Miracle-dz/UniFAR-FTUs huggingface dataset:
COPD Assessment Test as a Screening Tool for Anxiety and Depression in Stable COPD Patients: A Feasibility Study

Abstract Anxiety and depression are common comorbidities in chronic obstructive pulmonary disease (COPD) patients but are often under-diagnosed. We aimed to assess the suitability of the COPD Assessment Test (CAT) in screening anxiety and depression in patients with COPD. Stable COPD patients from a cross-sectional observational study were assessed by CAT. Anxiety and depression were identified using the Generalized Anxiety Disorder questionnaire (GAD-7) and Patient Health Questionnaire (PHQ-9), respectively. Logistic regression analysis and receiver operating characteristic curve analysis were used to identify factors associated with anxiety or depression and to calculate the predictive values. A total of 530 stable COPD patients were enrolled and of those, the proportions of anxiety and depression were 17.0% and 21.5%, respectively. The adjusted odds ratios of the CAT for the presence of anxiety and depression were 1.094 (95%CI: 1.057–1.131) and 1.143 (95%CI: 1.104–1.183), respectively. The CAT score had a significant predictive value for the presence of anxiety (AUC = 0.709) and depression (AUC = 0.791) with an optimum cutoff score of 15. However, the psychometric properties of CAT were undesirable, presenting high negative predictive value (NPV) but low positive predictive value (PPV). Among CAT items, analysis further showed that non-respiratory CAT components were superior to respiratory components in identifying both anxiety and depression. Our results indicated that CAT is more useful to exclude anxiety and depression rather than detect them.
Fast and furious: The neutrophil and its armamentarium in health and disease

Neutrophils are powerful effector cells leading the first wave of acute host‐protective responses. These innate leukocytes are endowed with oxidative and nonoxidative defence mechanisms, and play well‐established roles in fighting invading pathogens. With microbicidal weaponry largely devoid of specificity and an all‐too‐well recognized toxicity potential, collateral damage may occur in neutrophil‐rich diseases. However, emerging evidence suggests that neutrophils are more versatile, heterogeneous, and sophisticated cells than initially thought. At the crossroads of innate and adaptive immunity, neutrophils demonstrate their multifaceted functions in infectious and noninfectious pathologies including cancer, autoinflammation, and autoimmune diseases. Here, we discuss the kinetics of neutrophils and their products of activation from bench to bedside during health and disease, and provide an overview of the versatile functions of neutrophils as key modulators of immune responses and physiological processes. We focus specifically on those activities and concepts that have been validated with primary human cells.
The effect of combining punishment and reward can transfer to opposite motor learning

Recent laboratory findings have demonstrated that, when imposed separately, punishment and reward have different effects on motor learning. In real-world applications, however, they are usually used in combination to improve human behavior. For instance, a student may be punished when failing an examination and rewarded when getting a high score. It remains unclear precisely how people are motivated when punishment and reward are combined. Moreover, whether it is possible for the effects of punishment and reward to transfer to other learning situations remains unknown. In the present study, four groups of participants were trained on a motor adaptation task under conditions of either punishment, reward, both punishment and reward combination, or a neutral control condition (neither). We tested what the effect of combining punishment and reward is on motor learning and memory. Further, we examined whether the effect could transfer to later opposite-direction learning in the absence of motivational feedback. Specifically, during the initial learning when there is motivational feedback, combining punishment and reward can not only accelerate learning rate, but can also increase learning extent. More interestingly, the effect can even transfer to later opposite-direction learning. The findings suggest that the combination of punishment and reward has a distinct advantage over pure punishment or reward on motor learning and the effect can transfer to opposite motor learning.
A POLYNOMIAL-TIME ALGORITHM TO SOLVE THE AIRCRAFT REFUELING PROBLEM: THE SEQUENTIAL SEARCH ALGORITHM

Airplane refueling problem is a nonlinear combinatorial optimization problem with n ! feasible feasible solutions. Given a ﬂeet of n airplanes with mid-air refueling technique, each airplane has a speciﬁc fuel capacity and fuel consumption rate. The ﬂeet starts to ﬂy together to a same target and during the trip each airplane could instantaneously refuel to other airplanes and then be dropped out. The question is how to ﬁnd the best refueling policy to make the last remaining airplane travels the farthest. To solve the large scale of the airplane refueling problem in polynomial-time, we propose the deﬁnition of the sequential feasible solution by employing the data structural properties of the airplane refueling problem. We prove that if an airplane refueling problem has feasible solutions, it must have sequential feasible solutions, and its optimal feasible solution must be the optimal sequential feasible solution. Then we present the sequential search algorithm which has a computational complexity that depends on the number of sequential feasible solutions referred to Q n , which is proved to be upper bounded by 2 n − 2 as an exponential bound that lacks of applicability on larger input for worst case. Therefore we investigate the complexity behavior of the sequential search algorithm from dynamic perspective, and ﬁnd out that Q n is bounded by m 2 n C mn when the input n is greater than 2 m . Here m is a constant and 2 m is regarded as the ”inﬂection point” of the complexity of the sequential search algorithm from exponential-time to polynomial-time. Moreover, we build an eﬃcient computability scheme according to which we shall predict the speciﬁc complexity of the sequential search algorithm to choose a proper algorithm considering the available running time for decision makers or users.
How Would You Manage This Patient With Benign Prostatic Hyperplasia?

Lower urinary tract symptoms due to benign prostatic hyperplasia (BPH) are common in older patients assigned male sex at birth, regardless of gender identity, and treatment of these symptoms is therefore common in primary care practice. In 2021, the American Urological Association published guidelines for management of BPH. They recommend using a standardized scoring system such as the International Prostate Symptom Score to help establish a diagnosis and to monitor the efficacy of interventions, α-blockers as the first-choice pharmacotherapy option, and 5α-reductase inhibitors for patients with prostate size estimated to be at least 30 cc. Tadalafil is another option regardless of erectile dysfunction. Combination therapies with α-blockers and 5α-reductase inhibitors, anticholinergic agents, or β3-agonists are effective options. A surgical referral is warranted if the BPH results in chronic kidney disease, refractory urinary retention, or recurrent urinary tract infections; if there is concern for bladder or prostate cancer; or if symptoms do not respond to medical therapy. In this article, a general internal medicine physician and a urologist discuss the treatment options and how they would apply their recommendations to a patient who wishes to learn more about his options.
Coleoptera associated with intermittent streams and their riparian zones in south coastal British Columbia

Abstract Intermittent streams that periodically cease surface flow have long been understudied in ecology and underrepresented in conservation policy. However, they currently account for 30–50% of the global river network, and that number is rising due to anthropogenic water extraction, land-use change, and climate change. We explored the Coleoptera biodiversity of the south Pacific coast region of British Columbia, Canada, using pitfall traps at perennial and naturally intermittent stream reaches, in shoreline, dry streambed, and riparian habitats, in both flowing (spring and early summer) and nonflowing (late summer) phases. We found that habitats around perennial reaches had significantly greater abundance of Coleoptera individuals than did those around intermittent reaches. However, neither habitat type nor flow regime was a significant predictor of taxon richness, and intermittent stream sites featured unique taxa that were not found near perennial streams. This aligns with recent results from other taxonomic groups; that is, finding that intermittent ecosystems can host high taxonomic diversity of Coleoptera, on par with or even greater than that of perennial streams. Because intermittent streams will likely become more prevalent within the global river network, a better understanding of how different species use these habitats is needed to inform appropriate biodiversity conservation efforts and flow management.
Automated Testing in Super Metroid with Abstraction-Guided Exploration

Machine playtesting systems often aim to demonstrate how to reach certain moments of play. To provide design feedback in a timely manner, they often internally rely on heuristic-guided search. However, there are many types of videogames for which sufficiently accurate heuristics are not available. We use an imperfect abstraction of an underlying game to define progress scores, and show that combining these scores yields a highly effective cell selection heuristic for use in the Go-Explore algorithm. We demonstrate the impact of this approach in automated gameplay for Super Metroid (involving mandatory item collection, destructible blocks, and backtracking) using a tile-based abstraction of the game that only models a small subset of the game’s mechanics. Surprisingly, our abstraction guidance mechanism is able to explore this complex game several orders of magnitude more efficiently than past work with similar exploration methods in Montezuma’s Revenge.
Interactive Latent Variable Evolution for the Generation of Minecraft Structures

The open-world sandbox game Minecraft is well-known for applying a wide array of procedural content generation techniques to create unique and expansive game environments. However, procedurally generated buildings are absent in the Minecraft world, thus players must build their own structures to flesh out their worlds. This build process can be extremely time-consuming and appeals to more creatively-inclined players. To aid players in this process, we introduce a tool combining interactive evolution with latent variable evolution to evolve procedurally generated Minecraft structures to a player’s aesthetic choices. We employ two separate neural network models to generate structures: a 3D generative model for generating the structure design and an encoding model for applying Minecraft textures to the structure’s voxels. We evaluate this tool with a user study incorporating an online interface that allows participants to select, evolve, and guide a population of these generated 3D structures towards a specific design goal.
Integrating Players’ Perspectives in AI-Based Games: Case Studies of Player-AI Interaction Design

The game design community has a long history of adapting different forms of AI techniques to produce new playable experiences. However, current AI-based game design literature focuses primarily on designers’ intent and expression. This paper argues that engaging with players’ perspectives on AI during development is an essential but often overlooked piece in existing AI-based game design processes. By integrating this perspective, game designers can better outline how players may experience AI in the context of games and tailor design decisions to the intended experience. This paper offers three case studies that incorporate the player perspective into the design process and discusses design implications.
Why Oatmeal is Cheap: Kolmogorov Complexity and Procedural Generation

Although procedural generation is popular among game developers, academic research on the topic has primarily focused on new applications, with some research into empirical analysis. In this paper we relate theoretical work in information theory to the generation of content for games. We prove that there is a relationship between the Kolomogorov complexity of the most complex artifact a generator can produce, and the size of that generator’s possibility space. In doing so, we identify the limiting relationship between the knowledge encoded in a generator, the density of its output space, and the intricacy of the artifacts it produces. We relate our result to the experience of expert procedural generator designers, and illustrate it with some examples.
Decentralized PID controllers for multivariable systems

To improve the performance of decentralized PID controllers, a tuning method was proposed based on ultimate points calculation. First, Nyquist stability analysis and diagonal dominance were used to develop the equations describing the envelope of Gershgorin discs for diagonal elements in multivariable systems. The ultimate frequency and ultimate gain can be obtained from the intersections of the envelope of the Gershgorin discs and the negative part of the real axis. Thus, simple and decentralized PID controllers can be designed for multivariable systems using modified Z-N MZN formula or Tyreus-Luyben T-L formula. Simulations illustrate that the proposed system has smaller overshoots and better cross-coupling rejection, and also good performance robustness.
Research on Virtual 3D Remote Sensing Technology of Power Grid Station Based on 2D Vision

Aiming at the production safety management and control problems of substations, the digital twin 3D volume of substations is constructed based on 3D twinning technology, and the 2D/3D space fusion positioning perception technology based on existing multi-band surveillance cameras is studied. The automatic safety risk monitoring algorithm of common monitoring equipment, such as the automatic safety risk monitoring algorithm, realizes the high-precision perception analysis of the three-dimensional space of personnel/equipment in the substation, and can be applied to the safety management and control of personnel, equipment and perimeter of the substation, and improves the safety management level of the power grid.
Towards a Unified Language for Card Game Design

Card game creation is a powerful tool for game design. Using playing cards, game designers can rapidly prototype and iteratively playtest a game’s core mechanisms to explore alternatives and improve the gameplay. However, this process is time-consuming, imprecise and challenging to steer and focus. We aim to empower designers with solutions that automate game design processes. In particular, we study to what extent a unified game design language can offer theoretical foundations, systematic techniques and practical solutions. We propose a novel approach towards a solution that leverages the expressive power of playing cards. Initially focusing on well-known card games, we illustrate the steps for creating CardScript, a formal language and toolkit that supports game design processes. The approach also has the potential to impact a wider research area. When fully developed, a unified language with a common tool set can enable reuse, and eventually support joint research agendas. We start the discussion by highlighting perspectives that relate open challenges to opportunities for future collaboration.
Optimization-Aware Compiler-Level Event Profiling

Tracking specific events in a program’s execution, such as object allocation or lock acquisition, is at the heart of dynamic analysis. Despite the apparent simplicity of this task, quantifying these events is challenging due to the presence of compiler optimizations. Profiling perturbs the optimizations that the compiler would normally do—a profiled program usually behaves differently than the original one. In this article, we propose a novel technique for quantifying compiler-internal events in the optimized code, reducing the profiling perturbation on compiler optimizations. Our technique achieves this by instrumenting the program from within the compiler, and by delaying the instrumentation until the point in the compilation pipeline after which no subsequent optimizations can remove the events. We propose two different implementation strategies of our technique based on path-profiling, and a modification to the standard path-profiling algorithm that facilitates the use of the proposed strategies in a modern just-in-time (JIT) compiler. We use our technique to analyze the behaviour of the optimizations in Graal, a state-of-the-art compiler for the Java Virtual Machine, identifying the reasons behind a performance improvement of a specific optimization, and the causes behind an unexpected slowdown of another. Finally, our evaluation results show that the two proposed implementations result in a significantly lower execution-time overhead w.r. t. a naive implementation.
A Review of: “Cluster Randomised Trials, by R. J. Hayes and L. H. Moulton”

I should begin by noting that I have a conflict of interest as co-author of Donner and Klar (2000), a cluster randomization text written with Dr. Allan Donner. My conflict is of two parts. Firstly, I must admit to the obvious vested interest I have in publicizing Donner and Klar (2000). Second, Donner and Klar (2000) definitely benefited from insights gained by reading papers written by both Professor Hayes and Professor Moulton, with two of my favorites being Hayes and Bennett (1999) and Moulton and Zeger (1989). Cluster randomization trials are experiments in which clusters of individuals (e.g., families, schools, communities) are randomly assigned to different intervention groups. There has been a dramatic increase in the number of such trials since the 1980s. Cluster randomization is most frequently used in the evaluation of nontherapeutic interventions, including lifestyle modification and innovations in the provision of health care (Donner and Klar, 2000). The 15 chapters of Cluster Randomised Trials are grouped into four parts. Basic concepts are introduced in the three chapters of part A. Issues of study design and data analysis are respectively considered in part B and part C. The five chapters of part B (Chapters 4–8) and the four chapters of part C (Chapters 9–12) naturally comprise the bulk of the text. Ethical considerations (Chapter 13), data monitoring (Chapter 14), and reporting and interpretation (Chapter 15) are discussed in part D of the text. The key challenge of cluster randomization is that responses of subjects from the same cluster tend to be correlated. This intracluster correlation inflates the estimated variance of the observed intervention effect relative to a trial in which independent individuals are the unit of random assignment. Failure to account for variance inflation due to clustering may result in underpowered studies that yet are incorrectly claimed to have statistically significant results. The degree of variance inflation (i.e., the design effect) is a function of both cluster size and intracluster correlation, so that even very modest dependencies can dramatically inflate sample size, especially for trials where entire communities are being randomly assigned. Part A of the text provides a rationale for clustering of subject responses, explaining that it arises due to common environmental exposures and interactions among cluster members. Chapter 3 provides justification for cluster randomization, given the anticipated lower power of this design to detect intervention effects in comparison
A Convolution Method for Calculating the Trajectory Sensitivity Based on Measured Trajectory

Trajectory sensitivities provide a way for quantifying the variation of trajectory resulting from (small) changes of parameters and/or initial conditions. The trajectory sensitivity has been applied in power systems, such as for parameter identification, dynamic performance analysis and so on. The calculation of trajectory sensitivity based on the definition itself is usually time-consuming. It relies on the numerical integration, is liable to errors of model and parameters, and cannot provide the physical understanding about the sensitivity. A convolution method for calculating trajectory sensitivity is proposed in this paper, by use of typical system dynamic trajectories, which can be obtained by measurement. Based on the analytical characteristics of the measured trajectory in frequency domain, it is demonstrated that the trajectory sensitivity can be expressed as the linear composition or convolution of the step response and the impulse response. Power system example shows that the proposed method is simple, effective and feasible.
The association between uncertainty and mental health: a scoping review of the quantitative literature

Abstract Background The current moment is characterised by deep-rooted uncertainties, such as climate change and COVID-19. Uncertainty has been reported to be associated with negative mental health outcomes, such as stress and anxiety. However, no comprehensive review on the association between uncertainty and mental health exists. Aim The aim of the current scoping review was to systematically explore and describe the literature on the link between uncertainty and mental health. Methods A scoping review was undertaken following guidelines by Arksey and O’Malley (2005). Results One hundred and one papers addressing the association between uncertainty and mental health were identified. Most were cross-sectional studies (67%) conducted in the fields of medicine or nursing (59%), in high-income countries, among adult populations (74%), and in medical settings. Substantial heterogeneity was identified in the measurements of uncertainty and mental health. Most studies (79%) reported a positive association between uncertainty and mental health problems. Conclusions Research is needed in more diverse contexts and populations. More robust designs are required to provide insight into the directionality and strength of the association between uncertainty and mental health. Few studies reported how individuals coped with uncertainty. Future studies should address the identified gaps and investigate interventions to address uncertainty and its determinants.
Student perceptions of remote learning transitions in engineering disciplines during the COVID-19 pandemic: a cross-national study

ABSTRACT This study captures student perceptions of the effectiveness of remote learning and assessment in two associated engineering disciplines, mechanical and industrial, during the COVID-19 pandemic in a cross-national study. A structured questionnaire with 24 items on a 5-point Likert scale was used. Parallel and exploratory factor analyses identified three primary subscales. The links between student perceptions and assessment outcomes were also studied. There was a clear preference for face-to-face teaching, with the highest for laboratories. Remote live lectures were preferred over recorded. Although students found the switch to remote learning helpful, group work and communication were highlighted as concern areas. Mean scores on subscales indicate a low preference for remote learning (2.23), modest delivery effectiveness (3.05) and effective digital delivery tools (3.61). Gender effects were found significant on all subscales, along with significant interactions with university and year-group. Preference for remote delivery of design-based modules was significantly higher than others.