Miracle-dz/UniFAR-FTUs huggingface dataset:
Examination of the TIGIT-CD226-CD112-CD155 Immune Checkpoint Network during a Healthy Pregnancy

Background: The importance of immune checkpoint molecules is well known in tumor and transplantation immunology; however, much less information is available regarding human pregnancy. Despite the significant amount of information about the TIGIT and CD226 immune checkpoint receptors in immune therapies, very little research has been conducted to study the possible role of these surface molecules and their ligands (CD112 and CD155) during the three trimesters of pregnancy. Methods: From peripheral blood, immune cell subpopulations were studied, and the surface expression of immune checkpoint molecules was analyzed by flow cytometry. Soluble immune checkpoint molecule levels were measured by ELISA. Results: Notable changes were observed regarding the percentage of monocyte subpopulation and the expression of CD226 receptor by CD4+ T and NKT cells. Elevated granzyme B content by the intermediate and non-classical monocytes was assessed as pregnancy proceeded. Furthermore, we revealed an important relationship between the CD226 surface expression by NKT cells and the serum CD226 level in the third trimester of pregnancy. Conclusions: Our results confirm the importance of immune checkpoint molecules in immunoregulation during pregnancy. CD226 seems to be a significant regulator, especially in the case of CD4+ T and NKT cells, contributing to the maternal immune tolerance in the late phase of pregnancy.
KSC2: An Industrial-Scale Open-Source Kazakh Speech Corpus

We present the first industrial-scale open-source Kazakh speech corpus for automatic speech recognition research and development. Our corpus subsumes two previously presented corpora: 1) Kazakh speech corpus (KSC) and 2) Kazakh text-to-speech 2 (KazakhTTS2). We also provide additional data from other sources, including television news, television and radio programs, parliament speeches, and podcasts. Our corpus, which we have named KSC2, contains over a thousand hours of high-quality transcribed data, which is triple the size of KSC. KSC2 was manually transcribed with the help of native Kazakh speakers and validated via preliminary speech recognition experiments on various evaluation sets. Moreover, it contains utterances with Kazakh-Russian code-switching, a conversational practice common among Kazakh speakers. We believe that our corpus will facilitate speech processing research for Kazakh, which is widely considered an under-resourced language. To ensure the reproducibility of experiments, we share the KSC2 corpus, training recipes, and pretrained models 1 .
Calibrating cosmological radiative transfer simulations with Ly α forest data: evidence for large spatial UV background fluctuations at z ∼ 5.6–5.8 due to rare bright sources

We calibrate here cosmological radiative transfer simulation with ATON/RAMSES with a range of measurements of the Lyman alpha opacity from QSO absorption spectra. We find the Lyman alpha opacity to be very sensitive to the exact timing of hydrogen reionisation. Models reproducing the measured evolution of the mean photoionisation rate and average mean free path reach overlap at z ~ 7 and predict an accelerated evolution of the Lyman alpha opacity at z > 6 consistent with the rapidly evolving luminosity function of Lyman alpha emitters in this redshift range. Similar to "optically thin" simulations our full radiative transfer simulations fail, however, to reproduce the high-opacity tail of the Lyman alpha opacity PDF at z > 5. We argue that this is due to spatial UV fluctuations in the post-overlap phase of reionisation on substantially larger scales than predicted by our source model, where the ionising emissivity is dominated by large numbers of sub-L* galaxies. We further argue that this suggests a significant contribution to the ionising UV background by much rarer bright sources at high redshift.
Catalytic Performance and Sulfur Dioxide Resistance of One-Pot Synthesized Fe-MCM-22 in Selective Catalytic Reduction of Nitrogen Oxides with Ammonia (NH3-SCR)—The Effect of Iron Content

The catalytic performance of Fe-catalysts in selective catalytic reduction of nitrogen oxides with ammonia (NH3-SCR) strongly depends on the nature of iron sites. Therefore, we aimed to prepare and investigate the catalytic potential of Fe-MCM-22 with various Si/Fe molar ratios in NH3-SCR. The samples were prepared by the one-pot synthesis method to provide high dispersion of iron and reduce the number of synthesis steps. We have found that the sample with the lowest concentration of Fe exhibited the highest catalytic activity of ca. 100% at 175 °C, due to the abundance of well-dispersed isolated iron species. The decrease of Si/Fe limited the formation of microporous structure and resulted in partial amorphization, formation of iron oxide clusters, and emission of N2O during the catalytic reaction. However, an optimal concentration of FexOy oligomers contributed to the decomposition of nitrous oxide within 250–400 °C. Moreover, the acidic character of the catalysts was not a key factor determining the high conversion of NO. Additionally, we conducted NH3-SCR catalytic tests over the samples after poisoning with sulfur dioxide (SO2). We observed that SO2 affected the catalytic performance mainly in the low-temperature region, due to the deposition of thermally unstable ammonium sulfates.
Computer Methods and Programs in Biomedicine

Background and Objective: Chest X-ray imaging is a relatively cheap and accessible diagnostic tool that can assist in the diagnosis of various conditions, including pneumonia, tuberculosis, COVID-19, and others. However, the requirement for expert radiologists to view and interpret chest X-ray images can be a bottleneck, especially in remote and deprived areas. Recent advances in machine learning have made possible the automated diagnosis of chest X-ray scans. In this work, we examine the use of a novel Transformer-based deep learning model for the task of chest X-ray image classiﬁcation. Methods: We ﬁrst examine the performance of the Vision Transformer (ViT) state-of-the-art image clas-siﬁcation machine learning model for the task of chest X-ray image classiﬁcation, and then propose and evaluate the Input Enhanced Vision Transformer (IEViT), a novel enhanced Vision Transformer model that can achieve improved performance on chest X-ray images associated with various pathologies. Results: Experiments on four chest X-ray image data sets containing various pathologies (tuberculosis, pneumonia, COVID-19) demonstrated that the proposed IEViT model outperformed ViT for all the data sets and variants examined, achieving an F1-score between 96.39% and 100%, and an improvement over ViT of up to +5.82% in terms of F1-score across the four examined data sets. IEViT’s maximum sensitivity (recall) ranged between 93.50% and 100% across the four data sets, with an improvement over ViT of up to +3%, whereas IEViT’s maximum precision ranged between 97.96% and 100% across the four data sets, with an improvement over ViT of up to +6.41%. Conclusions: Results showed that the proposed IEViT model outperformed all ViT’s variants for all the examined chest X-ray image data sets, demonstrating its superiority and generalisation ability. Given the relatively low cost and the widespread accessibility of chest X-ray imaging, the use of the proposed IEViT model can potentially offer a powerful, but relatively cheap and accessible method for assisting diagnosis using chest X-ray images.
Communications and Cryptography: Two Sides of One Tapestry

Block Coding. On a Problem of Persi Diaconis E. Berlekamp. A Finite Fourier Transform for Vectors of Arbitrary Length C.G. Gunther. Massey's Theorem and the Golay Codes R.E. Blahut. Spherical Codes from the Hexagonal Lattice T. Ericson, V. Zinoviev. On Group Codes generated by Finite Reflection Groups T. Mittelholzer. Using Redundancy to speed up Disk Arrays D.L. Cohn, R.L. Stevenson. A Comparison of Error Patterns corrected by Block Codes and Convolutional Codes J. Justesen. Coded MPSK Modulation for the AWGN and Rayleigh Fading Channels S. Lin, S, Rajpal, D.J. Rhee. On the Basic Averaging Arguments for Linear Codes H.A. Loeliger. Coding and Multiplexing H.J. Matt. Convolutional Coding. Duality of Linear Input-Output Maps S.K. Mitter. Inverses of Linear Sequential Circuits: On Beyond Poles and Zeros M.K. Sain. Trellises Old and New G.D. Forney, Jr. On Canonical Encoding Matrices and the Generalized Constraint Lengths of Convolutional Codes R. Johannesson, Z. Wan. On Code Linearity and Rotational Invariance for a Class of Trellis Codes for M-PSK L.H. Zetterberg. Progress towards Achieving Channel Capacity D.J. Costello, L. Perez. Soft is better than Hard J. Hagenauer. Charge Constrained Convolutional Codes M.A. Herro, R.H. Deng, Y.X. Li. Five Views of Differential MSK: a Unified Approach B. Rimoldi. Binary Convolutional Codes Revisited G. Ungerboeck. Cryptography. Development of Fast Multiplier Structures with Cryptographic Applications G. Agnew. On Repeated-Single-Root Constacyclic Codes V.C. da Rocha, Jr. Delay Estimation for Truly Random Binary Sequences or How to Measure the Length of Rip van Winkle's Sleep I.Ingemarsson. Low Weight Parity Checks for Linear Recurring Sequences G. Kuehn. Higher Order Derivatives and Differential Cryptanalysis X. Lai. The Strong Secret Key Rate of Discrete Random Triples U.M. Maurer. International Commercial Standards in Cryptography J. Omura. The Self-Shrinking Generator W. Meier, O. Staffelbach. Models for Adder Channels I. Bar-David. Coding for Adder Channels I.F. Blake. Information Theory. Orthogonal Checksets in the Plane and Enumerations of the Rationals modp P. Elias. An Inequality on the Capacity Region of Multiaccess Multipath Channels R.G. Gallager. On the Performance of Aperiodic Inverse Filter J. Ruprecht. Capacity of a Simple Stable Protocol for Short Message Service over a CDMA Network A.J. Viterbi. Random Time and Frequency Hopping for Infinite User Population S. Csibi. Multiple Access Collision Channel without Feedback and User Population L. Gyorfi. Messy Broadcasting in Networks R. Ahlswede, H.S. Haroutunian, L.H. Khachatrian. Stochastic Events H. Ohnsorge. Leaf-Average Node-Sum Interchanges in Rooted Trees with Applications R.A. Rueppel, J.L. Massey. Some Reflections on the Interference Channel E.C. van der Meulen. The Sliding-Window Lempel-Ziv Algorithm is Asymptotically Optimal A.D. Wyner, J. Ziv.
Deep Self-Supervised Learning of Speech Denoising from Noisy Speeches

In the last few years, unsupervised learning methods have been proposed in speech denoising by taking advantage of Deep Neural Networks (DNNs). The reason is that such unsupervised methods are more practical than the supervised counterparts. In our scenario, we are given a set of noisy speech data, where any two data do not share the same clean data. Our goal is to obtain the denoiser by training a DNN based model. Using the set, we train the model via the following two steps: 1) From the noisy speech data, construct another noisy speech data via our proposed masking technique. 2) Minimize our proposed loss deﬁned from the DNN and the two noisy speech data. We evaluate our method using Gaussian and real-world noises in our numerical experiments. As a result, our method outperforms the state-of-the-art method on average for both noises. In addition, we provide the theoretical explanation of why our method can be efﬁcient if the noise has Gaussian distribution.
A better estimator of population mean with power transformation based on ranked set sampling

Ranked set sampling (RSS) was first suggested by McIntyre (1952) to increase the efficiency of estimate of the population mean. It has been shown that this method is highly beneficial to the estimation based on simple random sampling (SRS). There has been considerable development and many modifications were done on this method. This paper presents a modified ratio estimator using prior value of coefficient of kurtosis of an auxiliary variable x, with the intention to improve the efficiency of ratio estimator in ranked set sampling. The first order approximation to the bias and mean square error (MSE) of the proposed estimator are obtained. A generalized version of the suggested estimator by applying the Power transformation is also presented.
Pressure-induced superconductivity in WTe2

Tungsten ditelluride (WTe2) is emerging in interest due to its titanic unsaturated magnetoresistance and two dimensional atomic structures. Here we report the first successful observation of pressure-induced superconductivity in WTe2. We identify a dome-shaped superconducting phase in the pressure-temperature space: superconductivity sharply appears at the pressure of 2.5 GPa where it quickly reaches a maximum critical temperature of Tc=7 K at around 16.8 GPa, followed by a gradual decrease in Tc with increasing pressure. Theoretical calculations suggest that pressure significantly enlarges the density of states at the Fermi level (N(EF)), which may account for the emergence of superconductivity. The possible structural instability may be responsible for the decrease of Tc in the high pressure region.
The socket shield technique and its complications, implant survival rate, and clinical outcomes: a systematic review

Purpose The aim of this systematic review was to evaluate the effectiveness of the socket shield technique (SST), an innovative surgical method introduced in 2010, for reducing buccal bone plate resorption. Methods The review was conducted following the PRISMA guidelines. Clinical studies conducted in humans and investigating the SST were searched on PubMed (MEDLINE), Embase, Web of Knowledge, and Google Scholar in November and December 2021. The implant survival rate, percentage of complications, and clinical parameters (marginal bone loss [MBL], pink esthetic score [PES], and buccal bone plate resorption [BBPR]) were analyzed using the collected data. Results The initial search resulted in 132 articles. After article screening, the full texts of 19 studies were read and 17 articles were finally included in the review. In total, 656 implants were installed with the SST. Nine of the 656 implants experienced failure, resulting in an implant survival rate of 98.6%. The percentage of complications was about 3.81%. The analysis of clinical parameters (MBL, PES, and BBPR), showed favorable results for the SST. The mean MBL in implants placed with the SST was 0.39±0.28 mm versus 1.00±0.55 mm in those placed without the SST. PES had a better outcome in the SST group, with an average of 12.08±1.18 versus 10.77±0.74. BBPR had more favorable results in implants placed with the SST (0.32±0.10 mm) than in implants placed with the standard technique (1.05±0.18 mm). Conclusions The SST could be considered beneficial for preserving the buccal bone plate. However, since only 7 of the included studies were long-term randomized controlled trials comparing the SST with the standard implant placement technique, the conclusions drawn from this systematic review should be interpreted with caution. Trial Registration PROSPERO Identifier: CRD42020180637
Circuit quantum electrodynamics

Circuit Quantum Electrodynamics (cQED), the study of the interaction between superconducting circuits behaving as artificial atoms and 1-dimensional transmission-line resonators, has shown much promise for quantum information processing tasks. For the purposes of quantum computing it is usual to approximate the artificial atoms as 2-level qubits, and much effort has been expended on attempts to isolate these qubits from the environment and to invent ever more sophisticated control and measurement schemes. Rather than focussing on these technological aspects of the field, this thesis investigates the opportunities for using these carefully engineered systems for answering questions of fundamental physics.
Life Span Motor Development

Chapter 1. Fundamental Concepts Chapter 2. Theoretical Perspectives in Motor Development Chapter 3. Principles of Motion and Stability Chapter 4. Physical Growth, Maturation, and Aging Chapter 5. Development and Aging of Body Systems Chapter 6. Early Motor Development Chapter 7. Development of Human Locomotion Chapter 8. Development of Ballistic Skills Chapter 9. Development of Manipulative Skills Chapter 10. Sensory-Perceptual Development Chapter 11. Perception and Action in Development Chapter 12. Social and Cultural Constraints in Motor Development Chapter 13. Psychosocial Constraints in Motor Development Chapter 14. Knowledge As Functional Constraint in Motor Development Chapter 15. Development of Cardiorespiratory Chapter 16. Development of Strength and Flexibility Chapter 17. Development of Body Composition Chapter 18. Conclusion: Interactions Among Constraints.
MaterialBERT for natural language processing of materials science texts

ABSTRACT A BERT (Bidirectional Encoder Representations from Transformers) model, which we named “MaterialBERT”, has been generated using scientific papers in wide area of material science as a corpus. A new vocabulary list for tokenizer was generated using material science corpus. Two BERT models with different vocabulary lists for the tokenizer, one with the original one made by Google and the other newly made by the authors, were generated. Word vectors embedded during the pre-training with the two MaterialBERT models reasonably reflect the meanings of materials names in material-class clustering and in the relationship between base materials and their compounds or derivatives for not only inorganic materials but also organic materials and organometallic compounds. Fine-tuning with CoLA (The Corpus of Linguistic Acceptability) using the pre-trained MaterialBERT showed a higher score than the original BERT. The two MaterialBERTs could be also utilized as a starting point for transfer learning of a narrower domain-specific BERT. GRAPHICAL ABSTRACT
Integrated photometric parameters of open and globuler clusters

In this work we have discussed UBV parameters of 142 galactic clusters and 32 globular clusters. Comparison of the integrated parameters of galactic clusters with theoretical ones confirms the validity of the basic assumptions about the stars, which have been used to calculate the theoretical parameters. Evolutionary effects on integrated parameters of open clusters have also been discussed.
Radiative lifetimes in B I using ultraviolet and vacuum-ultraviolet laser-induced fluorescence

Radiative lifetimes of the eight lowest even parity levels in the doublet system of B I are measured using time-resolved laser-induced fluorescence in the UV and VUV on an atomic beam of boron. The accurate lifetimes provide a base for improved determination of absolute transition probabilities in B I. The techniques described are broadly applicable to measurement of lifetimes of levels with transitions in the visible, UV, and VUV in almost any element.
The f-vector of a realizable matroid complex is strictly log-concave

We show that f-vectors of matroid complexes of realizable matroids are strictly log-concave. This was conjectured by Mason in 1972. Our proof uses the recent result by Huh and Katz who showed that the coefficients of the characteristic polynomial of a realizable matroid form a log-concave sequence. We also prove a statement on log-concavity of h-vectors which strengthens a result by Brown and Colbourn. In the last two sections, we give a brief introduction to zonotopal algebra and we explain how it relates to our log-concavity results and various matroid/graph polynomials.
METHODS OF DIFFERENTIAL GEOMETRY IN CLASSICAL FIELD THEORIES: K-SYMPLECTIC AND K-COSYMPLECTIC APPROACHES

A Review of Hamiltonian and Lagrangian Mechanics: Hamiltonian and Lagrangian Mechanics k-Symplectic Formulation of Classical Field Theories: k-Symplectic Geometry k-Symplectic Formalism Hamiltonian Classical Field Theory Hamilton-Jacobi Theory in k-Symplectic Field Theories Lagrangian Classical Field Theories Examples k-Cosymplectic Formulation of Classical Field Theories: k-Cosymplectic Geometry k-Cosymplectic Formalism Hamiltonian Classical Field Theories Hamilton-Jacobi Equation Lagrangian Classical Field Theories Examples k-Symplectic Systems versus Autonomous k-Cosymplectic Systems Relationship between k-Symplectic and k-Cosymplectic Approaches and the Multisymplectic Formalism: Multisymplectic Formalism Appendices: Symplectic Manifolds Cosymplectic Manifolds Glossary of Symbols
The Burden of Carbohydrates in Health and Disease

Foods high in carbohydrates are an important part of a healthy diet, since they provide the body with glucose to support bodily functions and physical activity. However, the abusive consumption of refined, simple, and low-quality carbohydrates has a direct implication on the physical and mental pathophysiology. Then, carbohydrate consumption is postulated as a crucial factor in the development of the main Western diseases of the 21st century. We conducted this narrative critical review using MedLine (Pubmed), Cochrane (Wiley), Embase, and CinAhl databases with the MeSH-compliant keywords: carbohydrates and evolution, development, phylogenetic, GUT, microbiota, stress, metabolic health, consumption behaviors, metabolic disease, cardiovascular disease, mental disease, anxiety, depression, cancer, chronic kidney failure, allergies, and asthma in order to analyze the impact of carbohydrates on health. Evidence suggests that carbohydrates, especially fiber, are beneficial for the well-being and growth of gut microorganisms and consequently for the host in this symbiotic relationship, producing microbial alterations a negative effect on mental health and different organic systems. In addition, evidence suggests a negative impact of simple carbohydrates and refined carbohydrates on mood categories, including alertness and tiredness, reinforcing a vicious circle. Regarding physical health, sugar intake can affect the development and prognosis of metabolic disease, as an uncontrolled intake of refined carbohydrates puts individuals at risk of developing metabolic syndrome and subsequently developing metabolic disease.
Road User Exposure from ITS-5.9 GHz Vehicular Connectivity

This study addressed an important but not yet thoroughly investigated topic regarding human exposure to radio-frequency electromagnetic fields (RF-EMF) generated by vehicular connectivity. In particular, the study assessed, by means of computational dosimetry, the RF-EMF exposure in road users near a car equipped with vehicle-to-vehicle (V2V) communication antennas. The exposure scenario consisted of a 3D numerical model of a car with two V2V antennas, each fed with 1 W, operating at 5.9 GHz and an adult human model to simulate the road user near the car. The RF-EMF dose absorbed by the human model was calculated as the specific absorption rate (SAR), that is, the RF-EMF power absorbed per unit of mass. The highest SAR was observed in the skin of the head (34.7 mW/kg) and in the eyes (15 mW/kg); the SAR at the torso (including the genitals) and limbs was negligible or much lower than in the head and eyes. The SAR over the whole body was 0.19 mW/kg. The SAR was always well below the limits of human exposure in the 100 kHz–6 GHz band established by the International Commission on Non-Ionizing Radiation Protection (ICNIRP). The proposed approach can be generalized to assess RF-EMF exposure in different conditions by varying the montage/number of V2V antennas and considering human models of different ages.