Miracle-dz/UniFAR-FTUs huggingface dataset:
Pathologic and Environmental Studies Provide New Pathogenetic Insights Into Ringtail of Laboratory Mice

Ringtail is a pathologic condition of laboratory rodents characterized by annular constrictions of the tail. Traditionally, it is classified as an environmental disorder caused by low relative humidity, but other factors (temperature, dietary deficiencies, genetic susceptibility, and caging type) have also been proposed. Twenty litters of mice with ringtail lesions occurred from September 2010 to August 2013 in a facility located in the northern Italy. Mice were maintained under controlled environmental conditions and fed a standard diet. Retrospective analysis of environmental data (relative humidity, temperature) was carried out. Gross, histopathologic, scanning, and transmission electron microscopy examination of tails and limbs was performed. The incidence of ringtail was 0.075% (20/26 800) of all weaned litters over the 3-year period of examination. Temperature and relative humidity remained within accepted limits in all cases except one. We observed annular constrictions in tail, digits of pes, crus, and antebrachium in 116 (100.0%), 47 (40.5%), 11 (9.5%), and 2 (1.7%) of 116 affected mice, respectively. Histologic and ultrastructural examination revealed abnormal keratin desquamation and presence of a keratin ring encircling the tail, causing progressive strangulation of the growing tail with subsequent compression and ulceration of underlying soft tissues, resulting in circulatory changes (edema, hyperemia, thrombosis, hemorrhages), ischemic necrosis, and eventually auto-amputation distal to the constriction. On the basis of our findings, we suggest a disorder of cornification as the primary lesion of ringtail in mice. The cause of these cases, however, remained undetermined, even though traditional etiologic factors (relative humidity, temperature, diet, caging type) were reasonably excluded.
Experiments in Culture and Corruption: A Review

Two decades of empirical evaluation have shown that corruption has a negative impact on economic growth, political stability, judicial effectiveness, democratization, educational attainment, and equality of income. However, corruption exists, persists, and varies significantly by culture. Lab studies have recently come to the forefront in identifying both the incentives and disincentives for corrupt behavior. However, lab studies on culture and corruption have led to some puzzling, contradictory results. This paper begins with a discussion of non-experimental work in this area, and evaluates the experimental findings in the context of earlier research. The authors sketch out the channels through which culture interacts with corruption (through institutions and social norms), and argue that discrepancies in experimental results may be due to differences in design (including repetition or unobserved variation in beliefs) or to differences in the response to punishment across societies. In addition to exploring design-based reasons for previous contradictory findings, avenues for future research include: behavioral responses to different types of externalities; replicating results in different countries; and utilizing the lab to formulate effective anti-corruption measures.
Virulence, pathology, and pathogenesis of Pteropine orthoreovirus (PRV) in BALB/c mice: Development of an animal infection model for PRV

Background Cases of acute respiratory tract infection caused by Pteropine orthoreovirus (PRV) of the genus Orthoreovirus (family: Reoviridae) have been reported in Southeast Asia, where it was isolated from humans and bats. It is possible that PRV-associated respiratory infections might be prevalent in Southeast Asia. The clinical course of PRV is not fully elucidated. Methods The virulence, pathology, and pathogenesis of two PRV strains, a human-borne PRV strain (isolated from a patient, who returned to Japan from Bali, Indonesia in 2007) and a bat-borne PRV (isolated from a bat [Eonycteris spelaea] in the Philippines in 2013) were investigated in BALB/c mice using virological, pathological, and immunological study methods. Results The intranasal inoculation of BALB/c mice with human-borne PRV caused respiratory infection. In addition, all mice with immunity induced by pre-inoculation with a non-lethal dose of PRV were completely protected against lethal PRV infection. Mice treated with antiserum with neutralizing antibody activity after inoculation with a lethal dose of PRV showed a reduced fatality rate. In this mouse model, bat-borne PRV caused respiratory infection similar to human-borne PRV. PRV caused lethal respiratory disease in an animal model of PRV infection, in which BALB/c mice were used. Conclusions The BALB/c mouse model might help to accelerate research on the virulence of PRV and be useful for evaluating the efficacy of therapeutic agents and vaccines for the treatment and prevention of PRV infection. PRV was shown for the first time to be a causative virus of respiratory disease on the basis of Koch’s postulations by the additional demonstration that PRV caused respiratory disease in mice through their intranasal inoculation with PRV.
Analysis of Tourist Flow Forecasting Model Based on Multiple Additive Regression Tree

Accurate prediction of tourist flow is a key issue in tourism economic analysis and development planning. This paper proposes a tourist flow prediction model based on Multiple Additive Regression Tree (MART) by using machine learning ideas. The model uses factors such as temperature, sunshine duration, air quality and so on to construct eigenvector, and constructing multiple base learners through the boosting framework to predict tourist flow accurately. Take Guilin city from 2015 to 2018 Tourist as an example for analysis, the prediction accuracy of the model is evaluated by means of the average error, square equalization error and other indicators. The experimental results show that the proposed method has high accuracy in the prediction of tourist flow.
Diffusion anisotropy and diffusivity of white matter tracts within the temporal stem in Alzheimer disease: evaluation of the "tract of interest" by diffusion tensor tractography.

PURPOSE Our aim was to determine whether diffusion anisotropy and diffusivity of white matter tracts of the temporal stem in patients with Alzheimer (AD) can be evaluated independently by using diffusion tensor tractography. MATERIALS AND METHODS Subjects included 15 patients with AD (11 women and 4 men; mean age, 74 years) and 15 age-matched control subjects (11 women and 4 men; mean age, 72 years). Diffusion tensor images were acquired by using echo-planar imaging. We drew tractographies of the uncinate fasciculus, inferior occipitofrontal fasciculus, and Meyer's loop, with diffusion tensor analysis software. We measured diffusion anisotropy, diffusivity, and the number of voxels along the "tracts of interest" and used the Student t test to compare results between patients with AD and controls. RESULTS Values of diffusion anisotropy of the bilateral uncinate fasciculus and left inferior occipitofrontal fasciculus were significantly lower for patients with AD than for controls. Also, values of diffusivity in the bilateral uncinate fasciculus were significantly greater for patients with AD than for controls. There was no significant difference in diffusion anisotropy or diffusivity along Meyer's loop between the 2 groups. There was no significant difference in the number of voxels included in all constructed tracts between patients with AD and controls. CONCLUSION White matter tracts of the temporal stem can be evaluated independently by using diffusion tensor tractography, which appears to be a promising technique for determining changes in white matter in degenerative diseases.
The effect of positive affect on conflict resolution: Modulated by approach-motivational intensity

ABSTRACT The motivational dimensional model of affect proposes that the influence of positive affect on cognitive processing is modulated by approach-motivational intensity. The present research extended this model by examining the influence of positive affect varying in approach-motivational intensity on conflict resolution—the ability to resolve interference from task-irrelevant distractors in order to focus on the target. The global–local task (Experiment 1) and letter-Flanker task (Experiment 2) were used to measure conflict resolution. Additionally, the 4:2 mapping design that assigns two kinds of task-relevant stimuli to one response key and two more to another response key was used in these two tasks to dissociate stimulus and response conflict. Results showed that positive affect varying in approach motivation had opposite influences on conflict resolution. The opposite influences are primarily reflected in low approach-motivated positive affect impairing, while high approach-motivated positive affect facilitating the resolution of response conflict. Conversely, the stimulus conflict was slightly influenced. These findings highlight the utility of distinguishing stimulus and response conflict in future research.
Antimicrobial Activity of Ipomoea pes-caprae L. against Selected Microbial Species

In the present investigation, petroleum ether, chloroform, ethyl acetate and methanol extracts of leaves of Ipomea pes-caprae were studied for the antibacterial and antifungal activities against Gram-positive bacteria such as Bacillus pumilus, B. subtilis, Micrococcus luteus and Staphylococcus aureus, Gram-negative bacteria, Escherichia coli, Pseudomonas aeruginosa and Klebsiella pneumonia fungal strains such as Aspergillus niger, A. fumigates and A. flavus and the results are presented. The mean zone of inhibition for bacteria ranged from 8.5 to 25.6 mm. The minimum inhibitory concentration and minimum bactericidal concentrations were from 15.62 to 500 µg/mL and 31.25 to 1000 µg/mL respectively. The standard drug, Ciprofloxacin (10 µg/disc) was used for standard bacterial strains and recorded mean zone of inhibition ranged from 23.5 to 29.5 mm. The mean zone of inhibition for Aspergillus species ranged from 9.6 to 21.5 mm. The minimum inhibitory concentration and minimum fungicidal concentrations were from 31.25 to 500 µg /mL and 62.5 to 1000 µg/mL respectively. The standard drug, Ketoconazole (5 µg/disc) was used for Aspergillus species and recorded mean zone of inhibition ranged from 23.5 mm to 26.5 mm.
Biomechanical comparison of pullout strengths of five cortical screw types: An innovative measurement method.

OBJECTIVES This study aims to assess five different cortical screw types using artificial femurs, under equated testing conditions. MATERIALS AND METHODS We investigated the maximum force needed to cause deformation at screw-bone interface using fourth generation composite femurs by conducting separate pullout tests for each screw type. We normalized obtained results with traditional methods and cross-comparison. To conduct pullout tests dependent on screw dimensions, we eliminated the effect of bicortical bone thickness by equalizing the conditions of screw insertion. RESULTS Non-locking screws with larger diameter and pitch depth required larger pullout forces to be extracted, showing statistically superior performance compared to locking screws with smaller dimensions. However, the statistical differences between the absolute pullout forces decreased after the traditional normalization of the results. We proposed a new normalization method based on solid geometric reasoning. CONCLUSION This novel approach showed that a screw type that appeared to show average performance, in fact, did not have statistically significantly different results than the top performers. Surgeons are not required to prefer larger dimension screws in small dimension host bones.
Zero-Shot Learning with Generative Latent Prototype Model

Zero-shot learning, which studies the problem of object classification for categories for which we have no training examples, is gaining increasing attention from community. Most existing ZSL methods exploit deterministic transfer learning via an in-between semantic embedding space. In this paper, we try to attack this problem from a generative probabilistic modelling perspective. We assume for any category, the observed representation, e.g. images or texts, is developed from a unique prototype in a latent space, in which the semantic relationship among prototypes is encoded via linear reconstruction. Taking advantage of this assumption, virtual instances of unseen classes can be generated from the corresponding prototype, giving rise to a novel ZSL model which can alleviate the domain shift problem existing in the way of direct transfer learning. Extensive experiments on three benchmark datasets show our proposed model can achieve state-of-the-art results.
Examining the Minimal Important Difference of Patient-reported Outcome Measures for Individuals with Knee Osteoarthritis: A Model Using the Knee Injury and Osteoarthritis Outcome Score

Objective. To examine the influence of different analytical methods, baseline covariates, followup periods, and anchor questions when establishing a minimal important difference (MID) for individuals with knee osteoarthritis (OA). Second, to propose MID for improving and worsening on the Knee injury and Osteoarthritis Outcome Score (KOOS). Methods. Retrospective analysis of prospectively collected data from 272 patients with knee OA undergoing a multidisciplinary nonsurgical management strategy. The magnitude and rate of change as well as the influence of baseline covariates were examined for 5 KOOS subscales over 52 weeks. The MID for improving and worsening were investigated using 4 anchor-based methods. Results. Waitlisted for joint replacement and exhibiting unilateral/bilateral symptoms influenced change in KOOS over time. Generally, low correlations between anchors and KOOS change scores limited calculations of MID; thus, they were only proposed for the pain, activities of daily living, and quality of life subscales. The method used to calculate the MID influenced the cutpoint; however, the type of anchor question only influenced the MID when analyzed with a particular mean change method. Depending on patient and clinical characteristics, the subscale, and the analytical approach used, the MID for KOOS improvement ranged from an absolute change of −1.5 to 20.6 points and worsening ranged from −19.17 to 8.5 points. Conclusion. MID vary with patient and clinical characteristics, KOOS subscale, and analytical approach. Provided the anchor question is relevant to the patient-reported outcome and baseline status is considered, the anchor does not appear to influence the MID for improvement or worsening when using some anchor-based methods.
Two-Dimensional Warping for One-Dimensional Signals—Conceptual Framework and Application to ECG Processing

We propose a novel method for evaluating the similarity between two 1d patterns. Our method, referred to as two-dimensional signal warping (2DSW), extends the basic ideas of known warping techniques such as dynamic time warping and correlation optimized warping. By employing two-dimensional piecewise stretching 2DSW is able to take into account inhomogeneous variations of shapes. We apply 2DSW to ECG recordings to extract beat-to-beat variability in QT intervals (QTV) that is indicative of ventricular repolarization lability and typically characterised by a low signal-to-noise ratio. Simulation studies show high robustness of our approach in presence of typical ECG artefacts. Comparison of short-term ECG recorded in normal subjects versus patients with myocardial infarction (MI) shows significantly increased QTV in patients (normal subject 2.36 ms ± 1.05 ms vs. MI patients 5.94 ms ± 5.23 ms (mean ± std), ). Evaluation of a standard QT database shows that 2DSW allows highly accurate tracking of QRS-onset and T-end. In conclusion, the two-dimensional warping approach introduced here is able to detect subtle changes in noisy quasi-periodic biomedical signals such as ECG and may have diagnostic potential for measuring repolarization lability in MI patients. In more general terms, the proposed method provides a novel means for morphological characterization of 1d signals.
Multiple Nose Region Matching for 3D Face Recognition under Varying Facial Expression

An algorithm is proposed for 3D face recognition in the presence of varied facial expressions. It is based on combining the match scores from matching multiple overlapping regions around the nose. Experimental results are presented using the largest database employed to date in 3D face recognition studies, over 4,000 scans of 449 subjects. Results show substantial improvement over matching the shape of a single larger frontal face region. This is the first approach to use multiple overlapping regions around the nose to handle the problem of expression variation
Lossless compression of medical images using two-dimensional multiplicative autoregressive models

Presents new methods for lossless predictive coding of medical images using two dimensional multiplicative autoregressive models. Both single-resolution and multi-resolution schemes are presented. The performances of the proposed schemes are compared with those of four existing techniques. The experimental results clearly indicate that the proposed schemes achieve higher compression compared to the lossless image coding techniques considered.
MITRE at SemEval-2016 Task 6: Transfer Learning for Stance Detection

We describe MITRE's submission to the SemEval-2016 Task 6, Detecting Stance in Tweets. This effort achieved the top score in Task A on supervised stance detection, producing an average F1 score of 67.8 when assessing whether a tweet author was in favor or against a topic. We employed a recurrent neural network initialized with features learned via distant supervision on two large unlabeled datasets. We trained embeddings of words and phrases with the word2vec skip-gram method, then used those features to learn sentence representations via a hashtag prediction auxiliary task. These sentence vectors were then fine-tuned for stance detection on several hundred labeled examples. The result was a high performing system that used transfer learning to maximize the value of the available training data.
A clustering approach for admission control and optimal beamforming in cognitive radio networks

We propose a computationally efficient approach to the problem of admission control and beamforming in a cognitive radio network scenario in which a secondary base station selects the largest set of users to be optimally served with required quality of service while minimizing the transmit power and respecting the interference thresholds imposed by a dense incumbent primary system. To reduce the complexity of the combinatorial user selection problem we propose an initial user clustering scheme in which the similarity between the long term spatial signatures of the users is assessed. Based on these clusters, the users to be simultaneously served, along with their optimal transmit powers and beamforming vectors, are selected according to their instantaneous spatial signatures using an iterative uplink-downlink algorithm. Numerical results show a significant reduction in complexity of our approach compared to previous techniques.
Universal Platform for Software Defined Radio

In this paper, we propose a novel wireless radio platform suitable for software defined radio. This platform is capable of handling multiple radio standards. The proposed platform consists of a new broadband radio frequency (RF) front-end supported by a reconfigurable digital signal processor (DSP) or field programmable gate array (FPGA) technology. The advantages of our platform compared to other SDR architectures are presented in this paper. key words: Software Defined Radio, Universal Platform, Multimode Multiband Receiver, Direct Conversion, Five Port MMIC
RADIO FOLLOW-UP OF GRAVITATIONAL-WAVE TRIGGERS DURING ADVANCED LIGO O1

We present radio follow-up observations carried out with the Karl G. Jansky Very Large Array during the first observing run (O1) of the Advanced Laser Interferometer Gravitational-wave Observatory (LIGO). A total of three gravitational-wave triggers were followed-up during the months of O1, from 2015 September to 2016 January. Two of these triggers, GW150914 and GW151226, are binary black hole (BH) merger events of high significance. A third trigger, G194575, was subsequently declared as an event of no interest (i.e., a false alarm). Our observations targeted selected optical transients identified by the intermediate Palomar Transient Factory in the Advanced LIGO error regions of the three triggers, and a limited region of the gravitational-wave localization area of G194575 not accessible to optical telescopes due to Sun constraints, where a possible high-energy transient was identified. No plausible radio counterparts to GW150914 and GW151226 were found, in agreement with expectations for binary BH mergers. We show that combining optical and radio observations is key to identifying contaminating radio sources that may be found in the follow-up of gravitational-wave triggers, such as emission associated with star formation and active galactic nuclei. We discuss our results in the context of the theoretical predictions for radio counterparts to gravitational-wave transients, and describe our future plans for the radio follow-up of Advanced LIGO (and Virgo) triggers.
Repurposing medicines for the adjuvant treatment of cancer: An evaluation of aspirin and metformin

Introduction: Evidence from pre-clinical studies and observational data suggest that metformin and aspirin are good candidates for adjuvant therapies, though definitive phase III trials have not been completed. Prior to the initiation of this work, the Add-Aspirin trial had been conceived and funded with several potential challenges related to the implementation and design identified. Evidence to support the evaluation of metformin in a phase III adjuvant basket trial had not been systematically evaluated. Methods: I examined the implementation and conduct of the Add-Aspirin trial during its first year at individual UK research centres. Baseline clinical characteristics, and the feasibility and effect of the run-in period, in the first 500 participants was also examined. Additionally, I conducted a systematic review and meta-analysis to investigate the effect of metformin use on survival outcomes for individual tumour types in the adjuvant setting. Results: Centres recognised the efficiencies offered from a basket trial design particularly in terms of gaining approvals, staffing and data entry, though some unanticipated set-up and recruitment challenges have been identified. The baseline clinical characteristics were largely as expected. Overall, 88% of participants were randomised. The run-in period was effective in identifying, and preventing randomisation of participants who had less than 80% adherence (5.0%), and participants who developed significant aspirin related toxicities (1.2%). Other nonrandomisations were mostly due to minor toxicity and/or personal choice. A systematic review and meta-analysis found that metformin use was associated with significant benefits in recurrence-free survival, overall survival and cancer-specific survival in early-stage colorectal and prostate cancer. Conclusion: Opening a large multi-tumour type basket trial with an active run-in period was found to be feasible, but minor conduct modifications have been recommended and protocol amendments implemented. Metformin could be a useful adjuvant agent, and randomised control​ trials in colorectal and prostate cancer are advocated.