Miracle-dz/UniFAR-FTUs huggingface dataset:
Vibration-Rotation Bands and Molecular Structure of Allene

Some parallel vibration-rotation bands of allene and allene-d4 between 3–5. 2μ have been resolved, and values have been obtained for the rotational constants. The values of B0 for the two isotopic molecules are 0.2974 cm−1 and 0.2313 cm−1, and in both cases DJ is not greater than about 10−8 cm−1. From these values rCC=1.30A, which is lower than rCC in ethylene, but close to the value found spectroscopically in ketene. Some earlier results of Eyster for a parallel band of allene have been reconsidered and reasons for the different value of B0 found by him have been suggested.
Antecedents and Consequences of Banking Customers’ Behavior towards Social Media: Evidence from an Emerging Economy

Due to the aggressive competitive climate in practically every sector, modern firms in the digital age confront a variety of hurdles for survival and growth. Technology, mainly digital technology, has altered global business practices. To stay ahead of their competitors, marketers need to develop new strategies that make use of digital technology. Using more conventional forms of competition will not result in spectacular outcomes. In this respect, the rise of social media is a game-changer in marketing since it provides marketers with a strategic touchpoint to engage customers with a brand. Still, it is also important to note the customer’s attitude towards social media. Previous studies have, for the most part, ignored the connection between programs involving corporate social responsibility (CSR) and positive experiences for customers. As a result, the current study intends to evaluate the relationship between customer-related CSR activities on social media, customer attitude towards social media, and consumer behavioral outcomes, such as purchase intentions (PI) and electronic word of mouth (E-WOM). Information was collected from banking customers in a developing economy and evaluated with Smart PLS 4.0. According to the findings, customer-related corporate social responsibility activities carried out on social media have an effect on attitudes toward social media, customer behavioral outcomes, such as electronic word of mouth (E-WOM), and buying intentions. The findings also show that a consumer’s feelings toward a brand can bridge the gap between customer-related CSR, E-WOM, and purchase intentions. The current study’s outcomes can help policymakers comprehend the value of CSR practices from the standpoint of marketing, which is something that most CSR researchers overlook.
Iterative Doubly-spread Channel Estimation based on Reinforcement Learning for Underwater Acoustic Communication

Underwater acoustic (UWA) channels are usually featured with long delay spreads, significant Doppler effects and time-varying nature, due to internal waves, platform and sea-surface motion. Reinforcement learning (RL) is a feedback-based machine learning technique where an intelligent agent (computer program) can perceive and interpret the environment, take actions and learn through trials and errors. It motives us to use the RL to perceive the underwater acoustic environment, thus estimate the variation of the UWA channels. Therefore, we propose a channel estimation method based on the RL, we can estimate the time-varying Doppler scaler and multipath sparsity through interacting with the UWA channels with an iterative structure. Experimental results demonstrate the performance superiority of the proposed method over existing channel estimation methods.
One-Carbon and Polyamine Metabolism as Cancer Therapy Targets

Cancer metabolic reprogramming is essential for maintaining cancer cell survival and rapid replication. A common target of this metabolic reprogramming is one-carbon metabolism which is notable for its function in DNA synthesis, protein and DNA methylation, and antioxidant production. Polyamines are a key output of one-carbon metabolism with widespread effects on gene expression and signaling. As a result of these functions, one-carbon and polyamine metabolism have recently drawn a lot of interest for their part in cancer malignancy. Therapeutic inhibitors that target one-carbon and polyamine metabolism have thus been trialed as anticancer medications. The significance and future possibilities of one-carbon and polyamine metabolism as a target in cancer therapy are discussed in this review.
Chronic ankle instability and associated factors in the general population: a pilot study

Introduction: Acute ankle sprains have a high recurrence rate associated with the development of chronic ankle instability (CAI). However, such damage can be ameliorated by understanding the contributing factors. Therefore, this study investigated the relationship between the associated independent factors and chronic instability. Material and methods: This cross-sectional study included 273 volunteers (F/M: 175/98, mean age, 34.4 ± 13.2 years; range, 18–78). Data was collected by a structured two-part questionnaire: (1) sociodemographic features, viz. age, gender, height, weight, dominant side, type and duration of physical activity, presence of chronic medical problems, and (2) general health conditions, viz. history of operation and trauma, number of painful regions, intensity, duration, of foot and ankle). Subjects are classified as having CAI with a Cumberland Ankle Instability Tool (CAIT) score ≤ 27. Results: The mean CAIT score was significantly lower in women than men. For both sides, the lowest CAIT scores were demonstrated by subjects with a Body Mass Index (BMI) ≥ 30.0 (p < 0.05). The total number of painful areas bila - terally, pain level, and CAIT score of the opposite ankle were determined as predictive factors of CAI (Right: R2 = 0.54
Impact Factors in Chinese Construction Enterprises’ Carbon Emission-Reduction Intentions

The reduction in carbon emissions in the construction industry plays an important role in the realization of the goal of carbon peaking and carbon neutrality, especially in China. Construction enterprises’ personnel’s intentions to reduce their carbon emissions are closely related to low-carbon behavior. However, the research on the impact factors of carbon emission-reduction intention (CERI) is still limited. In order to understand the factors that affect the intentions of construction enterprises’ personnel to reduce carbon emissions, and to put forward valuable suggestions for reducing construction enterprises’ carbon emissions, it is necessary to explore the impact factors in carbon emission-reduction intention through empirical tests. This study adopted the theory of planned behavior (TPB) based on the three impact factors of behavioral attitude (BA), subjective norms (SNs) and perceived behavioral control (PBC), introduced the two potential impact factors of moral obligation (MO) and government supervision (GS), and also uses structural equation modeling (SEM) to test the impact factors in construction enterprises’ personnel’s carbon emission-reduction intention. The results show that BA, MO and GS have a significant positive impact on carbon emission-reduction intention (CERI). Among them, BA plays an intermediary role between MO and CERI, and BA and MO play a chain intermediary role between GS and CERI. The research conclusions will help to provide a theoretical reference for governments and construction enterprises to implement carbon emission-reduction development strategies and policies.
Accelerating 3-D MUSIC Algorithm With Fast Fourier Transform for Collocated FDMA-MIMO Radar With Subarray Configuration

Frequency division multiple access (FDMA) waveform possesses good orthogonality and thus is used in multiple-input multiple-output (MIMO) radar. Nevertheless, the transmitting steering vector of the FDMA-MIMO radar is dependent on both range and angle, and it has no form of a Vandermonde matrix at the subarray level. As a result, target locating using the conventional 3-D MUSIC algorithm should be realized by 3-D fine grid search (FGS), which yields a considerable computational burden. This article proposes a fast implementation of the 3-D MUSIC estimator via the 3-D fast Fourier transform (FFT). By exploiting the reduced-dimensional matrix and the property of the Kronecker product, the 3-D MUSIC spectrum can be reformulated in the form of a Vandermonde matrix. Thus, 3-D fine grid searching is avoided by using 3-D FFT, which can work in the collocated FDMA-MIMO radar with subarray configuration and significantly accelerate parameter estimation. Comparison experiments are performed to prove the rapidity and accuracy of the proposed algorithm.
Possibilities and limitations of using machine text processing tools in Russian radiology

Backgraund: In radiology, important information is contained not only in medical images, but also in the accompanying text descriptions created by radiologists. Identification of study protocols containing certain data and extraction of these data can be useful primarily for clinical problems, however, given the large amount of such data, the development of machine analysis algorithms is necessary. Aim: to estimate the possibilities and limitations of using of tool for machine processing of radiology reports to search for pathological findings. Material and Methods: to create an algorithm for automatic analysis of radiology reports, use cases were selected that participated in the Experiment on the use of innovative technologies in the computer vision for the analysis of medical images in 2020. The use cases included mammography, chest X-ray, chest CT and LDCT, performed in Moscow. A dictionary of keywords has been compiled. After the automatic marking of the reports by the developed tool, the results were assessed by a radiologist. The number of protocols analyzed by the radiologist was 977 for mammography, 4804 for all chest X-ray scans, 4074 for chest CT and 398 chest LDCT. Results: The best results were achieved in the search for viral pneumonia in chest CT reports (0.993), breast cancer in mammography reports (0.996). The accuracy of searching for signs of lung cancer in chest CT and LDCT, pathological findings in the chest X-ray reports was 0.972 and 0.982. Conclusions: Machine methods with high accuracy can be used to automatically classify the radiology reports of mammography, chest CT with viral pneumonia. To search for signs of lung cancer in chest CT and LDCT, pathological findings in chest X-ray, the achieved accuracy is sufficient for successful application to automatically compare the conclusions of physicians and artificial intelligence models.
Comparison of a Group-/Home-Based and a Weight-Machine-Based Exercise Training for Patients with Hip or Knee Osteoarthritis—A Secondary Analysis of Two Trial Interventions in a Real-World Context

This study aimed to compare an individual weight-machine-based strengthening program (MbT) with a group-/homebased training offering strengthening/functional exercises (GHT) in a general health care setting. A total of 657 participants (GHT = 521, MbT = 136) suffering from hip/knee OA were included and analysed with a pre–post design (baseline (T0)/3-months (T1)). Primary outcomes were pain and physical functioning (Western Ontario and McMaster Universities Osteoarthritis Index, range 0–10). Additionally, adherence and perceived patient benefit were measured (T1). Data were analysed with linear mixed models (time, treatment, baseline pain/physical impairment severity) adjusted for patient characteristics. No significant between-group differences in pain reduction/functional improvements (time*treatment*baseline pain/physical impairment severity, pain/function: n.s.; time*treatment, pain: p = 0.884, function: p = 0.067). Within-group improvements were dependent on baseline severity: Higher severity levels demonstrated larger changes from baseline. Perceived patient-benefit (very high to high, GHT: 78%, MbT: 92%) and exercise adherence (Dropouts T1: GHT: 27.8%, MbT: 16.2%; adherence to supervised sessions: GHT: 89%, MbT: 92%) was slightly better in the MbT. In summary, both MbT and GHT, showed positive results for patients with at least moderate disease symptoms. Findings for physical functioning, perceived patient-benefit, exercise adherence hint towards a superiority of MbT. Individual preferences should be considered when prescribing exercise therapy. Trial registration: (1) German Clinical Trial Register DRKS00009251. Registered 10 September 2015. (2) German Clinical Trial Register DRKS00009257. Registered 11 September 2015.
Analysis of factors affecting the accuracy of the rotation angle measurement using nanostructured metasurfaces

The work is devoted to the analysis of the accuracy characteristics of rotation angle sensors using angular scales from nanostructured metasurfaces. The principle of their operation is based on the dependence of the frequency response of metasurfaces on the orientation of the incident light polarization plane. The influence of the noise characteristic of angle sensors on the measurement result is considered. It is shown that for the sensors considered in the work, it might be on the order of units of arc seconds. The influence on the accuracy characteristics of misalignments of the angular scale and thermal effects that the sensor may experience during operation is analyzed. Recommendations to reduce the influence of parasitic effects and further improve the accuracy characteristics are given.
An Efficient Constrained Global optimization Method through Adaptively Adjusting Predicted Feasible Region and Its Application in Buckling Design of Stiffened Cylindrical Shell with Variable Ribs

Surrogate-based optimization methods are popular in tackling expensive problems due to their high efficiency. When constrained problems are encountered, obtaining the feasible global optimum becomes quite challenging due to the inaccuracy of constraint surrogates. In this study, an efficient constrained global optimization method based on Kriging surrogate models is proposed. In the proposed method, the feasible region predicted by the constraint surrogates is adaptively adjusted by checking the feasibility of the infill point, which is obtained through minimizing the lower confidence bound (LCB) of the objective prediction subject to the adjusted constraints. Specifically, the candidate infill region is initialized to the predicted feasible region without considering the uncertainty from constraint surrogates. Then, the feasibility of the infill point is checked by expensive evaluation. If the infill point is infeasible, the candidate infill region is shrunk to obtain the next infill point. Otherwise, it is extended to incorporate other promising regions that potentially contain a better solution. Through the shrink-and-extend strategy, both the feasible and infeasible points in the vicinity of the global optimum are infilled, which is beneficial to improving the surrogates’ accuracy on the feasible region boundary. In order to verify the effectiveness of the proposed method, it is first compared with three state-of-the-art algorithms on thirteen benchmark mathematical problems and on two engineering problems. Besides, the proposed method is also applied to the buckling design of stiffened cylindrical shell with variable ribs under constraints of strength and weight to demonstrate its applicability.
Recent results on B spectroscopy at the Tevatron

The Tevatron collider at Fermilab provides a rich environment for B spectroscopy. Recently the first direct observation of the B{sub c} meson has reduced its mass uncertainty by two orders of magnitude. A search for {eta}{sub b} mesons provides the best limit on its production in p{bar p} colliders. In studies on orbitally excited B{sub d} mesons for the first time the narrow states could be separated from each other. The orbitally excited B{sub s} mesons have been observed for the first time. With the charged {Sigma}{sub b}{sup (*)} a second B baryon could be established beside the {Lambda}{sub b}.
Line-end gap measurement with YieldStar scatterometer: towards an OPC model calibration

Line-end gap measurement for OPC calibration is a challenge for metrology. Even for CD-SEM, the rounded shape of the line end makes it very difficult to measure precisely. We have presented preliminary results of the application of scatterometry to these challenging structures using an angle resolved polarized scatterometer: ASML YieldStar [1]. In this paper, the exercise was extended to several different structures combining multiple line-end gap situations. Systematic comparison with CD-SEM is performed and discussed. Lithographic behavior of the main parameters is analyzed. Strengths and limits of the technique will be shown. Once validated, the metrology is used to build an OPC model and correct our test vehicle.
Mask-Guided Generation Method for Industrial Defect Images with Non-uniform Structures

Defect generation is a crucial method for solving data problems in industrial defect detection. However, the current defect generation methods suffer from the problems of background information loss, insufficient consideration of complex defects, and lack of accurate annotations, which limits their application in defect segmentation tasks. To tackle these problems, we proposed a mask-guided background-preserving defect generation method, MDGAN (mask-guided defect generation adversarial networks). First, to preserve the normal background and provide accurate annotations for the generated defect samples, we proposed a background replacement module (BRM), to add real background information to the generator and guide the generator to only focus on the generation of defect content in specified regions. Second, to guarantee the quality of the generated complex texture defects, we proposed a double discrimination module (DDM), to assist the discriminator in measuring the realism of the input image and distinguishing whether or not the defects were distributed at specified locations. The experimental results on metal, fabric, and plastic products showed that MDGAN could generate diversified and high-quality defect samples, demonstrating an improvement in detection over the traditional augmented samples. In addition, MDGAN can transfer defects between datasets with similar defect contents, thus achieving zero-shot defect detection.
Causality between Stock Market, Domestic and Global Economic Policy Uncertainty: Evidence from India

The aim of this article is to examine the relationship between the Indian stock market and the domestic and global economic policy uncertainty (EPU) during the period: January 2003–June 2020. The study employed unit root tests, Johansen cointegration test, vector error correction model (VECM), Granger causality test and impulse response function (IRF) for the analysis. This study finds the evidence for the presence of long-run equilibrium relationship between the stock market, domestic economic policy uncertainty (DEPU) and global economic policy uncertainty (GEPU) in India. The findings suggest that there is bidirectional causality between DEPU and stock market; however, no causality is found between GEPU and stock market in either direction. Also, it is found that there is bidirectional causality between DEPU and GEPU. The findings of the study may help policymakers to formulate decisive monetary and fiscal policies to achieve financial stability and are important for the financial investors and hedgers for portfolio allocations in India. JEL Codes: C32, D80, G12
Detoxification of Distillery Wastewater by AOP Fenton for the Enhancement of Biogas Production

Distillery wastewater from the bioethanol industry contains a high level of organic content which can be converted into biogas. However, the presence of toxic compounds in this wastewater could inhibit biogas production. Therefore, prior detoxification of distillery wastewater is required. Fenton, one of the Advanced Oxidation Process (AOP) methods, was selected due to its high performance to degrade organic pollutants, short reaction time, and the process is simple and easy. Additionally, this method can also be used as a pretreatment for biogas production. This paper aims to study the improvement of biogas production from distillery wastewater by applying AOP Fenton as a pretreatment method. The experiment consists of two stages, the first was application of AOP Fenton to the distillery wastewater in order to determine its effect on the concentration of COD and some toxic compounds such as phenol and sulfate. The second stage was biogas production through anaerobic digestion process, which was carried out under two conditions of raw materials: (i) distillery wastewater without pretreatment of AOP Fenton as a control and (ii) distillery wastewater that has been treated with AOP Fenton as pretreatment. Results show a remarkable decrease in COD concentration by 45%, phenol (63%), and sulfate (18,6%) from distillery wastewater after applying AOP Fenton. It implies that the application of AOP Fenton significantly detoxified distillery wastewater. As a biogas pretreatment, this method also increased biogas production by 33% higher, from 2.399 mL (without pretreatment) to 3.191 mL (with pretreatment). It indicates that AOP Fenton increased the biodegradability of distillery wastewater. Thus, it was easier to be converted into biogas.
Plant-Based Diets and Lipid, Lipoprotein, and Inflammatory Biomarkers of Cardiovascular Disease: A Review of Observational and Interventional Studies

Plant-based diets (PBDs) are becoming increasingly popular. Thus far, the literature has focused on their association with lipid profiles, with less investigation of lipoprotein and inflammatory profiles. Because pro-atherogenic lipid, lipoprotein, and inflammatory processes may facilitate the development of atherosclerosis, understanding the relation between PBDs and these processes is important to inform risk mitigation strategies. Therefore, the objective of this paper was to review the literature on PBDs and lipid, lipoprotein, and inflammatory biomarkers of cardiovascular disease (CVD). A structured literature search was performed, retrieving 752 records, of which 43 articles were included. Plant-based diets generally associated with favourable lipid and lipoprotein profiles, characterised by decreased total cholesterol, low-density lipoprotein cholesterol, and apolipoprotein B concentrations, and less low-grade inflammation, characterised by decreased C-reactive protein concentrations. Effect sizes from PBD interventions were greatest compared to habitual dietary patterns, and for non-low-fat vegan and tightly controlled dietary interventions. Associations between PBD indices and the reviewed biomarkers were less consistent. Findings are discussed with reference to the literature on PBDs and PBD indices and CVD risk, the associations between specific plant food groups and CVD outcomes and the reviewed biomarker outcomes, and the potential mechanisms underpinning associations between PBDs and reduced CVD risk.
Prospects of Utilizing Quantum Emitters to Control the Absorption of Non‐Noble Plasmonic Metal Nanoparticles

Prospects of controlling the absorption of the cost‐effective plasmonic metal nanoparticles (MNPs) Cu and Al using quantum emitters (QEs) are demonstrated semi‐analytically. The resulting spectra are compared with the absorption of commonly used noble plasmonic metal nanoparticles Au and Ag under similar conditions. It is observed that Cu and Au based plasmonic nanoparticles exhibit largely similar exciton–plasmon Fano interaction signatures in addition to their similar spectral regions of operation (lower end of the visible range). Furthermore, the QE‐enhanced maximum absorption (Fano maximum) of Cu based nanohybrids are seen to approach the maximum absorption level of isolated Au MNPs, with decreasing QE‐Cu separation, increasing QE dipole element magnitude, and increasing medium permittivity, in the parameter region considered. This renders Cu based exciton–plasmon nanohybrids as more economical alternatives for Au MNPs and Au‐based nanohybrids in absorption‐based applications (such as thermoplasmonic), when stabilized in protective embedding media such as poly (methyl methacrylate) (PMMA).