Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of National Board Certified Teachers on Students' Social-Emotional Competencies

The study examined the effect of National Board Certified Teachers (NBCTs) on social-emotional competencies of fifth and sixth graders in the 2018 – 19 academic year in Spokane, Washington. The study used archival data and quasi-experimental design with matching to compare social-emotional competencies of students taught by NBCTs and students taught by non-NBCTs. The study examined 10 social-emotional competencies. The results suggest that NBCTs are significantly more effective than non-NBCTs at facilitating students’ self-efficacy approximately 2 months after the start of the school year (effect size = 0.21). Results for self-management are in the same direction (effect size = 0.10), however not statistically significant. Findings for the remaining eight social-emotional competencies are not statistically significant, and the effect sizes are small. The results also suggest that NBCTs are effective at developing social-emotional competencies for students who are native English speakers for two social-emotional measures: self-efficacy (effect size = .23) and social awareness (effect size = .16). The study is the first attempt to rigorously examine the effect of NBCTs on students’ social-emotional competencies. Although the evidence is encouraging, additional rigorous research is needed to make confident conclusions, particularly for students who are English language learners and from different racial/ethnic subgroups because of the small number of these students in the current study.
Proteasomes Are Critical for Maintenance of CD133+CD24+ Kidney Progenitor Cells

Kidney progenitor cells, although rare and dispersed, play a key role in the repair of renal tubules after acute kidney damage. However, understanding these cells has been challenging due to the limited access to primary renal tissues and the absence of immortalized cells to model kidney progenitors. Previously, our laboratory utilized the renal proximal tubular epithelial cell line, RPTEC/TERT1, and the flow cytometry technique to sort and establish a kidney progenitor cell model called Human Renal Tubular Precursor TERT (HRTPT) which expresses CD133 and CD24 and exhibits the characteristics of kidney progenitors, such as self-renewal capacity and multi-potential differentiation. In addition, a separate cell line was established, named Human Renal Epithelial Cell 24 TERT (HREC24T), which lacks CD133 expression and shows no progenitor features. To further characterize HRTPT CD133+CD24+ progenitor cells, we performed proteomic profiling which showed high proteasomal expression in HRTPT kidney progenitor cells. RT-qPCR, Western blot, and flow cytometry analysis showed that HRTPT cells possess higher proteasomal expression and activity compared to HREC24T non-progenitor cells. Importantly, inhibition of the proteasomes with bortezomib reduced the expression of progenitor markers and obliterated the potential for self-renewal and differentiation of HRTPT progenitor cells. In conclusion, proteasomes are critical in preserving progenitor markers expression and self-renewal capacity in HRTPT kidney progenitors.
Research into Image Point Positioning Compensation of a High-Orbit Thermal Infrared Staring Camera

The sight of the high-orbit thermal infrared staring camera is concentrated and sensitive to temperature changes, and therefore its image point positioning is key to ensuring the geometric quality of the thermal infrared staring image and eliminating the errors of the imaging system in orbit. According to the geometric imaging characteristics of the high-orbit thermal infrared staring camera, internal and external positioning compensation models are proposed in this paper based on the two-dimensional pointing angle of temperature change, and four kinds of experimental schemes of image point positioning compensation are designed. The experimental results show that the method proposed in this paper has a good compensation effect on the image point positioning error.
One-Step Assembly of a PRRSV Infectious cDNA Clone and a Convenient CRISPR/Cas9-Based Gene-Editing Technology for Manipulation of PRRSV Genome

Porcine reproductive and respiratory syndrome (PRRS) has been a persistent challenge for the swine industry for over three decades due to the lack of effective treatments and vaccines. Reverse genetics systems have been extensively employed to build rapid drug screening platforms and develop genetically engineered vaccines. Herein, we rescued recombinant PRRS virus (rPRRSV) WUH3 using an infectious cDNA clone of PRRSV WUH3 acquired through a BstXI-based one-step-assembly approach. The rPRRSV WUH3 and its parental PRRSV WUH3 share similar plaque sizes and multiple-step growth curves. Previously, gene-editing of viral genomes depends on appropriate restrictive endonucleases, which are arduous to select in some specific viral genes. Thus, we developed a restrictive endonucleases-free method based on CRISPR/Cas9 to edit the PRRSV genome. Using this method, we successfully inserted the exogenous gene (EGFP gene as an example) into the interval between ORF1b and ORF2a of the PRRSV genome to generate rPRRSV WUH3-EGFP, or precisely mutated the lysine (K) at position 150 of PRRSV nsp1α to glutamine (Q) to acquire rPRRSV WUH3 nsp1α-K150Q. Taken together, our study provides a rapid and convenient method for the development of genetically engineered vaccines against PRRSV and the study on the functions of PRRSV genes.
A Transformer-Based Real-Time Focus Detection Technique for Wide-Field Interferometric Microscopy

Wide-field interferometric microscopy (WIM) has been utilized for visualization of individual biological nanoparticles with high sensitivity. However, the image quality is highly affected by the focusing of the image. Hence, focus detection has been an active research field within the scope of imaging and microscopy. To tackle this issue, we propose a novel convolution and transformer based deep learning technique to detect focus in WIM. The method is compared to other focus detecton techniques and is able to obtain higher precision with less number of parameters. Furthermore, the model achieves real-time focus detection thanks to its low inference time.
Mālama nā makua i nā keiki me ka hānō: Native Hawaiian Parents Car- ing for Their Children with Asthma

Native Hawaiian children have the highest prevalence rate of asthma among all ethnicities in the State of Hawai‘i. Literature is limited regarding native Hawaiian parents’ perception and experience caring for their children with asthma. The purpose of this study is to explore contemporary native Hawaiian parents’ perspective and experience of caring for their children with asthma in the context of uncertainty. We applied a descriptive qualitative approach by means of directed content analysis using focus groups. Directed content analysis applied Mishel’s Uncertainty in Illness Theory to guide data collection, organization, and analysis. We found that parents’ personal stories about their children to be rich and enlightening. Findings verified that native Hawaiian parents experience uncertainty regarding asthma care as commonly described in the literature. Contextual influences including indigenous worldview and cultural values affected native Hawaiian parents’ perceptions and experiences with conventional asthma care. Unique findings involved the etiology of asthma, features of social support (‘ohana), and differentiation between Western medicine and traditional healing practices. As nurses focus on supporting the family’s cultural values and preferences related to asthma care and alternative remedies, native Hawaiian parents’ care of their children with asthma will be strengthened.
Advanced Control Systems for Axial Piston Pumps Enhancing Variable Mechanisms and Robust Piston Positioning

Axial piston pumps provide a number of benefits, including strong pressure resistance, high efficiency, high transmission power, a broad speed range, and a long lifespan. These characteristics have led to their widespread usage in naval applications, construction machines, and hydraulic machinery. On the other hand, axial piston pumps frequently display reduced operating speeds as well as instability because of their inherently nonlinear properties. In this study, a mathematical model of these changeable (variable) processes is developed using a mix of theoretical calculations and acquired data. An investigation of variable mechanism control in axial piston pumps is carried out centered on robust control methods, and the controller is constructed utilizing robust H∞ theory. In terms of resilience, control precision, and system reaction time, simulations show that the H controller surpasses the PID controller.
A PUF Based on the Non-Linearity of Memristors

As autonomous devices are increasingly used in security and safety-critical applications the security of the systems they comprise is of increasing concern. In such situations it is important that devices can be securely identified and trusted. When an IC or device is in the supply chain, or in the field, the lack of control over actors who can obtain physical access can compromise the trust and overall security of a system. Counterfeit chips may be incorporated into the device, compromising reliability or security. Additionally, for implemented devices, keys stored on-device may be copied by a bad actor. To help improve the security of such devices this paper proposes a new physical unclonable function (PUF) architecture, based on a TiOx memristor-based resistive memory (RRAM), that exploits the inherent analogue non-linearity in resistance of some memristor technologies. By directly exploiting non-linearity of memristor cells, rather than relying on the devices' absolute resistance at a single test voltage, a multi-bit-per-comparison PUF is created. As the architecture directly exploits cells' non-linearity, an additional source of hard-to-clone entropy is incorporated.
Application study on the recognition of oral obstructed tooth images using semantic segmentation

Oral obstructive teeth are abnormal tooth development due to dysplasia or pressure on surrounding teeth and usually need to be removed during oral surgery. Prior to surgery, the surgeon needs to perform diagnostic imaging to determine the location and shape of the blocked tooth and to plan the surgical plan. Traditional diagnostic imaging methods mainly use radiographs and CT images, but these methods require manual measurement and analysis, which are complex and prone to errors. There is a fast development in Computer Vision and Deep Learning, semantic segmentation recognition of oral obstructive tooth images has become a new solution. In this paper, we will study the semantic segmentation recognition of oral obstructive dental images and propose a deep learning based semantic segmentation method for oral obstructive dental images.
Study on the failure prediction method of urban building materials based on the wavelength variation rule of rare earth ions*

With the continuous development of smart cities, the failure prediction of urban building structure materials has also become an unignorable part of smart city construction. In this study, $\mathrm{Eu}^{3+}$ was selected as the luminescent center, and $\mathrm{Eu}^{3+}$ was doped into Y3Al5O12 fibers (referred to as $(\mathrm{YAG}:\mathrm{Eu}^{3+})_{{\mathrm{sf}}}$ later in the paper) by electrostatic spinning method, which makes this fiber with luminescent performance and stress sensing function. The $(YAG:\mathrm{Eu}^{3+})_{\text{sf}}$ reinforced aluminum matrix composites were prepared by vacuum hot press sintering, and the emission spectra of $(\mathrm{YAG}:\mathrm{Eu}^{3+})_{\text{sf}}$ reinforced aluminum matrix composites were recorded by a continuous spectral response system under tensile stresses, and the structural changes within the composites were characterized using in situ XRD, and the relationship between the emission spectra of composites and the internal stresses of materials was analyzed. The relationship between the emission spectra of composites and the internal stresses of the materials was analyzed and empirical equations were established to provide a new method for the failure prediction of composites
Agrobacterium rhizogenes-mediated Hairy root Formation in Some Rubia tinctorum L. Populations Grown in Turkey

Rubia tinctorum L. seeds were collected from 4 different regions of Turkey. Plants were grown in greenhouse and cotyle- dons were inoculated with Agrobacterium rhizogenes strains 15834, 2628, R1000 and 9365. Rubia tinctorum plants were also grown in the field for comparative analysis of root anthraquinone content. Agrobacterium rhizogenes strain 2628 induced only callus formation on the cut surface of cotyledon explants while strains 15834, R1000 and 9365 produced hairy roots on the same explants. Anthraquinone content was identified in the extracts of the plant roots grown in the field and in the extracts of the Agrobacterium rhizogenes-induced hairy roots. The percentage of anthraquinone pres- ent in the plant roots was found to be different from that in the hairy roots.
Secrecy Maximization for Pico Edge Users in 5G Backhaul HWNs: A Quantum RL Approach

Picocells can enhance the capacity and spectral efficiency of heterogeneous wireless networks (HWNs) and reduce user equipment (UE) power consumption. Also, the wireless backhaul technology has emerged as an efficient way to boost the data rate in dense 5G HWNs. However, due to the dynamic and distributed nature of 5G HWNs, pico edge users (PEUs) cannot resist the eavesdropping attempts. Moreover, the PEUs are located far away from the PBS and receive considerably low signal-to-interference-plus-noise ratio (SINR) values. Thus, it is critical to improve the achievable secrecy rate (SR) of PEUs for reliable and secure transmission of confidential data in the existence of eavesdroppers. Aiming to enhance the SR of PEUs, this paper formulates a joint optimization problem of beamforming and power allocation of millimeter-wave (mmWave)enabled pico base station (PBS) having backhaul wireless links with macro base station (MBS). As the system is diverse and complex, addressing this non-convex optimization problem directly is challenging. Thus, we have used the Markov decision process (MDP) to transform this optimization problem into a multi-agent reinforcement learning (MARL) problem. Then, to determine the optimal policy for MARL problem of beamforming and power allocation, we propose a Quantum reinforcement learning (QRL) approach. It uses quantum parallelism and state superposition principles to maximize the SR of PEUs. Simulation results indicate that the proposed scheme achieves 28.12% and 7.9% better secrecy rate than MAQL and MADQL schemes, respectively.
Development and Application of a novel anaerobic/aerobic/anoxic process in municipal wastewater treatment utilizing intracellular carbon sources

Municipal wastewater treatment plants (WWTPs) face a significant challenge in controlling treatment costs while meeting increasingly stringent wastewater discharge standards. To address this challenge, A novel anaerobic/anoxic/aerobic (AOA) process has been proposed. In this study, long-term nutrient removal and microbial community variations were investigated in the AOA systems of different scales, including three laboratory-scale systems, one pilot-scale and one full-scale systems. In the AOA system, nitrogen removal exceeded 50% was carried out in the post-anoxic zone via endogenous denitrification driven by intracellular carbon sources. The synergistic effect of denitrifying bacteria (DNB), anaerobic ammonium oxidation (anammox) bacteria, and fermentative bacteria (FB) enhanced nitrogen removal. Advanced nutrient removal was successfully achieved in the AOA process under different environments and influent quality. Under a low influent carbon-nitrogen ratio, the effluent total nitrogen (TN) concentration was 3.6-8.7 mg/L, with a TN removal efficiency of 71-95%. Total phosphorus (TP) concentration in effluent of 0.2-0.3 mg/L was also achieved. Moreover, compared to the widely used anaerobic/aerobic/anoxic (AAO) process, the AOA process reduced 60% of energy consumption by aeration and recirculation. In conclusion, the AOA process has the potential for practical implementation and provides an economical and efficient nutrient removal process for municipal wastewater treatment.
Fashion Technology Research: A Scientometric Analysis

The paper brings out the results of a scientometric analysis of research publications in the field of fashion technology research during the period 1970-2013. It analyses 1,52,681 articles in the field of Fashion technology.It examines year wise distribution of articles, country wise distribution,languages distribution and bibliographic form of articles,doubling time, relative growth rate, high productive Institutes etc. inferences and findings are shown with relevant data analysis.
An educational intervention study to enhance breast cancer awareness among women and primary healthcare providers of an urban health center area, Visakhapatnam

Background: Breast cancer is the most common malignancy in women worldwide posing greater health challenge. The poor survival rate from breast cancer in India may be attributed to lack of awareness, low rate of screening uptake and presentation of cases in advanced stage. Objectives: To assess the baseline knowledge and effectiveness of educational intervention in improving the knowledge regarding breast cancer. Materials and Methods: A quasi-experimental community-based health educational intervention study was performed among 100 women and 18 female primary healthcare providers residing in urban field practice area. Face-to-face interviews were performed using a questionnaire adapted from the Breast Cancer Awareness Measure (Breast-CAM) Version 2. Data were analyzed using SPSS version 25. To assess the difference between pre- and postintervention scores, Mc-Nemar's test and paired sample t tests were applied. Association between socio-demographic variables and difference in mean scores was assessed by using ANOVA and independent t test. P value less than 0.05 was taken as statistically significant. Results: The mean pre-intervention score of knowledge items (21 including warning signs, risk factors of breast cancer) among 100 women participants was 7.19 ± 3.45 and postintervention mean score was 18.18 ± 2.42. The mean pre-intervention score among 18 primary healthcare providers was 10.89 ± 4.59 and postintervention score was 19.89 ± 1.28. There was significant improvement in mean scores. The increase in percentage of scores in all 21 items postintervention was significant (Mc-Nemar's test). There was significant association between socio-demographic profile and increase in mean scores. The study identified various barriers for seeking medical care among women. Conclusion: The community-based educational intervention was effective in enhancing the knowledge regarding breast cancer among women.
Brain Network Analysis of Schizophrenia Patients Based on Hypergraph Signal Processing

Since high-order relationships among multiple brain regions-of-interests (ROIs) are helpful to explore the pathogenesis of neurological diseases more deeply, hypergraph-based brain networks are more suitable for brain science research. Unlike the existing hypergraph based brain network (brain hypernetwork), where hyperedges containing the same number of ROIs are assumed to have equal weights (to some extent, the network is unweighted), and the underlying structure is described only by an incidence/adjacency matrix, in this paper, we propose a framework for constructing a truly weighted brain hypernetwork described by an adjacency tensor. Considering the relationships among vertices within a hyperedge, we propose a novel hyperedge weight estimation method and convert the incidence matrix into a weighted adjacency tensor. On the basis of tensor decomposition, we apply hypergraph signal processing tools, such as hypergraph Fourier transform, to analyze and compare the spectrum between schizophrenia patients and normal controls. It is found that there are more high frequency components in the spectrum of patients than controls, and the average amplitude is significantly greater than that of controls. Instead of extracting some simple topological features from brain hypernetworks for classification, we innovatively use the hypergraph spectrum and the spectral signal as classification features, and the classification results on two public datasets demonstrate the effectiveness of our proposed method.
Sputtered Zinc Electrodes on Pullulan Substrates for Flexible Biodegradable Transient Electronics

Biodegradable transient electronics, devices which easily breakdown to safe constituent parts at their end of life, are an important emerging research direction for tackling electronic waste, as well as enabling new applications such as wearable health monitors which can easily be washed off the body at the end of use. Pullulan is a widely used edible substrate which naturally biodegrades and has previously been used with Silver tracks for creating transient electronics. However, Silver tracks are not generally biodegradable. This paper demonstrates the creation of Zinc tracks for biodegradable transient devices, where the Zinc is approximately half of the recommended daily allowance to Zinc to be ingested. We demonstrate resistivities in the range 1–10 $\Omega/\square$ for potential use in electrode and antenna applications.
Mechanical Behavior and Sealing Performance Study of Subsea Connector Core-Sealing Components under the Combined Action of Internal Pressure, Bending Moment, and Axial Load

A complete subsea production system (SPS) is assembled by interconnecting subsea manufacturing facilities through subsea connectors. To ensure the reliability and longevity of the SPS, it is imperative to thoroughly investigate the mechanical behavior and sealing performance of the subsea connector’s core-sealing components. In this study, the loading conditions of the subsea clamp connector are examined to analyze the load transfer relationship between its components under different modes. A mathematical model for the load transfer between locking torque and sealing contact pressure is developed for the preloading mode, and the concept of mechanical transfer efficiency is introduced. Another mathematical model for the load transfer between the locking torque and the design pressure is developed for the operation mode. Furthermore, a three-dimensional full-size finite element model of the subsea clamp connector is established to analyze the effects of complex loads on the mechanical behavior and sealing performance of its core-sealing components. The simulation results indicate that internal pressure loading positively affects the sealing of the subsea connector, and that the stress distribution in the core-sealing components under bending moment loading exhibits significant asymmetric characteristics. Additionally, the superposition of axial tensile loads reduces the effect of the bending moment on the strength of the core seal member but further weakens the seal. Finally, an experimental system is designed to validate the simulation results.