Miracle-dz/UniFAR-FTUs huggingface dataset:
Epidemiology of Urban Canine Rabies, Santa Cruz, Bolivia, 1972–1997

We analyzed laboratory data from 1972 to 1997 from Santa Cruz, Bolivia, to determine risk factors for laboratory canine samples’ testing positive for Rabies virus (RABV). Of 9,803 samples, 50.7% tested positive for RABV; the number of cases and the percentage positive has dropped significantly since 1978. A 5- to 6-year cycle in rabies incidence was clearly apparent, though no seasonality was noted. Male dogs had significantly increased odds of testing positive for RABV (odds ratio [OR]=1.14), as did 1- to 2-year-old dogs (OR=1.73); younger and older dogs were at lower risk. Samples submitted from the poorer suburbs of the city were more likely to test positive for RABV (OR=1.71). We estimated the distribution of endemic canine rabies in an urban environment to facilitate control measures in a resource-poor environment.
Promoter Hypermethylation as an Independent Prognostic Factor for Relapse in Patients with Prostate Cancer Following Radical Prostatectomy

Purpose: To analyze the prognostic significance of six epigenetic biomarkers (APC, Cyclin D2, GSTP1, TIG1, Rassf1A, and RARβ2 promoter hypermethylation) in a homogeneous group of prostate cancer patients, following radical prostatectomy alone. Patients and Methods: Biomarker analyses were done retrospectively on tumors from 74 prostate cancer patients all with a Gleason score of 3 + 4 = 7 and minimum follow-up period of 7 years. Using quantitative methylation-specific PCR, we analyzed six gene promoters in primary prostate tumor tissues. Time to any progression was the primary end point, and development of metastatic disease and/or death from prostate cancer was a secondary point. The association of clinicopathologic and biomolecular risk factors to recurrence was done using the log-rank test and Cox proportional hazards model for multivariate analysis. To identify independent prognostic factors, a stepwise selection method was used. Results: At a median follow-up time of 9 years, 37 patients (50%) had evidence of recurrence: biochemical/prostate-specific antigen relapse, metastases, or death from prostate cancer. In the final multivariate analysis for time to progression (TTP), the significant factors were age > 60 [hazard ratio (HR), 0.4; 95% confidence interval (95% CI), 0.2-0.8; P = 0.01], hypermethylation of GSTP1 (HR, 0.23; 95% CI; 0.09-0.64; P = 0.004), and hypermethylation of APC (HR, 3.0; 95% CI, 1.42-6.32; P = 0.004). In another multivariate analysis, a profile of hypermethylation of APC and cyclin D2 hypermethylation was significant as well: if either any one was hypermethylated (HR, 1.84; 95% CI, 0.92-3.72; P = 0.09) or if both were hypermethylated (HR, 4.3; 95% CI, 1.52-12.33; P = 0.01). Conclusions: Methylation status of selected genes in the prostate cancer specimen may predict for time to recurrence in Gleason 3 + 4 = 7 patients undergoing prostatectomy. These results should be validated in a larger and unselected cohort.
Bin-packing based optimisation of EON Networks with S-BVTs

In the paper we address an important problem in minimum cost design of Elastic Optical Networks (EON), namely the problem of optimizing the configurations of Sliceable-Bandwidth Variable Transceivers (S-BVT) at the EON nodes. We first show how this optimization problem can be viewed and modeled as a combination of three bin-packing subproblems, with additional constraints ensuring feasibility of the solution. Then, we propose various valid inequalities and symmetry breaking constraints to strengthen the introduced model. Finally, we show, through computational results, that the strengthening techniques very effectively enable achieving near-optimal solutions.
Neuropsychology in Temporal Lobe Epilepsy: Influences from Cognitive Neuroscience and Functional Neuroimaging

Neuropsychologists assist in diagnosis (i.e., localization of dysfunction) and in prediction (i.e., how cognition may change following surgery) in individuals being considered for temporal lobe surgery. The current practice includes behavioural testing as well as mapping function via stimulation, inactivation, and (more recently) functional imaging. These methods have been providing valuable information in surgical planning for 60 years. Here, we discuss current assessment strategies and highlight how they are evolving, particularly with respect to integrating recent advances in cognitive neuroscience.
Virus and Autoantigen-Specific CD4+ T Cells Are Key Effectors in a SCID Mouse Model of EBV-Associated Post-Transplant Lymphoproliferative Disorders

Polyclonal Epstein-Barr virus (EBV)-infected B cell line (lymphoblastoid cell lines; LCL)-stimulated T-cell preparations have been successfully used to treat EBV-positive post-transplant lymphoproliferative disorders (PTLD) in transplant recipients, but function and specificity of the CD4+ component are still poorly defined. Here, we assessed the tumor-protective potential of different CD4+ T-cell specificities in a PTLD-SCID mouse model. Injection of different virus-specific CD4+ T-cell clones showed that single specificities were capable of prolonging mouse survival and that the degree of tumor protection directly correlated with recognition of target cells in vitro. Surprisingly, some CD4+ T-cell clones promoted tumor development, suggesting that besides antigen recognition, still elusive functional differences exist among virus-specific T cells. Of several EBV-specific CD4+ T-cell clones tested, those directed against virion antigens proved most tumor-protective. However, enriching these specificities in LCL-stimulated preparations conferred no additional survival benefit. Instead, CD4+ T cells specific for unknown, probably self-antigens were identified as principal antitumoral effectors in LCL-stimulated T-cell lines. These results indicate that virion and still unidentified cellular antigens are crucial targets of the CD4+ T-cell response in this preclinical PTLD-model and that enriching the corresponding T-cell specificities in therapeutic preparations may enhance their clinical efficacy. Moreover, the expression in several EBV-negative B-cell lymphoma cell lines implies that these putative autoantigen(s) might also qualify as targets for T-cell-based immunotherapy of virus-negative B cell malignancies.
The importance of entrepreneurs’ traits in explaining start-ups’ innovativeness

Purpose of the paper : several studies prove the existence of a relationship between entrepreneurs’ personality traits and firm performances. However, few of them focus on how these personality traits can be correlated with start-ups’ innovativeness. We focus on start-ups because entrepreneurs play a crucial role in managing them: their personality strongly influences business decisions. The main personality traits we consider are narcissism, the Big Five (i.e. extraversion, agreeableness, conscientiousness, neuroticism, openness to experience), and locus of control. We aim to shed light on how these traits impact on start-ups’ innovativeness and we draw propositions that hypothesize such impact. Methodology : being a theoretical paper, we carry out a thorough literature review and we propose some propositions. Findings : we suggest that entrepreneurs positively influence start-ups’ innovativeness whenever they are narcissistic and have a high level of extraversion, agreeableness, conscientiousness, openness to experience, and internal locus of control. Otherwise, entrepreneurs with a high level of neuroticism and external locus of control negatively influence start-ups’ innovativeness. Limitations : considering the theoretical nature of the paper, we have not tested our propositions yet; future research will involve testing them in an empirical business context. Implications : this paper makes significant contributions to two different literatures: entrepreneurship literature and innovation literature. Originality of the paper : this paper tries to fill a gap in the literature by analysing the relationship between start-ups’ innovation and entrepreneurs’ traits.
The Use and Misuse of Patent Data: Issues for Corporate Finance and Beyond

Patents and citations are powerful tools for understanding innovative activity inside the firm, and are increasingly use in corporate finance research. But due to the complexities of patent data collection and the changing spatial and industry composition of innovative firms, biases may be introduced. We highlight several patent-level biases induced by truncation of reported patent awards and citations, affecting estimates of time trends and patterns across technology classes and regions. We then introduce measures of patent and citation biases. When aggregated at the firm level, these survive popular methods of adjustment and are correlated with firm-level characteristics. We show that these issues can lead to problematic – and ex ante predictable – inferences, using several examples from prominent streams of finance literature that use patent data. We suggest a number of concrete steps that researchers can employ to avoid biased inferences.
Meta-Analysis-Based Preliminary Exploration of the Connection between ATDILI and Schizophrenia by GSTM1/T1 Gene Polymorphisms

Anti-tuberculosis drugs have some adverse effects such as anti-tuberculosis drug-induced liver injury (ATDILI) and mental disorders. The involvement of glutathione S-transferase (GST) genes in pathogenesis of ATDILI or schizophrenia (SCZ) has been reported. Therefore, GST genes may exemplify molecular connectors between ATDILI and SCZ. However, association studies of GSTM1/T1 polymorphisms with these two diseases have yielded conflicting results. After searching case-control association studies in PubMed, ISI Web of Science, EMBASE, Chinese National Knowledge Infrastructure (CNKI), and Chinese BioMedical Literature Database, we performed meta-analyses across a total of 20 published association studies on 3146 subjects for the association of GSTM1 and ATDILI, 2587 for the GSTT1-ATDILI association, 2283 for GSTM1-SCZ and 1116 for GSTT1-SCZ to test the associations of GSTM1/T1 polymorphisms with ATDILI and SCZ. The GSTM1 present genotype was significantly associated with decreased risks of ATDILI (risk ratio(RR): 0.81, 95% confidence interval (CI): 0.75–0.88, P < 0.0001) and SCZ (RR: 0.88, 95%CI: 0.80–0.96, P = 0.004) according to the fixed-effect model, while the GSTT1 present genotype was significantly associated only with a high risk of SCZ (RR: 1.17, 95%CI: 1.04–1.32, P = 0.01) according to both the random- and fixed-effect models, but not with ATDILI (P = 0.82) according to the fixed-effect model. Moreover, these significant results were supported with moderate evidence according to the Venice criteria. These results indicate that GSTM1 represents a genetic connection between ATDILI and SCZ, and suggest that ATDILI and SCZ may be co-occurring for the subjects with GSTM1 null genotype.
A Hierarchical Integration of Person-Centered Comorbidity Models: Structure, Stability, and Transition Over Time

Person-centered analyses of mental disorder comorbidity typically identify a single optimal latent group structure. We took an alternate approach, modeling every estimable comorbidity class model in a nationally representative sample (N = 34,653) and integrating them into a single overarching hierarchy, providing a full multilevel accounting of various person-centered comorbidity structures. We then investigated the structural stability of this hierarchy across two waves of data collection, and the stability of, and transition between, comorbidity classes over time using latent transition analysis. Findings suggested that comorbidity classes were structured into an interpretable hierarchy. Evidence for robust structural stability of the hierarchy over time was found, regardless of assessment time points and diagnostic time frames used. Latent transition analysis provided evidence for both continuity and change of comorbidity group membership. We discuss how person- and variable-centered models provide complementary perspectives toward empirically supported classification.
Fast and Energy Efficient Learning Algorithm for Kohonen Neural Network Realized in Hardware

A new fast energy efficient learning algorithm suitable for hardware implemented Kohonen Self-Organizing Map (SOM) is proposed in the paper. The new technique is based on a multistage filtering of the quantization error. The algorithm detects such periods in the learning process, in which the quantization error is decreasing (the ‘activity’ phases), which can be interpreted as a progress in training, as well as the ‘stagnation’ phases, in which the error does not decrease. The neighborhood radius is reduced by 1 always just after the training process enters one of the ‘stagnation’ phases, thus shortening this phase. The comprehensive simulations on the software model (in C++) have been carried out to investigate the influence of the proposed algorithm on the learning process. The learning process has been assessed by the used of five criteria, which allow assessing the learning algorithm in two different ways i.e., by expressing the quality of the vector quantization, as well as the topographic mapping. The new algorithm is able to shorten the overall training process by more than 90% thus reducing the energy consumed by the SOM also by 90%. The proposed training algorithm is to be used in a new high performance Neuroprocessor that will find a broad application in a new generation of Wireless Body Area Networks ( WBAN) used in the monitoring of the biomedical signals like, for example, the Electrocardiogram (ECG) signals.
Robust rotation-invariant texture classification using a model based approach

In this paper, a model based texture classification procedure is presented. The texture is modeled as the output of a linear system driven by a binary image. This latter retains the morphological characteristics of the texture and it is specified by its spatial autocorrelation function (ACF). We show that features extracted from the ACF of the binary excitation suffice to represent the texture for classification purposes. Specifically, we employ a moment invariants based technique to classify the ACF. The resulting proposed classification procedure is thus inherently rotation invariant. Moreover, it is robust with respect to additive noise. Experimental results show that this approach allows obtaining high correct rotation-invariant classification rates while containing the size of the feature space.
New trends and ideas in visual concept detection: the MIR flickr retrieval evaluation initiative

The MIR Flickr collection consists of 25000 high-quality photographic images of thousands of Flickr users, made available under the Creative Commons license. The database includes all the original user tags and EXIF metadata. Additionally, detailed and accurate annotations are provided for topics corresponding to the most prominent visual concepts in the user tag data. The rich metadata allow for a wide variety of image retrieval benchmarking scenarios. In this paper, we provide an overview of the various strategies that were devised for automatic visual concept detection using the MIR Flickr collection. In particular we discuss results from various experiments in combining social data and low-level content-based descriptors to improve the accuracy of visual concept classifiers. Additionally, we present retrieval results obtained by relevance feedback methods, demonstrating (i) how their performance can be enhanced using features based on visual concept classifiers, and (ii) how their performance, based on small samples, can be measured relative to their large sample classifier counterparts. Additionally, we identify a number of promising trends and ideas in visual concept detection. To keep the MIR Flickr collection up-to-date on these developments, we have formulated two new initiatives to extend the original image collection. First, the collection will be extended to one million Creative Commons Flickr images. Second, a number of state-of-the-art content-based descriptors will be made available for the entire collection.
Speaker identification on the SCOTUS corpus

This paper reports the results of our experiments on speaker identification in the SCOTUS corpus, which includes oral arguments from the Supreme Court of the United States. Our main findings are as follows: 1) a combination of Gaussian mixture models and monophone HMM models attains near‐100% text‐independent identification accuracy on utterances that are longer than one second; (2) the sampling rate of 11025 Hz achieves the best performance (higher sampling rates are harmful); and a sampling rate as low as 2000 Hz still achieves more than 90% accuracy; (3) a distance score based on likelihood numbers was used to measure the variability of phones among speakers; we found that the most variable phone is the phone UH (as in good), and the velar nasal NG is more variable than the other two nasal sounds M and N; 4. ) our models achieved “perfect” forced alignment on very long speech segments (one hour). These findings and their significance are discussed.
Sticks and Carrots in Procurement

We study differently framed incentives in dynamic laboratory buyerseller relationships with multi-tasking and endogenous matching. The experimental design tries to mitigate the role of social preferences and intrinsic motivation. Absent explicit incentives, effort is low in both tasks. Their introduction boosts efficiency substantially increasing effort in the contractible task, mildly crowding it out in the non-contractible one, and increasing buyer surplus. Bonuses and penalties are equivalent for efficiency and crowding-out, but different in distributional effects: sellers’ surplus increases with bonuses as buyers’ offers become more generous. Buyers tend to prefer penalties, which may explain why they are dominant in procurement.
Local Contrast in Natural Images: Normalisation and Coding Efficiency

The visual system employs a gain control mechanism in the cortical coding of contrast whereby the response of each cell is normalised by the integrated activity of neighbouring cells. While restricted in space, the normalisation pool is broadly tuned for spatial frequency and orientation, so that a cell's response is adapted by stimuli which fall outside its ‘classical’ receptive field. Various functions have been attributed to divisive gain control: in this paper we consider whether this output nonlinearity serves to increase the information carrying capacity of the neural code. 46 natural scenes were analysed with the use of oriented, frequency-tuned filters whose bandwidths were chosen to match those of mammalian striate cortical cells. The images were logarithmically transformed so that the filters responded to a luminance ratio or contrast. In the first study, the response of each filter was calibrated relative to its response to a grating stimulus, and local image contrast was expressed in terms of the familiar Michelson metric. We found that the distribution of contrasts in natural images is highly kurtotic, peaking at low values and having a long exponential tail. There is considerable variability in local contrast, both within and between images. In the second study we compared the distribution of response activity before and after implementing contrast normalisation, and noted two major changes. Response variability, both within and between scenes, is reduced by normalisation, and the entropy of the response distribution is increased after normalisation, indicating a more efficient transfer of information.
Predicting Major Neurological Improvement With Intravenous Recombinant Tissue Plasminogen Activator Treatment of Stroke

Background and Purpose— In the National Institute of Neurological Disorders and Stroke (NINDS) rt-PA Stroke Study, major neurological improvement within 24 hours (MNI) occurred significantly more frequently with recombinant tissue plasminogen activator (rtPA) treatment than with placebo. We explored the relationship between MNI and 3-month favorable outcome and sought clinical predictors of MNI. Methods— Data from 312 rtPA-treated patients from the NINDS trial were used to assess the ability of MNI to predict favorable outcome at 3 months as defined by a modified Rankin Scale score of 0 to 1. Next, a multivariable predictive model was developed for MNI within the same data set. Clinical variables examined included age, time to treatment (TTT), diabetes, pretreatment glucose, baseline National Institutes of Health Stroke Scale score, pretreatment blood pressure, history of atrial fibrillation, weight >100 kg, and a dense artery sign. Finally, this model was used to forecast into the placebo group of the NINDS trial to assess the uniqueness of the predictors in the rtPA-treated group. Results— MNI had a positive predictive value and negative predictive value of 0.70 for predicting favorable 3-month outcome. Only age [odds ratio (OR), 0.68; 95% confidence interval (CI), 0.47 to 0.99] and TTT (OR, 0.56; 95% CI, 0.34 to 0.91) appear to be independently associated with MNI. The model performed only moderately well (area under the receiver-operating characteristic curve, 0.66). Age (OR, 0.67; 95% CI, 0.45 to 0.99) but not TTT was associated with MNI in the placebo group. Conclusions— MNI may be a useful surrogate for thrombolytic activity and is predictive of favorable 3-month outcome. When rates of MNI in different populations of stroke patients treated with thrombolysis are compared, adjustments for age and TTT may be necessary.
To Hear or Not to Hear: Sound Availability Modulates Sensory-Motor Integration

When we walk in place with our eyes closed after a few minutes of walking on a treadmill, we experience an unintentional forward body displacement (drift), called the sensory-motor aftereffect. Initially, this effect was thought to be due to the mismatch experienced during treadmill walking between the visual (absence of optic flow signaling body steadiness) and proprioceptive (muscle spindles firing signaling body displacement) information. Recently, the persistence of this effect has been shown even in the absence of vision, suggesting that other information, such as the sound of steps, could play a role. To test this hypothesis, six cochlear-implanted individuals were recruited and their forward drift was measured before (Control phase) and after (Post Exercise phase) walking on a treadmill while having their cochlear system turned on and turned off. The relevance in testing cochlear-implanted individuals was that when their system is turned off, they perceive total silence, even eliminating the sounds normally obtained from bone conduction. Results showed the absence of the aftereffect when the system was turned off, underlining the fundamental role played by sounds in the control of action and breaking new ground in the use of interactive sound feedback in motor learning and motor development.