气象观测场在汽车试验场中的应用研究

汽车试验场作为汽车开展道路测试的重要场所,用于验证汽车产品的品质以及可靠性。除了场地道路外,气象条件作为汽车道路测试的重要一环,在《GB/T12534-1990汽车道路试验方法通则》中也有明确要求,如:试验时应是无雨无雾天气,相对湿度小于95%,气温0-40℃,风速不大于3m/s。同时气象条件也作为试验场道路管控的重要依据,实时风速、雨量、能见度等信息为场地管理者发布限速、限行、封场等通知提供必要参考依据,直接影响道路测试安全管控的及时性。因此,文章从气象观测场的建设、气象服务、异常天气道路管控等方面开展气象观测场在汽车试验场中的应用研究。

Intelligent Biometric Information Management

We advance here a novel methodology for robust intelligent biometric information management with inferences and predictions made using randomness and complexity concepts. Intelligence refers to learning, adap- tation, and functionality, and robustness refers to the ability to handle incomplete and/or corrupt adversarial information, on one side, and image and or device variability, on the other side. The proposed methodology is model-free and non-parametric. It draws support from discriminative methods using likelihood ratios to link at the conceptual level biometrics and forensics. It further links, at the modeling and implementation level, the Bayesian framework, statistical learning theory (SLT) using transduction and semi-supervised lea- rning, and Information Theory (IY) using mutual information. The key concepts supporting the proposed methodology are a) local estimation to facilitate learning and prediction using both labeled and unlabeled data;b) similarity metrics using regularity of patterns, randomness deficiency, and Kolmogorov complexity (similar to MDL) using strangeness/typicality and ranking p-values;and c) the Cover – Hart theorem on the asymptotical performance of k-nearest neighbors approaching the optimal Bayes error. Several topics on biometric inference and prediction related to 1) multi-level and multi-layer data fusion including quality and multi-modal biometrics;2) score normalization and revision theory;3) face selection and tracking;and 4) identity management, are described here using an integrated approach that includes transduction and boosting for ranking and sequential fusion/aggregation, respectively, on one side, and active learning and change/ outlier/intrusion detection realized using information gain and martingale, respectively, on the other side. The methodology proposed can be mapped to additional types of information beyond biometrics.

Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

Tamanu Oil in Acne Management: Potential Anti-Inflammatory and Wound-Healing Properties for Scar Reduction

Tamanu oil, derived from the nuts of Calophyllum inophyllum, has gained increasing attention for its potential in acne management due to its purported anti-inflammatory and wound-healing properties. This analysis evaluates the efficacy of tamanu oil in acne treatment with a specific focus on its impact on inflammation and scar reduction. The novelty of this research lies in its comprehensive analysis of tamanu oil’s dual mechanism of action: reducing acne-related inflammation and promoting the healing of acne scars. Clinical trials and laboratory analyses were conducted to assess the oil’s effectiveness in diminishing erythema, swelling, and post-acne scarring compared to conventional treatments. Preliminary findings demonstrate that tamanu oil significantly reduces inflammation and accelerates wound healing, potentially offering a promising adjunct or alternative to standard acne therapies. Future research should aim to optimize formulation and application protocols, long-term effects, and comparative therapeutic efficacy with other anti-inflammatory agents. Tamanu oil offers a novel and effective approach to acne management, with potential advantages that go beyond inflammation reduction to include enhanced scar reduction, making it a subject that warrants further investigation.

Management and Construction of University Books and Materials Under the Background of the Internet

The rapid development and popularization of Internet technology has provided important support for the informatization reform of various industries.University books and materials have the characteristics of large quantities and difficult storage and management.Its digital storage and management platform construction can effectively realize the digital storage and real-time retrieval of books and materials,and help students and teachers to find and use books and materials more quickly.Especially in recent years,with the update of intelligent platforms and other technologies,the resource-sharing platform of university books and materials can realize more convenient book information retrieval without the limitation of time and space.This paper mainly explores the optimization path and platform construction scheme of university libraries and information management under the background of the Internet,hoping to provide some theoretical references for university library managers.

Leveraging Predictive Analytics for Strategic Corporate Communications: Enhancing Stakeholder Engagement and Crisis Management

This study explores the integration of predictive analytics in strategic corporate communications, with a specific focus on stakeholder engagement and crisis management. Our mixed-methods approach, which combines a comprehensive literature review with case studies of five multinational corporations, allows us to investigate the applications, challenges, and ethical implications of leveraging predictive models in communication strategies. While our findings reveal significant potential for enhancing personalized content delivery, real-time sentiment analysis, and proactive crisis management, we stress the need for careful consideration of challenges such as data privacy concerns and algorithmic bias. This emphasis on ethical implementation is crucial in navigating the complex landscape of predictive analytics in corporate communications. To address these issues, we propose a framework that prioritizes ethical considerations. Furthermore, we identify key areas for future research, thereby contributing to the evolving field of data-driven communication management.

The Danger within:Covid-19 Affinity for ACE2 Receptors in Adipose Tissue and Testes.The Protective Effects of Estradiol,Fitness,and Weight Management

The imminent danger of the Covid-19 pandemic has accelerated research in pharmaceuticals that either target the viral Spike proteins fusion with ACE2 receptors,or the infectious RNA replication that often overwhelms immune defences.The scope of this review was to elucidate the main human vulnerabilities to Covid-19,including the accumulation of ACE2 receptors in testes,adipose tissue,thyroid,heart and kidneys that escalate viral affinity in males,the aged,and certain medical conditions,including diabetes,CVD,and pulmonary diseases.Pre-existing inflammation inherent in obesity may exacerbate the“cytokine storm,”a rampaging immune reaction during the course of Covid-19 that is deleterious to the host.We examined the molecular dynamics illustrating the action of new therapeutics necessary for Covid-19 patients;the estradiol advantage hypothesis;alternative therapies including hormone replacement procedures and mesenchymal stem cells;plus preventive and protective interventions.The current perspective also explored the primary components of dysregulated health predisposing individuals to Covid-19,including hormonal imbalance,increased lipids and lipoproteins,thyroid dysfunction,degraded fitness,and age-related testosterone decline accompanied by cortisol increase that provokes stress eating behaviours and weight accumulation.Obesity increases the probability of Covid-19 infection due to its abundance of ACE2 receptors;while physical activity may decrease Covid-19 vulnerability,by reducing fat and increasing muscle mass that manifests a relatively inhibited ACE2 expression.Several weight management solutions feature lasers and radiofrequency which diminish subcutaneous adiposity but do not enhance fitness.A data metanalysis of seven recently published clinical studies on 95 obese individuals,73 males and 22 females with an average BMI of 30.9,demonstrated visceral fat reduction combined with increased skeletal muscle mass.It also revealed a statistically significant decrease in BMI,lipids,lipoproteins,inflammation and toxicity as measured by CRP,Creatinine and Bilirubin respectively,juxtaposed by optimally healthier levels of Cortisol,Testosterone,Free T3,IGF-1,Insulin,and the appetite controlling hormones Leptin and Ghrelin.

Balancing Dermatological and Gynecological Considerations: Evaluating the Necessity of Pelvic Exams in OCP Prescriptions for Acne Management

Routine pelvic examinations in women prescribed oral contraceptive pills (OCPs) for acne management are scrutinized to assess their impact on dermatological outcomes versus gynecological health. A synthesis of clinical trials, patient surveys, and medical guidelines reveals that these routine exams do not significantly enhance the effectiveness of acne treatment with OCPs but are linked to increased patient discomfort and false-positive results. Evidence suggests that routine pelvic examinations do not significantly impact the effectiveness of acne management with OCPs but are associated with increased patient discomfort and higher rates of false-positive results. The analysis indicates that a more personalized approach, focusing on selective pelvic examinations based on individual risk factors and clinical symptoms, may offer a more practical and patient-centered alternative. The review advocates for a reexamination of existing guidelines to better align with a model of individualized care, emphasizing the need for further research to optimize best practices at the intersection of dermatological and gynecological care. Adopting a personalized approach to pelvic examinations could substantially improve patient care by minimizing unnecessary interventions and discomfort while maintaining the efficacy of acne treatment with oral contraceptive pills.

Is Alzheimer’s Disease an Adaptability Disorder? What Role Does Happiness Have in Treatment, Management and Prevention

A case presentation indicating the importance of “happiness” in childhood causing memory block until the patent presented with probable mixed vascular and neurodegenerative memory loss at 60 years of age is presented to highlight the role of emotional factors in causing the disease. The question of whether Alzheimer’s disease is an adaptability disorder is raised, given the patient blocked out her memory of her childhood experience. The importance of “happiness” as a treatment goal raises issues of advocacy and Guardianship as well as capacity, which is addressed by actual case reference and court action in defence of the patient’s rights to have their wishes respected and observed. Functional mental capacity assessment, using the Functional Mental State Measure (FMSM) gives a greater indication of neuronal reserve than standard cognitive testing, as it helps to unravel the dilemma associated with pure cognitive assessment in Alzheimer’s Disease as well as vascular dementia patients and patients who, despite retained and intact functional capacity and ability to express their wishes, i.e. “best interest”, are “wrongly” placed under Guardianship. Maladaptive responses, to control the change in external environment that are sensed or perceived, and which lead to disorder or to susceptibility to disease, exemplify a General Systems Theory approach, in which appropriate and adequate responses to environmental change, in behavioural terms, by a person, whether independently, or as the recipient or giver, or both, leads to functional interaction and happiness.

Drugs used for pain management in gastrointestinal surgery and their implications

Pain is the predominant symptom troubling patients.Pain management is one of the most important aspects in the management of surgical patients leading to early recovery from surgical procedures or in patients with chronic diseases or malignancy.Various groups of drugs are used for dealing with this;however,they have their own implications in the form of adverse effects and dependence.In this article,we review the concerns of different pain-relieving medicines used postoperatively in gastrointestinal surgery and for malignant and chronic diseases.

Security Monitoring and Management for the Network Services in the Orchestration of SDN-NFV Environment Using Machine Learning Techniques

Software Defined Network(SDN)and Network Function Virtualization(NFV)technology promote several benefits to network operators,including reduced maintenance costs,increased network operational performance,simplified network lifecycle,and policies management.Network vulnerabilities try to modify services provided by Network Function Virtualization MANagement and Orchestration(NFV MANO),and malicious attacks in different scenarios disrupt the NFV Orchestrator(NFVO)and Virtualized Infrastructure Manager(VIM)lifecycle management related to network services or individual Virtualized Network Function(VNF).This paper proposes an anomaly detection mechanism that monitors threats in NFV MANO and manages promptly and adaptively to implement and handle security functions in order to enhance the quality of experience for end users.An anomaly detector investigates these identified risks and provides secure network services.It enables virtual network security functions and identifies anomalies in Kubernetes(a cloud-based platform).For training and testing purpose of the proposed approach,an intrusion-containing dataset is used that hold multiple malicious activities like a Smurf,Neptune,Teardrop,Pod,Land,IPsweep,etc.,categorized as Probing(Prob),Denial of Service(DoS),User to Root(U2R),and Remote to User(R2L)attacks.An anomaly detector is anticipated with the capabilities of a Machine Learning(ML)technique,making use of supervised learning techniques like Logistic Regression(LR),Support Vector Machine(SVM),Random Forest(RF),Naïve Bayes(NB),and Extreme Gradient Boosting(XGBoost).The proposed framework has been evaluated by deploying the identified ML algorithm on a Jupyter notebook in Kubeflow to simulate Kubernetes for validation purposes.RF classifier has shown better outcomes(99.90%accuracy)than other classifiers in detecting anomalies/intrusions in the containerized environment.

Conflict and Emergency Management in a Post-Liberal World

The world is steadily moving to the post-liberal order with the urgent need of novel organizational and security approaches,also new levels of international cooperation,in order to support its stability and prosperity.The developed high-level Spatial Grasp Technology(SGT)and its Spatial Grasp Language(SGL)are briefed which may be particularly useful for solving numerous conflicts and crises problems emerging in different areas during this transitional period,in both local and global scale.SGT employs unlimited spatial scenario mobility and parallel holistic matching of distributed systems,with numerous communicating SGL interpreters potentially installed worldwide.Basic network creation and management operations are described in SGL which may operate on top of existing communication systems or serve individually as high level network protocols in case of non-local crises and disasters.Different operations on social networks are presented in SGL including finding strongest and weakest components with resultant changing of network topologies,also determining distances between different communities for preventing and predicting social conflicts.Fully distributed analysis,and tracing and simulation of multiple mobile objects in distributed spaces with complex routes are shown in SGL related to cruise missiles,defence objects and debris in outer space,as well as massively moving refugees through international borders.The proposed technology had trial implementations and applications in different countries,and its latest version can be readily installed by agreement on any platforms needed.

Erratum to “Is Alzheimer’s Disease an Adaptability Disorder? What Role Does Happiness Have in Treatment, Management and Prevention” [World Journal of Neuroscience 5 (2015) 180-188]

A case presentation indicating the importance of “happiness” in childhood causing memory block until the patent presented with probable mixed vascular and neurodegenerative memory loss at 60 years of age is presented to highlight the role of emotional factors in causing the disease. The question of whether Alzheimer’s disease is an adaptability disorder is raised, given the patient blocked out her memory of her childhood experience. The importance of “happiness” as a treatment goal raises issues of advocacy and Guardianship as well as capacity, which is addressed by actual case reference and court action in defence of the patient’s rights to have their wishes respected and observed. Functional mental capacity assessment, using the Functional Mental State Measure (FMSM) gives a greater indication of neuronal reserve than standard cognitive testing, as it helps to unravel the dilemma associated with pure cognitive assessment in Alzheimer’s Disease as well as vascular dementia patients and patients who, despite retained and intact functional capacity and ability to express their wishes, i.e. “best interest”, are “wrongly” placed under Guardianship. A General Systems approach, which recognises functional interaction as optimal and withdrawal or inadequate and/or inappropriate response as not, provides further understanding of the relationship between emotional factors, memory and neurodegenerative (Alzheimer’s) disease.

Understanding Osteoporosis: Pathophysiology, Risk Factors, Diagnosis, and Management

Osteoporosis is a systemic skeletal disease characterized by low bone mineral density (BMD) and deterioration of bone architecture, resulting in reduced bone strength and, consequently, increased susceptibility to fractures which poses a significant public health concern worldwide, particularly in aging populations [1]. The health-economic impact of vertebral and hip fractures has been extensively explored and it is well known that these fractures are associated with morbidity/disability and increased mortality;they also account for a substantial portion of the direct fracture costs. This review aims to provide a comprehensive overview of osteoporosis, including its pathophysiology, risk factors, diagnostic approaches, and management strategies. By elucidating the multifaceted nature of this condition, healthcare providers can better identify individuals at risk, implement preventive measures, and optimize treatment to reduce the burden of osteoporotic fractures.

Is medical management useful in Moyamoya disease?

Moyamoya disease(MMD),characterized by progressive internal carotid artery stenosis and collateral vessel formation,prompts cerebral perfusion complications and is stratified into idiopathic and Moyamoya syndrome subtypes.A multifa-ceted approach toward MMD management addresses cerebral infarctions through revascularization surgery and adjunctive medical therapy,while also navigating risks such as intracranial hemorrhage and cerebral infarction resulting from arte-rial stenosis and fragile collateral vessels.Addressing antithrombotic management reveals a potential role for treatments like antiplatelet agents and anticoagulants,despite the ambiguous contribution of thrombosis to MMD-related infarctions and the critical balance between preventing ischemic events and averting hemo-rrhagic complications.Transcranial doppler has proven useful in thromboembolic detection,despite persisting challenges concerning the efficacy and safety of an-tithrombotic treatments.Furthermore,antihypertensive interventions aim to ma-nage blood pressure meticulously,especially during intracerebral hemorrhage,with recommendations and protocols varying based on the patient’s hypertension status.Additionally,lipid-lowering therapeutic strategies,particularly employing statins,are appraised for their possible beneficial role in MMD management,even as comprehensive data from disease-specific clinical trials remains elusive.Com-prehensive guidelines and protocols to navigate the multifaceted therapeutic ave-nues for MMD,while maintaining a delicate balance between efficacy and safety,warrant further meticulous research and development.This protocol manuscript seeks to elucidate the various aspects and challenges imbued in managing and navigating through the complex landscape of MMD treatment.

A Framework for Intelligent Decision Support System for Traffic Congestion Management System

Traffic congestion problem is one of the major problems that face many transportation decision makers for urban areas. The problem has many impacts on social, economical and development aspects of urban areas. Hence the solution to this problem is not straight forward. It requires a lot of effort, expertise, time and cost that sometime are not available. Most of the existing transportation planning software, specially the most advanced ones, requires personnel with lots practical transportation planning experience and with high level of education and training. In this paper we propose a comprehensive framework for an Intelligent Decision Support System (IDSS) for Traffic Congestion Management System that utilizes a state of the art transportation network equilibrium modeling and providing an easy to use GIS-based interaction environment. The developed IDSS reduces the dependability on the expertise and level of education of the transportation planners, transportation engineers, or any transportation decision makers.

Management of lateral pelvic lymph nodes in rectal cancer:Is it time to reach an Agreement?

In this editorial,we proceed to comment on the article by Chua et al,addressing the management of metastatic lateral pelvic lymph nodes(mLLN)in stage II/III rectal cancer patients below the peritoneal reflection.The treatment of this nodal area sparks significant controversy due to the strategic differences followed by Eastern and Western physicians,albeit with a higher degree of convergence in recent years.The dissection of lateral pelvic lymph nodes without neoadjuvant therapy is a standard practice in Eastern countries.In contrast,in the West,preference leans towards opting for neoadjuvant therapy with chemoradiotherapy or radiotherapy,that would cover the treatment of this area without the need to add the dissection of these nodes to the total mesorectal excision.In the presence of high-risk nodal characteristics for mLLN related to radiological imaging and lack of response to neoadjuvant therapy,the risk of lateral local recurrence increases,suggesting the appropriate selection of strategies to reduce the risk of recurrence in each patient profile.Despite the heterogeneous and retrospective nature of studies addressing this area,an international consensus is necessary to approach this clinical scenario uniformly.

AI-Driven Learning Management Systems:Modern Developments, Challenges and Future Trends during theAge of ChatGPT

COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus.The foremost and most prime sector among those affected were schools,colleges,and universities.The education system of entire nations had shifted to online education during this time.Many shortcomings of Learning Management Systems(LMSs)were detected to support education in an online mode that spawned the research in Artificial Intelligence(AI)based tools that are being developed by the research community to improve the effectiveness of LMSs.This paper presents a detailed survey of the different enhancements to LMSs,which are led by key advances in the area of AI to enhance the real-time and non-real-time user experience.The AI-based enhancements proposed to the LMSs start from the Application layer and Presentation layer in the form of flipped classroom models for the efficient learning environment and appropriately designed UI/UX for efficient utilization of LMS utilities and resources,including AI-based chatbots.Session layer enhancements are also required,such as AI-based online proctoring and user authentication using Biometrics.These extend to the Transport layer to support real-time and rate adaptive encrypted video transmission for user security/privacy and satisfactory working of AI-algorithms.It also needs the support of the Networking layer for IP-based geolocation features,the Virtual Private Network(VPN)feature,and the support of Software-Defined Networks(SDN)for optimum Quality of Service(QoS).Finally,in addition to these,non-real-time user experience is enhanced by other AI-based enhancements such as Plagiarism detection algorithms and Data Analytics.

PhishGuard: Integrating Fine-Tuned Large Language Models (LLMs) into Password Management

In the digital age, phishing attacks have been a persistent security threat leveraged by traditional password management systems that are not able to verify the authenticity of websites. This paper presents an approach to embedding sophisticated phishing detection within a password manager’s framework, called PhishGuard. PhishGuard uses a Large Language Model (LLM), specifically a fine-tuned BERT algorithm that works in real time, where URLs fed by the user in the credentials are analyzed and authenticated. This approach enhances user security with its provision of real-time protection from phishing attempts. Through rigorous testing, this paper illustrates how PhishGuard has scored well in tests that measure accuracy, precision, recall, and false positive rates.

Design and Implementation of Book Recommendation Management System Based on Improved Apriori Algorithm

The traditional Apriori applied in books management system causes slow system operation due to frequent scanning of database and excessive quantity of candidate item-sets, so an information recommendation book management system based on improved Apriori data mining algorithm is designed, in which the C/S (client/server) architecture and B/S (browser/server) architecture are integrated, so as to open the book information to library staff and borrowers. The related information data of the borrowers and books can be extracted from books lending database by the data preprocessing sub-module in the system function module. After the data is cleaned, converted and integrated, the association rule mining sub-module is used to mine the strong association rules with support degree greater than minimum support degree threshold and confidence coefficient greater than minimum confidence coefficient threshold according to the processed data and by means of the improved Apriori data mining algorithm to generate association rule database. The association matching is performed by the personalized recommendation sub-module according to the borrower and his selected books in the association rule database. The book information associated with the books read by borrower is recommended to him to realize personalized recommendation of the book information. The experimental results show that the system can effectively recommend book related information, and its CPU occupation rate is only 6.47% under the condition that 50 clients are running it at the same time. Anyway, it has good performance.