Miracle-dz/UniFAR-FTUs huggingface dataset:
THE ULTRALUMINOUS GRB 110918A

GRB 110918A is the brightest long gamma-ray burst (GRB) detected by Konus-WIND during its almost 19 yr of continuous observations and the most luminous GRB ever observed since the beginning of the cosmological era in 1997. We report on the final Interplanetary Network localization of this event and its detailed multiwavelength study with a number of space-based instruments. The prompt emission is characterized by a typical duration, a moderate peak energy of the time-integrated spectrum, and strong hard-to-soft evolution. The high observed energy fluence yields, at z = 0.984, a huge isotropic-equivalent energy release Eiso = (2.1 ± 0.1) × 1054 erg. The record-breaking energy flux observed at the peak of the short, bright, hard initial pulse results in an unprecedented isotropic-equivalent luminosity Liso = (4.7 ± 0.2) × 1054 erg s−1. A tail of the soft γ-ray emission was detected with temporal and spectral behavior typical of that predicted by the synchrotron forward-shock model. The Swift/X-Ray Telescope and the Swift/Ultraviolet Optical Telescope observed the bright afterglow from 1.2 to 48 days after the burst and revealed no evidence of a jet break. The post-break scenario for the afterglow is preferred from our analysis, with a hard underlying electron spectrum and interstellar-medium-like circumburst environment implied. We conclude that, among the multiple reasons investigated, the tight collimation of the jet must have been a key ingredient to produce this unusually bright burst. The inferred jet opening angle of 1. °7–3. °4 results in reasonable values of the collimation-corrected radiated energy and the peak luminosity, which, however, are still at the top of their distributions for such tightly collimated events. We estimate a detection horizon for a similar ultraluminous GRB of z ∼ 7.5 for Konus-WIND and z ∼ 12 for the Swift/Burst Alert Telescope, which stresses the importance of GRBs as probes of the early Universe.
Combinatorics of lower order terms in the moment conjectures for the Riemann zeta function

Conrey, Farmer, Keating, Rubinstein and Snaith have given a recipe that conjecturally produces, among others, the full moment polynomial for the Riemann zeta function. The leading term of this polynomial is given as a product of a factor explained by arithmetic and a factor explained by combinatorics (or, alternatively, random matrices). We explain how the lower order terms arise, and clarify the dependency of each factor on the exponent $k$ that is considered. We use extensively the theory of symmetric functions and representations of symmetric groups, ideas of Lascoux on manipulations of alphabets, and a key lemma, due in a basic version to Bump and Gamburd. Our main result ends up involving dimensions of skew partitions, as studied by Olshanski, Regev, Vershik, Ivanov and others. In this article, we also lay the groundwork for later unification of the combinatorial computations for lower order terms in the moments conjectures across families of $L$-functions of unitary, orthogonal and symplectic types.
The Influence of Vitamin D Serum Concentration on Third Molar Extraction Outcome: a Pilot Study

Background: In the academic world, the debate continues on the subject of how far a lack of vitamin D can affect the healing of various wounds. Objective: To determine if basal serum levels of vitamin D significantly influence clinical parameters linked to post-extraction wound healing after surgical removal of impacted/semi-impacted third molars. Methods: A total of 23 patients were included in this study. Clinical outcome parameters were: edema, trismus, pain, soft tissue healing, and dry socket signs. The research was divided into four stages. Results: Due to the high prevalence of hypovitaminosis D (91%), patients were classified into an insufficient (≥ 20 ng/ml) or a deficient group (<20 ng/ml). The results showed no statistically significant differences in pain, edema, trismus, or soft tissue healing between those two groups. A slight statistical interaction was observed in the clinical parameters related to edema and trismus assessment, but not statistically significant. We did not notice signs of “dry socket” on any of the patients. Conclusion: Within its limitations (low number of patients, high prevalence of vitamin D deficiency), this pilot study failed to find a significant influence of serum vitamin D concentrations in wound healing or post-surgery symptom (pain, edema, trismus) development after third molar extraction. Further clinical investigations are necessary to elaborate on this function of vitamin D more precisely.
Galerkin Finite Element Process for Entropy Production and Thermal Evaluation of Third-Grade Fluid Flow: A Thermal Case Study

A fluid’s moving class improves its heat transmission capability, as well as its rigidity, owing to multivariate molecule suspension. In this way, nanofluids are superior to common fluids. In this study, we evaluated the features of ease and heat transfer. Furthermore, we investigated permeable media, heat source, variable heat conductivity, and warm irradiation results. A mathematical technique known as the Galerkin finite element (G-FEM) approach was used to solve the supervising conditions. Third-grade nanofluid (TGNF), which consists of two types of nanoparticles (NPs), single-walled carbon nanotubes (SWCNT), and multi-walled carbon nanotubes (MWCNTs) distributed in a base liquid of carboxymethyl cellulose (CMC) water, was used for this examination. The main conclusion of this study is that MWCNT-CMC nanofluid has a higher heat transfer velocity than SWCNT-CMC nanofluid. The entropy of the framework can be increased by adjusting the thermal conductivity. Additionally, we found that increasing the main volume section decreases the speed but increases the dispersion of atomic energy. In order to separately account for the development properties of inertial forces and shallow heat dispersion forces, Reynolds and Brinkman values can be used to accelerate the entropy rate of the heating framework.
Principal Components of Neural Convolution Filters

Convolutions in neural networks are still essential on various vision tasks. To develop neural convolutions, this study focuses on Structured Receptive Field (SRF), representing a convolution filter as a linear combination of widely acting designed components. Although SRF can represent convolution filters with fewer components than the number of filter bins, N-Jet, the sole component system implementation, requires ten trainable parameters per filter to improve accuracy even for $3 \times 3$ convolutions. Hence, we aim to formulate a new component system for SRF that can represent valid filters with fewer components. Our component system named “OtX” is based on the Principal Component Analysis of well-trained filter weights because the extracted components will also be principal for neural convolution filters. In addition to proposing the component system, we develop a component scaling method to defuse massive scale differences among the coefficients in a linear combination of OtX components. In the experimental section, we train image classification models on CIFAR-100 dataset under the hyperparameters tuned for the original models with the standard convolutions. For NFNet-F0 classifier, OtX with six components performs 0.5% better than the standard convolution, 3.1% better than N-Jet with six components, and only 0.1% worse than N-Jet with ten components. Besides, OtX with nine components provides stabler training than N-Jet, performing 0.5% better than the standard for NFNet-F0. OtX suits when replacing standard convolutions because OtX performs at least comparably against N-Jet with further parameter efficiency and training stability.
Modeling the Reserve Capacity of Wind Power and the Inherent Decision-Dependent Uncertainty in the Power System Economic Dispatch

The ever-increasing penetration of renewable generation is demanding additional flexibility for the operation of power systems. In this sense, it has been proved that wind power generators (WPGs) can provide part of the required operating reserve through pitch angle control (PAC) under a deloaded strategy. Unlike conventional operating reserve sources, however, the operating reserve provided by WPGs can't always be considered reliable, which renders the power system dispatch more challenging. In this research, the reserve capacity of the WPGs is modeled considering the decision-dependent uncertainty (DDU). The random wind speed introduces uncertainty to the available reserve capacity of the WPGs while the decisions on the deloading degrees of the WPGs directly affect their coefficients between wind speed and usable wind power, making the uncertainty decision-dependent. Moreover, the operational technical limits of the WPGs and the multiple possible wind speed scenarios are also considered in the wind power reserve capacity modeling. Then, a two-stage reliability constrained stochastic economic dispatch model with WPGs’ reserve provision (SED-WRP) is developed to jointly dispatch the generation and reserve. A group-based multi-cut Benders decomposition method is applied to improve the convergence performance of the solution algorithm. Case studies are solved to quantify the impact of considering the reserve provision of WPGs and the inherent DDU in power system dispatch decisions.
A chain of strongly correlated SU(2)_4 anyons: Hamiltonian and Hilbert space of states

One-dimensional lattice model of SU(2)_{4} anyons containing a transition into the topological ordered phase state is considered. An effective low-energy Hamiltonian is found for half-integer and integer indices of the type of strongly correlated non-Abelian anyons. The Hilbert state space properties in the considered modular tensor category are studied.
Bit extraction, hard-core predicates and the bit security of RSA

This thesis presents results on bit security and bit extraction. 1. A function b(·) is called secure or a hard-core function for a given function f(·), if for all probabilistic polynomial time algorithms, the information f(x) does not significantly aid in distinguishing b(x) from a random string of the same length. The benefit of studying hard-core functions is that they provide insight to the security of cryptosystems and means to construct pseudo-random generators. 2. The bit extraction problem is the problem of transforming n independent, identically biased, {−1, 1}-valued random variables, X1, . , Xn into a single {−1, 1} value, b(X1, . . . , Xn), so that this result is as unbiased as possible. (A {−1, 1} random variable Xi has bias β if E[Xi] = β.) In general, no function b produces a completely unbiased result. We perform the first study of the relationship between the bias β of these Xi and the rate at which b(X1, . . . , Xn) can converge to an unbiased {−1, 1} random variable as n→∞. Although our main interest in this problem is information theoretic, the access to true random bits is a primary tool in computer science and many other research areas. Since one does not always have access to a perfect (unbiased) random source, it may be necessary to simulate such. The first problem is considered in a purely complexity theoretic setting, whereas as mentioned, the second is mainly studied from an information theoretic point of view. For problem 1, we demonstrate the following results. • We consider the case when f is any one-way function and where h is chosen randomly from a family of strong universal hash functions, and b(x) is one (or more) bit(s) in the binary representation of h(x). We study the two families: – Affine functions on GF[2] (n = blog2(x)c + 1). – Affine functions on Zp, p an Ω(n)-bit prime. We show individual security for all bits in both cases, and both types of functions are also shown to have O(log n) bits that are simultaneously secure. • Next, we study the case when f(x) = EN (x) is RSA encryption and b(x) is a single bit in the binary representation of x. We show that given EN (x), predicting any single bit in x with non-negligible advantage over the trivial guessing strategy, is (through a polynomial time reduction) as hard as breaking RSA.
Impressive Remodeling of the Fractured Femur with Transposition of the Fractured Parts, Treated Conservatively with skin Traction, in a 3-Year-Old Boy

Introduction: Conservative management of femoral fractures in children in the preschool age is considered as the standard care. In the past years, there is an increase in the number of surgically treated children with IM nails, even in these young ages. Several papers report on the results comparing the final alignment of the fractures but there are no reports on the conservative treatment of a fracture with transposition of the fragments. Case Report: A 3-year-old boy was referred in our hospital with a spiral fracture of his right femur. There was transposition of the fragments, with the proximal part shifted medially and the distal part laterally. We informed the parents for the methods of treatment available for his fracture. After 1 week of hospitalization, the child was transferred home, with skin traction, with supervision of an orthopedic surgeon. The child was regularly evaluated with radiological examination, every 10 days. There was an uneventful healing of the fracture, with normal alignment of the leg and acceptable initial leg length discrepancy (LLD). One year after the fracture, there is an impressive remodeling of the fracture with restoration of the medullary canal and absent LLD. Conclusion: Conservative treatment of spiral fracture in a child younger than 3 years is an effective method. Remodeling in this young age can restore not only deviations on the frontal and sagittal plane but also correct the transposition of the fragments with restoration of the medullary canal.
The effect of electron interactions on the universal properties of systems with optimized intrinsic off-resonant hyperpolarizability

Because of the potentially large number of important applications of nonlinear optics, researchers have expended a great deal of effort to optimize the second-order molecular nonlinear-optical response, called the hyperpolarizability. The focus of our present studies is the {\em intrinsic} hyperpolarizability, which is a scale-invariant quantity that removes the effects of simple scaling, thus being the relevant quantity for comparing molecules of varying sizes. Past theoretical studies have focused on structural properties that optimize the intrinsic hyperpolarizability, which have characterized the structure of the quantum system based on the potential energy function, placement of nuclei, geometry, and the effects of external electric and magnetic fields. Those previous studies focused on single-electron models under the influence of an average potential. In the present studies, we generalize our calculations to two-electron systems and include electron interactions. As with the single-electron studies, universal properties are found that are common to all systems -- be they molecules, nanoparticles, or quantum gases -- when the hyperpolarizability is near the fundamental limit.
Will I See Faces Like Mine?: Exploring Perceived Constraints to Outdoor Recreation Experiences at an HBCU

The purpose of this qualitative study was to explore perceived constraints of structured outdoor recreation experiences for students attending a Historically Black College/University (HBCU). Data were collected from four focus group sessions. Grounded Theory was used to analyze the data and from an analysis of data, four themes emerged: 1. Family impact, 2. Companionship, 3. Social media and technology, and 4. HBCU and Black American cultures. This study confirmed the importance of social companionship and the need for relevant marketing strategies as motivators for Black student participation in outdoor recreation activities at this HBCU. A common thread among the groups, was the perception of Whiteness in outdoor spaces and its negative impact on outdoor recreation involvement.
Triggers for displaced decays of long-lived neutral particles in the ATLAS detector

A set of three dedicated triggers designed to detect long-lived neutral particles decaying throughout the ATLAS detector to a pair of hadronic jets is described. The efficiencies of the triggers for selecting displaced decays as a function of the decay position are presented for simulated events. The effect of pile-up interactions on the trigger efficiencies and the dependence of the trigger rate on instantaneous luminosity during the 2012 data-taking period at the LHC are discussed.
Analysis of inputs variability on rice growth stages in Mbeya region

As rice develops from sowing to harvesting stages require a combination of both natural and non-natural inputs. Thus, at every stage, specific proportions are demanded as aggregates which contribute to the final yields. Understanding these inputs and their impacts on rice yield will help the small scale rice farmers in Tanzania to boost rice yields. This study pursues to (i) characterize rice farmers’ in Mbeya Region of Tanzania; (ii) estimate parameters for factors affecting rice along the phenological stages and their influences on growth and yield; and (iii) disclose the perceived factors affecting rice production. Data collected through structured questionnaires, interviews and focus discussions. Data analyses were done by descriptive statistics, Garret ranking techniques, and the Translog Cobb Douglas (CD) model. The descriptive results indicated majority of respondents had ages between 45 and 50 years; only 3% of respondents had informal education and 80% of them own farm size of from 1 to 3 acres. Empirical results show that labour, fertilizer, seeds quantity, pesticide cost, floods, and sunshine duration significantly influenced rice yield. Rainfall was the most influential factors as perceived by farmers. Based on these current findings, suggestions were provided to the responsible policymakers to work on utilizing the potential available from the identified major influential factors to increase farmers' income and increase food security.
An introduction to the theory of superfluidity

A classic from 1965, this book covers the main aspects of the theory of quantum liquids, including the elementary excitation spectrum, hydrodynamics, and kinetic phenomena. The book requires no special training and assumes only general knowledge of the fundamentals of theoretical physics. It was developed from studies at the Institute of Physical Problems of the U.S.S.R. Academy of Sciences and can be used as a guide for professors teaching quantum liquid theory or as a text for graduate students.
Measurements of mixing and indirect CP violation

LHCb has collected the world's largest sample of charmed hadrons. This sample is used to measure the mixing parameters in the $D^0$-$\bar{D}^0$ system and to search for indirect $CP$ violation. This contribution focuses on measurements of $A_{\Gamma}$ with $D^*$ and semileptonic $B$ decays and on mixing measurements and a search for $CP$ violation in $D\to K\pi$ decays.
Antibacterial effects of oak bark (Quercus robur) and heather herb (Calluna vulgaris L.) extracts against the causative bacteria of bovine mastitis

Background and Aim: Bovine mastitis has a negative impact on animals, and improper antibiotic use has caused an increase in bacterial resistance. Therefore, medicinal plants could serve as an alternative treatment for this condition. Polyphenols have potential as antibiotic agents. Oak bark has long been used as a medicine and has shown antibacterial effects. Moreover, research on heather plant demonstrated that it has antibacterial properties. This study aimed to assess the antibacterial effects of oak (Quercus robur) bark and heather (Calluna vulgaris L.) herb extracts against common bovine mastitis pathogens. Materials and Methods: Dried oak bark and heather herb were used to prepare extracts using 30%, 50%, and 70% ethanol and acetone as solvents. Their polyphenol content was determined using the Folin–Ciocalteu method. Bovine mastitis-inducing clinical isolates of Escherichia coli, Streptococcus agalactiae, Streptococcus uberis, Serratia liquefaciens, Staphylococcus aureus, and reference cultures of S. aureus and E. coli were used for antibacterial tests. All extracts were screened through a disk diffusion test to ascertain their antibacterial effects, and the minimum inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) were determined for the most effective extracts. Results: Oak bark extracts had variable antibacterial effects against S. aureus and Streptococcus strains, but no statistically significant difference was observed in activity against E. coli. The disk diffusion test showed that the oak bark extracts obtained using acetone and ethanol at 30% yielded the best results. However, the 70% acetone oak extract alone affected all types of bacteria. Further antibacterial tests of 70% acetone and 30% ethanol oak extracts revealed that the lowest MIC and MBC scores were against S. aureus strains and E. coli reference cultures. Conversely, the heather herb extracts exhibited broader activity against all types of bacteria, although better results were observed against Gram-positive bacteria. There was also a negative correlation between solvent concentration and antibacterial effect (p < 0.05, r = −0.507). The highest inhibition zone scores and broadest spectrum were observed in samples prepared in 30% ethanol. There was no statistically significant correlation between the phenolic content of plants and their antibacterial effects. Conclusion: Oak bark and heather extracts could be used as potential antibacterial agents against bovine mastitis pathogens.
Lightweight and Parameter-Optimized Real-Time Food Calorie Estimation from Images Using CNN-Based Approach

Automated object identification has seen significant progress during the last decade with close to human-level accuracy, aided by deep learning methods. With the rapid rise of obesity and other lifestyle-related diseases worldwide, the availability of fast, automated, and reliable image-based food calorie estimation is becoming a necessity. With the help of a deep learning-based automated object identification system, it is possible to introduce accurate and intelligent solutions in the form of a mobile app. However, for these kind of applications, processing speed is an important concern as the images should be processed in real time. Although plenty of studies have been conducted that focus on food image detection-based calorie estimation, there is still a lack of an image-driven, lightweight, fast, and reliable food calorie estimation system. In this paper, we propose a method based on the parameter-optimized Convolution Neural Networks (CNN) for detecting food images of regular meals using a handheld camera. Once identification process of the food items are complete, the corresponding calories and nutritional facts can be calculated using prior knowledge about the food class. Through our findings, we demonstrate that our proposed approach ensures high accuracy and can significantly simplify the existing manual calorie estimation procedures by converting them into a real-time automated process.