Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultrawide bandgap semiconductor heterojunction p-n diodes with distributed polarization doped p-type AlGaN layers on bulk AlN substrates

Ultrawide bandgap heterojunction p-n diodes with polarization-induced AlGaN p-type layers are demonstrated using plasma-assisted molecular beam epitaxy on bulk AlN substrates. Current-voltage characteristics show a turn on voltage of $V_{\text{bi}}\approx5.5$ V, a minimum room temperature ideality factor of $\eta\approx 1.63$, and more than 12 orders of current modulation at room temperature. Stable current operation of the ultrawide bandgap semiconductor diode is measured up to a temperature of 300$^\circ$C. The one-sided n$^{+}$-p heterojunction diode design enables a direct measurement of the spatial distribution of polarization-induced mobile hole density in the graded AlGaN layer from the capacitance-voltage profile. The measured average mobile hole density is $p \sim 5.7 \times 10^{17}$ cm$^{-3}$, in close agreement with what is theoretically expected from distributed polarization doping. Light emission peaked at 260 nm (4.78 eV) observed in electroluminescence corresponds to interband radiative recombination in the n$^{+}$ AlGaN layer. A much weaker deep-level emission band observed at 3.4 eV is attributed to cation-vacancy and silicon complexes in the heavily Si-doped AlGaN layer. These results demonstrate that distributed polarization doping enables ultrawide bandgap semiconductor heterojunction p-n diodes that have wide applications ranging from power electronics to deep-ultraviolet photonics. These devices can operate at high temperatures and in harsh environments.
Piezoelectric Soft Robot Inchworm Motion by Tuning Ground Friction through Robot Shape: Quasi-Static Modeling and Experimental Validation

Electrically-driven soft robots based on piezoelectric actuators may enable compact form factors and maneuverability in complex environments. In most prior work, piezoelectric actuators are used to control a single degree of freedom. In this work, the coordinated activation of five independent piezoelectric actuators, attached to a common metal foil, is used to implement inchworm-inspired crawling motion in a robot that is less than 0.5 mm thick. The motion is based on the control of its friction to the ground through the robot's shape, in which one end of the robot (depending on its shape) is anchored to the ground by static friction, while the rest of its body expands or contracts. A complete analytical model of the robot shape, which includes gravity, is developed to quantify the robot shape, friction, and displacement. After validation of the model by experiments, the robot's five actuators are collectively sequenced for inchworm-like forward and backward motion.
Machine learning and feature selection: Applications in economics and climate change

Abstract Feature selection is an important component of machine learning for researchers that are confronted with high dimensional data. In the field of economics, researchers are often faced with high dimensional data, particularly in the studies that aim to understand the channels through which climate change affects the welfare of countries. This work reviews the current literature that introduces various feature selection algorithms that may be useful for applications in this area of study. The article first outlines the specific problems that researchers face in understanding the effects of climate change on countries’ macroeconomic outcomes, and then provides a discussion regarding different categories of feature selection. Emphasis is placed on two main feature selection algorithms: Least Absolute Shrinkage and Selection Operator and causality-based feature selection. I demonstrate an application of feature selection to discover the optimal heatwave definition for economic outcomes, enhancing our understanding of extreme temperatures’ impact on the economy. I argue that the literature in computer science can provide useful insights in studies concerned with climate change as well as its economic outcomes.
A systematic review of peer support interventions for student mental health and well-being in higher education

Background Higher education institutions (HEIs) are seeking effective ways to address the rising demand for student mental health services. Peer support is widely considered a viable option to increase service capacity; however, there are no agreed definitions of peer support, making it difficult to establish its impact on student mental health and well-being. Aims This systematic review aims to better understand and evaluate peer support in HEIs. Method Five databases, OpenGrey and Grey Matters were searched in May 2021. Included studies were quantitative, longitudinal (with and without a control) or cross-sectional with a control. The vote-counting method was used for synthesis. The risk of bias was assessed with the National Institutes of Health Quality Assessment Tool. Results Three types of peer support were represented in 28 papers: peer-led support groups, peer mentoring and peer learning. Peer learning and peer mentoring had more positive, significant results reported for the outcomes of anxiety and stress. Peer-led support groups were the only type targeting students with mental health difficulties. Conclusions The heterogeneity of measures and outcomes prevents firm conclusions on the effectiveness of peer support for mental health and well-being. Most studies were rated ‘poor’ or ‘fair’ in their risk of bias. There is not a solid evidence base for the effectiveness of peer support. Nonetheless, HEIs can use the terminology developed in this review for shared discussions that guide more robust research and evaluation of peer support as an intervention.
Quality of fluid balance charting and interventions to improve it: a systematic review

Introduction Fluid balance monitoring is pivotal to patients’ health. Thus, fluid balance charting is an essential part of clinical nursing documentation. This systematic review aimed to investigate and describe the quality of fluid balance monitoring in medical, surgical and intensive care units, with an emphasis on the completeness of charting data, calculation errors and accuracy, and to evaluate methods used to improve fluid balance charting. Materials and methods Quantitative studies involving adult patients and reporting data on fluid balance monitoring were included in the review. We searched MEDLINE, Embase, CINAHL and the Cochrane Library. The risk of bias in the included studies was assessed using tools developed by the Joanna Briggs Institute. Results We included a total of 23 studies, which involved 6649 participants. The studies were quasi-experimental, cohort or prevalence studies, and every third study was of low quality. Definitions of ‘completeness’ varied, as well as patient categories and time of evaluation. Eighteen studies reported the prevalence of patients with complete fluid balance charts; of those, 10 reported that not more than 50% of fluid balance charts were complete. Studies addressing calculation errors found them in 25%–35% of charts, including omissions of, for example, intravenous medications. The reported interventions consisted of various components such as policies, education, equipment, visual aids, surveillance and dissemination of results. Among studies evaluating interventions, only 38% (5 of 13) achieved compliance with at least 75% of complete fluid balance charts. Due to the heterogeneity of the studies, a meta-analysis was not possible. Conclusion The quality of fluid balance charting is inadequate in most studies, and calculation errors influence quality. Interventions included several components, and the impact on the completion of fluid balance charts varied.
Grand Challenges in Printed Circuit Board Defect Detection Based on Image Processing

It is difficult to avoid defects in the production process of printed circuit boards. Traditional manual methods are not effective. In recent years, deep learning has been gradually applied to printed circuit board (PCB) detection, but the accuracy is still not high. This paper starts with PCB image defect detection, preprocesses the image through image graying, grayscale histogram equalization and Gaussian filtering, uses machine vision technology to realize global defect detection and location, uses deep learning method in feature extraction, and then proposes a multi-scale feature fusion method, which has high quality of feature extraction, and forms a Resnet101 fine-tuning network. The network is trained and verified on the PCB image data set through migration learning. Experiments show that the recognition rate of the improved Resnet101 fine-tuning neural network is significantly improved, and its average accuracy is also higher. Finally, defect target detection of PCB image is realized based on fast RCNN algorithm. By improving the Faster RCNN algorithm, the efficiency and accuracy of target detection are improved. Experiments show that the average accuracy and mAP value of the algorithm are also higher than others, which verifies the effectiveness and versatility of the algorithm and has high practical value.
Analysis of Social Interrelationship with Multi-Source Interactive Information

Social relationship analysis is the primary issue of numerous issues concerning social computing. In the traditional social relationship analysis, the attribute of social relation is regarded as objective and independent of the subjective cognition of the participant. However, in real life, there are always differences between the cognitions about the relationship attributes of the two parties involved in the relationship. In this paper, we research the strength of social relationships. And we utilize the content of the interactive language between individuals to depict and analyze the subjective cognition about the relationship strength from the two participants in the relationship and the asymmetry of this cognition. Based on the critical features of interactive language in the theory of social linguistics, this paper proposes four kinds of language features that can be used to describe the key features of interactive language, including frequency, length, fluency, and sentiment polarity. Through the discussion and distinction of the language habit differences and subjective cognitive differences, we verify the asymmetry of the emotional cognition about the relationship strength from the two participants in the relationship by using the email data after eliminating interference from the factor of individual language habits. The experimental results show that linguistic information is more accurate than topological information in expressing and describing social relations, and the information contained in the combination of them is more abundant, and the effect is better than using any kind of information alone.
Mycoparasitic Sporothrix insectorum on Entomopathogenic Fungus Hirsutella citriformis on Diaphorina citri at Huasteca Potosina and Llera, Mexico

Abstract. In Mexico, Huanglongbing infection caused 42 and 33% decreases in orange and lemon production, respectively. Asian citrus psyllid, Diaphorina citri Kuwayama (Hemiptera: Liviidae), is a vector of Candidatus Liberibacter bacterium that causes the disease. Commercial orchards were searched to identify entomopathogenic fungi of D. citri in the citrus zone of Huasteca Potosina, San Luis Potosi, and Llera, Tamaulipas, Mexico. Entomopathogenic fungi associated with Asian citrus psyllid adults are in three genera: Hirsutella citriformis (88%), Beauveria bassiana (2%), and Sporothrix insectorum (10%). This is the first report of Sporothrix insectorum parasitizing H. citriformis in México. Resumen. En México, el Huanglongbing ha causado pérdidas en la producción de naranja y limón del 42 y 33% respectivamente. El psílido asiático de los cítricos Diaphorina citri Kuwayama (Hemíptera: Liviidae), es el vector de la bacteria Candidatus Liberibacter causante de la enfermedad. En huertos comerciales de la zona citrícola de la Huasteca Potosina, San Luis Potosí y Llera, Tamaulipas, México se realizaron búsquedas de los hongos entomopatógenos presentes en D. citri. Encontramos tres géneros en el psílido, Hirsutella citriformis (88%), Beauveria bassiana (2%), y Sporothrix insectorum (10%). Este es el primer reporte de Sporothrix insectorum parasitando a H. citriformis en México.
Integrating palliative care and heart failure: a systematic realist synthesis (PalliatHeartSynthesis)

Objectives (1) Develop a programme theory of why, for whom and in what contexts integrated palliative care (PC) and heart failure (HF) services work/do not work; (2) use the programme theory to co-produce with stakeholders, intervention strategies to inform best practice and future research. Methods A systematic review of all published articles and grey literature using a realist logic of analysis. The search strategy combined terms significant to the review questions: HF, PC and end of life. Documents were included if they were in English and provided data relevant to integration of PC and HF services. Searches were conducted in November 2021 in EMBASE, MEDLINE, PsycINFO, AMED, HMIC and CINAHL. Further relevant documents were identified via monthly alerts (up until April 2023) and the project stakeholder group (patient/carers, content experts and multidisciplinary practitioners). Results 130 documents were included (86 research, 22 literature reviews, 22 grey literature). The programme theory identified intervention strategies most likely to support integration of PC and HF services. These included protected time for evidence-based PC and HF education from undergraduate/postgraduate level and continuing professional practice; choice of educational setting (eg, online, face-to-face or hybrid); increased awareness and seeing benefits of PC for HF management; conveying the emotive and intellectual need for integrating PC and HF via credible champions; and prioritising PC and HF guidelines in practice. Conclusions The review findings outline the required steps to take to increase the likelihood that all key players have the capacity, opportunity and motivation to integrate PC into HF management. PROSPERO registration number CRD42021240185.
The impact of PCR duplication on RNAseq data generated using NovaSeq 6000, NovaSeq X, AVITI and G4 sequencers

RNA sequencing (RNA-seq) is a powerful technology for gene expression and functional genomics profiling. Expression profiles generated using this approach can be impacted by the methods utilised for cDNA library generation. Selection of the optimal parameters for each step during the protocol are crucial for acquisition of high-quality data. Polymerase chain reaction (PCR) amplification of transcripts is a common step in many RNA-seq protocols and, if not optimised, high PCR duplicate proportions can be generated, resulting in the inflation of transcript counts and introduction of bias. In this study, we investigate the impact of input amount and PCR cycle number on the PCR duplication rate and on the RNA-seq data quality using a broad range of inputs (1 ng -1,000 ng) for RNA-seq library preparation with unique molecular identifiers (UMIs) and sequencing the data on four different short-read sequencing platforms: Illumina NovaSeq 6000, Illumina NovaSeq X, Element Biosciences AVITI, and Singular Genomics G4. Across all platforms, samples of input amounts greater than 125 ng had a negligible PCR duplication rate and the number of PCR cycles did not have a significant effect on data quality. However, for input amounts lower than 125ng we observed a strong negative correlation between input amount and the proportion of PCR duplicates; between 34% and 96% of reads were discarded via deduplication. Fortunately, UMIs were effective for removing in silico PCR duplicates without removing valuable biological information. Removal of PCR duplicates resulted in more comparable gene expression obtained from the different PCR cycles. Data generated with each of the four sequencing platforms presented similar associations between starting material amount and the number of PCR cycles on PCR duplicates, a similar number of genes detected, and comparable gene expression profiles. However, the sequencers using conversion kits for Illumina libraries (AVITI, G4) exhibited lower adapter dimer abundance across all input amounts, but also a higher PCR duplication rate in very low input amounts (<15ng). Overall, this study showed that the choice of input amount and number of PCR cycles are important parameters for obtaining high-quality RNA-seq data across all sequencing platforms. UMI deduplication is an effective way to remove PCR duplicates, improving the data quality and removing any variation caused by the conversion kits.
EGCG promotes the sensory function recovery in rats after dorsal root crush injury by upregulating KAT6A and inhibiting pyroptosis

Abstract Dorsal root injury usually leads to irreversible sensory function loss and lacks effective treatments. (−)-epigallocatechin-3-gallate (EGCG) is reported to exert neuroprotective roles in the nervous systems. However, the function of EGCG in treating dorsal root injury remains unclear. Hence, we built the dorsal root crush injury (DRCI) rat model to be treated with EGCG, followed by the western blot, Enzyme-linked immunosorbent assay, and sensory behavior tests. We observed that EGCG can upregulate the Lysine acetyltransferase 6A (KAT6A) level and inhibit the pyroptosis, indicated by downregulated gasdermin-D, caspase-1, and interleukin 18 protein levels, and alleviate the neuropathic pain, indicated by the decreased paw withdraw threshold in Plantar test and decreased paw withdraw latency in von Frey test, and downregulated calcitonin gene-related peptide, nerve growth factor, and c-Fos protein levels. But EGCG cannot alleviate the neuropathic pain when the KAT6A was inhibited by CTX-0124143 and pyroptosis was activated by Miltirone. These combined results indicated that EGCG can promote the sensory function recovery in rats after DRCI via upregulating KAT6A and inhibiting pyroptosis, laying the foundation for EGCG to be a novel candidate for the treatment of dorsal root injury.
Accuracy prediction of wearable flexible smart gloves

Abstract This article aimed at providing a new biomechanical three-dimensional dynamic finite element model of the hand–glove combination for exploring the distribution of the overall continuous dynamic contact pressure of the hand with the flexible glove in the state of grabbing an object, and further predicting the accuracy of sensors of wearable smart gloves. The model was validated by garment pressure experiments at eight muscle points. The results showed that the pressure value measured with three flexible gloves was highly consistent with the finite element simulation value. Based on the model, the distribution of dynamic pressure between the soft tissue of the hand and the fabric in the process of flexing the fingers and grabbing external objects were predicted accurately and effectively, which indicated that the model with high accuracy could be applied to evaluate the accuracy of the pressure value collected by sensors of smart gloves. In addition, the model had been confirmed that it has a certain application value. The findings could help to provide a reference for dynamic continuous monitoring equipment or other intelligent wearable devices, and promote the development of the intelligent clothing industry in the future.
Basement membrane extract potentiates the endochondral ossification phenotype of bone marrow-derived mesenchymal stem cell-based cartilage organoids

Endochondral ossification is a developmental process in the skeletal system and bone marrow of vertebrates. During endochondral ossification, primitive cartilaginous anlages derived from mesenchymal stem cells (MSCs) undergo vascular invasion and ossification. In vitro regeneration of endochondral ossification is beneficial for research on the skeletal system and bone marrow development as well as their clinical aspects. However, to achieve the regeneration of endochondral ossification, a stem cell-based artificial cartilage (cartilage organoid, Cart-Org) that possesses an endochondral ossification phenotype is required. Here, we modified a conventional 3D culture method to create stem cell-based Cart-Org by mixing it with a basement membrane extract (BME) and further characterized its chondrogenic and ossification properties. BME enlarged and matured the bone marrow MSC-based Cart-Orgs without any shape abnormalities. Histological analysis using Alcian blue staining showed that the production of cartilaginous extracellular matrices was enhanced in Cart-Org treated with BME. Transcriptome analysis using RNA sequencing revealed that BME altered the gene expression pattern of Cart-Org to a dominant chondrogenic state. BME triggered the activation of the SMAD pathway and inhibition of the NK-κB pathway, which resulted in the upregulation of SOX9, COL2A1, and ACAN in Cart-Org. BME also facilitated the upregulation of genes associated with hypertrophic chondrocytes (IHH, PTH1R, and COL10A1) and ossification (SP7, ALPL, and MMP13). Our findings indicate that BME promotes cartilaginous maturation and further ossification of bone marrow MSC-based Cart-Org, suggesting that Cart-Org treated with BME possesses the phenotype of endochondral ossification. Highlights Basement membrane extract (BME) enlarges MSC-based Cart-Org. BME activates the SMAD pathway and inhibits the NK-kB pathway of the Cart-Org. BME promotes cartilaginous maturation and further ossification of Cart-Org.
Study protocol for a single-blind, parallel-group, randomised, controlled non-inferiority trial of 4-day intensive versus standard cognitive behavioural therapy for adults with obsessive–compulsive disorder

Introduction Individual cognitive behavioural therapy (CBT) with exposure and response prevention is an effective treatment for obsessive–compulsive disorder (OCD). However, individual CBT is costly and time-consuming, requiring weekly therapy sessions for 3–4 months. A 4-day intensive version of CBT for OCD delivered in group format has been recently developed in Norway (Bergen 4-day treatment, B4DT). B4DT has shown promising results in several uncontrolled and one small, randomised trial, but its non-inferiority to the gold standard treatment has not been established. Methods and analysis This single-blind, randomised controlled trial including 120 patients (60 per arm) will compare B4DT to individual CBT. The primary outcome is the blind assessor-rated Yale-Brown Obsessive Compulsive Scale (Y-BOCS). We hypothesise that B4DT will be non-inferior to gold standard CBT 15 weeks after treatment start. The non-inferiority margin is set at four points on the Y-BOCS. Secondary outcomes include time to treatment response, cost-effectiveness, response and remission rates, drop-out rates and adverse events. Ethics and dissemination This study has been approved by the Swedish Ethical Review Authority. Hypotheses were specified and analysis code published before data collection started. Results from all analyses will be reported in accordance with the Consolidated Standards of Reporting Trials statement for non-pharmacological trials and Consolidated Health Economic Evaluation Reporting Standards irrespective of outcome. Trial registration number NCT05608278.