Miracle-dz/UniFAR-FTUs huggingface dataset:
Recognition Of Learners’ Personality Traits For Software Engineering Education

It is vital for educators to teach learners in accordance with their aptitude, which can be useful to help learners reach their full potential. Educators have been taking the Myers-Briggs Type Indicator (MBTI) as a powerful tool to understand the differences in students’ learning styles, adopting appropriate teaching strategies to accommodate the learning styles of different types of students can effectively prevent students from being tired of studying. It is a problem worthy of research to recognize the students’ personality traits with technological means. Therefore, we propose a method to recognize learners’ MBTI from videos, which can be applied in the course learning and practice stages of software engineering education. We propose a novel approach to recognize the MBTI personality traits of learners from videos. Personality and emotion unconsciously affect facial expression, the speaking style in social contexts. However, in the current literature, there is no publicly available source of images dataset labeled with the MBTI personality scale; nearly all the available data are text. In this paper, we use two datasets: images extracted from ChaLearn First Impressions dataset and the Myer-Briggs Personality Type Dataset from Kaggle for our training tasks. Furthermore, we take plentiful text data labeled with the MBTI personality scale as the source domain and image data as the target domain for borrowing knowledge from the source domain to facilitate the learning task in a target domain. By adopting feature transfer, a bridge is built between the source domain and the target domain. We perform experiments on the transfer task and evaluate the effectiveness of this approach, the results of this study can assist educators in regards to the identification of learners’ MBTI personality types in a new way.
Intelligent BERT-BiLSTM-CRF Based Legal Case Entity Recognition Method

In the past decade, the main natural language processing technologies in the field of artificial intelligence are Word2Vec and ELMO traditional models in the application of intelligent legal systems. For the reason that they are basically one-way training algorithms from left to right and only one-way information is learned, so these traditional models have some disadvantages such as low efficiency and accuracy. In order to identify specific elements in the legal case intelligently, such as time, location, perpetrator, and recipient, and improve the efficiency of case processing, a new entity recognition method using the BERT (Bidirectional Encoder Representations from Transformers) model as the input layer is proposed. The BERT model is a new type of word vector model that relies on context by joint adjusting the bidirectional Transformer in all layers. Basing on BERT model, we proposed a new method comprise BERT, BiLSTM and CRF (Conditional Random Fields) to carry on the intelligent identification of legal case entities. And with abundant experiment result, the better accuracy and efficiency of our method has been proved comparing to traditional models such as Word2Vec.
Study On Long Term Sea Surface Temperature (SST) Prediction Based On Temporal Convolutional Network (TCN) Method

The short term and small-scale sea surface temperature prediction using deep learning has achieved good results. It is still an important challenge to obtain accurate large-scale and long-term SST predictions. In this study, we used a temporal convolutional network (TCN) to predict the SSTs of the Indian Ocean in the sea area of 40°E -110°E and 25°N to -25°S from 2014 to 2018 at a spatial resolution of 1°×1°. By using the observation data of the previous 10 years to forecast the monthly SSTs of the next 5 years, this study accomplished a 5-year forecast with one model, which had a monthly mean of the root mean square error (RMSE) of 0.506°C. In contrast, the National Oceanic and Atmospheric Administration needs to constantly collect observation data and use seven models to make 5-year forecasts. The results showed that the predicted SST through the proposed TCN can better fit the long-term SST variation curve.
Emotion

and discuss three different psychological perspectives toward studying emotion that have strongly influenced emotion modeling in SIAs. I will motivate why SIAs can make constructive use of emotions. In Section 10.2, I cover computational representation of affective concepts and four approaches toward computational modeling of appraisal. I also give four working examples. In Sections 10.3 to 10.5, I cover the history, state of the art, and outlook of emotion modeling in SIAs. Emotion
Intragenic proviral elements support transcription of defective HIV-1 proviruses

HIV-establishes a persistent proviral reservoir by integrating into the genome of infected host cells. Current antiretroviral treatments do not target this persistent population of proviruses which include latently infected cells that upon treatment interruption can be reactivated to contribute to HIV-1 rebound. Deep sequencing of persistent HIV proviruses has revealed that greater than 90% of integrated HIV genomes are defective and unable to produce infectious virions. We hypothesized that intragenic elements in the HIV genome support transcription of aberrant HIV-1 RNAs from defective proviruses that lack long terminal repeats (LTRs). Using an intact provirus detection assay, we observed that resting CD4+ T cells and monocyte-derived macrophages (MDMs) are biased towards generating defective HIV-1 proviruses. Multiplex reverse transcription digital drop PCR identified Env and Nef transcripts which lacked 5’ untranslated regions (UTR) in acutely infected CD4+ T cells and MDMs indicating transcripts are generated that do not utilize the promoter within the LTR. 5’UTR-deficient Env transcripts were also identified in a cohort of people living with HIV (PLWH) on ART, suggesting that these aberrant RNAs are produced in vivo. Using 5’ rapid amplification of cDNA ends (RACE), we mapped the start site of these transcripts within the Env gene. This region bound several cellular transcription factors and functioned as a transcriptional regulatory element that could support transcription and translation of downstream HIV-1 RNAs. These studies provide mechanistic insights into how defective HIV-1 proviruses are persistently expressed to potentially drive inflammation in PLWH. Author Summary People living with HIV establish a persistent reservoir which includes latently infected cells that fuel viral rebound upon treatment interruption. However, the majority of HIV-1 genomes in these persistently infected cells are defective. Whether these defective HIV genomes are expressed and whether they contribute to HIV associated diseases including accelerated aging, neurodegenerative symptoms, and cardiovascular diseases are still outstanding questions. In this paper, we demonstrate that acute infection of macrophages and resting T cells is biased towards generating defective viruses which are expressed by DNA regulatory elements in the HIV genome. These studies describe an alternative mechanism for chronic expression of HIV genomes.
Immune function of the serosa in hemimetabolous insect eggs

Insects comprise more than a million species and many authors have attempted to explain this success by evolutionary innovations. A much overlooked evolutionary novelty of insects is the serosa, an extraembryonic epithelium around the yolk and embryo. We have shown previously that this epithelium provides innate immune protection to eggs of the beetle Tribolium castaneum. It remained elusive, however, whether this immune competence evolved in the Tribolium lineage or is ancestral to all insects. Here, we expand our studies to two hemimetabolous insects, the bug Oncopeltus fasciatus and the swarming grasshopper Locusta migratoria. For Oncopeltus, RNA sequencing reveals an extensive response upon infection, including the massive upregulation of antimicrobial peptides (AMPs). We demonstrate antimicrobial activity of these peptides using in vitro bacterial growth assays, and describe two novel AMP families called Serosins and Ovicins. For both insects, qPCRs show immune competence of the eggs when the serosa is present, and in situ hybridizations demonstrate that immune gene expression is localized in the serosa. This first evidence from hemimetabolous insect eggs suggests that immune competence is an ancestral property of the serosa. The evolutionary origin of the serosa with its immune function might have facilitated the spectacular radiation of the insects.
Long-read sequencing reveals atypical mitochondrial genome structure in a New Zealand marine isopod

Most animal mitochondrial genomes are small, circular, and structurally conserved. However, recent work indicates that diverse taxa possess unusual mitochondrial genomes. In Isopoda, species in multiple lineages have atypical and rearranged mitochondrial genomes. However, more species of this speciose taxon need to be evaluated to understand the evolutionary origins of atypical mitochondrial genomes in this group. In this study, we report the presence of an atypical mitochondrial structure in the New Zealand endemic marine isopod, Isocladus armatus. Data from long and short read DNA sequencing, suggests that I. armatus has two mitochondrial chromosomes. The first chromosome consists of two mitochondrial genomes that have been inverted and fused together in a circular form, and the second chromosome consists of a single mitochondrial genome in a linearized form. This atypical mitochondrial structure has been detected in other isopod lineages, and our data from an additional divergent isopod lineage (Sphaeromatidae) lends support to the hypothesis that atypical structure evolved early in the evolution of Isopoda. Additionally, we find that a heteroplasmic site previously observed across many species within Isopoda is absent in I. armatus, but confirm the presence of two heteroplasmic sites recently reported in two other isopod species.
Tuning Epithelial Cell–Cell Adhesion and Collective Dynamics with Functional DNA-E-Cadherin Hybrid Linkers

The binding strength between epithelial cells is crucial for tissue integrity, signal transduction and collective cell dynamics. However, there is no experimental approach to precisely modulate cell-cell adhesion strength at the cellular and molecular level. Here, we establish DNA nanotechnology as tool to control cell-cell adhesion of epithelial cells. We designed a DNA-E-cadherin hybrid system consisting of complementary DNA strands covalently bound to a truncated E-cadherin with a modified extracellular domain. DNA sequence design allows to tune the DNA-E-cadherin hybrid molecular binding strength, while retaining its cytosolic interactions and downstream signaling capabilities. The DNA-E-cadherin hybrid facilitates strong and reversible cell-cell adhesion in E-cadherin deficient cells by forming mechanotransducive adherens junctions. We assess the direct influence of cell-cell adhesion strength on intracellular signaling and collective cell dynamics. This highlights the scope of DNA nanotechnology as a precision technology to study and engineer cell collectives.
DenVar: density-based variation analysis of multiplex imaging data

Multiplex immunohistochemistry (mIHC) and multiplexed ion beam imaging (MIBI) platforms have become increasingly popular for studying complex single-cell biology in cancer patients. In such studies, researchers test for association between functional markers and survival in a two-step process. First, they count the number of positive cells, defined as the number of cells where a functional marker is significantly expressed. Then, they partition the patients into two groups and test for association between the group label with survival. Consequently, the approach suffers from subjectivity and lack of robustness. In this paper, we propose a threshold-free distance metric between patients solely based on their marker probability densities. Using the proposed distance, we have developed two association tests, one based on hierarchical clustering and the other based on linear mixed model. Our method obviates the need for the arduous step of threshold selection, getting rid of the subjectivity bias. The method also intuitively generalizes to joint analysis of multiple markers. We assessed the performance of our method through extensive simulation studies and also used it to analyze two multiplex imaging datasets.
Versatile and Robust Method for Antibody Conjugation to Nanoparticles with High Targeting Efficiency

The application of antibodies in nanomedicine is now standard practice in research since it represents an innovative approach to deliver chemotherapy agents selectively to tumours. The variety of targets or markers that are overexpressed in different types of cancers results in a high demand for antibody conjugated nanoparticles which are versatile and easily customizable. Considering upscaling, the synthesis of antibody conjugated nanoparticles should be simple and highly reproducible. Here, we developed a facile coating strategy to produce antibody conjugated nanoparticles using ‘click chemistry’ and further evaluated their selectivity towards cancer cells expressing different markers. Our approach was consistently repeated for the conjugation of antibodies against CD44 and EGFR, which are prominent cancer cell markers. The functionalized particles presented excellent cell specificity towards CD44 and EGFR overexpressing cells, respectively. Our results indicated that the developed coating method is reproducible, versatile, non-toxic, and can be used for particle functionalization with different antibodies. This grafting strategy can be applied to a wide range of nanoparticles and will contribute to the development of future targeted drug delivery systems.
De novo biosynthesis of para-nitro-L-phenylalanine in Escherichia coli

Nitroaromatic functional groups can impart valuable properties to chemicals and to biological macromolecules including polypeptides. Para-nitro-L-phenylalanine (pN-Phe) is a nitroaromatic amino acid with uses including immune stimulation and fluorescence quenching. As the chemical synthesis of pN-Phe does not follow green chemistry principles and impedes provision of pN-Phe to engineered bacterial cells in some contexts, we sought to design a de novo biosynthetic pathway for pN-Phe in Escherichia coli. To generate the nitro chemical functional group, we identified natural diiron monooxygenases with measurable in vitro and in vivo activity on envisioned amine-containing precursors of para-amino-L-phenylalanine (pA-Phe) and para-aminophenylpyruvate. By expressing one of these N-oxygenase genes together with previously characterized genes for the biosynthesis of pA-Phe, we achieved the synthesis of pN-Phe from glucose. Through further optimization of the chassis, plasmid constructs, and media conditions, we were able to improve the selectivity of pN-Phe biosynthesis, resulting in a maximum titer of 819 µM in rich defined media under shake-flask conditions. These results provide a foundation for the biosynthesis of related nitroaromatic chemicals and for downstream biological applications that could utilize pN-Phe as a building block. Highlights Para-nitro-L-phenylalanine (pN-Phe) is a valuable small molecule for its applications in genetic code expansion. We establish de novo biosynthesis of pN-Phe from glucose in E. coli, which is also the first example of a de novo pathway design for an unnatural but commonly used non-standard amino acid. We show the first use of an N-oxygenase enzyme in the de novo synthesis of a nitroaromatic product. Screening of natural N-oxygenases and strain engineering resulted in final pN-Phe titers of 820 ± 130 µM in shake flask experiments with rich defined media.
Recent Advances in Effective Reduction of Graphene Oxide for Highly Improved Performance Toward Electrochemical Energy Storage

The demand for high‐quality graphene from various applications promotes the exploration of various synthesis methods such as chemical vapor deposition, chemical reduction of graphite oxide, liquid‐phase exfoliation, and electrochemical exfoliation. Among those, chemical treatments for the production of reduced graphene oxide (RGO) dictate the current technologies for mass production of graphene powder. However, such conventional chemical reduction methods are rather ineffective in removing oxygen‐containing functional groups from graphene oxide (GO), with resultant RGO products containing high level of structural defects. This leads to significantly damaged crystallinity and drastically lowered electric and thermal conductivity, which is probably the main bottleneck to limit the performance of RGO‐based materials. Great efforts such as thermal reduction, microwave‐irradiation reduction, or other novel reduction methods (e.g., photoreduction) have been developed to repair defects in RGO materials. This perspective review is to outline the latest advances toward effective reduction of GO for significantly enhanced properties. We demonstrate that effectively repaired RGO with large specific surface area and highly improved crystallinity is key to highly improved electric and thermal conductivity, thus leading to significantly enhanced properties essential for chemical energy storage devices.
Determination of Fluoroquinolones in Animal Feed by Ion Pair High-performance Liquid Chromatography with Fluorescence Detection

ABSTRACT A sensitive and simple method is described for the determination of fluoroquinolones by high-performance liquid chromatography (HPLC) using a C18 column and fluorescence detection. The mobile phase was acetonitrile and 0.025M phosphate acid with 0.0025M sodium 1-heptanesulfonate monohydrate in water with a gradient program. The chromatographic conditions were optimized for the determination of ciprofloxacin, enrofloxacin, sarafloxacin, and flumequine in animal feed. The samples were extracted by a hydrochloric acid and acetonitrile followed by dilution in 0.01M oxalic acid at pH 4.0 and purified by solid-phase extraction. The procedure was validated by fortifying feed at 200, 1000, and 2000 µg/kg. The limits of detection and quantification were from 28.5 to 74.7 and 31.7 to 94.6 µg/kg, respectively. The average recoveries for fluoroquinolones were from 89.7 to 100.3%. The method was validated and shown to be efficient and precise for quantification of fluoroquinolones in animal feed. The results demonstrate the feasibility of the method for routine use to monitor these substances in feed.
Experience Paper: sgx-dl: dynamic loading and hot-patching for secure applications

Trusted execution as offered by Intel's Software Guard Extensions (SGX) is considered as an enabler to protect the integrity and confidentiality of stateful workloads such as key-value stores and databases in untrusted environments. These systems are typically long running and require extension mechanisms built on top of dynamic loading as well as hot-patching to avoid downtimes and apply security updates faster. However, such essential mechanisms are currently neglected or even missing in combination with trusted execution. We present sgx-dl, a lean framework that enables dynamic loading of enclave code at the function level and hot-patching of dynamically loaded code. Additionally, sgx-dl is the first framework to utilize the new SGX version 2 features and also provides a versioning mechanism for dynamically loaded code. Our evaluation shows that sgx-dl introduces a performance overhead of less than 5% and shrinks application downtime by an order of magnitude in the case of a database system.
Frailty and rate of fractures in patients initiating antihypertensive medications: a cohort study in primary care

Background Treatment for hypertension improves cardiovascular outcomes. Frailty may be present in older people treated for hypertension, but associates with adverse drug effects, potentially including falls resulting in fractures. We aimed to determine the association between baseline frailty and fractures in patients initiated on antihypertensive treatment. Methods We conducted a retrospective cohort study using United Kingdom primary care data, including new users of first-line antihypertensives aged 65 years or over. We reported degree of frailty (fit, mild, moderate, severe) at antihypertensive initiation using the Electronic Frailty Index. We examined the association of frailty with fractures using multivariable Poisson regression, and assessed for interaction between antihypertensive class and frailty. Results Of 113,779 patients aged 65 years or over who initiated on first-line antihypertensives, 49,634 patients (44%) were mildly or more frail. Over 4.1 years mean follow-up, 6567 (5.8%) experienced a fracture, with 3832 (58%) of these fractures occurring in frail people. Among those with severe frailty, doubling of fracture risk was observed after antihypertensive initiation, compared with fit people [adjusted rate ratio 2.26, 95% confidence interval (CI) 1.93–2.65]. Secondary analyses indicate this pattern was replicated for hip and arm fractures, and strongest for spine fractures, and the association between different types of antihypertensives and fractures varied by frailty ( p = 0.004), being lower in moderately frail users of renin-angiotensin blockers compared with calcium channel blockers [rate ratio 0.81, 95% CI 0.71–0.94]. Conclusions Frailty is common among older patients initiating first-line antihypertensive treatment, and was associated with an increased fracture rate. Awareness of this is important to encourage clinicians to consider risk of falls and fractures when treating hypertension.
Recombinant adjuvanted zoster vaccine and reduced risk of COVID-19 diagnosis and hospitalization in older adults

Background: Vaccines may elicit long-term boosting of innate immune responses that can help protect against COVID-19. We evaluated the association between recombinant adjuvanted zoster vaccine (RZV) and COVID-19 outcomes at Kaiser Permanente Southern California. Methods: In a cohort design, adults aged [≥]50 years who received [≥]1 RZV dose prior to 3/1/2020 were matched 1:2 to unvaccinated individuals and followed until 12/31/2020. Adjusted hazard ratios (aHR) and 95% confidence intervals (CIs) for COVID-19 outcomes were estimated using Cox proportional hazards regression. In a test-negative design, cases had a positive SARS-CoV-2 test and controls had only negative tests, from 3/1/2020-12/31/2020. Adjusted odds ratios (aOR) and 95% CIs for prior receipt of RZV were estimated using logistic regression. Results: In the cohort design, 149,244 RZV recipients were matched to 298,488 unvaccinated individuals. The aHRs (95% CI) for COVID-19 diagnosis and hospitalization were 0.84 (0.81-0.87) and 0.68 (0.64-0.74), respectively. In the test-negative design, 8.4% of 75,726 test-positive cases and 13.1% of 340,898 test-negative controls had received [≥]1 RZV dose. The aOR (95% CI) was 0.84 (0.81-0.86). Conclusion: RZV vaccination was associated with a 16% lower risk of COVID-19 diagnosis and 32% lower risk of hospitalization, suggesting RZV elicits heterologous protection, possibly through trained immunity.