Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of obesity on quality of life, psychological distress, and coping on patients with colon cancer.

BACKGROUND Despite the causal relationship between obesity and colon cancer being firmly established the effect of obesity on the course of cancer calls for further elucidation. The objective was to assess differences in clinical-pathological and psychosocial variables between obese and non-obese individuals with colon cancer. PATIENTS AND METHODS Prospective, multicentric, observational study conducted from 2015-2018. The sample comprised patients with stage II-III, resected colon cancer about to initiate adjuvant chemotherapy with fluoropyrimidine in monotherapy or associated with oxaliplatin and grouped into non-obese (BMI <30kg/m2 ) or obese (≥30kg/m2 ). Subjects completed questionnaires appraising quality of life (EORTC-QLQ-C30), coping (M-MAC), psychological distress (BSI-18), perceived social support (MSPSS), personality (BFI-10), and pain (BPI). Toxicity, chemotherapy compliance, 12-month recurrence and mortality rate data were recorded. RESULTS Seventy-nine of the 402 individuals recruited (19.7%) were obese. Obese subjects exhibited more comorbidities (≥2 comorbidities, 46.8% vs 30.3%, p=0.001) and expressed feeling slightly more postoperative pain (small size-effect). There was more depression, greater helplessness, less perceived social support from friends, and greater extraversion among the obese versus non-obese subjects (all p<0.04). The non-obese group treated with fluoropyrimidine and oxaliplatin suffered more grade 3-4 hematological toxicity (p=0.035), whereas the obese had higher rates of treatment withdrawal (17.7% vs 7.7%, p=0.033) and more recurrences (10.1% vs 3.7%, p=0.025). No differences in sociodemographic, quality of life, or 12-month survival variables were detected. CONCLUSION Obesity appears to affect how people confront cancer, as well as their tolerance to oncological treatment and relapse. IMPLICATIONS FOR PRACTICE Obesity is a causal factor and affects prognosis in colorectal cancer. Obese patients displayed more comorbidities, more pain following cancer surgery, worse coping, more depression, and perceived less social support than the non-obese. Severe hematological toxicity was more frequent among non-obese subjects, whereas withdrawal from adjuvant chemotherapy rates was higher in the obese cohort and during follow-up, they presented greater 12-month recurrence rates. With the growing and maintained increase of obesity and cancers associated with it, including colorectal cancer, we must adapt our approach to these more fragile cases who have a worse prognosis, to improve outcomes.
Hungarian validation of the Buss–Perry Aggression Questionnaire—Is the short form more adequate?

We aim to provide a publicly available Hungarian version of the BPAQ; compare the BPAQ factors to other personality traits; and compare both the original BPAQ factor structure provided by Buss and Perry (J. Pers. Soc. Psychol., 63, 1992, 452), the revised BPAQ‐SF factor structure by Bryant and Smith (J. Res. Pers., 35, 2001, 138), and the BAQ by Webster et al. (Aggress. Behav., 40, 2014, 120).
The association of maternal folic acid supplementation and prenatal folate and vitamin B12 concentrations with child dental development

Abstract Objective Low folic acid, folate and vitamin B12 might affect tooth formation and mineralization. The conversion of folic acid into folate is catalysed by the methylenetetrahydrofolate (MTHFR) enzyme which is encoded by the MTHFR gene. Among 3728 mothers and their 10‐year‐old children from the Generation R Study, we investigated associations of maternal folic acid supplementation and prenatal folate and vitamin B12 concentrations with child dental development. Secondly, we checked the modifying effect of MTHFR‐C677T polymorphism. Methods Information on folic acid supplementation was obtained by questionnaires. Concentrations of folate and vitamin B12 were measured from venous samples taken in early pregnancy. Developmental stages of teeth were defined by the Demirjian method at the age‐10 assessment. In addition, dental age of the children was calculated using the Dutch standard. GLM and multivariate linear regression models were built to study the associations. Results Folic acid supplementation started when pregnancy was known (β = −0.09; 95% CI: −0.17, −0.01) and folic acid supplementation started prior to known pregnancy (β = −0.12; 95% CI: −0.20, −0.04) were both associated with decelerated dental development by 1‐2 months lower dental age of 10‐year‐old children. Folate (β = −0.02, 95% CI: −0.05, 0.02) and vitamin B12 (β = 0.03, 95% CI: −0.00, 0.06) were not associated with dental age. MTHFR‐C677T did not modify the associations. Conclusions Maternal folic acid supplementation delays dental development of children by 1‐2 months dental age, whereas maternal folate and vitamin B12 concentrations in early pregnancy do not affect the timing of child dental development.
Service User Experiences of Integrating a Mobile Solution (IMPACHS) Into Clinical Treatment for Psychosis

Innovative technological solutions are increasingly being introduced into psychotherapy. Understanding service user perspectives is a key aspect in adapting this technology to treatment. This study investigated service users’ personal experience of the utility, challenges, and rewards of using an mHealth solution in cognitive behavioral therapy for psychosis (CBTp). People participating in an early intervention program for psychosis (n = 16) utilized the mHealth solution for up to 6 months. Semi-structured qualitative interviews were conducted to capture participant experiences, and quantitative data were collected on psychopathology, usage, and quality of the solution. The solution was widely accepted and utilized in treatment. Four dominant themes were constructed from the interviews: (a) Accessibility and supporting recall, (b) Promotion of dialogue with the therapist, (c) Encouraging reflection, and (d) Factors that affected engagement with the solution. The mHealth solution was perceived as facilitating psychotherapeutic processes and supported underlying CBTp treatment principles.
Screen‐Printed Electrodes Modified with Carbon Nanomaterials: A Comparison among Carbon Black, Carbon Nanotubes and Graphene

In this work a comparative study using Screen-Printed Electrodes (SPEs) modified by drop casting with Carbon Black, Single Walled Carbon Nanotubes[BOND]COOH, Graphene Oxide, and reduced Graphene Oxide is reported. The carbon nanomaterials employed were characterized by X-ray photoelectron and Raman spectroscopy, while the modified SPEs have been morphologically and electrochemically characterized. Nanoengineered SPEs have been tested with ferricyanide, NADH, ascorbic acid and cysteine. We observed valuable electroanalytical performances of Carbon Black with the advantage to be i) cost-effective ii) suitable to obtain stable and homogenous dispersion and iii) mass-producible following a well established route.
Prenatal choline, cannabis, and infection, and their association with offspring development of attention and social problems through 4 years of age

Abstract Background Prenatal choline is a key nutrient, like folic acid and vitamin D, for fetal brain development and subsequent mental function. We sought to determine whether effects of higher maternal plasma choline concentrations on childhood attention and social problems, found in an initial clinical trial of choline supplementation, are observed in a second cohort. Methods Of 183 mothers enrolled from an urban safety net hospital clinic, 162 complied with gestational assessments and brought their newborns for study at 1 month of age; 83 continued assessments through 4 years of age. Effects of maternal 16 weeks of gestation plasma choline concentrations ⩾7.07 μM, 1 s.d. below the mean level obtained with supplementation in the previous trial, were compared to lower levels. The Attention Problems and Withdrawn Syndrome scales on Child Behavior Checklist 1½–5 were the principal outcomes. Results Higher maternal plasma choline was associated with lower mean Attention Problems percentiles in children, and for male children, with lower Withdrawn percentiles. Higher plasma choline concentrations also reduced Attention Problems percentiles for children of mothers who used cannabis during gestation as well as children of mothers who had gestational infection. Conclusions Prenatal choline's positive associations with early childhood behaviors are found in a second, more diverse cohort. Increases in attention problems and social withdrawal in early childhood are associated with later mental illnesses including attention deficit disorder and schizophrenia. Choline concentrations in the pregnant women in this study replicate other research findings suggesting that most pregnant women do not have adequate choline in their diets.
A Unified Approach to Mixed-Integer Optimization Problems With Logical Constraints

We propose a unified framework to address a family of classical mixed-integer optimization problems with logically constrained decision variables, including network design, facility location, unit commitment, sparse portfolio selection, binary quadratic optimization, sparse principal analysis and sparse learning problems. These problems exhibit logical relationships between continuous and discrete variables, which are usually reformulated linearly using a big-M formulation. In this work, we challenge this longstanding modeling practice and express the logical constraints in a non-linear way. By imposing a regularization condition, we reformulate these problems as convex binary optimization problems, which are solvable using an outer-approximation procedure. In numerical experiments, we establish that a general-purpose numerical strategy, which combines cutting-plane, first-order and local search methods, solves these problems faster and at a larger scale than state-of-the-art mixed-integer linear or second-order cone methods. Our approach successfully solves network design problems with 100s of nodes and provides solutions up to 40\% better than the state-of-the-art; sparse portfolio selection problems with up to 3,200 securities compared with 400 securities for previous attempts; and sparse regression problems with up to 100,000 covariates.
Measurement of Low Pressure Plasma Parameters by the Floating Double Probe Method in Magnetic Field on a Subnormal Glow Discharge Region in Molecular and Rare Gases

In floating double probe technique in equivalent resistance method [1,2] the plasma parameters have been measured in subnormal gas discharge. The electron temperature and electron density have been studied in both the transverse and longitudinal magnetic field in low pressure for air, hydrogen and argon gases. It is observed that in case of transverse magnetic field, the electron temperature increases whereas the radial electron density decreases and in case of longitudinal magnetic field, the electron temperature decreases and the radial electron density increases.
Improving Classification Accuracy With Graph Filtering

In machine learning, classifiers are typically susceptible to noise in the training data. In this work, we aim at reducing intra-class noise with the help of graph filtering to improve the classification performance. Considered graphs are obtained by connecting samples of the training set that belong to a same class depending on the similarity of their representation in a latent space. We show that the proposed graph filtering methodology has the effect of asymptotically reducing intra-class variance, while maintaining the mean. While our approach applies to all classification problems in general, it is particularly useful in few-shot settings, where intra-class noise can have a huge impact due to the small sample selection. Using standardized benchmarks in the field of vision, we empirically demonstrate the ability of the proposed method to slightly improve state-of-the-art results in both cases of few-shot and standard classification.
Efficient downscaling of satellite oceanographic data with convolutional neural networks

Space-borne satellite radiometers measure Sea Surface Temperature (SST), which is pivotal to studies of air-sea interactions and ocean features. Under clear sky conditions, high resolution measurements are obtainable. But under cloudy conditions, data analysis is constrained to the available low resolution measurements. We assess the efficiency of Deep Learning (DL) architectures, particularly Convolutional Neural Networks (CNN) to downscale oceanographic data from low spatial resolution (SR) to high SR. With a focus on SST Fields of Bay of Bengal, this study proves that Very Deep Super Resolution CNN can successfully reconstruct SST observations from 15 km SR to 5km SR, and 5km SR to 1km SR. This outcome calls attention to the significance of DL models explicitly trained for the reconstruction of high SR SST fields by using low SR data. Inference on DL models can act as a substitute to the existing computationally expensive downscaling technique: Dynamical Downsampling. The complete code is available on this Github Repository.
Simulation of non-line-of-sight imaging system based on the light-cone transform

Non-line-of-sight (NLOS) imaging is an emerging technique, which can observe objects obscured by occluders. Thanks to the improvement of optical configurations, it is receiving growing interest from researchers. In this paper, we reconstruct both 2D and 3D images by adopting the light-cone transform and validated on simulated data. Numerical results are evaluated by structural similarity index (SSIM). The results showed the good performance of the algorithm in preserving the details of 2D image and reconstruction of 3D image. The structural similarity index of the reconstructed image and the reference image is more than 50%, the target is hence being identified. This work contributes to the construction of the real system.
An improved reliability-guided phase unwrapping algorithm for digital holographic microscopic

Phase unwrapping is an essential procedure in digital holographic microscopy (DHM). There are many algorithms have been proposed to unwrap the phase such as the reliability-guided phase unwrapping algorithm that intro- duced in this paper. It is necessary to do a comparison of these algorithms in order to determine which method has better performance in the actual experiment. For higher quality and fewer error points, we also introduce an improved phase unwrapping path base on path-following method such as the reliability-guided phase unwrapping algorithm, and the experimental images demonstrate the validity of our algorithms. In addition, we propose a method to accelerate the phase unwrapping process for biomedical dynamic imaging. The experimental results suggest that this method can significantly improve the dynamic measurement speed while ensuring the accuracy of phase unwrapping.
The Industrial Sodium Cooled Fast Reactor

This paper investigates the use of enrichment and moderator zoning methods for optimizing the r-z power distribution within sodium cooled fast reactors. These methods allow overall greater fuel utilization in the core resulting in more fuel being irradiated near the maximum allowed thermal power. The peak-to-average power density was held to 1.18. This core design, in conjunction with a multiple-reheat Brayton power conversion system, has merit for producing an industrial level of electrical output (2400 MWth, 1000 MWe) from a relatively compact core size. The total core radius, including reflectors and shields, was held to 1.78 m. Preliminary safety analysis suggests that positive reactivity insertion resulting from a leak between the sodium primary loop and helium power conversion system can be mitigated using simple gas-liquid centripetal separation strategies in the plant’s primary loop.
Ground surveillance radar target classification based on 2D CNN

In this paper, a new approach for classifying targets captured by low-resolution Ground Surveillance Radar is proposed. Radar target is detected by the Doppler effect in radar echo signal. Those signals can be disposed in various domains to gain unique features of targets which can be used in radar target classification and enhance its effectiveness. The proposed approach consists of two steps, transforming original signals from 1D to 2D and constructing deep 2D convolution neural networks(CNN). In first step, Toeplitz matrix is made use of reconstructing Radar signal, to build a 2D plane of data. Reconstruction does not change the characteristic distribution of the signal but maps the signal from one to two dimensions in a rearranged method. Whilst,it makes possible of using 2D CNN to train the data. In second step, we take advantage of the “bottleneck” block to create 2D CNN, which guarantee the depth of CNN and ease the problem of vanishing/exploding gradients in back propagation process. method was tested on actual collected database including human and car, which achieve 99.7% accuracy on the original test set and 97% accuracy after adding noise.
Nonlinear input/output analysis: application to boundary layer transition

Abstract We extend linear input/output (resolvent) analysis to take into account nonlinear triadic interactions by considering a finite number of harmonics in the frequency domain using the harmonic balance method. Forcing mechanisms that maximise the drag are calculated using a gradient-based ascent algorithm. By including nonlinearity in the analysis, the proposed frequency-domain framework identifies the worst-case disturbances for laminar-turbulent transition. We demonstrate the framework on a flat-plate boundary layer by considering three-dimensional spanwise-periodic perturbations triggered by a few optimal forcing modes of finite amplitude. Two types of volumetric forcing are considered, one corresponding to a single frequency/spanwise wavenumber pair, and a multi-harmonic where a harmonic frequency and wavenumber are also added. Depending on the forcing strategy, we recover a range of transition scenarios associated with $K$-type and $H$-type mechanisms, including oblique and planar Tollmien–Schlichting waves, streaks and their breakdown. We show that nonlinearity plays a critical role in optimising growth by combining and redistributing energy between the linear mechanisms and the higher perturbation harmonics. With a very limited range of frequencies and wavenumbers, the calculations appear to reach the early stages of the turbulent regime through the generation and breakdown of hairpin and quasi-streamwise staggered vortices.
The effects of nanoscale nuclei on cavitation

Abstract Under certain conditions, experimental values of the tensile strength of water are found to be much lower than theoretical values, even when the water is purified and degassed as much as possible. The discrepancy could be ascribed to stabilized nanobubbles or nanoparticles suspended in the liquid, as such contaminants cannot be eliminated completely from a substantial liquid volume. Thus, the present study aims at elucidating the effects of such nanoscale nuclei on cavitation. A parameter-free mathematical model is derived to predict the cavitation arising from nanoscale nuclei, based on classical nucleation theory. To verify the model, molecular dynamics is used to simulate cavitation at nuclei of different sizes, embedded either in water or in liquid copper at different temperatures. The cavitation pressures calculated from the molecular dynamics results are compared with the predictions of the present mathematical model, with a good agreement between them. The results show that nanoscale nuclei significantly promote cavitation, i.e. the tensile strength is reduced notably by the presence of nanoscale nuclei. The tensile strength decreases when the size of nuclei increases, and the change rule of cavitation pressure is also affected by the liquid properties, such as liquid temperature. The present study may provide an acceptable explanation of the discrepancy between theory and experiment on the cavitation pressure in liquids purified and degassed as much as possible.
Political orientation and system justification: the moderating role of national identity in a Spanish sample (Orientación política y justificación del sistema: el rol moderador de la identidad nacional en una muestra española)

ABSTRACT Right-wing people usually justify the system more than left-wing people. The social identity approach suggests that system justification may be an ingroup bias at overarching national levels and that differences between leftists and rightists could be linked to differences in party norms in promoting national identification. A cross-sectional design was used in which 192 adults (64.6% men, mean age of 35.61 years) were enrolled. Political orientation, national identification and general and economic system justification were collected. Results from structural equation modelling indicated that rightists, as compared with leftists, were higher in national identification and both general and economic system justification. National identification mostly mediated the relationship between political orientation and general system justification, while mediation on the relationship between political orientation and economic system justification was less marked. The social identity approach expectation that differences in system justification could be linked to the extent to which people identify with their overarching social category appears to be supported.
Silver ion transporting mechanism in superionic conducting AgI-Ag2O-TeO2 glasses

Superionic conducting glasses in the ternary AgI-Ag2O-TeO2 system have been prepared and investigated by different techniques. Comparison between conductivities of the present glasses and those of glasses in other different systems has been carried out. The obtained results revealed that the optimum value of conductivity at room temperature is of the order of 10-2 S cm-1 at about 60 mol% AgI for all the considered superionic systems, regardless of their composition or types. The highest conduction at about 60 mol% AgI was correlated to the creation of maximum pathways which favour the Ag+ ion transporting mechanism. Formation of some crystalline phases from AgI at higher concentrations (>60 mol% AgI) was considered the main reason for decreasing the conduction of AgI-rich glasses. Some specific structural models have been proposed to explain the Ag+ ion transport mechanism in the AgI-Ag2O-TeO2 glasses.
Catechol-O-Methyltransferase Gene Val158Met Polymorphism Moderates the Effect of Social Exclusion and Inclusion on Aggression in Men: Findings From a Mixed Experimental Design

Accumulating research has identified the interactive effects of catechol-O-methyltransferase (COMT) gene Val158Met polymorphism and environmental factors on aggression. However, available evidence was mainly based upon correlational design, which yields mixed findings concerning who (Val vs. Met carriers) are more affected by environmental conditions and has been challenged for the low power of analyses on gene–environment interaction. Drawing on a mixed design, we scrutinized how COMT Val158Met polymorphism (between-group variable) impacts on aggression, assessed by hostility, aggressive motivation, and aggressive behavior, under different social conditions (exclusion vs. inclusion, within-group variable) in a sample of 70 Chinese male undergraduate students. We found that both Val/Val homozygote and Met alleles carriers showed differences in the feelings of hostility and aggressive motivation under conditions of exclusion versus inclusion, but these differences were more pronounced for Met allele carriers. These findings implied that COMT Val158Met polymorphism did not respond to environmental stimuli in an all-or-none way and shed light on the importance of examining the gene–environment interaction using a mixed design.