bluuebunny/crossref_metadata_2025 huggingface dataset:
Culture and Language Are Inextricably Linked: Surveying the Effectiveness of Culture-Based Instructional Materials on Enhancing Reading Comprehension (RC), Inclination to Reading, and Reading Attitude (RA) among EFL Learners
Authors: Ngoc Diep Le Thi , Gustina Zainal Anna , Keezhatta Muhammed Salim , Imamutdinovna Gabidullina Farida , Hassan Isyaku , Heydarnejad Tahereh
Published: May 2022

Students who learn about different cultures during their education feel more comfortable and safer with these differences later in life. This allows them to interact in a wider range of social groups and feel more confident in themselves and in their interactions with others. Thus, language and culture are not separated. Considering this important point, the present research inspected the impacts of having English CBK on improving the EFLL learners’ RC and motivation. In addition, the EFLL learners’ attitudes towards incorporating English cultural-based materials (CBMs) into their English coursebook were examined. This was accomplished by randomly dividing 50 pre-intermediate students from a private English language institution into two groups: an experimental group (EG) and a control group (CG). Next, the motivation questionnaire developed by Hayami and colleagues (1989) was delivered to the individuals in both groups of participants. Following that, all participants received a pretest of RC, and then, the intervention was performed. The EG was instructed through using the English CBMs, while the CG received the instruction using culture-free materials. The entire treatment took 11 sessions. In the last three sessions, the reading posttest, the motivation, and the attitude questionnaires were administered to assess the influences of the treatment on the RC and motivation of the EFL learners (EFLLs). The results of the statistical analyses indicated that the EG had better performances than the CG on the posttests of RC and reading motivation (RM). Also, the results divulged that the EFL students manifested positive attitudes towards integrating English CBMs into their English coursebook. Considering the findings of this study, some implications are proposed at the end of this study.
An Intelligent Cloud Computing Data Processing System for College Innovation and Entrepreneurship Data Statistics
Authors: Jia Hongjun , Chen Wenjing
Published: May 2022

With the improvement of the enrollment rate in recent years, innovation and entrepreneurship in colleges and universities have become the focus of the country and people. However, the statistics of innovation and entrepreneurship in colleges and universities have become more and more complicated and difficult. The purpose of this paper is to study how to face the statistics of innovation and entrepreneurship in colleges and universities, then to study the intelligent cloud computing data processing system, and put forward the importance of innovation and entrepreneurship and cloud computing in colleges and universities. The experiment results show that it can be seen that the number of graduates has risen sharply from 2011 to 2020 and the percentage has risen from about 20% to about 90%, which has also led to a great increase in the difficulty of graduate entrepreneurial data management. The difficulty of graduate entrepreneurial data management has risen from around 18% at the beginning to around 87% in 2020. Therefore, it is necessary to study the data processing system to make data processing more efficient. The intelligent cloud computing data processing system significantly improves the quality and efficiency of entrepreneurial service management, and the data mining application in the system can also provide data support for the analysis and prediction of graduates’ entrepreneurial situations. The intelligent cloud computing data processing system significantly improves the quality and efficiency of entrepreneurial service management, and the data mining application in the system can also provide data support for the analysis and prediction of graduates’ entrepreneurial situations.
Ischemic Brain Stroke and Mesenchymal Stem Cells: An Overview of Molecular Mechanisms and Therapeutic Potential
Authors: Jingli Yang , Jing Wang , Saeed Yasmeen
Published: May 2022

Ischemic brain injury is associated with a high rate of mortality and disability with no effective therapeutic strategy. Recently, a growing number of studies are focusing on mesenchymal stem cell-based therapies for neurodegenerative disorders. However, despite having the promising outcome of preclinical studies, the clinical application of stem cell therapy remained elusive due to little or no progress in clinical trials. The objective of this study was to provide a generalized critique for the role of mesenchymal stem cell therapy in ischemic stroke injury, its underlying mechanisms, and constraints on its preclinical and clinical applications. Thus, we attempted to present an overview of previously published reports to evaluate the progress and provide molecular basis of mesenchymal stem cells (MSCs) therapy and its application in preclinical and clinical settings, which could aid in designing an effective regenerative therapeutic strategy in the future.
Optimization of Computer Web Page Interface Based on BP Neural Network Algorithm and Multimedia
Authors: Ma Yan
Published: May 2022

In web design, we need to make full use of computer multimedia technology, which can effectively improve the quality of web design and provide greater convenience. The neural network needs to calculate a large amount of training data in image optimization, and the calculation speed cannot keep up with real-time data processing, resulting in the problem of poor quality of optimized images. This paper analyzes the problems existing in the traditional optimized BP neural network algorithm and puts forward an optimized BP neural network image optimization method which combines the increase of momentum term with the adaptive adjustment of learning rate. This method can speed up the iteration speed and jump out of the situation of premature local minimum. The test results show that the user satisfaction of the text visual effect of the web interface optimized by this method is more than 98% and the user satisfaction of other methods is only about 90%. The visual satisfaction of the web interface optimized by this method is significantly higher than that of the comparative method. The web interface visual optimization effect of the method in this article is better, and it can meet the satisfaction requirements of most users.
Estimating Smallholder Farmers’ Willingness to Pay for Sustainable Irrigation Water Use in North Western Ethiopia: A Contingent Valuation Method Study in Gumara Irrigation Project
Authors: Getnet Aklok , Tassie Kassahun , Ayele Zewdu Brehanie
Published: May 2022

Ethiopia is the water tower of sub-Saharan Africa countries with 12 major river basins and 22 natural and artificial lakes, which make a median of 1,557.5 m3 of water available per person per year. This study specifically was aimed to estimate smallholder farmers’ willingness to pay for sustainable irrigation water use in northwestern Ethiopia using double-bounded dichotomous choice with a follow-up of open-ended contingent valuation questions. For this study, as a source of quantitative data, a total of 288 households were selected through a systematic random sampling method. Additionally, qualitative and secondary data were collected from the focus group discussions and desk reviews, respectively. A seemingly unrelated bivariate probit model and descriptive statistics were used to estimate households’ mean and aggregate willingness to pay. The result of the study revealed that about 283 (98.26%) households were willing to pay for sustainable irrigation water use via constructing water storage, allocation, and distribution channels. Moreover, the result from seemingly unrelated bivariate probit model regression results from double-bounded dichotomous choice questions, mean, and aggregate willingness to pay were 950.7 ETB (€25.7) and 1,087,159.09 ETB (€29,382.7) per month and per year, respectively. On the other hand, the mean and aggregate willingness to pay from the open-ended questions were 926.059 ETB (€25.03) and 1,072,990.52 ETB (€28,999.74) per month and year per household, respectively. Therefore, the study suggested for the concerned body to introduce proper irrigation water pricing systems based on households’ willingness and ability to pay. And an estimate of willingness to pay provides an indication of the demand for introducing proper irrigation water use system leading to sustainable use system.
Research on Metallogenic System and Deposit Genesis: With Zhacun Goldmine in Weishan County of Yunnan as an Example
Authors: Ding Xing-yu , Hu Wen-jun , Chang Yi
Published: May 2022

This paper mainly takes Zhacun goldmine as the research object and carries out research on the metallogenic system and genesis of the deposit in the area. The research methods are as follows: according to the geological characteristics of the metallogenic mining area in the Zhacun goldmine, combined with the comparative analysis of the metallogenic age, alteration characteristics and lithology between the Zhacun goldmine and the Lianhuashan alkali rich rock mass, and the analysis of the isotopic data in the Zhacun goldmine, this paper demonstrates that the magmatic activity of the Lianhuashan quartz monzonite porphyry plays an important role in the mineralization of this area, which is both an important ore source and fluid source. It is also the main heat source driving the circulation of ore-forming fluid. On this basis, through the analysis of the metallogenic elements in the area, the metallogenic system model of Zhacun goldmine is constructed. It is considered that under the action of long-term horizontal compressive stress, the atmospheric precipitation infiltrated into the formation continued to penetrate along the fractures and fissures to deep crust and finally mixed with the magmatic water sealed in the thick formation. During this period, a series of shallow and ultrashallow porphyry mass intruded, providing heat source and part of the ore-forming materials and resulting in incomplete homogenization under high temperature and high pressure, which formed highly mineralized mixed water. Under the combined action of long-term compressive stress and various deep thermal dynamics, these mineral fluids migrated along the buried deep faults near the core of the duplex anticline to the upper part of the crust. When the metal elements in these ore fluids migrated over long distances to the nappe fault zone of the gold-bearing fracture zone, the gold began to precipitate, and the native gold and the coarse-grained pyrite and quartz formed at the same time or earlier started to fill the fracture zone along the fissures and accumulate into minerals. Then, through the analysis of metallogenic conditions, gold mineralization process, and genetic mechanism of the deposit, it is proposed that the genetic type of the ore deposit in this area is magmatic mesothermal-epithermal gold deposit. The establishment of metallogenic system model in Zhacun goldmine will provide theoretical and practical guidance for deep and peripheral prospecting prediction in the area, carry out targeted and reasonable prediction, and improve prospecting effectiveness.
Study of Chinese Shadow Mapping Classification with the Application of Deep Learning Algorithms
Authors: Fu Qin , Hu Qingtong
Published: May 2022

Shadow puppetry is a traditional Chinese fascinating theatre act performed by large group of artists. An artist generally uses sticks, transparent cloth screen, and flat puppets behind an illuminated background to create illusion of moving pictures during the act. These acts showcase the culture, heritage, social belief, and customs of Chinese and are a popular form of entertainment especially to youths. The modern method of digital shadow puppetry has gained a tremendous interest in the diversifying entertainment industry. Proper identification and classification of shadow puppetry is a tedious process, demanding significant research studies attention to solve the real-world vision-based problem. The proposed research studies focus on the design of artificial intelligence-based modified Grey Wolf Optimized Classifier (mGWOC) for the digital shadow puppetry problem. Data augmentation process is performed in the initial stage of the work to increase the size of the dataset used for training and testing. Secondly, to derive feature vectors from shadow puppet images, Alex Net-a deep neural network model as a part of feature extraction is adopted. Finally, Extreme Learning Classifier (ELC) is applied to allocate proper class labels. The experimental results of the proposed mGWOC reports betterment over the ResNet model, DenseNet model, and grey wolf optimization algorithm in terms of precision, recall, F-score, and kappa statistical performance measure reporting average accuracy as 0.951.
Fixed Points of Proinov Type Multivalued Mappings on Quasimetric Spaces
Authors: Karapinar Erdal , Fulga Andreea , Yeşilkaya Seher Sultan
Published: May 2022

In this paper, we obtain new results which have not been encountered before in the literature, in multivalued quasimetric spaces, inspired by Proinov type contractions. We use admissible function as proving theorems. We also give an example that supports our theorems.
Numerical Solution via Operational Matrix for Solving Prabhakar Fractional Differential Equations
Authors: Md Nasrudin Farah Suraya , Phang Chang
Published: May 2022

In this work, we apply the operational matrix based on shifted Legendre polynomials for solving Prabhakar fractional differential equations. The Prabhakar derivative is defined in three‐parameter Mittag‐Leffler function. We achieve this by first deriving the analytical expression for Prabhakar derivative of xp where p is positive integer, via integration. Hence, for the first time, the operational matrix method for Prabhakar derivative is derived by using the properties of shifted Legendre polynomials. Hence, we transform the Prabhakar fractional differential equations into a system of algebraic equations. By solving the system of algebraic equations, we were able to obtain the numerical solution of fractional differential equations defined in Prabhakar derivative. Only a few terms of shifted Legendre polynomials are needed for achieving the accurate solution.
A Novel Method for Lithium-Ion Battery Fault Diagnosis of Electric Vehicle Based on Real-Time Voltage
Authors: Li Fang , Min Yongjun , Zhang Ying
Published: May 2022

The cell faults of lithium-ion batteries will lead to the atypical deterioration of battery performance and even thermal runaway. In this paper, a novel fault diagnosis method for lithium-ion batteries of electric vehicles based on real-time voltage is proposed. Firstly, the voltage distribution of battery cells is confirmed in electric vehicles, and the reasons are analyzed. Furthermore, kurtosis is utilized to discover cell faults for the first time. After the kurtosis-based strategy alarm, the faulty cells in the battery pack are identified through multidimensional scaling and density-based spatial clustering of applications with noise. This method reduces the computational load of the data platform due to the characteristics of the sequential structure. Finally, the strategies to quantify the level of faulty cells and evaluate the safety of electric vehicles are presented. Through the real-time data collected by electric vehicles, it has been proven that this method can warn and locate faulty cells earlier than the original system method and has better robustness than other unsupervised fault diagnosis methods.
TEE-Watchdog: Mitigating Unauthorized Activities within Trusted Execution Environments in ARM-Based Low-Power IoT Devices
Authors: Khurshid Anum , Yalew Sileshi Demesie , Aslam Mudassar , Raza Shahid
Published: May 2022

Trusted execution environments (TEEs) are on the rise in devices all around us ranging from large-scale cloud-based solutions to resource-constrained embedded devices. With the introduction of ARM TrustZone-M, hardware-assisted trusted execution is now supported in IoT nodes. TrustZone-M provides isolated execution of security-critical operations and sensitive data-generating peripherals. However, TrustZone-M, like all other TEEs, does not provide a mechanism to monitor operations in the trusted areas of the device and software in the secure areas of an IoT device has access to the entire secure and nonsecure software stack. This is crucial due to the diversity of device manufacturers and component suppliers in the market, which manifests trust issues, especially when third-party peripherals are incorporated into a TEE. Compromised TEEs can be misused for industrial espionage, data exfiltration through system backdoors, and illegal data sharing. It is of utmost importance here that system peripheral behaviour in terms of resource access is in accordance with their intended usage that is specified during integration. We propose TEE-Watchdog, a lightweight framework that establishes MPU protections for secure system peripherals in TrustZone-enabled low-end IoT devices. TEE-Watchdog ensures blocking unauthorized peripheral accesses and logging of application misbehaviour running in the TEE based on a manifest file. We define lightweight specifications and structure for the application manifest file enlisting permissions for critical system peripherals using concise binary object representation (CBOR). We implement and evaluate TEE-Watchdog using a Musca-A2 test chipboard. Our microbenchmark evaluations on CPU time and RAM usage demonstrated the practicality of TEE-Watchdog. Securing the system peripherals using TEE-Watchdog protections induced a 1.4% overhead on the latency of peripheral accesses, which was 61 microseconds on our test board. Our optimized CBOR-encoded manifest file template also showed a decrease in manifest file size by 40% as compared to the standard file formats, e.g., JSON.
Monoclonal Gammopathy of Renal Significance with Progression to Multiple Myeloma in a Patient with ASIA-MO Syndrome
Authors: Vargas Gutiérrez David Alejandro , Arias Callejas Karina Ivonne , Palacios Ruiz Edwin Pavel , Pérez Vinueza Priscila Joseline , Muñoz Vega Juan Diego , Mejía Geraldo Ana Karen G. , Zaldívar Ingrid Salinas
Published: May 2022

Background. Autoimmune/inflammatory syndrome induced by adjuvants is a disease associated with an unregulated hyperactivity of the immune system and may also be associated with a high frequency of hematologic malignancies. Report. This is a case of a female with ASIA-MO syndrome secondary to infiltration of mineral oil for aesthetic purposes and presented with multiple episodes of urolithiasis resulting in renal impairment of her left kidney confirmed by scintigraphy and ending in unilateral nephrectomy. Retrospective renal piece analysis confirmed tubulointerstitial infiltration with light chains and plasma cells. Paraffin fixation prevented subsequent immunofluorescence analysis for better follow-up of the patient. Conclusion. The presence of positive immunofixation kappa chains explained the sudden deterioration of renal function with monoclonal gammopathy of renal significance which concluded in an association between diseases, such as multiple light chain myeloma, as a final diagnosis.
Potential Value of Circular RNA circTBC1D4 in Gastrointestinal Stromal Tumors
Authors: Chunyan-Zou  , Yanpeng-He  , Changshun-Xie  , Fulai-Gao  , Xiaoli-Xie  , Xiukun-Chai  , Chenxi-He  , Dongqiang-Zhao
Published: May 2022

Aims. To explore the expression of circular RNA (circRNA) in gastrointestinal stromal tumors. Background. Gastrointestinal stromal tumors (GIST) are mainly distributed in the stomach and small intestine. Recently, it has been verified that circular RNA (circRNA) has an important function in the regulation of GIST. Nevertheless, detailed investigations of circRNA-miRNA-mRNA regulatory networks in GIST are lacking. Objective. To analyze the gastrointestinal stromal tumor circRNA-miRNA-mRNA network, assessing the effect of circle RNA in gastrointestinal stromal tumors. Method. All the differential circRNAs and mRNAs were obtained from Gene Expression Omnibus (GEO) microarray data (GSE131481 and GSE147303, GSE131481, and GSE13861). Furthermore, a circRNA-miRNA-mRNA network was established. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were used to reveal the correlation between the functions of signaling pathways and target genes. The hub genes of protein-protein interaction (PPI) network and cytoHubba were also defined. Quantitative real-time PCR (qRT-PCR) was used to measure the expression levels of hsa-circ-0002917 (circTBC1D4), hsa-miR-590-5p (miR-590-5p), and PLN. Results. PPI network and Cytoscape showed that ATP1A2, PLN, KCNMA1, and SCNN1B were four central DEGs. GO analysis results revealed that DEGs were involved in negative management of myocardial contraction, regulation of myocardial cell contraction, ethanol oxidation, cellular potassium ion homeostasis, and relaxation of cardiac muscle, and KEGG analysis showed that major DEGs were with cGMP-PKG signaling pathway. Moreover, we obtained two pairs of axes, namely, hsa-circ-0039216/hsa-miR-338-3p/ATP1A2 and hsa-circ-0002917/hsa-miR-590-5p/PLN. The target of TBC1D4 is miR-590-5p, and miR-590-5p increased after knocking down TBC1D4. Moreover, PLN was the target of miR-590-5p, and miR-590-5p exerts antitumor effects by reducing PLN. Conclusions. In this study, we constructed a circRNA-miRNA-mRNA management network interrelated with GIST and researched the potential roles of circRNA. Moreover, we discovered a new molecular landmarker for the prediction, diagnosis, and therapy of patients.
A Prediction Model of Recidivism of Specific Populations Based on Big Data
Authors: Leng Jing , Xu Wei , Li Tonghong , Chen Likun , Xu Mingwei
Published: May 2022

This research is aimed at establishing and improving the relevant information database of “released prisoners,” integrating the behavior data of specific populations, constructing the early-warning model of recidivism, evaluating the database file information by using prediction analysis technology, and making a prediction alarm to the people who are most likely to commit the crime again on the basis of big data analysis so as to ultimately achieve the goal of reducing the recidivism rate. The research used the data exchange technology of the heterogeneous database to complete data collection and database establishment, used the feature engineering technology to analyze the big data of specific populations, obtained the multidimensional behavior trajectory data, and carried out sorting and statistics. On this basis, the linear regression algorithm was applied to make the prediction and evaluation, and the visual results were presented to assist in researching and judging the possibility of recidivism of specific personnel. Through programming realization and simulation experiments, the research obtained the tendency prediction of the people to commit crimes again by statistical analysis from multidimensional data with a long time span. In the next step, the real test will be carried out to help the public security work in China and contribute to the maintenance of national and social stability.
Blockade of NLRP3/Caspase-1/IL-1β Regulated Th17/Treg Immune Imbalance and Attenuated the Neutrophilic Airway Inflammation in an Ovalbumin-Induced Murine Model of Asthma
Authors: Chen Ling , Hou Weiwei , Liu Fen , Zhu Ruochen , Lv Anping , Quan Wenqiang , Mao Song
Published: May 2022

Asthma is a heterogeneous inflammatory disorder of the airways, and multiple studies have addressed the vital role of the nucleotide-binding oligomerization domain-like receptor family pyrin domain containing 3 (NLRP3)/caspase-1/interleukin-1β (IL-1β) pathway in asthma, but its impact on ovalbumin- (OVA-) induced neutrophilic asthma remains unclear. Here, we explored this pathway’s effect on airway inflammation in neutrophilic asthma to clarify whether blocking this signaling could alleviate asthmatic airway inflammation. Using an established OVA-induced neutrophilic asthma mouse model, we provided asthmatic mice with a highly selective NLRP3 inhibitor, MCC950, and a specific caspase-1 inhibitor, Ac-YVAD-cmk. Our results indicated that asthmatic mice exhibited increased airway hyperresponsiveness, neutrophil infiltration, and airway mucus hypersecretion, upregulated retinoid-related orphan receptor-γt (RORγt) mRNA expression, and downregulated fork head box p3 (Foxp3) mRNA expression, which was concurrent with NLRP3 inflammasome activation and upregulation of caspase-1, IL-1β, and IL-18 expression in lung. Treatment of NLRP3 inflammasome inhibitors significantly attenuated airway hyperresponsiveness, airway inflammation, and reversed T helper 17 (Th17)/regulatory T (Treg) cell imbalance in asthmatic mice. We propose that the NLRP3/caspase-1/IL-1β pathway plays an important role in the pathological process of neutrophilic asthma and provides evidence that blocking this pathway could potentially be a treatment strategy to ameliorate airway inflammation in asthma after validation with future experimental and clinical studies.
A Novel Genetic Neural Network Algorithm with Link Switches and Its Application in University Professional Course Evaluation
Authors: Ji Honghai , Zhou Jinyao , Liu Shida , Wang Li , Fan Lingling
Published: May 2022

This study exploits a novel enhanced genetic neural network algorithm with link switches (EGA-NNLS) to model the professional university course evaluating system. Various indices should be employed to evaluate the learning effect of a professional course comprehensively and objectively, and the traditional artificial evaluation methods cannot achieve this goal. The presented data-driven modeling method, EGA-NNLS, combines a neural network with link switches (NN-LS) with an enhanced genetic algorithm (EGA) and the Levenberg–Marquardt (LM) algorithm. It employs an optimized network structure combined with EGA and NN-LS to learn the relationships between the system’s input and output from historical data and uses the network’s gradient information via the LM algorithm. Compared with the traditional backpropagation neural network (BPNN), EGA-NNLS achieves a faster convergence speed and higher evaluation precision. In order to verify the efficiency of EGA-NNLS, it is applied to a collection of experimental data for modeling the professional university course evaluating system.
Improving Solute Clearances by Hemodialysis
Authors: Lee Seolhyun , Sirich Tammy L. , Meyer Timothy W.
Published: May 2022

The adequacy of hemodialysis is now assessed by measuring the removal of the single-solute urea. The urea clearance provided by contemporary dialysis is a large fraction of the blood flow through the dialyzer and therefore cannot be increased much further. Other solutes however likely contribute more than urea to the residual uremic illness suffered by hemodialysis patients. We here review methods which could be employed to increase the clearance of nonurea solutes. We will separately consider the clearances of free low-molecular-mass solutes, free larger solutes, and protein-bound solutes. New clinical studies will be required to test the extent to which increasing the clearance on nonurea solutes with these various characteristics can improve patients' health.
Shattering the Concept of EU Citizenship? The Potential Impact of Brexit and Potential Secession of Catalonia on EU Citizenship
Authors: Schewe Christoph
Published: May 2022

In 2020, Brexit dominated the political agenda of the EU for its considerable consequences. One important aspect, however, has surprisingly been neglected: the question what Brexit means to the concept of EU citizenship.

Apart from the specific relevance for citizens, the effects of Brexit on rights granted under EU citizenship are of importance for the abstract concept of EU citizenship. Differently from market freedoms – which are intrinsically linked to the market, where workers as economic actors may be constantly affected by the changing economic policies of their national States and of their trade partners – EU citizenship also has a unique political and ideological basis and hence partially follows different aims. Its concept fundamentally differs, as it is intended to establish a bond existing beyond the market and – by attributing to EU citizens a fundamental status – is directly addressed to citizens as citizens, not as economic actors. The perspective of a disorderly Brexit with the consequence of Article 50 (3) teu, that “[…] the Treaties cease to apply […]”, depriving EU/ UK citizens of all corresponding rights against their will, would mean a severe setback to this concept and thus expose it as a hollow ideology. This message, however, would not only concern citizens who lose these rights but would, moreover, affect the entire concept in the EU27.

While being raised in the context of Brexit, this aspect goes beyond, given that the same question is raised in the context of potential secessions from EU Member States and the fate of their citizens, for instance Catalunya where Catalan citizens might immediately be stripped of EU citizenship whether they would have opted for Catalan independence or not.
On some species of Omaliini McLeay, 1825 of Chile (Coleoptera: Staphylinidae: Omaliinae)
Authors: SHAVRIN ALEXEY V.
Published: May 2022

New taxonomic and faunisic data for five species of Omaliini McLeay, 1825 of Chile are provided. Two species are (re-) described: Omaliopsis russata (Fairmaire & Germain, 1861) and O. struyvei sp.n. (southern Chile). The genus Stenomalium Blackwelder, 1943, previously known from Australian and Oceanic regions, is recorded from South America for the first time: S. picipenne (Fauvel, 1867) comb. nov. (from Omalium Gravenhorst, 1802) and unnamed S. sp. A new faunistic material for Xenanthobium andicola (Fauvel, 1867) is given. The habitus of all species, and aedeagi and abdominal segments of three species (except Stenomalium) are provided.
A New Algorithm for Estimating Low Cloud-Base Height in Southwest China
Authors: Wang Rongjiang , Zhou Renjun , Yang Shuping , Li Rui , Pu Jiangping , Liu Kaiyu , Deng Yi
Published: May 2022

The prevalence of low clouds significantly affects flight safety in Southwest China. However, relevant cloud parameters, especially low cloud-base height (LCBH), lack accurate forecasts. Based on the hourly atmospheric vertical profiles of ERA5 from 2008 to 2019, we developed a new algorithm for estimating LCBH by combining relative humidity (RH) threshold methods with convective condensation level (CCL) (RHs-CCL). To evaluate the performance of RHs-CCL, we use it to estimate the hourly LCBH of airports in Southwest China and compare the results with those based on the ground-based observations and the ERA5 CBH data. Using the observations as a ground truth, we compare the RHs-CCL algorithm with several existing algorithms with the following findings: 1) The correlation coefficient between RHs-CCL and observations reaches 0.5 on average, and the error of RHs-CCL is smaller than those of existing algorithms, with the minimum mean absolute error and root-mean-square error at the four airports studies being able to reach 243 and 321 m. 2) The bias score of RHs-CCL is 0.97 on average, and low clouds classification utilizing RHs-CCL attains the highest accuracy, up to 86%. 3) The errors of ERA5 CBH are the largest when compared with the others. 4) By implementing convective cloud occurrence condition and CCL, RHs-CCL has better applicability in regions of enhanced convective activity. These results suggest the potential of RHs-CCL as an algorithm moving forward for improvement of the LCBH estimates based upon high-resolution reanalysis products and for better predictions of the LCBH utilizing outputs from numerical weather prediction models.

Significance Statement

The new algorithm developed in this study can accurately estimate low cloud-base heights from vertical profiles of atmospheric variables. It provides us a much more computationally efficient approach for predicting low cloud-base height relative to running cloud models, which is critical for weather forecasting at locations lacking computational resources and/or cloud modeling capability. In areas such as Southwest China, low clouds are very common, and they pose major threats to aviation safety. The new algorithm has been successfully integrated into the daily operation at Guiyang Airport in Southwest China and demonstrated excellent skills in estimating cloud-base heights. The implementation of the algorithm in aviation forecasting over a broader region is on the horizon.
Enhanced Interannual Variability in Temperature during the Last Glacial Maximum
Authors: Shi Jiawen , Jiang Dabang , Tian Zhiping , Lang Xianmei
Published: May 2022

Using all relevant climate experiments archived in phases 3 and 4 of the Paleoclimate Modeling Intercomparison Project (PMIP3/4), we examine the interannual variability change in global-scale surface air temperature and associated physical mechanisms during the Last Glacial Maximum (LGM). The results show that relative to the preindustrial period, the LGM interannual temperature variability increased by 20% globally, which was mainly attributed to the large-scale increase in the meridional temperature gradient, especially at midlatitudes. Larger magnitudes of change occurred in areas where the underlying surface properties, such as the surface altitude, land–sea distribution, and ice sheet extent, differed from those in the preindustrial period. In addition, the relationship between changes in the meridional temperature gradient and the interannual temperature variability became closer in the winter hemisphere. In the tropical land regions, changes in interannual temperature variability are mainly related to the adjustment of latent and sensible heat fluxes during the LGM.
Future Changes in African Heatwaves and Their Drivers at the Convective Scale
Authors: Birch C. E. , Jackson L. S. , Finney D. L. , Marsham J. M. , Stratton R. A. , Tucker S. , Chapman S. , Senior C. A. , Keane R. J. , Guichard F. , Kendon E. J.
Published: May 2022

The future change in dry and humid heatwaves is assessed in 10-yr pan-African convective-scale (4.5 km) and parameterized convection (25 km) climate model simulations. Compared to reanalysis, the convective-scale simulation is better able to represent humid heatwaves than the parameterized simulation. Model performance for dry heatwaves is much more similar. Both model configurations simulate large increases in the intensity, duration, and frequency of heatwaves by 2100 under RCP8.5. Present-day conditions that occur on 3–6 heatwave days per year will be normal by 2100, occurring on 150–180 days per year. The future change in dry heatwaves is similar in both climate model configurations, whereas the future change in humid heatwaves is 56% higher in intensity and 20% higher in frequency in the convective-scale model. Dry heatwaves are associated with low rainfall, reduced cloud, increased surface shortwave heating, and increased sensible heat flux. In contrast, humid heatwaves are predominately controlled by increased humidity, rainfall, cloud, longwave heating, and evaporation, with dry-bulb temperature gaining more significance in the most humid regions. Approximately one-third (32%) of humid heatwaves commence on wet days. Moist processes are known to be better represented in convective-scale models. Climate models with parameterized convection, such as those in CMIP, may underestimate the future change in humid heatwaves, which heightens the need for mitigation and adaptation strategies and indicates there may be less time available to implement them to avoid future catastrophic heat stress conditions than previously thought.

Significance Statement

Temperatures are higher in dry heatwaves, but humid heatwaves can be more dangerous, as the ability to cool by sweating is limited. We found that dry heatwaves are caused by decreased cloud, allowing the sun to heat the surface, whereas humid heatwaves are caused by increased cloud, rainfall, and evaporation from the surface. We found that a state-of-the-art very high-resolution climate model predicts a larger future change in humid heatwaves compared to a more traditional global climate model. Previous estimates of the prevalence of humid heatwaves in the future may therefore be underestimated. If we do not cut emissions of greenhouse gases, present-day African heatwave conditions could be experienced on up to half of all days of the year by 2100.
The Arctic Surface Heating Efficiency of Tropospheric Energy Flux Events
Authors: Cardinale Christopher J. , Rose Brian E. J.
Published: May 2022

This paper examines the processes that drive Arctic anomalous surface warming and sea ice loss during winter-season tropospheric energy flux events, synoptic periods of increased tropospheric energy flux convergence (Ftrop), using the NASA MERRA-2 reanalysis. During an event, a poleward anomaly in Ftrop initially increases the sensible and latent energy of the Arctic troposphere; as the warm and moist troposphere loses heat, the anomalous energy source is balanced by a flux upward across the tropopause and a downward net surface flux. A new metric for the Arctic surface heating efficiency (Etrop) is defined, which measures the fraction of the energy source that reaches the surface. Composites of high-, medium-, and low-efficiency events help identify key physical factors, including the vertical structure of Ftrop and Arctic surface preconditioning. In high-efficiency events (Etrop ≥ 0.63), a bottom-heavy poleward Ftrop occurs in the presence of an anomalously warm and unstratified Arctic—a consequence of decreased sea ice—resulting in increased vertical mixing, enhanced near-surface warming and moistening, and further sea ice loss. Smaller Etrop, and thus weaker surface impacts, are found in events with anomalously large initial sea ice extent and more vertically uniform Ftrop. These differences in Etrop are manifested primarily through turbulent heat fluxes rather than downward longwave radiation. The frequency of high-efficiency events has increased from the period 1980–99 to the period 2000–19, contributing to Arctic surface warming and sea ice decline.
Sea Surface Salinity Changes in Response to El Niño–like SST Warming and Relevant Ocean Dynamics in the Tropical Pacific under the CMIP6 Abrupt-4XCO2 Scenario
Authors: Sun Qiwei , Du Yan
Published: May 2022

Based on the abrupt-4XCO2 scenario in phase 6 of the Coupled Model Intercomparison Project (CMIP6), this study investigates the response of the rainfall changes to El Niño–like SST warming and the role of ocean dynamical processes in the salinity changes in the tropical Pacific. The results show that the Walker circulation weakening and eastward shift, related to El Niño–like SST warming, dominates the zonal precipitation change. Precipitation decreases (increases) in the Maritime Continent (the equatorial Pacific), partly offsetting the effect of specific humidity. At the same time, the El Niño–like warming triggers convergence of meridional winds, which leads to a precipitation increase in the equatorial Pacific and a decrease in the intertropical convergence zone and the South Pacific convergence zone, following the “warmer-get-wetter” mechanism. Unlike the spatial pattern of precipitation changes, the sea surface salinity changes become fresher in the tropical western Pacific, related to the precipitation and the mean horizontal advection. The precipitation increase leads to negative salinity anomalies in the equatorial central Pacific. The westward climatological zonal currents transport the negative salinity anomalies westward. The meridional currents advect the salinity anomalies to both sides of the equator, partly offsetting the contribution of the freshwater flux on the salinity change. In addition, shallower mixed layer depth and weakening upwelling bring less high-salinity water to the surface and impact salinity redistribution through the vertical process in the equatorial regions.
The moral foundations of restraint: Partisanship, military training, and norms of civilian protection
Authors: Bell Andrew M , Gift Thomas , Monten Jonathan
Published: May 2022

How does partisan identification shape the attitudes of US military officers toward the protection of civilians in war? Drawing on unique cross-cohort surveys of soon-to-be commissioned officers in 12 Army Reserve Officers’ Training Corps (ROTC) training battalions, we find that Democratic-leaning cadets generally prioritize norms of civilian protection more than Republican-leaning cadets when confronted with competing values of military advantage and force protection as part of a ‘combatant’s trilemma’. This gap remains partially resilient after sustained exposure to military training and socialization, including in the norms of restraint embodied by principles of combat ethics and the law of war. We attribute these partisan differences to insights from Moral Foundations Theory (MFT), which suggests that the moral values of Democrats and Republicans guide their views toward the individual use of force in combat. Our findings have important implications for comprehending the impact of political ideology and military training and socialization on attitudes regarding restraint toward civilians in war. Given the widely recognized conservative composition of the US military’s membership, these findings may help to further inform understanding of US military operations and the underlying causes of US adherence to – or violation of – the laws of armed conflict.
Linking mean level and variability in affect to changes in perceived regard: A dyadic longitudinal burst study of African American couples
Authors: Urganci Betul , Ong Anthony D. , Burrow Anthony L. , DeHart Tracy
Published: May 2022

High positive affect and low negative affect have been repeatedly tied to better individual and interpersonal well-being. However, research has focused on mean levels whereas the day-to-day unfolding of affect and its impact on romantic relationships remain largely understudied. Here, we examined the links between mean levels and variability in affect and changes in perceptions of partner regard —the extent to which people believe that their partners value and accept them. One hundred twenty-five African American couples ( N = 250 individuals) reported how positively they thought their partners viewed them across two sessions (T1 and T2), separated by a 3-week daily diary study in which participants reported on their positive and negative affect each day for 21 consecutive days. Using dyadic analysis, we found that higher actor negative affect variability was associated with lower perceived regard at T2 controlling for perceived regard at T1. This finding held when controlling for mean levels of actor and partner negative affect. By contrast, PA variability was curvilinearly associated with perceived regard, with moderate levels of variability associated with higher subsequent perceived regard. These results highlight the importance of accounting for mean levels and curvilinear effects when examining links between affect dynamics and relational well-being.
Effects of asymmetric stroke deviation on the aerodynamic performance of flapping wing
Authors: Hu Fujia , Wang Yuanying , Li Dian , Liu Xiaomin
Published: May 2022

The kinematics of insect flapping flight are complex and asymmetric, which are contributed to their superior flying capabilities, and the design of novel flapping micro air vehicles can draw inspiration from relevant researches. Previous studies usually focus on the wing with asymmetric stroke or pitch motions. A trajectory with asymmetric deviation motion, named as “pear-shaped” pattern, is proposed in current work. The hovering aerodynamics and vortex dynamics of a rigid flapping wing have been numerically investigated by comparing with that of “line-shaped” pattern with no deviation. In order to have a better insight into the influences of the asymmetric deviation, we change the kinematic parameters, that is, stroke amplitude, pitching amplitude, deviation amplitude, and phase lag between stroke and pitch angles. The results show that the wing with asymmetric deviation exhibits superior capability in lift enhancement for most of the cases analyzed, which is accompanied by the extra power cost and slight reduction in efficiency. The asymmetric deviation in cases with high stroke amplitude or low pitching amplitude may be considered as a cost-saving strategy, subject to slight damage on lift generation (if acceptable). Additionally, the asymmetric deviation brings a strong asymmetry into the instantaneous forces during one flapping cycle. The underlying lift-enhancing mechanism is explored by examining the dominant vortex structures in the adjacent flow field of the wing, which is mainly attributed to the changes in the effective angle of attack, increasing with downward deviation and decreasing with upward deviation.
Combined Use of Glucose-Specific Model Identification and Alarm Strategy Based on Prediction-Funnel to Improve Online Forecasting of Hypoglycemic Events
Authors: Faccioli Simone , Prendin Francesco , Facchinetti Andrea , Sparacino Giovanni , Del Favero Simone
Published: May 2022

Background:

Advanced decision support systems for type 1 diabetes (T1D) management often embed prediction modules, which allow T1D people to take preventive actions to avoid critical episodes like hypoglycemia. Real-time prediction of blood glucose (BG) concentration relies on a subject-specific model of glucose-insulin dynamics. Model parameter identification is usually based on the mean square error (MSE) cost function, and the model is usually used to predict BG at a single prediction horizon (PH). Finally, a hypo-alarm is raised if the predicted BG crosses a threshold. This work aims to show that real-time hypoglycemia forecasting can be improved by leveraging: a glucose-specific mean square error (gMSE) cost function in model’s parameters identification, and a “prediction-funnel,” that is, confidence intervals (CIs) for multiple PHs, within the hypo-alarm-raising strategy.

Methods:

Autoregressive integrated moving average with exogenous input (ARIMAX) models are selected to illustrate the proposed solution (use of gMSE and prediction-funnel) and its assessment against the conventional approach (MSE and single PH). The gMSE penalizes the model misfit in unsafe BG ranges (e.g., hypoglycemia), and the prediction-funnel allows raising an alarm by monitoring if the CIs cross a suitable threshold. The algorithms were evaluated by measuring precision ( P), recall ( R), F1-score ( F1), false positive per day (FP/day), and time gain (TG) on a real dataset collected in 11 T1D individuals.

Results:

The best performance is achieved exploiting both the gMSE and the prediction-funnel: P = 65%, R = 88%, F1 = 75%, FP/day = 0.29, and mean TG = 15 minutes.

Conclusions:

The combined use of a glucose-specific metric and an alarm-raising strategy based on the prediction-funnel allows achieving a more effective and reliable hypoglycemia prediction algorithm.