Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and Rasch Analysis of the 18-Item Health Resilience Profile (HRP)

Existing resilience measures have psychometric shortcomings, and there is no current gold-standard resilience measure. Previous work indicates adults enrolled in a health coaching program may benefit from a resilience measure that is tailored and contextualized to this sample. This two-part study aimed to develop and evaluate a resilience instrument focused on health behavior change in adults in a health coaching program. Two studies were conducted to (1) create a resilience instrument (Health Resilience Profile; HRP) specific to adults attempting health behavior change (n = 427; female = 83.8%; age = 44.5 ± 11.9 years) and to (2) optimize the instrument performance using Rasch analysis (n = 493; female = 62.1%; age = 49.8 ± 12.5 years). Study 1 identified two issues: (1) four unacceptable misfit items and (2) inappropriate rating scale functioning. Study 2 evaluated an improved instrument based on the outcome of study 1 resulting in one more misfit item, and unidimensionality was supported. The new four-category rating scale functioned well. The item-person map indicated that item difficulty distribution was well matched to participants’ resilience level, and items were free from measurement error. Finally, items did not show differential item functioning across age, sex, alcohol use, and obesity status. The 18-item HRP is optimized for adults in a health coaching program.
Modeling of ionospheric magnetic field perturbations induced by earthquakes

[1] The objective of this study is to present a simple coupled seismo-ionospheric model to account for magnetic field perturbations in response to geophysical phenomena such as Earthquakes or tsunamis. For this purpose, we include a simple gravity wave model in the two dimensional mid latitude ionosphere model SAMI2. Following an earthquake, the disturbances in the neutral atmosphere density and velocity associated with gravity waves propagate vertically upward up to ionospheric altitudes 150–350 km, where significant coupling between the neutral atmosphere and the ionosphere occurs. As a result, a rapid variation in the ionospheric plasma density and temperature is observed associated with the photoionization of the perturbed neutral density. This variation in the electron density leads in turn to a variation in the total electron content (TEC). Strong variations in the TEC are observed close to the epicenter which correspond to large plasma density perturbations in this region associated with the ion acoustic mode. The calculation of magnetic perturbations is based on a set of reduced MHD equations. These are solved numerically using the finite element code TOPO coupled with the mid latitude ionospheric model SAMI2. The coupling between the two codes accounts for the variations in neutral gas density and the collisional drag force between ions and neutrals. Two wave modes are considered: the shear Alfven mode and the compressional mode. The results of the magnetic field perturbations and of ions' velocity perturbations associated with the shear Alfven and the compressional modes are presented. Variations in the TEC values are also computed for the compressional mode by taking into account the density perturbations transverse to the magnetic field. The results representing TEC perturbations associated with the compressional mode show strong variations at high latitudes both as a function of time and latitude.
Self-Efficacy to Regulate Eating Behaviors Scale for Children: A Validation Study

Self-efficacy has a strong influence on children’s eating behavior. Feeling capable of regulating one’s eating behavior is especially relevant in situations of activation while facing temptations or experiencing negative emotions. Despite the relevance, there is no validated measure to assess children’s self-efficacy to regulate eating behaviors in these domains. The present study examines the psychometric properties of the Self-Efficacy to Regulate Eating Behaviors Scale for Children based on a sample of 724 elementary school children in Portugal. The sample was split randomly into two groups, and a principal component analysis with Group 1 and a confirmatory factor analysis with Group 2 were carried out. The scale comprises two distinct but related factors—self-efficacy to regulate eating behaviors in activation and temptation situations and self-efficacy to regulate eating behaviors in negative emotional situations. Moreover, self-efficacy to regulate eating behaviors was positively and statistically related to self-regulation processes toward healthy eating, declarative knowledge about healthy eating, and attitudes and perceptions toward healthy eating. The present study provides preliminary evidence that the Self-Efficacy to Regulate Eating Behaviors Scale for Children is valid and reliable for evaluating children’s self-efficacy in regulating their eating behaviors.
Physicochemical and Sensory Properties and Shelf Life of Block-Type Processed Cheeses Fortified with Date Seeds (Phoenix dactylifera L.) as a Functional Food

Processed cheese has rapidly been established as a commercial product in recent years. A new ingredient, a byproduct from date fruit seed (DFS), was obtained and tested as a fortified fiber from food industrial waste in block-type processed cheese. This is the first inclusive investigation to report such a test. Different concentrations of DFS (0%, 5%, 10%, 15%, and 20%) were added to block-type processed cheese as a partial substitution for butter. The current investigation was undertaken to estimate the impact of the partial substitution of butter by DFS and its effect on the product’s quality in terms of its shelf life and physicochemical, microstructure, color, and sensory properties. Quality was assessed over a 150-day storage period. The results indicate that adding DFS to cheese increased its nutritional value due to the addition of fiber. Additionally, the texture profile of cheese was decreased in terms of hardness, adhesion, springiness, and cohesiveness. The overall structure of cheeses became less compact and had a more open cheese network, which increased with increasing DFS% and duration of storage. Moreover, DFS exhibited the darkest color with increasing ratios of supplementary DFS and duration of storage. Based on the results found in the present investigation, it was concluded that an acceptable quality of block-type processed cheese could be achieved using DFS fiber at 5% and 10% levels of fortification.
NASA/National Space Science Data Center trapped radiation models

The National Space Science Data Center (NSSDC) trapped radiation models calculate the integral and differential electron and proton flux for given values of particle energy E, drift shell parameter L, and magnetic field strength normalized to the equatorial/minimum value on the field line B/BQ for either solar maximum or solar minimum conditions. The most recent versions of the series of models, which have been developed and continuously improved over several decades by Vette and co-workers at NSSDC, are AE-8 for electrons and AP-8 for protons. The paper provides a brief history of the modeling efforts at NSSDC and discusses some of the problems encountered when applying the models at low altitudes. Recommendations are made and discussed about the correct use of the trapped particle models in conjunction with geomagnetic field models. Specifically, the importance of using the correct dipole moment and the correct #0 value (i.e., obtained by field line tracing) is illustrated.
Growth Stages and Inter-Species Gut Microbiota Composition and Function in Captive Red Deer (Cervus elaphus alxaicus) and Blue Sheep (Pseudois nayaur)

Simple Summary Gut microbiota play a significant role in the diet digestion and health of the host. Many zoos provide research sites for biological scientists to reintroduce animals, especially those facing extinction. Therefore, to prevent the extinction of wild animals, captive wild animals have become one of the ways to protect threatened taxa. Monitoring the structure and function of the gut microbiota of captive animals can help elucidate whether animals have adapted to their artificial environment, which is one of the key issues in wildlife conservation. This study investigated the gut microbiota of blue sheep and red deer at different growth stages and inter-species. The result shows gut microbiota of blue sheep and red deer will change to some extent in different growth stages, but the dominant flora remains stable. In blue sheep and red deer, the gut microbiota differ significantly between species. In addition, several potentially pathogenic microbial communities were identified based on the current findings. The study highlights key gut microbiota across species and ages. Abstract Blue sheep and red deer, second-class key protected animals in China, are sympatric species with a high degree of overlap of food resources in the Helan Mountains, China. Previous studies with blue sheep and red deer in nature have shown that their physiology is closely related to their gut microbiota. However, growth stages and changes occurring in these species in captivity are still unknown. Thus, 16S rRNA gene sequencing was used to explore diversity, composition and function of the gut microbiota in these two animal species. The diversity and structure of the gut microbiota in captive blue sheep and red deer changed at different growth stages, but the dominant microbiota phyla in the gut microbiota remained stable, which was composed of the phyla Firmicutes, Bacteroidetes and Verrucomicrobia. Moreover, gut microbiota diversity in juvenile blue sheep and red deer was low, with the potential for further colonization. Functional predictions showed differences such as red deer transcription being enriched in adults, and blue sheep adults having a higher cell wall/membrane/envelope biogenesis than juveniles. Microbial changes between blue sheep and red deer at different growth stages and between species mainly depend on the abundance of the microbiota, rather than the increase and absence of the bacterial taxa.
LGBTQIA+ Adolescents’ Perceptions of Gender Tailoring and Portrayal in a Virtual-Reality-Based Alcohol-Prevention Tool: A Qualitative Interview Study and Thematic Analysis

Gender-sensitive interventions in alcohol-prevention that target adolescents often lead to binary tailoring for girls and boys. However, increased societal and legal recognition of sexual and gender minorities as well as research with this age group demand a broader understanding of gender. Therefore, the present study addresses the question of how interventions should be further developed to include sexual and gender diversity by exploring LGBTQIA+ adolescents’ perceptions of gender portrayal and gender-tailoring using Virtual LimitLab—a virtual-reality simulation for training refusal skills under peer pressure to consume alcohol. Qualitative interviews with 16 LGBTQIA+ adolescents were conducted after individual simulation testing. Using a thematic analysis with reflexive orientation, four themes were identified: Statements on relevance of gender, opinions on tailoring- and flirting options, and opinions on characters. Participants called for greater diversity representation among the characters, regarding gender identity and sexual orientation, as well as for representing, e.g., racialised peers. Moreover, participants suggested expanding the simulation’s flirting options by adding bisexual and aromantic/asexual options. Divergent views on the relevance of gender and wishes for tailoring options reflected the participant group’s heterogeneity. Based on these findings, future gender-sensitive interventions should conceptualise gender in a complex and multidimensional manner that intersects with further diversity categories.
Self-energy and Fermi surface of the two-dimensional Hubbard model

We present an exact diagonalization study of the self-energy of the two-dimensional Hubbard model. To increase the range of available cluster sizes we use a corrected t-J model to compute approximate Greens functions for the Hubbard model. This allows to obtain spectra for clusters with 18 and 20 sites. The self-energy has several `bands' of poles with strong dispersion and extended incoherent continua with k-dependent intensity. We fit the self-energy by a minimal model and use this to extrapolate the cluster results to the infinite lattice. The resulting Fermi surface shows a transition from hole pockets in the underdoped regime to a large Fermi surface in the overdoped regime. We demonstrate that hole pockets can be completely consistent with the Luttinger theorem. Introduction of next-nearest neighbor hopping changes the self-energy stronlgy and the spectral function with nonvanishing next-nearest-neighbor hopping in the underdoped region is in good agreement with angle resolved photoelectron spectroscopy.
Distorted Innovation: Does the Market Get the Direction of Technology Right?

In the presence of markup differences, externalities, and other social effects, the direction of innovation can be systematically distorted. I build a simple model of endogenous technology to study distortions in the direction of innovation. Empirical findings across a number of different areas are consistent with this framework's predictions. I use data from several studies to estimate the framework's key parameters and combine them with rough estimates of differential externalities and markups to provide suggestive evidence that innovation distortions can be substantial in the context of industrial automation, health care, and energy, and that correcting them could have sizable welfare benefits.
Artificial Intelligence-Assisted Transcriptomic Analysis to Advance Cancer Immunotherapy

The emergence of immunotherapy has dramatically changed the cancer treatment paradigm and generated tremendous promise in precision medicine. However, cancer immunotherapy is greatly limited by its low response rates and immune-related adverse events. Transcriptomics technology is a promising tool for deciphering the molecular underpinnings of immunotherapy response and therapeutic toxicity. In particular, applying single-cell RNA-seq (scRNA-seq) has deepened our understanding of tumor heterogeneity and the microenvironment, providing powerful help for developing new immunotherapy strategies. Artificial intelligence (AI) technology in transcriptome analysis meets the need for efficient handling and robust results. Specifically, it further extends the application scope of transcriptomic technologies in cancer research. AI-assisted transcriptomic analysis has performed well in exploring the underlying mechanisms of drug resistance and immunotherapy toxicity and predicting therapeutic response, with profound significance in cancer treatment. In this review, we summarized emerging AI-assisted transcriptomic technologies. We then highlighted new insights into cancer immunotherapy based on AI-assisted transcriptomic analysis, focusing on tumor heterogeneity, the tumor microenvironment, immune-related adverse event pathogenesis, drug resistance, and new target discovery. This review summarizes solid evidence for immunotherapy research, which might help the cancer research community overcome the challenges faced by immunotherapy.
Severe hypercalcemia caused by repeated mineral oil injections: a case report

SUMMARY Hypercalcemia is a frequent condition in clinical practice and when the most frequent causes are excluded, etiological diagnosis can be challenging. A rare cause of PTH-independent hypercalcemia is described in the present case report. A male adult with a history of androgenic-anabolic steroids abuse, and injection of mineral oil and oily veterinary compound containing vitamins A, D and E into muscles for local hypertrophy presented with hypercalcemia, nephrocalcinosis, and end-stage renal disease. On physical examination, the presence of calcified subcutaneous nodules and calcification of musculature previously infused with oily substances drew attention. Laboratory tests confirmed hypercalcemia of 12.62 mg/L, low levels of PTH (10 pg/mL), hyperphosphatemia (6.0 mg/dL), 25(OH)D of 23.3 ng/mL, and elevated 1,25(OH)2D (138 pg/mL). Imaging exams showed diffuse calcification of muscle tissue, subcutaneous tissue, and organs such as the heart, lung, and kidneys. The patient was diagnosed with PTH-independent hypercalcemia secondary to foreign body reaction in areas of oil injection. The patient underwent treatment with hydrocortisone for 10 days, single dose zoledronic acid and hemodialysis. He evolved with serum calcium levels of 10.4 mg/dL and phosphorus of 7.1 mg/dL. In addition, sertraline and quetiapine were prescribed to control body dysmorphic disorder. The medical community should become aware of new causes of hypercalcemia as secondary to oil injection since this should become increasingly frequent due to the regularity with which such procedures have been performed.
Epiglottis Cartilage, Costal Cartilage, and Intervertebral Disc Cartilage as Alternative Materials in the Postmortem Diagnosis of Methanol Poisoning

Alternative materials for postmortem diagnosis in the case of fatal poisonings are much needed when standard materials, such as blood and urine, are unavailable. The study presents a case of fatal mass methanol intoxication resulting from industrial alcohol consumption. The study aimed to determine methanol and formic acid concentrations in epiglottis cartilage, costal cartilage, and intervertebral disc cartilage and to analyze the correlation between their concentrations in cartilage tissues and the femoral blood. Methanol and formic acid concentrations in samples collected from 17 individuals (n = 17) were estimated using gas chromatography with flame ionization detection (GC-FID). Methanol concentration in the costal cartilage correlated with its concentration in the femoral blood (r = 0.871). Similar correlations were found for epiglottis cartilage (r = 0.822) and intervertebral disc cartilage (r = 0.892). Formic acid concentration in the blood correlated only with its concentration in urine (r = 0.784) and the epiglottis (r = 0.538). Cartilage tissue could serve as an alternative material for methanol analyses in postmortem studies. Formic acid, a methanol metabolite, does not meet the requirements for its presence determination in cartilage tissues.
Ab Initio Computational Screening and Performance Assessment of van der Waals and Semimetallic Contacts to Monolayer WSe2 P-Type Field-Effect Transistors

Recent technology development of logic devices based on 2-D semiconductors such as MoS2, WS2, and WSe2 has triggered great excitement, paving the way to practical applications. Making low-resistance p-type contacts to 2-D semiconductors remains a critical challenge. The key to addressing this challenge is to find high-work function metallic materials which also introduce minimal metal-induced gap states (MIGSs) at the metal/semiconductor interface. In this work, we perform a systematic computational screening of novel metallic materials and their heterojunctions with monolayer WSe2 based on ab initio density functional theory and quantum device simulations. Two contact strategies, van der Waals (vdW) metallic contact and bulk semimetallic contact, are identified as promising solutions to achieving Schottky-barrier-free and low-contact-resistance p-type contacts for WSe2 p-type field-effect transistor (pFETs). Good candidates of p-type contact materials are found based on our screening criteria, including 1H-NbS2, 1H-TaS2, and 1T-TiS2 in the vdW metal category, as well as Co3Sn2S2 and TaP in the bulk semimetal category. Simulations of these new p-type contact materials suggest reduced MIGS, less Fermi-level pinning effect, negligible Schottky barrier height and small contact resistance (down to $20~\Omega \mu \text{m}$ ).
Serum Ferritin Levels and Other Associated Parameters with Diabetes Mellitus in Adult Patients Suffering from Beta Thalassemia Major

Background Although beta thalassemia major (BTM) patients are properly treated with blood transfusions in accompany with iron chelation therapy, they suffer from complications, such as diabetes mellitus (DM). Purpose The purpose was to detect the critical serum ferritin level and other parameters correlated with DM among adult BTM patients. Also, it was to study whether each of these parameters is associated with a certain period of age. Patients and Methods This study included 200 adult BTM patients. A cross-sectional study was carried out. Patients clinical and laboratory variables, such as ferritin levels, and fasting blood glucose (FBS) were extracted from medical records at Zagazig University Hospital, Egypt. Liver and cardiac iron contents were assessed using MRI T2* methods. Statistical analysis was performed using IBM SPSS V26.0 software package. Results The overall frequency of DM over the total sample equals 6.5%. There were no impaired fasting glucose (IFG) in the medical records. Statistical significance between serum ferritin and DM was (P = 0.014). The serum ferritin 2500 ng/mL with age group (27–<32) years-old were risk factors. The distributions of DM according to BMI were (3.5%) of class overweight. Significant association between DM and BMI was (r = 0.357, P < 0.001). Liver MRI T2* has significant correlation with serum ferritin, but cardiac MRI T2* was poorly correlated. Association between liver and cardiac MRI T2* was not found. Conclusion Age group (27–<32) years-old and ferritin >2500 ng/mL should be properly treated immediately. The serum ferritin and BMI of class “overweight” were risk factors for DM. Factors such as diet should be followed. Serum ferritin can be used for estimating liver iron content for economic factors. But cardiac MRI T2* must be performed for evaluating cardiac iron accurately.
Fast Differentiable Transient Rendering for Non-Line-of-Sight Reconstruction

Research into non-line-of-sight imaging problems has gained momentum in recent years motivated by intriguing prospective applications in e.g. medicine and autonomous driving. While transient image formation is well understood and there exist various reconstruction approaches for non-line-of-sight scenes that combine efficient forward renderers with optimization schemes, those approaches suffer from runtimes in the order of hours even for moderately sized scenes. Furthermore, the ill-posedness of the inverse problem often leads to instabilities in the optimization.Inspired by the latest advances in direct-line-of-sight inverse rendering that have led to stunning results for reconstructing scene geometry and appearance, we present a fast differentiable transient renderer that accelerates the inverse rendering runtime to minutes on consumer hardware, making it possible to apply inverse transient imaging on a wider range of tasks and in more time-critical scenarios. We demonstrate its effectiveness on a series of applications using various datasets and show that it can be used for self-supervised learning.