Miracle-dz/UniFAR-FTUs huggingface dataset:
Safe Policy Learning for Continuous Control

: We study continuous action reinforcement learning problems in which it is crucial that the agent interacts with the environment only through near-safe policies, i.e., policies that keep the agent in desirable situations, both during training and at convergence. We formulate these problems as constrained Markov decision processes (CMDPs) and present safe policy optimization algorithms that are based on a Lyapunov approach to solve them. Our algorithms can use any standard policy gradient (PG) method, such as deep deterministic policy gradient (DDPG) or proximal policy optimization (PPO), to train a neural network policy, while enforcing near-constraint satisfaction for every policy update by projecting either the policy parameter or the selected action onto the set of feasible solutions induced by the state-dependent linearized Lyapunov constraints. Compared to the existing constrained PG algorithms, ours are more data efﬁcient as they are able to utilize both on-policy and off-policy data. Moreover, in practice our action-projection algorithm often leads to less conservative policy updates and allows for natural integration into an end-to-end PG training pipeline. We evaluate our algorithms and compare them with the state-of-the-art baselines on several simulated (MuJoCo) tasks, as well as a real-world robot obstacle-avoidance problem, demonstrating their effectiveness in terms of balancing performance and constraint satisfaction.
Improving indoor localization accuracy through information fusion

• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website. • The final author version and the galley proof are versions of the publication after peer review. • The final published version features the final layout of the paper including the volume, issue and page numbers.
Symptomatic treatment after ACS Anti-anginal therapy in patients after acute coronary syndrome: evaluation of newer agents

Coronary heart disease (CAD) is the leading cause of death worldwide. Many patients who survive an acute myocardial infarction will experience recurrent angina which significantly impairs quality of life and in severe cases is associated with increased mortality. Angina occurs when there is a mismatch between coronary supply and demand. Traditional agents including β-blockers, calciumchannel blockers and nitrates exert their effect by reducing the hemodynamic components of myocardial oxygen demand such as heart rate, blood pressure and preload. After several decades without new therapies in our pharmacologic armamentarium, several promising new agents have undergone clinical evaluation with promising results. Some of these novel agents exert their antianginal effects through reduction in traditional hemodynamic parameters but others target novel steps in the ischemic pathway. This review examines the pharmacologic management of angina in patients after acute coronary syndrome (ACS) with a focus on novel agents.
Public Sector Organizational Culture: Experience from Frontline Bureaucracies

This chapter discusses the practice of organizational culture by the frontline bureaucrats in Bangladesh. Culture scholars argue that organizational culture—commonly defined as the beliefs, values, attitudes, and practices of the members of an organization—is a powerful force in determining the health and well-being of an organization. Scholars also suggest the existence of different dimensions of organizational culture. Although they do not agree in naming these dimensions, commonalities are found in their understanding. How organizational culture is practiced by the frontline bureaucrats in Bangladesh has not been studied much. A study was designed to know how the frontline public bureaucrats practice organizational culture and how they differ in their practices along their service lines. Four dimensions of organizational culture—power distance, uncertainty avoidance tendency, participation, and team orientation—were considered. The chosen culture dimensions impact the overall management of any public sector organization. Three hundred and twenty-six frontline public bureaucrats were studied using a survey questionnaire. Both descriptive and inferential statistics have been used for analyzing the collected data. Findings from independent samples t-tests revealed that the frontline bureaucrats significantly differ along their service lines in practicing the culture dimensions.
Gender in Executive Ireland: An Exploratory Study into the Impact of Gender on Career Progression

Purpose: This research study aims to explore the challenges facing women in attaining senior leadership positions in large Irish organisations by obtaining the experiences of both male and females who currently occupy executive level position. The objective of this qualitative based study is to investigate the individual experiences of men and women who currently hold the title of Chief Executive Officer (CEO). It seeks to determine if the challenges and barriers for female career progression demonstrated in the literature, are represented in the modern work place in Ireland. Approach / Design / Methodology: A qualitative study, applying semi-structured interviews, with a sample of five Chief Executive Officers from Irish organisations was undertaken to gather in depth insight into the male and female experience of gender and leadership. Interviews were conducted confidentially and were recorded, transcribed, reviewed and assessed. It is not intended for generalisations to be extrapolated from the research as the true value of the study is found in the detailed qualitative insight offered by the participants’ professional experiences. Findings: Men continue to hold a distinct advantage in both the opportunity for, and achievement of, executive level positions in large Irish organisations. The small sample in the study, representative of Irish businesses, confirmed that men continue to occupy much of the senior leadership positions. These findings inform us that gender has a significant impact on career progression and concurs with the literature on the topic. Originality / Value: This study enhances the knowledge and research in gender and leadership and the experiences of Chief Executive Officers in Ireland. When undertaking research under the topic of women in leadership, there was no evidence of a previous, peerreviewed qualitative study, specific to the senior executive leadership experience of Irish women. This research may help to close the gap in this knowledge taxonomy.
ANALISIS PEMAHAMAN KONSEP GELOMBANG MEKANIK MELALUI APLIKASI ONLINE QUIZIZZ

Gelombang mekanik merupakan salah satu materi penting yang dipelajari dalam fisika.Materi gelombang mekanikdipelajari dalam beberapa submateri sehingga menyebabkan pengukuran tingkat pemahaman konsep mahasiswa menjadi sulit. Aplikasi online Quizizz merupakan salah satu alternatif media yang dapat digunakan untuk mengetahui pemahaman konsep mahasiswa secara interaktif dan fleksibel.Penelitian ini dilakukan pada 29 mahasiswa jurusan fisika dengan menggunakan 15 soal konseptual yang diklasifikasikan ke dalam tiga materi yaitu, gelombang bunyi, gelombang mekanik pada air, dan gelombang mekanik pada tali. Pengambilan data pemahaman kosep gelombang mekanik dilakukan melalui kuis yang disajikan pada Quizizz. Hasil analisis menunjukkan bahwa secara keseluruhan pemahaman konsep mahasiswa fisika terhadap gelombang mekanik adalah 51%. Hal ini menunjukkan bahwa tingkat pemahaman konsep yang dimiliki mahasiswa fisika berada pada kategori sedang.
Multi-Task Allocation Under Time Constraints in Mobile Crowdsensing

Mobile crowdsensing (MCS) is a popular paradigm to collect sensed data for numerous sensing applications. With the increment of tasks and workers in MCS, it has become indispensable to design efficient task allocation schemes to achieve high performance for MCS applications. Many existing works on task allocation focus on single-task allocation, which is inefficient in many MCS scenarios where workers are able to undertake multiple tasks. On the other hand, many tasks are time-limited, while the available time of workers is also limited. Therefore, time validity is essential for both tasks and workers. To accommodate these challenges, this paper proposes a multi-task allocation problem with time constraints, which investigates the impact of time constraints to multi-task allocation and aims to maximize the utility of the MCS platform. We first prove that this problem is NP-complete. Then two evolutionary algorithms are designed to solve this problem. Finally, we conduct the experiments based on synthetic and real-world datasets under different experiment settings. The results verify that the proposed algorithms achieve more competitive and stable performance compared with baseline algorithms.
DIFFERENT CLINICAL PRESENTATIONS OF RECURRENT EPISODE OF MAJOR DEPRESSIVE DISORDER WITH OR WITHOUT POSTTRAUMATIC STRESS DISORDER

The aim of this study was comparison of the severity of the recurrent episode in the group of subjects suffering from Major Depressive Disorder with comorbid Posttraumatic Stress Disorder and the group of subjects suffering only from Major Depressive Disorder. A total of 120 subjects were assessed and divided into two groups. Group D/PTSD consisted of subjects who fulfilled diagnostic criteria for recurrent episode of Major Depressive Disorder and comorbid Posttraumatic Stress Disorder. Group D/only consisted of subjects who fulfilled diagnostic criteria for Recurrent episode of Major Depressive Disorder. Assessments were performed using the following instruments: Montgomery-Asberg Depression Rating Scale, Hamilton Depression Rating Scale and Quick Inventory for Depressive Symptomatology Self -Report Version. Statistical analyses were performed using chi square and independent-samples t-test. Results suggest that recurrent episode of Major Depressive Disorder occurring in comorbidity with Posttraumatic stress disorder is more severe than the recurrent episode in the category of patients suffering from recurrent episode of Major Depressive Disorder only and that recurrent episode occurring in comorbidity with Posttraumatic stress disorder might represent a significant clinical entity. Acta Medica Medianae 2019;58(3):67-71.
Understanding of boundary conditions imposed at multiple outlets in computational haemodynamic analysis of cerebral aneurysm

Computational fluid dynamics (CFD) is considered to be a promising tool for haemodynamic analysis of the intracranial aneurysm. However, aneurysm CFD is still not regarded as fully reliable mainly because the computational result is influenced by too many factors such as the luminal geometry of the model, spatiotemporal resolutions and boundary conditions. Among the influential factors, this paper focuses on outflow boundary conditions used when the computational domain has multiple outlets. Four outflow strategies found in published articles are reviewed: 1) pre-scription of constant or zero pressure, 2) flow splitting based on the power law, 3) traction-free and zero velocity-gradient conditions and 4) coupling of CFD with a reduced-order model. None of them has proved definitely superior or inferior to others. For accurate quantification of the haemodynamic state in the aneurysm, it is crucial to incorporate the physiologically correct flow splitting ratio in CFD analysis by means of accurate specification of pressure or flow rate at the outlets. A coupling of CFD and a 0-d model (a subtype of the reduced-order model) appears to be the most promising although further study is necessary to achieve accurate estimation of model parameters.
EXPLORING THE IMPACT OF KNOWLEDGE AND SOCIAL ENVIRONMENT ON INFLUENZA PREVENTION AND TRANSMISSION IN MIDWESTERN UNITED STATES HIGH SCHOOL STUDENTS

We used data from a convenience sample of 410 Midwestern United States students from six secondary schools to develop parsimonious models for explaining and predicting precautions and illness related to influenza. Scores for knowledge and perceptions were obtained using two-parameter Item Response Theory (IRT) models. Relationships between outcome variables and predictors were verified using Pearson and Spearman correlations, and nested (student within school) fixed effects multinomial logistic regression models were specified from these using Akaike's Information Criterion (AIC). Neural network models were then formulated as classifiers using 10-fold cross validation to predict precautions and illness. Perceived barriers against taking precautions lowered compliance with the CDC recommended preventative practices of vaccination, hand washing quality, and respiratory etiquette. Perceived complications from influenza illness improved social distancing. Knowledge of the influenza illness was a significant predictor for hand washing frequency and respiratory etiquette. Ethnicity and gender had varying effects on precautions and illness severity, as did school-level effects: enrollment size, proficiency on the state's biology end-of-course examination, and use of free or reduced lunch. Neural networks were able to predict illness, hand hygiene, and respiratory etiquette with moderate success. Models presented may prove useful for future development of strategies aimed at mitigation of influenza in high school youths. As more data becomes available, health professionals and educators will have the opportunity to test and refine these models.
Possible implications of weather variation on reproductive phenology of European common toad in southeastern Europe

We tracked yearly variation in breeding phenology in relation to weather parameters in a common European toad population from the southeastern part of its range. Phenological data were collected from 2001 to 2003 and from 2011 to 2017 and compared to open-access daily weather data from a nearby weather station. Data analysis revealed no significant effect of weather on initiation of breeding and a negative relationship between mean daily humidity and mean cloud cover on the duration of breeding season (P = 0.03). Further analysis showed a decreasing trend in breeding season humidity in the past 70 years. Our results predict a tendency toward longer toad breeding seasons in years with drier winter/spring. A projected decrease in humidity in this region could prolong toad breeding season, potentially exposing adults to higher predation. Therefore, the scenario of further decline in our study population should be considered and conservation measures planned accordingly.
Perturbational and nonperturbational inversion of Love-wave velocities

We describe a set of MATLAB codes to forward model and invert Love-wave phase or group velocities. The forward modeling is based on a finite-element method in the frequencywavenumber domain, and we obtain the different modes with an eigenvector-eigenvalue solver. We examine the issue of parasitic modes that arises for modeling Love waves, in contrast to the Rayleigh wave case, and how to discern parasitic from physical modes. Once the matrix eigenvector-eigenvalue problem has been solved for Love waves, we show a straightforward technique to obtain sensitivity kernels for S-wave velocity and density. In practice, the sensitivity of Love waves to density is relatively small and inversions only aim to estimate the S-wave velocity. Two types of inversion accompany the forward-modeling codes: One is a perturbational scheme for updating an initial model, and the other is a nonperturbational method that is well-suited for defining a good initial model. The codes are able to implement an optimal nonuniform layering designed for Love waves, invert combinations of phase and group velocity measurements of any mode, and seamlessly handle the transition from guided to leaky modes below the cutoff frequency. Two software examples demonstrate use of the codes at near-surface and crustal scales.
Object-Independent Grasping in Heavy Clutter

When grasping objects in a cluttered environment, a key challenge is to find appropriate poses to grasp effectively. Accordingly, several grasping algorithms based on artificial neural networks have been developed recently. However, these methods require large amounts of data for learning and high computational costs. Therefore, we propose a depth difference image-based bin-picking (DBP) algorithm that does not use a neural network. DBP predicts the grasp pose from the object and its surroundings, which are obtained through depth filtering and clustering. The object region is estimated by the density-based spatial clustering of applications with noise (DBSCAN) algorithm, and a depth difference image (DDI) that represents the depth difference between adjacent areas is defined. To validate the performance of the DBP scheme, bin-picking experiments were conducted on 45 different objects, along with bin-picking experiments in heavy clutters. DBP exhibited success rates of 78.6% and 83.3%, respectively. In addition, DBP required a computational time of approximately 1.4 s for each attempt.
A methodology for quantifying flow patterns in a water-table apparatus for naturally ventilated buildings

Wind-driven ventilation in buildings is an effective way of diluting the indoor air for maintaining thermal comfort and acceptable indoor air quality. Visualization of the wind-induced flow patterns in a building using a water-table apparatus is a relatively convenient method that produces instantaneous results. The present study focused on the quantification of the flow patterns generated in and around buildings using water-table experiments. The flow patterns were analyzed photographically to derive different ventilation metrics, such as dead spots, ventilation efficiency, etc., which would reveal quantitative information regarding the flow in the different zones of the building. Experiments were conducted using different configurations in order to verify the results obtained with the photographic method. The method used in the present study could be useful in the prediction of flow patterns for complex geometries, which would assist in undertaking early decisions for the proper orientation of a building and its openings. Abbreviations: ACH: Air Changes per Hour (h−1); AS: Room with windows on adjacent walls configuration; AVE: Absolute Ventilation Efficiency; BHK: Bedroom, Hall, Kitchen; C: dye concentration at a point after t, s (g/l); CFD: Computational Fluid Dynamics; Ci: average inside concentration(g/l); Cmax: maximum dye concentration at a point (g/l); Co: initial concentration at a point (g/l); Cs: concentration in the outdoor supply air (g/l); d: characteristic length (mm or m); D: Dining room; dC: change in concentration (g/l); DS: Dead Spots; Ea: Absolute Ventilation Efficiency; fps: Frames per seconds; IAQ: Indoor Air Quality; k reactivity rate (h−1); K: Kitchen; L: Living Room; MATLAB: Matrix Laboratory; OS: Room with windows on opposite walls configuration; P: Dimensionless penetration factor; P1: Passage 1; P2: Passage 2; P3: Passage 3; Pix: Pixel value (px); PNG Portable network graphics; R1: Room 1; R2: Room 2; R3: Room 3; Re: Reynolds Number; RGB: Red, Green, Blue; S: indoor source emission rate (μg/h); SS: Room with single-sided window configuration; T1: Toilet 1; T2: Toilet 2; T3: Toilet 3; U: Utility room; V: Room volume, m3; v: velocity (m/s); VLC: VideoLAN Client
Is Comprehensive Income Superior To Net Income In Equity Valuation? Evidence From The Capital Market Of Kuwait

The study examines whether comprehensive income numbers reported under International Financial Reporting Standards (IFRS) have value relevance over net income in equity valuation. We use a sample of firms that are listed in Kuwait Stock Exchange from banking, investment, real estate, industrial, basic materials, telecommunications, consumer services, oil & gas and health care sectors during the years 2012-2015.The study applies a methodology used by Collins, Maydew and Weiss (1997) that is based on Ohlson (1995) equity valuation model and Theil (1971) technique to measure and compare the relative and the incremental explanatory power of comprehensive income and net income. The study provides evidence that comprehensive income is not superior to net income in equity valuation. Reporting other comprehensive income gains and losses as elements of the income statement produces a measure of earnings that decreases the explanatory power of the valuation model; decreases the incremental information content of earnings. Other comprehensive income gains and losses when added as an explanatory variable to the valuation model did not enhance significantly its explanatory power.The results we obtained supports the current requirement by the IFRS and US GAAP of deferring other comprehensive gains and losses and contributes to the literature on the value relevance of other comprehensive income gains and losses in emerging capital markets.
Environmental impact of toxic metals on water and soil by agrochemicals, emerging pollutants and remediation methods

This review article has aimed at environment and impact of different pollutants, define, classify, analyze and cite methods of remediation according to Brazilian environmental legislation. Concerns about the preservation of the environment is extensively debated nowadays, with a view mainly to the production of effluents in agriculture, toxic metals, emerging pollutants and excessive use of agrochemicals. However, some impacts are necessary to meet the needs of economic development and social to ensure they are carried out rationally. Furthermore, application of remediation methods reduce the impact of these pollutants as small as possible. In this sense, the environment's definition, the main current impacts, the size and consequences of these and some remediation methods, as well as Brazilian environmental legislation will be addressed.
A frequentist’s resolution of the exchange paradox

Abstract In this paper, we provide a frequentist’s resolution of the exchange paradox. We propose a probability space with which we can explain both the Bayesian and likelihood-based resolutions. Under the proposed probability space, we find the optimal conditional strategy for the game to maximize the expected gain in money, which equals to that in Bayesian resolution. The probability space also allows us to understand that the paradox is from the additional symmetry assumption which is mistakenly taken. We show that the assumption is not feasible, at least in frequentist view, in the sense that no distribution of the money (inside the envelope) exists to satisfy the assumption. This understanding to the paradox is equivalent to the likelihood-based solution by Pawitan (2001) that the failure of our reasoning arises from treating the above likelihood function as the probability function and taking expectation over the likelihood function.