bluuebunny/crossref_metadata_2025 huggingface dataset:
Design of Coupling Coil Parameters for Wireless Charging Tram Based on Electromagnetic Safety
Authors: Xiu Sanmu , Hao Wenmei , Zhou Ying , Leng Fengyu
Published: May 2022

As a new type of urban rail transit tram, wireless charging tram uses high frequency electromagnetic field to conduct inductive power transmission, which gets rid of the traditional overhead catenary network, but inevitably causes electromagnetic radiation to the surrounding environment. Research shows that excessive electromagnetic radiation will affect the normal operation of equipment and the safety of human body. This paper analyzes the structure and coil configuration of the dynamic charging system for wireless charging tram. Aiming at the problem of electromagnetic radiation, a mathematical model with minimum electromagnetic radiation as the target and system parameters as the constraint condition is established. Finally, the system parameters of the electromagnetic coupling mechanism of the wireless charging tram are designed and optimized. The simulation and experimental results show that the method can meet the operating requirements of the system and reduce the electromagnetic radiation to the surrounding environment.
Research on the Reform of Higher Education Training Mode under the Background of Big Data and Internet of Things
Authors: Wang Jing
Published: May 2022

With the rapid development of information processing, storage, and transmission technologies, the demand for talents from all walks of life in the society has increased, which has put forward higher requirements for the diversity of Chinese higher education. In China’s higher education, undergraduate education is in a fundamental position. China’s undergraduate education has undergone several reforms in talent training, but there are still many problems in the innovative talent training model. With the gradual improvement of the Internet of Things infrastructure, various applications characterized by big data are deeply embedded in people’s daily life. In the era of big data, the amount of data is larger and the structure is more complex. It penetrates into all fields of human life and shows unprecedented vitality and vigor. Especially in the field of higher education, the era of big data provides more information resources for education and learning and also brings new opportunities for the cultivation of applied talents in local undergraduate colleges and universities. This paper deeply studies the training mode of applied talents in local undergraduate colleges and universities under the background of big data and the Internet of Things. Based on the data analysis results of big data application technicians and industry talents, professional ability-course structure data, this paper completes the design of the corresponding talent training mode analysis system. Under the application of the system designed in this paper, it is possible to realize the analysis of the differences in the knowledge structure requirements of talents in various positions and the needs of talents’ ability, as well as the optimization and reform of the talent training curriculum system. The design of this paper can play an important guiding role in talent training in the environment of big data and Internet of Things.
Deep Neural Network-Based Intrusion Detection System through PCA
Authors: Alotaibi Shoayee Dlaim , Yadav Kusum , Aledaily Arwa N. , Alkwai Lulwah M , Yousef Dafhalla Alaa Kamal , Almansour Shahad , Lingamuthu Velmurugan
Published: May 2022

Today, challenges such as a high false-positive rate, a low detection rate, a slow processing speed, and a big feature dimension are all part of intrusion detection. To address these issues, decision trees (DTs), deep neural networks (DNNs), and principal component analysis (PCA) are available. Through a higher detection rate and a lower false-positive rate, the research-based intrusion detection model DT-PCA-DNN increases the processing speed of intrusion detection systems (IDSs). To minimize the overall data volume and accelerate processing, DT is used to initially differentiate the data. Differentiate DTs save the temporary training sample set for intrusion data in order to retrain and optimize the DT and DNN, treat the DT judges as standard data, and delete the added average data. After signing, we should lower the dimension of the data using PCA and then submit the data to DNN for secondary discrimination. However, DT employs a shallow structure in order to prevent an excessive quantity of average numbers from being interpreted as intrusion data. As a result, additional DNN secondary processing cannot effectively increase the accuracy. DNN accelerates data processing by utilizing the ReLU activation function from the simplified neural network calculation approach and the faster convergence ADAM optimization algorithm. Class two and five trials on the NSL-KDD dataset demonstrate that the proposed model is capable of achieving high detection accuracy when compared to other deep learning-based intrusion detection approaches. Simultaneously, it has a faster detection rate, which effectively solves the real-time intrusion detection problem.
Research on Urban Intelligent Medical Service System Design Based on Multiobjective Decision-Making Optimization Strategy
Authors: Huang Yulei
Published: May 2022

Aiming at the problems of difficult medical treatment for urban residents, low efficiency of hospitals, imbalance of medical resources and difficulty to meet the demands of patients, this paper proposes an urban intelligent medical service system based on multiobjective decision-making optimization strategy. Firstly, it analyzes the medical service demands of urban residents and points out that the urban intelligent medical service system should provide comprehensive services for residents; the main demands include basic medical demands, expected medical demands, and health care medical demands. Secondly, based on demand analysis, an urban intelligent medical service system composed of government, community hospital, large hospital, and urban residents is designed. The system has three kinds of system functions: customer business services, basic services, and institutional information services. Then, the overall process of the system before and after treatment of urban residents is introduced. Finally, according to the optimization objectives of the system: low medical cost, fast treatment speed, and high service satisfaction, the corresponding optimization strategies are formulated to optimize the urban intelligent medical system, reduce medical cost, improve treatment speed, and improve customer satisfaction, to better serve urban residents.
The Intestinal Redox System and Its Significance in Chemotherapy-Induced Intestinal Mucositis
Authors: Yu Qing-Qing , Zhang Heng , Guo Yujin , Han Baoqin , Jiang Pei
Published: May 2022

Chemotherapy-induced intestinal mucositis (CIM) is a significant dose-limiting adverse reaction brought on by the cancer treatment. Multiple studies reported that reactive oxygen species (ROS) is rapidly produced during the initial stages of chemotherapy, when the drugs elicit direct damage to intestinal mucosal cells, which, in turn, results in necrosis, mitochondrial dysfunction, and ROS production. However, the mechanism behind the intestinal redox system-based induction of intestinal mucosal injury and necrosis of CIM is still undetermined. In this article, we summarized relevant information regarding the intestinal redox system, including the composition and regulation of redox enzymes, ROS generation, and its regulation in the intestine. We innovatively proposed the intestinal redox “Tai Chi” theory and revealed its significance in the pathogenesis of CIM. We also conducted an extensive review of the English language-based literatures involving oxidative stress (OS) and its involvement in the pathological mechanisms of CIM. From the date of inception till July 31, 2021, 51 related articles were selected. Based on our analysis of these articles, only five chemotherapeutic drugs, namely, MTX, 5-FU, cisplatin, CPT-11, and oxaliplatin were shown to trigger the ROS-based pathological mechanisms of CIM. We also discussed the redox system-mediated modulation of CIM pathogenesis via elaboration of the relationship between chemotherapeutic drugs and the redox system. It is our belief that this overview of the intestinal redox system and its role in CIM pathogenesis will greatly enhance research direction and improve CIM management in the future.
Cross-Cultural Learning: A Visualized Bibliometric Analysis Based on Bibliometrix from 2002 to 2021
Authors: Wang Jing , Zhang Sihong
Published: May 2022

With the significant increase of studies on cross-cultural learning (CCL) in the recent two decades, it is essential to conduct a systematic review of various literature and their development processes. This article is aimed at revealing research hotspots and emerging trends in CCL studies. This study adapted a visualized bibliometric approach to analyze research articles in the Cross-Cultural Learning-Internet of Things area. We extracted papers published in respected journals as the dataset. Based on bibliometrix, this study collects 1,899 records indexed in the Core Collection of Web of Science (WoS) in the domain of CCL from 2002 to 2021. The findings indicate that the number of published articles shows an apparently upward trend; the United States occupies the leading position, while the most productive journal is Computers & Education; King from Nanyang Technological University of Singapore is the most prolific author, and Nielsen ranks the first in terms of citation; cross-cultural, culture, learning, cross-cultural comparison, and cross-cultural research are found to be the most high-frequency keywords used by authors; cross-cultural projects, students and teachers, cross-cultural research, and educational technologies are the most discussed topics in this field; several notable topics related to CCL and Internet of Things. Visualization study is beneficial to track the hotspots and frontiers of CCL studies in order to effectively grasp the breakthrough points for future research. The results provide helpful information for newcomers, researchers, scholars, and practitioners to identify knowledge gaps, point out future research directions, and move this field forward.
Laboratory-Scale Insight into Fractal Dimension Indicators for Seismic Hazard Assessment Associated with Rock Failures
Authors: Cai Wu
Published: May 2022

Investigation of acoustic emission (AE) characteristics during laboratory tests of coal samples can provide useful guidance on the recognition of microseismicity (MS) precursors for seismic hazards in underground coal mining. In this study, a methodology, involving fractal dimension indices and a fuzzy comprehensive evaluation model, was developed and demonstrated using AE monitoring data in a uniaxial loading test of coal samples, which allows for a better and quantitative recognition of AE/MS precursors to seismic hazards associated with rock failures. In this methodology, the fractal dimension indices include six information dimension indices as well as three previously used capacity dimension indices. The assessment results were initially characterised as probabilities belonging to each of four risk levels (none, weak, moderate, and strong), and then output as a comprehensive result corresponding to one of these four risk levels. The results indicated that this developed methodology was able to recognise the AE precursors for rock failures.
Point Cloud Data Hole Repair Aggregation Algorithm Based on Optimized Neural Network
Authors: Fu Siyong
Published: May 2022

In order to solve the problem of cost cloud data and hole repair efficiency and accuracy, this article offers a study of integrated cloud network hole algorithm research based on optimal neural network. This paper first introduces a common point cloud hole-filling algorithm, provides a neural network-based point cloud blank filling algorithm, and introduces hotspot problems in a given algorithm, combined with the technology related to high-performance computing, the parallel optimization technology based on OpenMP and CUDA is adopted to accelerate the algorithm accordingly. Experiments have shown that the accuracy of pre- and postoptimization of CUDA-based algorithms varies. As the model and input point cloud data increase, the accuracy of the algorithm decreases slightly. However, when the data increases to 104 orders of magnitude, the rate of accuracy decline meets an inflection point and finally stabilizes to about 96.8% in the environment of 132457 data of monk model. The point cloud hole-filling algorithm based on the optimal neural network given in this article is highly predictable, can well repair incomplete point cloud holes, has good repair effect on point cloud holes, and can obtain high acceleration ratio, which can provide reference for practical engineering application.
[Retracted] Novel Concepts in Bipolar Fuzzy Graphs with Applications
Authors: Wan Chang , Deng Fei , Li Shitao , Omidbakhsh Amiri S. , Talebi A. A. , Rashmanlou H.
Published: May 2022

Many problems of practical interest can be modeled and solved by using bipolar graph algorithms. Bipolar fuzzy graph (BFG), belonging to fuzzy graphs (FGs) family, has good capabilities when facing with problems that cannot be expressed by FGs. Hence, in this paper, we introduce the notion of (ϑ, δ)−homomorphism of BFGs and classify homomorphisms (HMs), weak isomorphisms (WIs), and co‐weak isomorphisms (CWIs) of BFGs by (ϑ, δ)−HMs. Also, an application of homomorphism of BFGs has been presented by using coloring‐FG. Universities are very important organizations whose existence is directly related to the general health of the society. Since the management in each department of the university is very important, therefore, we have tried to determine the most effective person in a university based on the performance of its staff.
Study on the Heterogeneity of Social Security Affecting the Sense of Security of Urban and Rural Residents
Authors: Liu Yuanfeng , Luo Shujiao
Published: May 2022

Social security is an important part of the national security system from the perspective of the overall security concept, and social security is an important influencing factor of social security. Using the CFPS2018 data, this study uses the critical weight method to measure residents’ individual security and uses path analysis to empirically study the impact of endowment insurance and medical insurance on residents’ security in urban and rural areas. The results show that the depth of endowment insurance has a significant positive impact on the sense of security of urban residents. The depth of meniscal insurance has no impact on the sense of security of urban residents. The depth of endowment insurance and medical insurance has a significant positive impact on the sense of security of rural residents. The depth of endowment insurance has a significant positive impact on the sense of security of urban residents. The influence of full sense is greater than that in rural areas, and the influence of meniscal insurance coverage depth on residents’ sense of security in rural areas is greater than that in urban areas. Therefore, the impact of social security on residents’ sense of security is heterogeneous between urban and rural areas. We should allocate the limited social security investment to urban and rural areas in a reasonable and balanced way to promote the overall sense of security of social residents. Integrate and improve the social security system and promote regional and group equity. Change the concept of government management, build a communication platform between the government and the people, and improve residents’ subjective sense of security. We should continue to expand the coverage of the system, promote the coverage of basic social security projects, and improve the ability of urban and rural residents to cope with risks.
Effect of Alteplase Thrombolysis on Coagulation Function and Nerve Function of Patients with Ischemic Stroke
Authors: Zhao Hong-Ying , Yang Guo-Tao , Zhang Hui-Fang , Wang Wen-Hao
Published: May 2022

Objective. To investigate the effects of alteplase thrombolysis on coagulation function and nerve function of patients with ischemic stroke. Methods. 76 cases with ischemic stroke receiving thrombolytic therapy in Cangzhou Central Hospital from November 2018 to November 2019 were recruited. They were assigned via the random number table method at a ratio of 1 : 1 to receive alteplase thrombolysis either within 3h after the onset (observation group) or within 3–4.5 h after the onset (control group), followed by aspirin administration after no bleeding in cranial computed tomography (CT). Outcome measures included plasma fibrinogen (FIB), activated partial prothrombin time (APTT), platelet (PLT) levels, the National Institute of Health stroke scale (NIHSS) score, and adverse events. Results. Alteplase thrombolysis within 3 h was associated with better prothrombin time (PT), APTT, FIB, and PLT levels versus thrombolysis within 3–4.5 h (

P
<
0.05

). Thrombolysis within 3 h showed significantly lower NIHSS scores versus within 3–4.5 h (

P
<
0.05

). The two groups showed a similar incidence of adverse events (X2 = 2.963,

P
=
0.615

). Conclusion. Alteplase thrombolysis showed benefits in mitigating the coagulation function and nerve function damage of patients with ischemic stroke, especially within 3 hours after the onset, with a high safety profile.
New Method of Sensitivity Computation Based on Markov Models with Its Application for Risk Management
Authors: Gu Zheng , Liu Yue , Yang Aijun , Li Kaodui
Published: May 2022

Sensitivity analysis is at the core of risk management for financial engineering; to calculate the sensitivity with respect to parameters in models with probability expectation, the most traditional approach applies the finite difference method, whereafter integration by parts formula was developed based on the Brownian environment and applied in sensitivity analysis for better computational efficiency than that of finite difference. Establishing a similar version of integration by parts formula for the Markovian environment is the main focus and contribution of this paper. It is also shown by numerical simulation that our proposed methodology and approach outperform the traditional finite difference method for sensitivity computation. For empirical studies of sensitivity analysis on an NPV (net present value) model, we show the approaches of modeling, especially for parameter estimation of Markov chains given data of company loan states. Applying our newly established integration by parts formula, numerical simulation estimates the variations caused by the capital return rate and multiplier of overdue loan. Furthermore, managemental implications of these results are discussed for the effectiveness of modeling and the investment risk control.
Informatization of National Public Service Fitness in Constructing a Smart City Using Big Data
Authors: Dong Xinjun , Yi Feng , Wang Zhenzhong
Published: May 2022

The public service system of national fitness is the condition and guarantee for the public to participate in various fitness activities. In order to effectively integrate the existing national fitness service resources and to improve the efficiency of the public service supply, this paper aims to study the informatization of building national fitness public services in smart city under the background of big data. Firstly, we build a public service information platform of national fitness in the smart city, consisting of different modules, and then describe each module in detail. Secondly, we consider different types of fitness projects and establish the database structure model of network resources. Thirdly, we obtain the multitree cascade system of the national fitness and the heterogeneous data model of the national fitness benefit index by using high-dimensional statistical analysis method. Combined with the national fitness behavior, data mining, and support vector machine (SVM), the objective function of data mining statistical decision-making is established. Finally, the well-known particle swarm optimization (PSO) method is used to optimize the target parameters so as to realize the national fitness, big data mining, and feature analysis. The simulation results show that the proposed model has superior performance, as it can realize heterogeneous data mining of the national fitness benefit index. In addition, we quantitatively analyze the promoting effect of the national fitness on the physical quality and health level of the public.
Association between Vitamin D Status and Mortality among Adults with Diabetic Kidney Disease
Authors: Xu Feng , Lu Hongyu , Lai Tianwen , Lin Ling , Chen Yongsong
Published: May 2022

Objective. Emerging evidence demonstrates that vitamin D status contributes to the incidence of diabetic kidney disease (DKD). However, the causal relationships between vitamin D and mortality among individuals with DKD are inconclusive. Our study is aimed at exploring the relationship between serum 25-hydroxyvitamin D (25(OH)D) concentrations and mortality among adults with DKD. Research Design and Methods. Our study included 1,202 adult participants with DKD from the National Health and Nutrition Examination Survey (NHANES) 2001–2014. Cox and competing-risks regression were used to estimate hazard ratios (HRs) and 95% CIs for associations between 25(OH)D concentrations and survival. Results. The overall mean serum 25(OH)D concentration was

55.9
±
26.3

. Vitamin D deficiency (

25

OH

D
<
50
 
nmol
/
l

), insufficiency group (

50
≤
25

OH

D
<
75
 
nmol
/
l

), and sufficiency group (

25

OH

D
≥
75
 
nmol
/
l

) were observed in 552 (45.9%), 409 (34.0%), and 241 (20.0%) participants, respectively. Higher levels of vitamin D were significantly associated with improved all-cause and nonaccident- and malignant neoplasm-cause mortality among individuals with DKD after adjusting for the potential confounding factors. Conclusions. We observed widespread vitamin D deficiency or insufficiency in DKD patients. Higher 25(OH)D values were significantly correlated with lower risk of mortality after adjusting for confounding variables.
Poor Performer: A Distinct Entity in Cochlear Implant Users?
Authors: Völter Christiane , Oberländer Kirsten , Haubitz Imme , Carroll Rebecca , Dazert Stefan , Thomas Jan Peter
Published: May 2022

Introduction: Several factors are known to influence speech perception in cochlear implant (CI) users. To date, the underlying mechanisms have not yet been fully clarified. Although many CI users achieve a high level of speech perception, a small percentage of patients does not or only slightly benefit from the CI (poor performer, PP). In a previous study, PP showed significantly poorer results on nonauditory-based cognitive and linguistic tests than CI users with a very high level of speech understanding (star performer, SP). We now investigate if PP also differs from the CI user with an average performance (average performer, AP) in cognitive and linguistic performance. Methods: Seventeen adult postlingually deafened CI users with speech perception scores in quiet of 55 (9.32) % (AP) on the German Freiburg monosyllabic speech test at 65 dB underwent neurocognitive (attention, working memory, short- and long-term memory, verbal fluency, inhibition) and linguistic testing (word retrieval, lexical decision, phonological input lexicon). The results were compared to the performance of 15 PP (speech perception score of 15 [11.80] %) and 19 SP (speech perception score of 80 [4.85] %). For statistical analysis, U-Test and discrimination analysis have been done. Results: Significant differences between PP and AP were observed on linguistic tests, in Rapid Automatized Naming (RAN: p = 0.0026), lexical decision (LexDec: p = 0.026), phonological input lexicon (LEMO: p = 0.0085), and understanding of incomplete words (TRT: p = 0.0024). AP also had significantly better neurocognitive results than PP in the domains of attention (M3: p = 0.009) and working memory (OSPAN: p = 0.041; RST: p = 0.015) but not in delayed recall (delayed recall: p = 0.22), verbal fluency (verbal fluency: p = 0.084), and inhibition (Flanker: p = 0.35). In contrast, no differences were found hereby between AP and SP. Based on the TRT and the RAN, AP and PP could be separated in 100%. Discussion: The results indicate that PP constitute a distinct entity of CI users that differs even in nonauditory abilities from CI users with an average speech perception, especially with regard to rapid word retrieval either due to reduced phonological abilities or limited storage. Further studies should investigate if improved word retrieval by increased phonological and semantic training results in better speech perception in these CI users.
Autoimmune Haemolytic Anaemia Due to Cold Antibodies in a Renal Cancer Patient
Authors: Terán Brage Eduardo , Fonseca Santos Marta , Lozano Mejorada Rebeca , García Domínguez Rocío , Olivares Hernández Alejandro , Amores Martín Arantzazu , Vidal Tocino Rosario , Fonseca Sánchez Emilio
Published: May 2022

Autoimmune haemolytic anaemia (AIHA) is an acquired disorder in which antibodies are produced against self-erythrocyte antigens. We distinguish those produced by cold antibodies (IgM), which may be associated with lymphoproliferative syndromes, infectious diseases, other autoimmune phenomena, as well as drugs or solid tumours. We report a case of AIHA due to cold antibodies as a paraneoplastic syndrome (PNS) in a patient with metastatic renal carcinoma. A 67-year-old man with newly diagnosed stage IV renal carcinoma with hepatic, bone, and lymph node involvement was consulted for abdominal pain. Laboratory tests showed grade 4 anaemia (4.5 g/dL), with positive direct Coombs’ test C3bC3d and agglutinated red blood cells in the blood smear. AIHA by cold antibodies was labelled as PNS in the context of the patient; therefore, blood transfusion as well as treatment of the underlying disease with tyrosine kinase inhibitors (sunitinib) were initiated, with subsequent clinical and analytical improvement. AIHA due to cold antibodies is a well-known PNS in lymphoproliferative disorders, although association with solid tumours, such as Kaposi’s sarcoma and non-small-cell lung cancer have also been described in a small percentage. However, there are few reported cases of AIHA due to cold antibodies associated with renal carcinoma. Management with corticosteroids and immunosuppressors is effective in the majority of cases, but treatment of the underlying disease is critical.
Patients with Type 2 Diabetes Mellitus Accompanied by Elevated Serum CA19-9 Associated Not with Pancreatic Cancer but Interstitial Lung Disease
Authors: Okada Shuichi , Okada Junichi , Kikkawa Koji , Yamada Eijiro , Okada Kazuya , Ohshima Kihachi
Published: May 2022

Introduction: CA19-9 is the most reliable tumor marker for pancreatic cancer, with 70–90% sensitivity, 90% specificity, 69% positive predictive value, and 90% negative predictive value. However, increased CA19-9 levels have been observed in benign conditions, pancreatitis, pulmonary disease, smoking, and hepatobiliary system disease. Numerous studies have reported that circulating CA19-9 levels are elevated during hyperglycemia in diabetes mellitus (DM) and have been associated with hemoglobin A1c (HbA1c). However, the precise mechanism behind increased serum CA19-9 levels in diabetes remains still unclear. Here, we report a case of type 2 DM (T2DM) accompanied by elevated serum CA19-9 levels due to not pancreatic cancer but interstitial pneumonitis. Case Report: The patient, a 73-year-old Japanese woman, was taking metformin (1,500 mg/day), repaglinide (1.5 mg/day), and sitagliptin (50 mg/day). Over the past year, she also took atorvastatin (5 mg/day) and azilsartan (40 mg/day). The patient had been followed up for systemic scleroderma (with low-dose steroid therapy) and mild interstitial lung disease (ILD) (without treatment) for a number of years at a different hospital. The patient’s peripheral blood laboratory findings were normal range. Her HbA1c level fluctuated between 7.0% and 8.0% in the past 6 months. Her CA19-9 level was fluctuated between 562.7 and 823.2 U/mL (normal <37), and her KL-6 level was fluctuated between 516 and 557 U/L (normal <500) in the past 6 months. Due to the marked increase in the CA19-9 level, an extensive screening examination was performed for malignancy, including abdominal ultrasound scan, computed tomography (CT), and magnetic resonance cholangiopancreatography, revealing no malignancy. We observed bilateral pulmonary lesions (bottom of lungs) and ground-glass opacity on the chest CT. The pancreatic monoclonal antigen type 2 (DU-PAN-2) level was <25 U/mL. Conclusions: In our case, CA19-9 levels were increased in association not with pancreatic cancer but with ILD. Thus, when T2DM is accompanied by elevated serum CA19-9 levels, attention needs to be paid not only to the presence of pancreatic cancer but also to the possible ILD. Especially, when diabetes and ILD are treated in different hospitals, diabetologists need to pay attention about the presence of hidden ILD besides DM.
Radical Antegrade Modular Pancreatosplenectomy for Left-Sided Pancreatic Ductal Adenocarcinoma May Reduce the Local Recurrence Rate
Authors: Kiritani Sho , Kaneko Junichi , Arita Junichi , Ishizawa Takeaki , Akamatsu Nobuhisa , Hasegawa Kiyoshi
Published: May 2022

Introduction: Although several clinical applications have reported the usefulness of the radical antegrade modular pancreatosplenectomy (RAMPS) procedure for left-sided pancreatic ductal adenocarcinoma, few studies have reported the advantages of RAMPS with respect to the local recurrence (LR) rate. Methods: As of 2018, 68 and 62 patients underwent RAMPS and standard retrograde pancreatosplenectomy (SRPS). The first recurrence and all subsequent recurrence sites observed on images during a follow-up period and/or chemotherapy. The clinical variables are collected retrospectively. Results: LR only was found in 5 patients in the RAMPS group (5/68, 7.3%) and in 15 patients in the SRPS group (15/62, 24.2%; p = 0.008) as the first recurrence site. Any chemotherapies were not a risk factor for the incidence of LR. The 5-year cumulative LR rate was significantly lower in patients in the RAMPS group compared with those in the SRPS group (23.6% vs. 49.6%; p = 0.019). The 5-year overall survival was 42.2% in the RAMPS group and 33.0% in the SRPS group (p = 0.251). Conclusion: The RAMPS procedure for left-sided pancreatic ductal adenocarcinoma may reduce the LR, cumulative LR rates.
Rethinking Sri Lanka's Industrialization Strategy:  Achievements,  Lost Opportunities and Prospects
Authors: Athukorala Prema-chandra
Published: May 2022

The purpose of this paper is to contribute to the contemporary policy debate on the industrialization strategy in developing countries by analyzing policy regime shifts and outcomes in Sri Lanka during the post-independence era. The analysis is guided by the received body of knowledge relating to the challenges faced by a small economy that takes world prices as given and is unable to affect world demand and supply in designing national industrialization strategy in this era of economic globalization. The findings demonstrate that the backlash against liberalization reforms in the contemporary Sri Lankan policy debate is largely based on ideological predilections rather than factual analysis. The comparative analysis of Sri Lanka's industrialization experience during the state-led import-substitution era and that of the post-reform era (in particular during the first two decades) makes a strong case for reconsidering the merit of the emerging emphasis on combining import substitution with export orientation with a sector specific focus. Selective policies to promote import substitution essentially impose a “tax” on export producers.
Advancements in Algorithms and Neuromorphic Hardware for Spiking Neural Networks
Authors: Javanshir Amirhossein , Nguyen Thanh Thi , Mahmud M. A. Parvez , Kouzani Abbas Z.
Published: May 2022

Artificial neural networks (ANNs) have experienced a rapid advancement for their success in various application domains, including autonomous driving and drone vision. Researchers have been improving the performance efficiency and computational requirement of ANNs inspired by the mechanisms of the biological brain. Spiking neural networks (SNNs) provide a power-efficient and brain-inspired computing paradigm for machine learning applications. However, evaluating large-scale SNNs on classical von Neumann architectures (central processing units/graphics processing units) demands a high amount of power and time. Therefore, hardware designers have developed neuromorphic platforms to execute SNNs in and approach that combines fast processing and low power consumption. Recently, field-programmable gate arrays (FPGAs) have been considered promising candidates for implementing neuromorphic solutions due to their varied advantages, such as higher flexibility, shorter design, and excellent stability. This review aims to describe recent advances in SNNs and the neuromorphic hardware platforms (digital, analog, hybrid, and FPGA based) suitable for their implementation. We present that biological background of SNN learning, such as neuron models and information encoding techniques, followed by a categorization of SNN training. In addition, we describe state-of-the-art SNN simulators. Furthermore, we review and present FPGA-based hardware implementation of SNNs. Finally, we discuss some future directions for research in this field.
Do Congruent Auditory Stimuli Facilitate Visual Search in Dynamic Environments? An Experimental Study Based on Multisensory Interaction
Authors: Sun Xiaofang , Chen Pin-Hsuan , Rau Pei-Luen Patrick
Published: May 2022

The purpose of this study was to investigate the cue congruency effect of auditory stimuli during visual search in dynamic environments. Twenty-eight participants were recruited to conduct a visual search experiment. The experiment applied auditory stimuli to understand whether they could facilitate visual search in different types of background. Additionally, target location and target orientation were manipulated to clarify their influences on visual search. Target location was related to horizontal visual search and target orientation was associated with visual search for an inverted target. The results regarding dynamic backgrounds reported that target-congruent auditory stimuli could speed up the visual search time. In addition, the cue congruency effect of auditory stimuli was critical for the center of the visual display but declined for the edge, indicating the inhibition of horizontal visual search behavior. Moreover, few improvements accompanying auditory stimuli were provided for the visual detection of non-inverted and inverted targets. The findings of this study suggested developing multisensory interaction with head-mounted displays, such as augmented reality glasses, in real life.
Synopsis of the wasp genus Clystopsenella Kieffer (Hymenoptera: Scolebythidae)
Authors: LEPECO ANDERSON , MELO GABRIEL A. R.
Published: May 2022

Scolebythidae are ectoparasitoid wasps which develop gregariously as idiobionts on wood-boring beetle larvae. Among them, the genus Clystopsenella is restricted to the Neotropical region and the eastern coast of Australia. The genus also includes a fossil species, †Clystopsenella mirabilis Engel, 2015, from Miocene Dominican amber. In the present study we review the genus Clystopsenella and describe a new species from Costa Rica, Clystopsenella pacifica sp. nov. A key to the extant and extinct species is provided. The type locality of Clystopsenella longiventris Kieffer, 1911 is reinterpreted based on the original labels. The distribution of the genus is mostly confined to woodlands under tropical and subtropical climates. The biology of scolebythids is discussed based on a new host record for C. longiventris.
Toward Better and Healthier Air Quality: Implementation of WHO 2021 Global Air Quality Guidelines in Asia
Authors: Ouyang Huiling , Tang Xu , Kumar Rajesh , Zhang Renhe , Brasseur Guy , Churchill Ben , Alam Mozaharul , Kan Haidong , Liao Hong , Zhu Tong , Chan Emily Ying Yang , Sokhi Ranjeet , Yuan Jiacan , Baklanov Alexander , Chen Jianmin , Patdu Maria Katherina
Published: May 2022

Air pollution is estimated to contribute to approximately 7 million premature deaths, of which around 4.5 million deaths are linked to ambient (outdoor) air pollution. The deaths attributed to air pollution rank the highest in the Asian region, and thus, the implementation of the stricter World Health Organization (WHO) Global Air Quality Guidelines (AQGs) released on 22 September 2021 will generate the greatest health benefits in the Asian region. Here we present some key messages and recommendations at national, regional, and global levels to promote the strategies for implementation of the ambitious WHO 2021 AQGs in the Asian region.
Empirical Evidence for the Frontal Modification of Atmospheric Boundary Layer Depth Variability over Land
Authors: Clark Nicholas E. , Pal Sandip , Lee Temple R.
Published: May 2022

Despite many observational studies on the atmospheric boundary layer (ABL) depth zi variability across various time scales (e.g., diurnal, seasonal, annual, and decadal), zi variability before, during, and after frontal passages over land, or simply zi variability as a function of weather patterns, has remained relatively unexplored. In this study, we provide an empirical framework using 5 years (2014–18) of daytime rawinsonde observations and surface analyses over 18 central and southeastern U.S. sites to report zi variability across frontal boundaries. By providing systematic observations of front-relative contrasts in zi (i.e., zi differences between warm and cold sectors, ) and boundary layer moisture (i.e., ABL-q) regimes in summer and winter, we propose a new paradigm to study zi changes across cold-frontal boundaries. For most cases, we found deeper zi over the warm sector than the cold sector in both summer and winter, although with significant site-to-site variability in Δzi. Additionally, our results show a positive ΔqABL (i.e., frontal contrasts in ABL-q) in summer and winter, supporting what is typically observed in midlatitude cyclones. We found that a front-relative ΔqABL of 1 g kg−1 often yielded at least a 100-m Δzi across the frontal boundary in both summer and winter. This work provides a synoptic-scale basis for zi variability and establishes a foundation for model verification to examine the impact of airmass exchange associated with advection on zi. This work will advance our understanding of ABL processes in synoptic environments and help unravel sources of front-relative zi variability.

Significance Statement

The atmospheric boundary layer (ABL) is the lowermost part of the atmosphere adjacent to Earth’s surface. The irregular motion of air inside the ABL plays an essential role in relocating air near the surface to the free troposphere. Meteorologists use ABL depth in weather forecast models to determine the atmosphere’s ability to dilute or enrich tracers within the ABL. However, knowledge about the changes in ABL depth during stormy conditions remains incomplete. Here, we investigate how the ABL depth varies before and after cold-frontal passages. We found that ABL depths were much deeper before the cold-frontal passages than after. This knowledge will help us develop new approaches to consider how storms modify the ABL in weather forecast models.
Insured Corn Losses in the United States from Weather and Climate Perils
Authors: Bundy Logan R. , Gensini Vittorio A. , Russo Mark S.
Published: May 2022

This study used corn insurance data as a proxy for agricultural loss to better inform producers and decision-makers about resilience and mitigation. Building on previous research examining crop losses based on weather and climate perils, updates to the peril climatology, identification of peril hotspots, and the quantification of annual trends using inflation-adjusted indemnities for corn were performed over the period 1989–2020. Normalization techniques in loss cost and acreage loss at county-level spatial resolution were also calculated. Indemnity data showed drought and excess moisture as the two costliest and most frequent perils for corn in the United States, although changes in the socioeconomic landscape and frequency of extreme weather events in the recent decade have led to significant increases in corn indemnities for drought, heat, excess moisture, flood, hail, excess wind, and cold wet weather. Normalized losses also displayed significant trends but were dependent on the cause of loss and amount of spatial aggregation. Perhaps most notable were the documented robust increases in corn losses associated with excess moisture, especially considering future projections for increased mid and end-of-century extreme precipitation. Subtle decreasing trends in drought, hail, freeze/frost, and flood loss cost over the study period indicates hedging taking place to protect against these perils, especially in corn acreage outside the Corn Belt in high-risk production zones. The use of crop insurance as a proxy for agricultural loss highlights the importance for quantifying spatiotemporal trends by informing targeted adaption to certain hazards and operational management decisions.

Significance Statement

This study quantified the climatology and trends of weather and climate perils affecting corn in the United States. Robust increases in losses were noted with perils causing excess moisture, which is cause for further concern given projected increases in extreme rainfall under a warming climate.
A Conceptual Synoptic Model Approach to the Development of a Precipitation Climatology as Applied to Montreal, Quebec
Authors: Melamed-Turkish Kai , Milrad Shawn , Gyakum John , Atallah Eyad
Published: May 2022

This study documents the frequency and intensity of precipitation at Montreal, Canada, from 1979 to 2018 as it relates to four quadrants of a 500-hPa wave, identified by the position of troughs, ridges, and inflection points. These quadrants provide a simplified conceptualization of the contributions from the temperature and vorticity advection forcing terms in the quasigeostrophic (QG) omega equation. Precipitation is found to be significantly more intense in every season except summer in the quadrant immediately upstream of the 500-hPa ridge, where differential cyclonic vorticity advection (DCVA) and a local maximum in horizontal warm-air advection (WAA) tend to promote unambiguous QG ascent. In summer, the average precipitation is still most intense in the DCVA-WAA quadrant, but not significantly more than in the quadrant immediately downstream of the 500-hPa trough, where DCVA and a local maximum in horizontal cold-air advection (CAA) are expected to compete, resulting in ambiguous QG vertical motion. Precipitation in the DCVA-CAA quadrant is more intense in every season than in the expected differential anticyclonic vorticity advection (DAVA) quadrants, with significantly higher intensities in spring and fall. Furthermore, the DCVA quadrants exhibit significantly stronger ascent compared to the DAVA quadrants and the DCVA-WAA quadrant features significantly warmer 850-hPa equivalent potential temperatures compared to the three other quadrants in every season. Odds ratios indicate a statistically significant association between heavy precipitation episodes and the DCVA-WAA quadrant. Heavy precipitation episodes in the DCVA-CAA quadrant are associated with a negatively tilted 500-hPa geopotential height pattern in winter and fall.

Significance Statement

Operational weather forecasters apply conceptual models that connect upper-atmospheric weather patterns to vertical motion and precipitation. However, few studies have quantified this connection over a longer, continuous period of time. In this study, we examine the relationship between historical subdaily precipitation at Montreal, Canada, and a simple large-scale conceptual model that relates vertical motion to the position of upper-level troughs and ridges. We find significant evidence for heavy precipitation to occur upstream of the upper-level ridge, and for very little, or very light, precipitation to occur upstream of the upper-level trough. These results provide quantitative support to some of the conceptual methods available to operational weather forecasters in preliminary analyses that support their precipitation forecasts.
Self-Perceived ADL/IADL Function is Influenced by Residual Neurological Impairment, Aphasia, and Anxiety
Authors: Juniper Ashley R. , Connor Lisa Tabor
Published: May 2022

Background. Self-perceptions of performance of activities of daily living (ADL) and instrumental activities of daily living (IADL) are reduced following stroke. Research investigating contributing factors is lacking. Purpose: We examined the extent to which aphasia status, neurological impairment and poststroke depression, and anxiety contribute to self-perceived ADL/IADL function. Method: Seventy-six community-dwelling individuals at least 6 months poststroke, 44 with and 32 without aphasia, participated in the cross-sectional study. The Stroke Impact Scale (SIS) ADL/IADL domain was the primary outcome measure with aphasia status, residual neurological impairment, depressive symptoms, and anxiety as predictor variables. Findings: Aphasia status, residual neurological impairment, and anxiety were independent predictors of self-perceived ADL/IADL function, together accounting for more than half the variance. Depression was not associated with ADL/IADL. Implications: Clinician awareness of the influence of anxiety on self-perceived ADL/IADL function, particularly for people with aphasia, may lead to future interventions that improve self-perceived ADL/IADL function.
Teaching reading: Development and differentiation
Authors: Kuhn Melanie R. , Stahl Katherine A. Dougherty
Published: May 2022

Children’s development as readers is a complex and multifaceted process. Rather than emphasizing individual components of reading instruction, Melanie R. Kuhn and Katherine A. Dougherty Stahl argue that it is more effective to view the reading process as a reciprocal or interactive one in which readers’ development in one component of reading can support their growth in other components. Further, while some components need to be consistently emphasized (i.e., vocabulary, comprehension) across readers’ developmental path, others should be focused on at specific developmental moments (e.g., alphabet knowledge, phonemic awareness). The authors present a general overview of how readers develop and discuss how to flexibly design instruction to meet students’ needs, enhance student learning, and better ensure all students become skilled readers.
A skill-building approach to reducing students’ anxiety and challenging behavior
Authors: Minahan Jessica , Ablon J. Stuart
Published: May 2022

Anxiety, one of the most common underlying causes of challenging student behavior, typically goes undiscovered and unaddressed through school-based behavior supports. Jessica Minahan and Stuart Ablon combine their expertise as a behavior analyst and a psychologist to outline how best to support students whose anxiety leads to challenging behavior. They describe the role of anxiety in challenging behavior and introduce skill-building approaches that help students develop the skills they need to succeed. These approaches can help teachers analyze skill deficits in students with anxiety, identify strategies to prevent anxiety from escalating, and build skills by combining opportunities to practice problem solving with specific strategies to manage anxiety.
Washington View: Is forgive and forget the best policy?
Authors: Ferguson Maria
Published: May 2022

In its first year, the Biden administration played it safe with public education, giving schools the funding they needed to cope with the pandemic and requiring little federal oversight. But in March 2022, the administration began responding to pressure to do something about the huge amount of student loan debt Americans are carrying. Maria Ferguson discusses the ensuing debate about whether cancelling student loan debt is the most fiscally responsible way to assist Americans in need.