Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Generative Models using Transformations

One of the fundamental problems in machine learning and statistics is learning generative models of data. Explicit generative models, which model probability densities of data, have been intensively studied in numerous applications.However, it is usually difficult to model complex data, such as natural images, by using combinations of simple parametric distributions. Implicit generative models (IGMs), which model transformations between known source distributions and target distributions to simulate the sampling process withoutspecifying densities explicitly, regain its attention with explosion of interests. With recent success of deep learning, IGMs have yielded impressive empirical performance in different applications. While there are new algorithms for learning IGMs, its theoretical properties are weakly justified and their relationships with existing methods are underexplored.The first thrust of this thesis is to understand statistical guarantees of learning IGMs. By connecting IGMs with two-sample test, we propose a new generic algorithm that can be built on the top of many existing approaches and bring performance improvement over the state-of-the-art. On the other hand, from the perspective of statistical analysis, IGMs, which model transformations, is fundamentally different from traditional explicit models, whichmakes the existing results not directly applicable. We then study error bounds and sample complexities of learning IGMs taking a step forward in building its rigorous foundations. In the second part, we shift our focus to different types of data that we are interested in. We develop algorithms for learning IGMs on various data rangingfrom images, text, to point clouds, by exploiting their underlying structures. Instead of modeling IGM transformations blindly via powerful functions only,such as deep neural networks, we propose to leverage human priors into algorithm designs to reduce model sizes, save computational overhead, and achieve interpretable results. In this thesis, we show an example of incorporating asimple yet fairly representative renderer developed in computer graphics into IGM transformations for generating realistic and highly structured body data, which paves a new path of learning IGMs. Finally, we study how IGMs can improve existing machine learning algorithms. From its nature of modeling sampling processes, we propose learning powerful kernels via Fourier analysis and IGM sampling. By thinking IGMs as learning transformations, we extend IGMs to broader applications in diff erent domains. In the second example, we present how to learn proximal operators as IGM transformations to solve important linear inverse problems in computer vision. Lastly, we introduce a new way of using IGMs by treating them as auxiliarycomponents to benefit non-generative tasks while the final output of the interest is not the generative models. We present an application of optimizing test power in anomaly detection by constructing a lower bound of test powervia auxiliary IGMs.
Population dynamics of pod borer, Helicoverpa armigera (Hubner) infesting chickpea.

The results of the investigation on population dynamics of chickpea pod borer, Helicoverpa armigera (Hubner) on chickpea revealed that the pest appeared from 2nd week of December and attained a peak of 3.12 larvae per plant during 2nd week of January. The pest was active during the last week of December to 3rd week of January. Later on, the pest population declined gradually towards the maturity of the crop. Correlation of H. armigera with different weather parameters indicated that maximum temperature exhibited highly significant negative correlation (r=-0.7514) with larval population of H. armigera, whereas, minimum temperature (r=-0.5771) and mean temperature (r=-0.6836) exhibited significant negative correlation. However, the pest population showed highly significant positive correlation with morning relative humidity (r=0.7098), evening relative humidity (r=0.7293) and mean relative humidity (r=0.8063).
Incidental findings on magnetic resonance imaging of lumbosacral spine in patients with back pain and/orradiculopathy

Background and objective: An incidental lesion is an asymptomatic lesion found while examining a patient for an unrelated reason. Lumbar spine imaging may reveal either clinically insignificant spine incidental abnormalities and/or extra-spinal Incidental finding that, at times, may even explain the patient’s symptoms. This study aimed to evaluate the frequency and types of incidental findings in lumbosacral magnetic resonance examination and to find the correlation between the frequency distribution of findings in terms of age and sex. Methods: This cross-sectional study involved 1250 persons who were referred for lumbosacral spine magnetic resonance imaging because of low back pain and/or radiculopathy. The magnetic resonance images were viewed to evaluate the frequency of incidental findings which were divided into extra and intraspinal findings. Results: Incidental findings were noted in 332 (26.6%) patients of the 1250 comprising 94 (28.3%) males and 238(71.7%) females. Some of them had more than one incidental finding. Cortical and para pelvic renal cysts were the most common extra spinal incidental findings, while vertebral hemangioma was the most common intraspinal incidental finding. Conclusion: Incidental findings were common in magnetic resonance imaging examination of the lumbar spine, and most were clinically insignificant; however some of these findings may be more significant than the spinal problems being evaluated and can have a significant impact on patient management. Therefore, they should be included in the reports since they will give additional and valuable information.
Índices biométricos de duas variedades de cana-de-açúcar

As caracteristicas biometricas das variedades NA 56-79 e CB 41-14 de cana-de-acucar revelaram padroes semelhantes durante um ciclo de crescimento. Tanto o acumulo da fitomassa como o aumento da area foliar, com o tempo, tiveram forma sigmoide sem aparente influencia varietal. O indice de area foliar aumentou ate o valor maximo de 3,7 ao redor de 300 dias apos o plantio (d.a.p.), permanecendo constante ate o final do ciclo. Inicialmente, as folhas representaram mais de 70% da massa seca total; posteriormente, tal proporcao decaiu ate 9% aos 400 d.a. p. Nos estadios iniciais da cultura, houve superproducao de colmos em ambas as variedades, com um pico por volta de 125 d.a. p. Posteriormente, devido, em parte, ao sombreamento e competicao entre as plantas, houve uma reducao natural de 50% no numero de colmos/m 2 . A taxa de crescimento da cultura e a taxa de assimilacao liquida atingiram um maximo por volta de 300 d.a. p. com, respectivamente, 25 e 7 g – m -2 – d -1 .
FAKTOR-FAKTO YANG BERHUBUNGAN DENGAN TINGKAT KEPATUHAN PERAWAT TERHADAP PENGGUNAAN ALAT PELINDUNG DIRI (APD) DI RSUP DR. KARIADI SEMARANG (Studi Kasus di Instalasi Rawat Inap Merak)

As a healthcare service, hospital can also be source of infection. An infection that exist in the hospital, known as Nosocomial infection, can occur in patient, health workers and person who came to the hospital. One of efforts to prevent nosocomial infection is by using personal protective equipments This research uses a quantitative with cross sectional approach. Analysis was done by using Chi square test. The populations of this research are nurses in Merak Inpatient Installation. This research use univariate and bivarite analysis. Based on the result of the research, it is know that 46,8% respondents was disobedience to use personal protective equipments according to procedure. The result of Chi-square test shows that education level of respondents (p=0,021) and peer support (p=0,04) are significantly associated with the obedience level of nurses with the use of personal protective equipments behavior. While age of respondents (p=0,779), Work period of respondents (p=0,871), knowledge of respondents (p= 0,516), attitude of respondents (p=0,354), workload of respondents (p=0,059), regulation (p=0,207), facilities (p=1,000), and Supervision (p=0,642) are not significantly associated with obedience level of nurses to use personal protective equipments. The result of this research study suggests that strict sunction should be applied on the supervision toward non compliant nurse.
A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions

Interference is traditionally viewed as a performance limiting factor in wireless communication systems, which is to be minimized or mitigated. Nevertheless, a recent line of work has shown that by manipulating the interfering signals such that they add up constructively at the receiver side, known interference can be made beneficial and further improve the system performance in a variety of wireless scenarios, achieved by symbol-level precoding (SLP). This paper aims to provide a tutorial on interference exploitation techniques from the perspective of precoding design in a multi-antenna wireless communication system, by beginning with the classification of constructive interference (CI) and destructive interference (DI). The definition for CI is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed. In addition, the extension of CI precoding to other application scenarios as well as for hardware efficiency is also described. Proof-of-concept testbeds are demonstrated for the potential practical implementation of CI precoding, and finally a list of open problems and practical challenges are presented to inspire and motivate further research directions in this area.
Guidance on Communication of Uncertainty in Scientific Assessments

Abstract This document provides guidance for communicators on how to communicate the various expressions of uncertainty described in EFSA's document: ‘Guidance on uncertainty analysis in scientific assessments’. It also contains specific guidance for assessors on how best to report the various expressions of uncertainty. The document provides a template for identifying expressions of uncertainty in scientific assessments and locating the specific guidance for each expression. The guidance is structured according to EFSA's three broadly defined categories of target audience: ‘entry’, ‘informed’ and ‘technical’ levels. Communicators should use the guidance for entry and informed audiences, while assessors should use the guidance for the technical level. The guidance was formulated using evidence from the scientific literature, grey literature and two EFSA research studies, or based on judgement and reasoning where evidence was incomplete or missing. The limitations of the evidence sources inform the recommendations for further research on uncertainty communication.
Changes in fatty acid composition during yogurt processing and their effects on yogurt and probiotic bacteria in milk procured from cows fed different diets

Milk was collected from cows fed four diets consisting of a control (C), C with 2% fish oil (FO), C with 1% each of fish oil and extruded soybeans (FOES), and C with 2% extruded soybeans (ES). Milks were processed and fermented with a starter culture comprised of yogurt (S. thermophilus and L. delbrueckii ssp. bulgaricus) and probiotic (L. acidophilus and bifidobacteria) bacteria. Changes in the fatty acid composition of yogurt mix and yogurt during manufacture and storage were monitored. Also, changes in viable numbers of starter bacteria were monitored in fresh yogurt and after 30 d storage. Milkfat of cows fed C, FO, FOES, and ES diets were 3.31%, 2.58%, 2.94% and 3.47%, respectively. Milk, yogurt mix and yogurt from cows fed with FO or FOES diets showed a 4-fold increase (p 0.05) on fatty acids composition, especially CLA, TVA, and omega-3 fatty acids. Further, changes in fatty acids composition (as a result of change in diet) did not show any significant effects on the viable numbers of starter bacteria. Viable numbers of yogurt bacteria were >10 7 /g and probiotic bacteria were >10 5 /g at the end of 30 d storage periods. Fermentation with yogurt and probiotic bacteria and storage did not alter (p>0.05) the CLA, TVA, or omega-3 fatty acids. Thus, probiotic yogurt made from milk with increased CLA and TVA can be produced by changing the diets of cows and it could offer health benefits to consumers.
Performance of crossbred female calves fed complete ration as mash or block vis-à-vis conventional ration.

An experiment was conducted to discern the effect of feeding complete ration as mash or block form in comparison to conventional feeding system on feed intake, growth, nutrient utilization and certain blood biochemical parameters in growing crossbred female calves. Crossbred female calves (15) of 8 – 11 months age were divided into 3 groups of 5 calves each on the basis of body weight. Calves in control, group 1 (G 1) were fed wheat straw ad lib. and concentrate mixture separately as per requirement along with 2 kg green fodder (mixed green oats + mustard + berseem) to each calf daily. The same concentrate mixture as in group 1, wheat straw and green fodder on as such basis in the ratio of 40 : 40 : 20 were blended into uniform mix as complete feed mash and fed to calves in group 2 (G 2), whereas the calves in group 3 (G 3) were fed complete feed processed into block containing the same concentrate mixture, wheat straw and green fodder in the ratio of 40 : 40 : 20 as in group 2 on as such basis and fed ad lib. along with 1 kg green fodder. Feeding trial lasted for 90 days. Average daily weight gain was 509, 556 and 496 g in G 1, G 2 and G 3, respectively. There was no significant difference in average daily weight gain in crossbred calves of different groups, although calves in group 2 fed complete feed mash gained higher body weight than calves in G 1 and G 3. The calves in G 2 fed a complete ration in mash form consumed significantly higher DM/kg W0.75 than the calves in G 3 and equal to calves in G 1 during the whole feeding trial. During the digestion trial, there was no difference in DM intake between G 1 and G 3 and between G1 and G 2, whereas DCP intake (g/kg W0.75) was significantly higher in calves of G 1 and G 2 than in calves of G 3. The digestibility of DM, OM, CP and NFE did not differ significantly among the groups, whereas the digestibility of EE differed significantly, and it was significantly higher in G 2 than in G 1 and G 3. The serum glucose, total protein, albumin and globulin concentrations and SGOT activities were similar among different groups, whereas serum alkaline phosphatase and SGPT activity were significantly lower in G 3 as compared to G 1 but the difference was nonsignificant between G 1 and G 2. It was inferred that feeding of complete ration in mash form is beneficial in terms of feed intake, body weight gain, nutrient utilization and feed conversion efficiency in growing crossbred female calves in comparison to conventional feeding system and also with complete feed in block form.
Stable Model Semantics for Recursive SHACL

SHACL (SHape Constraint Language) is a W3C recommendation for validating graph-based data against a set of constraints (called shapes). Importantly, SHACL allows to define recursive shapes, i.e. a shape may refer to itself, directly of indirectly. The recommendation left open the semantics of recursive shapes, but proposals have emerged recently to extend the official semantics to support recursion. These proposals are based on the principle of possibility (or non-contradiction): a graph is considered valid against a schema if one can assign shapes to nodes in such a way that all constraints are satisfied. This semantics is not constructive, as it does not provide guidelines about how to obtain such an assignment, and it may lead to unfounded assignments, where the only reason to assign a shape to a node is that it allows validating the graph. In contrast, we propose in this paper a stricter, more constructive semantics for SHACL, based on stable models, which are well-known in Answer Set Programming (ASP). This semantics additionally requires a shape assignment to be properly justified by the input constraints. We further exploit the connection to logic programming, and show that SHACL constraints can be naturally represented as logic programs, and that the validation problem for a graph and a SHACL schema can be encoded as an ASP reasoning task. The proposed semantics also enjoys computationally tractable validation in the presence of constraints with stratified negation (as opposed to the previous semantics). We also extend our semantics to 3-valued stable models, which yields a more relaxed notion of validation, tolerant to certain faults in the schema or data. By exploiting a connection between 3-valued stable model semantics and the well-founded semantics for logic programs, we can use our translation into ASP to show another tractability result. Finally, we provide a preliminary evaluation of the approach, which leverages an ASP solver to perform graph validation.
Identification of Helicobacter pylori in Saliva of Patients with and without Gastritis by Polymerase Chain Reaction

Aims and Objective: The aim of this study was to identify the presence of Helicobacter pylori in saliva of patients with and without gastritis by polymerase chain reaction (PCR) method. Materials and Methods: The study comprised 20 patients in Group I presenting with various symptoms of gastritis and 10 asymptomatic subjects in Group II. The intestinal endoscopy antral biopsies were collected from 20 symptomatic patients with gastroduodenal disorders. The saliva specimens were taken from all patients before endoscopy. PCR was performed using genomic DNA, isolated from the saliva and the biopsies of the patients as the template to detect the presence of the 16S ribosomal RNA gene in H. pylori. Results: In Group I, 10 (50%) cases of clinical gastritis were positive for H. pylori by endoscopy biopsy and 10 (50%) were negative. Of the 10 endoscopy biopsy positive cases for H. pylori, eight were PCR positive in saliva and two were negative. Of the 10 endoscopy biopsy negative cases, three were PCR positive for H. pylori in saliva and seven were negative. In Groups II, four were symptomatic for gastritis and six were negative. Of the six gastritis negative cases, three were PCR positive, four were gastritis positive, and three were PCR positive. Sensitivity and specificity of PCR were found to be 80% and 70%, respectively. The positive predictive and negative predictive values of PCR in saliva were 72.7% and 77.7%, respectively. Conclusion: PCR analysis of saliva may be handy in identification of H. pylori and serves as a noninvasive technique to diagnose and monitor the prognosis.
Monocular depth estimation for image segmentation and filtering

This Ph.D. dissertation addresses the problem of estimating depth ordering information from single images, a key issue in image understanding that in recent years has focused the interest of the community. Motivation behind this tendency is provided by several important applications that could beneficiate of advances in the field such as automatic object removal, image indexing, 3D scene reconstruction and synthesis. In contrast to state-of-the-art works, this Ph.D. dissertation investigates a general low-level approach to the problem of monocular depth estimation, in which the depth ordering is directly inferred from a set of monocular depth cues without relying on any previously learned contextual information nor on any assumption on the image structure. New methods for monocular depth cue detection are proposed, the problem of depth cue integration is analysed, and depth ordering information is exploited to improve classical color segmentation, and create new depth-oriented fitering applications. The investigation for depth cue integration leads to the development of two distinct frameworks based on different strategies: a diffusion based strategy and a region merging based strategy. The former is based on the use of a nonlinear filter which iteratively extends initial depth values arisen from monocular depth cues to the entire image domain until stability is attained. The result is a flexible framework that allows the integration of several monocular depth cues and that gives a correct interpretation of a plurality of vision phenomena. The latter strategy is based on the construction of a hierarchical region-based representation of images, that incorporates depth ordering information provided by depth cues, as well as on a graph formalization, which encodes depth relationships between regions and allows to infer a global, consistent depth ordering.
Detection and Classification of Acoustic Scenes and Events

For intelligent systems to make best use of the audio modality, it is important that they can recognize not just speech and music, which have been researched as specific tasks, but also general sounds in everyday environments. To stimulate research in this field we conducted a public research challenge: the IEEE Audio and Acoustic Signal Processing Technical Committee challenge on Detection and Classification of Acoustic Scenes and Events (DCASE). In this paper, we report on the state of the art in automatically classifying audio scenes, and automatically detecting and classifying audio events. We survey prior work as well as the state of the art represented by the submissions to the challenge from various research groups. We also provide detail on the organization of the challenge, so that our experience as challenge hosts may be useful to those organizing challenges in similar domains. We created new audio datasets and baseline systems for the challenge; these, as well as some submitted systems, are publicly available under open licenses, to serve as benchmarks for further research in general-purpose machine listening.
Bit Error Rate for NOMA Network

This letter examines the bit error rate (BER) performance of downlink non-orthogonal multiple access networks for binary phase-shift keying modulation. Exact BER expression is derived for each user in closed-form under additive white Gaussian noise and Rayleigh fading channels in perfect and imperfect successive interference cancellation (SIC) cases. Next, in perfect SIC case, the asymptotic BER expression in a high signal-to-noise ratio (SNR) region is obtained to express the behavior of the network with diversity and array gains. On the other hand, in imperfect SIC case, the upper bound for BER is attained, and at high SNR values, the BER reveals an error floor, and hence a zero diversity gain is achieved. Then, a feasible range of power allocation coefficients is found such that a good BER performance can be provided for each user. Finally, through simulations and software-defined radio-based real-time tests, analytical results are validated.
Clinical study of ankle fractures and role of fibula fixation

The objective of this study was to classify the different clinical scenarios in ankle fractures, looking at their mechanism of injury, relevant to the mode of treatment and to determine the functional outcome and role of fixation of the fibula. Out of forty patients treated, overall good to excellent results were obtained in 36 patients. The results were fair and poor in two patients each. There were no intraoperative complications. The only postoperative complication seen was superficial skin infection in eight patients.