Miracle-dz/UniFAR-FTUs huggingface dataset:
Training for Faster Adversarial Robustness Verification via Inducing ReLU Stability

We explore the concept of co-design in the context of neural network verification. Specifically, we aim to train deep neural networks that not only are robust to adversarial perturbations but also whose robustness can be verified more easily. To this end, we identify two properties of network models - weight sparsity and so-called ReLU stability - that turn out to significantly impact the complexity of the corresponding verification task. We demonstrate that improving weight sparsity alone already enables us to turn computationally intractable verification problems into tractable ones. Then, improving ReLU stability leads to an additional 4-13x speedup in verification times. An important feature of our methodology is its "universality," in the sense that it can be used with a broad range of training procedures and verification approaches.
Identifying emerging topics and difficulties in software engineering education in Brazil

Technological evolution has contributed to the emergence of new paradigms and trends that meet demands of a dynamic market. In this context, teaching software engineering (SE) becomes a challenge. SE professors in turn seek strategies to prepare students for dealing with industry's demands. Therefore, it is important to know how emerging SE topics has affected the teaching-learning process. This paper aims to identify the emerging SE topics in undergraduate courses in the Brazilian scenario and difficulties in its teaching-learning process. A survey with SE professors was carried out and allowed us to identify a set of emerging topics explored in Brazilian SE courses as well as underlying difficulties in the teaching-learning process. Qualitative analysis was applied. Some topics identified from the dataset were agile methods, reuse, software architecture, software product lines, SE for software as a service, SE for startups, among others. Relations between such emerging topics and difficulties regarding pedagogy, materials, students and content were identified as well.
Delivery-Secrecy Tradeoff for Cache-Enabled Stochastic Networks: Content Placement Optimization

Wireless caching has been widely recognized as a promising technique for efficient content delivery. In this paper, by taking different file secrecy levels into consideration, physical-layer security oriented content placement is optimized in a stochastic cache-enabled cellular network. We propose an analytical framework to investigate the nontrivial file delivery-secrecy tradeoff. Specifically, we first derive the closed-form expressions for the file hit and secrecy probabilities. The globally optimal probabilistic content placement policy is then analytically derived in terms of hit probability maximization under file secrecy constraints. Numerical results are demonstrated to verify our analytical findings and show that the targeted file secrecy levels are crucial in balancing the file delivery-secrecy tradeoff.
Treatment Response Analysis in Patients with Multidrug Resistant Tuberculosis (MDR TB) at Labuang Baji Public Hospital in Makassar City

This study aims to describe the results of analysis of some risk factors including education level, income level, treatment compliances, comorbidity history, role of health centre staff, and family support in relation with treatment response in patients with Multidrug Resistant Tuberculosis (MDR TB). The research was conducted at Labuang Baji Public Hospital in Makassaar city. It used the retrospective cohort research design with a total sample of 48 people. The sampling technique used in the research was the purposive sampling. The data were collected using direct interviews with a questionnaire, and they were analyzed with univariate, bivariate, and multivariate methods using the Relative Risk (RR) test. The result reveal that the significant risk factor is treatment compliance (RR = 4.25, 95% CI = 2.007 to 9.021; p = 0.000), while the insignificant factors are the level of education (RR = 1.04; 95% CI= 0.504 to 2.151), income level (RR = 1.13; 95% CI= 0.432 to 2.973) comorbidity history (RR = 1.02; 95% CI=0.514 - 2.013), support from health centre staff (RR= 1.81, 95% CI= 0.969 - 3.385) and family support (RR= 1.94; 95% CI=0.986 - 3.821). The multivariate analysis shows that treatment compliance is the most significant risk factor for the result of treatment response in patients with MDR TB (RR = 17.930)
ViZDoom Competitions: Playing Doom From Pixels

This paper presents the first two editions of Visual Doom AI Competition, held in 2016 and 2017. The challenge was to create bots that compete in a multiplayer deathmatch in a first-person shooter game Doom. The bots had to make their decisions solely based on visual information, i.e., a raw screen buffer. To play well, the bots needed to understand their surroundings, navigate, explore, and handle the opponents at the same time. These aspects, together with the competitive multiagent aspect of the game, make the competition a unique platform for evaluating the state-of-the-art reinforcement learning algorithms. This paper discusses the rules, solutions, results, and statistics that give insight into the agents’ behaviors. Best performing agents are described in more detail. The results of the competition lead to the conclusion that, although reinforcement learning can produce capable Doom bots, they still are not yet able to successfully compete against humans in this game. This paper also revisits the ViZDoom environment, which is a flexible, easy to use, and efficient three-dimensional platform for research for vision-based reinforcement learning, based on a well-recognized first-person perspective game Doom.
Case studies for software engineers

The topic of this paper was the correct use and interpretation of case studies as an empirical research method. Using an equal blend of lecture and discussion, it gave a foundation for conducting, reviewing, and reading case studies. There were lessons for software engineers as researchers who conduct and report case studies, reviewers who evaluate papers, and practitioners who are attempting to apply results from papers. The main resource for the course was the book Case Study Research: Design and Methods by Robert K. Yin. This text was supplemented with positive and negative examples from the literature.
Hidden Hunger: Solutions for America’s Aging Populations

The global population, including the United States, is experiencing a demographic shift with the proportion of older adults (aged ≥ 65 years) growing faster than any other age group. This demographic group is at higher risk for developing nutrition-related chronic conditions such as heart disease and diabetes as well as infections such as influenza and pneumonia. As a result, an emphasis on nutrition is instrumental for disease risk reduction. Unfortunately, inadequate nutrient status or deficiency, often termed hidden hunger, disproportionately affects older adults because of systematic healthcare, environmental, and biological challenges. This report summarizes the unique nutrition challenges facing the aging population and identifies strategies, interventions, and policies to address hidden hunger among the older adults, discussed at the scientific symposium “Hidden Hunger: Solutions for America’s Aging Population”, on March 23, 2018.
Molecular and Physio-Biochemical Characterization of Cotton Species for Assessing Drought Stress Tolerance

Drought stress significantly limits cotton growth and production due to the necessity of water at every stage of crop growth. Hence, it is essential to identify tolerant genetic resources and understand the mechanisms of drought tolerance in economically and socially important plants such as cotton. In this study, molecular and physio-biochemical investigations were conducted by analyzing different parameters by following standard protocols in three different cotton species, namely TM-1 (Gossypium hirsutum), Zhongmian-16 (Gossypium arboreum), and Pima4-S (Gossypium barbadense). Drought stress significantly decreased plant growth, chlorophyll content, net photosynthetic rate (Pn), stomatal conductance (Gs), maximum photochemical efficiency of PSII (Fv/Fm), and relative water content. TM-1 resulted in more tolerance than the other two species. The accumulation of proline, soluble proteins, soluble sugars, hydrogen peroxide (H2O2), and superoxide radicals (O2•−) increased significantly in TM-1. In addition, TM-1 maintained the integrity of the chloroplast structure under drought conditions. The relative expression level of drought-responsive genes including coding for transcription factors and other regulatory proteins or enzymes controlling genes (ERF, ERFB, DREB, WRKY6, ZFP1, FeSOD, CuZnSOD, MAPKKK17, P5CR, and PRP5) were higher in TM-1 under drought, conferring a more tolerant status than in Zhongmian-16 and Pima4-S. The findings of this research could be utilized for predicting a tolerant cotton genotype as well as evaluating prospective cotton species in the variety development program.
Fully Functional Suffix Trees and Optimal Text Searching in BWT-Runs Bounded Space

Indexing highly repetitive texts—such as genomic databases, software repositories and versioned text collections—has become an important problem since the turn of the millennium. A relevant compressibility measure for repetitive texts is r, the number of runs in their Burrows-Wheeler Transforms (BWTs). One of the earliest indexes for repetitive collections, the Run-Length FM-index, used O(r) space and was able to efficiently count the number of occurrences of a pattern of length m in a text of length n (in O(m log log n) time, with current techniques). However, it was unable to locate the positions of those occurrences efficiently within a space bounded in terms of r. In this article, we close this long-standing problem, showing how to extend the Run-Length FM-index so that it can locate the occ occurrences efficiently (in O(occ log log n) time) within O(r) space. By raising the space to O(r log log n), our index counts the occurrences in optimal time, O(m), and locates them in optimal time as well, O(m + occ). By further raising the space by an O(w/ log σ) factor, where σ is the alphabet size and w = Ω (log n) is the RAM machine size in bits, we support count and locate in O(⌈ m log (σ)/w ⌉) and O(⌈ m log (σ)/w ⌉ + occ) time, which is optimal in the packed setting and had not been obtained before in compressed space. We also describe a structure using O(r log (n/r)) space that replaces the text and extracts any text substring of length ℓ in the almost-optimal time O(log (n/r)+ℓ log (σ)/w). Within that space, we similarly provide access to arbitrary suffix array, inverse suffix array, and longest common prefix array cells in time O(log (n/r)), and extend these capabilities to full suffix tree functionality, typically in O(log (n/r)) time per operation. Our experiments show that our O(r)-space index outperforms the space-competitive alternatives by 1--2 orders of magnitude in time. Competitive implementations of the original FM-index are outperformed by 1--2 orders of magnitude in space and/or 2--3 in time.
Macrophages of distinct origins contribute to tumor development in the lung

Tissue-resident macrophages can self-maintain without contribution of adult hematopoiesis. Herein we show that tissue-resident interstitial macrophages (Res-TAMs) in mouse lungs contribute to the pool of tumor-associated macrophages (TAMs) together with CCR2-dependent recruited macrophages (MoD-TAMs). Res-TAMs largely correlated with tumor cell growth in vivo, while MoD-TAMs accumulation was associated with enhanced tumor spreading. Both cell subsets were depleted after chemotherapy, but MoD-TAMs rapidly recovered and performed phagocytosis-mediated tumor clearance. Interestingly, anti-VEGF treatment combined with chemotherapy inhibited both Res and Mod-TAM reconstitution without affecting monocyte infiltration and improved its efficacy. Our results reveal that the developmental origin of TAMs dictates their relative distribution, function, and response to cancer therapies in lung tumors.
Moderate developmental alcohol exposure reduces repetitive alternation in a zebrafish model of fetal alcohol spectrum disorders

The damaging effects of alcohol on a developing fetus are well known and cause a range of conditions known as fetal alcohol spectrum disorder (FASD). High levels of alcohol exposure lead to physical deformity and severe cognitive deficits, but more moderate exposure leads to a range of subtle cognitive effects such as reduced social behavior, higher propensity to develop addictions, and reduced spatial working memory. Previous studies have demonstrated that following exposure to relatively low levels of ethanol during early brain development (equivalent in humans to moderate exposure) zebrafish display a range of social and behavioral differences. Here, our aim was to test the hypothesis that moderate developmental ethanol exposure would affect aspects of learning and memory in zebrafish. In order to do this, we exposed zebrafish embryos to 20mM [0.12% v/v] ethanol from 2 to 9 dpf to model the effects of moderate prenatal ethanol (MPE) exposure. At 3 months old, adult fish were tested for appetitive and aversive learning, and for spatial alternation in a novel unconditioned y-maze protocol. We found that MPE did not affect appetitive or aversive learning, but exposed-fish showed a robust reduction in repetitive alternations in the y-maze when compared to age matched controls. This study confirms that moderate levels of ethanol exposure to developing embryos have subtle effects on spatial working memory in adulthood. Our data thus suggest that zebrafish may be a promising model system for studying the effects of alcohol on learning and decision-making, but also for developing treatments and interventions to reduce the negative effects of prenatal alcohol.
The Feeding Infants and Toddlers Study (FITS) 2016: Moving Forward

The years from birth through preschool involve more changes in growth, development, eating patterns, nutrition, and other functions than any other time of life (1). Food consumption during this time is dynamic and is influenced by rapidly changing trends in feeding practices for infants and young children, as well as by longer-term trends in family incomes and food programs. It is critical to know what children are being fed, what they are eating, and how practices are changing, if we are to craft interventions that lay a solid nutritional foundation for later health, decrease risks of inappropriate eating habits, and develop evidence-based feeding recommendations. Informal guidelines for feeding the young have been available since antiquity. Today, we use formal evaluation of the evidence before making recommendations (2–5). Of particular relevance here is the Birth to 24 Months (B-24) project to evaluate data and support the addition of the first ever recommendations for children younger than 24 mo to the 2020–2025 Dietary Guidelines for Americans (6). Sound recommendations must be based on up-to-date information, and yet data on intakes and eating patterns are sparse, particularly for those <24 mo of age. NHANES provides much useful information for children <24 mo of age, but the sample sizes of both breast- and bottle-fed infants and toddlers are insufficient to trace the rapid changes in intakes that occur during that time (7, 8). The Feeding Infants and Toddlers Study (FITS) 2016 contributes to this evidence base and complements NHANES by applying similar methods to a large sample of infants and toddlers aged <24 mo, including minorities, providing greater detail about the adequacy of usual nutrient intakes and the foods and food groups consumed. FITS 2016 is a cross-sectional study of caregivers of children under the age of 4 y living in the 50 states and Washington DC. Data collection occurred between June 2015 and May 2016. A recruitment interview (respondent and child characteristics, feeding practices including responsive feeding and reasons for starting or stopping breastfeeding, physical activity, screen use, sleep habits, participation in food assistance programs) was completed by telephone or online. This was followed by a feeding practices questionnaire and a 24-h recall conducted by telephone. A second 24-h recall was collected for a random subsample of 25% of the total sampled population. Because FITS is a telephone survey, direct anthropometric data could not be collected; the lack of accurate anthropometric data or other biomarkers to link the food consumption data collected to health outcomes is a limitation (9).
Computerised cognitive behavioural therapy: helping Ireland log on

Objectives The aim of this article is to review and highlight evidence-based computerised cognitive behavioural therapy (cCBT) programmes that can potentially be used in Ireland for the treatment of mild-to-moderate mental health difficulties. Methods The authors undertook a literature search using three databases, and consulted a recognised, university-developed web portal. For a programme to be included in this review, it had to (a) have at least one randomised controlled trial demonstrating its efficacy; (b) be available on the internet; and (c) be delivered in English. Findings Twenty-five cCBT programmes that met the inclusion criteria were profiled. Taken together, these programmes target various anxiety difficulties (i.e. generalised anxiety, panic/phobia, social anxiety and post-traumatic stress), depression (or low mood), eating problems, stress, insomnia, pain and alcohol misuse. Conclusions cCBT programmes, preferably administered as part of a stepped-care model, offer effective, low-cost and low-intensity interventions for a wide range of psychological problems. Their use could be beneficial given how underdeveloped primary care mental health services are in Ireland.
Factors Affecting Enjoyment of Virtual Reality Games: A Comparison Involving Consumer-Grade Virtual Reality Technology.

OBJECTIVE This study investigated psychological responses to playing videogames using a virtual reality (VR) head-mounted display (HMD). We also investigated how cybersickness impacts the sense of presence one feels in the virtual environment, as well as how cybersickness affects enjoyment. MATERIALS AND METHODS Participants played randomly assigned VR games that varied in the level of sensory conflict they provided: "Lucky's Tale," "Elite: Dangerous," and "Minecraft. " Results were compared based on two headset conditions-the Oculus DK2 and the recently released Oculus Rift Consumer Version (CV1). RESULTS Cybersickness was not reduced by playing games with a VR HMD of higher technological quality-the Oculus Rift CV1. Furthermore, cybersickness responses were significantly different based on the level of sensory conflict in the games. Games with less sensory conflict, such as third-person platformer games, or space and flight simulator games, produce less cybersickness in players than first-person games. Enjoyment of VR games was shown to be directly influenced by a sense of spatial presence, which was affected by interactivity and realism. Findings suggest that the variables that are important to the enjoyment of console, mobile, or motion-based games are consistently important to enjoyment of VR games. CONCLUSION Better technology does not affect the frequency or severity of cybersickness for players; but sensory conflict has a significant impact on how sick users become. Additionally, we present a model that indicates how enjoyment is produced in VR gaming experiences. These findings bear further investigation as new methods of interacting with VR games are developed.
Does Physical Fitness Affect Academic Achievement among Japanese Adolescents? A Hybrid Approach for Decomposing Within-Person and Between-Persons Effects

Positive association between physical fitness and academic achievement in adolescents has been suggested yet the causal effect of physical fitness on academic achievement remains unclear. This study examined if longitudinal changes in physical fitness were associated with changes in academic achievement among junior high school students. Analyses were based on a two-year with three time-point data of 567 students (aged 12–13 years old at the baseline-point; 303 boys) who entered in five Japanese junior high schools in 2015. Academic achievement was evaluated using the student’s overall grade point average. Comprehensive physical fitness score was summed up from eight fitness tests: 50-m sprint, standing broad jump, repeated side-steps, sit and reach, sit-ups, hand-grip strength, handball throw, and 20-m shuttle run or endurance run. The hybrid regression model was applied to examine the impact of change in physical fitness on change in academic achievement using multiple imputation to account for non-response at follow-up. The changes in fitness score within-person and the differences in average of fitness score of three-time points between-person were associated with change in overall grade point average for boys. No significant association between fitness score and overall grade point average was observed in girls. Opportunities for increased physical fitness may be important to support academic achievement, particularly in junior high school boys.
The Importance of an Early and Accurate MEN1 Diagnosis

Multiple Endocrine Neoplasia type 1 (MEN1) is a rare autosomal dominant inherited condition, causing significant morbidity, and a reduction of life expectancy. A timely and accurate diagnosis of MEN1 is paramount to improve disease outcomes. This enables early identification of tumor manifestations allowing timely treatment for reducing morbidity and improving survival. Current management of MEN1 poses two challenges regarding the MEN1 diagnosis: diagnostic delay and the issue of phenocopies. A delay in diagnosis can be caused by a delay in identifying the index case, and by a delay in identifying affected family members of an index case. At present, lag time between diagnosis of MEN1 in index cases and genetic testing of family members was estimated to be 3.5 years. A subsequent delay in diagnosing affected family members was demonstrated to cause potential harm. Non-index cases have been found to develop clinically relevant tumor manifestations during the lag times. Centralized care, monitoring of patients outcomes on a national level and thereby improving awareness of physicians treating MEN1 patients, will contribute to improved care. The second challenge relates to “phenocopies. ” Phenocopies refers to the 5–25% of clinically diagnosed patients with MEN1in whom no mutation can be found. Up to now, the clinical diagnosis of MEN1 is defined as the simultaneous presence of at least two of the three characteristic tumors (pituitary, parathyroids, or pancreatic islets). These clinically diagnosed patients undergo intensive follow up. Recent insights, however, challenge the validity of this clinical criterion. The most common mutation-negative MEN1 phenotype is the combination of primary hyperparathyroidism and a pituitary adenoma. This phenotype might also be caused by mutations in the CDKN1B gene, causing the recently described MEN4 syndrome. Moreover, primary hyperparathyroidism and pituitary adenoma are relatively common in the general population. Limiting follow-up in patients with a sporadic co-occurrence of pHPT and PIT could reduce exposure to radiation from imaging, healthcare costs and anxiety.