Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Evolutionary Programming to Add Deterministic and Probabilistic Skill to Spatial Model Forecasts

Evolutionary programming is applied to the postpocessing of ensemble forecasts of temperature on a spatial domain. These forecasts are obtained from the 11-member Reforecast V2 ensemble over the region from 24°–53°N to 125°–66°W for the period 1 January 1985–14 May 2011. The evolution is based upon a static ecosystem model that holds constant the number of individuals (algorithms), using a fixed rate of introduction of new algorithms and removal of existing algorithms. Each algorithm adheres to a specific underlying genetic architecture, and the selection pressure on the “species” is according to deterministic performance (root-mean-square error) on a training dataset. On a 2325-case, independent test dataset, the method improved root-mean-square error and ranked probability score relative to the Reforecast ensemble by 0.31°F (8.7%) and 3.3%, respectively, across the domain, with 96% of the grid points showing simultaneous improvements in both measures. The use of input information by the evolutionary programming algorithms varied by region; while the algorithm forecasts at all locations are fundamentally tied to the Reforecast ensemble forecast, northeastern locations found snow cover to be the next most useful input, whereas southwestern locations preferentially employed precipitable water. An adaptive form of the approach, developed to be readily implemented into operations, is tested in the absence of improving inputs but is found to only slightly degrade performance (1.2% in root-mean-square error and 0.6% in ranked probability skill score). A number of future extensions are discussed.
Early period intensive care follow-up after liver transplantation in children: a single center experience.

BACKGROUND Liver transplantation (LT) is a well-established, life-saving treatment for children with irreversible acute and chronic liver failure (LF). We aimed to evaluate the factors associated with morbidity and mortality in the early period of LT in children by reviewing our pediatric intensive care unit (PICU) experience. METHODS We reviewed children`s medical records followed in the PICU after LT between May 2015-August 2021, including demographic parameters, indications for LT, operative variables, respiratory and circulatory support requirements, LT-related complications and survival. RESULTS During this period, 40 pediatric patients who underwent LT were evaluated. LT was performed in 35 (87.5%) cases of chronic liver disease and 5 (12.5%) cases of acute liver failure. Twenty-four patients had chronic liver failure due to cholestatic liver disease. The patients` Pediatric Risk of Mortality (PRISM) III score was 18.82±SD (2-58) at PICU admission. 1-year survival was 87.5%, and overall survival was 85%. Younger age, low body weight, preoperative pediatric end-stage liver disease (PELD), and model for end-stage liver disease (MELD) values of 20 and higher were important risk factors for unfavorable outcomes after living donor liver transplantation (LDLT). These risk factors are both associated with technically more challenging vascular and bile duct reconstruction and higher complication rates, and increased mortality during the early period after LT. CONCLUSIONS The early period of optimum PICU management in pediatric LT recipients is crucial for successful outcomes, which is also related to the patients` characteristics, disease severity scores, and surgical procedures.
Serum Leptin Level is Positively Correlated with Aortic Stiffness in Patients with Type 2 Diabetes Mellitus.

BACKGROUND The global number of people living with diabetes mellitus (DM) continues to grow. Obesity, smoking, hypercholesterolemia, and hypertension are independently correlated with the risk of cardiovascular disease (CVD) in diabetic patients regardless of differences in race or ethnicity. We aimed to investigate the relationship between serum leptin levels and aortic stiffness in patients with type 2 DM to identify cardiovascular risk at the early stage. METHODS A total of 128 diabetic patients were enrolled after screening for eligibility at a medical center in Eastern Taiwan. Aortic stiffness was defined as having a carotid-femoral pulse wave velocity (cfPWV) of >10 m/s using applanation tonometry. Fasting serum levels of leptin and other associated biomarkers were determined by enzyme immunoassay or biochemical analyses. RESULTS Forty-six diabetic patients with a cfPWV of >10 m/s were included in the aortic stiffness group. Compared with the control group (n = 82), our aortic stiffness group was significantly older (p = 0.019) and had higher body fat mass (p = 0.002), systolic blood pressure (SBP) (p < 0.001), serum triglyceride (p = 0.02), and serum leptin (p < 0.001). Aortic stiffness was also associated with insulin resistance (p = 0.026) and poorer blood sugar control (higher fasting glucose (p = 0.044) and glycated hemoglobin (HbA1c) (p = 0.049)). In the multivariable linear regression analyses examining the correlations between aortic stiffness and clinical variables, we found that age (β = 0.291; p < 0.001), SBP (β = 0.176; p = 0.033), logarithmically transformed urinary albumin-creatinine ratio (β = 0.256; p = 0.002), and serum leptin levels (β = 0.244; p = 0.002) were independently associated with cfPWV values. The analyses showed that only leptin was correlated with a higher probability of aortic stiffness (odds ratio: 1.055, 95% confidence interval: 1.005-1.107, p = 0.031). CONCLUSIONS The results suggested that serum leptin is positively associated with aortic stiffness in patients with type 2 DM.
The Notion of Truth through Dialetheism, Deflationism and Fictionalism

In the present work three different areas about the truth predicate coexist: the semantic area, whose focus is on theories dealing with the solution to the semantic paradoxes that involve the truth predicate; the ontological area, which covers the theories investigating the nature of truth; and the area of discourse, in which the focus is on those theories that analyse how the discourse about the truth predicate has to be understood. The aim of this work is to analyze the consequences arising from certain specific ways in which these areas can interact with each other. The first three chapters expose the main features of the theories corresponding to the three areas about the truth predicate, respectively dialetheism, deflationism and fictionalism. The possible combinations between those theories are the focus of the two following chapters. Finally, a new attempt to account for the liar paradox is provided.
Antimicrobial therapies for chronic pain (part 1): analgesic mechanisms

There is increasing evidence that the relationship between chronic pain and infections is complex and intertwined. Bacterial and viral infections can cause pain through numerous mechanisms such as direct tissue damage and inflammation, the induction of excessive immunologic activity, and the development of peripheral or central sensitization. Treating infections might relieve pain by attenuating these processes, but a growing body of literature suggests that some antimicrobial therapies confer analgesic effects, including for nociceptive and neuropathic pain symptoms, and affective components of pain. The analgesic mechanisms of antimicrobials are indirect, but might be conceptualized into two broad categories: 1) the reduction of the infectious burden and associated pro-inflammatory processes; and 2) the inhibition of signaling processes (e.g., enzymatic and cytokine activity) necessary for nociception and maladaptive neuroplastic changes via off-target effects (unintended binding sites). For the former, there is evidence that symptoms of chronic low back pain (when associated with Modic type 1 changes), irritable bowel syndrome, inflammatory bowel disease, chronic pelvic pain, and functional dyspepsia might be improved after antibiotic treatment, though significant questions remain regarding specific regimens and dose, and which subpopulations are most likely to benefit. For the latter, there is evidence that several antimicrobial classes and medications exert analgesic effects independent of their reduction of infectious burden, and these include cephalosporins, ribavirin, chloroquine derivatives, rapalogues, minocycline, dapsone, and piscidin-1. This article aims to comprehensively review the existing literature for antimicrobial agents that have demonstrated analgesic efficacy in preclinical or clinical studies.
The Use of Machine Learning for Image Analysis Artificial Intelligence in Clinical Microbiology

The growing transition to digital microbiology in clinical laboratories creates the opportunity to interpret images using software. Software analysis tools can be designed to use human-curated knowledge and expert rules, but more novel artificial intelligence (AI) approaches such as machine learning (ML) are being integrated into clinical microbiology practice. ABSTRACT The growing transition to digital microbiology in clinical laboratories creates the opportunity to interpret images using software. Software analysis tools can be designed to use human-curated knowledge and expert rules, but more novel artificial intelligence (AI) approaches such as machine learning (ML) are being integrated into clinical microbiology practice. These image analysis AI (IAAI) tools are beginning to penetrate routine clinical microbiology practice, and their scope and impact on routine clinical microbiology practice will continue to grow. This review separates the IAAI applications into 2 broad classification categories: (i) rare event detection/classification or (ii) score-based/categorical classification. Rare event detection can be used for screening purposes or for final identification of a microbe including microscopic detection of mycobacteria in a primary specimen, detection of bacterial colonies growing on nutrient agar, or detection of parasites in a stool preparation or blood smear. Score-based image analysis can be applied to a scoring system that classifies images in toto as its output interpretation and examples include application of the Nugent score for diagnosing bacterial vaginosis and interpretation of urine cultures. The benefits, challenges, development, and implementation strategies of IAAI tools are explored. In conclusion, IAAI is beginning to impact the routine practice of clinical microbiology, and its use can enhance the efficiency and quality of clinical microbiology practice. Although the future of IAAI is promising, currently IAAI only augments human effort and is not a replacement for human expertise.
Within- and between-host dynamics of producer and non-producer pathogens

Abstract Abstract For infections to be maintained in a population, pathogens must compete to colonize hosts and transmit between them. We use an experimental approach to investigate within-and-between host dynamics using the pathogen Pseudomonas aeruginosa and the animal host Caenorhabditis elegans. Within-host interactions can involve the production of goods that are beneficial to all pathogens in the local environment but susceptible to exploitation by non-producers. We exposed the nematode host to ‘producer’ and two ‘non-producer’ bacterial strains (specifically for siderophore production and quorum sensing), in single infections and coinfections, to investigate within-host colonization. Subsequently, we introduced infected nematodes to pathogen-naive populations to allow natural transmission between hosts. We find that producer pathogens are consistently better at colonizing hosts and transmitting between them than non-producers during coinfection and single infection. Non-producers were poor at colonizing hosts and between-host transmission, even when coinfecting with producers. Understanding pathogen dynamics across these multiple levels will ultimately help us predict and control the spread of infections, as well as contribute to explanations for the persistence of cooperative genotypes in natural populations.
Geometrically Flexible and Efficient Flow Analysis of High Speed Vehicles Via Domain Decomposition, Part 1: Unstructured-Grid Solver for High Speed Flows

The ability to solve the equations governing the hypersonic turbulent flow of a real gas on unstructured grids using a spatially-elliptic, 2nd-order accurate, cell-centered, finite-volume method has been recently implemented in the VULCAN-CFD code. This paper describes the key numerical methods and techniques that were found to be required to robustly obtain accurate solutions to hypersonic flows on non-hex-dominant unstructured grids. The methods and techniques described include: an augmented stencil, weighted linear least squares, cell-average gradient method, a robust multidimensional cellaverage gradient-limiter process that is consistent with the augmented stencil of the cell-average gradient method and a cell-face gradient method that contains a cell skewness sensitive damping term derived using hyperbolic diffusion based concepts. A data-parallel matrix-based symmetric Gauss-Seidel pointimplicit scheme, used to solve the governing equations, is described and shown to be more robust and efficient than a matrix-free alternative. In addition, a y+ adaptive turbulent wall boundary condition methodology is presented. This boundary condition methodology is designed to automatically switch between a solve-to-the-wall and a wall-matching-function boundary condition based on the local y+ of the 1st cell center off the wall. The aforementioned methods and techniques are then applied to a series of hypersonic and supersonic turbulent flat plate unit tests to examine the efficiency, robustness and convergence behavior of the implicit scheme and to determine the ability of the solve-to-the-wall and y+ adaptive turbulent wall boundary conditions to reproduce the turbulent law-of-the-wall. Finally, the thermally perfect, chemically frozen, Mach 7.8 turbulent flow of air through a scramjet engine flowpath is computed and compared with experimental data to demonstrate the robustness, accuracy and convergence behavior of the unstructured-grid solver for a realistic 3-D geometry on a non-hex-dominant grid.
Translation and population-based validation of the Arabic version of the brief resilience scale

Abstract Purpose This study aimed to translate the Brief Resilience Scale (BRS) into the Arabic language and to assess the reliability and validity of the translated version of the scale among a sample of the Saudi population. Material and methods The internal consistency and test–retest reliability of the translated BRS were analyzed. Factor analyses were conducted to examine the factor structure of the scale. Convergent validity was measured by correlating BRS scores with those from the Hospital Anxiety and Depression Scale (HADS), Satisfaction with Life Scale (SWLS), Perceived Stress Scale (PSS), and WHO-5 Well-Being Index (WHO-5). Results A total of 1072 participants were included in the analysis. The score of the Arabic version showed excellent internal consistency (alpha = 0.98) and good test–retest reliability (ICC = 0.88, 95% CI: 0.82–0.92, p ≤ 0.0001). The results of factor analyses showed that the two-factor model is a good model fit with [CMIN/DF = 9.105; GFI = 0.97; CFI = 0.99; RMSEA = 0.09]. The BRS scores were negatively correlated with levels of anxiety (r = −0.61), depression (r = −0.6), and stress (r = −0.53) and positively correlated with levels of satisfaction with life (r = 0.44) and mental well-being (r = 0.58). Conclusions Our findings firmly support the reliability and validity of the Arabic version of the BRS to be used in research and clinical settings with the Saudi population. KEY MESSAGES Resilience, defined as the ability to bounce back from stressors, is a psychological factor that may buffer the harmful effects of health-related stress. The Arabic version of the BRS demonstrates strong reliability and validity for assessing resilience among the Arabic-speaking Saudi population. The scale will provide the rehabilitation field in the Arabic-speaking population and other health communities with a tool for research and clinical practice. The scale will also guide the development of strategic plans and psychological protective and rehabilitative intervention protocols for those in health-related stressful circumstances.
A functional partial differential equation arising in a cell growth model with dispersion

In this paper we solve an initial‐boundary value problem that involves a pde with a nonlocal term. The problem comes from a cell division model where the growth is assumed to be stochastic. The deterministic version of this problem yields a first‐order pde; the stochastic version yields a second‐order parabolic pde. There are no general methods for solving such problems even for the simplest cases owing to the nonlocal term. Although a solution method was devised for the simplest version of the first‐order case, the analysis does not readily extend to the second‐order case. We develop a method for solving the second‐order case and obtain the exact solution in a form that allows us to study the long time asymptotic behaviour of solutions and the impact of the dispersion term. We establish the existence of a large time attracting solution towards which solutions converge exponentially in time. The dispersion term does not appear in the exponential rate of convergence.
AlvaBuilder: A Software for De Novo Molecular Design.

AlvaBuilder is a software tool for de novo molecular design and can be used to generate novel molecules having desirable characteristics. Such characteristics can be defined using a simple step by step graphical interface, and they can be based on molecular descriptors, on predictions of QSAR/QSPR models, and on matching molecular fragments or used to design compounds similar to a given one. The molecules generated are always syntactically valid since they are composed by combining fragments of molecules taken from a training data set chosen by the user. In this paper, we demonstrate how the software can be used to design new compounds for a defined case study. AlvaBuilder is available at https://www.alvascience. com/alvabuilder/.
RFID antenna design for circular polarization in UHF band

A miniature half cross dipole antenna for defense and aerospace RFID applications in UHF band is presented. The dipole printed line arms are half crossed shape on top of dielectric substrate backed by reactive impedance surface. The antenna fed by a coaxial cable at the gap separating the dipole arms. Our design is intended to work at 2.42 GHz for RFID readers. The radiation pattern obtained has HPBW of 112, return loss of 22.24 dB and 90 MHz bandwidth.
‘Life became slow down’: A descriptive qualitative study of the experiences of cancer-related fatigue amongst people with advanced lung cancer

Background: Cancer-related fatigue is a complex multidimensional concept. However, little is known about the experience of cancer-related fatigue in people with advanced lung cancer. How they emotionally react to and cope with the experience of cancer-related fatigue according to cultural influences has not been extensively explored. Aim: To explore the experience of cancer-related fatigue, its impacts and emotional reactions to and coping strategies for cancer-related fatigue amongst people with advanced lung cancer in China. Design: This was a cross-sectional, descriptive qualitative study with face-to-face semi-structured interviews. Data were analysed using content analysis. Setting/participants: Twenty-one people with advanced lung cancer who experienced cancer-related fatigue were recruited in a hospital setting. Results: Four themes were identified: multifaceted experiences of cancer-related fatigue, impacts of cancer-related fatigue, negative perceptions of cancer-related fatigue and avoiding cancer-related fatigue. The multifaceted experience of cancer-related fatigue had physical, psychological and social impacts along the cancer trajectory. Informants regarded it as a sign of a ‘bad ending’, searched for root causes and had negative attitudes towards role changes. Avoiding coping strategies included not discussing cancer-related fatigue, refusing encouragement and support, hiding feelings, withdrawing from social life and attempting to control cancer-related fatigue. Conclusion: The findings provide insights into the lack of flexibility of people with advanced lung cancer to adapt to the multidimensional experience of cancer-related fatigue. The reactions and coping towards cancer-related fatigue are profoundly influenced by Chinese culture. Developing psychological interventions based on the cultural background are highly recommended to cultivate the ability to cope flexibly with stressful events and live a meaningful cancer life.
Valgus Stress Radiograph Can Predict Alignment Change of Medial Mobile‐Bearing Unicompartmental Knee Arthroplasty

Finding reliable tools to predict alignment change after medial mobile‐bearing unicompartmental knee arthroplasty (UKA) can help surgeons avoid under‐ or over‐correction. This prospective study aimed to investigate whether the parameters related to medial collateral ligament tension on valgus stress radiograph can predict the alignment change of medial mobile‐bearing UKA and establish a prediction model.
Application of EBMT, MASCC, and qSOFA Scores to Predict Complicated Febrile Neutropenia and Mortality in Autologous Stem Cell Transplant Recipients.

BACKGROUND AND OBJECTIVES Three different scores were addressed as predictors of outcomes in autologous stem cell transplant (Auto SCT): one was calculated by pretransplant characteristics (European Society for Blood and Marrow Transplantation [EBMT] risk score), and two were calculated at the onset of febrile neutropenia (Multinational Association for Supportive Care in Cancer [MASCC] and Quick Sequential Organ Failure Assessment [qSOFA]). We considered bloodstream infection (BSI), carbapenem prescription, admission to the intensive care unit (ICU), and mortality as outcomes. PATIENTS A total of 309 patients with a median age of 54 years were enrolled. RESULTS Patients with EBMT score ≥4 (EBMT 4+) had higher ICU rates (14% vs. 4%; p < 0.01) and more carbapenem prescriptions (61% vs. 38%; p < 0.001) than those with EBMT score <4. MASCC <21 points (MASCC HR) was associated with carbapenem prescription (59% vs. 44%; p = 0.013), ICU (19% vs. 3%; p < 0.01), and death (4% vs. 0; p = 0.014). Patients with at least two points by qSOFA (qSOFA 2+) had more frequent BSI (55% vs. 22%; p = 0.03), ICU admissions (73% vs. 7; p < 0.01), and death (18% vs. 0.7, p = 0.02). EBMT 4+ and MASCC HR achieved the best sensitivities for ICU. For death, the best sensitivity was obtained with MASCC. CONCLUSION In conclusion, risk scores for Auto SCT showed an association with outcomes and had different performances when combined or used alone. Therefore, risk scores for Auto SCT are useful in supportive care and clinical surveillance in stem cell transplant recipients.