Miracle-dz/UniFAR-FTUs huggingface dataset:
Sequential training algorithm for neural networks

A sequential training method for large-scale feedforward neural networks is presented. Each layer of the neural network is decoupled and trained separately. After the training is completed for each layer, they are combined together. The performance of the network would be sub-optimal compared to the full network training if the optimal solution would be achieved. However, achieving the optimal solution for the full network would be infeasible or require long computing time. The proposed sequential approach reduces the required computer resources significantly and would have better convergences as a single layer is optimised for each optimisation step. The required modifications of existing algorithms to implement the sequential training are minimal. The performance is verified by a simple example.
Physician and Practice Characteristics Associated with the Early Utilization of New Prescription Drugs

Background. Prescription of new drugs contributes to substantial increases in annual drug expenditures. A small proportion of physicians appear to be early users of new prescription drugs and little is known about their characteristics. Objective. To estimate the initial utilization rate of new prescription drugs among physicians, and the physician and practice characteristics associated with early use. Design. Cumulative prospective assessment over a 5 year period (1989–1994) of new drug utilization rates in a randomly selected cohort of Quebec physicians. Participants. 1661 physicians and 669,867 elderly patients. Outcome. Prescribing rate of 20 new drugs, in 6 therapeutic categories, to elderly patients in the first 6 months after inclusion in the Quebec formulary. Results. The 20 new drugs were prescribed by 1.3–22.3% of physicians, and there was an 8 to 17‐fold difference in new drug utilization rates among prescribers. Characteristics associated with higher rates of utilization differed for general practitioners and specialists. Male general practitioners, and physicians graduating from the most recently established medical school in the province, had higher rates of new drug utilization, whereas recent graduation was only associated with higher utilization rates among specialists. Practice volume was associated with higher rates of utilization among GPs. For both GPs and specialists, having a high proportion of elderly in one's practice and a rural or remote practice location was associated with lower utilization rates. Conclusions. Physician sex, specialty, medical school, years since graduation, practice location, volume, and relative proportion of elderly in the physician's practice influence the utilization of new drugs.
Club Cell Protein 16 (CC16) Augmentation: A Potential Disease-modifying Approach for Chronic Obstructive Pulmonary Disease (COPD)

ABSTRACT Introduction: Club cell protein 16 (CC16) is the most abundant protein in bronchoalveolar lavage fluid. CC16 has anti-inflammatory properties in smoke-exposed lungs, and chronic obstructive pulmonary disease (COPD) is associated with CC16 deficiency. Herein, we explored whether CC16 is a therapeutic target for COPD. Areas Covered: We reviewed the literature on the factors that regulate airway CC16 expression, its biologic functions and its protective activities in smoke-exposed lungs using PUBMED searches. We generated hypotheses on the mechanisms by which CC16 limits COPD development, and discuss its potential as a new therapeutic approach for COPD. Expert Opinion: CC16 plasma and lung levels are reduced in smokers without airflow obstruction and COPD patients. In COPD patients, airway CC16 expression is inversely correlated with severity of airflow obstruction. CC16 deficiency increases smoke-induced lung pathologies in mice by its effects on epithelial cells, leukocytes, and fibroblasts. Experimental augmentation of CC16 levels using recombinant CC16 in cell culture systems, plasmid and adenoviral-mediated over-expression of CC16 in epithelial cells or smoke-exposed murine airways reduces inflammation and cellular injury. Additional studies are necessary to assess the efficacy of therapies aimed at restoring airway CC16 levels as a new disease-modifying therapy for COPD patients.
High-order feature-based mixture models of classification learning predict individual learning curves and enable personalized teaching

Pattern classification learning tasks are commonly used to explore learning strategies in human subjects. The universal and individual traits of learning such tasks reflect our cognitive abilities and have been of interest both psychophysically and clinically. From a computational perspective, these tasks are hard, because the number of patterns and rules one could consider even in simple cases is exponentially large. Thus, when we learn to classify we must use simplifying assumptions and generalize. Studies of human behavior in probabilistic learning tasks have focused on rules in which pattern cues are independent, and also described individual behavior in terms of simple, single-cue, feature-based models. Here, we conducted psychophysical experiments in which people learned to classify binary sequences according to deterministic rules of different complexity, including high-order, multicue-dependent rules. We show that human performance on such tasks is very diverse, but that a class of reinforcement learning-like models that use a mixture of features captures individual learning behavior surprisingly well. These models reflect the important role of subjects’ priors, and their reliance on high-order features even when learning a low-order rule. Further, we show that these models predict future individual answers to a high degree of accuracy. We then use these models to build personally optimized teaching sessions and boost learning.
Actinobacilli in domestic fowl.

Reports on haemolytic rods from salpingitis in hens and from organs of died chicks may be found since the year 1950 (Kjos-Hanssen). Correct systematic classification on these microorganisms is still lacked because not all relations to the nearest pasteurellae were known as well as the clear differences in the Pasteurella-Actinobacillus group. The authors have isolated 34 suspected strains from 14 localities; 25 strains were from salpingitis or internal organs of died fowl inclusively chicks, and 9 strains from choanas of pullets clinically healthy. Bacteriological, serological, chemical and biological tests gave the results as follows: 1) All strains exhibit fundamental properties of Pasteurella-Actinobacillus group, and moreover, they show ability to grow on MacConkey agar with crystal violet (BioQuest) being a significant feature of the genus Actinobaccillus (Mráz, 1975). 2) From the nearest species Actinobacillus haemolyticus (Newsom and Cross, 1932) Mráz, 1969, they differ with expressive haemolysis on agar with sheep blood, single haemolytic zone on agar with lamb blood according to Smith (1962), structure of somatic antigen, with natural hosts (gallinaceous birds) and pathogenicity for 5-day-old chicks. The GC content in DNA was determined in the range 39,6-42,9% (mean value 41,5%). 3) The first who presumed an independent state of these microorganisms, was Kohlert (1968), from the work of which the epithet for correct name, i.e. Actinobacillus salpingitidis (Kohlert, 1968) comb. nov., was accepted.
Gastrointestinal helminths from the common warthog, Phacochoerus africanus (Gmelin) (Suidae), in KwaZulu-Natal Province, South Africa, with comments on helminths of Suidae and Tayassuidae worldwide

Abstract Thirty warthogs, Phacochoerus africanus, were collected in the Pongola Game Reserve, South Africa and examined for helminths. Gastrointestinal helminth assemblages comprised Gastrodiscus aegyptiacus, the cestode genus Moniezia and seven species of nematodes. A single warthog harboured a metacestode of Taenia hydatigena in the mesenteries. No helminths were found in the heart, lungs or liver of the warthogs. Probstmayria vivipara and Murshidia spp. were the most prevalent as well as abundant helminth species, followed by Physocephalus sexalatus. The incidence of Moniezia did not differ between hosts of different sex or age. Numbers of Murshidia spp. were not affected by host sex, but were higher in adults than in juveniles. Conversely, burdens of Trichostrongylus thomasi were not affected by host age, but were higher in males than in females. While not highly significant, helminth assemblages in male warthogs were more species rich than in females. Helminth communities in the three genera of wild sub-Saharan suids are largely unique, but Ph. africanus and Hylochoerus meinertzhageni share more worm species with each other than with Potamochoerus larvatus, possibly because the former two are more closely related. Overlap between helminth communities of African wild suids and those of other suids and Tayassuidae worldwide is limited.
Adaptation of problem-solving therapy for primary care to prevent late-life depression in Goa, India: the ‘DIL’ intervention

ABSTRACT Background: Depression in late life is a major, yet unrecognized public health problem in low- and middle-income countries (LMICs). The dearth of specialist resources, together with the limited ability of current depression treatments to avert years lived with disability, underscores the need for preventive interventions that can be delivered by lay health workers in primary care settings. We describe the development of an intervention for the indicated prevention of depression in older adults at risk due to subsyndromal symptoms, attending rural and urban public primary care clinics in Goa, India. Objectives: (1) to describe a mixed-methods approach (qualitative and quantitative)to the development of ‘DIL,’ an intervention for preventing the onset of major depression in older adults living with subsyndromal symptoms in Goa, India; (2) to describe resulting components of the ‘DIL’ intervention; and (3) to present data on the feasibility, acceptability, and benefit of DIL to participants. Methods: We followed a mixed-methods design, including in-depth interviews, focus group discussions, a theory of change workshop to develop a logic model, and an open-case series. Results: The mixed-method approach led to the development and adaptation of the DIL (Depression in Later Life) intervention for the indicated prevention of depression in older adults. The intervention was delivered by lay health counselors (LHCs). ‘DIL’ is a hybrid model of simple behavioral strategies grounded in Problem-solving Therapy for Primary Care, improved self-management of common, co-occurring medical disorders such as diabetes mellitus, and pragmatic assistance in navigating to needed social services. The use of ‘DIL’ in an open-case series with 19 participants led to a moderate reduction in symptoms of depression and anxiety on the General Health Questionnaire. A pictorial flipchart was developed to assist in delivering the intervention to participants with low levels of literacy. High rates of participant retention and satisfaction were achieved. Conclusion: The DIL intervention was adapted to the local context for delivery by lay health counselors and was found to be acceptable and feasible among the elderly participants in the study.
bcr‐abl, the hallmark of chronic myeloid leukaemia in man, induces multiple haemopoietic neoplasms in mice.

The chromosome translocation forming the hybrid bcr‐abl gene is thought to be the initiating event in chronic myeloid leukaemia (CML) and some cases of acute lymphoblastic leukaemia. To assess the impact of bcr‐abl upon haemopoiesis, lethally irradiated mice were reconstituted with bone marrow cells enriched for cycling stem cells and infected with a bcr‐abl bearing retrovirus. The mice developed several fatal diseases with abnormal accumulations of macrophage, erythroid, mast and lymphoid cells, and marked strain differences in disease distribution and kinetics. Some mice exhibited more than one neoplastic cell type and, in some instances, these were clonally related, indicating that a progenitor or stem cell had been transformed. While classical CML was not observed, the macrophage tumours were accompanied by a mild CML‐like syndrome, probably due to myeloid growth factor production by tumour cells. The erythroid and mast cell diseases were rarely transplantable, in contrast to the macrophage tumours and lymphomas, but all disease types displayed limited clonality. These results establish that bcr‐abl confers a proliferative advantage on diverse haemopoietic cells but complete transformation probably involves additional genetic changes.
Shaping the learning landscape in neural networks around wide flat minima

Significance Deep neural networks (DNN) are becoming fundamental learning devices for extracting information from data in a variety of real-world applications and in natural and social sciences. The learning process in DNN consists of finding a minimizer of a loss function that measures how well the data are classified. This optimization task is typically solved by tuning millions of parameters by stochastic gradient algorithms. This process can be thought of as an exploration process of a highly nonconvex landscape. Here we show that such landscapes possess very peculiar wide flat minima and that the current models have been shaped to make the loss functions and the algorithms focus on those minima. We also derive efficient algorithmic solutions. Learning in deep neural networks takes place by minimizing a nonconvex high-dimensional loss function, typically by a stochastic gradient descent (SGD) strategy. The learning process is observed to be able to find good minimizers without getting stuck in local critical points and such minimizers are often satisfactory at avoiding overfitting. How these 2 features can be kept under control in nonlinear devices composed of millions of tunable connections is a profound and far-reaching open question. In this paper we study basic nonconvex 1- and 2-layer neural network models that learn random patterns and derive a number of basic geometrical and algorithmic features which suggest some answers. We first show that the error loss function presents few extremely wide flat minima (WFM) which coexist with narrower minima and critical points. We then show that the minimizers of the cross-entropy loss function overlap with the WFM of the error loss. We also show examples of learning devices for which WFM do not exist. From the algorithmic perspective we derive entropy-driven greedy and message-passing algorithms that focus their search on wide flat regions of minimizers. In the case of SGD and cross-entropy loss, we show that a slow reduction of the norm of the weights along the learning process also leads to WFM. We corroborate the results by a numerical study of the correlations between the volumes of the minimizers, their Hessian, and their generalization performance on real data.
Prelexical representations and processes in reading: Evidence from acquired dyslexia

We report a detailed and extensive single-case study of an acquired dyslexic patient, L.H. D. , who suffered a left-hemisphere lesion as a result of a ruptured aneurysm. We present evidence that L.H. D. ’s reading errors stem from a deficit in visual letter identification, and we use her deficit as a basis for exploring a variety of issues concerning prelexical representations and processes in reading. First, building on the work of other researchers, we present evidence that the prelexical reading system includes an allograph level of representation that represents each distinct visual shape of a letter (e.g., a, A, etc., for the letter A). We extend a theory proposed by Caramazza and Hillis [Caramazza, A. , & Hillis, A. (1990a). Spatial representation of words in the brain implied by studies of a unilateral neglect patient. Nature, 346, 267–269] to include an allograph level, and we probe the nature of the allograph representations in some detail. Next, we explore the implications of visual similarity effects and letter perseverations in L.H. D. ’s reading performance, arguing that these effects shed light on activation dynamics in the prelexical reading system and on the genesis of L.H. D. ’s errors. We also probe the processing of letter case in the visual letter identification process, proposing that separate abstract letter identity and case representations are computed. Finally, we present evidence that the allograph level as well as the abstract letter identity level implement a word-based frame of reference.
Mean-field Langevin dynamics and energy landscape of neural networks

We present a probabilistic analysis of the long-time behaviour of the nonlocal, diffusive equations with a gradient flow structure in 2-Wasserstein metric, namely, the Mean-Field Langevin Dynamics (MFLD). Our work is motivated by a desire to provide a theoretical underpinning for the convergence of stochastic gradient type algorithms widely used for non-convex learning tasks such as training of deep neural networks. The key insight is that the certain class of the finite dimensional non-convex problems becomes convex when lifted to infinite dimensional space of measures. We leverage this observation and show that the corresponding energy functional defined on the space of probability measures has a unique minimiser which can be characterised by a first order condition using the notion of linear functional derivative. Next, we show that the flow of marginal laws induced by the MFLD converges to the stationary distribution which is exactly the minimiser of the energy functional. We show that this convergence is exponential under conditions that are satisfied for highly regularised learning tasks. At the heart of our analysis is a pathwise perspective on Otto calculus used in gradient flow literature which is of independent interest. Our proof of convergence to stationary probability measure is novel and it relies on a generalisation of LaSalle's invariance principle. Importantly we do not assume that interaction potential of MFLD is of convolution type nor that has any particular symmetric structure. This is critical for applications. Finally, we show that the error between finite dimensional optimisation problem and its infinite dimensional limit is of order one over the number of parameters.
Marker of Endothelial Dysfunction Asymmetric Dimethylarginine Is Elevated in HIV Infection but Not Associated With Subclinical Atherosclerosis

Background:Cardiovascular disease contributes to excess morbidity and mortality in HIV infection, and endothelial dysfunction may contribute to this pattern. We aimed to determine the endothelial function in treated and untreated HIV-infected individuals and investigate potential associations with viral replication, immune activation, coagulation, platelet function, and subclinical atherosclerosis. Methods:Asymmetric dimethylarginine (ADMA, marker of endothelial dysfunction) and soluble CD14 (sCD14, marker of monocyte activation) were measured in plasma from two previously established cross-sectional cohorts: cohort A including 50 untreated and 50 antiretroviral therapy (ART)–treated HIV-infected individuals with previously assessed coagulation and platelet function and cohort B including 105 HIV-infected individuals on ART and 105 uninfected controls with previously assessed coronary artery calcium score, myocardial perfusion defects, and carotid intima–media thickness. Results:Concentrations of ADMA were higher in HIV-infected individuals compared with uninfected controls, and higher ADMA was found in ART-treated compared with untreated HIV-infected individuals. ADMA was associated with viral load, sCD14, D-dimer, and low CD4+ T-cell count in untreated HIV infection. Only viral load remained significant in multivariate analyses. In ART-treated HIV-infected individuals, ADMA was not associated with coronary artery calcium score, myocardial perfusion defects, or intima–media thickness. Conclusions:Evidence of endothelial dysfunction was found in HIV infection and in untreated compared with treated HIV infection. In untreated HIV infection, the main driver of endothelial dysfunction was viral replication. Importantly, in treated HIV infection, ADMA was not associated with subclinical atherosclerosis. Thus, our data question the potential of ADMA as a useful biomarker of early atherosclerosis in treated HIV infection.
Duty-related and sexual stress in the etiology of PTSD among women veterans who seek treatment.

OBJECTIVE The stressful experiences of women serving in the military have been a focus of increasing concern. A model of the impact of stress related to military duty and stress related to sexual abuse and harassment on the development of posttraumatic stress disorder (PTSD) among female veterans was evaluated. METHODS Structural equation modeling was applied to data from 327 women treated in a VA clinical program for women with stress disorders. The model was a chronological one and included variables related to the women's premilitary experience, their military service, and their postmilitary experience. RESULTS Altogether 48 percent of the sample served overseas, and 12 percent were exposed to enemy fire. A total of 63 percent reported experiences of physical sexual harassment during military service, and 43 percent reported rape or attempted rape. Both duty-related and sexual stress were found to contribute separately and significantly to the development of PTSD. Sexual stress was found to be almost four times as influential in the development of PTSD as duty-related stress. Postmilitary social support played a highly significant mediational role between sexual stress during military service and development of PTSD. CONCLUSIONS Women's exposure to sexual stress in the military is much more prevalent than previously believed. It is particularly toxic for the development of PTSD. Correct assessment is essential to effective treatment.
Automatic karyotyping based on computational vision and intelligent classifiers

The objective of this work is to create an intelligent system to support the construction of the karyotype through the automatic classification of chromosomes. The karyotype construction, or karyotyping, is a part of a type of analysis realized in laboratory at genetic level. This process part, is time consuming and requires highly specialized personal in live science. Thus, this work uses techniques and algorithms of image processing and intelligent systems of decision (artificial neural networks and fuzzy logic) to implement a method that can build automatically the karyotype. Image processing techniques were developed to characterize some of the descriptors, particularly in terms of obtaining the middle axis of the chromosome. Features were tested, getting results without resorting to the location of the centromere. The performance of the two classification systems was tested and compared.