Miracle-dz/UniFAR-FTUs huggingface dataset:
Hypothesis Testing in High-Dimensional Instrumental Variables Regression with an Application to Genomics Data

Gene expression and phenotype association can be affected by potential unmeasured confounders from multiple sources, leading to biased estimates of the associations. Since genetic variants largely explain gene expression variations, they can be used as instruments in studying the association between gene expressions and phenotype in the framework of high dimensional instrumental variable (IV) regression. However, because the dimensions of both genetic variants and gene expressions are often larger than the sample size, statistical inferences such as hypothesis testing for such high dimensional IV models are not trivial and have not been investigated in literature. The problem is more challenging since the instrumental variables (e.g., genetic variants) have to be selected among a large set of genetic variants. This paper considers the problem of hypothesis testing for sparse IV regression models and presents methods for testing single regression coefficient and multiple testing of multiple coefficients, where the test statistic for each single coefficient is constructed based on an inverse regression. A multiple testing procedure is developed for selecting variables and is shown to control the false discovery rate. Simulations are conducted to evaluate the performance of our proposed methods. These methods are illustrated by an analysis of a yeast dataset in order to identify genes that are associated with growth in the presence of hydrogen peroxide.
Towards Automatic Annotation for Semantic Segmentation in Drone Videos

Semantic segmentation is a crucial task for robot navigation and safety. However, it requires huge amounts of pixelwise annotations to yield accurate results. While recent progress in computer vision algorithms has been heavily boosted by large ground-level datasets, the labeling time has hampered progress in low altitude UAV applications, mostly due to the difficulty imposed by large object scales and pose variations. Motivated by the lack of a large video aerial dataset, we introduce a new one, with high resolution (4K) images and manually-annotated dense labels every 50 frames. To help the video labeling process, we make an important step towards automatic annotation and propose SegProp, an iterative flow-based method with geometric constrains to propagate the semantic labels to frames that lack human annotations. This results in a dataset with more than 50k annotated frames - the largest of its kind, to the best of our knowledge. Our experiments show that SegProp surpasses current state-of-the-art label propagation methods by a significant margin. Furthermore, when training a semantic segmentation deep neural net using the automatically annotated frames, we obtain a compelling overall performance boost at test time of 16.8% mean F-measure over a baseline trained only with manually-labeled frames. Our Ruralscapes dataset, the label propagation code and a fast segmentation tool are available at our website: this https URL
The Structure of Solar Coronal Mass Ejections in the Extreme-ultraviolet Passbands

So far, most studies on the structure of coronal mass ejections (CMEs) are conducted through white-light coronagraphs, demonstrating that about one third of CMEs exhibit the typical three-part structure in the high corona (e.g., beyond 2 ), i.e., the bright front, the dark cavity, and the bright core. In this paper, we address the CME structure in the low corona (e.g., below 1.3 ) through extreme-ultraviolet (EUV) passbands and find that the three-part CMEs in the white-light images can possess a similar three-part appearance in the EUV images, i.e., a leading edge, a low-density zone, and a filament or hot channel. The analyses identify that the leading edge and the filament or hot channel in the EUV passbands evolve into the front and the core later within several solar radii in the white-light passbands, respectively. What is more, we find that the CMEs without an obvious cavity in the white-light images can also exhibit the clear three-part appearance in the EUV images, which means that the low-density zone in the EUV images (observed as the cavity in white-light images) can be compressed and/or transformed gradually by the expansion of the bright core and/or the reconnection of the magnetic field surrounding the core during the CME propagation outward. Our study suggests that more CMEs can possess the clear three-part structure in their early eruption stage. The nature of the low-density zone between the leading edge and the filament or hot channel is discussed.
X-ray Transform in Asymptotically Conic Spaces

In this article, we study the properties of the geodesic X-ray transform for asymptotically Euclidean or conic Riemannian metrics and show injectivity under non-trapping and no conjugate point assumptions. We also define a notion of lens data for such metrics and study the associated inverse problem.
Galactic outflow rates in the EAGLE simulations

We present measurements of galactic outflow rates from the eagle suite of cosmological simulations. We find that gas is removed from the interstellar medium (ISM) of central galaxies with a dimensionless mass loading factor that scales approximately with circular velocity as $V_{\mathrm{c}}^{-3/2}$ in the low-mass regime where stellar feedback dominates. Feedback from active galactic nuclei causes an upturn in the mass loading for halo masses ${\gt}10^{12} \, \mathrm{M_\odot }$. We find that more gas outflows through the halo virial radius than is removed from the ISM of galaxies, particularly at low redshifts, implying substantial mass loading within the circumgalactic medium. Outflow velocities span a wide range at a given halo mass/redshift, and on average increase positively with redshift and halo mass up to $M_{200} \sim 10^{12} \, \mathrm{M_\odot }$. Outflows exhibit a bimodal flow pattern on circumgalactic scales, aligned with the galactic minor axis. We present a number of like-for-like comparisons to outflow rates from other recent cosmological hydrodynamical simulations, and show that comparing the propagation of galactic winds as a function of radius reveals substantial discrepancies between different models. Relative to some other simulations, eagle favours a scenario for stellar feedback where agreement with the galaxy stellar mass function is achieved by removing smaller amounts of gas from the ISM, but with galactic winds that then propagate and entrain ambient gas out to larger radii.
Adversarial Example Detection by Classification for Deep Speech Recognition

Machine Learning systems are vulnerable to adversarial attacks and will highly likely produce incorrect outputs under these attacks. There are white-box and black-box attacks regarding to adversary’s access level to the victim learning algorithm. To defend the learning systems from these attacks, existing methods in the speech domain focus on modifying input signals and testing the behaviours of speech recognizers. We, however, formulate the defense as a classification problem and present a strategy for systematically generating adversarial example datasets: one for white-box attacks and one for black-box attacks, containing both adversarial and normal examples. The white-box attack is a gradient-based method on Baidu DeepSpeech with the Mozilla Common Voice database while the black-box attack is a gradient-free method on a deep model-based keyword spotting system with the Google Speech Command dataset. The generated datasets are used to train a proposed Convolutional Neural Network (CNN), together with cepstral features, to detect adversarial examples. Experimental results show that, it is possible to accurately distinct between adversarial and normal examples for known attacks, in both single-condition and multi-condition training settings, while the performance degrades dramatically for unknown attacks. The adversarial datasets and the source code are made publicly available.
Bacteriology of Peritonitis in Children Treated at the University Hospital of Marrakech

Child peritonitis are severe intra-abdominal infections, involving vital prognosis. The available microbiological data of peritonitis in children are inadequate, and antibiotic therapy is not consensual. Description of the bacteriological profile and the antibiotic resistance of the isolated bacteria in the various samples of peritoneal fluid from the different departments of the University Hospital of Marrakech. It is a descriptive study spread over two years. carried out at the Laboratory of Microbiology of the Mohamed VI Hospital of Marrakech (CHU MED VI), covering all the bacterial strains, isolated in the peritoneal fluid samples from the various pediatric departments of the University Hospital. During this period, 92 samples were treated in the laboratory with a positivity rate of 80%. The average age of his children is 11.7 years with a sex ratio of 1.4. The infection was polymicrobial in 40%. Escherichia. coli dominated the bacteriological profile of these peritonitis in 74% of cases, followed by Streptococcus spp (30%), Pseudomonas aeruginosa (18%), Enterobacter cloacae (6%) and Klebsiella pneumoniae (1%). The susceptibility to amoxicillin in enterobacteria isolated from peritonitis was 32%, 68% for amoxicillin/clavulanic acid, 92% for 3rd generation cephalosporins, 97% for fluoroquinolones, 67% for cotrimoxazole and 89% for gentamycin. Only one strain of Pseudomonas aeruginosa was resistant to ceftazidime. All strains remained sensitive to amikacin and carbapenems. Resistance of Enterobacteria to 3rd generation cephalosporins by the production of Extended Spectrum Betalactamase (ESBL) in the isolates was 4%. This prompts us to reconsider our therapeutic approach. We believe that the association C3G + aminoglycoside + metronidazole should be used first-line in severe pediatric peritonitis in our context. The quick initiation of an antibiotic therapy adapted to the resistance profile would be an important factor in improving the prognosis, hence the interest of close collaboration between surgeons, anesthesiologist-intensive care and microbiologists.
A Parallel Bi-objective Hybrid Genetic Algorithm to Minimize Energy Consumption and Makespan Using Dynamic Voltage Scaling

Precedence-constrained parallel applications are one of the most typical application models used in scientific and engineering fields. Such applications can be deployed on homogeneous or heterogeneous systems. Only recently that some works were interested in minimizing the energy consumption. Various techniques including dynamic voltage scaling (DVS), resource hibernation, and memory optimizations have been investigated and developed. DVS among these has been proven to be a very promising technique with its demonstrated capability for energy savings. For this reason, we adopt this technique and it is of particular interest to this study. In this paper, we investigated the energy issue in task scheduling particularly on high-performance computing systems (HCSs). We propose a new parallel island-based bi-objective hybrid algorithm that takes into account, not only makespan, but also energy consumption. The remainder of the paper is organized as follows. Section 2 describes the related work. Our algorithm is presented in Section 3. The results of our comparative evaluation study are discussed in Section 4. The conclusion is drawn in Section 5.
Bulletin of the Geological Society of Greece

Due to their high extinction rate, the Molluscs of the Pliocene in the Mediterranean, resulted potentially useful as a tool for climatic-oceanographic and chronological inferences. In the present study, we document the possibility of application of the model of Raffi and Monegatti (1993) in the region of Eastern Mediterranean, by studying two examples from the Hellenic area and Cyprus. This model concerns the extinction events of Molluscs of Pliocene, separating 4 dif­ ferent units of Molluscs with different climatic-oceanographic importance. It is docu­ mented that the two selected sections, Atsipades in central Crete and Athienou in southern Cyprus, give elements for the correlation of their deposits with this model. The Atsipades section is connected with the first significant extinction event, at the Mollusc Units of Raffi and Monegatti, resulting from the first important Pliocene cooling phenomenon of our hemisphere. The Athienou section is connected with the MPMU2 unit of Raffi and Monegatti, between the first and second distinctive extinction events of the Pliocene Molluscs.
Benign Breast Diseases: Profile at a Teaching Hospital

Benign breast diseases are the most common cause of breast problems. About a quarter of women during her lifetime will suffer from a benign breast disorder that requires some form of treatment. The most common symptoms are breast pain, lumpiness or a lump and nipple discharge. Triple assessment that includes clinical examination, imaging like ultrasonography (USG) or mammography and a pathological examination – FNAC or core needle biopsy has a very high accuracy rate in diagnosing, discrete benign breast diseases and this can be used for reassurance. This was a hospital based prospective study to determine the frequency of benign breast diseases and their pattern. Demographic data, investigations and histopathological diagnosis were collected and analyzed from patients who attended presenting to the department of surgery with breast complaints. The clinical diagnoses were compared with final diagnosis. After that they were appropriately managed. There were 160 patients in the cohort. Out of the patients presenting with benign breast diseases female (96%) were predominant. The majority of the patients (67%) were in the age group of 21 years to 40 years. The commonest presentation of benign breast diseases was pain (45%), followed by lump (26%). Fibroadenoma accounted for 46%. This study showed that among the benign breast diseases in females there were preponderance of mastalgia and fibroadenoma followed by fibrocystic diseases.
Terrain Segmentation and Roughness Estimation using RGB Data: Path Planning Application on the CENTAURO Robot

Robots operating in real world environments require a high-level perceptual understanding of the chief physical properties of the terrain they are traversing. In unknown environments, roughness is one such important terrain property that could play a key role in devising robot control/planning strategies. In this paper, we present a fast method for predicting pixel-wise labels of terrain (stone, sand, road/sidewalk, wood, grass, metal) and roughness estimation, using a single RGB-based deep neural network. Real world RGB images are used to experimentally validate the presented approach. Furthermore, we demonstrate an application of our proposed method on the centaur-like wheeled-legged robot CENTAURO, by integrating it with a navigation planner that is capable of re-configuring the leg joints to modify the robot footprint polygon for stability purposes or for safe traversal among obstacles.
VALIDATION OF THE POSITIVE BEHAVIORS QUESTIONNAIRE IN EDUCATIVE

The aim of the current research was to validate into the educative dance in Mexican secondary school, the questionnaire of positive behaviors in physical education. The sample was formed by 921 students, both female (n = 421) and male (n = 500) participants, ranging in age from 11 to 17 years old, belonged to four schools from Mexico. This research was organized by ConArte (International Consortium of Art and School). The results showed that the instrument had an adequate factorial validity and internal consistency. Furthermore, the instrument was invariant regarding individuals ́ gender and age. Thus, this work gives empiric evidences that the questionnaire of positive behaviors in educative dance is valid and reliable to assess these behaviors.
The Heterogeneous Impact of Market Size on Innovation: Evidence from French Firm-Level Exports

We analyze how demand conditions faced by a firm in its export markets affect its innovation decisions. We exploit exogenous firm-level export demand shocks and find that firms respond by patenting more; furthermore this response is driven by the subset of initially more productive firms. The patent response arises 2 to 5 years after the shock, highlighting the time required to innovate. In contrast, the demand shock raises contemporaneous sales and employment for all firms regardless of their productivity. This skewed innovation response to common demand shocks arises naturally from a model of endogenous innovation and competition with firm heterogeneity.
Title : Habitat-dependent effects of personality on survival and reproduction in red squirrels 1 2

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Does Mandatory Ifrs Adoption and Macroeconomic Factors Affect Cost of Equity Capital? Empirical Evidence From South African Listed Firms

Purpose: This paper investigates the collaboration of International Financial Reporting Standards (IFRS) adopted and macroeconomic variables interaction with information asymmetry, analysts following and managerial opportunism affecting the cost of equity capital, and also influence investor’s decision taking on companies in South Africa. Design/Approach: A sample of 49 listed Johannesburg mining and manufacturing firms was extracted from archival database of INET BFA/IRESS SA, Morningstar, and Anupedia. A leverage fixed effects panel data set of firms from 2001 to 2014 was examined, which shows that Breusch-Lagrange Multiplier tests and the test of over-identifying restrictions used, form the basis of the content analysis of the most recent IFRS effect after mandatory adoption. We used a hand-collected dataset between 2000 and 2015. Findings: Our findings suggest that a signiﬁcant association is found between IFRS and its interactions with managerial opportunism and integrity but with a reasonable statistical effect. However, the IFRS adoption effect on the cost of equity capital of South African firms’ has no significant effect. Practical implications: This study reveals that most firms report more, the credibility of annual financial statements which may not be sufﬁcient because of the qualitative data for an assessment of managerial opportunism, information asymmetry and analysts following. Of such myopia of company managers, their reputation causes agency problems and as a result, shareholders interest is mainly focused on improving reporting standards Originality: The research considers dual harmonizing facets: ﬁrst, that the interaction with IFRS adoption and economic factors impact on the cost of equity capital may be so pathetic and obvious; and second, that IFRS moderation impacts on the cost of equity capital in Sub- Saharan African. This finding should be meaningful to managers, analysts, policymakers, and supervisory bodies in nations with similar capital structure decisions and socioeconomic systems.
Do Investors Value Dividend Smoothing Stocks Differently?

It is widely documented that managers strive to maintain smooth dividends. Yet, it is not clear if this behavior reflects investors’ preferences. In this paper, we study whether investors indeed value dividend smoothing stocks differently by exploring the implications of dividend smoothing for firms’ investor clientele, stock prices and cost of capital. We find that retail investors are less likely to hold dividend smoothing stocks, while institutional investors, and especially mutual funds, are more likely. However, this preference does not result in any detectable relation between the smoothness of a firm’s dividends and the expected return, or market value, of its stock. Together, the evidence suggests that firms adjust the supply of smoothed dividends to match investors’ demand. Dividend smoothing affects the composition of a firm’s shareholders but has little impact on its stock price.
Implementation of the nursing process in Portuguese hospitals

Objective: To obtain a description of the implementation of the nursing process by nurses who work in hospitals. Methods: Qualitative, descriptive study that was carried out in 19 hospitals in Continental Portugal with 56 nurses. Data were collected through a semi-structured interview. Results: Content analysis originated the categories nursing process, initial evaluation, diagnosis, planning, implementation, and final evaluation. Although there has been a progressive appropriation of the nursing process in the past years, the description of nurses’ practices evinces some weaknesses. Conclusion: The results of this study show that the application of the nursing process requires more clarification and comprehensiveness of the contents included in its stages.
Effects of insoluble per soluble dietary fiber ratio in weaned pig diet on visceral organ weight and gut morphology นุจริา ทกัษิณานันต์

Insoluble dietary fiber (iDF) has many physiological effects on the digestive system. This study aims to investigate effects of the ratio of insoluble per soluble dietary fiber (iDF:sDF ratio) in weaning pig diet on digestive tract development. Total 64 crossbred pigs, weaned at 21±3 days with initial weight about 6±0.5 kg, were randomized to feed four experimental diets: control diet (CON), and 3 differences iDF:sDF ratio: 4±0.5 (R4), 5±0.5 (R5) and 6±0.5 (R6), respectively. All diets were cornbroken rice-soybean meal based diets. The visceral organ weight and gut morphology were collected at 29 days after weaning. The result show increasing iDF:sDF ratio was decreased small intestine weight significantly (P=0.025) and numerically increased large intestine weight (P=0.850) while the weight of stomach was not changed (P=0.214). The duodenal villus height trended to decrease that cause of lower the villus height per crypt depth ratio (VH:CD ratio) in the pig fed R5 and R6 diets (P=0.214). In jejunum, pig fed high iDF:sDF ratio tended to increase villus height. However, the pigs fed R6 diet had greater VH:CD ratio than the others (P=0.004) due to high villus height and less crypt depth. In summary, the increasing of iDF:sDF ratio had negative effect of small intestine weight and decreased the VH:CD ratio in duodenum and jejunum in small intestine.
The role of computed tomography in the evaluation of the spread of ovarian cancer

The aim: To determine the role of CT in the evaluation of the spread of ovarian cancer. Methods: The data of 64 female patients who underwent abdominal and pelvic CT examinations due to the suspicion of ovarian cancer during 2014–2015 in HLUHS CK were analyzed. All patients were operated and ovarian cancer was confirmed histologically. Results: The average age of the patients was 60,06 ± 14,95 years. By the histological type, 37 (57,7%) cases of tumor were serous type. By the differentiation degree, 41 (63,5%) cases of tumor were G3. 27 (42,2%) of all the cases of ovarian cancer were diagnosed in the stage IIIC. CT sensitivity in the assessment of pathological lymph nodes was 41,9%, specificity – 81,8%, PPV – 68,4%, NPV – 60,0%, accuracy – 51,6%. CT sensitivity in the evaluation of peritoneal carcinomatosis was 62,5%, specificity – 81,3%, PPV – 90,9%, NPV – 41,9%, accuracy – 67,2%. The CT sensitivity to ascites was – 86,5%, specificity – 88,9%, PPV – 91,4%, NPV – 82,8%, accuracy – 87,5%. Conclusions: 1. The symptoms of the ovarian cancer spread were determined more frequent in high-grade tumors. 2. Larger ovarian tumors typically were spread to the bladder and rectum. 3. The results of lymph nodes and peritoneal carcinomatosis showed that CT had moderate sensitivity, NPV, and accuracy, but it had high specificity. According to the pathological lymph nodes, PPV was average, but high according to peritoneal carcinomatosis. 4. The evaluation of ascites showed that CT sensitivity, specificity, PPV, NPV, and accuracy were high.