bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on the Influence of Reform of Cultural Administrative System on the Upgrading of Urban Industrial Structure
Authors: Che Guangye
Published: July 2022

This paper aims at identifying the causal relationship between the reform of the cultural system and the upgrading of industrial structure, revealing the causal relationship between the reform of the cultural system and the upgrading of industrial structure, which is of great significance for promoting the reform of the cultural system and the upgrading of industrial structure. The impact of cultural administrative reform on industrial structure upgrading is empirically tested using panel data from 261 prefecture‐level cities in China from 2001 to 2017. The double difference model and PSM‐DID method are used. This includes conducting placebo tests and examining the robustness of empirical findings using other methods. The findings indicated that (1) the influence coefficient of the cultural administrative system reform on industrial structure upgrading is positive and passed the significance level test, indicating that the cultural administrative system reform significantly promoted industrial structure upgrading, and on average, it can improve the level of the urban industrial structure by 11.81 percent. (2) Theoretical analysis of the mechanism demonstrates that the innovation level acts as a link between cultural administrative system reform and industrial structure upgrading, implying that cultural administrative system reform promotes industrial structure upgrading by stimulating the innovation level of cultural enterprises. (3) The results of the heterogeneity analysis indicate that the influence of cultural administrative reform on industrial structure upgrading is highly regionally and economically differentiated. The higher the economic level of the local community, the more effective the promotion effect on industrial structure upgrading. The reform of the cultural administrative system has a greater impact on industrial structure upgrading in the eastern region than in the central and western regions. On the basis of the foregoing research findings, this paper makes some policy recommendations for releasing the overall system reform dividend based on the cultural system and promoting regional industrial structure upgrading.
Development of Automatic English Translation System Based on Fuzzy Matching and Software Simulation
Authors: Tan Qian
Published: July 2022

Software requirements are changeable, and the changes in requirements have led to many technical, economic, and management problems in the software development process, which are also considered to be the main source of software development risks. Based on the relationship between software requirements and design, this article analyzes the propagation process of requirement changes and the two dimensions of requirement change risk, opportunity and impact, and discusses software architecture customization that combines requirements, software architecture, and risk. On the basis of QFD and DSM, a composite relationship matrix is created according to requirements and software architecture, and two aspects of software architecture adaptability are analyzed from the perspective of the risk of changes in requirements. With the advent of the 5G era, this issue has gradually been paid attention to in its evolution. In order to further improve the intelligence level of the English translation system and improve the accuracy of English translation, this paper designs a translation algorithm that takes the changes in software requirements as the basis. On this basis, cross-compilation and multithreaded phrase translation loading methods are used to automate the translation system. System test results show that the system has high translation accuracy and good intelligence. Overall, the development of an automatic English translation system based on software change management and 5G networks will further enhance the intelligence and automation of English translation.
Enhanced Secure Technique for Detecting Cyber Attacks Using Artificial Intelligence and Optimal IoT
Authors: Kumar Anand , Rahmath Mohammed , Raju Yeligeti , Reddy Vulapula Sridhar , Prathap Boppuru Rudra , Hassan Mohamed M. , Mohamed Mohamed A. , Asakipaam Simon Atuah
Published: July 2022

The Internet of Things (IoT) is a broad term that refers to the collection of information about all of the items that are linked to the Internet. It supervises and controls the functions from a distance, without the need for human interaction. It has the ability to react to the environment either immediately or via its previous experiences. In a similar vein, robots may learn from their experiences in the environment that is relevant to their applications and respond appropriately without the need for human interaction. A greater number of sensors are being distributed across the environment in order to collect and evaluate the essential information. They are gaining ground in a variety of industries, ranging from the industrial environment to the smart home. Sensors are assisting in the monitoring and collection of data from all of the real-time devices that are reliant on all of the different types of fundamental necessities to the most advanced settings available. This research study was primarily concerned with increasing the efficiency of the sensing and network layers of the Internet of Things to increase cyber security. Due to the fact that sensors are resource-constrained devices, it is vital to provide a method for reacting, analysing, and transmitting data collected from the sensors to the base station as efficient as possible. Resource requirements, such as energy, computational power, and storage, vary depending on the kind of sensing devices and communication technologies that are utilised to link real-world objects together. Sensor networks' physical and media access control layers, as well as their applications in diverse geographical and temporal domains, are distinct from one another. Transmission coverage range, energy consumption, and communication technologies differ depending on the application requirements, ranging from low constraints to high resource enrich gadgets. This has a direct impact on the performance of the massive Internet of Things environment, as well as the overall network lifetime of the environment. Identifying and communicating matching items in a massively dispersed Internet of Things environment is critical in terms of spatial identification and communication.
Application of Convolutional Neural Network to GIS and Physics
Authors: Liu Jinglei , Dong Fangfang , Li Zhiyao
Published: July 2022

Human life and property are often seriously threatened and lost due to natural disasters such as earthquakes. As a spatial information system, the geographic information system (GIS) can collect, store, and manage the local or whole related physical data of the surface space to be measured with the support of software and hardware. The physical data is collected through GIS for performance testing. The data are collected from the aftershock event records of the Wenchuan earthquake. Among them, 14,000 Wenchuan earthquake events are used as the original data set, and 8,800 aftershock events are used as the test data set. Seismic data involves the detection of multiple physical quantities, which makes the seismic data gradually increase, many data have no obvious linear relationship, and traditional detection methods are difficult to meet the detection requirements. The artificial intelligence method led by a convolutional neural network (CNN) can perform pattern matching on complex nonlinear variables, and models with general characteristics can be generated from different seismic waveforms for the prediction of seismic waveforms. The results show that GIS can effectively intercept and collect seismic physical signals. The training and detection accuracy of CNN combined with GIS physical data is higher than 90%. Compared with traditional training methods, CNN is obviously superior in detection accuracy and recall rate. At the same time, a large number of microseismic events that are easily missed by manual selection can also be found.
Experimental Study on Seepage Characteristics of Coal Containing Gas and Water
Authors: Ma Shuyin , Zhang Qinghua , Xue Sheng
Published: July 2022

The effect of gas drainage is often affected by water after hydraulic infiltration enhancement measures are adopted for soft and weak permeability coal. In order to understand the permeability characteristics of coal in the state of gas and water, a three-phase pipe domain model is established. Using the improved triaxial seepage test platform, three groups of cyclic seepage tests under different pressure and water injection conditions are carried out on three groups of raw coal samples under the conditions of constant temperature, fixed axial pressure, and confining pressure. The test results show that (1) after the test of three groups of circulating coal samples, the moisture content of each group of coal samples is different. The change trend of permeability of the first cycle natural coal sample and the second cycle pressureless water injection coal sample is similar to that of gas pressure, which decreases slowly with the increase of gas pressure and the permeability of the third cycle pressure water injection coal sample increases with the increase of gas pressure, which is different from the first two cycles. (2) In the ultrasonic wave velocity test of pressure water injection, the change trend of longitudinal wave velocity of coal sample is opposite to that of gas pressure, that is, the longitudinal wave velocity decreases with the increase of gas pressure. When the gas pressure is 0.9 MPa to 1.0 MPa, the reduction of longitudinal wave velocity is more significant. (3) During the test, when the gas pressure of the coal sample is less than 1.11 MPa, the gas sensitivity coefficient of the third cycle pressurized water injection coal sample is lower than that of the first two cycles. When the gas pressure increases to 1.11 MPa, there is an inflection point; that is, the gas sensitivity coefficient of the third cycle pressurized water injection coal sample is higher than that of the first two cycles.
Incorporating Sulfur and CO2 Emission Reduction Options into the Container Fleet Capacity Renewal Alternatives for a Shipping Operator in the Post-COVID-19 Era
Authors: Liu Ding , Zhonghao Zhang , Zhang Jin
Published: July 2022

In this article, a cost-benefit decision framework is proposed to analyze the three alternative options of the container fleet capacity renewal for a ship operator. In this decision framework, the ship operator can trade off the following factors: MGO fuel or LNG option vessels, carbon neutrality, and other investment factors. The following variables are considered: the distance of the round trip, the prices of LNG and MGO, the freight rates of each option, and the initial investment ratios of new vessels. It was found that (1) the retrofitted vessels were more stable and suitable in an uncertain shipping market and have better investment potential. (2) The MGO option was the best option before the epidemic of COVID-19. In the postepidemic era, under the double carbon (carbon neutral and carbon peaking) policy, the advantage of low fuel consumption for the LNG ships disappeared due to the increase in LNG prices, and the NPV advantage of MGO ships becomes significant.
Construction and Validation of a Recurrent Risk Nomogram Model for Non-Small Cell Lung Cancer within 1 Year after Radical Resection
Authors: Zeng Dechuang , Tang Xiqiang , Nong Feng , Yi Jinyuan , Yao Yuanxi , Luo Shiguan
Published: July 2022

Objective. To explore the risk factors of recurrence within 1 year after radical resection of non-small cell lung cancer (NSCLC) and construct the nomogram model. Methods. The clinical data of 186 patients with NSCLC treated with radical surgery in Affiliated Hospital of Youjiang Medical University for Nationalities of Baise were retrospectively analyzed. Multivariate logistic regression was applied to analyze the risk factors of recurrence within 1 year after radical resection of NSCLC. The R language (R 4.0.3 software package) was used in constructing the nomogram model, and the predictive value of the model was evaluated. Results. The recurrence rate of 186 patients within 1 year after radical surgery was 29.57%. After multivariate logistic regression analysis, pathological stage, number of lymph node metastasis, chronic obstructive pulmonary disease (COPD), postoperative plasma D-dimer, and carcinoembryonic antigen were independent factors for recurrence within 1 year after radical resection of NSCLC (

P
<
0.05

). Based on the above independent risk factors, a nomogram model was established, with the distinction of AUC = 0.891 (95% CI: 0.819–0.964) and sensitivity and specificity of 70.3% and 97.8%, respectively. The calibration curve was close to the ideal curve. External validation of the model showed AUC = 0.801 (95% CI: 0.674–0.928), and sensitivity and specificity were 66.7% and 84.2%, respectively. Conclusion. The recurrence of NSCLC within 1 year after radical surgery was related to a variety of factors, and the nomogram model constructed based on risk factors had good goodness of fit, calibration, consistency of prediction, and prediction efficiency.
Research on Data Analysis and Visualization of Recruitment Positions Based on Text Mining
Authors: Chen Yuanyuan , Pan Ruijie
Published: July 2022

With the rapid development of the Internet and the impact of COVID-19, online recruitment has gradually become the mainstream form of recruitment. However, existing online recruitment platforms fail to fully combine the job seekers’ demands for salary, region, benefits, and other aspects, which cloud not display the information related to recruitment positions in a multidimensional way. To solve this problem, this paper firstly uses a web crawler to collect job information from recruitment websites based on keywords retrieved by users, then extracts job information using regular expressions, and cleans and processes the extracted job information using third-party libraries such as Pandas and NumPy. Finally, through the probabilistic theme model of text mining, the topic model of job description content in the recruitment information is modeled. Combining with the django development framework and related visualization technology, the relationship among education requirement, experience requirement, job location, salary, and other aspects in the recruitment information is visually displayed in a multidimensional way. At the same time, the GM model is used to realize the gray prediction of the number of employment personnel in related industries, which provides employment reference for the majority of job seekers and enterprises.
Spectral Solutions for Fractional Black–Scholes Equations
Authors: Abdelkawy M. A. , Lopes António M.
Published: July 2022

This paper presents a numerical method to solve accurately the fractional Black–Scholes model of pricing evolution. A fully spectral collocation technique for the two independent variables is derived. The shifted fractional Jacobi–Gauss–Radau and shifted fractional Jacobi–Gauss–Lobatto collocation techniques are utilized. Firstly, the independent variables are interpolated at the shifted fractional Jacobi nodes, and the solution of the model is approximated by means of a sequence of shifted fractional Jacobi orthogonal functions. Then, the residuals at the shifted fractional Jacobi quadrature locations are estimated. As a result, an algebraic system of equations is obtained that can be solved using any appropriate approach. The accuracy of the proposed method is demonstrated using two numerical examples. It is observed that the new technique is more accurate, efficient, and feasible than other approaches reported in the literature. Indeed, the results show the exponential convergence of the method, both for smooth and nonsmooth solutions.
Deep Learning Distributed Architecture Design Implementation for Computer Vision
Authors: Zhang Yizhong
Published: July 2022

In the era of big data, to achieve an efficient deep learning and computer vision system for big data, developers need to build a computerized deep learning and computer vision system, and the system can simultaneously complete the tasks of deep learning and computer vision and large-scale data processing. The existing training dataset is reused, and the scene information is small, which cannot meet the needs of large-scale machine training, so it is necessary to include large-scale data, distributed computer system to complete the training. How to meet the training accuracy requirements of deep learning models and minimize the resource cost within the constrained time is a major challenge for distributed deep learning systems. Resource and batch size hyperparameter allocation are the main approaches to optimize the training accuracy and resource cost of models. Existing works have independently configured resources and batch size hyperparameters in terms of computational efficiency and training accuracy, respectively. However, the impact of the two types of configurations on model training accuracy and resource cost has complex dependencies, and it is difficult to achieve the goals of satisfying the model training accuracy requirements and minimizing the resource cost simultaneously by the existing independent configuration methods. To address these problems, this paper proposes a collaborative resource-batch size optimization configuration method for distributed deep learning systems. This method was firstly based on the monotonic function relationship between resource allocation and batch size hyperparameter allocation and model training time and training accuracy, and we select the order-preserving regression theoretical tool to build a model prediction model for single-round complete training time and final training accuracy for computer vision target classification and recognition, respectively; then, we use the abovementioned models together to solve the resource and batch size optimal allocation solutions to meet the model training accuracy requirements with the goal of minimizing resource cost. The optimal allocation of resources and batch size to meet the training accuracy requirements of the model is solved. In this paper, we evaluate the performance of the proposed method for computer vision target recognition based on the proposed distributed deep learning system.
Application Analysis of Multimedia Technology in College English Curriculum
Authors: Luo Jinxia
Published: July 2022

Over the past 30 years, neural computational models have achieved great success in the field of language learning, bringing about remarkable improvements in the study of individual differences across languages. However, most of the existing research on neural computational models is about the cognitive development of mother tongue, and there is no correlation model of phonological ability, short-term memory ability, and long-term memory ability with individual differences in the research. Therefore, the intervention suggestions in English learning disabilities cannot be targeted. Through neural network simulation and t-test, it can be seen that the factors influencing the overall English performance of learners are not phonological awareness, but rather short-term memory and long-term memory. It can be seen from the simulated individual ANN that the role of working memory is particularly obvious. This conclusion is consistent with neuroscience theories on bilingual control in the brain. Individual ANN can provide a basis for predicting learners’ learning ability and risk analysis of learning disabilities by simulating the learning path of learners, and at the same time providing more accurate clues and directions for subject teachers to carry out personalized teaching.
Follicular Lymphoma Microenvironment Characteristics Associated with Tumor Cell Mutations and MHC Class II Expression
Authors: Han Guangchun , Deng Qing , Marques-Piubelli Mario L. , Dai Enyu , Dang Minghao , Ma Man Chun John , Li Xubin , Yang Haopeng , Henderson Jared , Kudryashova Olga , Meerson Mark , Isaev Sergey , Kotlov Nikita , Nomie Krystle J. , Bagaev Alexander , Parra Edwin R. , Solis Soto Luisa M. , Parmar Simrit , Hagemeister Fredrick B. , Ahmed Sairah , Iyer Swaminathan P. , Samaniego Felipe , Steiner Raphael , Fayad Luis , Lee Hun , Fowler Nathan H. , Flowers Christopher R. , Strati Paolo , Westin Jason R. , Neelapu Sattva S. , Nastoupil Loretta J. , Vega Francisco , Wang Linghua , Green Michael R.
Published: July 2022

Follicular lymphoma (FL) is a B-cell malignancy with a complex tumor microenvironment that is rich in nonmalignant immune cells. We applied single-cell RNA sequencing to characterize the diverse tumor and immune cell populations of FL and identified major phenotypic subsets of FL T cells, including a cytotoxic CD4 T-cell population. We characterized four major FL subtypes with differential representation or relative depletion of distinct T-cell subsets. By integrating exome sequencing, we observed that somatic mutations are associated with, but not definitive for, reduced MHC expression on FL cells. In turn, expression of MHCII genes by FL cells was associated with significant differences in the proportions and targetable immunophenotypic characteristics of T cells. This provides a classification framework of the FL microenvironment in association with FL genotypes and MHC expression, and informs different potential immunotherapeutic strategies based upon tumor cell MHCII expression.

Significance:

We have characterized the FL-infiltrating T cells, identified cytotoxic CD4 T cells as an important component that is associated with tumor cell–intrinsic characteristics, and identified sets of targetable immune checkpoints on T cells that differed from FLs with normal versus low MHC expression.

See related commentary by Melnick, p. 374.

This article is highlighted in the In This Issue feature, p. 369
The Description of Parents Knowledge Level in Teaching Sex Education to Preschool Age Children in Banjar Kertagraha Kesiman Kertalangu Denpasar
Authors: Dewi Luh Putu Diah Kusuma , Prihatiningsih Diah , Laksmi I Gusti Ayu Putu Satya
Published: July 2022

Early childhood sex education is teaching, awareness, and enlightenment to children about sex problems since they think about sexual problems. The initial stage of sex education is teaching the concept of right and wrong, getting used to cleaning the body, teaching how to take care of yourself, and how to build relationship with other people so that children do not have wrong understandings and fall into acts of violence and as a prevention of sexual violence. The purpose of this study was to describe the knowledge of parents about the learning process of sex education in pre-school age children in Banjar Kertagraha, Kesiman Kertalangu Village, Denpasar, Bali. This research uses a descriptive method. This study uses a total sampling technique. The number of respondents is 63 people. The location of this research is in Banjar Kertagraha, Kesiman Kertalangu Village, Denpasar, Bali. This research was conducted on 12-19 November 2021. The research instrument used a questionnaire with univariate data analysis technique. The results showed that the level of parental knowledge about sex education for preschool children in Banjar Kertagraha, Kesiman Kertalangu Village, Denpasar Bali, generally found that most of the parents who have sufficient knowledge are 33 respondents (52.4%), and those who have good and low knowledge are 18 respondents (28.6%) and 12 respondents (19%). For further researchers to carry out broader research related to parental knowledge in teaching sex education to preschool age children.
divulgação científica nas tiras digitais do personagem Armandinho
Authors: Gomes Nataniel dos Santos , Rosa Eduarda Fernandes da
Published: July 2022

Objetiva compreender como ocorre a construção do conhecimento coletivo na cultura participativa dos comentários do Facebook nas tiras digitais de divulgação científica do personagem Armandinho, de Alexandre Beck. A análise tem como base comentários construídos por recursos multimodais, fazendo uso das linguagens verbais e não verbais, buscando diferentes perspectivas de discussão sobre o assunto em destaque. A investigação aponta para a possibilidade de novos conhecimentos e diferentes reflexões dos participantes das conversações.
The Confucian Way of Family under the Gongfu 功夫 Perspective – A Re-description (II)
Authors: Ni Peimin
Published: July 2022

Unlike typical journal articles that deal with specific issues in detail, this article offers a sketchy comprehensive re-description of the Confucian Way of family that serves the purpose of providing a bird’s-eye view to grasp the fact that, for Confucianism, family is not merely a part of the puzzle of human life, nor merely an ontological entity that serves as the foundation of the Confucian theory, but more a “Way” of living or gongfu 功夫 that comprised of values toward which cultivation of the person is practiced, an art of life to be mastered, and a model of social order to be implemented.
A Moral Metaphysics and a Metaphysics of Morals: Xunzi and Kant
Authors: Bunnin Nicholas
Published: July 2022

I explore two important ways of thinking that the philosophical understanding of morality requires metaphysics: the moral metaphysics I ascribe to Xunzi and Kant’s metaphysics of morals. Both Xunzi and Kant held that a metaphysics of nature is inadequate for a metaphysical understanding of human moral agency. Xunzi invoked the human Dao to allow for the agency of the heart-mind, and Kant invoked the Categorical Imperative to allow for the agency of the moral self. Both Xunzi and Kant stretched metaphysics through rejecting the wrong sorts of rigour as preventing us from having an appropriate understanding of metaphysics and morality. I turn to their different placements of humanity that reflect deep differences in Xunzi’s and Kant’s underlying metaphysics. Xunzi placed humanity as a virtue or power that allows our psychology to become a moral psychology. Kant placed humanity as an ideal that allows our psychology to be a moral psychology.
The Scope of the Means Principle
Authors: Parry Jonathan
Published: July 2022

This paper focuses on Quong’s account of the scope of the means principle (the range of actions over which the special constraint on using a person applies). One of the key ideas underpinning Quong’s approach is that the means principle is downstream from an independent and morally prior account of our rights over the world and against one another. I raise three challenges to this ‘rights first’ approach. First, I consider Quong’s treatment of harmful omissions and argue that Quong’s view generates counter-intuitive results. Second, I argue that cases of harmful omissions raise problems for Quong’s claim that intentions are irrelevant to permissibility. Third, I consider Quong’s extension of the means principle to include uses of persons’ rightfully-owned property. I suggest that, contra Quong, questions of distributive justice are not morally prior to the ethics of defensive harm. Instead the two normative domains mutually inform one another.
Getting a Read on the Pandemic
Authors: Ebert Emma
Published: July 2022

This article explores the links between psychology – specifically, psychological needs, motivations, and coping mechanisms – and the sales of backlist titles during the COVID-19 pandemic. It shows how select titles on spirituality as well as The Boy, the Mole, the Fox and the Horse by Charlie Mackesy and Man’s Search for Meaning by Viktor E. Frankl help readers to attribute meaning to the pandemic and in turn, to cope with the struggles of the pandemic. The article concludes that such books are connected by their psychological value to readers – the psychological needs they fulfil – and that books from disparate genres and on varying topics can help readers cope in similar ways.
Four new species of the genus Eophileurus Arrow, 1908 (Coleoptera: Scarabaeidae: Dynastinae) from Thailand and Vietnam, with notes on some Indochinese species
Authors: YANG QIAO-ZHI , PATHOMWATTANANURAK WUTTIPON
Published: July 2022

Four new species of the genus Eophileurus Arrow, 1908 are described: E. minor Yang & Pathomwattananurak, new species (Thailand and Vietnam), E. prelli Yang & Pathomwattananurak, new species (Vietnam), E. quadratifovealis Yang & Pathomwattananurak, new species and E. sidereus Yang & Pathomwattananurak, new species (both Thailand). Two new junior synonyms are proposed: E. confinis Prell, 1913 = E. takakuwai Yamaya & Muramoto, 2008, new synonym and E. felschei Prell, 1913 = E. grossepunctatus Dupuis, 2014, new synonym. Lectotypes for E. andamanicus Arrow, 1914 and E. siamensis Arrow, 1914 are designated. Taxonomic problems regarding E. confinis and E. malyi Endrődi, 1978 are discussed. Type material of E. andamanicus, E. confinis, E. decipiens Prell, 1913, E. felschei, E. gracilis Prell, 1913, E. grossepunctatus, E. malyi, E. nicobarensis Endrődi, 1978 and E. siamensis is illustrated. A distribution map of the new species and their closest relatives is also provided.
Novel Au–Se Nanoprobes for Specific Thrombin Detection in Diagnosis of Lung Cancer
Authors: Zhu Koujun , Lu Rongguo , Qu Weifeng , Gu Jiaqi , Xiang Hu , Zhang Weimin , Ni Bin
Published: July 2022

Thrombin is associated with malignant tumors and promotes tumor development, metastasis, and angiogenesis, therefore its identification especially in lung cancer cells is crucial. Because the interference of in vivo biothiols caused false positive findings with prior gold fluorescent
nanoprobes, in this manuscript, an Au-selenol(Se) nanoprobe (5-FAM-peptide-Se-AuNPs) that could specifically detect thrombin was designed and compared to traditional Au–S nanoprobes. For reaching this goal, fluorophore-bearing thrombin-specific peptide containing selenol at the end was
synthesized. The nanoprobe may be broken by thrombin to regain its fluorescence in lung cancer cells, allowing for high-sensitivity thrombin detection. Since the Au–Se bond is more stable than the Au–S bond, the accuracy of the detection results can be guaranteed. The probe synthesis
method is simple and cost-effective, as well as having high biocompatibility. Low concentrations of thrombin can be detected and imaged in lung cancer cells. The synthetic method of this probe opens up new avenues for the application of Au–Se bonds.
Using the Resected Kidney for Transplantation After Nephrectomy for Nutcracker Syndrome
Authors: Fonseca Bauza Maria V. , Toledo Alexander H. , Rodriguez Pablo Serrano
Published: July 2022

Nutcracker syndrome (NCS) is the clinical manifestation of unilateral renal venous hypertension. It develops secondary to the nutcracker phenomenon caused by compression of the left renal vein between the superior mesenteric artery and the aorta. We present the case of a 43-year-old female with a history of left flank pain, pelvic congestion, and hematuria secondary to NCS. The patient frequently required high-dose non-steroidal anti-inflammatory medications with minimal relief. She initiated a kidney donor evaluation after electing to undergo a nephrectomy for the possible long-term resolution of NCS symptoms. If diagnosed early, NCS does not generate pathology within the kidney. This finding allows an individual with medically refractory NCS to avoid the morbidity of a complex surgical procedure by instead donating their kidney. Attention to this treatment modality could provide individuals with NCS resolution of symptoms while providing someone with end-stage renal disease with a life-saving organ.
Impact of Stress Hyperglycemia on the Timing of Complete Revascularization in Non-diabetes Patients with ST Elevation Myocardial Infarction and Multivessel Disease
Authors: Zheng Wen , Huang Xin , Zhao Xuedong , Gong Wei , Wang Xiao , Nie Shaoping
Published: July 2022

Background: Stress hyperglycemia (SHG) is related to an increased risk of mortality in diabetic patients with ST elevation myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention (PPCI). However, data are limited in non-diabetic patients especially in patients with multivessel disease (MVD). Methods and Results: In this retrospective study, 742 non-diabetic patients with STEMI and MVD were divided into SHG group and non-SHG group. The overall incidence of SHG was 24.9%. The incidence of no-reflow (NR) phenomenon (18.4% vs 11.8%; P = .024) and in-hospital mortality (1.6% vs .2%; P = .020) in SHG group were significantly higher than those in non-SHG group. SHG was associated with 30-day MACE (hazard ratio, 4.265; 95% confidence interval (CI), 1.354–13.439; P = .013), but not 1-year. Multivariate logistic analysis showed that SHG (odds ratio: 1.691, 95% CI: 1.072–2.667, P = .024) was an independent predictor of NR. If complete revascularization (CR) was performed during PPCI, the incidence of NR would be significantly higher. Conclusion: In non-diabetic patients with STEMI and MVD, SHG is associated with increased SF-NR and short-term adverse events, and CR during PPCI further increases the risk of NR.
Pattern of Neurological Outpatient Practice: Implications for Undergraduate and Postgraduate Training
Authors: Perkin G D
Published: July 2022

A case analysis has been performed on 4000 successive outpatient referrals to one consultant neurologist, representing 72% of all referrals to Charing Cross Hospital and 82% to Hillingdon Hospital. A specific diagnosis was not possible in 1013 patients (25.3%). Amongst the remainder certain diagnoses were predictably common: for example, migraine (241), tension headaches (296) and epilepsy (470). Based on data obtained for the incidence of various neurological disorders in the community, an attempt has been made to assess what proportion of patients with certain diagnoses are likely to be seen by a neurologist. The rarity with which certain classical conditions, for example syringomyelia, is encountered is stressed and the implications for teaching discussed.
Depressive Disorder Due to Craniopharyngioma
Authors: Spence Sean A , Taylor David G , Hirsch Steven R
Published: July 2022

Secondary causes of depression are legion, and must always be considered in patients presenting with features atypical of primary idiopathic depressive disorder. The case described is that of a middle-aged woman presenting initially with a major depressive disorder who was subsequently found to have a craniopharyngioma, leading to a revised diagnosis of mood disorder due to the tumour. Some features of the presentation might have led to earlier diagnosis had their localizing significance been recognized. Diencephalic lesions should always be considered in patients presenting with the hypersomnic-hyperphagic variant of depressive disorder.
Value of hematological parameters for predicting patients with severe coronavirus disease 2019: a real-world cohort from Morocco
Authors: Azghar Ali , Bensalah Mohammed , Berhili Abdelilah , Slaoui Mounia , Mouhoub Boutaina , El Mezgueldi Imane , Nassiri Oumaima , El Malki Jalila , Maleb Adil , Seddik Rachid
Published: July 2022

Objective

Coronavirus disease 2019 (COVID-19) is a viral disease caused by severe acute respiratory syndrome coronavirus 2. The clinical manifestations and the evolution of patients with COVID-19 are variable. In addition to respiratory involvement, COVID-19 leads to systemic involvement and can affect the hematopoietic system. This study aimed to evaluate the prognostic value of hematological and hemocytometric parameters in predicting the severity of patients with COVID-19.

Methods

We performed a retrospective study at Mohammed VI university Hospital from 1 March to 11 November 2020. We collected demographic characteristics and hematological findings of incident COVID-19 cases.

Results

A total of 245 patients were included in our study. We found that the rate of lymphopenia was significantly reduced in patients who were severely affected by COVID-19. Additionally, the rate of neutrophilia, the neutrophil side fluorescence light signal, monocyte fluorescent intensity, monocyte size, the neutrophil-to-lymphocyte ratio, the platelet-to-lymphocyte ratio, and the lymphocyte-to-monocyte ratio were significantly elevated in patients who were severely affected by COVID-19.

Conclusions

These results are consistent with the literature regarding the predictive value of these markers. A prospective validation in a large population with a longer follow-up is required.
“Don't Just Study our Distress, Do Something”: Implementing and Evaluating a Modified Stepped-Care Model for Health Care Worker Mental Health During the COVID-19 Pandemic
Authors: Sheehan Kathleen A. , Schulz-Quach Christian , Ruttan Lesley A. , MacGillivray Lindsey , McKay Martha S. , Seto Alison , Li Adrienne , Stewart Donna E. , Abbey Susan E. , Berkhout Suze G.
Published: July 2022

Objective

Throughout the COVID-19 pandemic, there have been concerns about the mental health of health care workers (HCW). Although numerous studies have investigated the level of distress among HCW, few studies have explored programs to improve their mental well-being. In this paper, we describe the implementation and evaluation of a program to support the mental health of HCW at University Health Network (UHN), Canada's largest healthcare network.

Methods

Using a quality improvement approach, we conducted a needs assessment and then created and evaluated a modified stepped-care model to address HCW mental health during the pandemic. This included: online resources focused on psychoeducation and self-management, access to online support and psychotherapeutic groups, and self-referral for individual care from a psychologist or psychiatrist. We used ongoing mixed-methods evaluation, combining quantitative and qualitative analysis, to improve program quality.

Results

The program is ongoing, running continuously throughout the pandemic. We present data up to November 30, 2021. There were over 12,000 hits to the UHN's COVID mental health intranet web page, which included self-management resources and information on group support. One hundred and sixty-six people self-referred for individual psychological or psychiatric care. The mean wait time from referral to initial appointment was 5.4 days, with an average of seven appointments for each service user. The majority had moderate to severe symptoms of depression and anxiety at referral, with over 20% expressing thoughts of self-harm or suicide. Post-care user feedback, collected through self-report surveys and semistructured interviews, indicated that the program is effective and valued.

Conclusions

Development of a high-quality internal mental health support for HCW program is feasible, effective, and highly valued. By using early and frequent feedback from multiple perspectives and stakeholders to address demand and implement changes responsively, the program was adjusted to meet HCW mental health needs as the pandemic evolved.
Comparison of assessment of coagulation in healthy dogs by the TEG 6s and TEG 5000 viscoelastic analyzers
Authors: Wheeler Lance R. , Edwards Thomas H. , Heinz Justin A. , Scott Laura L. F. , Grantham Lonnie E. , Keesee Jeffrey D. , Henderson Alice F. , Gerardo Angelina C. , Hoareau Guillaume , Bynum James A.
Published: July 2022

The TEG 6s (Haemonetics) point-of-care viscoelastic analyzer is portable, compact, simple to use, and has the potential for rapid viscoelastic analysis that can guide the treatment of veterinary patients at the site of care. Although approved for use in people, the TEG 6s has yet to be evaluated for hemostatic analysis in veterinary medicine. Citrated whole blood (CWB) was collected from 27 healthy dogs. An aliquot of CWB from each dog was diluted by 33% with an isotonic crystalloid, representing an in vitro model of hemodilution. Unaltered and diluted CWB samples were analyzed using 2 TEG 6s and 6 TEG 5000 (Haemonetics) analyzers. The 6 TEG 5000 analyzers ran duplicate analyses of either unaltered or diluted samples using 1 of 3 reagents (Haemonetics): Kaolin TEG, RapidTEG, or TEG Functional Fibrinogen. Duplicate TEG 5000 analyses were averaged and compared with a single TEG 6s analysis. Lin concordance correlation coefficient and Bland–Altman plots were used to evaluate agreement of reaction time, kinetic time, alpha angle, maximum amplitude (MA), and G value (G) for samples activated with Kaolin TEG, and agreement of MA for samples activated with RapidTEG between the 2 machines. Overall, agreement between the TEG 6s and TEG 5000 analyzers was poor. Viscoelastic measurements by the TEG 6s and TEG 5000 in healthy dogs were not all interchangeable. Agreement was satisfactory only for MA and G measurements of diluted blood samples activated with Kaolin TEG, and MA measurements for both unaltered and diluted blood samples activated with RapidTEG.
Analysis of Competitive Endogenous RNA Regulatory Network of Exosomal Breast Cancer Based on exoRBase
Authors: Zhu Kangle , Wang Qingqing , Wang Lian
Published: July 2022

Objective:

To construct a competitive endogenous RNA (ceRNA) regulatory network derived from exosomes of human breast cancer (BC) by using the exoRbase database, to explore the possible pathogenesis of BC, and to develop new targets for future diagnosis and treatment.

Methods:

The exosomal gene sequencing data of BC patients and normal controls were downloaded from the exoRbase database, and the expression profiles of exosomal mRNA, long non-coding RNA (lncRNA), and circular RNA (circRNA) were analyzed by using R language. Use Targetscan and miRanda database to jointly predict and differentially express miRNA (microRNA), miRNA combined with mRNA. The miRcode database was used to predict the miRNA combined with differentially expressed lncRNA, and the starBase database was used to predict the miRNA combined with circRNA in the difference table. The related mRNA, circRNA, lncRNA, and their corresponding miRNA prediction data were imported into Cytoscape software to visualize the ceRNA network. Enrichment analysis and visualization of KEGG were carried out using KOBAS. Hub gene was determined by Cytohubba plug-in.

Results:

Forty-two differentially expressed mRNA, 43 differentially expressed circRNA, and 26 differentially expressed lncRNA were screened out. The ceRNA network was constructed by using Cytoscape software, including 19 mRNA nodes, 2 lncRNA nodes, 8 circRNA nodes, and 41 miRNA nodes. KEGG enrichment analysis showed that differentially expressed mRNA in the regulatory network mainly enriched the p53 signaling pathway. Find the key Hub gene PTEN.

Conclusion:

The ceRNA regulatory network in blood exosomes of BC patients has been successfully constructed in this study, which provides an exact target for the diagnosis and treatment of BC.
The Influence of Digital Affinity on the Continuous Glucose Monitoring System Choice by People With Type 1 Diabetes
Authors: Kinzel Carolin , Manfras Burkhard
Published: July 2022

Background:

Since several years, continuous glucose monitoring (CGM) systems became a standard of care in patients with intensified conventional treatment (ICT) in many countries. CGM results in an ongoing record of digital information that provides an added value to patients with type 1 diabetes (T1D) and healthcare providers, among others. This implies the patient’s acceptance of data analyses and storage and an adjustment on self-management. The aim of the study was to investigate the influence of digital affinity on the CGM use and the choice of a particular system.

Methods:

In a quantitative survey 2102 patients with T1D were interviewed via an online questionnaire. The study is based on the technology acceptance model (TAM). Self-assessment of digital affinity was correlated with various features of CGM use and preferences. Significance of associations and correlations was tested.

Results:

Digital affinity correlated positively with CGM use for the self-management with ICT. Significant differences were found regarding the use of a particular system suggesting a correlation between digital affinity and the complexity of CGM data portrayal and interconnectivity with smart devices (eg, smartwatches).

Conclusions:

While suppliers of CGM systems focus on progress regarding the ease of use of their systems, they also provide a developing interconnectivity with smart devices and cloud-based data storage. This requires a higher digital affinity among users. While factors such as recommendations by physicians and coverage by health insurance companies have an impact on the system choice, the data demonstrate a correlation between digital affinity and particular CGM systems.
Steatosis Grading Comparison Between Qualitative Ultrasonography and Magnetic Resonance Spectroscopy in Patients With Nonalcoholic Fatty Liver Disease
Authors: Stahlschmidt Fábio L. , Weber Isabela L. , Ludwig Maria V. D. , Feuerschuette Léo M.
Published: July 2022

Objective:

Assess the correlation between the qualitative sonographic score for detecting hepatic steatosis (HS) and liver fat quantification, using proton magnetic resonance spectroscopy (MRS).

Materials and Methods:

Sixty-six patients with known or suspected nonalcoholic fatty liver disease (NAFLD) underwent ultrasonography (US) and magnetic resonance imaging (MRI). The qualitative sonographic score and fat quantification, measured by MRS, were the techniques used. A Kappa coefficient was used for agreement calculation, and a Fisher test was used to assess the normality of the variables. The MRS results were the gold standard for US quality assessment.

Results:

The agreement between MRS and US was 50% (Kappa 0.35). Ultrasonography results were more severe in 42.4% of the cases, and 66.7% of the patients had a body mass index greater than 30 ( P = .017). For diagnosis of HS, US presented 100% sensitivity, 30.8% to 60% specificity, 61.7% to 72.7% accuracy, 40% to 69.2% false-positive rate, 0% false-negative rate, 53.8% positive predictive value, and 100% negative predictive value.

Conclusion:

Ultrasonography is a reliable exam for detecting HS, although not for grading purposes. Therefore, US is not a good predictor of HS severity for the management and follow-up of NAFLD.