Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relation of Calculated Plasma Volume Status to Sublingual Microcirculatory Blood Flow and Organ Injury

Background: The calculated plasma volume status (cPVS) was validated as a surrogate of intravascular filling. The aim of this study is to assess the cPVS in relation to sublingual perfusion and organ injury. Methods: Pre- and postoperative cPVS were obtained by determining the actual and ideal plasma volume levels in surgical patients. The sublingual microcirculation was assessed using SDF imaging, and we determined the De Backer score, the Consensus Proportion of Perfused Vessels (Consensus PPV), and the Consensus PPV (small). Our primary outcome was the assessment of the distribution of cPVS and its association with intraoperative sublingual microcirculation and postoperative complications. Results: The median pre- and postoperative cPVS were −7.25% (IQR −14.29–−1.88) and −0.4% (IQR −5.43–6.06), respectively (p < 0.001). The mean intraoperative administered fluid volume was 2.5 ± 2.5 L (1.14 L h−1). No statistically significant correlation was observed between the pre- or postoperative cPVS and sublingual microcirculation variables. Higher preoperative (OR = 1.04, p = 0.098) and postoperative cPVS (OR = 1.057, p = 0.029) were associated with postoperative organ injury and complications (sepsis (30%), anemia (24%), respiratory failure (13%), acute kidney injury (6%), hypotension (6%), stroke (3%)). Conclusions: The calculated PVS was associated with an increased risk of organ injury and complications in this cohort.
Hydrogel-Based Bioelectronics and Their Applications in Health Monitoring

Flexible bioelectronics exhibit promising potential for health monitoring, owing to their soft and stretchable nature. However, the simultaneous improvement of mechanical properties, biocompatibility, and signal-to-noise ratio of these devices for health monitoring poses a significant challenge. Hydrogels, with their loose three-dimensional network structure that encapsulates massive amounts of water, are a potential solution. Through the incorporation of polymers or conductive fillers into the hydrogel and special preparation methods, hydrogels can achieve a unification of excellent properties such as mechanical properties, self-healing, adhesion, and biocompatibility, making them a hot material for health monitoring bioelectronics. Currently, hydrogel-based bioelectronics can be used to fabricate flexible bioelectronics for motion, bioelectric, and biomolecular acquisition for human health monitoring and further clinical applications. This review focuses on materials, devices, and applications for hydrogel-based bioelectronics. The main material properties and research advances of hydrogels for health monitoring bioelectronics are summarized firstly. Then, we provide a focused discussion on hydrogel-based bioelectronics for health monitoring, which are classified as skin-attachable, implantable, or semi-implantable depending on the depth of penetration and the location of the device. Finally, future challenges and opportunities of hydrogel-based bioelectronics for health monitoring are envisioned.
Mathematical Optimization for Routing and Logistic Problems

In this thesis, we focus on mathematical optimization models and algorithms for solving routing and logistic problems. The first contribution regards a path and mission planning problem, called Carrier-Vehicle Traveling Salesman Problem (CVTSP), for a system of heterogeneous vehicles. A Mixed-Integer Second Order Conic Programming (MISOCP) model and a Benders-like enumeration algorithm are presented for solving CVTSP. The second work concerns a class of routing problems, referred to as Interceptor Vehicle Routing Problems (IVRPs). They generalize VRPs in the sense that target points are allowed to move from their initial location according to a known motion. We present a novel MISOCP formulation and a Branch-and-Price algorithm based on a Lagrangian Relaxation of the vehicle-assignment constraints. Other two contributions focus on waste flow management problems: the former considers a deterministic setting in which a Mixed-Integer Linear Programming (MILP) formulation is used as a Decision Support System for a real-world waste operator, whereas the latter deals with the uncertainty of the waste generation amounts by means of Two-Stage Multiperiod Stochastic Mixed-Integer Programming formulations. Finally, we give an overview on the optimization challenges arising in electric car-sharing systems, both at strategic and tactical planning level.
EasiEI: A Simulator to Flexibly Modeling Complex Edge Computing Environments

In edge computing scenarios, there is a need for modeling dedicated features and heterogeneous devices functions, as well as integrating multiple complex scenarios with diverse objectives and frequent interactions. However, existing platforms modeling for the whole device ignores the independence between functional components resulting in limited scenario support. We propose an open-source simulator named EasiEI. EasiEI addresses the need for higher level feature replaceability and independence in modeling complex edge scenarios through independent functional component-level modeling and microkernel architecture. This approach enables users to assemble independent functional components in a plug-and-play manner for heterogeneous devices or different application requirements. EasiEI is fully compatible with all the existing built-in modules in NS3 (a powerful network discrete event simulator). To verify the flexibility and extensibility of EasiEI, we implement several centralized and decentralized computing paradigms cases in a step-by-step way. These cases restore and simulate the performance state of various real devices in real time, meeting the requirements for verifying the edge computing ideas such as task scheduling in a distributed manner. Results show that the simulations have well reflected the characteristics of the real world and can construct complex environment flexibly.
Application of Spectral Polarimetry to a Hailstorm at Low Elevation Angle

Spectral polarimetry has the potential to be used to study microphysical properties in relation to the dynamics within a radar resolution volume by combining Doppler and polarimetric measurements. The past studies of spectral polarimetry have focused on using radar measurements from higher elevation angles, where both the size sorting from the hydrometeors’ terminal velocities and polarimetric characteristics are maintained. In this work, spectral polarimetry is applied to data from the 0° elevation angle, where polarimetric properties are maximized. Radar data collected by the C-band University of Oklahoma Polarimetric Radar for Innovations in Meteorology and Engineering (OU-PRIME) during a hailstorm event on 24 April 2011 are used in the analysis. The slope of the spectral differential reflectivity exhibits interesting variations across the hail core, which suggests the presence of size sorting of hydrometeors caused by vertical shear in a turbulent environment. A nearby S-band polarimetric Weather Surveillance Radar-1988 Doppler (KOUN) is also used to provide insights into this hailstorm. Moreover, a flexible numerical simulation is developed for this study, in which different types of hydrometeors such as rain and melting hail can be considered individually or as a combination under different sheared and turbulent conditions. The impacts of particle size distribution, shear, turbulence, attenuation, and mixture of rain and melting hail on polarimetric spectral signatures are investigated with the simulated Doppler spectra and spectral differential reflectivity.
A Step-by-Step Approach for User Acceptance Evaluation in Games Based on Sentiment Analysis and Machine Learning

User opinion analysis is an important tool to guide the decision-making process of independent game developers and game studios, once such activity leads to better product development towards the user satisfaction. Sentiment Analysis (SA) techniques have been widely used by companies to discover what customers are saying about their products, and the game industry could also benefit from such research field, once user feelings about a video game may have a relevant impact in retention and revenues. In this work, a thorough analysis on user acceptance in video games is performed by means of Natural Language Processing and SA approaches, where game reviews are exploited to understand what are the most relevant topics users are taking into consideration when they evaluate a game. A Sentiment Classification approach is performed, and the proposed methodology is discussed step-by-step, seeking out to motivate further researches in the field. Also, a new data set is proposed, composed by game reviews written in Brazilian Portuguese, given the relevance of Brazilian market in game industry.
NEEDLE & KNOT: A framework for meta-theoretical specifications with binding

This extended abstract showcases NEEDLE & KNOT, a framework for programming language mechanization. Our framework tackles the problem that formal proofs about programming language semantics and type-systems are long and error-prone. To guarantee their correctness, techniques for mechanical formalization in proof assistants, such as ones based on type-theories, have received much attention in recent years. However, human mechanizers of programming language meta-theory are unnecessarily burdened with boilerplate that arises from variable bindings in programming languages. To tackle the substantial boilerplate for richer languages, support from the proof assistant or from tools is mandatory. NEEDLE & KNOT specifically target the boilerplate that arises in type-safety proofs of typed programming languages. In particular, they use the syntactic approach to programming language metatheory, invented by Wright and Felleisen [13] and popularized by Pierce [10]. The treatment of variable binding typically comprises the better part of such formalizations. Most of this variable binding infrastructure is repetitive and tedious boilerplate. By boilerplate we mean mechanical operations and lemmas that appear in many languages, such as: 1) common operations like calculating the sets of free variables or the domain of a typing context, appending contexts and substitutions; 2) lemmas about operations like commutation of substitutions or the interaction between the free-variable calculation and substitution; and 3) lemmas about semantic relations such as the preservation of well-scoping and typing under operations. Our approach consists of two ingredients: 1) KNOT, a domainspecific specification language for abstract syntax and relational semantics of programming languages and 2) NEEDLE, a tool to generate COQ code from KNOT specifications. Our case studies demonstrate that this approach significantly reduces the size of language mechanizations and enables the mechanizer to skip the tedious boilerplate and directly work on the interesting meta-theory.
Radar Target Detection via Global Optimality Conditions for Binary Quadratic Programming

This article considers the problem of radar target detection in compound Gaussian clutter background. Different from the existing detector design criteria, we propose two new detection schemes for the detection problem from the optimization perspective. Specifically, in the first scheme, the detection problem is firstly studied by introducing an auxiliary variable and transforming it into a maximum likelihood estimation problem. Under this scheme, the maximum likelihood detector and its improved version with parameter estimation are developed by using maximum likelihood criterion. In the second scheme, the detection problem is recast into a binary quadratic programming (BQP) problem. Resorting to the global optimality conditions and solution for the BQP problem, we design four BQP detectors named BQPH, BQPS, BQPM and BQPW with the aid of hard decision fusion, data fusion based on summation and taking median, and whitening respectively. At the analysis stage, the statistical distributions of the BQP detectors are modelled using $t$ location-scale distribution, and the theoretical closed-form expressions of the false alarm probability, thresholds and detection probability of the four BQP detectors are further derived. Finally, simulation experiments on the simulated data and real sea clutter data are performed to highlight the effectiveness of the proposed detectors in comparison with several state-of-the-art detectors.
Study of the Effect of Exercises on the Quality of Life, Fatigue, Sarcopenia in Breast, and Prostate and Colorectal Cancers

Breast, prostate, and colorectal cancers are the most common cancers and have the highest mortality rates worldwide. Objective: To determine the benefits of continuous training at moderate and high intensity on quality of life, fatigue and sarcopenia in breast, prostate, and colorectal cancer. Method: A quasi-experimental study was performed with 356 patients with stage II breast cancer. The patients were distributed in 2 groups, and EORTC QLQ C-30 scale, FACT- Fatigue Scale, quality of life test, stress test, dynamometry and others were carried out. Results: The study population presented with sarcopenia. At the end of the study, the prevalence of sarcopenia decreased significantly (GE1: 31 % [before] vs. 24 % [after], and GE2: 38 % [before] vs. 19 % [after]; P ≤ 0.05). As did the values for fatigue (GE1: 17.3 ± 3.8 [before] vs. 10.4 ± 2.5 [after], and GE2: 19.6 ± 4.2 [before] vs. 9.4 ± 3.1 [after]; P = 0.012) and in the quality-of-life questionnaire (GE1: 61.7 ± 10.4 [before] vs. 69.5 ± 14.4 [after]; GE2: 76.5 ± 7.4 [before] vs. 106; P = 0.005). Conclusion: Continuous training at moderate and high intensity inevitably improved the variables evaluated, especially quality of life, fatigue, and sarcopenia. It should be noted that the improvements were more notable in the high intensity group.
The Moderating Effects of Self-Care on the Relationships between Perceived Stress, Job Burnout and Retention Intention in Clinical Nurses

This study determines the importance of nurses’ self-care by identifying its effects as a moderating variable on the relationships between perceived stress, job burnout, and retention intention in clinical nurses. Hence, 174 clinical nurses who worked at two university hospitals and one general hospital located in Seoul, South Korea, participated in this study. As the hospitals required the use of recruitment notices, convenience sampling methods were adopted to recruit volunteers. The data were collected using the perceived stress scale, the burnout assessment tool, the nurse retention index, and the self-care assessment worksheet. Descriptive statistics were used to analyze the general characteristics of participants, and t-test and analysis of variance were conducted for comparisons. Moderated multiple regression was conducted to verify the moderating effects of self-care on the relationships between perceived stress and retention intention and between job burnout and retention intention. The results revealed that the effect of perceived stress on retention intention and the moderating effect of self-care on the relationship between perceived stress and retention intention were not significant, whereas job burnout had a direct effect on retention intention, and self-care had a positive moderating effect on job burnout. Therefore, it is necessary to consider an instructional program on the importance of self-care and conduct campaign activities at the organizational level. Moreover, various support structures should be provided at the organizational level such that nurses can reduce their levels of job burnout.
Motion pattern generation based on the free vibration for an explosive increase of the kinetic energy in the robot end-link during swing motion

The purpose of our research is to improve robot motion ability without depending on only actuator power by effectively exploiting the dynamic properties of a robot. In this paper, we focused on swing motion (e.g., throwing or kicking motion). The prime purpose in swing motion is to increase the kinetic energy of the end-link (e.g., hand or foot). In this paper, using a multi-link planar robot, we proposed a method to generate a robot motion for an explosive increase of the kinetic energy in the robot end-link. Humans increase the kinetic energy of the end-link by exploiting the dynamic properties during swing motion. The kinetic energy of the end-link increases because large energy produced by strong muscles in the center side of the body is transferred toward the end side. We constructed mathematical models to explain this mechanical phenomenon on the basis of the free vibration. Furthermore, we proposed a method to generate a robot motion for an explosive increase of the kinetic energy in the robot end-link using the models. The results of simulation experiments showed that the kinetic energy of the end-link increases because large energy produced by actuators in the center side of the robot is transferred toward the end side. Furthermore, the robot motion generated by our method is similar to a trajectory optimized based on energetic cost. Then, we proposed a method to generate a robot motion considering the torque limits of actuators by revising the method mentioned above. The results of simulation experiments showed that torques required by actuators are reduced by using the revised method.
Robust and Decentralized Control of Positive Systems: A Convex Approach

This thesis focuses on robust and decentralized control problems for positive systems. We begin by revisiting a classical modeling framework that allows us to model uncertain systems in a systematic way and, using tools from convex analysis, we derive tractable necessary and suﬃcient conditions for robust stability of uncertain positively dominated systems. These conditions involve only the system’s static gain and can be veriﬁed using convex optimization. We illustrate our results by deriving conditions for the robust stability of the Foschini-Miljanic algorithm, with applications to power control for communication systems with uncertain interference matrix. We then derive equivalent necessary and suﬃcient state-space conditions for the robust stability of positive systems. We use these conditions to show that designing structured controllers that enforce robust stability and close-loop positivity is a tractable problem that can be solved using convex optimization. We further extend our results to a class of systems with sector-bound nonlinearities, proving that the S-Procedure is lossless for positive systems. In the second part of the thesis we study a class of decentralized control problems for positive systems with application to biology and network theory. We show that, despite the structural constraints, these problems are convex both in the nominal and in the robust case and can be solved eﬃciently using custom descent algorithms. We provide several examples from leader selection in directed networks to robust optimal drug therapy for HIV. In the ﬁnal
PMBOK Game II: Um Jogo Educacional para Apoiar o Ensino de Gestão de Projetos de Software

O ensino tradicional da disciplina de gestão de projetos na área de Computação é complexo, visto que esses conteúdos são densos e de difícil memorização, além de serem pouco atrativos para os estudantes. Nesse sentido, diferentes iniciativas têm sido propostas visando dar suporte para o ensino de gestão de projetos. Dentre elas, encontram-se os jogos educacionais que são ferramentas que promovem a diversão e engajamento dos estudantes. Em particular, o PMBOK Game é um jogo de tabuleiro que visa apoiar o ensino dos conteúdos de gestão de projetos contidos no guia PMBOK 5ª edição. Assim, este trabalho visa apresentar a versão atual do PMBOK Game II, bem como sua aplicação para apoiar o processo de ensino e aprendizagem dos estudantes.
Some Natural Solutions to the p-Value Communication Problem—and Why They Won’t Work

It is well known that even experienced scientists routinely misinterpret p-values in all sorts of ways, including confusion of statistical and practical significance, treating nonrejection as acceptance of the null hypothesis, and interpreting the p-value as some sort of replication probability or as the posterior probability that the null hypothesis is true. A common conceptual error is that researchers take the rejection of a straw-man null as evidence in favor of their preferred alternative (Gelman 2014). A standard mode of operation goes like this: p < 0.05 is taken as strong evidence against the null hypothesis, p > 0.15 is taken as evidence in favor of the null, and p near 0.10 is taken either as weak evidence for an effect or as evidence of a weak effect. Unfortunately, none of those inferences is generally appropriate: a low p-value is not necessarily strong evidence against the null (see, e.g., Morris 1987; Gelman and Carlin 2014), a high p-value does not necessarily favor the null (the strength and even the direction of the evidence depends on the alternative hypotheses), and p-values are in general notmeasures of the size of any underlying effect. But these errors persist, reflecting (a) inherent difficulties in the mathematics and logic of p-values, and (b) the desire of researchers to draw strong conclusions from their data. Continued evidence of these and other misconceptions and their dire consequences for science (the “replication crisis” in psychology, biology, and other applied fields), especially in light of new understanding of how common it is that abundant “researcher degrees of freedom” (Simmons, Nelson, and Simonsohn 2011) and “gardens of forking paths” (Gelman and Loken 2014) allow researchers to routinely obtain statistically significant and publishable results from noise, motivated the American Statistical Association to release a Statement on Statistical Significance and p-values in an attempt to highlight the magnitude and importance of problems with current standard practice (Wasserstein and Lazar 2016). At this point, it would be natural for statisticians to think that this is a problem of education and communication. If we could just add a few more paragraphs to the relevant sections of our textbooks, and persuade applied practitioners to consult more with statisticians, then all would be well, or so goes this logic.
The millennials: Adversity intelligence and work engagement

The industrial world is transforming towards the era of revolution 4.0 and society 5.0. In this era, digital technology is applied and becomes the center of human life. Demand that the millennial generation who currently dominates the job market in Indonesia have adversity intelligence so that they can be more engaged in their work and have a positive impact on company performance and development. This study aims to determine the relationship between adversity intelligence and work engagement in the millennial generation. Subjects in this study were 214 employees, aged 20-39 years who live in Yogyakarta and have worked at least one year. The data collection method in this study uses a Likert scale model. Data were collected using the Work Engagement Scale and the Adversity Intelligence Scale, by sending the scale via Google Form to respondents. The data analysis technique used is the product-moment correlation from Karl Pearson. Based on the data analysis, the correlation coefficient (R) was obtained for 0.820 (p <0.01). These results indicate that there is a very significant positive relationship between adversity intelligence and work engagement among millennial employees living in Yogyakarta. This study provides an overview of the level of work engagement and adversity intelligence for millennial generation employees, so as to increase the work engagement of millennial generation employees by increasing their adversity intelligence.