance and Seasonality of Zooplankton in Mida Creek, Kenya

Samples were collected monthly at four fixed stations in Mida creek from May 1996 to April 1997, in order to determine the species composition, abundance and diversity of phytoplankton and zooplankton collected with 20- and 332-μm mesh size plankton nets respectively. Sampling also included measurement of salinity and temperature. Peaks in phytoplankton abundance occurred in May and January, following the long rains in April-May and the short rains in November-December. Zooplankton densities followed the phytoplankton peaks with the main peak occurring in February after the major phytoplankton bloom. Similarly, smaller peaks occurred in May and March. Copepods dominated the zooplankton forming up to 60% of total species composition. High zooplankton diversity occurred in June-July when zooplankton abundance was lowest as compared to February-March. Spatially, the highest diversity was recorded at station 1 located towards the open sea as compared to the other stations located farther inshore.
Visualizing Past Personal Data Disclosures

Today's rich service offer in the World Wide Web increasingly requires the disclosure of personal user data. Service providers' appetite for personal user data, however, is accompanied by growing privacy implications for Internet users. Addressing this rising threat, privacy-enhancing technologies aim at aiding users in protecting their personal data. Even though effective privacy laws facilitate users to edit and revoke already disclosed personal data, few PET solutions support users in exercising this right. Available tools lack intuitive interfaces and are built on powerful infrastructures on the provider side. In this paper we introduce the Data Disclosure Log component within a user-centric privacy architecture. Built on a browser-based logging extension, we present a visualization tool that displays past personal data disclosures from different perspectives. A graph-based view allows for the dynamic presentation of relations between selected entity types. Such an overview enables users to know the conditions of past personal data transactions at any time. This knowledge represents a prerequisite for an ex post revision or revocation of personal data. Usability and user acceptance of the developed prototype is evaluated in a conducted user test.
Adaptation to altered support and visual conditions during stance: patients with vestibular deficits

Patients whose deficits were limited to clinically well qualified vestibular disorders have been exposed to a number of altered support surface and visual environments while standing unsupported. A six- degrees-of-freedom platform employing movable support surfaces for each foot and a movable visual surround deprived patients of normal inputs derived from a fixed level support surface and from an immobile surround. Various tests employing EMG, force, and body movement recording identified quantitative changes in the patients' strategy for the relative weighting of proprioceptive, vestibular, and visual inputs. The most dramatic performance deficit of patients was their inability to suppress the influence of visual and proprioceptive inputs appropriately whenever motions of external surface disturbed the orientation information provided by these inputs. Thus, the more mildly afflicted patients experienced instability not so much because of the loss of vestibular inputs directly to posture but because of their inappropriate responses to proprioceptive inputs and vision. Discussion is centered on the role of vestibular input as an internal reference system for orientation about which adaptive changes in proprioceptive and visual inputs are made.
Bandwidth Extension of Ultra-wideband Microstrip Antenna Using Metamaterial Double-side Planar Periodic Geometry

A compact extended bandwidth UWB microstrip antenna is designed utilizing metamaterial (MTM) doubleside planar periodic structures. The proposed antenna comprises two MTM unit cells made by etching X-shaped slots on the main radiating patch, and four slots at the vertices of a square periodically repeated in two-dimensions on the ground plane. The proposed antenna fabricated on 1.6 mm low-cost FR4 substrate is compact, measuring 27.6 × 32 mm, with relative permittivity of 4.5 and loss tangent of 0.02. It has a broad bandwidth covering 3.2 to 23.9 GHz, with a peak gain of 6.2 dB at 8.7 GHz. The antenna has good radiation characteristics for UWB applications. The measured return loss (S11) of the test antenna fabricated for this study was in good agreement with the simulated results.
Type Oriented Logic Meta Programming for Java

This paper presents Type-Oriented Logic Meta Programming. The idea is based on a representation of programs as sets of logic propositions focusing on the type properties of the base-language program. This representation allows generation of base-level code from compiletime logic meta programs that manipulate code fragments and their type properties. We apply this idea to Java and present TyRuBa, a Type-Oriented Logic Meta Programming system for Java. We illustrate that TyRuBa subsumes existing proposals for adding parametric and bounded parametric polymorphism to Java and surpasses them in expressive power.
Causal relevance learning for robust classification under interventions

In some classification problems the distribution of the test data is different from that of the training data because of external manip- ulations to the variables we observe. We propose a classification scheme which is robust to outside interventions by identifying causes in the train- ing data, given that causes of a target variable remain predictive even when the data is manipulated. We do this by extending Relevance Learn- ing Vector Quantization (RLVQ), a classification scheme that learns a relevance profile for the classification task presented. Our proposed al- gorithm, Causal-RLVQ, learns a relevance profile that weights causally relevant features more strongly. The algorithm can determine a trade- off between robustness to intervention and accuracy on non-manipulated data, yielding RLVQ as a special case.
Toxicological impact of butralin, glyphosate-isopropylammonium and pendimethalin herbicides on physiological parameters of Biomphalaria alexandrina snails

ABSTRACT Biomphalaria alexandrina snails have been used as bioindicators for freshwater qaulity and the effects of some herbicides such as butralin, glyphosate-isopropylammonium and pendimethalin). In the present study the effect of these three herbicides on snail biochemistry was examined. The results indicated that the herbicides increased alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in the haemolymph of B. alexandrina snails and significantly decreased total protein and albumin content. Light microscopical examinations of haemocytes monolayers of B. alexandrina snails showed three different cell types (small cells, granulocytes and hyalinocytes). All three herbicides caused abnormalities in cell shapes. Flow cytometric analysis of haemocytes from B. alexandrina demonstrated that circulating haemocyte populations could be divided into two main subtypes differing in their granularity (granulocytes or hyalinocytes) and size (large and small cells). In addition, the flow cytometric analysis showed that the total number of dead haemocytes in the haemolymph was significantly increased in treated groups compared to the control group. Phagocytosis in groups treated with the herbicides was highly significantly increased compared to the control indicating a very strong response of the treated snails. The results of the alkaline comet assay of DNA damage demonstrated that these herbicides have a genotoxic effect.
Touching the private parts: how gender and sexuality norms affect medical students’ first pelvic examination

Abstract Gynaecologists are in a position to challenge norms about gender and sexuality in relation to female genitals. Through their work they have the opportunity to educate patients, which is why teaching medical students to perform examinations in a gender sensitive way is significant. Medical students performing their first pelvic examination often experience the examination as uncomfortable because it is a body part that is connected to sex and to something private. This paper uses medical students’ interpretations of performing their first pelvic examination as a means to discuss how cultural norms for gender, sexuality and female genitals affect these examinations. Issues raised include how cultural connotations of female genitals affect the pelvic examination, how female and male students relate differently to examining female genitals and the interpretations they make in relation to themselves. Findings show that the female genitals are perceived as a special body part connected to sexuality and intimacy. Students’ gender also affects the interpretations they make during pelvic examinations. Norms of gender, sexuality and female genitals need to be challenged in the teaching and performance of pelvic examination in order to demystify this experience.