Miracle-dz/UniFAR-FTUs huggingface dataset:
CSMD1 Shows Complex Patterns of Somatic Copy Number Alterations and Expressions of mRNAs and Target Micro RNAs in Esophageal Squamous Cell Carcinoma

Simple Summary Human Cub and Sushi Multiple Domains 1 (CSMD1) is a novel candidate tumor-suppressor gene. We investigated CSMD1 in esophageal squamous cell carcinoma (ESCC) by performing an integrated analysis of somatic DNA alterations (i.e., copy number alteration, allelic imbalance, and loss of heterozygosity) with RNA expressions (mRNA and target miRNAs) on specimens from the same ESCC patients, using data from SNP, miRNA, and RT-PCR arrays. Our results indicate that the CSMD1 gene may play a role in the development of ESCC through complex patterns involving somatic alterations and mRNA expression. Furthermore, somatic copy number alterations in SNPs located in non-coding regions of CSMD1 appear to influence expression of both this gene and its target miRNAs. Abstract Background: Human Cub and Sushi Multiple Domains 1 (CSMD1) is a novel candidate tumor-suppressor gene that codes for multiple domains, including complement regulatory and adhesion proteins, and has recently been shown to have alterations in multiple cancers. We investigated CSMD1 in esophageal squamous cell carcinoma (ESCC) by performing an integrated analysis on somatic copy number alterations (CNAs), including copy-number gain or loss, allelic imbalance (AI), loss of heterozygosity (LOH), and the expressions of mRNA and its target miRNAs on specimens from the same patients with ESCC. Results: (i) Two-thirds of ESCC patients had all three types of alterations studied—somatic DNA alterations in 70%, and abnormal expressions of CSMD1 RNA in 69% and in target miRNAs in 66%; patterns among these alterations were complex. (ii) In total, 97% of 888 CSMD1 SNPs studied showed somatic DNA alterations, with most located near exons 4–11, 24–25, 39–40, 55–56, and 69–70. (iii) In total, 68% of SNPs with a CNA were correlated with expression of CSMD1. (iv) A total of 33 correlations between non-coding SNPs and expression of CSMD1 target miRs were found. Conclusions: Our results indicate that the CSMD1 gene may play a role in ESCC through complex patterns of DNA alterations and RNA and miRNA expressions. Alterations in some somatic SNPs in non-coding regions of CSMD1 appear to influence expression of this gene and its target miRNAs.
Making maps of cosmic microwave background polarization for B-mode studies: the POLARBEAR example

Analysis of cosmic microwave background (CMB) datasets typically requires some filtering of the raw time-ordered data. For instance, in the context of ground-based observations, filtering is frequently used to minimize the impact of low frequency noise, atmospheric contributions and/or scan synchronous signals on the resulting maps. In this work we have explicitly constructed a general filtering operator, which can unambiguously remove any set of unwanted modes in the data, and then amend the map-making procedure in order to incorporate and correct for it. We show that such an approach is mathematically equivalent to the solution of a problem in which the sky signal and unwanted modes are estimated simultaneously and the latter are marginalized over. We investigated the conditions under which this amended map-making procedure can render an unbiased estimate of the sky signal in realistic circumstances. We then discuss the potential implications of these observations on the choice of map-making and power spectrum estimation approaches in the context of B-mode polarization studies. Specifically, we have studied the effects of time-domain filtering on the noise correlation structure in the map domain, as well as impact it may haveon the performance of the popular pseudo-spectrum estimators. We conclude that although maps produced by the proposed estimators arguably provide the most faithful representation of the sky possible given the data, they may not straightforwardly lead to the best constraints on the power spectra of the underlying sky signal and special care may need to be taken to ensure this is the case. By contrast, simplified map-makers which do not explicitly correct for time-domain filtering, but leave it to subsequent steps in the data analysis, may perform equally well and be easier and faster to implement. We focused on polarization-sensitive measurements targeting the B-mode component of the CMB signal and apply the proposed methods to realistic simulations based on characteristics of an actual CMB polarization experiment, POLARBEAR. Our analysis and conclusions are however more generally applicable.
Dynamic Neural Recommender System

Today’s recommenders need to work on dynamic datasets, i.e., datasets where users, items, and ratings change frequently. Our main contribution is a dynamic recommender system that periodically recommends a subset of unseen items to all users in a user base without retraining. Our second contribution is the evaluation of techniques to decrease catastrophic forgetting in neural networks. Our work builds on the work done by Sedhain et al. [SMSX15], a neural Autoencoder that takes a vector of all user ratings for one item and reconstructs it. The Autoencoder imputes missing ratings by using a learned latent representation of the users’ feedback behavior. To learn the hidden representation that permits imputation, we implement a custom training procedure in TensorFlow that only considers observed entries in the input and does partial forward-and backward propagation. Our approach achieves an Root Mean Squared Error (RMSE) of 0.86 on the MovieLens-1M dataset [Mov21] and of 0.77 on the Microsoft MIND dataset [WQC+20]. Out of the techniques aimed at decreasing catastrophic forgetting, replaying old training samples emerged as the most effective technique.
An exploration of the semantic knowledge in vector models: polysemy, synonymy and idiomaticity

In this paper, we present the project An exploration of the semantic knowledge in vector models: polysemy, synonymy and idiomaticity , funded by the Xunta de Galicia within the program “Consolidación e estruturación de unidades de investigación competitivas e outras accións de fomento: Proxectos de Excelencia”, with a duration of 5 years (2021-2026). The main objective of the project is the analysis of the most recent language models regarding the representation of several aspects of lexical semantics: polysemy and homonymy, synonymy and idiomaticity. The languages in which we are working are Galician-Portuguese (in its Galician and Portuguese varieties, fundamentally), Spanish and English.
Consumer-Based Product Creativity, Product-Brand Fit, and Product-Category Fit: Which is More Influential in Consumer Responses?

This study examines the effects of consumer-based product creativity (i.e., novelty and meaningfulness dimensions), product-brand fit, and product-category fit on attitude toward the product and purchase intention. A total of 544 university students participated in a survey, in which respondents were exposed to a stimulus product image and then required to respond to a questionnaire. Structural equation modelling results show that novelty and meaningfulness and product-brand fit significantly influence attitude, subsequently increasing purchase intention. Notably, meaningfulness, rather than product-brand fit, is found to be more influential on both the attitude and purchase intention. The importance of meaningfulness can be even more highlighted for the products less fitted for their category. Theoretical and practical implications are further discussed.
LIFETIME OF THE EMBEDDED PHASE OF LOW-MASS STAR FORMATION AND THE ENVELOPE DEPLETION RATES

Motivated by a considerable scatter in the observationally inferred lifetimes of the embedded phase of star formation, we study the duration of the Class 0 and Class I phases in upper-mass brown dwarfs and low-mass stars using numerical hydrodynamic simulations of the gravitational collapse of a large sample of cloud cores. We resolve the formation of a star/disk/envelope system and extend our numerical simulations to the late accretion phase when the envelope is nearly totally depleted of matter. We adopt the classification scheme of André et al. and calculate the lifetimes of the Class 0 and Class I phases (τC0 and τCI, respectively) based on the mass remaining in the envelope. When cloud cores with various rotation rates, masses, and sizes (but identical otherwise) are considered, our modeling reveals a sub-linear correlation between the Class 0 lifetimes and stellar masses in the Class 0 phase with the least-squares fit exponent m = 0.8 ± 0.05. The corresponding correlation between the Class I lifetimes and stellar masses in Class I is super-linear with m = 1.2 ± 0.05. If a wider sample of cloud cores is considered, which includes possible variations in the initial gas temperature, cloud core truncation radii, density enhancement amplitudes, initial gas density and angular velocity profiles, and magnetic fields, then the corresponding exponents may decrease by as much as 0.3. The duration of the Class I phase is found to be longer than that of the Class 0 phase in most models, with a mean ratio τCI/τC0≈ 1.5–2. A notable exception are young stellar objects that form from cloud cores with large initial density enhancements, in which case τC0 may be greater than τCI. Moreover, the upper-mass (≳1.0 M☉) cloud cores with frozen-in magnetic fields and high cloud core rotation rates may have the τCI/τC0 ratios as large as 3.0–4.0. We calculate the rate of mass accretion from the envelope onto the star/disk system and provide an approximation formula that can be used in semi-analytic models of cloud core collapse.
Classification and Prediction of Nitrogen Dioxide in a Portuguese Air Quality Critical Zone

This study presents classification and prediction exercises to evaluate the future behavior of nitrogen dioxide in a critical air quality zone located in Portugal using a dataset, the time span of which covers the period between 1 September 2021 and 23 July 2022. Three main results substantiate the importance of this research. First, the classification analysis corroborates the idea of a neutrality principle of road traffic on the target since the respective coefficient is significant, but quantitatively close to zero. This result, which may be the first sign of a paradigm shift regarding the adoption of electric vehicles in addition to reflect the success of previously implemented measures in the city of Lisbon, is reinforced by evidence that the carbon monoxide emitted mostly by diesel vehicles exhibits a significant, negative and permanent effect on satisfying the hourly limit value associated with the target. Second, robustness checks confirm that the period between 8 h and 16 h is particularly remarkable for influencing the target. Finally, the predictive exercise demonstrates that the internationally patented Variable Split Convolutional Attention model has the best predictive performance among several deep learning neural network alternatives. Results indicate that the concentration of nitrogen dioxide is expected to be volatile and only a redundant downward trend is likely to be observed. Therefore, in terms of policy recommendations, additional measures to avoid exceeding the legal nitrogen dioxide ceiling at the local level should be focused on reducing carbon monoxide emissions, rather than just being concerned about halting the intensity of road traffic.
Designing Positive Experiences in Creative Workshops at Work Using a Warm UP Set Based on Psychological Needs

With working from home becoming more normalized, creative workshops are increasingly taking place in digital and hybrid form. However, participants are usually less engaged and motivated in these contexts. This is due to less physical presence and activity, complex technical systems and a lack of social interaction and communication. This leaves the facilitators with the challenge that these creative workshops are sometimes not experienced as positively, and therefore participants are not able to work as creatively. An important approach that can strengthen these factors in workshops is the use of warm-ups as a type of playful intervention. Although some research on and compilations of warm-ups exist and may help the situation, they do not yet provide direction on how to specifically promote a positive experience in creative workshops with warm-ups. An important link here is user experience research, which assumes that positive experiences are due to the fulfilment of psychological needs. Based on research about warm-ups and playful interventions in general, we derive categories for classifying warm-ups that can potentially address several specific psychological needs. Then, 28 warm-ups are selected according to their applicability in analogue, digital and hybrid application spaces. Moreover, those 28 warm-ups are assigned to the two most relevant classifying categories. The results are mapped in the form of a ready-to-use Warm UP Set, which is then evaluated for applicability from the facilitators’ perspective and regarding the influence on the emotional experience of the participants. The evaluation shows that the developed Warm UP Set with its categories seems to be suitable to support facilitators in systematically inducing positive experiences in participants in creative workshops.
Effects of Feedback-Supported Online Training during the Coronavirus Lockdown on Posture in Children and Adolescents

(1) Background. The coronavirus pandemic had a serious impact on the everyday life of children and young people with sometimes drastic effects on daily physical activity time that could have led to posture imbalances. The aim of the study was to examine whether a six-week, feedback-supported online training programme could improve posture parameters in young soccer players. (2) Methods. Data of 170 adolescent soccer players (age 15.6 ± 1.6 years) were analyzed. A total of 86 soccer players of a youth academy participated in an online training program that included eight exercises twice per week for 45 min (Zoom group). The participants’ exercise execution could be monitored and corrected via smartphone or laptop camera. Before and after the training intervention, participants’ posture was assessed using photographic analysis. The changes of relevant posture parameters (perpendicular positions of ear, shoulder and hips, pelvic tilt, trunk tilt and sacral angle) were statistically tested by robust mixed ANOVA using trimmed means. Postural parameters were also assessed post hoc at 8-week intervals in a control group of 84 participants of the same age. (3) Results. We found a statistically significant interaction (p < 0.05) between time and group for trunk tilt, head and shoulder protrusion and for hip anteversion in the Zoom group. No changes were found for these parameters in the control group. For pelvic tilt no significant changes were found. (4) Conclusions. Feedback-based online training with two 45 min sessions per week can improve postural parameters in adolescent soccer players over a period of six weeks.
MODERN CHALLENGES OF HIGHER LEGAL EDUCATION: THE ISSUES OF LEGAL SUPPORT

: The article considers external and internal impacts on modern society that create unique conditions for its functioning, i.e. a combination of exponential information-technological development and the COVID-19 unstable dynamics. Assuming an objectively conditioned coexistence of modern challenges and social society with its most important institutions, the authors of the article conduct a comprehensive interdisciplinary study. This allows them to trace the mutual influence of internal socio-psychological properties and external institutional forms of society management provided by the system of legal regulation. The authors have analyzed the modernization of the most important social institution that regulates the socialization of a personality (education), the transformation of its goals, objectives, mechanisms, methods and tools. As a result, the authors have concluded that the popularization of digital technologies is objectively and naturally predetermined by new goals and objectives of this social institution in modern conditions. However, it requires a transformation of the current regulatory framework. discussion technologies in the system of higher education – Changing
A Framework Validation for ERP Implementation in Thailand: A Case Study Approach

The purpose of this research is to study the factors that affect the success of Enterprise Resource Planning (ERP) implementation in the organizations. For this study, the researcher used qualitative research methods to validate the framework of ERP implementation based on the literature. In-depth interviews were conducted with four organizations that have already used ERP systems for longer than 6 months to discover the findings of ERP systems usage. The study shows that the understanding and awareness of the value of information among employees and executives is influence ERP system implementation, and this focus tend to improve its effectiveness. The research outcomes may be utilized as conceptual framework for future ERP development.
VLT/MAGELLAN SPECTROSCOPY OF 29 STRONG LENSING SELECTED GALAXY CLUSTERS

We present an extensive spectroscopic follow-up campaign of 29 strong lensing (SL) selected galaxy clusters discovered primarily in the Second Red-Sequence Cluster Survey (RCS-2). Our spectroscopic analysis yields redshifts for 52 gravitational arcs present in the core of our galaxy clusters, which correspond to 35 distinct background sources that are clearly distorted by the gravitational potential of these clusters. These lensed galaxies span a wide redshift range of 0.8 ≤ z ≤ 2.9, with a median redshift of zs = 1.8 ± 0.1. We also measure reliable redshifts for 1004 cluster members, allowing us to obtain robust velocity dispersion measurements for 23 of these clusters, which we then use to determine their dynamical masses by using a simulation-based σDM − M200 scaling relation. The redshift and mass ranges covered by our SL sample are 0.22 ≤ z ≤ 1.01 and , respectively. We analyze and quantify some possible effects that might bias our mass estimates, such as the presence of substructure, the region where cluster members are selected for spectroscopic follow-up, the final number of confirmed members, and line-of-sight effects. We find that 10 clusters of our sample with Nmem ≳ 20 show signs of dynamical substructure. However, the velocity data of only one system is inconsistent with a uni-modal distribution. We therefore assume that the substructures are only marginal and not of comparable size to the clusters themselves. Consequently, our velocity dispersion and mass estimates can be used as priors for SL mass reconstruction studies and also represent an important step toward a better understanding of the properties of the SL galaxy cluster population.
A machine learning approach to predict university students Hookah Smoking (HS)

In recent years, Hookah (Shisha) has spread in general and large, including classical and electronic types, which have spread especially among young university students. the dataset was used on the university student at the University of Kirkuk, which was collected and analyzed using a special questionnaire about Hookah Smoking (HS) in the university students. The aim of this work is to find out how much the students are concerned about the recent Hookah Smoking in the university students and the extent of their consumption of the time that the student is supposed to devote to his studies at the college. Using the algorithms and techniques of data mining and machine learning to Hookah Smoking (HS), used decision tree and random forest algorithms to classify hookah smoking for university students. Then predict when the students smoke shisha and the negative impact of this time on the health of the university student, which in turn negatively affects his scientific level. Furthermore, best algorithm archive random forest has high classification rate than decision tree. New predictions can also be made for the development of statistics and tables that determined the type and quantity of consumption of Hookah Smoking and other side effects.
Artificial Neural Network Analysis On Motor Imagery Electroencephalogram

Research on brain signal analysis has been performed decades ago. This research field has benefited other industries such as health and analytics. Various analysis methods either conventional or intelligent methods had been explored in ensuring the best application was produced. In this project, a secondary dataset from motor cortex brain signals had been utilized and the dataset is captured by a non-invasive method using an electroencephalogram (EEG) tool. The dataset is then proposed to be extracted and classified using the Deep Learning Neural Network method. High accuracy and sensitivity of model analysis are expected as the outcome of the project. Besides, statistical analysis had been conducted to observe the significance between electrode placement and the output of the dataset. Thus, the Artificial Neural Network model was observed as the final finding.
NUMERICAL SOLUTION OF THE DISTRIBUTION OF WIND AND TURBULENCE IN THE PLANETARY BOUNDARY LAYER

Abstract : Meteorology is subdivided according to the scales of micrometeorology, mesometeorology and macrometeorology. This division appears real since research interests and successes have been widely separated. If meso-scale phenomena are regarded as perturbations within the macroscale, two elements can be selected to characterize the divisions. These would be the logarithmic wind profile to characterize micrometeorology and the geostrophic wind to characterize the others. The purpose of this report is to present a hypothesis which unifies these two concepts. The model resulting from the hypothesis is solved and the results are presented in a form usable for many situations where it is necessary to predict the vertical distribution of the wind and turbulence characteristics within the planetary boundary layer. The treatment will be limited to the barotropic, adiabatic, steady state case.
Another Chilarity Quantum Phase Transition in the Atom-Cavity Interaction

This paper is devoted to a study of a kind of chirality appearing in a model in cavity or circuit quantum electrodynamics. The model especially describes an artificial atom fully coupled to a 1-mode photon in a cavity. This chirality is played in the fully coupled (FC) Hamiltonian by two modified Jaynes-Cummings (JC) Hamiltonians. The modified JC Hamiltonian as well as the standard one has the superradiant ground state energy for sufficiently large coupling strength. The superradiance is caused by a phase transition found by Preparata, called the Dicke-Preparata (DP) superradiance. Using the one common Hamiltonian formalism with the chirality, we theoretically prove the followings: (i) when the coupling strength makes the weak or standard strong coupling regime, the ground state energy of the FC Hamiltonian can be well approximated with that of the standard and modified JC Hamiltonians since the chirality does not work in the regime; (ii) once the coupling strength plunges into the ultra-strong coupling regime, the effect of the chirality is turned on and works in the ground state energy of the FC Hamiltonian. That is, there is a kind of a phase transition concerning the chirality associated with the DP superradiance between the strong coupling regime and the ultra-strong coupling one.