Miracle-dz/UniFAR-FTUs huggingface dataset:
Restratification of the Upper Ocean after the Passage of a Tropical Cyclone: A Numerical Study

The role of baroclinic instability in the restratification of the upper ocean after the passage of a tropical cyclone (TC) is determined by means of numerical simulations. Using a regional ocean model, the Regional Ocean Modeling System (ROMS), a high-resolution three-dimensional simulation that includes the process of baroclinic instability and is initialized with moderate-amplitude eddy structures reproduces the satelliteobserved decay rate of the TC-induced sea surface temperature (SST) anomaly and is also in qualitative agreement with published observations after the passage of Hurricane Fabian in 2003 that showed decaying cold and warm anomalies located in the climatological mixed layer (CML) and upper thermocline, respectively. The model ocean is restratified after approximately one month with a net heat gain in the water column due to anomalous air–sea heat fluxes. The model shows, however, that vertical heat fluxes associated with baroclinic instability dominate over air–sea heat fluxes in restoring the CML heat content during the first month. A comparison with two-dimensional simulations that exclude baroclinic adjustment further highlights the importance of baroclinic instability: it can not only input a considerable amount of heat into the CML, but also establish strong stratification there, inhibiting the downward penetration of heat contributed by diabatic heating at the surface; both effects hasten the recovery of the SST. Additional experiments were performed to examine the sensitivity of the model results to changes in Newtonian cooling rate, changes in the magnitude of the eddy structures used to initialize the simulation, and changes in poststorm wind strength; the results indicate that, although some of them may have a significant effect on the recovery time of the SST, their influence on the contribution of baroclinic instability to the recovery of the CML heat content is modest. However, the contribution of baroclinic instability exhibits pronounced positive dependence on the depth of the mixing layer relative to the CML depth and the relative size of the area with unperturbed water. Its dependence on the shape of the spatial variation of the mixing depth is relatively weak but in a more complicated manner. These dependencies are consistent with those predicted by a simple front adjustment model, whereas the latter also suggest that the contribution of baroclinic instability is independent of the prestorm stratification below the CML. Overall, the idealized simulations in this study suggest that, for a typical situation in the real ocean, baroclinic instability can account for approximately 50% of the full recovery of the CML heat content, whereas under specific conditions the contribution can be significantly smaller. Those estimates provide a limit to the maximum net warming of the water column after the initial mixing event and thus have important implications regarding estimating the long-term effect of TCs on the upper-ocean heat budget.
Construction of Data Center Security System Based on Micro Isolation under Zero Trust Architecture

With the development of Internet technology, the rapid growth of data volume strongly promotes the construction of data centers, which also makes the security threats to data centers more and more serious. The architecture of the internal network of the data center has changed from the traditional IT architecture to virtualization, hybrid cloud and containerization, and the security isolation inside the data center has become more and more difficult. Aiming at the isolation of the internal network of the data center, the paper builds a more reliable system with the help of the zero-trust thought. On the basis of analyzing the key technologies of micro-isolation and constructing a micro-isolation system, we design a zero-trust security architecture based on micro-isolation propose a zero-trust security system for data center based on micro-isolation, and provides a set of security isolation scheme for the internal network of the data center.
Targeting Acute Myeloid Leukemia with Venetoclax; Biomarkers for Sensitivity and Rationale for Venetoclax-Based Combination Therapies

Simple Summary Venetoclax has proven to be a promising therapy for newly diagnosed, relapsed and refractory AML patients ineligible for induction chemotherapy. Current ongoing clinical trials are evaluating its effectivity as frontline therapy for all acute myeloid leukemia (AML) patients. However, response rates vary wildly, depending on patient characteristics and mutational profiles. This review elaborates on the efficacy and safety of venetoclax compared to conventional chemotherapy for treatment of AML patients, comparing the response rates, overall survival and adverse events. Moreover, it gives an overview of genetic and epigenetic AML cell characteristics that give enhanced or decreased response to venetoclax and offers insights into the pathogenesis of venetoclax sensitivity and resistance. Additionally, it suggests possible treatment combinations predicted to be successful based on identified mechanisms influencing venetoclax sensitivity of AML cells. Abstract Venetoclax is a BCL-2 inhibitor that effectively improves clinical outcomes in newly diagnosed, relapsed and refractory acute myeloid leukemia (AML) patients, with complete response rates (with and without complete blood count recovery) ranging between 34–90% and 21–33%, respectively. Here, we aim to give an overview of the efficacy of venetoclax-based therapy for AML patients, as compared to standard chemotherapy, and on factors and mechanisms involved in venetoclax sensitivity and resistance in AML (stem) cells, with the aim to obtain a perspective of response biomarkers and combination therapies that could enhance the sensitivity of AML cells to venetoclax. The presence of molecular aberrancies can predict responses to venetoclax, with a higher response in NPM1-, IDH1/2-, TET2- and relapsed or refractory RUNX1-mutated AML. Decreased sensitivity to venetoclax was observed in patients harboring FLT3-ITD, TP53, K/NRAS or PTPN11 mutations. Moreover, resistance to venetoclax was observed in AML with a monocytic phenotype and patients pre-treated with hypomethylating agents. Resistance to venetoclax can arise due to mutations in BCL-2 or pro-apoptotic proteins, an increased dependency on MCL-1, and usage of additional/alternative sources for energy metabolism, such as glycolysis and fatty acid metabolism. Clinical studies are testing combination therapies that may circumvent resistance, including venetoclax combined with FLT3- and MCL-1 inhibitors, to enhance venetoclax-induced cell death. Other treatments that can potentially synergize with venetoclax, including MEK1/2 and mitochondrial complex inhibitors, need to be evaluated in a clinical setting.
Store-and-Forward Images in Teledermatology: Narrative Literature Review

Background Store-and-forward (SAF) teledermatology uses electronically stored information, including patient photographs and demographic information, for clinical decision-making asynchronous to the patient encounter. The integration of SAF teledermatology into clinical practice has been increasing in recent years, especially during the COVID-19 pandemic. Despite this growth, data regarding the outcomes of SAF teledermatology are limited. A key distinction among current literature involves comparing the quality and utility of images obtained by patients and trained clinicians, as these metrics may vary by the clinical expertise of the photographer. Objective This narrative literature review aimed to characterize the outcomes of SAF teledermatology through the lens of patient- versus clinician-initiated photography and highlight important future directions for and challenges of the field. Methods A literature search of peer-reviewed research was performed between February and April 2021. Key search terms included patient-initiated, patient-submitted, clinician-initiated, clinician-submitted, store-and-forward, asynchronous, remote, image, photograph, and teledermatology. Only studies published after 2001 in English were included. In total, 47 studies were identified from the PubMed electronic database and Google Scholar after omitting duplicate articles. Results Image quality and diagnostic concordance are generally lower and more variable with patient-submitted images, which may impact their decision-making utility. SAF teledermatology can improve the efficiency of and access to care when photographs are taken by either clinicians or patients. The clinical outcomes of clinician-submitted images are comparable to those of in-person visits in the few studies that have investigated these outcomes. Coinciding with the onset of the COVID-19 pandemic, asynchronous teledermatology helped minimize unnecessary in-person visits in the outpatient setting, as many uncomplicated conditions could be adequately managed remotely via images captured by patients and referring clinicians. For the inpatient setting, SAF teledermatology minimized unnecessary contact during dermatology consultations, although current studies are limited by the heterogeneity of their outcomes. Conclusions In general, photographs taken by trained clinicians are higher quality and have better and more relevant diagnostic and clinical outcomes. SAF teledermatology helped clinicians avoid unnecessary physical contact with patients in the outpatient and inpatient settings during the COVID-19 pandemic. Asynchronous teledermatology will likely play a greater role in the future as SAF images become integrated into synchronous teledermatology workflows. However, the obstacles summarized in this review should be addressed before its widespread implementation into clinical practice.
DepressNet: A Multimodal Hierarchical Attention Mechanism approach for
Depression Detection

Depression has been the prime cause of mental-health illness globally. A major depressive disorder is a common mental health disorder that affects both psychologically and physically, which could lead to the loss of life in extreme cases. Detection of depression from the recording of an interview could help with early diagnosis. This paper proposes a three-stage framework multimodal machine learning approach called DepressNet for depression detection using the PHQ-8 Questionnaire score. Bidirectional Long Short-Term Memory (BLSTM) layer network has been proposed, and Extended Distress Analysis Interview Corpus (E-DAIC) dataset was used for the training and validation of the proposed method with the uses multiscale temporal features from audio, video, and text modality and attention mechanisms for fusion. The method achieved the RMSE of 4.32 and CCC of 0.662 on the development set, and on the test set, we got RMSE of 5.36 and CCC of 0.457, outperforming the other methods.
Design of Dual-Electrical-Port DC-Coil-Free Hybrid-Excited Machines

This paper incorporates the idea of integrated field and armature windings into the design of novel hybrid excited machines with bi-directional flux modulating effect, which results in a new hybrid-excited machine concept that is referred as dual-electrical-port dc-coil-free hybrid-excited machine (DEP-DCF-HEM). In the proposed design, dc field windings are eliminated and dc bias currents are injected into the windings to generate dc excitation field. In addition, the armature windings are divided into dual electrical ports, and zero-sequence current flows between these two ports can adjust the air-gap field effectively. Compared with existing HEMs with additional dc coils, the proposed machines can achieve both higher torque density and wider flux weakening range. The presented design principle can be utilized in a variety of configurations of DEP-DCF-HEMs. Topologies with stator permanent magnet (PM), rotor PM, and dual PM are possible designs, which are all investigated in this paper. A dual PM DEP-DCF-HEM prototype is manufactured, and experimental measurements are conducted to verify its performances.
The Effect of GPX2 on the Prognosis of Lung Adenocarcinoma Diagnosis and Proliferation, Migration, and Epithelial Mesenchymal Transition

Objective To investigate the expression of glutathione peroxidase 2 (GPX2) in human lung adenocarcinoma tissues and its effect on the biological function of lung adenocarcinoma A549 cells. Methods The expression of GPX2 in lung adenocarcinoma and its effect on survival were analyzed by the TCGA database and the GEPIA 2 database. A total of 45 cases of primary lung adenocarcinoma tissue specimens and 45 cases of their paracancerous tissue specimens were collected, and the expression of GPX2 in the two types of tissues was detected by immunohistochemistry. Lung adenocarcinoma A549 cells were divided into the GPX2 overexpression group (GPX2), the GPX2 knockdown group (si-GPX2), the empty vector group (Vector), the siRNA negative control group (si-NC), and the WT group; the mRNA level and protein expression of GPX2 in each group of A549 cells were detected by real-time fluorescence quantitative PCR and Western blotting; the proliferation activity of each group of cells was detected by the CCK-8 assay; the effect of GPX2 on cell migration and invasion ability was detected by the scratch assay and the Transwell invasion assay; the apoptosis of each group of cells was detected by flow cytometry; Western blotting was performed to detect the expression levels of Bax, Bcl-2, E-cadherin, vimentin, and MMP2 and MMP9 proteins in each group of cells. Results Bioinformatics analysis showed that the expression of GPX2 was strongly correlated with the prognosis of lung adenocarcinoma patients (P < 0.01). The positive expression rates of GPX2 in lung adenocarcinoma and its paracancerous tissues were 66.0% and 15.7%, respectively (P < 0.05). The results of RT-qPCR and Western blotting showed that the expression level of GPX2 mRNA and protein in A549 cells in the GPX2 group increased, which was significantly higher than that in the WT group (P < 0.05); the expression levels of GPX2 mRNA and protein in A549 cells in the si-GPX2 group were the same, that is, significantly lower than the WT group (P < 0.05). GPX2 overexpression promoted the proliferation, migration, and invasion of A549 cells and inhibited their apoptosis; the results in the si-GPX2 group were opposite to those in the GPX2 group. Compared with the WT group, the expression of Bcl-2, vimentin, and MMP2 and MMP9 protein in the GPX2 group increased (P < 0.05), while the expression of Bax and E-cadherin protein decreased in the GPX2 group (P < 0.05); the results in the si-GPX2 group were opposite to those in the GPX2 group. Conclusion The expression of GPX2 in lung adenocarcinoma is related to the prognosis of patients. It is proved that GPX2 can promote the migration and invasion of lung adenocarcinoma cells and is related to the EMT/β-catenin pathway. Thus, GPX2 is expected to be an important target for the diagnosis and treatment of lung adenocarcinoma.
Effect of Petal Color, Water Status, and Extraction Method on Qualitative Characteristics of Rosa rugosa Liqueur

Flowers of Rosa rugosa Thunb. are a rich source of bioactive compounds with high antioxidant properties and are used for the production of jams, teas, juices, and wines. In the present paper, the petals of R. rugosa cv. Alba (white flowers) and Rubra (purple flowers) were evaluated for their morphological and phytochemical characteristics, and for the preparation of an alcoholic liqueur. In particular, the effect of two extraction procedures (conventional and maceration) of fresh and dry petals on the quality of a rose liqueur was determined. As expected, the concentration of the flower’s bioactive compounds was affected by petal water content and by tested cultivars: dry petals showed higher total carotenoids and anthocyanins contents with respect to the fresh ones; cv. Rubra evidenced higher values compared to cv. Alba. As regards the quality of rose liqueur, the two petal extraction procedures did not affect the polyphenol content and higher values were recorded only on dry petals with respect to the fresh ones and, in particular, on those from cv. Rubra. The liqueur’s flavonoid content was influenced by the petal extraction method, water content, and color as higher values were recorded on rose liqueur prepared after the maceration of cv. Rubra dry petals whereas lower values were observed on alcoholic drinks prepared after the conventional extraction of cv. Alba fresh petals. Our study shows that R. rugosa petals have a fair amount of secondary metabolites with antioxidant activity, making them suitable for use in the beverage industry.
Cloud-Based Underactuated Resilient Control for Cyber-Physical Systems Under Actuator Attacks

Cyber attacks threaten the security of cyber-physical systems (CPSs) seriously. Resilient control has been studied to defend cyber attacks. However, existing resilient control schemes have not considered system structure changes caused by actuator attacks. Such structure changes are more destructive and harmful than the actuator attack scenarios investigated in the literature, demanding new resilient control strategies. They will be addressed in this article in cloud computing environments, which are increasingly deployed in large-scale CPSs. More specifically, a resilient control scheme is designed which consists of two controllers: a local resilient controller and cloud-based resilient controller. The local resilient controller withstands actuator attacks that simply tampers the actuator output to a large extent. The cloud-based resilient controller aims to resist the actuator attacks that destroy the system structure. Simulations are conducted on a permanent synchronous motor control system to demonstrate the proposed resilient control scheme.
Prediction of Depression, Anxiety and Stress Levels Using Dass-42

Over the past few decades, many people are suffering from psychological health issues such as anxiety, depression, and stress. It is crucial to detect mental health condition on a timely basis and cure before it turns into a severe problem. In this paper, we analyze the performance of Machine learning (ML) algorithms to predict severity levels of depression, anxiety, and stress (DAS). Severity levels can be measured by the Depression, Anxiety, and Stress Scale (DASS) which consists of a set of questionnaires (DASS42). The intention of this research is to enhance and compare the performance of two different ML algorithms namely Support Vector Machine (SVM) and Logistic Regression (LR) based on classification accuracy with other algorithms. After parameter tuning SVM attains a classification accuracy of 97.35%, 97.49%, and 97.20% for Depression, Anxiety, and Stress. LR attains a classification accuracy of 98.15%, 98.05%, and 98.45% for Depression, Anxiety, and Stress dataset respectively. Parameter tuning is done for SVM and LR to obtain better accuracy with the best suitable parameters, and the results revealed that LR achieved better performance in terms of accuracy compared to SVM.
Editorial: Eating disorders and emotion regulation, looking at the spectrum from overcontrolling to dysregulation

COPYRIGHT © 2022 Meneguzzo, Oldershaw, Monaco and Giel. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Editorial: Eating disorders and emotion regulation, looking at the spectrum from overcontrolling to dysregulation
Cyberbullying Among Teenagers in China: From the Perspective of Major Factors and Coping Strategies

“Cyberbullying” as well as “online harassment” and “electronic violence”, has become a serious public health concern in recent decades, particularly among Chinese youth. Cyberbullying among teenagers has many kinds of characteristics, such as strong concealment and great harm, which could not only be considered as an extension of school bullying. The 46th China Statistical Report on the Development of the Internet indicates that China's internet penetration rate was 67% as of June 2020, with 940 million internet users. Nonetheless, because of its unique and widespread nature, cyberbullying can further harm a victim's mental and behavioral well-being and well-being. In the current social context, it is critical to strengthen the research and practice of cyberbullying education to prevent and reduce the occurrence of cyberbullying among young people, safeguard their healthy development, and safeguard national security. To lessen the prevalence of cyberbullying and the harm it does to young people, it is necessary to first understand how cyberbullying occurs to identify effective remedies to the core causes. This study looks at the fundamental causes of cyberbullying, concentrating on the actual circumstances of young people and what motivates them to commit cyberbullying and victimize young people. Furthermore, coping strategies for reducing the prevalence of cyberbullying and psychological protection for teenagers are presented.
Cycle-Spinning Convolution for Object Detection

Deep convolutional networks are prominently used in object detection tasks due to their notable performances. These networks typically have pooling layers following the convolution, which effectively subsamples the convolution output, potentially introducing aliasing. An aliased signal emerging in the earlier layers inevitably propagates throughout the network and such distortion potentially prevents getting the best performance out of a network. In this study, we propose integrating the cycle-spinning (CS) into the convolutional layer to have a more robust object detection pipeline. CS makes use of the shift-variant characteristics of pooling, where each shifted version of the image results in a different output. The CS combines these outputs after unshifting them to remove artifacts and alleviate distortion. The proposed method does not introduce any additional trainable parameters and can be straightforwardly integrated into convolution layers. The experimental results show that integrating CS into object detection algorithms in the DOTA dataset results in an up to 5.5% increase in the mAP values.
Interaction of the sea breeze with urban heat islands of different sizes and locations

The interactions of the sea breeze with urban heat islands (UHI) are examined with use of a two-dimensional numerical model. The strength of the interaction depends on the intensity of the sea breeze, the intensity of the heat island circulation that develops over the inland side of the urban area, and the penetrating speed of the sea breeze. These factors are basically controlled by three characteristics of the urban area-the size or width, the distance from the sea, and the intensity of the UHI.