Miracle-dz/UniFAR-FTUs huggingface dataset:
Recent progress in the development of grating-gate InGaAs-channel HEMTs for fast and sensitive THz detection

We review recent progress in the development of grating-gate plasmonic THz detectors based on InGaAs-channel high-electron- mobility transistors for fast, highly sensitive, room-temperature-operating THz detection. First, a 2D diffraction grating structure, instead of the conventional 1D grating structure, was proposed for realization of polarization-independent detection and was experimentally demonstrated to alter the polarization characteristic of output photoresponse drastically. Second, it was demonstrated that a new way to read the output photovoltage from the gate of a detector simultaneously enables the scaling of the photovoltage with the active area size and the impedance matching with 50-Ω interconnection systems, which were the main issues in the conventional drain-readout configuration. Third, a significant enhancement of the photovoltage was observed at a positive gate bias voltage application in the gate-readout configuration, due to the “3D rectification effect" originating from the heterobarrier between the InGaAs channel layer and InAlAs spacer/carrier-supply/ barrier layers.
Row-Column designs with varying replications

A class of Row-Column designs in two sets of treatments having different replications has been constructed by replacing the diagonal treatments of a 2v x 2v standard cyclic Latin Square by a new treatment ‘2v+1’. The designs so obtained have been identified as Simple partially efficiency balanced Row-Column designs (SPEB RC-designs) (Singh and Dey, 1978; Pal, 1980).
Photometric observations of three high mass X-ray binaries and a search for variations induced by orbital motion

We searched for long period variation in V-band, IC-band and RXTE X-ray light curves of the High Mass X-ray Binaries (HMXBs) LS 1698 / RX J1037.5-5647, HD 110432 / 1H 1249-637 and HD 161103 / RX J1744.7-2713 in an attempt to discover orbitally induced variation. Data were obtained primarily from the ASAS database and were supplemented by shorter term observations made with the 24- and 40-inch ANU telescopes and one of the robotic PROMPT telescopes. Fourier peri-odograms suggested the existence of long period variation in the V-band light curves of all three HMXBs, however folding the data at those periods did not reveal convincing periodic variation. At this point we cannot rule out the existence of long term V-band variation for these three sources and hints of longer term variation may be seen in the higher precision PROMPT data. Long term V-band observations, on the order of several years, taken at a frequency of at least once per week and with a precision of 0.01 mag, therefore still have a chance of revealing long term variation in these three HMXBs.
Rapidly Changing Emissions Drove Substantial Surface and Tropospheric Ozone Increases Over Southeast Asia

We combined observations and simulations to assess tropospheric ozone trends over Southeast Asia from 2005 to 2016. Multi‐platform observations showed that surface ozone had been increasing at rates of 0.7–1.2 ppb year−1 over the Peninsular Southeast Asia (PSEA) and 0.2–0.4 ppb year−1 over the Maritime Continents (MC); tropospheric ozone columns had been rising throughout Southeast Asia by 0.21–0.35 DU year−1. These observed ozone trends were better reproduced by simulations driven with satellite‐constrained NOx emissions, indicating that NOx emission growths may have been underestimated for the PSEA and overestimated for the MC in the Community Emissions Data System and the Global Fire Emissions Data set. The surface ozone increases over the PSEA were driven by rapidly growing local emissions, wherein fire emission growths may still be underestimated even with satellite constraints. We highlighted the need for better quantifying Southeast Asian emissions to benefit air quality management.
Hadronic decays of the X(3872) to χcJ in effective field theory

The decays of the $X(3872)$ to $P$-wave quarkonia are calculated under the assumption that it is a shallow bound state of neutral charmed mesons. The $X(3872)$ is described using an effective theory of nonrelativistic $D$ mesons and pions (X-EFT). We calculate $X(3872)$ decays by first matching heavy hadron chiral perturbation theory ($\mathrm{HH}\ensuremath{\chi}\mathrm{PT}$) amplitudes for ${D}^{0}{\overline{D}}^{*0}\ensuremath{\rightarrow}{\ensuremath{\chi}}_{cJ}({\ensuremath{\pi}}^{0},\ensuremath{\pi}\ensuremath{\pi})$ onto local operators in X-EFT, and then using these operators to calculate the $X(3872)$ decays. This procedure reproduces the factorization theorems for $X(3872)$ decays to conventional quarkonia previously derived using the operator product expansion. For single pion decays, we find nontrivial dependence on the pion energy from $\mathrm{HH}\ensuremath{\chi}\mathrm{PT}$ diagrams with virtual $D$ mesons. This nontrivial energy dependence can potentially modify heavy-quark symmetry predictions for the relative sizes of decay rates. At leading order, decays to final states with two pions are dominated by the final state ${\ensuremath{\chi}}_{c1}{\ensuremath{\pi}}^{0}{\ensuremath{\pi}}^{0}$, with a branching fraction just below that for the decay to ${\ensuremath{\chi}}_{c1}{\ensuremath{\pi}}^{0}$. Decays to all other final states with two pions are highly suppressed.
Effective field theory methods to model compact binaries

In this short review we present a self-contained exposition of the effective field theory method approach to model the dynamics of gravitationally bound compact binary systems within the post-Newtonian approximation to General Relativity. Applications of this approach to the conservative sector, as well as to the radiation emission by the binary system are discussed in their salient features. Most important results are discussed, as in-depths and details can be found in the referenced papers.
Quantum macroscopicity measure for arbitrary spin systems and its application to quantum phase transitions

We explore a previously unknown connection between two important problems in physics, i.e., quantum macroscopicity and the quantum phase transition. We devise a general and computable measure of quantum macroscopicity that can be applied to arbitrary spin states. We find that a macroscopic quantum superposition of an extremely large size arises during the quantum phase transition of the transverse Ising model in contrast to some seeming macroscopic quantum phenomena such as superconductivity, superfluidity, and Bose-Einstein condensates. Our result may be an important step forward in understanding macroscopic quantum properties of many-body systems.
A Machine Learning Model for Predicting the Risk of Readmission in Community-Acquired Pneumonia

Background Pneumonia is a common respiratory infection that affects all ages, with a higher rate anticipated as age increases. It is a disease that impacts patient health and the economy of the healthcare institution. Therefore, machine learning methods have been used to guide clinical judgment in disease conditions and can recognize patterns based on patient data. This study aims to develop a prediction model for the readmission risk within 30 days of patient discharge after the management of community-acquired pneumonia (CAP). Methodology Univariate and multivariate logistic regression were used to identify the statistically significant factors that are associated with the readmission of patients with CAP. Multiple machine learning models were used to predict the readmission of CAP patients within 30 days by conducting a retrospective observational study on patient data. The dataset was obtained from the Hospital Information System of a tertiary healthcare organization across Saudi Arabia. The study included all patients diagnosed with CAP from 2016 until the end of 2018. Results The collected data included 8,690 admission records related to CAP for 5,776 patients (2,965 males, 2,811 females). The results of the analysis showed that patient age, heart rate, respiratory rate, medication count, and the number of comorbidities were significantly associated with the odds of being readmitted. All other variables showed no significant effect. We ran four algorithms to create the model on our data. The decision tree gave high accuracy of 83%, while support vector machine (SVM), random forest (RF), and logistic regression provided better accuracy of 90%. However, because the dataset was unbalanced, the precision and recall for readmission were zero for all models except the decision tree with 16% and 18%, respectively. By applying the Synthetic Minority Oversampling TEchnique technique to balance the training dataset, the results did not change significantly; the highest precision achieved was 16% in the SVM model. RF achieved the highest recall with 45%, but without any advantage to this model because the accuracy was reduced to 65%. Conclusions Pneumonia is an infectious disease with major health and economic complications. We identified that less than 10% of patients were readmitted for CAP after discharge; in addition, we identified significant predictors. However, our study did not have enough data to develop a proper machine learning prediction model for the risk of readmission.
Longitudinal associations for right-wing authoritarianism, social justice, and compassion among seminary students

Religious/spiritual communities in the United States hold significant differences in the relative valuing of social order and progress toward social justice, and religious/spiritual leaders play an influential role in fostering those values. This recognition has prompted calls for theological education to revise the process of student formation, equipping them to address an increasingly diverse social world and the social disparities within their larger communities. Right-wing authoritarianism tends to be associated with a preference for social order and various forms of prejudice, and negatively associated with prosocial attitudes and behaviors. However, there is a limited amount of research examining associations between right-wing authoritarianism and the prosocial constructs of social justice commitment and compassion. The present study explored the longitudinal associations between right-wing authoritarianism, social justice commitment, and compassion in a sample of graduate students from 18 Christian seminaries across North America over two and a half years of their education (N = 580; Mage = 31.50; 47.3% female; 62.9% White). Longitudinal data analysis indicated that right-wing authoritarianism exerted a negative influence on social justice commitment and compassion, during the initial time interval which then faded over time. Results also indicated a reciprocal process among right-wing authoritarianism and social justice commitment. Practical implications centered on the potential for interventions targeting the reduction of right-wing authoritarianism to increase social justice commitment and compassion, and interventions targeting greater social justice commitment to lower right-wing authoritarianism.
Heterogeneous Graph Contrastive Learning for Stance Prediction

SUMMARY Stance prediction on social media aims to infer the stances of users towards a speciﬁc topic or event, which are not expressed explicitly. It is of great signiﬁcance for public opinion analysis to extract and determine users’ stances using user-generated content on social media. Existing research makes use of various signals, ranging from text content to online network connections of users on these platforms. However, it lacks joint modeling of the heterogeneous information for stance prediction. In this paper, we propose a self-supervised heterogeneous graph contrastive learning framework for stance prediction in online debate forums. Firstly, we perform data augmentation on the original heterogeneous information network to generate an augmented view. The original view and augmented view are learned from a meta-path based graph encoder respectively. Then, the contrastive learning among the two views is conducted to obtain high-quality representations of users and issues. Finally, the stance prediction is accomplished by matrix factorization between users and issues. The experimental results on an online debate forum dataset show that our model outperforms other competitive baseline methods signiﬁcantly.
A Dual-Band Resonator Sensor for Low Permittivity Characterization

Low permittivity materials are widely used in many electronic systems. However, dielectric measurement on low permittivity material is challenging. To address this difficulty, a dual-band resonant sensor is developed. The proposed sensor is an improved design from the complementary square spiral resonator (CSSR). By adding a square patch on top of the resonant cell, the local field is significantly increased. Therefore, the interaction between field and material is strengthened, resulting in an enhancement in measurement sensitivity. Owing to the increased sensitivity, low permittivity samples down to 1.19 can be measured with an accuracy of better than 3%. Such results demonstrate that this sensor is promising for low permittivity characterization. Moreover, this sensor is also capable of measuring samples with permittivity in the range of 2–10, with an accuracy of 5%. Furthermore, two resonances are created, enabling dual-band operation. The unloaded resonances take place at 2.00 and 5.41 GHz. Particularly, the measurement can be conducted simultaneously in the two operation bands. Measured results demonstrate that the accuracy and sensitivity are satisfactorily high and comparatively superior to the designs in the literature for low permittivity measurement.
Relative K-area homology and applications

We show an Uhlenbeck type estimate for closed simply connected manifolds which provides the existence of certain exact sequences in K-area homology. This leads to the behavior of the K-area homology under surgery. Moreover, we give an index theoretic obstruction to positive scalar curvature on compact spin manifolds with boundary.
Zigzag phosphorene nanoribbons: one-dimensional resonant channels in two-dimensional atomic crystals

We theoretically investigate phosphorene zigzag nanoribbons as a platform for constriction engineering. In the presence of a constriction at one of the edges, quantum confinement of edge-protected states reveals conductance peaks, if the edge is uncoupled from the other edge. If the constriction is narrow enough to promote coupling between edges, it gives rise to Fano-like resonances as well as antiresonances in the transmission spectrum. These effects are shown to mimic an atomic chain like behavior in a two dimensional atomic crystal.
Kinesiophobia Levels in Patients with Multiple Sclerosis: A Case-Control Investigation

Simple Summary Fear of movement or kinesiophobia is a health problem related to an irrational fear of physical movement and fatigue that can lead to a limitation of functional capacity and a decrease in daily physical activity. Thus, the purpose of this study was to test the level of kinesiophobia in people with multiple sclerosis and compare it with a group of healthy people. The findings of this research support evidence that kinesiophobia is higher in people with multiple sclerosis than in a healthy control group. Therefore, people with multiple sclerosis should be evaluated and monitored to plan the treatment and preventive care activities of a multidisciplinary health team (podiatrists, physiotherapists, nurses, physicians, occupational therapists) in the attempt to improve their quality of life, autonomy, and wellbeing. Abstract Fear of movement or kinesiophobia is an irrational fear of physical movement and fatigue that causes a limitation of functional capacity and decreased physical activity. The purpose of this study was to ascertain the level of kinesiophobia in people with multiple sclerosis (pwMS) and compare it with a group of healthy people, through the Tampa Scale for Kinesiophobia with 11 items (TSK-11). Method: A total of 116 subjects were recruited in a multicenter case-control study; 58 subjects suffered from MS and 58 were healthy subjects from different associations and the same locality. To assess the levels of fear of movement, the Spanish version of the TSK-11 self-questionnaire was used. Results: Most pwMS suffer from some degree of kinesiophobia (TSK-11 ≥ 18), and 60.3% had moderate to maximum kinesiophobia scores (TSK-11 ≥ 25). In contrast, healthy subjects presented a percentage of kinesiophobia from none to moderate (82.7%). Conclusions: Kinesiophobia is higher in pwMS than in the healthy control group. Accordingly, individuals showing pwMS should be assessed and monitored in order to diagnosed initial kinesiophobia levels, to allow planning treatment and preventive care activities that may improve the foot health and overall health in this group of patients.
Hybridization of Fuzzy Sets and Rough Sets: Achievements and Opportunities

Fuzzy rough sets are the fruit of an intense and long-lasting collaboration effort between fuzzy set theory and rough set theory. Seminal research on the hybridization originated in the late 1980's, and has inspired generations of researchers from around the globe to address both theoretical and practical challenges. In this paper, we gauge the state-of-the-art in this domain and identify opportunities for further development. In particular, we highlight the potential of fuzzy quantifiers in creating new robust fuzzy rough models, we advocate closer integration with granular computing as a stepping stone for designing rule induction algorithms, and we contemplate the role of fuzzy rough sets vis-a-vis explainable artificial intelligence.
Essential Oil from Hibiscus Flowers through Advanced Microwave-Assisted Hydrodistillation and Conventional Hydrodistillation

Due to the increased demand and importance of essential oils in medicinal applications, advanced essential oil extraction techniques have been employed. Both conventional hydrodistillation (HD) and microwave-assisted hydrodistillation (MAHD) were employed to extract the essential oils from the hibiscus flower. Extraction time and solvent polarity were the most critical factors. Scanning electron microscopy (SEM) was used to investigate the surface morphologies of raw powdered hibiscus flowers (not exposed to any pretreatment) and pretreated powdered hibiscus flowers (exposed to methanol absorption for 60 minutes prior to extraction). Extractive chemistry analysis utilizing Fourier transform infrared (FTIR) spectroscopy was performed on the volatile oil obtained by MAHD. Different peaks in the gas chromatography/mass spectrometry (GC/MS) analysis indicated the presence of thirty-seven different compositions. MAHD was more energy efficient, had higher yield production, and was environmentally friendly, reducing HD’s overall carbon footprint by 40%. Oxygenated monoterpene, sesquiterpene, and sesquiterpene hydrocarbons were found in the hibiscus flower’s crude extract. Moreover, the methanolic extract of Hibiscus rosa-sinensis has potent antioxidant properties. A hibiscus flower extract had scavenging activities of 51.2% at 0.2 mg/mL, 0.3% at 0.6 mg/mL, 0.8% at 1.0 mg/mL, and 68.5% at 1.2 mg/mL against DPPH free radicals. Therefore, the MAHD method is well-suited to extracting essential oils from hibiscus flowers, and the resulting oil has the potential to provide significant therapeutic advantages.
Automatic analysis of caregiver input and child production

The present study explores the applicability of Natural Language Processing (NLP) techniques to investigate child corpora in Korean. We employ caregiver input and child production data in the CHILDES database, currently the largest and open-access Korean child corpus data, and apply NLP techniques to the data in two ways: automatic Part-of-Speech tagging by adapting a machine learning algorithm, and (semi-)automatic extraction of constructional patterns expressing a transitive event (active transitive and suffixal passive). As the first empirical report on NLP-assisted analysis of Korean child corpora, this study is expected to reveal its advantages and drawbacks, thereby opening the window to furthering corpus-mediated research on child language development in Korean. Implications of this study’s findings will also contribute to research practice regarding developmental studies on Korean through child corpora, ensuring the reproducibility of procedures and results, which is often lacking in previous corpus-based research on child language development in Korean.
A high definition view of the COSMOS Wall at z ~ 0.73

Aims. We present a study of a large filamentary structure at z similar to 0.73 in the field of the COSMOS survey, the so-called COSMOS Wall. This structure encompasses a comprehensive range of environments from a dense cluster and a number of galaxy groups to filaments, less dense regions, and adjacent voids. It thus provides a valuable laboratory for the accurate mapping of environmental effects on galaxy evolution at a look-back time of similar to 6.5 Gyr, when the Universe was roughly half its present age. Methods. We performed deep spectroscopic observations with VIMOS at VLT of a K-band selected sample of galaxies in this complex structure, building a sample of galaxies complete in galaxy stellar mass down to a lower limit of log(M-*/M-circle dot)similar to 9.8, which is significantly deeper than previously available data. Thanks to its location within the COSMOS survey, each galaxy benefits from a wealth of ancillary information: HST-ACS data with I-band exposures down to I-AB similar to 28 complemented by extensive multiwavelength ground-and space-based observations spanning the entire electromagnetic spectrum. Results. In this paper we detail the survey strategy and weighting scheme adopted to account for the biases introduced by the photometric preselection of our targets. We present our galaxy stellar mass and rest-frame magnitudes estimates together with a group catalog obtained with our new data and their member galaxies color / mass distribution. Conclusions. Owing to our new sample we can perform a detailed, high definition mapping of the complex COSMOS Wall structure. The sharp environmental information, coupled with high quality spectroscopic information and rich ancillary data available in the COSMOS field, enables a detailed study of galaxy properties as a function of local environment in a redshift slice where environmental effects are important, and in a stellar mass range where mass and environment driven effects are both at work.
OBSERVATION OF THE 2011-02-15 X2.2 FLARE IN THE HARD X-RAY AND MICROWAVE

Previous studies have shown that the energy release mechanism of some solar flares follow the Standard magnetic-reconnection model, but the detailed properties of high-energy electrons produced in the flare are still not well understood. We conducted a unique, multi-wavelength study that discloses the spatial, temporal and energy distributions of the accelerated electrons in the X2.2 solar flare on 2011 February 15. We studied the source locations of seven distinct temporal peaks observed in hard X-ray (HXR) and microwave (MW) light curves using the RHESSI in 50–75 keV channels and Nobeyama Radioheliograph in 34 GHz, respectively. We found that the seven emission peaks did not come from seven spatially distinct sites in HXR and MW, but rather in HXR we observed a sudden change in location only between the second and the third peak, with the same pattern occurring, but evolving more slowly in MW. Comparison between the HXR light curve and the temporal variations in intensity in the two MW source kernels also confirmed that the seven peaks came predominantly from two sources, each with multiple temporal peaks. In addition, we studied the polarization properties of MW sources, and time delay between HXR and MW. We discuss our results in the context of the tether-cutting model.