Miracle-dz/UniFAR-FTUs huggingface dataset:
Microservice-Based System for Environmental Science Software Applications

—When an environmental research project grows, technical concerns over system scalability, data exposure, and third-party application support are overlooked. This paper presents a system, the Microservice-based Envirosensing Support Applications (MESA), that provides a scalable environment and data infrastructure solutions for the NSF-funded Solar Energy-Water-Environment Nexus project. MESA can be broken into 4 major parts: a suite of microservices exposed over an API, an overarching service discovery, a series of tables replicated from an existing monolith, and the applications that MESA lends its support. In order to evaluate the capability of MESA, the features of this system were compared against three other existing microservice-based research systems. MESA features were more robust than two of the other systems, but was found lacking when compared to the last, as it does not lender support to advanced techniques like HPC or Machine Learning.
Learning From Peers' Eye Movements in the Absence of Expert Guidance: A Proof of Concept Using Laboratory Stock Trading, Eye Tracking, and Machine Learning

Existing research shows that people can improve their decision skills by learning what experts paid attention to when faced with the same problem. However, in domains like financial education, effective instruction requires frequent, personalized feedback given at the point of decision, which makes it time-consuming for experts to provide and thus, prohibitively costly. We address this by demonstrating an automated feedback mechanism that allows amateur decision-makers to learn what information to attend to from one another, rather than from an expert. In the first experiment, eye movements of N = 100 subjects were recorded while they repeatedly performed a standard behavioral finance investment task. Consistent with previous studies, we found that a significant proportion of subjects were affected by decision bias. In the second experiment, a different group of N = 100 subjects faced the same task but, after each choice, they received individual, machine learning-generated feedback on whether their pre-decision eye movements resembled those made by Experiment 1 subjects prior to good decisions. As a result, Experiment 2 subjects learned to analyze information similarly to their successful peers, which in turn reduced their decision bias. Furthermore, subjects with low Cognitive Reflection Test scores gained more from the proposed form of process feedback than from standard behavioral feedback based on decision outcomes.
Knowledge Cycles and Corporate Investment

Investment is a means to experiment with technologies, creating valuable knowledge for firms. We analyze the feedback interaction between investment and knowledge through endogenous cycles of experimentation and exploration. Because experimentation is uncertain, firms become averse to investing when knowledge is scarce and q is high, overturning neoclassical insights. Investment is increasing in knowledge and its relation with q varies over the knowledge cycle. Experimentation further shortens cycle length. Using a text-based proxy for firms' knowledge cycles, we provide evidence supporting these novel predictions. Shorter knowledge cycles could explain weak aggregate investment despite high valuations in recent years.
Influence of Nonfinancial Information on Abnormal Returns

Financial information has a weakness in biases as a reference in decision making by investors. Nonfinancial information is needed to supplement financial information to show a company’s overall profile. This study aims to analyze the level of nonfinancial information disclosure and influence of prospector, defender, and analyzer strategies to level of nonfinancial information disclosure with control variable industry, age, share owned by public, and size of the company. The research also examines whether the level of nonfinancial information disclosure has a negative influence on abnormal returns with return on equity (ROE) and price-book value (PBV) as the control variables. The research is quantitative, with a sample number of 819 company annual reports from the period between 2014 and 2015, as listed on the Indonesia Stock Exchange. The research explains that prospector strategy has significantly positive influence on the level of nonfinancial information disclosure and defender strategy has significantly negative influence on the level of nonfinancial information disclosure. The industry, age, and share owned by the public have significantly positive influence on level of nonfinancial information disclosure. The research also finds that the level of nonfinancial information disclosure has a significantly positive influence on abnormal returns. While ROE has an insignificantly positive influence on abnormal returns, PBV has a significantly negative influence. Keywords—disclosure, nonfinancial information disclosure, abnormal returns
Towards A Semantic Indoor Trajectory Model

In this paper we present a Semantic Indoor Trajectory Model aimed at supporting the design and implementation of context-aware mobility data mining and statistical analytics methods. Motivated by a compelling museum case study, and by what we perceive as a lack in indoor trajectory research, we are interested in combining aspects of state-of-the art semantic outdoor trajec-tory models, with a semantically-enabled hierarchical symbolic representation of the indoor space, which abides by OGC's In-doorGML standard. We drive the discussion on those modeling issues and details that have been overlooked so far or where our approach deviates from typical practices. We illustrate the modeling part with instantiations from the Louvre Museum in an effort to provide a pragmatic view of what a Semantic Indoor Trajectory Model ought to represent and ideally also how.
EXPLORING BIOPSYCHOSOCIAL (BPS) FACETS OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE (COPD) IN PATIENTS IN AN ACUTE INPATIENT PHYSICAL REHABILITATION FACILITY (IRF)

OF DISSERTATION EXPLORING BIOPSYCHOSOCIAL (BPS) FACETS OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE (COPD) IN PATIENTS IN AN ACUTE INPATIENT PHYSICAL REHABILITATION FACILITY (IRF) From a BPS perspective, COPD and other chronic diseases may have a significant negative impact on those living with them and may be associated with higher rates of depression and anxiety and lower levels of health-related quality of life (HRQOL). Certain factors, such as spirituality, may influence the negative impact of chronic disease on the relationship between mood and functional independence and HRQOL. Also, gender may influence the relationship between mood, spirituality, and HRQOL for men and women living with chronic diseases. The current study included 136 patients undergoing physical rehabilitation at an IRF. Anxiety, depression, spirituality, HRQOL, and functional independence were evaluated for all. Mediation models were tested to determine the impact of spirituality on the relationships between mood and HRQOL and functional independence, and moderation models were tested to evaluate the impact of gender on the relationships between mood, spirituality, functional independence, and HRQOL. The current study yielded some inconclusive results but did evidence that COPD patients in acute inpatient physical rehabilitation facilities (IRF) have higher levels of anxiety than patients without COPD and also revealed that men with COPD have better HRQOL than do women with COPD. Spirituality was found to partially mediate the relationship between depression and HRQOL in IRF patients with COPD, but gender did not appear to moderate the relationships between mood, spirituality, functional independence, or HRQOL in IRF patients. As few studies on IRF patients with chronic diseases exist, continuing to evaluate patients in IRFs is important to enhance our BPS understanding of chronic disease.
On Entropic Framework Based on Standard and Fractional Phonon Boltzmann Transport Equations

Generalized expressions of the entropy and related concepts in non-Fourier heat conduction have attracted increasing attention in recent years. Based on standard and fractional phonon Boltzmann transport equations (BTEs), we study entropic functionals including entropy density, entropy flux and entropy production rate. Using the relaxation time approximation and power series expansion, macroscopic approximations are derived for these entropic concepts. For the standard BTE, our results can recover the entropic frameworks of classical irreversible thermodynamics (CIT) and extended irreversible thermodynamics (EIT) as if there exists a well-defined effective thermal conductivity. For the fractional BTEs corresponding to the generalized Cattaneo equation (GCE) class, the entropy flux and entropy production rate will deviate from the forms in CIT and EIT. In these cases, the entropy flux and entropy production rate will contain fractional-order operators, which reflect memory effects.
IACIS: A Profile of Conferences (1990–2004)

This study examines conference programs of the International Association for Computer Information Systems from 1990–2004. Program data are extracted from conference proceedings and entered into a database. Papers are profiled according to their strategy (research vs. pedagogical) and theme (content focus); institutions are profiled by location (US vs. non-US), type (academic or other), and frequency on program; authorship is examined through number of authors per paper and country of origin for non-US participants. The data revealed definite growth in the number of papers, authors, and institutions associated with the conference. Research papers outweighed pedagogical papers; co-authored papers outweighed single-authored papers. Geographical diversity has increased in terms of US states and non-US representation. International participation has possibly leveled off. Non-academic affiliations represent about 5% of all institutions. Program content reflects a wide-range of interests by IACIS participants. Results of the study provide a point of reflection on the development of the IACIS organization.
Microalbuminuria, Nondipping and Diastolic Dysfunction in Normotensive Type 2 Diabetic Patients

Microalbuminuria is an independent marker for cardiovascular morbidity and mortality however its relation with diastolic dysfunction in normotensive, well-controlled type 2 diabetic patients is not clearly documented. In twenty normoalbuminuric and 16 microalbuminuric type 2 diabetic patients, twenty-four hour ambulatory blood pressure monitoring, left ventricular echocardiographic evaluation, 12-hour daytime and nighttime urinary albumin excretion rate measurements were performed. A ≥ 10% drop in systolic blood pressure at night was accepted as the criteria for normal dipping (“dippers”). Mean day/night systolic blood pressure values of normoalbuminuric group were significantly higher than the microalbuminuric group (1.09±0.09 vs. 1.02±0.06, p=0.013). Twenty-four hour systolic blood pressures (110.3±6.3 mmHg vs. 103.5±8.8 mmHg, p=0.013, respectively) and diastolic blood pressures (79±5.1 mmHg vs. 75.1±5.1 mmHg, p=0.044, respectively) were significantly higher in nondippers compared to dippers. Diastolic dysfunction rates didn’t differ significantly between normoand microalbuminuric groups (40% (8/20) vs. 43.8% (7/16), respectively, p>0.05). Microalbuminuria wasn’t related with a more atherogenic lipid profile, increased rate of retinopathy and higher left ventricular mass index. These results indicate that, even in normotensive and well-controlled type 2 diabetic patients, microalbuminuria is related to nondipping. However, similar diastolic dysfunction rates between normoand microalbuminuric subjects suggest that, good metabolic control in the presence of normotension may alleviate the increased likelihood of diastolic dysfunction and higher left ventricular mass index attributed to microalbuminuria and nondipping in the previous studies.
Medical Problems in High Mountain Environments. A Handbook for Medical Officers.

Abstract : This Technical Note describes the physiological and medical basis for the prevention and treatment of altitude-related illnesses and a description of the reduced mental and physical performance incurred by troops in an operational high terrestrial altitude environment. Medical officers are provided with background information for the diagnosis, prevention and management of the primary altitude-induced medical problems: acute mountain sickness (AMS), high altitude pulmonary edema (HAPE) and high altitude cerebral edema (HACE). Secondary medical problems are also reviewed as are precautionary and contributory sea-level medical conditions and general physiological and psychological factors affecting the performance of soldiers at altitude. Altitude, Acute Mountain Sickness, Pulmonary Edema, Cerebral Edema, Occupational and Preventive Medicine, Acclimatization, Altitude Medicine, High Terrestrial Elevation
Identification of I‐equivalent subnetworks in Bayesian networks to incorporate experts' knowledge

Bayesian networks (BNs) have been widely used in causal analysis because they can express the statistical relationship between significant variables. To gain superior causal analysis results, numerous studies have emphasized the importance of combining a knowledge‐based approach and a data‐based approach. However, combining these two approaches is a difficult task because it can reduce the effectiveness of the BN structure learning. Further, the learning schemes of BNs for computational efficiency can cause an inadequate causal analysis. To address these problems, we propose a knowledge‐driven BN structure calibration algorithm for rich causal semantics. We first present an algorithm that can efficiently identify the subnetworks that can be altered to satisfy the learning condition of the BNs. We then reflect experts' knowledge to reduce erroneous causalities from the learned network. Experiments on various simulation and benchmark data sets were conducted to examine the properties of the proposed method and to compare its performance with an existing method. Further, an experimental study with real data from semiconductor fabrication plants demonstrated that the proposed method provided superior performance in improving structural accuracy.
Further Development of the NASA X-57 Maxwell Mission Planning Tool for Mods II, III, and IV

The goal of the experimental, fully electric X-57 Maxwell aircraft to enable lower energy consumption at cruise compared to a fuel burning baseline. A sum of subsystem benefits incorporated in the electric, airframe, and propulsion systems result in this reduction in energy consumption. The Mission Planning Tool is used to predict the performance and operation of this aircraft. It captures the aerodynamics, propulsion, heat transfer, and power system of the aircraft with trajectory optimization capabilities throughout all phases of flight. This paper details the continued development of the X-57 Mission Planning Tool and demonstrates its capability to assess the effect of subsystem performance on the integrated aircraft system. The tool can also analyze how the aircraft will react if performance goals, such as electric component efficiencies, are either not met or exceeded. The results presented achieve maximum cruise duration of the X-57 through each stage in development as well as trajectory analyses predicting component efficiency limits and energy consumption.
Factors Associated with Health Promotion of Caregivers Based on a Socio-ecological Model

Purpose: To investigate the behavioural factors of the health promotion for caregivers based on a socio-ecological model. Methods: This study was a cross-sectional descriptive study using a self administered questionnaire. The survey was conducted in 219 people chosen through convenient sampling between September and December 2008. The collected information included general characteristics, individual, interpersonal, community, policy level. Results: For the statistical analysis, the t-test was used for the health promotion according to the general characteristics and to each level of the socio-ecological model, by assessing the high and low values and dividing them into mean points. The influence elicited by different health promotion factors was determined using the hierarchical multiple regression. At the individual level, the factors influencing health promotion in caregivers included perceived seriousness, perceived benefits, and self efficacy. Social support was important at interpersonal level, and the use of community resource was relevant for the community level. We found no statistically significant factors relating to the policy level. Conclusions: In conclusion, the socio-ecological models seems appropriate for explaining health promotion and its associated factors in caregivers. We suggest that, for caregivers, strategies should be developed for their social support and to offer information about how to use community resources in relation with factors relating to the individual level.
Antecedents of Use-Continuance in Information Systems: Toward an Inegrative View

The effectiveness of investment in information system (IS) can be partly explained by the continuous usage of installed systems. Therefore, the research on IS user retention is important from both practical and academic perspectives. In order to develop an integrative model for IS users' continued usage, this paper explores the main antecedents that cause the retention of IS users. In addition to attitude, the integrative model links previous behavior like habit and behavioral control belief like switching cost, to IS continuance intention. For an empirical exploration, 345 samples were collected from the users of a web portal site. Data analysis using Structural Equation Modeling shows that IS quality in terms of desire congruency and expectation congruency has a direct effect on attribute satisfaction. The attribute satisfaction shows a significant effect on continuance intention mediated by the attitude toward use-continuance. Lastly, it is found that switching cost has a significant direct effect on continuance intention while habit has an indirect effect via switching cost.
A Panoramic Survey on Grasping Research Trends and Topics

Abstract Grasping and object manipulation is a key element of intelligent behavior. Many innovative cyberphysical systems involve some kind of object grasp and manipulation, to the extent that grasping has been recognized as a critical technology for the next generation industrial systems. In this survey, we aim to draw a broad landscape of applications and current research trends and topics relating to grasping techniques and tools. Applications range from biomedical and surgical to industrial warehouse pick and place tasks, covering a wide range of spatial scales, from micro to macro scales. The resources involved and research lines under development include the latest computational intelligence tools as well as the research on new materials and devices for sensing and actuation.
Improving a Medication Error Monitoring Program at an Acute-Care Hospital

This report describes the development and implementation of a medication error monitoring program (MEMP) at an acute-care hospital in a multisite health care system. Data from every reported potential error (mistakes in prescribing, transcribing, dispensing, or planned administration that are detected and corrected before actual administration) and actual error (mistakes identified after drug is administered or failure to administer a scheduled drug) were entered in an electronic database. Medication errors with more than one potential cause were counted more than once. A designated pharmacist, in consultation with other health care professionals, assigned a severity level (levels I–IV; from no apparent injury to permanent functional impairment or death based on published definitions1) to the clinical outcome of every error. A summary of the data and performance improvement activities were reported to the hospital's Pharmacy and Therapeutics Committees, Quality Improvement Committees, and Board of Trustees.
Interrupting Teachers’ Assumptions about English Learners through Literature Discussion

ABSTRACT Although classrooms across the United States continue to become more diverse, teachers are often underprepared to support the learning of immigrant students and students labeled as English learners (ELs). In the current investigation, we turn toward literature discussion using bilingual poetry with teachers to learn how participants recognize their assumptions and beliefs related to language and culture. In this phenomenological study framed with sociocultural and transactional theories, we present data related to teachers’ discussions of one bilingual poetry picture book. We share findings related to teachers’ understandings about their own assumptions, as well as personal connections to challenge those assumptions. We contend that teachers’ individual transactions and connections with literature led to interruptions in their assumptions and beliefs about students.
Model-based routing in flexible manufacturing systems

Abstract In this paper, a model-based routing approach for flexible manufacturing systems (FMS) with alternative routes for the work pieces is proposed. For each work piece, an individual task has to be accomplished, which consists of several processing steps. Each processing step can be executed on alternative working stations of the FMS. The proposed routing method employs a model of the conveying system to find energy efficient and fast routes for the respective work pieces. The conveying system model is based on a directed graph, where the individual conveyors are modeled as weighted edges. It can be straightforwardly applied to several types of FMS by adjusting the application-dependent parameters. Efficient computation of the fastest route through the conveying system is accomplished by means of dynamic programming, i. e. , by integration of Dijkstra’s algorithm in a dynamic programming framework, which is based on the proposed conveying system model. Additional consideration of energy efficiency aspects leads to a Mixed Integer Quadratically Constraint Program (MIQCP), which is solved by substitution of Dijkstra’s algorithm by a branch and bound method. Experimental results for an application scenario, where the energy efficient routing method is applied to route work pieces between the working stations of an FMS, lead to 20 % reduction of energy consumption on average.
Performance Evaluation of Fixed Sample Entropy in Myographic Signals for Inspiratory Muscle Activity Estimation

Fixed sample entropy (fSampEn) has been successfully applied to myographic signals for inspiratory muscle activity estimation, attenuating interference from cardiac activity. However, several values have been suggested for fSampEn parameters depending on the application, and there is no consensus standard for optimum values. This study aimed to perform a thorough evaluation of the performance of the most relevant fSampEn parameters in myographic respiratory signals, and to propose, for the first time, a set of optimal general fSampEn parameters for a proper estimation of inspiratory muscle activity. Different combinations of fSampEn parameters were used to calculate fSampEn in both non-invasive and the gold standard invasive myographic respiratory signals. All signals were recorded in a heterogeneous population of healthy subjects and chronic obstructive pulmonary disease patients during loaded breathing, thus allowing the performance of fSampEn to be evaluated for a variety of inspiratory muscle activation levels. The performance of fSampEn was assessed by means of the cross-covariance of fSampEn time-series and both mouth and transdiaphragmatic pressures generated by inspiratory muscles. A set of optimal general fSampEn parameters was proposed, allowing fSampEn of different subjects to be compared and contributing to improving the assessment of inspiratory muscle activity in health and disease.