bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating the Performance of Connected and Automated Vehicles in Fixed Signal-Controlled Conventional Intersections and Superstreets with Platooning-Based Trajectory Planning
Authors: Liu Shaojie , Fan Wei David
Published: June 2022

Connected and autonomous vehicles (CAVs) are emerging technology that attracts the interests of many transportation professionals and computational scientists. Several recent studies have investigated different model frameworks of CAVs in different transportation environments, such as on freeways and at conventional intersections. Nevertheless, few efforts have been made to investigate the performances of CAVs at innovative intersections, and the lack of knowledge can result in an inaccurate prediction of CAVs performances in the existing transportation network. This research intends to mitigate this research gap by studying the traffic delay and fuel consumption of CAVs in the environment of the superstreet and its equivalent conventional intersection through simulation-based experiments. A real-world superstreet in Leeland, NC, is selected and used. A conventional intersection with equivalent road designs is established in the simulation platform to make a comparison with the selected superstreet. This research develops both platooning and trajectory planning modeling frameworks to examine the implications of CAVs with different capabilities. The Intelligent Driver Model (IDM) is selected and applied to model the CAV behaviors, while Wiedemann 99 (W99) is used to model Human-Driven Vehicles (HDVs). The simulation results demonstrate the efficiency of both platooning and trajectory planning, respectively. Different effects of CAVs in the superstreet and its equivalent conventional intersection are observed. The findings from this research can provide an important reference for transportation planners and policymakers in predicting the influence of CAVs on the existing transportation infrastructure.
Design of an Intelligent Sensor Teaching Experiment System and Measurement of Student Innovation Literacy
Authors: Li Xiaorong , Xing Qianli
Published: June 2022

Most of the experimental teaching links adopt experimental teaching, and few of them are taught through experimental simulation system. The intelligent sensor teaching experimental simulation system is a simulation measurement software system compiled by access and LabVIEW software to assist the use of sensor measurement and virtual instrument practical teaching platform, which realizes the network teaching of experimental links and carries out exploratory work. It has important practical significance for the modernization of experimental links. At the same time, the intelligent sensor experimental system can effectively improve the problems of students’ low learning motivation and poor learning effect in the learning process and finally let students participate in the construction of sensor teaching experimental system, improve students’ learning interest and enthusiasm, and cultivate students’ autonomous learning and innovation ability. Through the establishment of intelligent sensor teaching simulation system, this paper successfully improves students’ innovative literacy in teaching level, scientific research practice, teaching content, teaching methods, and intelligent lectures and greatly improves students’ learning enthusiasm, learning efficiency, and teaching quality.
Optimal Location and Sizing of BESS for Performance Improvement of Distribution Systems with High DG Penetration
Authors: Khunkitti Sirote , Boonluk Punyawoot , Siritaratiwat Apirat
Published: June 2022

This work proposes an optimal location and sizing of battery energy storage system (BESS) installation for performance improvement of distribution systems with high distributed generation (DG) penetration level where the DGs comprise photovoltaics (PV) and wind turbines (WT). The installation of the BESS can reduce costs incurred in the systems, alleviate reverse power flow when the systems are in the high DG penetration level, and also achieve peak shaving during high demand. To find the optimal location and sizing of the BESS, three optimization algorithms, genetic algorithm (GA), particle swarm optimization (PSO), and salp swarm algorithm (SSA), are applied, and their performances are compared. The considered objective function is the system costs consisting of transmission loss cost, peak power cost, and voltage deviation cost. The system performance improvement is compared in terms of transmission loss, peak demand, and voltage regulation reductions. IEEE 33- and 69-bus distribution systems with high DG penetration are tested to investigate the performance improvement of the BESS installation. The results found that the installation of the BESS could successfully decrease system cost, improve voltage profile, reduce power losses, alleviate reverse power flow, and achieve peak shaving where PSO and SSA are found to be the best competitive algorithms. So, the proposed method can be further applied to find the optimal location and sizing of the BESS to improve the performance of practical systems in the future.
Intrusion Detection System for IoT Based on Deep Learning and Modified Reptile Search Algorithm
Authors: Dahou Abdelghani , Abd Elaziz Mohamed , Chelloug Samia Allaoua , Awadallah Mohammed A. , Al-Betar Mohammed Azmi , Al-qaness Mohammed A. A. , Forestiero Agostino
Published: June 2022

This study proposes a novel framework to improve intrusion detection system (IDS) performance based on the data collected from the Internet of things (IoT) environments. The developed framework relies on deep learning and metaheuristic (MH) optimization algorithms to perform feature extraction and selection. A simple yet effective convolutional neural network (CNN) is implemented as the core feature extractor of the framework to learn better and more relevant representations of the input data in a lower-dimensional space. A new feature selection mechanism is proposed based on a recently developed MH method, called Reptile Search Algorithm (RSA), which is inspired by the hunting behaviors of the crocodiles. The RSA boosts the IDS system performance by selecting only the most important features (an optimal subset of features) from the extracted features using the CNN model. Several datasets, including KDDCup-99, NSL-KDD, CICIDS-2017, and BoT-IoT, were used to assess the IDS system performance. The proposed framework achieved competitive performance in classification metrics compared to other well-known optimization methods applied for feature selection problems.
Advances in the Study of Inhaled Formulations for the Treatment of Pulmonary Arterial Hypertension
Authors: Han Fei , Chen Yongqi , Li Shijie , Yang Yankun , Bai Zhonghu
Published: June 2022

Pulmonary arterial hypertension (PAH) is a serious disease with reduced systemic circulation and low bioavailability associated with conventional and dosed therapy, which inhaled drugs can avoid. A mean pulmonary artery pressure (mPAP) of ≥25 mmHg (

1
 
mmHg
=
0.133
 
kPa

) at rest or ≥30 mmHg during exercise and a pulmonary capillary pressure or left atrial pressure (PLA) of ≤15 mmHg can be diagnosed with PAH. Pulmonary hypertension is classified into primary PAH and secondary PAH according to the presence or absence of principles or risk factors. The main symptoms of pulmonary hypertension include dyspnoea, syncope, weakness, chest pain, and the presence of varying degrees of peripheral oedema. It is a highly pathogenic and life-threatening disease and can lead to delays in treatment if not diagnosed in time. In the past few years, the studies related to this progressed slowly, which brought great harm to patients with PAH. Reports showed that patients diagnosed with PAH should receive routine preventative care, such as pneumococcal and influenza vaccinations. Inhalation therapy is mainly used for the treatment of respiratory diseases and is of great interest due to the concentration of the drug in the airways and lung tissues. Therefore, the present situation of pulmonary hypertension and the characteristics of inhalation preparation were reviewed in this paper to provide some related cue for the treatment of pulmonary hypertension. In the future, it is necessary to develop more treatment methods for pulmonary hypertension.
A BL-CC Converter-Based BLDC Motor Drive for Marine Electric Vehicle Applications
Authors: Shukla Tanmay , Kalla Ujjwal Kumar
Published: June 2022

This article presents a BLDC (permanent magnet brushless DC) motor drive for marine electric vehicle (MEV) application. The presented scheme uses bridgeless canonical cell (BL-CC) converter with center-tapped inductor (shown as two separate inductors for analysis purpose) for source-side power factor correction (PFC); however, the BL-CC converter requires two inductors. In the presented scheme use of one center-tapped inductor eliminates the requirement of one extra inductor. Thus, center-tapped inductor usage in BLDC motor drive results in decrement in components count. The BL-CC converter-based BLDC motor drive scheme do not require extra back-feeding diodes like other bridgeless (BL) schemes, but it uses inbuilt antiparallel diodes of insulated gate bipolar transistor (IGBT) switches for the same purpose this again leads to decrement in required component count. In this work, PFC BL-CC converter is operated in discontinuous inductor current (DIC) mode to attain better power quality. The DIC mode operation requires only one voltage sensor to sense DC-link voltage, whereas in continuous conduction mode (CCM), the sensor requirement increases to three (two voltage sensors and one current sensor). The PFC BL-CC converter also eliminates the diode bridge rectifier stage. The elimination of one extra inductor, two extra back-feeding diodes, DBR stage and also requirement of only one voltage sensor in DIC mode operation instead of three sensors for CCM implies reduction in components count which implies the reduction in cost and also the volume and weight of the BLDC motor drive. The weight reduction for marine (on-board) electric vehicle is very important as this enhances the vehicle performance. This paper also presents the detailed mathematical modeling and stability analysis of presented BL-CC converter using pole zero map and Bode plot. The BL-CC converter-based BLDC motor driving system for MEV application for DIC mode operation has been developed in the laboratory as well as on MATLAB/Simulink platform and simulated MATLAB and real-time experimental results have been presented to validate the presented BLDC motor drive under steady-state and dynamic operating conditions.
A Hierarchical Passenger Mobility Prediction Model Applicable to Large Crowding Events
Authors: Guo Bao , Yang Hu , Zhang Fan , Wang Pu
Published: June 2022

Predicting individual mobility of subway passengers in large crowding events is crucial for subway safety management and crowd control. However, most previous models focused on individual mobility prediction under ordinary conditions. Here, we develop a passenger mobility prediction model, which is also applicable to large crowding events. The developed model includes the trip-making prediction part and the trip attribute prediction part. For trip-making prediction, we develop a regularized logistic regression model that employs the proposed individual and cumulative mobility features, the number of potential trips, and the trip generation index. For trip attribute prediction, we develop an

n

-gram model incorporating a new feature, the trip attraction index, for each cluster of subway passengers. The incorporation of the three new features and the clustering of passengers considerably improves the accuracy of passenger mobility prediction, especially in large crowding events.
Ecological and Coevolutionary Dynamics in Modern Markets Yield Nonstationarity in Market Efficiencies
Authors: Van Oort Colin M. , Ring IV John Henry , Dewhurst David Rushing , Danforth Christopher M. , Tivnan Brian F.
Published: June 2022

The U.S. stock market is one of the largest and most complex marketplaces in the global financial system. Over the past several decades, this market has evolved at multiple structural and temporal scales. New exchanges became active, and others stopped trading, regulations have been introduced and adapted, and technological innovations have pushed the pace of trading activity to blistering speeds. These developments have supported the growth of a rich machine‐trading ecology that leads to qualitative differences in trading behavior at human and machine time scales. We conduct a longitudinal analysis of comprehensive market data to quantify nonstationary dynamics throughout this system. We quantify the relationship between fluctuations in the number of active trading venues and realized opportunity costs experienced by market participants. We find that information asymmetries, in the form of quote dislocations, predict market‐wide volatility indicators. Lastly, we uncover multiple micro‐to‐macro level pathways, including those exhibiting evidence of self‐organized criticality.
A Survey on Generalized Topological Indices for Silicon Carbide Structure
Authors: Alam Sajid Mahboob , Jarad Fahd , Mahboob Abid , Siddique Imran , Altunok Taner , Waheed Rasheed Muhammad
Published: June 2022

The application of graphs in chemical and molecular structures has exponentially increased during the last few years. Topological indices facilitate the collection of beneficial information and provide an approach to understanding the properties of chemical structure by providing information about algebraic graphs. Let G be a graph with

u

-vertices and

Ω

u

be the degree of

u

t
h

vertex. In this manuscript, we compute Zagreb index (ZI), first, and second, Hyper F-indices and sum and product connectivity of F-index of silicon carbides, namely, SiC4 – I[r, s] and SiC4 – II[r, s].
Vibration and Constitutive Relations of Viscoelastic Cantilever Beam of HTPB Propellant
Authors: Gao Bo , Li Zhuo
Published: June 2022

A cantilever beam test specimen of a viscoelastic material, which is sourced from the hydroxy-terminated polybutadiene (HTPB) propellant, has been made. The traditional experimental modal analysis (EMA) is performed using the SIEMENS TESTLAB software to obtain the first six orders of modal frequencies based on the Poly MAX method, thereby determining the frequency range associated with the frequency domain analysis. The relaxation modulus of this viscoelastic material is first measured using a thermo-viscoelasticity analyzer (DMA); subsequently, the relaxation modulus is adopted to fit the 19-parameter Prony series of conformational models that characterize this viscoelastic material. Sinusoidal frequency sweep is then conducted on the SIEMENS TESTLAB platform, and the corresponding measured signals are obtained. Using the finite element method, a transient analysis simulation of the experimental conditions is performed. The dynamic response of this viscoelastic material under sinusoidal frequency sweep is evaluated by comparing it with the experimental data. It is observed that the overall acceleration peak error and the finite element simulation result are less than 3%. This study verifies that the obtained static constitutive equation (19-parameter Prony series) can describe the dynamic responses at low frequencies (<80 Hz).
[Retracted] Pathological, Histological, and Molecular Based Investigations Confirm Novel Mycobacterium bovis Infection in Boselaphus tragocamelus
Authors: Hussain Riaz , Jamal Adil , Ahmed Zulfiqar , Mohamed Bahaeldeen Babiker , Siddique Abu Baker , Khan Iahtasham , Mansoor Muhammad Khalid , Du Xiaoxia , Khan Ahrar
Published: June 2022

Mycobacterium bovis (M. bovis) being the main cause of animal tuberculosis is a complex infectious agent and can be a cause of zoonotic tuberculosis zoonosis in public health. To date, the uncommon infection in public health due to M. bovis still is a great challenge to both veterinary and medical professions and requires a careful diagnosis and confirmation of the bacterium. Therefore, this study for the first time reports the clinical, gross, histopathological, and molecular based confirmation of M. bovis infection in wildlife animals (nilgai). Prior to death, the morbid animal showed severe pneumonic ailments like moist cough, thick nasal exudates, and dyspnoea. At necropsy, enlargement of mandibular cervical and mesenteric lymph nodes was observed. Different macroscopic lesions such as congestion and hyperaemia, creamy white and catarrhal exudates in trachea, consolidation, grey and red hepatisation of lungs, and micro‐ and macrogranulomatous tubercles containing caseous materials in lungs were observed. The heart of morbid animal showed congestions, myocarditis, and a copious amount of straw‐colored fluid in the pericardial sac. At the microscopic level, lungs indicated granulomatous inflammatory response, presence of multinucleated giant cells, fibrosis, and punctuation of alveoli with chronic inflammatory cells. Histopathological examination of various sections of the heart of the infected animal showed chronic inflammatory response consisting of chronic inflammatory cells like monocyte, lymphocytes, and fibroblasts along with noncalcified eosinophilic materials. At the molecular level, M. bovis infection was confirmed in various tissues like the heart, lungs, cervical, and mesenteric lymph nodes in morbid animals. In conclusion, based on our results, it can be suggested that more molecular based epidemiological studies are crucial to know the exact cause of pulmonary and cervical tuberculosis in wild animals.
SARS-CoV-2: Molecular Structure, Pathogenesis, Potential Therapeutic Targets, and Immune Response of the Infected Subject
Authors: Wumba R. , Mandina M. , Nlandu Y. , Makulo J. R. , Tshimpi A. , Mbala P. , Mbangama A. , Kabututu P. , Kayembe J. M.
Published: June 2022

Background. The pathogenic mechanisms and immune response of COVID-19 are far from clear. Through a documentary review of literature, the authors describe virological and molecular aspects of SARS-CoV-2, the intimate mechanisms of cell infection, and potential therapeutic targets. They also analyze the characteristics of immune response of the infected subject. Objectives. Objectives of this study are to describe the state of knowledge on virological data, molecular and physiopathogenic mechanisms of SARS-CoV-2, with a view to a better understanding of the therapeutic targets, as well as the immune response of the infected subject. Methodology. This documentary review is a compilation of several meta-analyses, consistent with the methodology described in the PRISMA statement on literature data on SARS-CoV-2, published between March 22 and August 14, 2020 (Moher et al.). The search engines used for the selection of articles were as follows: PubMed, Google Scholar, Global Health, and WHO reports. Papers of interest were those addressing virological and molecular data on SARS-CoV-2, therapeutic aspects of COVID-19, and immunity of the infected subject. Of the 617 eligible papers, 417 could be retained after removing the duplicates. Ultimately, only 50 articles were retained for final evaluation. The data collected allowed the development of a two-armed model around the physiopathological aspects and potential therapeutic targets, as well as aspects of host immunity, respectively. The model was then compared to data from the HIV literature. Conclusion. Reported data could contribute to a better understanding of molecular mechanisms of cellular infection by SARS-CoV-2 as well as to a more easy explanation of the action of pharmacological agents used for the treatment, while elucidating intimate mechanisms of the immunity of infected subject.
Deep Learning for Chinese Language Sentiment Extraction and Analysis
Authors: Zhu Zhu
Published: June 2022

In recent years, vocabulary emotion processing has become immensely popular and the requirements for language emotion analysis mining and processing have become significantly abundant. The sentiment extraction and analysis work has always been very challenging; especially, the Chinese word segmentation operation is difficult to deal with effectively, the multiple combinations of implicit and explicit words make the task of sentiment analysis mining more difficult, and, in particular, the efficiency of machine analysis of language sentiment is feeble. We use some expressions and sentiment vocabulary dictionaries combined with hybrid structures and use information synergy methods to get in touch with sentiment analysis methods. We use the relevant sentiment to evaluate the explicit or implicit emotional association of the emotional connection of the vocabulary and add the unique emotional word matrix to analyze the related clustering results of the emotional words to continuously optimize and upgrade the performance, so that our sentiment analysis results are systematic in terms of efficiency and significantly improved.
Healthcare Data Security Using IoT Sensors Based on Random Hashing Mechanism
Authors: Khadidos Adil O. , Shitharth S. , Khadidos Alaa O. , Sangeetha K. , Alyoubi Khaled H.
Published: June 2022

Providing security to the healthcare data stored in an IoT-cloud environment is one of the most challenging and demanding tasks in recent days. Because the IoT-cloud framework is constructed with an enormous number of sensors that are used to generate a massive amount of data, however, it is more susceptible to vulnerabilities and attacks, which degrades the security level of the network by performing malicious activities. Hence, Artificial Intelligence (AI) technology is the most suitable option for healthcare applications because it provides the best solution for improving the security and reliability of data. Due to this fact, various AI-based security mechanisms are implemented in the conventional works for the IoT-cloud framework. However, it faces significant problems of increased complexity in algorithm design, inefficient data handling, not being suitable for processing the unstructured data, increased cost of IoT sensors, and more time consumption. Therefore, this paper proposed an AI-based intelligent feature learning mechanism named Probabilistic Super Learning- (PSL-) Random Hashing (RH) for improving the security of healthcare data stored in IoT-cloud. Also, this paper is aimed at reducing the cost of IoT sensors by implementing the proposed learning model. Here, the training model has been maintained for detecting the attacks at the initial stage, where the properties of the reported attack are updated for learning the characteristics of attacks. In addition to that, the random key is generated based on the hash value of the data matrix, which is incorporated with the standard Elliptic Curve Cryptography (ECC) technique for data security. Then, the enhanced ECC-RH mechanism performs the data encryption and decryption processes with the generated random hash key. During performance evaluation, the results of both existing and proposed techniques are validated and compared using different performance indicators.
[Retracted] Key Frame Extraction Method for Minors’ Participation in Online Short‐Form Video from the Perspective of Government Administration
Authors: Wu Qiuli
Published: June 2022

With the progress of the Internet era, the audience scope of online short‐form video and live broadcast platform is rapidly expanding. In this situation, the physical and mental health of minors is affected and harmed, and serious social problems have been caused. In view of the random images of minors participating in short online videos, the monitoring department should strengthen supervision and control and establish a good network atmosphere. The focus of surveillance is to identify short‐form videos in which minors participate, monitor the content of short‐form videos, and effectively identify minors. On the basis of analyzing and studying the existing methods of moving object extraction, the method of spatio‐temporal information combined with geometric curve evolution is used to improve the effect of moving object extraction. Firstly, the time dynamic information of video frames is fully utilized and the initial contour of the target is segmented by high‐order statistical algorithm. Based on the improved watershed algorithm, the spatial frames of the original image are segmented and the secondary contour of the target is obtained by combining the spatial and temporal information. The level set evolution algorithm is used to remove the noise and information void in the secondary target, and the final moving target is obtained. Through the extraction of key frames, it can effectively control the appearance of minors in short‐form videos, which can actively guide the benign development of the platform, and put forward governance suggestions based on the perspective of government management.
Clinical Features and Body Composition in Men with Hormone-Sensitive Metastatic Prostate Cancer: A Pilot Study Examining Differences by Race
Authors: Sheean Patricia M. , O’Connor Paula , Joyce Cara , Vasilopoulos Vasilios , Badami Ami , Stolley Melinda
Published: June 2022

Black men treated with frontline therapies for metastatic prostate cancer (MPC) show better clinical outcomes than non-Black men receiving similar treatments. Variations in body composition may contribute to these findings. However, preliminary data are required to support this concept. We conducted a retrospective cohort study for all men with MPC evaluated at our center over a 4-year period, collecting demographic and clinical data (N = 74). Of these, 55 men had diagnostic computed tomography images to quantify adipose tissue and skeletal muscle, specifically sarcopenia and myosteatosis. Nineteen men had repeat imaging to explore changes over time. Frequencies, medians, interquartile ranges, and time to event analyses (hazard ratios (HR); confidence interval (CI)) are presented, stratified by race. Overall, 49% (n = 27) of men had sarcopenia, 49% (n = 27) had myosteatosis, and 29% (n = 16) had sarcopenia and myosteatosis simultaneously. No significant relationship between body mass index (Log-rank

p
=
0.86

; HR: 1.05, 95% CI: 0.45–2.49) or sarcopenia (Log-rank

p
=
0.92

; HR: 1.01, 95% CI: 0.46–2.19) and overall survival was observed. However, the presence of myosteatosis at diagnosis was associated with decreased overall survival (Log-rank

p
=
0.09

; HR: 2.34, 95% CI: 1.05–5.23), with more pronounced (statistically nonsignificant) negative associations for Black (HR: 4.39, 95% CI: 0.92–21.1,

p
=
0.06

) versus non-Black men (HR: 1.89, 95% CI: 0.79–4.54,

p
=
0.16

). Over the median 12.5 months between imaging, the median decline in skeletal muscle was 4% for all men. Black men displayed a greater propensity to gain more adipose tissue than non-Black men, specifically subcutaneous (

p
=
0.01

). Because of the potential for Type II errors in this pilot, future studies should seek to further evaluate the implications of body composition on outcomes. This will require larger, adequately powered investigations with diverse patient representation.
Protective Effects of Amauroderma rugosum on Doxorubicin-Induced Cardiotoxicity through Suppressing Oxidative Stress, Mitochondrial Dysfunction, Apoptosis, and Activating Akt/mTOR and Nrf2/HO-1 Signaling Pathways
Authors: Li Jingjing , Cheng Yanfen , Li Renkai , Wu Xiaoping , Zheng Chengwen , Shiu Polly Ho-Ting , Chan Jacqueline Cho-Ki , Rangsinth Panthakarn , Liu Conghui , Leung Susan Wai-Sum , Lee Simon Ming-Yuen , Zhang Chen , Fu Chaomei , Zhang Jinming , Cheung Timothy Man-Yau , Leung George Pak-Heng
Published: June 2022

Clinical outcomes for doxorubicin (Dox) are limited by its cardiotoxicity but a combination of Dox and agents with cardioprotective activities is an effective strategy to improve its therapeutic outcome. Natural products provide abundant resources to search for novel cardioprotective agents. Ganoderma lucidum (GL) is the most well-known edible mushroom within the Ganodermataceae family. It is commonly used in traditional Chinese medicine or as a healthcare product. Amauroderma rugosum (AR) is another genus of mushroom from the Ganodermataceae family, but its pharmacological activity and medicinal value have rarely been reported. In the present study, the cardioprotective effects of the AR water extract against Dox-induced cardiotoxicity were studied in vitro and in vivo. Results showed that both the AR and GL extracts could potentiate the anticancer effect of Dox. The AR extract significantly decreased the oxidative stress, mitochondrial dysfunction, and apoptosis seen in Dox-treated H9c2 rat cardiomyocytes. However, knockdown of Nrf2 by siRNA abolished the protective effects of AR in these cells. In addition, Dox upregulated the expression of proapoptotic proteins and downregulated the Akt/mTOR and Nrf2/HO-1 signaling pathways, and these effects could be reversed by the AR extract. Consistently, the AR extract significantly prolonged survival time, reversed weight loss, and reduced cardiac dysfunction in Dox-treated mice. In addition, oxidative stress and apoptosis were suppressed, while Nrf2 and HO-1 expressions were elevated in the heart tissues of Dox-treated mice after treatment with the AR extract. However, the GL extract had less cardioprotective effect against Dox in both the cell and animal models. In conclusion, the AR water extract demonstrated a remarkable cardioprotective effect against Dox-induced cardiotoxicity. One of the possible mechanisms for this effect was the upregulation of the mTOR/Akt and Nrf2/HO-1-dependent pathways, which may reduce oxidative stress, mitochondrial dysfunction, and cardiomyocyte apoptosis. These findings suggested that AR may be beneficial for the heart, especially in patients receiving Dox-based chemotherapy.
Establishing a Regulatory Science System for Supervising the Application of Artificial Intelligence for Traditional Chinese Medicine: A Methodological Framework
Authors: He Ying , Wen Qian , Wang Ying , Li Juan , Li Ning , Jin Rongjiang , Li Nian , Zhang Yonggang
Published: June 2022

In this study, we reported a methodological framework for the development of a guideline for establishing a regulatory science system for supervising the application of artificial intelligence for traditional Chinese medicine (TCM). It introduced all of the key steps for developing the guideline as follows: the composition of the guideline expert groups, summary steps, agency, purpose, targeted population, writing, publishing, updating, dissemination, dynamic monitoring, and evaluation. The guideline will provide the basis for national authorities to effectively regulate artificial intelligence technology and enrich the supervisory system for TCM, and it will be of great significance to TCM.
Partial Analysis of the Capsid Protein (VP1) of Human Sapovirus Isolated from Children with Diarrhoea in Rural Communities of South Africa
Authors: Magwalivha Mpho , Ngandu Jean-Pierre Kabue , Traore Afsatou Ndama , Potgieter Natasha
Published: June 2022

Background. Viral diarrhoea is a concern in acute gastroenteritis cases among children younger than 5 years of age. Sapovirus has been noted as an emerging causative agent of acute gastroenteritis worldwide. Objective/Study Design. The aim of this study was to characterize human sapoviruses targeting the VP1 (NVR and N-terminal) region. Twenty-five samples were randomly selected from 40 sapovirus-positive samples previously detected and analyzed for the VP1 region using the One-Step RT-PCR assay. The PCR products were subjected to Sanger sequencing analysis. Results. The polyprotein segment (NVR and N-terminal) was successfully amplified from 10/25 samples. Sapovirus GI.1 was the most predominant strain (6/10; 60%), followed by SV-GII.1 (2/10; 20%) and 10% of each GI.3 and GII.3. Conclusion. Through the partial analysis of the VP1 region, this study provides more data to add on the human sapovirus genetic characterization of circulating strains in South Africa, with the proposition of further analysis of sapovirus VP1 fragments for the viral structure and function.
New Periodic and Localized Traveling Wave Solutions to a Kawahara‐Type Equation: Applications to Plasma Physics
Authors: Alyousef Haifa A. , Salas Alvaro H. , Alharthi M. R. , El-Tantawy S. A.
Published: June 2022

In this study, some new hypotheses and techniques are presented to obtain some new analytical solutions (localized and periodic solutions) to the generalized Kawahara equation (gKE). As a particular case, some traveling wave solutions to both Kawahara equation (KE) and modified Kawahara equation (mKE) are derived in detail. Periodic and soliton solutions to this family are obtained. The periodic solutions are expressed in terms of Weierstrass elliptic functions (WSEFs) and Jacobian elliptic functions (JEFs). For KE, some direct and indirect approaches are carried out to derive the periodic and localized solutions. For mKE, two different hypotheses in the form of WSEFs are used to derive the periodic and localized solutions. Also, the cnoidal wave solutions in the form of JEFs are obtained. As a realistic physical application, the solutions obtained can be dedicated to studying many nonlinear waves that propagate in plasma.
Time Trends for Incidence and Net Survival of Cervical Cancer in Sweden 1960–2014—A Nationwide Population-Based Study
Authors: Sundqvist Avalon , Moberg Louise , Dickman Paul W. , Högberg Thomas , Borgfeldt Christer
Published: June 2022

Background:

The aim was to investigate time trends for incidence and long-term net survival in the morphologic subtypes and stages of cervical cancer in Sweden during the period 1960 to 2014.

Methods:

Women with invasive cervical cancer were identified through the Swedish Cancer Registry. Incidence and net survival were calculated according to morphology, age at diagnosis, and FIGO stage at diagnosis.

Results:

In total, 29,579 cases of invasive cervical cancer between 1960 and 2014 were included. The age-standardized incidence for squamous cell carcinoma (SCC) decreased until 2000; thereafter, the incidence rate stagnated, and a small increase was found in 2014. The incidence of adenocarcinoma continuously increased. The age-standardized 5-year net survival increased. However, decreasing net survival with increasing age was found. A higher stage at diagnosis showed a worse net survival. SCC and adenocarcinoma did not statistically differ as regards net survival in the last years of the study.

Conclusions:

Age-standardized 5-year net survival improved between 1960 and 2014. A positive trend for short- and long-term net survival was seen for women ages 18 to 64 years but long-term net survival for women ≥75 years decreased. In this study, age and FIGO stage at diagnosis were found to be important prognostic factors in determining net survival. The morphologies, SCC, and adenocarcinoma did not statistically differ as regards net survival in the last years of the study.

Impact:

This study demonstrates longitudinal data on cervical cancer in Sweden for over 50 years with sub analyses on morphology, age, and stage at diagnosis.
Association of Abdominal Visceral Adiposity and Total Fat Mass with Cancer Incidence and Mortality in White and Black Adults
Authors: Katzmarzyk Peter T. , Brown Justin C. , Yang Shengping , Mire Emily F. , Wu Xiao-Cheng , Miele Lucio , Ochoa Augusto C. , Zabaleta Jovanny
Published: June 2022

Background:

Race modifies the association between anthropometric measures of obesity and cancer risk. However, the degree to which abdominal visceral adipose tissue (VAT) and total fat mass (FM) are associated with cancer risk is not known.

Methods:

The sample included 3,017 White and 1,347 Black adults who were assessed between 1995 and 2016 and followed for outcome assessment through 2017. Abdominal VAT and FM were measured using imaging techniques. The co-primary endpoints were diagnosis of histologically confirmed invasive cancer (excluding nonmelanoma skin cancer) or death from cancer. Multivariable Cox proportional hazards models quantified the HR of incident cancer and cancer mortality.

Results:

There were 353 incident cancer cases and 75 cancer deaths in an average of 12.9 years of follow-up. Both VAT [HR, 1.21; 95% confidence interval (CI), 1.09–1.36] and FM (HR, 1.25; 95% CI, 1.10–1.43) were significantly associated with incident cancer, while VAT (HR, 1.28; 95% CI, 1.01–1.61) was significantly associated with cancer mortality after adjustment for several covariates. VAT remained significantly associated with cancer incidence (HR, 1.22; 95% CI, 1.03–1.46) after additional inclusion of FM in the multivariable model, but not vice versa. There were no significant sex- or race-interactions.

Conclusions:

VAT was associated with risk of cancer and cancer mortality in this cohort, and the associations did not differ by sex or race. The association between VAT and incident cancer was largely independent of total FM.

Impact:

Our results suggest that utility of anthropometry in assessing obesity-related cancer risk may need to be further refined by including more direct measures of adiposity.
Phase II Trial of Adjuvant Nivolumab Following Salvage Resection in Patients with Recurrent Squamous Cell Carcinoma of the Head and Neck
Authors: Leddon Jennifer L. , Gulati Shuchi , Haque Sulsal , Allen Casey , Palackdharry Sarah , Mathews Maria , Kurtzweil Nicky , Riaz Muhammed Kashif , Takiar Vinita , Nagasaka Misako , Patil Yash , Zender Chad , Tang Alice , Cervenka Brian , McGrath Julie , Korn W. Michael , Hinrichs Benjamin H. , Jandarov Roman , Harun Nusrat , Sukari Ammar , Wise-Draper Trisha M.
Published: June 2022

Purpose:

Locoregional relapse in patients with head and neck squamous cell carcinoma (HNSCC) is common, approaching 50% for some subsites despite multimodality therapy. Salvage surgery is the standard of care, but able to achieve durable control in only a minority of patients. While adjuvant radiotherapy or chemo-radiotherapy is offered to select patients, this approach can be prohibitively toxic. Given the activity and tolerability of programmed death-1 inhibitors in metastatic HNSCC, we investigated the safety and efficacy of adjuvant nivolumab after salvage surgical resection.

Patients and Methods:

This was an open-label, multi-institutional phase II clinical trial (NCT03355560). Patients with recurrent, resectable HNSCC were enrolled within 6 weeks of salvage surgery. Six 28-day cycles of adjuvant nivolumab were planned. The primary endpoint was 2-year disease-free survival (DFS) more than 58%, based on an institutional historical control group of 71 patients with recurrent HNSCC who underwent salvage surgery.

Results:

Between February 2018 and February 2020, 39 patients were enrolled. At a median follow-up of 22.1 months, 2-year DFS was 71.4% [95% confidence interval (CI), 57.8–88.1] and the 2-year overall survival (OS) was 73% (95% CI, 58–91.8). Three of 39 (8%) patients experienced grade 3 treatment-related adverse events and 3 of 39 (8%) discontinued treatment due to side effects. Ten of 39 had locoregional recurrence, while 2 of 10 also had synchronous metastatic disease. There was no difference in DFS between PD ligand-1 (PD-L1)–positive and PD-L1–negative patients. There was a nonsignificant trend toward improved DFS in patients with high tumor mutational burden (P = 0.083).

Conclusions:

Adjuvant nivolumab after salvage surgery in locally recurrent HNSCC is well tolerated and showed improved DFS compared with historical controls.
Artificial Intelligence and Machine Learning Technologies in Cancer Care: Addressing Disparities, Bias, and Data Diversity
Authors: Dankwa-Mullan Irene , Weeraratne Dilhan
Published: June 2022

Artificial intelligence (AI) and machine learning (ML) technologies have not only tremendous potential to augment clinical decision-making and enhance quality care and precision medicine efforts, but also the potential to worsen existing health disparities without a thoughtful, transparent, and inclusive approach that includes addressing bias in their design and implementation along the cancer discovery and care continuum. We discuss applications of AI/ML tools in cancer and provide recommendations for addressing and mitigating potential bias with AI and ML technologies while promoting cancer health equity.
Identifying High-Risk Comorbidities Associated with Opioid Use Patterns Using Electronic Health Record Prescription Data
Authors: Jennings Mariela V. , Lee Hyunjoon , Rocha Daniel B. , Bianchi Sevim B. , Coombes Brandon J. , Crist Richard C. , Faucon Annika B. , Hu Yirui , Kember Rachel L. , Mallard Travis T. , Niarchou Maria , Poulsen Melissa N. , Straub Peter , Urman Richard D. , Walsh Colin G. ,   PsycheMERGE Substance Use Disorder Workgroup, Davis Lea K. , Smoller Jordan W. , Troiani Vanessa , Sanchez-Roige Sandra
Published: June 2022

Introduction: Opioid use disorders (OUDs) constitute a major public health issue, and we urgently need alternative methods for characterizing risk for OUD. Electronic health records (EHRs) are useful tools for understanding complex medical phenotypes but have been underutilized for OUD because of challenges related to underdiagnosis, binary diagnostic frameworks, and minimally characterized reference groups. As a first step in addressing these challenges, a new paradigm is warranted that characterizes risk for opioid prescription misuse on a continuous scale of severity, i.e., as a continuum. Methods: Across sites within the PsycheMERGE network, we extracted prescription opioid data and diagnoses that co-occur with OUD (including psychiatric and substance use disorders, pain-related diagnoses, HIV, and hepatitis C) for over 2.6 million patients across three health registries (Vanderbilt University Medical Center, Mass General Brigham, Geisinger) between 2005 and 2018. We defined three groups based on levels of opioid exposure: no prescriptions, minimal exposure, and chronic exposure and then compared the comorbidity profiles of these groups to the full registries and to those with OUD diagnostic codes. Results: Our results confirm that EHR data reflects known higher prevalence of substance use disorders, psychiatric disorders, medical, and pain diagnoses in patients with OUD diagnoses and chronic opioid use. Comorbidity profiles that distinguish opioid exposure are strikingly consistent across large health systems, indicating the phenotypes described in this new quantitative framework are robust to health systems differences. Conclusion: This work indicates that EHR prescription opioid data can serve as a platform to characterize complex risk markers for OUD using existing data.
Prevalence of Progressive Supranuclear Palsy and Corticobasal Syndrome in Scotland
Authors: Swallow Diane M.A. , Counsell Carl E.
Published: June 2022

Introduction: We estimated the point prevalence of progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS) at regional and national levels in Scotland, UK, as there are few high-quality prevalence studies of these conditions. Methods: Nationally, multiple methods of case ascertainment were used including clinician and nurse specialist referral, searches of ICD-10 diagnostic coding in routinely collected electronic health data (Scottish Morbidity Record), and patient self-referral. In one region, we also searched GP databases and unselected hospital correspondence. Cases were verified by clinical examination or medical record review. National and regional total and age-sex-stratified crude prevalence rates on December 31, 2018, were calculated. Results: The regional crude point prevalence was 4.28 per 100,000 (95% CI 2.90, 6.31) for PSP and 2.05 per 100,000 (95% CI 1.17, 3.59) for CBS. The national crude prevalence rates were lower due to the greater reliance on passive case ascertainment. There were no clear sex differences. At a national level, the peak crude prevalence rate for both PSP and CBS was in the 70–79 age group. Discussion: The prevalence rates of PSP and CBS were similar to previous estimates with little change over the past 20 years.
Perinatal exposure to an aromatase inhibitor glyphosate-base herbicide reduced male and female social behavior in juvenile age and the sexual behavior at adult female rat
Authors: Ricci Esther Lopes , Ribeiro Miriam Oliveira , Fukushima André Rinaldi , Sandini Thaisa Meira , Rocha Paulo Ricardo Dell’Armelina , Waziry Paula Andrea Faria Waziry , Bernardi Maria Martha , Spinosa Helenice de Souza
Published: June 2022

Objectives: The herbicide glyphosate, a pesticide used in agriculture to control weeds, both in food crops and in other agricultural areas, has been identified as an endocrine modulator through the inhibition of aromatase activity and the activation of estrogen receptors. The present study examined the effects of a glyphosate-based herbicide (Roundup® (GLY-BH) on sexual dimorphism of rats after perinatal exposure to low and high GLY-BH in males and females offspring. Methods: Two groups of pregnant rats were treated with two doses of GLY-BH (50 or 150 mg/kg) from day 15 of gestation (GD15) to postnatal day 7 (PND7). Play fighting behavior was observed at the juvenile stage and during social and sexual behaviors in adulthood. Results: Perinatal GLY BH exposure reduced male and female body weight at 28, 75, and 90 days of age. The play fighting behavior was decreased in both sexes, but female rats were more affected. The sexual behaviors were reduced only in females. Conclusions: Perinatal exposure to both doses of GLY-BH promoted sexually dimorphic effects in both juvenile and adulthood stages. These effects were attributed to the inhibition of aromatase activity induced by exposure to GLY-BH in the perinatal period.
Diagnostic Utility of Computed Tomography Perfusion in the Telestroke Setting
Authors: Arora Kshitij , Gaekwad Aaron , Evans James , O’Brien William , Ang Timothy , Garcia-Esperon Carlos , Blair Christopher , Edwards Leon S. , Chew Beng L.A. , Delcourt Candice , Spratt Neil J. , Parsons Mark W. , Butcher Ken S.
Published: June 2022

Background:

Definitive diagnosis of acute ischemic stroke is challenging, particularly in telestroke settings. Although the prognostic utility of CT perfusion (CTP) has been questioned, its diagnostic value remains under-appreciated, especially in cases without an easily visible intracranial occlusion. We assessed the diagnostic accuracy of routine CTP in the acute telestroke setting.

Methods:

Acute and follow-up data collected prospectively from consecutive suspected patients with stroke assessed by a state-wide telestroke service between March 2020 and August 2021 at 12 sites in Australia were analyzed. All patients in the final analysis had been assessed with multimodal CT, including CTP, which was post-processed with automated volumetric software. Diagnostic sensitivity and specificity were calculated for multimodal CT and each individual component (noncontrast CT [NCCT], CT angiogram [CTA], and CTP). Final diagnosis determined by consensus review of follow-up imaging and clinical data was used as the reference standard.

Results:

During the study period, complete multimodal CT examination was obtained in 831 patients, 457 of whom were diagnosed with stroke. Diagnostic sensitivity for ischemic stroke increased by 19.5 percentage points when CTP was included with NCCT and CTA compared with NCCT and CTA alone (73.1% positive with NCCT+CTA+CTP [95% CI, 68.8–77.1] versus 53.6% positive with NCCT+CTA alone [95% CI, 48.9–58.3],
P
<0.001). No difference was observed between specificities of NCCT+CTA and NCCT+CTA+CTP (98.7% [95% CI, 98.5–100] versus 98.7% [95% CI, 96.9–99.6],
P
=0.13). Multimodal CT, including CTP, demonstrated the highest negative predictive value (75.0% [95% CI, 72.1–77.7]). Patients with stroke not evident on CTP had small volume infarcts on follow-up (1.2 mL, interquartile range 0.5–2.7mL).

Conclusions:

Acquisition of CTP as part of a telestroke imaging protocol permits definitive diagnosis of cerebral ischemia in 1 in 5 patients with normal NCCT and CTA.