Miracle-dz/UniFAR-FTUs huggingface dataset:
New algorithmic approaches for reinforcement learning , with application to integer programming

Reinforcement Learning (RL) is one of the most powerful paradigm of learning and sequential decision making with a broad range of applications, including autonomous vehicle control, robot navigation, personalized medical treatments, intelligent game playing and problem solving. Due to their generality, RL models for most real applications suffer from a prohibitively large state space. A widely employed technique called function approximation is to use a lowerdimensional feature representation of the states, and learn parametric approximations of the policies or the state-action value functions. Recently, great strides have been made in this area, with unprecedented success in game playing applications using deep learning methods for function approximation; most notably an RL agent with superhuman performance for Atari 2600 [Mnih et al., 2015, 2013], and the successes of AlphaGo in playing the game of Go [Silver et al., 2016]. This proposal identifies and addresses two critical challenges in obtaining such successes in other application areas: (a) Lack of a perfect simulator of system dynamics: An advantage enjoyed by computer game playing applications is that a perfect and inexpensive simulation of system dynamics is readily available for sample generation and training. This is in contrast to most real applications, especially those involving biological systems, unexplored terrains, and unpredictable environments, where building such a simulator itself requires extensive learning and modeling, and one needs to rely on samples from real world experiments. Consequently sample generation is expensive and time-consuming, and methods for reducing sample complexity are critical. (b) Complex action space: The action space in most gaming applications is well-defined, discrete, and often small (e.g., moving paddle left or right in Pong). On the other hand, in many applications like automatic control and navigation, one may be dealing with a continuous constrained action space, or actions which are implicitly composed of a sequence of actions (skills). Learning and optimization over such complex action spaces requires a synergistic design that combines learning with advanced constrained optimization and search techniques. Motivated by the above challenges, this proposal investigates novel reinforcement learning algorithm design approaches that can achieve scalable solutions for large and complex reinforcement learning problems by adapting a synergistic view of learning and optimization. In order to evaluate our methods, and provide concrete proof of concepts, we focus on a specific problem-solving application. The application in focus is to build a reinforcement learning agent that can learn to solve Integer Programs (IP).
Asking the right questions

Lynn Arthur Steen Department of Mathematics, Statistics, and Computer Science St. Olaf College steen@stolaf.edu Assessment is about asking and answering questions. For students, “how am I doing? ” is the focus of socalled “formative” assessment, while “what’s my grade? ” often seems to be the only goal of “summative” assessment. For faculty, “how’s it going? ” is the hallmark of within-course assessment using instruments such as tenminute quizzes or one-minute responses on 3×5 cards at the end of each class period. Departments, administrations, trustees, and legislators typically ask questions about more aggregated levels: they want to know not about individual students but about courses, programs, departments, and entire institutions. The conduct of an assessment depends importantly on who does the asking and who does the answering. Faculty are accustomed to setting the questions and assessing answers in a context where outcomes count for something. When assessments are set by someone other than faculty, skepticism and resistance often follow. And when tests are administered for purposes that don’t “count,” (for example, sampling to assess general education or to compare different programs), student effort declines and results lose credibility. The assessment industry devotes considerable effort to addressing a variety of similar contextual complications, such as: • different purposes (diagnostic, formative, summative, evaluative, self-assessment, ranking); • different audiences (students, teachers, parents, administrators, legislators, voters); • different units of analysis (individual, class, subject, department, college, university, state, nation); • different types of tests (multiple choice, open ended, comprehension, performance-based, timed or untimed, calculator permitted, individual or group, seen or unseen, external, written or oral); • different means of scoring (norm-referenced, criterion referenced, standards-based, curriculum-based); • different components (quizzes, exams, homework, journals, projects, presentations, class participation); • different standards of quality (consistency, validity, reliability, alignment); • different styles of research (hypothesis-driven, ethnographic, comparative, double-blind, epidemiological). Distinguishing among these variables provides psychometricians with several lifetimes’ agenda of study and research. All the while, these complexities cloud the relation of answers to questions and weaken inferences drawn from resulting analyses. These complications notwithstanding, questions are the foundation on which assessment rests. The assessment cycle begins with and returns to goals and objectives
Towards Smart Urban Planning through Knowledge Infrastructure

— In companies, the use of the so-called business intelligence and knowledge engineering is more and more commonly found. By essence, companies are using computer tools, which tends to include them in the knowledge society; from a mathematical point of view, knowledge representation is made through rules and logics. And then comes the question: what could be done in this direction for urban planning? The big challenge is to deal with urban and environmental features which are usually described, stored and manipulated via computational geometry and spatial analysis. But those disciplines cannot easily be combined with logics. The goal of this position paper is to show how knowledge engineering can be the foundation of a new type of urban planning, i.e . , urban planning based on knowledge. Geographic knowledge bunches are usually described through geographic objects, relations, structures, ontologies, gazetteers, rules and mathematical models. After having explained those bunches of knowledge, the structure of a geographic inference engine is sketched so to renovate urban planning. Then beyond Spatial Data Infrastructure, we explain that some geographic knowledge infrastructure could be the basis of a new generation of tools for urban planning.
Study of Insulin Secretory Response after Oral Glucose Load in Obese Subjects

Obesity is a medical condition in which excess body fat has accumulated to the extent that it may have an adverse effect on health, leading to reduced life expectancy or increased health problem [1, 2]. Overweight and obesity are the fifth leading risk for global health. At least 2.8 million adults die each year as a result of overweight or obese. In addition, 44% of the diabetes, 23% of ischaemic heart disease and between 7% and 41% certain cancer are attributable to overweight and Obese [3]. Obesity is associated with other well proved risk factors such as diabetes, hypertension, dyslipidemia, high blood cholesterol, and physical inactivity [4]. The combination of insulin resistance and hyperinsulinaemia cause a number of metabolic and cardiovascular changes that result in a syndrome typically characterized by type 2 DM, obesity, dyslipidemia, coronary artery disease and hypertension [5]. Thus in present study an attempt has been made to examine the insulin secretory response to oral glucose load to test whether obesity is associated with insulin resistance. Materials and Methods
DEVELOPMENT OF NEUTRON TOMOGRAPHY AND ITS APPLICATIONS IN NONDESTRUCTIVE ANALYSIS

Neutron tomography is a very powerful technique for nondestructive evaluation of heavy industrial components as well as for soft hydrogenous materials enclosed in heavy metals which are usually difficult to image using X-rays. It has found a variety of applications in aerospace engineering, nuclear industry, medicine, agriculture and other heavy industries. In our effort to use this technique for non-destructive testing, an experimental station for neutron tomography has been designed and developed at Beam-hole E12 of CIRUS reactor. It consists of a specially designed neutron beam collimator, shielding hutch, neutron sensitive imaging camera, sample manipulator system and control system. Several experiments have been carried out on this experimental station to study the feasibility of neutron tomography for various applications. Nondestructive detection and evaluation of location, shape and size of hydride blisters formed in pressure tube of PHWR reactor has been carried out along with quantitative determination of hydride concentration in it. Similarly the pellets as well as welded area of end-cap of PHWR fuel pin were imaged which shows imperfections in welded in the end cap and presence of defects in the pellets. Other samples which were analyzed using this facility are (a) turbine blade which is used in heat exchanger turbine systems (b) crack in SS Bar caused due to excessive tensile load applied on it, and (c) internal structures as well as distribution of chocked oil in the fuel injector of automobile engine.
Effect of brief corticosterone administration on SGK1 and RGS4 mRNA expression in rat hippocampus

Acute stress and corticosterone enhance 5-HT1A receptor-mediated responses in rat hippocampal CA1 cells within 1–2 h, through a process involving transcriptional regulation of unknown genes. Earlier studies showed that regulation of the 5-HT1A receptor gene cannot explain the functional effects. We here tested the hypothesis that corticosterone targets genes encoding RGS4 or SGK1, which can both affect the 5-HT1A receptor associated Kir channel, thus affecting 5-HT1A receptor function. To this end, the effect of a single corticosterone injection on hippocampal expression of RGS4 and SGK1 mRNAs, measured by in situ hybridization, was studied. Expression of RGS4 or SGK1 mRNA was not affected by the corticosterone injection, neither in the CA1 area nor in other hippocampal subregions. Strikingly, SGK1 mRNA expression was strongly up-regulated in the corpus callosum. We reject, however, the hypothesis that the effect of corticosterone on 5-HT1A responsiveness is mediated via altered RGS4 or SGK1 mRNA expression.
Identification of promoter regions in genomic sequences by 1-dimensional constraint clustering

Size constrained clustering has been recently proposed to embed "a priori" knowledge in clustering methods. By exploiting the "string property" we propose an exact and efficient algorithm based on dynamic programming techniques to solve size-constrained one-dimensional clustering problems. We show the applicability of the proposed method in a difficult computational biology problem: the prediction of the transcription start sites of genes. The obtained experimental results clearly show the potential of the proposed approach when compared with previously published methods.
Money in a DSGE framework with an application to the Euro Zone

In the current New Keynesian literature, the role of monetary aggregates is generally neglected. Yet it's hard to imagine money completely “passive” to the rest of the system. By entering real money balances in a non-separable utility function, we introduce an explicit role for money via preference redefinition in a simple New Keynesian Dynamic Stochastic General Equilibrium (DSGE) model. It involves new inflation and output gap specifications where money plays a significant role. We use the General Method of Moments (GMM) to calibrate our DSGE model of the Euro area and we show that the European Central Bank –ECB) should react more strongly to economic shocks as far as the role of money is found significant.
The effect of temperature on soldering and the sequence of formation of the soldered layer during high pressure die casting of Al-11Si-3Cu alloy

Soldering is an important cause of die failure in high pressure die casting (HPDC), but mechanisms of the formation of the soldered layer are not clear. In this study, HPDC soldering experiments with Al-11Si-3Cu alloy have been conducted using core pins as soldering targets. Due to heat loss in the process, soldering reactions in the die cavity occurred at temperatures equal to or below the liquidus temperature of the cast alloy. Local solidification time was found to be the determining factor for the severity of soldering. Hence, in thicker sections of the casting, the pin was in contact with the solidifying alloy longer than in thinner sections and therefore required less cycles to solder. Soldering started with the formation of intermetallic outbursts accompanied by build-up of solidified cast alloy. A soldered layer developed by the growth of soldering intermetallics via a solid state reaction, together with coarsening of the phases in the cast alloy layer adjacent to the soldering intermetallics. The.
Optical coherence tomography longitudinal evaluation of retinal nerve fiber layer thickness in glaucoma.

OBJECTIVES To longitudinally evaluate optical coherence tomography (OCT) peripapillary retinal nerve fiber layer thickness measurements and to compare these measurements across time with clinical status and automated perimetry. METHODS Retrospective evaluation of 64 eyes (37 patients) of glaucoma suspects or patients with glaucoma participating in a prospective longitudinal study. All participants underwent comprehensive clinical assessment, visual field (VF) testing, and OCT every 6 months. Field progression was defined as a reproducible decline of at least 2 dB in VF mean deviation from baseline. Progression of OCT was defined as reproducible mean retinal nerve fiber layer thinning of at least 20 mum. RESULTS Each patient had a median of 5 usable OCT scans at median follow-up of 4.7 years. The difference in the linear regression slopes of retinal nerve fiber layer thickness between glaucoma suspects and patients with glaucoma was nonsignificant for all variables; however, Kaplan-Meier survival curve analysis demonstrated a higher progression rate by OCT vs VF. Sixty-six percent of eyes were stable throughout follow-up, whereas 22% progressed by OCT alone, 9% by VF mean deviation alone, and 3% by VF and OCT. CONCLUSIONS A greater likelihood of glaucomatous progression was identified by OCT vs automated perimetry. This might reflect OCT hypersensitivity or true damage identified by OCT before detection by conventional methods.
The influence of stress

Abstract The first stage of fatigue is an important problem because its width is very short but its life is 80 % of the whole life. And it is well known that initial crack growth is very fast under the conditions of existing compressive stress. The reason is that a crack opening arises from the remaining tensile stress. Therefore, in this study the effect of compressive stress was investigated. As a result, it was found that the acceleration of initial crack growth is proportional to compressive stress, and striations were found in the initial crack.
Organisational effectiveness of Australian fast growing small to medium-sized enterprises (SMEs)

Purpose – Small to medium‐sized enterprises (SMEs) continue to make a major contribution to the Australian economy. However, research into organisational processes within SMEs has been limited to date. This study aims to examine the links between communication processes and organisational effectiveness in SMEs.Design/methodology/approach – This quantitative study uses social capital theory as a framework to investigate whether employees' level of satisfaction with organisational communication processes affects organisational outcomes within three high growth manufacturing SMEs in one area of Australia.Findings – Results indicate that organisational communication processes does affect employees' levels of ambiguity regarding customers, job satisfaction and commitment to their firms.Research limitations/implications – While generalisability is limited because of the small number of SMEs participating in the study, the research indicates great potential for developing theoretical and practical insights into .
Impact of medical and demographic factors on long-term quality of life and body image of breast cancer patients.

BACKGROUND The impact of various medical and demographic factors on the quality of life (QoL) of breast cancer patients has been discussed controversially. We investigated the influence of six different factors on long-term QoL and body image of women with primary breast cancer. PATIENTS AND METHODS Two-hundred and seventy-four breast cancer patients were administered the QoL questionnaire following a mean interval of 4.2 years after primary diagnosis. All women had been primarily treated for stage I to III breast cancer without evidence of distant metastases. QoL was evaluated by using the QLQ-C30 questionnaire Version 2.0. Supplementary scales included body image, satisfaction with surgical treatment, cosmetic result and fear of recurrence. We analyzed the impact of tumor stage, surgical treatment, adjuvant radiotherapy, adjuvant cytotoxic therapy, age and length of follow-up period on the examined outcome parameters. RESULTS At the time of the follow-up examination, patients showed minor impairment of QoL (mean 67.8) and body image (mean 24.8), but more fear of recurrence (mean 60.7). None of the studied factors had a significant impact on overall QoL (P >0.05) according to the QLQ-C30 questionnaire. In contrast, with the exception of the factors 'cytotoxic therapy' and 'radiotherapy' all investigated variables influenced at least one of the additional psychological scales (P <0.05). The primary surgical treatment modality had the strongest impact and affected all four scales. Patients treated with breast conservation reported a more favorable body image, compared to those treated with mastectomy (17.2 versus 37.5, P <0.01), more satisfaction with surgical treatment (4.0 versus 10.7, P = 0.01), rated a better cosmetic result (75.5 versus 57.1, P <0.01), but presented more fear of recurrence (63.9 versus 55.3, P = 0.04). CONCLUSION Current QoL questionnaires do not sufficiently cover all relevant aspects of QoL, but might be complemented by breast cancer specific aspects such as body image and fear.
Autophagy in Thyroid Cancer: Present Knowledge and Future Perspectives

Thyroid cancer is the most common endocrine malignancy. Despite having a good prognosis in the majority of cases, when the tumor is dedifferentiated it does no longer respond to conventional treatment with radioactive iodine, the prognosis worsens significantly. Treatment options for advanced, dedifferentiated disease are limited and do not cure the disease. Autophagy, a process of self-digestion in which damaged molecules or organelles are degraded and recycled, has emerged as an important player in the pathogenesis of different diseases, including cancer. The role of autophagy in thyroid cancer pathogenesis is not yet elucidated. However, the available data indicate that autophagy is involved in several steps of thyroid tumor initiation and progression as well as in therapy resistance and therefore could be exploited for therapeutic applications. The present review summarizes the most recent data on the role of autophagy in the pathogenesis of thyroid cancer and we will provide a perspective on how this process can be targeted for potential therapeutic approaches and could be further explored in the context of multimodality treatment in cancer and personalized medicine.
Learning From Real-Life Experiences : A Data-Driven Emotion Contagion Approach Towards More Realistic Virtual

We propose a data-driven approach for measuring, validating and optimizing crowd simulation systems by learning parameters from real-life videos. We discuss the common traits of incidents and their video footage suitable for the learning step. We then demonstrate the learning process in a real-life incident that happened in 2015, Ankara, Turkey. We reanimate the incident with an existing emotion contagion and crowd simulation framework and optimize the parameters that take role in defining agent behavior with respect to the data extracted from the video footage of the incident.
Internet-Based Recruitment to a Depression Prevention Intervention: Lessons From the Mood Memos Study

Background Recruiting participants to randomized controlled trials of health interventions can be very difficult. Internet-based recruitment is becoming an increasingly important mode of recruitment, yet there are few detailed accounts of experiences recruiting participants to mental health interventions. Objective To report on our experience with Internet-based recruitment to an online depression prevention intervention and pass on lessons we learned. Methods Participants were recruited to the Mood Memos study, an online preventive depression intervention, purely through Internet-based sources. The study was targeted to adults with subthreshold depression symptoms from several English-speaking countries. A variety of online recruitment sources were trialed, including search engine advertising (Google, Yahoo! , Bing), Facebook advertising, posts in forums and online noticeboards, and promotion through relevant websites and email newsletters of mental health organizations. Results The study website received visits from 94,808 individuals over the 14-month recruitment period. The recruitment target was reached with 1699 individuals signing up to the randomized controlled trial and 1326 fully enrolling. Most visitors arrived via Google advertising, which promoted a depression-screening questionnaire. Google advertising accounted for nearly half of the total participants who signed up to the study, at an average cost of AUD $12 per participant. Promoting the study through trustworthy organizations and websites known to participants was also effective. Recruitment techniques that were less effective were contacting forums, email groups, and community noticeboards. Conclusions Several techniques, including Google advertising, were successful in recruiting participants to a trial evaluating an online depression intervention. Results suggest that Internet-based recruitment to mental health interventions is feasible and can be relatively affordable. Trial Registration ACTRN12609000925246