Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing Pool Utilization in Constructing the Multistage Test Using Mixed-Format Tests

This study investigated a new pool utilization method of constructing multistage tests (MST) using the mixed-format test based on the generalized partial credit model (GPCM). MST simulations of a classification test were performed to evaluate the MST design. A linear programming (LP) model was applied to perform MST reassemblies based on the initial MST construction. Three subsequent MST reassemblies were performed. For each reassembly, three test unit replacement ratios (TRRs; 0.22, 0.44, and 0.66) were investigated. The conditions of the three passing rates (30%, 50%, and 70%) were also considered in the classification testing. The results demonstrated that various MST reassembly conditions increased the overall pool utilization rates, while maintaining the desired MST construction. All MST testing conditions performed equally well in terms of the precision of the classification decision.
Photographic evidence of the formation and growth of vorticity behind plates accelerated from rest in still air

The shedding of vorticity from the edges of a plate, which is accelerated normal to itself from rest in still air, is investigated experimentally by means of a new flow-visualization technique using spark-lighted shadowgraphs and heated air, benzene or other vapours to introduce sufficient changes in density along the surface of discontinuity. The photographs show small-scale undulations and the formation of a number of centres of vorticity along the well known big-scale vortex sheets which roll up along their edges.
Characteristics of Field-Emission-Induced Breakdown With Conical Microprotrusion

Microprotrusions on plane electrode surface of vacuum interrupter are the main cause of field-emission-induced breakdown. The microprotrusions are difficult to observe because of the ceramic insulations and floating shield, and they will be destroyed by breakdown events. This article aims to reveal the characteristics of field-emission-induced breakdown with conical microprotrusion. The conical microprotrusions are reconstructed based on Fowler–Nordheim theory with field-emission current and applied voltage from breakdown experiment. The conical microprotrusions temperature characteristics are obtained with Joule heating effect taking into consideration, which could help to confirm the validity of the reconstructed microprotrusions. The relationship between conical microprotrusions geometrical parameters and field-emission characteristics is analyzed. The results would clarify the effects of conical microprotrusion on plane electrode surface on field-emission-induced breakdown.
Current-driven drift wave instability in a collisional dusty negative ion plasma

Abstract The excitation of drift waves by an electron current parallel to the magnetic field is investigated in a nonuniform plasma composed of electrons, positive ions, negative ions, and massive, negatively charged dust. Electrostatic drift waves with frequencies smaller than the ion gyrofrequencies and wavelengths larger than the ion gyroradii are considered. Linear kinetic theory is used, and collisions of charged particles with neutrals are taken into account. The present results may be relevant to laboratory collisional magnetoplasmas containing negative ions and dust.
Multimodality-Aided Multicarrier Waveform Recognition in Low SNR Regimes Based on Denoised Cyclic Autocorrelation Transformation

Wireless signal recognition driven by artificial intelligence (AI) plays a pivotal role in 6G ultrareliable wireless communications, facilitating spectrum surveillance to impede illegal radio interference. As a promising wireless technique, multicarrier waveform recognition (MWR) has been explored to enhance the reliability of wireless data transmission. However, existing works fail to achieve reliable recognition accuracy under strong noise. It remains a daunting task for MWR in signal-to-noise ratio (SNR) regimes. To deal with this issue, we propose a denoised cyclic autocorrelation-based multimodality fusion network (DCA-MFNet). Specifically, we first leverage the cyclic autocorrelation (CA) transformation to convert intercepted signals into CA features in cyclic frequency domains, which have the robust property of being insensitive to low SNR. Next, the singular value decomposition method is employed to weaken the strong noise effects on useful CA peak values. Based on the denoised CA matrix (DCAM), the projection accumulation strategy is proposed to generate the time delay accumulation vector (TDV) and cyclic frequency accumulation vector (CFV), which can enlarge the discrimination among multicarrier signals. Finally, we fed the multimodality features of DCAM, TDV, and CFV into the developed DCA-MFNet to perform hierarchical learning, feature aggregation training, and multicarrier type prediction. Experimental results demonstrate that the proposed DCA-MFNet obtains better recognition performance than existing algorithms. Moreover, DCA-MFNet can effectively identify six multicarrier signals with a recognition accuracy of 100% at a low SNR of even −2 dB.
Influence of Genetics on the Response to Omalizumab in Patients with Severe Uncontrolled Asthma with an Allergic Phenotype

Omalizumab is a monoclonal antibody indicated for the treatment of severe uncontrolled asthma with an allergic phenotype. Its effectiveness could be influenced by clinical variables and single nucleotide polymorphisms (SNPs) in one or more of the genes involved in the mechanism of action and process of response to omalizumab, and these could be used as predictive biomarkers of response. We conducted an observational retrospective cohort study that included patients with severe uncontrolled allergic asthma treated with omalizumab in a tertiary hospital. Satisfactory response after 12 months of treatment was defined as (1) Reduction ≥ 50% of exacerbations or no exacerbations, (2) Improvement of lung function ≥ 10% FEV1, and (3) Reduction ≥ 50% of OCS courses or no OCS. Polymorphisms in the FCER1A (rs2251746, rs2427837), FCER1B (rs1441586, rs573790, rs1054485, rs569108), C3 (rs2230199), FCGR2A (rs1801274), FCGR2B (rs3219018, rs1050501), FCGR3A (rs10127939, rs396991), IL1RL1 (rs1420101, rs17026974, rs1921622), and GATA2 (rs4857855) genes were analyzed by real-time polymerase chain reaction (PCR) using TaqMan probes. A total of 110 patients under treatment with omalizumab were recruited. After 12 months of treatment, the variables associated with a reduction in exacerbations were the absence of polyposis (odds ratio [OR] = 4.22; 95% confidence interval [CI] = 0.95–19.63), IL1RL1 rs17026974-AG (OR = 19.07; 95% CI = 1.27–547), and IL1RL1 rs17026974-GG (OR = 16.76; 95% CI = 1.22–438.76). Reduction in oral corticosteroids (OCS) was associated with age of starting omalizumab treatment (OR = 0.95; 95% CI = 0.91–0.99) and blood eosinophil levels > 300 cells/µL (OR = 2.93; 95% CI = 1.01–9.29). Improved lung function showed a relationship to the absence of chronic obstructive pulmonary disease (COPD) (OR = 12.16; 95% CI = 2.45–79.49), FCGR2B rs3219018-C (OR = 8.6; 95% CI = 1.12–117.15), GATA2 rs4857855-T (OR = 15.98; 95% CI = 1.52–519.57) and FCGR2A rs1801274-G (OR = 13.75; 95% CI = 2.14–142.68; AG vs. AA and OR = 7.46; 95% CI = 0.94–89.12; GG vs. AA). Meeting one response criterion was related to FCER1A rs2251746-TT (OR = 24; 95% CI = 0.77–804.57), meeting two to age of asthma diagnosis (OR = 0.93; 95% CI = 0.88–0.99), and meeting all three to body mass index (BMI) < 25 (OR = 14.23; 95% CI = 3.31–100.77) and C3 rs2230199-C (OR = 3; 95% CI = 1.01–9.92). The results of this study show the possible influence of the polymorphisms studied on the response to omalizumab and the clinical benefit that could be obtained by defining predictive biomarkers of treatment response.
The complete chloroplast genome of Striga asiatica (L.) Kuntze 1891 (Orobanchaceae), a hemiparasitic weed from Guangxi China

Abstract Striga asiatica (L.) Kuntze 1891 is a hemiparasitic plant native to Asia and Africa. It is invasive and causes yield losses in crops such as corn, rice and sorghum. Lack of chloroplast genomic data has limited research into its obligate parasitic lifestyle. In this study, the complete chloroplast genome of Striga asiatica was sequenced and characterized. It is a quadripartite structure with a total length of 191,085 bp and a GC content of 37.86%. It has a large single copy region (LSC) of 51,406 bp, a small single copy region (SSC) of 273 bp, and two copies of the reverse repeat sequence (IRA and IRB) of 69,703 bp. A total of 122 protein-coding genes, 8 rRNA genes, and 44 tRNA genes were annotated in the chloroplast genome. There were a lot of ndh gene deletions and pseudogenizations in this chloroplast genome. For example, ndhA, D, E, H, I, and K were all pseudogenes because they were missing the 5′ end start codon. ndhB, C, and J had shorter gene lengths than their homologs, and ndhF and ndhG were missing genes. The phylogenetic tree reveals that all Striga species form a clade, and a bootstrap value of 100 indicates that S. asiatica is closely related to Striga hermonthica and Striga sepera. The comprehensive chloroplast genomic resource of S. asiatica would assist researchers in comprehending hemiparasitic mechanisms, molecular markers, and evolutionary patterns of the genus Striga.
Bridging the Gaps: Advancing the Communication Theory of Identity

ABSTRACT Extending the focus and scope of the communication theory of identity (CTI), this paper introduces a new theoretical construct within CTI’s interpenetration of frames – identity bridging. Theoretical extensions of CTI have established identity gaps, which are inconsistencies between individuals’ personal, enacted, relational, communal, and material identities. Identity bridges represent individuals’ responses to identity gaps. Identity bridging consists of psychological, behavioral, and communicative responses to identity gaps. This paper aims to define identity bridging, outline how past literature advocates the validity of the new construct, examine how identity bridging can be integrated into CTI, explore the relationship between identity gaps and identity bridging, propose extensions to CTI’s current assumptions, and discuss implications and future research directions.
Effects of Non-Solar Abundance Ratios on Star Spectra: Observations versus Models

Abstract Element abundance ratios hold important clues to understanding the evolution of stellar populations, through the varying timescales of different nucleosynthetic contributors. Newly measured and compiled [Mg/Fe] ratios in the MILES stellar library are used to confront models of star spectra. Such models have been used in recent years to provide estimates of differential changes in spectral line strengths, due to enhancements in [α/Fe]. In this paper we test one widely used set of theoretical element response functions. Using magnesium as a proxy for all alpha elements we test the reliability of these theoretical response functions against empirical observations, and thus the reliability of current methods of measuring element abundance ratios in the stellar populations.
Relaxed Policy Iteration Algorithm for Nonlinear Zero-Sum Games With Application to H-Infinity Control

Though policy evaluation error profoundly affects the direction of policy optimization and the convergence property, it is usually ignored in policy iteration methods. This work incorporates the practical inexact policy evaluation into a simultaneous policy update paradigm to reach the Nash equilibrium of the nonlinear zero-sum games. In the proposed algorithm, the restriction of precise policy evaluation is removed by bounded evaluation error characterized by Hamiltonian without sacrificing convergence guarantees. By exploiting Fréchet differential, the practical iterative process of value function with estimation error is converted into the Newton's method with variable steps, which are inversely proportional to evaluation errors. Accordingly, we construct a monotone scalar sequence that shares the same Newton's method with the value sequence to bound the error of the value function, which enjoys an exponential convergence rate. Numerical results show its convergence in affine systems, and the potential to cope with general nonlinear plants.
Assessing the elasticity change of cataract lens with OCE

Cataract is one of the most common degenerative diseases that causes blindness. Careful quantification of lens biomechanical properties can greatly assist in early detection of the disease as well as personalization of treatment procedures. In this study, we utilize a phase-sensitive optical coherence elastography (OCE) system to assess the effects of the cold cataract on the biomechanical properties of porcine crystalline lens in vitro. Relaxation rates of air puff induced elastic waves were measured on the same crystalline lens with and without cold cataract. Results demonstrate that the relaxation rate and, thus, associated elasticity of the porcine lens, increased due to the presence of cold cataract.
The effects of crossover and mutation operators on variable length linear structures

In the search space of variable length strings, it is possible to define crossover and mutation operators that are equivalent to those used in genetic programming on tree structures. We study the effects of these operators on the lengths of strings within a population. It is shown that the distributions by which different string lengths are sampled are strongly biased. To investigate these biases, the effects of repeated application of the operators (without regard for fitness) is considered, and in some cases the fixed-point distributions are found.
Identification of Single-Nucleotide Polymorphisms (SNPs) Associated with Heat Tolerance at the Reproductive Stage in Synthetic Hexaploid Wheats Using GWAS

The projected rise in global ambient temperature by 3–5 °C by the end of this century, along with unpredicted heat waves during critical crop growth stages, can drastically reduce grain yield and will pose a great food security challenge. It is therefore important to identify wheat genetic resources able to withstand high temperatures, discover genes underpinning resilience to higher temperatures, and deploy such genetic resources in wheat breeding to develop heat-tolerant cultivars. In this study, 180 accessions of synthetic hexaploid wheats (SHWs) were evaluated under normal and late wheat growing seasons (to expose them to higher temperatures) at three locations (Islamabad, Bahawalpur, and Tando Jam), and data were collected on 11 morphological and yield-related traits. The diversity panel was genotyped with a 50 K SNP array to conduct genome-wide association studies (GWASs) for heat tolerance in SHW. A known heat-tolerance locus, TaHST1, was profiled to identify different haplotypes of this locus in SHWs and their association with grain yield and related traits in SHWs. There was a 36% decrease in grain yield (GY), a 23% decrease in thousand-grain weight (TKW), and an 18% decrease in grains per spike (GpS) across three locations in the population due to the heat stress conditions. GWASs identified 143 quantitative trait nucleotides (QTNs) distributed over all 21 chromosomes in the SHWs. Out of these, 52 QTNs were associated with morphological and yield-related traits under heat stress, while 15 of them were pleiotropically associated with multiple traits. The heat shock protein (HSP) framework of the wheat genome was then aligned with the QTNs identified in this study. Seventeen QTNs were in proximity to HSPs on chr2B, chr3D, chr5A, chr5B, chr6D, and chr7D. It is likely that QTNs on the D genome and those in proximity to HSPs may carry novel alleles for heat-tolerance genes. The analysis of TaHST1 indicated that 15 haplotypes were present in the SHWs for this locus, while hap1 showed the highest frequency of 25% (33 SHWs). These haplotypes were significantly associated with yield-related traits in the SHWs. New alleles associated with yield-related traits in SHWs could be an excellent reservoir for breeding deployment.
Towards a solution of the Omega problem in power law and chaotic inflation

In recent years it has been suggested that inflation does not necessarily lead to the observable Universe having an energy density very close to the critical density. The original argument is extended to incorporate a general inflationary scenario driven by a scalar field that self-interacts through an arbitrary potential V( phi ). Specific attention is paid to exponential and phi 4-type potentials. It is found that a universe with the observed value of Omega o is possible in these theories when the initial conditions satisfy certain constraints.
Perceived social support among pregnant women attending the antenatal clinic of a tertiary care hospital

BACKGROUND: Social support among pregnant women is identified to have a positive influence on maternal, fetal outcome, personal competence, and self-esteem. This study was conducted with the aim to assess the social support as perceived by pregnant women and to find out the association between perceived social support and sociodemographic, obstetric variables. MATERIALS AND MATERIALS: After obtaining approval from the Institutional Ethics Committee, a cross-sectional study was carried out among pregnant women attending the Antenatal Clinic of a Tertiary Care Hospital for a period of two months. The Multidimensional Scale of Perceived Social Support (MSPSS) was used to assess social support among study participants. RESULTS: A total of 111 pregnant women were included. Majority, 98 (88.30%), were educated till High School. Nearly 87 (78.40%) were in the third trimester and 68 (61.30%) were primigravidae. Mean MSPSS score was found to be 5.36 ± 0.83. Majority, 75 (67.60%), had high social support (mean total score of 5.1-7.0). Those engaged in occupation had 2.922 odds for high social support (adjusted odds ratio = 2.92, 95% confidence interval = 0.612-13.95) when compared to housewives (P < 0.05). Women in third trimester had 2.104 odds for high social support, when compared to those in first and second trimesters (adjusted odds ratio = 2.014, 95% confidence interval = 0.715-6.185). CONCLUSION: Majority scored high on MSPSS. Furthermore, involvement in occupation was found to be a significant predictor of high social support among the study participants.
Estimation of glomerular filtration rate in cardiorenal patients: a step forward

ABSTRACT The progressive reduction in estimated glomerular filtration rate (eGFR) resulting in chronic kidney disease (CKD) is associated with increased risk of cardiovascular disease (CVD) (i.e., cardiorenal disease). Cardiorenal disease is associated with poor outcomes, mainly due to increased cardiovascular (CV) complications and CV death. Data from general population–based studies and studies of cohorts with CKD and/or CVD show that compared with creatinine-based eGFR, cystatin C–based eGFR and creatinine plus cystatin C–based eGFR detect higher risks of adverse CV outcomes and add predictive discrimination to current CVD risk scores. On the other hand, growing clinical evidence supports kidney and CV protective effects of sodium–glucose cotransporter-2 (SGLT2) inhibitors in cardiorenal patients. However, recent data suggest that some detrimental effects of SGLT2 inhibitors on skeletal muscle mass may lead to overestimation of creatinine-based eGFR and subsequent misinterpretation of associated CV risk in patients treated with these agents. Within this framework, we suggest the advisability of using cystatin C and/or creatinine plus cystatin C–based eGFR for routine clinical practice in cardiorenal patients to more accurately stratify CV risk and evaluate the kidney and CV protective effects of SGLT2 inhibitors. In this regard, we make a call to action to investigate the protective effects of these pharmacological agents using cystatin C–based eGFR.
A Multidimensional Parallel Convolutional Connected Network Based on Multisource and Multimodal Sensor Data for Human Activity Recognition

Human activity recognition (HAR) technology based on wearables has received increasing attention in recent years. The traditional methods have used hand-crafted features to recognize human activities, resulting in shallow feature extraction. With the development of deep learning, an increasing number of researchers have focused on studying deep learning methods. To achieve higher recognition accuracy, the majority of the current HAR research involves multisource and multimodal sensors (MMSs) data. However, due to the limitations in the receptive fields of single-dimensional convolutional kernels, these networks are still infeasible for extracting spatiotemporal features. In this study, a multidimensional parallel convolutional connected (MPCC) deep learning network based on MMS data for HAR is proposed that fully utilizes the advantages of multidimensional convolutional kernels. Moreover, multiscale residual convolutional squeeze-and-excitation (MRCSE) modules are proposed to enrich the diversity of feature information by combining squeeze-and-excitation (SE) blocks. A daily home activity (DHA) data set is constructed based on the requirements for HAR in certain scenarios, such as smart home, and we conduct experiments on the optimal combination of sensor locations on the DHA data set according to a weighted <inline-formula> <tex-math notation="LaTeX">$\text{F}1~({\mathrm{ F}}_{\mathrm{ W}})$ </tex-math></inline-formula>-score. Both tenfold and leave-one-subject-out (LOSO) cross-validations (CVs) are used to evaluate the performance of the proposed network. The MPCC-MRCSE network achieves <inline-formula> <tex-math notation="LaTeX">${\mathrm{ F}}_{\mathrm{ W}}$ </tex-math></inline-formula>-scores of 98.33% and 95.42% on the physical activity monitoring for aging people (PAMAP2) and OPPORTUNITY data sets using tenfold CVs, respectively, and achieves <inline-formula> <tex-math notation="LaTeX">${\mathrm{ F}}_{\mathrm{ W}}$ </tex-math></inline-formula>-scores of 81.47% on the PAMAP2 when applying an LOSO CV.
Glioblastoma Microenvironment and Invasiveness: New Insights and Therapeutic Targets

Glioblastoma (GBM) is the most common and malignant primary brain cancer in adults. Without treatment the mean patient survival is approximately 6 months, which can be extended to 15 months with the use of multimodal therapies. The low effectiveness of GBM therapies is mainly due to the tumor infiltration into the healthy brain tissue, which depends on GBM cells’ interaction with the tumor microenvironment (TME). The interaction of GBM cells with the TME involves cellular components such as stem-like cells, glia, endothelial cells, and non-cellular components such as the extracellular matrix, enhanced hypoxia, and soluble factors such as adenosine, which promote GBM’s invasiveness. However, here we highlight the role of 3D patient-derived glioblastoma organoids cultures as a new platform for study of the modeling of TME and invasiveness. In this review, the mechanisms involved in GBM-microenvironment interaction are described and discussed, proposing potential prognosis biomarkers and new therapeutic targets.