bluuebunny/crossref_metadata_2025 huggingface dataset:
Online-Semisupervised Neural Anomaly Detector to Identify MQTT-Based Attacks in Real Time
Authors: Gao Zhenyu , Cao Jian , Wang Wei , Zhang Huayun , Xu Zengrong
Published: September 2021

Industry 4.0 focuses on continuous interconnection services, allowing for the continuous and uninterrupted exchange of signals or information between related parties. The application of messaging protocols for transferring data to remote locations must meet specific specifications such as asynchronous communication, compact messaging, operating in conditions of unstable connection of the transmission line of data, limited network bandwidth operation, support multilevel Quality of Service (QoS), and easy integration of new devices. The Message Queue Telemetry Transport (MQTT) protocol is used in software applications that require asynchronous communication. It is a light and simplified protocol based on publish-subscribe messaging and is placed functionally over the TCP/IP protocol. It is designed to minimize the required communication bandwidth and system requirements increasing reliability and probability of successful message transmission, making it ideal for use in Machine-to-Machine (M2M) communication or networks where bandwidth is limited, delays are long, coverage is not reliable, and energy consumption should be as low as possible. Despite the fact that the advantage that MQTT offers its way of operating does not provide a serious level of security in how to achieve its interconnection, as it does not require protocol dependence on one intermediate third entity, the interface is dependent on each application. This paper presents an innovative real-time anomaly detection system to detect MQTT-based attacks in cyber-physical systems. This is an online-semisupervised learning neural system based on a small number of sampled patterns that identify crowd anomalies in the MQTT protocol related to specialized attacks to undermine cyber-physical systems.
The Role of Technology in COVID‐19 Pandemic Management and Its Financial Impact
Authors: Zhao Jin , Ahmad Zubair , Khosa Saima K. , Yusuf M. , Alamri Osama Abdulaziz , Mohamed Mohamed S.
Published: September 2021

A pandemic caused by the novel coronavirus (COVID‐19) is causing an unprecedented situation for the world’s health services. Health, local communities, and government are adversely affected by the COVID‐19 pandemic. Moreover, on January 21, 2020, the WHO Emergency Committee declared a global health emergency because of increasing numbers of COVID‐19 case notifications from countries overseas. While the pandemic caused grave damage to socioeconomic phenomena and multiple global phenomena such as commodity prices, remittances, trade, tourism, significant job loss, and drastically lower wages, the pandemic has also negatively affected multiple global phenomena. The advent of technology has spurred significant changes in many aspects of our lives and improved the exchange of information, the presentation of data, and the management of medical resources through telemedicine. In this article, we present a mathematical data visualization approach for analyzing pandemic data behaviors, such as exponential growth and deviations using the data related to COVID‐19 events. Furthermore, this article will include studies on the implications of the COVID‐19 pandemic on finance sector.
Experimental Microemulsion Flooding Study to Increase Low Viscosity Oil Recovery Using Glass Micromodel
Authors: Hematpur Hamed , Abdollahi Reza , Safari-Beidokhti Mohsen , Esfandyari Hamid
Published: September 2021

The growing demand for clean energy can be met by improving the recovery of current resources. One of the effective methods in recovering the unswept reserves is chemical flooding. Microemulsion flooding is an alternative for surfactant flooding in a chemical-enhanced oil recovery method and can entirely sweep the remaining oil in porous media. The efficiency of microemulsion flooding is guaranteed through phase behavior analysis and customization regarding the actual field conditions. Reviewing the literature, there is a lack of experience that compared the macroscopic and microscopic efficiency of microemulsion flooding, especially in low viscous oil reservoirs. In the current study, one-quarter five-spot glass micromodel was implemented for investigating the effect of different parameters on microemulsion efficiency, including surfactant types, injection rate, and micromodel pattern. Image analysis techniques were applied to represent the phase saturations throughout the microemulsion flooding tests. The results confirm the appropriate efficiency of microemulsion flooding in improving the ultimate recovery. LABS microemulsion has the highest efficiency, and the increment of the injection rate has an adverse effect on oil recovery. According to the pore structure’s tests, it seems that permeability has little impact on recovery. The results of this study can be used in enhanced oil recovery designs in low-viscosity oil fields. It shows the impact of crucial parameters in microemulsion flooding.
Research on Influencing Factors of Adoption Behavior of Mobile Readers Based on Meta-Analysis
Authors: Zhou Haihua , Liu Jing , Cui Xiaodong
Published: September 2021

Many scholars have conducted extensive research on the adoption behavior of mobile readers, and there are obvious differences in the degree and direction of conclusions drawn from different individual studies. In this study, a meta-analysis method was used to comprehensively analyze a total of 74,964 independent samples of 31 relevant empirical research documents at home and abroad. The results show that the main influencing factors of mobile reading are perceived usefulness, perceived ease of use, perceived mobility, perceived entertainment, social influence, cognitive adjustment, perceived value, usage attitude, interface design, etc. Cognitive adjustment and usage attitude have the greatest impact on intention to use, followed by perceived usefulness, perceived mobility, subjective norms, perceived ease of use; perceived ease of use has a significant positive impact on perceived usefulness; interface design has a significant positive effect on perceived ease of use; behavioral intention has a significant positive effect on actual behavior; and perceived usefulness and perceived ease of use have a significant positive effect on usage attitude.
Generalized Thermal Flux Flow for Jeffrey Fluid with Fourier Law over an Infinite Plate
Authors: Asjad Muhammad Imran , Basit Abdul , Akgül Ali , Muhammad Taseer
Published: September 2021

The unsteady flow of Jeffrey fluid along with a vertical plate is studied in this paper. The equations of momentum, energy, and generalized Fourier’s law of thermal flux are transformed to non-dimensional form for the proper dimensionless parameters. The Prabhakar fractional operator is applied to acquire the fractional model using the constitutive equations. To obtain the generalized results for velocity and temperature distribution, Laplace transform is performed. The influences of fractional parameters

α
,
β
,
γ

, thermal Grashof number

Gr

, and non-dimensional Prandtl number

Pr

upon velocity and temperature distribution are presented graphically. The results are improved in the form of decay of energy and momentum equations, respectively. The new fractional parameter contains the Mittag-Leffler kernel with three fractional parameters which are responsible for better memory of the fluid properties rather than the exponential kernel appearing in the Caputo–Fabrizio fractional operator. The Prabhakar fractional operator has advantage over Caputo–Fabrizio in the real data fitting where needed.
Automatic Detection of Fractures Based on Optimal Path Search in Well Logging Images
Authors: Zhang Wei , Wu Tong , Li Zhipeng , Li Yanjun , Qiu Ao , Shi Yibing
Published: September 2021

Reservoir fractures are essential locations to gather oil and gas. Recently, imaging logging technology has become a mainstream method for obtaining stratigraphic information. This paper proposed a combined optimal path search strategy to effectively identify and extract the fracture information in well logging images. Specifically, the threshold segmentation of logging images is used to obtain the binary image. In addition, the identification of connected fractures in the logging image is transformed into the optimal path search, and the identification and extraction of reservoir fractures are realized by constructing the optimal path between the two ends of fractures. Finally, an improved ant colony algorithm is applied to filter irrelevant information and extract fractures automatically by recording all the ants’ exploration trajectories in the ant colony. Compared with previous approaches, the proposed method can eliminate irrelevant background features and merely reserve pixels corresponding to fractures. Simultaneously, relative to the conventional strategy, the time consumption is reduced by more than 98%. The findings of this study can help for better extracting fractures automatically and reducing manual workload.
HSP60 Regulates Lipid Metabolism in Human Ovarian Cancer
Authors: Li Na , Li Nannan , Wen Siqi , Li Biao , Zhang Yaying , Liu Qing , Zheng Shu , Yang Jingru , Shen Liang , Xing Ligang , Zhan Xianquan
Published: September 2021

Accumulating evidence demonstrates that cancer is an oxidative stress‐related disease, and oxidative stress is closely linked with heat shock proteins (HSPs). Lipid oxidative stress is derived from lipid metabolism dysregulation that is closely associated with the development and progression of malignancies. This study sought to investigate regulatory roles of HSPs in fatty acid metabolism abnormality in ovarian cancer. Pathway network analysis of 5115 mitochondrial expressed proteins in ovarian cancer revealed various lipid metabolism pathway alterations, including fatty acid degradation, fatty acid metabolism, butanoate metabolism, and propanoate metabolism. HSP60 regulated the expressions of lipid metabolism proteins in these lipid metabolism pathways, including ADH5, ECHS1, EHHADH, HIBCH, SREBP1, ACC1, and ALDH2. Further, interfering HSP60 expression inhibited migration, proliferation, and cell cycle and induced apoptosis of ovarian cancer cells in vitro. In addition, mitochondrial phosphoproteomics and immunoprecipitation‐western blot experiments identified and confirmed that phosphorylation occurred at residue Ser70 in protein HSP60, which might regulate protein folding of ALDH2 and ACADS in ovarian cancers. These findings clearly demonstrated that lipid metabolism abnormality occurred in oxidative stress‐related ovarian cancer and that HSP60 and its phosphorylation might regulate this lipid metabolism abnormality in ovarian cancer. It opens a novel vision in the lipid metabolism reprogramming in human ovarian cancer.
Chaiqin Qingning Capsule Inhibits Influenza Virus Infection and Inflammation In Vitro and In Vivo
Authors: Zhao Jin , Hao Yanbing , Xia Xuanzi , Li Runfeng , Huang Xiaodong , Yang Zifeng , Wang Xinhua
Published: September 2021

Background. Chaiqin Qingning Capsule (CQ-C) is a traditional Chinese medicine (TCM) formula commonly used to treat respiratory infectious diseases in China. The aim of this study was to detect the effect and mechanism of CQ-C treated with influenza virus in vitro and vivo. Methods. The cytotoxicity and antiviral activity of CQ-C in vitro was determined by methyl thiazolyl tetrazolium (MTT) assay. The regulation of CQ-C on cytokine/chemokine expression was evaluated using RT-qPCR. In addition, the effect of CQ-C on the pathway protein, NF-κB, and its phosphorylation level was verified by western blotting. After virus inoculation, BALB/c mice were administered with CQ-C of different concentrations for 7 days. Body weight, viral titer, lung pathology, and mortality of the mice were measured, and the level of inflammatory cytokines was also examined using real-time RT-qPCR. Results. CQ-C inhibited the proliferation of influenza virus of various strains in vitro, with the 50% inhibitory concentration (IC50) ranging from 49 to 59 µg/mL. CQ-C downregulated virus-induced gene expression of IL-6, TNF-α, CXCL8, CXCL10, CCL5, and COX-2 in a dose-dependent manner in A549 cells. Also, CQ-C inhibited the expression of NF-κB protein of the signaling pathway. Moreover, a decrease of the lung index and mortality of mice was observed in the CQ-C (1 g/kg/d) group. The related cytokine/chemokine expression was also decreased in the early stages of infection in the mRNA level. Conclusion. As a clinically applied Chinese prescription, our study shows that CQ-C has a wide range of effects on several influenza viruses. Moreover, CQ-C could play an important role in anti-influenza activity and anti-inflammation in vitro and in vivo. Thus, CQ-C may be a promising treatment option for influenza.
[Retracted] Structural Classification of Basalt FRP at High Temperatures
Authors: Vummadisetti Sudhir , Pasalapudi Sesha Ratnam , Gottapu Santosh Kumar , Goriparthi Kranthi Kumar , Batu Areda
Published: September 2021

In this study, two different temperatures are considered to verify the mechanical response of basalt fiber‐reinforced polymer specimens. Initially, fibers are subjected to 300°C temperature for 4 hours and 600°C temperature for 2 hours in an electrical muffle furnace effectively. Later, laminates were prepared with these fibers and machined into test strips to verify their mechanical properties by conducting tensile and flexural tests. These laminates were compared with specimens prepared with normal fibers, i.e., fibers without temperature treatment. Moreover, the ductility and elastic behavior of the basalt fiber‐laminated specimens are studied to figure out the possible structural applications. The residual stress of specimens subjected to 300°C temperature under tensile loading is about 84%, whereas for 600°C temperature, it is only 13% of maximum stress. A similar trend has been observed for specimens tested under flexural loading condition. Hence, it is concluded that the basalt fiber‐reinforced polymer laminate can withstand and depict satisfactory results up to 300°C elevated temperature irrespective of time.
Channel Estimation for Switch-Based Millimeter-Wave Communications via Atomic Norm
Authors: Ma Tao , Fan Xiangning , Wu Xiaohuan
Published: September 2021

Channel estimation is a challenging issue in millimeter-wave massive multiple-input-multiple-output (MIMO) communication systems due to the large number of antennas in the transceiver. Existing methods are usually based on phase shifters which may not be a simple circuit at mmWave band. In this paper, we construct a switch-based architecture for analog processors from the coarray point of view and then propose an atomicℓ0-norm minimization problem. We then propose an efficient algorithm to solve this problem based on Wirtinger projection. Since the proposed method requires no angle discretization, it does not suffer from grid mismatch effect that greatly deteriorates the estimation performance of grid-based channel estimation methods. Compared to the atomic norm minimization (ANM) method, our method does not involve vectorization of the channel matrix and hence the dimensionality of the problem is much less than that of ANM. We show that our method is able to provide comparable estimation performance to ANM but with much less computational time. Extensive simulations are carried out to verify the effectiveness of our proposed method.
The First Vietnamese Patient of LEOPARD Syndrome due to a PTPN11 Mutation: A Case Report and Review of the Literature
Authors: Nguyen Hao Trong , Pham Nguyen Nhat , Anh Vu Hoang , Tran Tu Nguyen Anh
Published: September 2021

LEOPARD syndrome is a rare congenital anomaly that involves several organs. Patients with this syndrome develop multiple lentigines resembling a leopard’s hide. LEOPARD is an acronym of the major features constituting the syndrome including lentigines, electrocardiographic conduction defects, ocular hypertelorism, pulmonary valve stenosis, anomalies of genitalia, retardation of growth, and deafness. The syndrome is rare, and only 200 cases have been reported yet worldwide. We present the case of an 8-year-old female patient who visited the Ho Chi Minh City Hospital of Dermato-Venereology because of multiple brownish-black “dots” on her face and body. On examination, she also showed abnormalities in the maxillofacial bones, vertebrae, shoulders, sternum, and teeth, as well as deaf-mutism and growth retardation, which are typical of LEOPARD syndrome. Genetic analysis revealed a PTPN11 gene mutation in this case. To the best of our knowledge, this is the first case of LEOPARD syndrome reported in Vietnam.
Malware Detection Using CNN via Word Embedding in Cloud Computing Infrastructure
Authors: Wang Rong , Tian Cong , Yan Lin
Published: September 2021

The Internet of Things (IoT), cloud, and fog computing paradigms provide a powerful large-scale computing infrastructure for a variety of data and computation-intensive applications. These cutting-edge computing infrastructures, however, are nevertheless vulnerable to serious security and privacy risks. One of the most important countermeasures against cybersecurity threats is intrusion detection and prevention systems, which monitor devices, networks, and systems for malicious activity and policy violations. The detection and prevention systems range from antivirus software to hierarchical systems that monitor the traffic of whole backbone networks. At the moment, the primary defensive solutions are based on malware feature extraction. Most known feature extraction algorithms use byte N-gram patterns or binary strings to represent log files or other static information. The information taken from program files is expressed using word embedding (GloVe) and a new feature extraction method proposed in this article. As a result, the relevant vector space model (VSM) will incorporate more information about unknown programs. We utilize convolutional neural network (CNN) to analyze the feature maps represented by word embedding and apply Softmax to fit the probability of a malicious program. Eventually, we consider a program to be malicious if the probability is greater than 0.5; otherwise, it is a benign program. Experimental result shows that our approach achieves a level of accuracy higher than 98%.
Bioinspired Feathered Flapping Wing UAV Design for Operation in Gusty Environment
Authors: Abbasi S. H. , Mahmood A. , Khaliq Abdul
Published: September 2021

The flight of unmanned aerial vehicles (UAVs) has numerous associated challenges. Small size is the major reason of their sensitivity towards turbulence restraining them from stable flight. Turbulence alleviation strategies of birds have been explored in recent past in detail to sort out this issue. Besides using primary and secondary feathers, birds also utilize covert feathers deflection to mitigate turbulence. Motivated from covert feathers of birds, this paper presents biologically inspired gust mitigation system (GMS) for a flapping wing UAV (FUAV). GMS consists of electromechanical (EM) covert feathers that sense the incoming gust and mitigate it through deflection of these feathers. A multibody model of gust-mitigating FUAV is developed appending models of the subsystems including rigid body, propulsion system, flapping mechanism, and GMS-installed wings using bond graph modeling approach. FUAV without GMS and FUAV with the proposed GMS integrated in it are simulated in the presence of vertical gust, and results’ comparison proves the efficacy of the proposed design. Furthermore, agreement between experimental results and present results validates the accuracy of the proposed design and developed model.
EMM‐CLODS: An Effective Microcluster and Minimal Pruning CLustering‐Based Technique for Detecting Outliers in Data Streams
Authors: Bah Mohamed Jaward , Wang Hongzhi , Zhao Li-Hui , Zhang Ji , Xiao Jie
Published: September 2021

Detecting outliers in data streams is a challenging problem since, in a data stream scenario, scanning the data multiple times is unfeasible, and the incoming streaming data keep evolving. Over the years, a common approach to outlier detection is using clustering‐based methods, but these methods have inherent challenges and drawbacks. These include to effectively cluster sparse data points which has to do with the quality of clustering methods, dealing with continuous fast‐incoming data streams, high memory and time consumption, and lack of high outlier detection accuracy. This paper aims at proposing an effective clustering‐based approach to detect outliers in evolving data streams. We propose a new method called Effective Microcluster and Minimal pruning CLustering‐based method for Outlier detection in Data Streams (EMM‐CLODS). It is a clustering‐based outlier detection approach that detects outliers in evolving data streams by first applying microclustering technique to cluster dense data points and effectively handle objects within a sliding window according to the relevance of their status to their respective neighbors or position. The analysis from our experimental studies on both synthetic and real‐world datasets shows that the technique performs well with minimal memory and time consumption when compared to the other baseline algorithms, making it a very promising technique in dealing with outlier detection problems in data streams.
Effects of Stress Psychological Intervention on the Cardiopulmonary Function, Negative Emotion, Self-Efficacy, and Quality of Life in Patients with Acute Respiratory Failure
Authors: Zhu Na , Gu Fang , Hu Yiqian , Bian Wen
Published: September 2021

Objective. To investigate the changes in cardiopulmonary function, negative emotion, self-efficacy, and quality of life in patients with acute respiratory failure (ARF) after stress psychological intervention. Methods. A prospective study was conducted on 104 patients with ARF admitted to our hospital from March 2019 to March 2021. According to the random number method, the patients were divided into a control group (n = 52) and an experimental group (n = 52). Routine intervention was implemented in the control group, and stress psychological intervention was implemented in the experimental group on the basis of the control group. The cardiopulmonary function, negative emotion, self-efficacy, and quality of life in the two groups were compared. Results. The left ventricular ejection fractions and fraction shortening in the experimental group were higher than those in the control group, as well as the left ventricular mass index was lower than that in the control group (

P
<
0.05

). The first forced expiratory volume (FEV1), forced vital capacity (FVC), and FEV1/FVC in the experimental group were higher than those in the control group (

P
<
0.05

). The Self-Rating Anxiety Scale scores and Self-Rating Depression Scale scores in the experimental group were lower than those in the control group (

P
<
0.05

). The General Self-Efficacy Scale scores of the experimental group were higher than those of the control group (

P
<
0.05

). The Concise Health Measurement Scale scores of the experimental group were higher than those of the control group (

P
<
0.05

). Conclusion. Stress psychological intervention in patients with ARF can improve cardiopulmonary function, reduce negative emotions, improve self-efficacy, and improve quality of life.
Research on the Role of Big Data Technology in the Reform of English Teaching in Universities
Authors: Jia Xiaoge
Published: September 2021

This paper provides an in‐depth understanding and analysis of the reform of English teaching in colleges and universities by analyzing the role of big data technology for the reform through in‐depth research and analysis. Based on the background of the era of education informatization, this study explores the transformative value of the integration of information technology and teaching activities and elaborates the relevant significance at the theoretical and practical levels. Based on this, the research method of this study is established. The realm of integration of information technology and teaching activities and its transformative value is taken as the focus of the study. The integration of information technology and teaching activities means that it is not only a simple superposition between information technology and teaching but also a process to explore the role and influence of information technology into teaching activities by deeply exploring the inner connection between the two, to complete the integration of information technology and teaching activities, and finally to realize the comprehensive development of student’s personality.
Diagnostic Management and Surgical Treatment of Isolated Tricuspid Regurgitation
Authors: de Assis Arthur Cicupira Rodrigues , Boros Gustavo Andre Boeing , Demarchi Lea Maria Macruz Ferreira , Scudeler Thiago Luis , Rezende Paulo Cury
Published: September 2021

Severe tricuspid regurgitation is especially caused by pulmonary hypertension. Primary tricuspid regurgitation in the absence of pulmonary hypertension and of unknown etiology is a very rare condition with scarce data about its diagnosis, treatment, and follow-up. The particularities of surgery indication and outcomes are still not clearly known. A 72-year-old woman with a medical history of coronary artery bypass grafting three years ago presented with shortness of breath and low limb edema. Physical examination revealed a prominent bilateral jugular turgescence, hepatomegaly, peripheral edema, and a left midsternal border holosystolic murmur, suggestive of tricuspid regurgitation. The echocardiogram confirmed the diagnosis and showed preserved right and left ventricular dimensions and function. Coronary angiography showed no new obstructive lesions and patent surgical grafts. Right cardiac catheterization revealed mild pulmonary hypertension and increased right atrium pressure. Cardiac magnetic resonance showed mild right ventricular dilation with normal systolic function and normal left chambers. No late gadolinium enhancement was detected. Because of persistent symptoms, even after optimization of medical therapy, the patient was submitted to tricuspid valve replacement surgery. Immediately after the surgery, the patient developed significant right ventricular dysfunction, with the need of continuous hemodynamic support. She had progressive clinical recovery that was confirmed by serial echocardiograms that showed improvement in right ventricular volume and function. The patient was discharged with no signs or symptoms of right heart failure. The histopathological examination showed significant and diffuse myxomatous degeneration of the leaflets. No signs of infection or vegetation nor disruption of strands were observed. This report illustrates a very rare case of symptomatic primary isolated severe tricuspid regurgitation caused by myxomatous degeneration of the leaflets. The thoroughly diagnostic workup is presented, and only the histopathological analysis of the leaflets revealed the etiologic process. Surgical treatment indicated before the onset of right ventricular failure was essential to patient’s full recovery.
InNetGAN: Inception Network-Based Generative Adversarial Network for Denoising Low-Dose Computed Tomography
Authors: Kulathilake K. A. Saneera Hemantha , Abdullah Nor Aniza , Bandara A. M. Randitha Ravimal , Lai Khin Wee
Published: September 2021

Low-dose Computed Tomography (LDCT) has gained a great deal of attention in clinical procedures due to its ability to reduce the patient’s risk of exposure to the X-ray radiation. However, reducing the X-ray dose increases the quantum noise and artifacts in the acquired LDCT images. As a result, it produces visually low-quality LDCT images that adversely affect the disease diagnosing and treatment planning in clinical procedures. Deep Learning (DL) has recently become the cutting-edge technology of LDCT denoising due to its high performance and data-driven execution compared to conventional denoising approaches. Although the DL-based models perform fairly well in LDCT noise reduction, some noise components are still retained in denoised LDCT images. One reason for this noise retention is the direct transmission of feature maps through the skip connections of contraction and extraction path-based DL modes. Therefore, in this study, we propose a Generative Adversarial Network with Inception network modules (InNetGAN) as a solution for filtering the noise transmission through skip connections and preserving the texture and fine structure of LDCT images. The proposed Generator is modeled based on the U-net architecture. The skip connections in the U-net architecture are modified with three different inception network modules to filter out the noise in the feature maps passing over them. The quantitative and qualitative experimental results have shown the performance of the InNetGAN model in reducing noise and preserving the subtle structures and texture details in LDCT images compared to the other state-of-the-art denoising algorithms.
Protein Signatures of NK Cell–Mediated Melanoma Killing Predict Response to Immunotherapies
Authors: Cappello Sabrina , Sung Hsu-Min , Ickes Christian , Gibhardt Christine S. , Vultur Adina , Bhat Hilal , Hu Zhongwen , Brafford Patricia , Denger Andreas , Stejerean-Todoran Ioana , Köhn Rixa-Mareike , Lorenz Verena , Künzel Nicolas , Salinas Gabriela , Stanisz Hedwig , Legler Tobias , Rehling Peter , Schön Michael P. , Lang Karl S. , Helms Volkhard , Herlyn Meenhard , Hoth Markus , Kummerow Carsten , Bogeski Ivan
Published: September 2021

Despite impressive advances in melanoma-directed immunotherapies, resistance is common and many patients still succumb to metastatic disease. In this context, harnessing natural killer (NK) cells, which have thus far been sidelined in the development of melanoma immunotherapy, could provide therapeutic benefits for cancer treatment. To identify molecular determinants of NK cell–mediated melanoma killing (NKmK), we quantified NK-cell cytotoxicity against a panel of genetically diverse melanoma cell lines and observed highly heterogeneous susceptibility. Melanoma protein microarrays revealed a correlation between NKmK and the abundance and activity of a subset of proteins, including several metabolic factors. Oxidative phoshorylation, measured by oxygen consumption rate, negatively correlated with melanoma cell sensitivity toward NKmK, and proteins involved in mitochondrial metabolism and epithelial–mesenchymal transition were confirmed to regulate NKmK. Two- and three-dimensional killing assays and melanoma xenografts established that the PI3K/AKT/mTOR signaling axis controls NKmK via regulation of NK cell–relevant surface proteins. A “protein-killing-signature” based on the protein analysis predicted NKmK of additional melanoma cell lines and the response of patients with melanoma to anti-PD-1 checkpoint therapy. Collectively, these findings identify novel NK cell–related prognostic biomarkers and may contribute to improved and personalized melanoma-directed immunotherapies.

Significance:

NK-cell cytotoxicity assays and protein microarrays reveal novel biomarkers of NK cell–mediated melanoma killing and enable development of signatures to predict melanoma patient responsiveness to immunotherapies.
Age‐Specific and Sex‐Specific Trends in Life‐Sustaining Care After Acute Stroke
Authors: Joundi Raed A. , Smith Eric E. , Yu Amy Y. X. , Rashid Mohammed , Fang Jiming , Kapral Moira K.
Published: September 2021

Background

Temporal trends in life‐sustaining care after acute stroke are not well characterized. We sought to determine contemporary trends by age and sex in the use of life‐sustaining care after acute ischemic stroke and intracerebral hemorrhage in a large, population‐based cohort.

Methods and Results

We used linked administrative data to identify all hospitalizations for acute ischemic stroke or intracerebral hemorrhage in the province of Ontario, Canada, from 2003 to 2017. We calculated yearly proportions of intensive care unit admission, mechanical ventilation, percutaneous feeding tube placement, craniotomy/craniectomy, and tracheostomy. We used logistic regression models to evaluate the association of age and sex with life‐sustaining care and determined whether trends persisted after adjustment for baseline factors and estimated stroke severity. There were 137 358 people with acute ischemic stroke or intracerebral hemorrhage hospitalized during the study period. Between 2003 and 2017, there was an increase in the proportion receiving care in the intensive care unit (12.4% to 17.7%) and mechanical ventilation (4.4% to 6.6%). There was a small increase in craniotomy/craniectomy, a decrease in percutaneous feeding tube use, and no change in tracheostomy. Trends were generally consistent across stroke types and persisted after adjustment for comorbid conditions, stroke‐center type, and estimated stroke severity. After adjustment, women and those aged ≥80 years had lower odds of all life‐sustaining care, although the disparities in intensive care unit admission narrowed over time.

Conclusions

Use of life‐sustaining care after acute stroke increased between 2003 and 2017. Women and those at older ages had lower odds of intensive care, although the differences narrowed over time. Further research is needed to determine the reasons for these findings.
Transcatheter Aortic Valve Replacement With Self‐Expandable Supra‐Annular Valves for Degenerated Surgical Bioprostheses: Insights From Transcatheter Valve Therapy Registry
Authors: Dallan Luis Augusto P. , Forrest John K. , Reardon Michael J. , Szeto Wilson Y. , George Isaac , Kodali Susheel , Kleiman Neal S. , Yakubov Steven J. , Grubb Kendra J. , Liu Fang , Baeza Cristian , Attizzani Guilherme F.
Published: September 2021

Background

Transcatheter aortic valve replacement with supra‐annular transcatheter heart valves has been adopted in patients with degenerated surgical aortic valves. The next generation self‐expanding Evolut PRO valve has not been evaluated in patients with surgical valve failure.

Methods and Results

Patients undergoing transcatheter aortic valve replacement in degenerated surgical aortic valve procedures using the Evolut R or Evolut PRO transcatheter heart valves in the Society of Thoracic Surgeons and American College of Cardiology Transcatheter Valve Therapy Registry between April 2015 and June 2019 were evaluated. Transcatheter valve performance was evaluated by clinical site echocardiography. In‐hospital, 30‐day, and 1‐year clinical outcomes were based on the Society of Thoracic Surgeons‐American College of Cardiology‐Transcatheter Valve Therapy registry definitions. Transcatheter aortic valve replacement in degenerated surgical aortic valve was performed in 5897 patients (5061 [85.8%] patients received the Evolut R valve and 836 [14.2%] received the Evolut PRO valve). Thirty‐day transcatheter heart valves hemodynamic performance was excellent in both groups (mean gradient: Evolut PRO: 13.8±7.5 mm Hg; Evolut R: 14.5±8.1 mm Hg), while paravalvular regurgitation was significantly different between valve types (
P
=0.02). Clinical events were low at 30 days (Evolut PRO: for the all‐cause mortality, 2.8%, any stroke was 1.8%, new pacemaker implantation, 3.0%: Evolut R:all‐cause mortality, 2.5%, any stroke was 2.2%, new pacemaker implantation, 5.3%) and 1 year (Evolut PRO: all‐cause mortality, 9.2%; any stroke, 3.1%; Evolut R: all‐cause mortality, 9.8%; any stroke, 2.9%).

Conclusions

Transcatheter aortic valve replacement in degenerated surgical aortic valve with self‐expandable supra‐annular transcatheter heart valves is associated with excellent clinical outcomes and valve hemodynamics. Additional reductions in residual paravalvular regurgitation were obtained with the next generation Evolut PRO.
How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answering
Authors: Jiang Zhengbao , Araki Jun , Ding Haibo , Neubig Graham
Published: September 2021

Recent works have shown that language models (LM) capture different types of knowledge regarding facts or common sense. However, because no model is perfect, they still fail to provide appropriate answers in many cases. In this paper, we ask the question, “How can we know when language models know, with confidence, the answer to a particular query?” We examine this question from the point of view of calibration, the property of a probabilistic model’s predicted probabilities actually being well correlated with the probabilities of correctness. We examine three strong generative models—T5, BART, and GPT-2—and study whether their probabilities on QA tasks are well calibrated, finding the answer is a relatively emphatic no. We then examine methods to calibrate such models to make their confidence scores correlate better with the likelihood of correctness through fine-tuning, post-hoc probability modification, or adjustment of the predicted outputs or inputs. Experiments on a diverse range of datasets demonstrate the effectiveness of our methods. We also perform analysis to study the strengths and limitations of these methods, shedding light on further improvements that may be made in methods for calibrating LMs. We have released the code at https://github.com/jzbjyb/lm-calibration.
Catalogue and typification of the Moroccan taxa published by Carlos Pau
Authors: NUALART NEUS , SORIANO IGNASI , PÉREZ PRIETO David , IBÁÑEZ NEUS
Published: September 2021

Carlos Pau was one of the first Spanish botanists interested in the flora of northern Morocco. He proposed 421 taxa for this area, including some illegitimate names and nomina nuda. A complete and annotated catalogue of names by Pau for Moroccan taxa is presented here. For all of them, the typification and synonymy have been evaluated. For 63 taxa the holotype is indicated, and 206 taxa are typified here. The main collection of Pau and most types are preserved in Herb. MA, but many types have also been found in Herb. BC and other European herbaria.
Morphological evidence for the conspecific status of the rediscovered Mimulicalyx rosulatus and M. paludigenus
Authors: ZHAO FEI , MIN DAO-ZHANG , XIANG CHUN-LEI , CHEN BIN , ZHOU XIN-XIN , LIU BING , LI BO
Published: September 2021

Mimulicalyx is an oligo-genus including two species that are endemic to southwest China. Based on investigation of the rediscovered populations of M. rosulatus and M. paludigenus, examination of herbarium specimens (including types), as well as consultation of protologues and distributions, no obvious morphorlogical differences has been found and we concluded that they are conspecific. Therefore, M. paludigenus is reduced to a synonym of M. rosulatus. Field photographs and an updated morphological description of M. rosulatus are provided.
The type specimens of bees (Hymenoptera, Apoidea) deposited in the Zoological Institute of the Russian Academy of Sciences, St. Petersburg. Contribution IV. Family Andrenidae, genus Andrena Fabricius, 1775, species described by F. Morawitz
Authors: ASTAFUROVA YULIA V. , PROSHCHALYKIN MAXIM YU. , SIDOROV DMITRY A. , OSYTSHNJUK ANNA Z.
Published: September 2021

The type specimens for names of bee taxa in the genus Andrena Fabricius, 1775 of family Andrenidae described by F. Morawitz and deposited in the Zoological Institute, Russian Academy of Sciences (St. Petersburg) are reviewed. Name-bearing types of 68 species are illustrated and detailed information is provided. Lectotypes are designated here for the following 32 nominal taxa: Andrena adjacens Morawitz, 1875, A. anthracina Morawitz, 1880, A. atrohirta Morawitz, 1893, A. croceiventris Morawitz, 1871, A. ehnbergi Morawitz, 1888, A. formosa Morawitz, 1877, A. glasunowi Morawitz, 1894, A. inconspicua Morawitz, 1871, A. laticeps Morawitz, 1877, A. melanura Morawitz, 1877, A. mongolica Morawitz, 1880, A. mucronata Morawitz, 1871, A. nigrobarbata Morawitz, 1871, A. nylanderi Morawitz, 1865, A. ochracea Morawitz, 1872, A. opaca Morawitz, 1868, A. orbitalis Morawitz, 1871, A. paliuri Morawitz, 1877, A. pretiosa Morawitz, 1893, A. ranunculorum Morawitz, 1877, A. rotundilabris Morawitz, 1877, A. sahlbergi Morawitz, 1888, A. salicina Morawitz, 1877, A. schencki Morawitz, 1866, A. semirubra Morawitz, 1875, A. sexguttata Morawitz, 1877, A. sylvatica Morawitz, 1877, A. transitoria Morawitz, 1871, A. truncatilabris Morawitz, 1877, A. tscheki Morawitz, 1872, A. virago Morawitz, 1894, A. curiosa Morawitz, 1877.
Rapid Sea-Level Rise in the Southern-Hemisphere Subtropical Oceans
Authors: Duan Jing , Li Yuanlong , Wang Fan , Hu Aixue , Han Weiqing , Zhang Lei , Lin Pengfei , Rosenbloom Nan , Meehl Gerald A.
Published: September 2021

The subtropical oceans between 35°-20°S in the Southern Hemisphere (SH) have exhibited prevailingly rapid sea-level rise (SLR) rates since the mid-20thcentury, amplifying damages of coastal hazards and exerting increasing threats to South America, Africa, and Australia. Yet, mechanisms of the observed SLR have not been firmly established, and its representation in climate models has not been examined. By analyzing observational sea-level estimates, ocean reanalysis products, and ocean model hindcasts, we show that the steric SLR of the SH subtropical oceans between 35°-20°S is faster than the global mean rate by 18.2%±9.9% during 1958-2014. However, present climate models—the fundamental bases for future climate projections—generally fail to reproduce this feature. Further analysis suggests that the rapid SLR in the SH subtropical oceans is primarily attributable to the persistent upward trend of the Southern Annular Mode (SAM). Physically, this trend in SAM leads to the strengthening of the SH subtropical highs, with the strongest signatures observed in the southern Indian Ocean. These changes in atmospheric circulation promote regional SLR in the SH subtropics by driving upper-ocean convergence. Climate models show systematic biases in the simulated structure and trend magnitude of SAM and significantly underestimate the enhancement of subtropical highs. These biases lead to the inability of models to correctly simulate the observed subtropical SLR. This work highlights the paramount necessity of reducing model biases to provide reliable regional sea-level projections.
A Comparison of Arctic and Atlantic Cyclone Predictability
Authors: Capute Peyton K. , Torn Ryan D.
Published: September 2021

Arctic cyclones (ACs) are synoptic-scale features that can be associated with strong, intense winds over the Arctic Ocean region for long periods of time, potentially leading to rapid declines of sea ice during the summer. As a consequence, sea ice predictions may rely on the predictability of cyclone-related wind speed and direction, which critically depends on the cyclone track and intensity. Despite this, there are relatively few studies that have documented the predictability of ACs during the summer, beyond a few case studies, nor has there been an extensive comparison of whether these cyclones are more or less predictable relative to comparable midlatitude cyclones, which have been studied in greater detail. The goal of this study is to document the practical predictability of AC position and intensity forecasts over 100 cases and compare it with 89 Atlantic Ocean basin midlatitude cyclones using the Global Ensemble Forecast System (GEFS) Reforecast V2. This dataset contains 11-member ensemble forecasts initialized daily from 1985 to the present using a fixed model. In this study, forecasts initialized 1 and 3 days prior to the cyclone development time are compared, where predictability is defined as the ensemble mean root-mean-square error and ensemble standard deviation (SD). Although Atlantic basin cyclone tracks are characterized by higher predictability relative to comparable ACs, intensity predictability is higher for ACs. In addition, storms characterized by low ensemble SD and predictability are found in regions of higher baroclinic instability than storms characterized by high predictability. There appears to be little, if any, relationship between latent heat release and precipitable water and predictability.
Conveying Listenership Status Through Multiple duis in Mandarin Chinese Conversation
Authors: Lee Jee Won
Published: September 2021

This study explores the use of multiple reactive tokens ( duis) in responsive turns in Mandarin, particularly in the sequential and interactional environments that project them in daily interactions. Data analysis of over 100 unscripted conversations between two or three native speakers indicate that an increase in the number of duis co-occurring corresponds to a higher level of listenership, resulting in a hierarchy of displayed stances ranging from neutral to active to affiliative. I argue that almost no practice of multiple duis in conversation is guaranteed to work mechanistically and automatically, as it requires at least a two-party collaboration. Multiple duis as reactive tokens in interaction are systematic, conversationally strategic, and sequentially as well as socially organized. Furthermore, they are recurrent patterns at the discourse level that must be recognized as routine practices in conversation, as their format can help accomplish unique interactional tasks that exhibit strong coherence and utility at the interactional level.
Indian Migrant Workers’ Experience During the COVID-19 Pandemic Nationwide Lockdown
Authors: Kumar Navin , Udah Hyacinth , Francis Abraham , Singh Sanchita , Wilson Anica
Published: September 2021

This article explores the lived experiences of some Indian migrant workers (MW) during the first COVID-19 pandemic nationwide lockdown, investigating their plights from a social identity perspective. It analyses crises associated with the COVID-19 pandemic, and with hunger and starvation. Drawing on a qualitative study conducted with twelve participants in the city of Pune in the Western Indian state of Maharashtra, the findings suggest that the participants’ plights have been exacerbated by the COVID-19 pandemic. The findings indicate the need for policy responses to focus on addressing conditions of work, terms of employment and access to necessities for Indian MW, including ensuring conditions for a prompt job-ready recovery and mental health care after the COVID-19 pandemic.
Exome Sequencing of 5 Families with Severe Early-Onset Periodontitis
Authors: Richter G.M. , Wagner G. , Reichenmiller K. , Staufenbiel I. , Martins O. , Löscher B.S. , Holtgrewe M. , Jepsen S. , Dommisch H. , Schaefer A.S.
Published: September 2021

Periodontitis is characterized by alveolar bone loss leading to tooth loss. A small proportion of patients develop severe periodontitis at the juvenile or adolescent age without exposure to the main risk factors of the disease. It is considered that these cases carry rare variants with large causal effects, but the specific variants are largely unknown. In this study, we performed exome sequencing of 5 families with children who developed stage IV, grade C, periodontitis between 3 and 18 y of age. In 1 family, we found compound heterozygous variants in the gene CTSC (p.R272H, p.G139R), 1 of which was previously identified in a family with prepubertal periodontitis. Subsequent targeted resequencing of the CTSC gene in 24 patients <25 y of age (stage IV, grade C) identified the known mutation p.I453V (odds ratio = 4.06, 95% CI = 1.6 to 10.3, P = 0.001), which was previously reported to increase the risk for adolescent periodontitis. An affected sibling of another family carried a homozygous deleterious mutation in the gene TUT7 (p.R560Q, CADD score >30 [Combined Annotation Dependent Depletion]), which is implicated in regulation of interleukin 6 expression. Two other affected siblings shared heterozygous deleterious mutations in the interacting genes PADI1 and FLG (both CADD = 36), which contribute to the integrity of the environment–tissue barrier interface. Additionally, we found predicted deleterious mutations in the periodontitis risk genes ABCA1, GLT6D1, and SIGLEC5. We conclude that the CTSC variants p.R272H and p.I453V have different expressivity and diagnostic relevance for prepubertal and adolescent periodontitis, respectively. We propose additional causal variants for early-onset periodontitis, which also locate within genes that carry known susceptibility variants for common forms. However, the genetic architecture of juvenile periodontitis is complex and differs among the affected siblings of the sequenced families.