Miracle-dz/UniFAR-FTUs huggingface dataset:
A non-conformal holographic model for D-meson suppression at LHC energy

The drag force of charm quarks propagating through a thermalized system of Quark Gluon Plasma (QGP) has been considered within the framework of both conformal/non-conformal Anti de Sitter (AdS) correspondence. Newly derived Einstein Fluctuation-Dissipation relation has been used to calculate the heavy flavor diffusion coefficients. Using the drag and diffusion coefficients as inputs Langevin equation has been solved to study the heavy flavor suppression factor. It has been shown that within conformal AdS correspondence the D-meson suppression at LHC energy can be reproduced where as the non-conformal AdS correspondence fail to reproduce the experimental results. It suggests collisional loss alone within non-conformal AdS correspondence can not reproduce the experimental results and inclusion of radiative loss becomes important.
The Influence of Screen Media Usage on Child Social Development: A Systematic Review

The relative contribution of screen time and media content to young children's social development has been unclear recently, and information on effective interventions to reduce children's screen time is limited. This review investigates the current status of electronic media use among young children and the effect of screen media usage on children's social development and attempts to explore the correlation between the two in order to enrich and improve related research. It is also supposed to give ideas for how families can use electronic media better to help children develop socially and reduce behavior problems. Parenting styles, media content, household income, the number of children in the family, how the parents use media, their habits, and cognitive stimuli in the home were also linked to young children's media use. The correlations identified in this study suggest intervention pathways to decrease children's screen time consumption and optimize media content. But more research needs to be done to look at some of the environmental, sociocultural, and behavioral factors that haven't been looked at much in young children. This could help make prevention and intervention plans better.
Clinical use of gastric antisecretory drugs in pediatric patients with gastroesophageal reflux disease: a narrative review

Background and Objective Gastroesophageal reflux (GER) is a common condition in infants. Usually, it resolves spontaneously in 95% of cases within 12–14 months of age, but gastroesophageal reflux disease (GERD) may develop in some children. Most authors do not recommend pharmacological treatment of GER, while the management of GERD is debated. The aim of this narrative review is to analyze and summarize the available literature on the clinical use of gastric antisecretory drugs in pediatric patients with GERD. Methods References were identified through MEDLINE, PubMed, and EMBASE search engines. Only articles in English were considered. The following keywords were used: “gastric antisecretory drugs”, “H2RA”, “PPI”, “ranitidine”, “GERD”, “infant”, “child”. Key Content and Findings Increasing evidence of poor efficacy and potential risks of proton pump inhibitors (PPIs) is emerging in neonates and infants. Histamine-2 receptor antagonists (H2RAs), including ranitidine, have been used successfully in older children, although less effective than PPIs at relieving symptoms and healing GERD. However, in April 2020, both the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) requested manufacturers of ranitidine to remove all ranitidine products from the market due to the risk of carcinogenicity. Pediatric studies comparing effectiveness and safety of different acid-suppressing treatments for GERD are generally inconclusive. Conclusions A proper differential diagnosis between GER and GERD is crucial to avoid the overuse of acid-suppressing medications in children. Further research should be directed towards the development of novel antisecretory drugs, with proven efficacy and good safety profile, for treating pediatric GERD, particularly in newborns and infants.
MOTIVASI BELAJAR SISWA KELAS XI MA PADA PEMBELAJARAN BIOLOGI SECARA DARING DI KECAMATAN KEBUMEN (STUDI ANALISIS)

This study aims to analyze the learning motivation of class XI MA students in online biology learning in Kebumen District. This research is qualitative and quantitative research methods (mixed method). The research was conducted in public and private MA in Kebumen District. The data analysis technique was carried out by calculating the percentage of students' answers based on indicators. The results showed that: (1) students' learning motivation of MA Negeri 1 Kebumen was high with an average of 69.3%; (2) the learning motivation of students at MA Negeri 2 Kebumen is moderate with an average of 66.6%; (3) the learning motivation of the students of MA Salafiyah Wonoyoso is high with an average of 71.1%; (4) the learning motivation of MA-PK Ma'arif 1 Kebumen students is high with an average of 71.5%. The learning motivation of class XI MA students in Kebumen District is categorized as high with an average of 69.6%. This is motivated by encouragement from within students and support from people around students so that students have a high desire to succeed even though there are still students who have moderate motivation even low.
Non-Linear Programming--A Survey

Some of the more recent theoretical and computational developments in non-linear programming are surveyed. The notions of Lagrange multipliers and duality are discussed together with applications of these ideas to scientific and business problems. Moreover, several algorithms for solving quadratic programming problems are reviewed. Explicit rules are given for two of these algorithms, and a simple example is solved by both methods. A large step gradient method for the solution of convex programs is given and one of Gomory's algorithms for integer programming is described. Simple examples are solved using both of these techniques. Linear fractional programming is also discussed briefly.
Maintaining Stability for a Matching Problem Under Dynamic Preference

This study investigates two-sided matching and considers dynamic preference. In a stable matching problem, dynamic preference is a situation that often happens in real-world situations where the agent cannot express their preference with certainty. This study proposes a new concept to find stable matching using the blocking pair perspective. A stable matching is determined by identifying a matching by finding a matching with the minimum blocking pairs in multiple instances. In addition, the definition of stability is extended for the stable matching problem under dynamic preference to propose three new notions of stability. The proposed concept demonstrates more detailed information to assist in determining a stable matching with a dynamic preference. Moreover, the experiment results show that matching with the lowest expected value of the blocking pair gains the highest satisfaction score of agents in the market.
A Novel Fuzzy-BELBIC Structure for the Adaptive Control of Satellite Attitude

The performance of the satellite not only relies on environmental factors but also is impacted by internal disturbances. The influential factors complicate the design of accurate controllers for attitude adjustments. The proposed research addresses this control problem by introducing a Brain Emotional Learning Based Intelligent Controller (BELBIC) tuned by a fuzzy inference system. Here, the learning weights and the gain inputs of the BELBIC are adjusted using a fuzzy inference system. In contrast, the initial parameters of the fuzzy inference system are adapted through the whale optimization algorithm. We validate and evaluate the performance of the proposed intelligent controller utilizing simulation studies. The results demonstrate the applicability and satisfactory performance of the proposed controller compared to the PID-BELBIC.
An Angiogenic Gene Signature for Prediction of the Prognosis and Therapeutic Responses of Hepatocellular Carcinoma

Among cancer-related deaths worldwide, hepatocellular carcinoma (HCC) ranks second. The hypervascular feature of most HCC underlines the importance of angiogenesis in therapy. This study aimed to identify the key genes which could characterize the angiogenic molecular features of HCC and further explore therapeutic targets to improve patients’ prognosis. Public RNAseq and clinical data are from TCGA, ICGC, and GEO. Angiogenesis-associated genes were downloaded from the GeneCards database. Then, we used multi-regression analysis to generate a risk score model. This model was trained on the TCGA cohort (n = 343) and validated on the GEO cohort (n = 242). The predicting therapy in the model was further evaluated by the DEPMAP database. We developed a fourteen-angiogenesis-related gene signature that was distinctly associated with overall survival (OS). Through the nomograms, our signature was proven to possess a better predictive role in HCC prognosis. The patients in higher-risk groups displayed a higher tumor mutation burden (TMB). Interestingly, our model could group subsets of patients with different sensitivities to immune checkpoint inhibitors (ICIs) and Sorafenib. We also predicted that Crizotinib, an anti-angiogenic drug, might be more sensitive to these patients with high-risk scores by the DEPMAP. The inhibitory effect of Crizotinib in human vascular cells was obvious in vitro and in vivo. This work established a novel HCC classification based on the gene expression values of angiogenesis genes. Moreover, we predicted that Crizotinib might be more effective in the high-risk patients in our model.
Peptide-Protected Gold Nanoclusters Efficiently Ameliorate Acute Contact Dermatitis and Psoriasis via Repressing the TNF-α/NF-κB/IL-17A Axis in Keratinocytes

Immune-mediated skin diseases have a high prevalence and seriously affect patients’ quality of life. Gold compounds have been considered promising therapeutic agents in dermatology, but the high incidence of adverse reactions have limited their clinical application. There is a great need to develop more effective and less toxic gold-based drugs. Gold nanoclusters fabricated by using peptides (pep-AuNCs) have appeared as potential biomedical nanomaterials because of their excellent biocompatibility, ease of fabrication and unique physicochemical properties. Glutathione (GSH) is an endogenous tripeptide and has been used for lightening the skin color. Therefore, we fabricated a well-defined gold nanocluster with GSH as an example to explore the immunomodulatory effect of AuNCs on a TNF-α-treated human keratinocyte cell line (HaCaT) in vitro, the 12-O-tetradecanoylphorbol-13-acetate (TPA)-induced irritant contact dermatitis (ICD) model and the oxazolone (OXA)-induced psoriatic model in vivo. The results indicated that topically applied AuNCs successfully attenuated the severity of ICD and psoriasis-like lesions. In vitro and in vivo, AuNCs effectively inhibited the abnormal activation of the NF-κB pathway and the consequent overexpression of proinflammatory cytokines in keratinocytes. In particular, the transactivation of IL-17A, the most important cytokine in psoriasis pathology, was effectively inhibited by AuNCs treatment. In addition, AuNCs did not show any obvious cytotoxicity in HaCaT cells at doses even up to 100 µM and did not induce any irritation in the healthy skin and major organs, which indicated their favorable biosafety. These results indicate that biocompatible pep-AuNCs might be a promising gold-based nanomedicine for the treatment of inflammatory skin diseases.
Development of a Compliant Gripper Driven by 3 DOF Soft Robot

This study presents the design, development, and experimental testing of a single piece designed compliant gripper manipulated by a 3 DOF soft robot. The manipulator consists of two soft links. While the bottom arm is 2 DOF and is tendon driven by two servo motors, the SDOF upper arm is also tendon driven by a servo motor. The two-finger-designed compliant gripper is also actuated by a servo motor. The base of the robot holds the motors and the soft manipulator. The MATLAB Simscape model of the robot is created to perform deformation and motion analysis of the gripper and soft manipulator. The cad model of the robot is imported, and the manipulator parts are converted into soft links using discrete beam elements. The large deflecting hinges on the compliant grippers are also transformed to mimic the physical gripper. Since the soft manipulator and the compliant gripper were designed monolithically, the robot was 3D printed as a single piece using thermoplastic polyurethane (TPU). The gripper is tested for its grasping and lifting performance while recording the applied forces by the gripper using a Flex sensor. Using the opencv tool for image processing and object analysis, we used a dual-camera setup with a known environment to add intelligence to the robot. Since the manipulator is designed as soft, the gripper can reach any position within its working space with any orientation.
Component commonality in assemble-to-order systems: Models and properties

This article presents a general multiperiod model of an assemble-to-order system with component commonality and proves that its solution is myopic. The model is then endowed with a capacity or storage constraint, and the resulting behavior of optimal policies is investigated. Interestingly, with such constraint, the optimal stocks of product-specific components can be lower in an assemble-to-order system than in a corresponding make-to-stock one, a behavior that is impossible in an unconstrained model.
An Improved PCA-SIFT Algorithm by Fuzzy K-Means for Image Matching

Image matching plays an important role in computer vision. The features extracted by SIFT algorithm have high stability invariant to scale, rotation and light, so it is the most popular algorithm for image matching. While SIFT algorithm also has its disadvantages of high dimensional data and time-consuming. To solve this problem, the traditional method employs PCA algorithm to reduce dimensionality of the descriptors. While PCA is a linear dimensionality reduction algorithm which means that it can only be used for linear distributed data. This paper employs the fuzzy K-means algorithm to improve it (referred to as FKPCA) and improved RANSAC algorithm to eliminate false matching points after matching with PCA-SIFT and FKPCA-SIFT. From the experimental results, compared with PCA-SIFT algorithm, it can be seen that FKPCA-SIFT can keep the high matching accuracy for image. Moreover, FKPCA-SIFT can also be applied to non-linear data to expand the scope of PCA-SIFT and provides a better reference platform for further research.
Molecular basis of heat stress tolerance in wheat

The rise in Earth’s temperature is one of the most alarming climatic issues in the field of agriculture and food production, in the present context. The increase in temperature leads to heat stress, major abiotic stress responsible for a huge decline in the production of crops. Wheat (Triticum aestivum), among many crops, also experiences a significant decline in yield and overall productivity due to extreme heat stress. But Wheat has also developed natural tolerance mechanisms to defend itself from heat damage. The selection of cultivars with a higher degree of tolerance mechanism protects against thermal stress, which minimizes the risk of poor productivity to a greater extent. In this review, we discuss the current works of literature concerning the heat stress tolerance mechanism in wheat plants and also highlight the strategic approaches that improve their heat stress tolerance at the molecular level. The success of these approaches depends on a better understanding of heat tolerance traits, their genomic composition, and molecular responses.
Multiphoton fluorescence imaging of NADH to quantify metabolic changes in epileptic tissue in vitro

A powerful advantage of multiphoton microscopy is its ability to image endogenous fluorophores such as the ubiquitous coenzyme NADH in discrete cellular populations. NADH is integral in both oxidative and non-oxidative cellular metabolism. NADH loses fluorescence upon oxidation to NAD+; thus changes in NADH fluorescence can be used to monitor metabolism. Recent studies have suggested that hypo metabolic astrocytes play an important role in cases of temporal lobe epilepsy (TLE). Current theories suggest this may be due to defective and/or a reduced number of mitochondria or dysfunction of the neuronal-astrocytic metabolic coupling. Measuring NADH fluorescence changes following chemical stimulation enables the quantification of the cellular distribution of metabolic anomalies in epileptic brain tissue compared to healthy tissue. We present what we believe to be the first multiphoton microscopy images of NADH from the human brain. We also present images of NADH fluorescence from the hippocampus of the kainate-treated rat TLE model. In some experiments, human and rat astrocytes were selectively labeled with the fluorescent dye sulforhodamine 101 (SR101). Our results demonstrate that multiphoton microscopy is a powerful tool for assaying the metabolic pathologies associated with temporal lobe epilepsy in humans and in rodent models.
Machine Learning for Detection of 3D Features using sparse X-ray data

In many inertial confinement fusion (ICF) experiments, the neutron yield and other parameters cannot be completely accounted for with one and two dimensional models. This discrepancy suggests that there are three dimensional effects that may be significant. Sources of these effects include defects in the shells and defects in shell interfaces, the fill tube of the capsule, and the joint feature in double shell targets. Due to their ability to penetrate materials, x rays are used to capture the internal structure of objects. Methods such as computational tomography use x-ray radiographs from hundreds of projections, in order to reconstruct a three dimensional model of the object. In experimental environments, such as the National Ignition Facility and Omega-60, the availability of these views is scarce, and in many cases only consists of a single line of sight. Mathematical reconstruction of a 3D object from sparse views is an ill-posed inverse problem. These types of problems are typically solved by utilizing prior information. Neural networks have been used for the task of 3D reconstruction as they are capable of encoding and leveraging this prior information. We utilize half a dozen, different convolutional neural networks to produce different 3D representations of ICF implosions from the experimental data. Deep supervision is utilized to train a neural network to produce high-resolution reconstructions. These representations are used to track 3D features of the capsules, such as the ablator, inner shell, and the joint between shell hemispheres. Machine learning, supplemented by different priors, is a promising method for 3D reconstructions in ICF and x-ray radiography, in general.
1.3 μm electro‐optic silicon switch

Silicon‐based optical switches have been fabricated which rely on refractive index change induced by injected minority carriers. Multimode raised‐rib 2×2 structures are fabricated using epitaxial silicon and diffused homojunctions. The first evidence of 1.3 μm optical switching is observed.
THE COMBINATORICS OF THE r-FREE CONVOLUTION

In this paper we shall give combinatorial remarks on the r-free convolution. In particular, we shall introduce the set partition statistic on non-crossing partitions, which gives the r-free deformed moment-cumulant formula. We shall also give the probability measure of the r-free Poisson law and its moments, exactly.
Atualizações em pré-eclâmpsia - do diagnóstico ao tratamento

A pré-eclâmpsia é um diagnóstico comum mundialmente e com incidência crescente, sendo a principal causa de mortalidade materna no Brasil, principalmente quando ocorre o desenvolvimento de suas formas mais graves, a síndrome HELLP e a eclâmpsia. Esta revisão busca, na literatura médica, as atualizações mais importantes para o entendimento desta patologia, trazendo dados das principais diretrizes dos mais recentes estudos da literatura médica, no intuito de incrementar mais conhecimentos aos profissionais de saúde, visando a tomadas de condutas mais assertivas a nível de prevenção, manejo e tratamento, visando a prevenção de complicações e melhores resultados materno-fetais. Foram selecionados 49 artigos nas bases de dados: SciELO, PubMed, NCBI e capítulos de livros com definições clássicas e atuais, dentre eles artigos em português e em inglês publicados entre 2015 e 2020, incluindo também as principais e mais recentes recomendações publicadas em diretrizes. Nos últimos anos, ocorreram algumas mudanças quanto ao diagnóstico e à conduta desta patologia, a fim de sensibilizar, tratar precocemente e mudar o desfecho de muitas gestações. Desta forma, o manejo correto do quadro e a assistência materno-fetal adequada são algumas das estratégias mais importantes que irão basear os guidelines atuais envolvendo pré-eclâmpsia. De acordo com esta revisão de literatura, foram vistas que as finalidades principais dessas diretrizes mais recentes baseiam-se no controle pressórico de manutenção e de resgate, na prevenção de convulsões e na abordagem das possíveis complicações de uma forma mais ágil e adequada.
2D/3D Deep Registration Along Trajectories With Spatiotemporal Context: Application to Prostate Biopsy Navigation

Objective: The accuracy of biopsy targeting is a major issue for prostate cancer diagnosis and therapy. However, navigation to biopsy targets remains challenging due to the limitations of transrectal ultrasound (TRUS) guidance added to prostate motion issues. This article describes a rigid 2D/3D deep registration method, which provides a continuous tracking of the biopsy location w.r. t the prostate for enhanced navigation. Methods: A spatiotemporal registration network (SpT-Net) is proposed to localize the live 2D US image relatively to a previously aquired US reference volume. The temporal context relies on prior trajectory information based on previous registration results and probe tracking. Different forms of spatial context were compared through inputs (local, partial or global) or using an additional spatial penalty term. The proposed 3D CNN architecture with all combinations of spatial and temporal context was evaluated in an ablation study. For providing a realistic clinical validation, a cumulative error was computed through series of registrations along trajectories, simulating a complete clinical navigation procedure. We also proposed two dataset generation processes with increasing levels of registration complexity and clinical realism. Results: The experiments show that a model using local spatial information combined with temporal information performs better than more complex spatiotemporal combination. Conclusion: The best proposed model demonstrates robust real-time 2D/3D US cumulated registration performance on trajectories. Those results respect clinical requirements, application feasibility, and they outperform similar state-of-the-art methods. Significance: Our approach seems promising for clinical prostate biopsy navigation assistance or other US image-guided procedure.