Practical System Research Articles

Research Progress of Chitosan-based Multifunctional Nanoparticles in Cancer Targeted Therapy.

Conventional tumor therapeutic modalities, such as radiotherapy, chemotherapy, and surgery, involve low tumor inhibition efficiency, non-targeted drug delivery, and side effects. The development of novel and practical nano-drug delivery systems (DDSs) for targeted tumor therapy has become particularly important. Among various bioactive nanoparticles, chitosan is considered a suitable candidate for drug delivery due to its non-toxicity, good biocompatibility, and biodegradability. The amino and hydroxyl groups of chitosan endow it with the diverse function of chemical modification, thereby improving its physical and biological properties to meet the requirements of advanced biomedical applications. Therefore, it is necessary to review the property and applications of chitosan-based materials in biomedicine. In this review, the characteristics of chitosan related to its applications are first introduced, and then the preparation and modification of chitosan-based nanoparticles, including the function tailoring of chitosan-modified nanoparticles, are demonstrated and discussed. Finally, the opportunities and challenges of chitosan-based nanomaterials in this emerging field are proposed from the perspective of the rational and systematic design for the biomedicine field.

Using a Biofeedback-Based Mindfulness Practice System to Enhance Mindfulness and Alleviate Anxiety in College Students: A Randomized Controlled Trial.

Objective: College students experience intense anxiety, for which biofeedback mindfulness techniques show effectiveness in relief. However, typical biofeedback products often lead to user fatigue and boredom because of a single or fixed feedback and lack of focus on mindfulness enhancement. Materials and Methods: In this research, we developed Mindjourney, a VR-based respiratory feedback mindfulness system, designed to enhance mindfulness and alleviate anxiety through continuous/noncontinuous feedback and nonjudgmental reward/punishment for self-perception and attention management. A randomized controlled trial involved 72 college students, split equally into short-term (n = 34, age: 23.11 ± 1.729) and 4-week long-term (n = 38, age: 24.12 ± 1.408) groups, with equal randomization for intervention and control groups. Pre/postintervention tests were measured by using Trait Anxiety Inventory (TAI) and Five Facet Mindfulness Questionnaire (FFMQ) for long-term groups and Galvanic Skin Response and State Anxiety Inventory (SAI) for short-term groups. Results: Results showed that the long-term intervention group showed a significant increase in mindfulness (P = 0.001 for FFMQ total score). Furthermore, observe and act with awareness subscales showed significant increase after intervention (P = 0.034 for observe, P < 0.001 for act with awareness) compared with the control group. Both intervention groups demonstrated a significant decrease in anxiety levels compared with the control groups (P = 0.049 for SAI, P = 0.01 for TAI). Moreover, participants expressed high interest in this biofeedback mindfulness system and willingness for long-term usage. Conclusion: The proposed biofeedback mindfulness practice system could potentially facilitate mindfulness practice and serve as a convenient tool for anxiety relief in campus college students.

Tensions in primary care cancer detection: An embedded qualitative intervention development study.

UK cancer mortality is worse than many other high-income countries, partly due to diagnostic delays in primary care. To understand beliefs and behaviour of GPs, and systems of general practice teams, to inform the Think Cancer! intervention development. An embedded qualitative study guided by behaviour change models (COM-B and TDF) in primary care in Wales, UK. Twenty qualitative, semi-structured telephone interviews with GPs and four face-to-face focus groups with practice teams. Analysis used Framework, results were mapped to multiple, overlapping components of COM-B and TDF. Three themes illustrate (1) complex, multi-level referral considerations facing GPs and practice teams, (2) external influences and constraints, (3) the role of practice systems and culture. Tensions emerged between individual considerations of GPs (Capability, Motivation) and context-dependent external pressures (Opportunity). Detecting cancer was guided not only by external requirements, but also by motivational factors GPs described as part of their cancer diagnostics process. External influences on the diagnosis process often resulted from the primary-secondary care interface and social pressures. GPs adapted their behaviour to deal with this disconnect. Positive practice culture and supportive practice-based systems ameliorated these tensions and complexity. By exploring individual GP behaviours together with practice systems and culture we contribute new understandings on how cancer diagnosis operates in primary care and how delays can be improved. We highlight commonly overlooked dynamics and tensions, experienced by GPs as a tension between individual decision-making (Capability, Motivation) and external considerations such as pressures in secondary care (Opportunity).

Optimal power dispatch in hybrid power system for medium- and large-scale practical power systems using self-adaptive bonobo optimizer algorithm

Incorporating renewable energy sources (RESs) introduces a notable amount of uncertainty in the optimal planning and operation of electrical power grids. Under these circumstances, this paper proposes the application of a recently introduced metaheuristic optimization technique to solve the stochastic optimal power flow (OPF) problem involving wind and solar power sources. The self-adaptive bonobo optimizer (SaBO) is used to minimize three distinct objective functions: (i) Total generation cost (TGC) minimization, including both thermal and wind/solar generation costs, (ii) Power loss minimization, (iii) Combined generation cost and emissions effect minimization. The costs associated with the stochastic generation of wind and solar power included direct costs, reserves and penalty costs from the overestimation and underestimation of available wind and solar power, respectively. The performance of the proposed algorithm is evaluated on two power systems: the modified IEEE 30-bus and the Algerian DZA 114-bus test systems. To demonstrate the efficacy of the SaBO, the obtained results have been compared with those obtained from the Kepler optimization algorithm (KOA) and other recently published optimizers under the same case studies and constraints. The comparative results clearly show the superiority of the SaBO algorithm over all other well-known optimization algorithms provided in the literature for solving the OPF problem. This is evidenced by minimizing total generation costs of 781.2363 $/h for the modified IEEE 30-bus and 16,706.1630 $/h for the Algerian DZA-114-bus system. Furthermore, the integration of RES led to a notable 2.33% and 11.67% reduction in total generation cost for the IEEE 30-bus and Algerian DZA 114-bus systems, respectively, compared to their initial configurations without RESs. The promising findings highlight the powerful of the optimizer to solve non-linear and complex optimization problems in power systems.

Construction of a virtual simulation practical teaching system for intelligent manufacturing under the background of new engineering

Construction of a virtual simulation practical teaching system for intelligent manufacturing under the background of new engineering

#2168 Lupus nephritis histopathological classification system: a questionnaire-based survey of the Renal Pathology Society (RPS)

Abstract Background and Aims Kidney biopsy is the gold standard for lupus nephritis diagnosis, defining histologic class, disease activity and chronicity in detail and providing guidance for treatment. The updated 2018 ISN/RPS histopathological classification in lupus nephritis is widely used for prognosis and treatment decisions. Given the evolving phenotypes of lupus nephritis and the success of new targeted agents in clinical trials, there is ongoing discussion about the need for updating existing classification systems. A survey to assess the current use of the lupus nephritis histopathological classification systems in everyday practice was conducted on behalf of the RPS. Method An online survey was sent between September 27th and October 24th, 2023 to active members of the RPS. The survey used an internet platform and contained both multiple-choice and open-ended questions; results were analyzed anonymously. Results 185 of 562 RPS members replied to the questionnaire. 179 (97%) were pathologists and the level of expertise in lupus nephritis was good: 120 (65%) participants indicated they encounter more than 20 biopsies with lupus nephritis per year, while only 13% encounter fewer than 10. Almost 90% of responders discuss kidney biopsy results in a multidisciplinary meeting involving both clinicians and pathologists, on a weekly or monthly basis. The 2018 ISN/RPS lupus nephritis classification is used in most cases (92%), while 7% of participants prefer the earlier 2004 version. The average grade on the utility of the 2018 ISN/RPS classification was 8 (IQR 7-9) on a scale from 0 (not useful) to 10 (extremely useful). Almost 90% of the pathologist responders indicated they include the NIH activity/chronicity indices in biopsy reports. Reasons for not adding the activity/chronicity indices were given as responses to open-ended questions: (1) clinicians usually do not ask for activity/chronicity indices—(2) the extra workload outweighs the perceived clinical benefit—(3) a quantitative description of the degree of activity/chronicity is less time-consuming and more understandable than the indices—(4) reproducibility is not guaranteed. The average grade on the utility of the activity/chronicity indices was 7 (IQR 7-9) on a scale from 0 (not useful) to 10 (extremely useful). Pathologists rated treating clinicians' understanding of kidney biopsy reports and lupus classification at light microscopy with an average score of 8 (IQR 7-9) on a scale from 0 (no understanding) to 10 (complete understanding). Suggested improvements of the 2018 ISN/RPS lupus nephritis classification were further standardization and simplicity. Clearer definitions were requested for: class III vs class IV; segmental sclerosis vs fibrotic crescents; the role of globally sclerosed glomeruli; lupus-like entities; and lupus podocytopathy. Furthermore, there was a request on guidelines for new parameters: e.g., focus on extraglomerular involvement, laboratory and clinical features and biomarkers; CD68+ staining to detect endocapillary hypercellularity; and EXT1/2 immunostaining. Conclusion Our survey shows the 2018 ISN/RPS lupus nephritis classification is widely used in everyday practice by pathologists, and well known by clinicians. The results obtained by the RPS survey serve as a starting point for the new Working Group of lupus nephritis classification. We will consider the ideas and suggestions of the international community to evaluate biopsies from extensively phenotyped cohorts, to modify the classification and to facilitate improved targeted treatment decisions—a current unmet need.

Development and analysis of a practical absorption air conditioning system employing waste heat recovered from vehicle exhaust

Development and analysis of a practical absorption air conditioning system employing waste heat recovered from vehicle exhaust

Adaptive event-triggered optimal [formula omitted] tracking control for uncertain nonlinear systems: Comparative analysis applied to autonomic tractor-trailer system

In this paper, an event-triggered tracking optimization control method is proposed for nonlinear uncertain systems with H∞ discounted cost. First, the linearization method using the infinite series expansion theorem is given. And the tracking control design problem is solved by appropriate state augment. Secondly, the zero sum differential game strategy is introduced to address the control design problem of uncertain systems with event-triggered inputs. The actor-critic-disturbance networks framework is used to approximate the optimization of event- triggered controller strategy, optimization costs, and the disturbance strategy, respectively. Due to the consideration of discrete time and continuous time dynamics, we put the impulsive system method to use and choose appropriate Lyapunov functions to prove stability and boundedness, at the same time, there will be no infinite triggering situation. Finally, the effectiveness of the proposed scheme is demonstrated by an example of a practical tractor system with n trailers through simulation compared with another typical design method.

Safe System in Practice: A Study of Practitioner Awareness, Support and Implementation

Safe System in Practice: A Study of Practitioner Awareness, Support and Implementation

Nanoscale-Confined Synthesis of 2D Metal Compounds for Electrochemical Applications.

2D metal compounds, such as transition metal dichalcogenides (TMDs), layered double hydroxides (LDHs), and MXenes, are emerging as important electrocatalyst materials in the transition to a sustainable energy future. Aided by their high surface area, electrical conductivity, and tunable electronic properties, these materials have provided a crucial research thrust in enhancing the efficiency of green hydrogen production, fuel cells, and carbon reduction processes. Most importantly, the synthesis of nanostructured 2D compounds, while challenging, is the key to optimizing their catalytic performance. Recent advancements in this field have highlighted the potential of 2D metal compounds in revolutionizing energy conversion technologies, which entails the discovery of new material compositions, the development of novel synthetic routes, and the integration of these materials into practical energy conversion systems. This review presents an overview of the distinctive characteristics of nanoscale-confined 2D metal compounds, the challenges encountered in their synthesis, and electrochemical applications.

Power-exponential and fixed-time consensus of conformable fractional-order quantum cellular neural networks via event-triggered control

Quantum neural networks (QNNs) are considered to be superior to classical ANNs in machine learning, memory capacity, information processing, and quantum system simulation. However, In a practical and complex system, the dynamic behavior of an open quantum system could not be accurately described by an integer-ordered Schrödinger equation. In this paper, the conformable time-fractional-order Schrödinger equation is proposed, and accordingly, the model of conformable fractional-order quantum cellular neural networks (CFOQCNNs) is established and derived from the as-proposed equation. The properties of the conformable fractional-order derivative are studied and several new inequalities regarding the power-exponential and fixed-time convergence of conformable fractional-order systems are obtained. To save the communication resource, we introduce the event-triggered mechanism to construct the controllers and then the power-exponential and fixed-time synchronizations of the master-slave systems derived from the above CFOQCNNs are studied. We also prove the absence of Zeno behaviors regarding the event-triggered strategies. According to the numerical simulation, the dynamic behavior of the CFOQCNNs is discussed and the dissipativity of the CFOQCNNs is briefly revealed. Then the synchronization behaviors of the master and slave CFOQCNNs under power-exponential and fixed-time event-triggered control are demonstrated, where the effectiveness of the event-triggered control strategy is verified. Control behaviors with different fractional orders are also presented. We also discuss the hybrid of power-exponential control and fixed-time control and illustrate the advantages of the hybrid strategy. In the last, we conclude our studies, analyze the drawbacks of this work, and briefly introduce our future research.

Research on Practical Training Mode of Chemical Engineering Specialty from the Perspective of City-Wide Industry-Education Consortium

This paper focuses on the construction of an industry-education consortium in Pingdingshan, Henan Province, analyzing the difficulties in practical training for chemical engineering majors under this background. It initially outlines the “learning site” practical training curriculum system. Building upon this system, it proposes methods for constructing training modules, setting training objectives, enhancing training content, designing training methods, and establishing evaluation criteria. It then summarizes the significance of research on the training model for chemical majors from the perspective of urban-industrial-educational consortiums.

The impact of green finance on companies’ overcapacity: Evidence from green financial reform and innovation policy in China

The Green Financial Reform and Innovation (GFRI) policy not only serves as a crucial tool for facilitating a comprehensive transition towards sustainable practices in economic and social development but also has a significant influence on the operational activities of companies. However, there is limited research on whether the GFRI policy can affect companies’ overcapacity. To address this gap, we use data from the China Stock Market & Accounting Research Database and the Chinese Research Data Services Platform to evaluate the impact of green finance on companies’ overcapacity. The results show that the GFRI policy can effectively alleviate companies’ overcapacity. Moreover, the GFRI policy can alleviate companies’ overcapacity by strengthening market competition, enhancing financing constraints, and promoting innovation. Further, the GFRI policy exerts a more pronounced effect on alleviating overcapacity in non-labor-intensive companies, companies in heavily polluting industries, and companies in regions with weak environmental supervision. This paper not only supplements the relevant literature on alleviating overcapacity but also provides more theoretical support for promoting a national green financial system in practice.

A core competency evaluation index system for the graded use of clinical nurse specialists: A Delphi study.

To describe a grading system that can be used to evaluate core competency of clinical nurse specialists (CNSs) at different levels. Evaluate core competence of CNSs at different levels reflects the quality of nursing and the development of the nursing profession. This research employed the Delphi method. The STROBE checklist for observational cross-sectional studies was followed to report this research study. This study consisted of two main phases: a literature review and semistructured interviews. Individual semistructured interviews were conducted with 11 healthcare experts and two patients. Two rounds of questionnaire surveys were administered to 21 nursing experts using the Delphi method. The CNSs were classified as primary, intermediate or advanced based on their years of work, professional titles and educational qualifications. The graded competency evaluation system consisted of five first-level indicators (clinical practice, consulting guidance and teaching, scientific research innovation, management and discipline development, and ethical decision-making), 15 second level indicators, and 40 third-level indicators. The authority coefficients (Cr) of the experts were .865 and .901. The Kendall's concordance coefficients of the three-level indicators were .417, .289 and .316 for primary CNSs; .384, .294 and .337 for intermediate CNSs; and .489, .289 and .239 for advanced CNSs. The graded use evaluation system in clinical practice initially involves a comprehensive evaluation of the core abilities of CNSs. This is a tool for cultivating and grading the abilities of specialised nurses that can promote a practical upwards spiral. The evaluation system can promote the scientific management and continuous improvement of CNSs in clinical nursing and can serve as a practical and objective reference for the effective management and development of CNSs. Patients participated in the data collection process, during which they shared their health-seeking experience with our research team.

Machine Learning Models for Parkinson Disease: Systematic Review.

With the increasing availability of data, computing resources, and easier-to-use software libraries, machine learning (ML) is increasingly used in disease detection and prediction, including for Parkinson disease (PD). Despite the large number of studies published every year, very few ML systems have been adopted for real-world use. In particular, a lack of external validity may result in poor performance of these systems in clinical practice. Additional methodological issues in ML design and reporting can also hinder clinical adoption, even for applications that would benefit from such data-driven systems. To sample the current ML practices in PD applications, we conducted a systematic review of studies published in 2020 and 2021 that used ML models to diagnose PD or track PD progression. We conducted a systematic literature review in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines in PubMed between January 2020 and April 2021, using the following exact string: "Parkinson's" AND ("ML" OR "prediction" OR "classification" OR "detection" or "artificial intelligence" OR "AI"). The search resulted in 1085 publications. After a search query and review, we found 113 publications that used ML for the classification or regression-based prediction of PD or PD-related symptoms. Only 65.5% (74/113) of studies used a holdout test set to avoid potentially inflated accuracies, and approximately half (25/46, 54%) of the studies without a holdout test set did not state this as a potential concern. Surprisingly, 38.9% (44/113) of studies did not report on how or if models were tuned, and an additional 27.4% (31/113) used ad hoc model tuning, which is generally frowned upon in ML model optimization. Only 15% (17/113) of studies performed direct comparisons of results with other models, severely limiting the interpretation of results. This review highlights the notable limitations of current ML systems and techniques that may contribute to a gap between reported performance in research and the real-life applicability of ML models aiming to detect and predict diseases such as PD.

Attack detection scheme for continuous variable quantum key distribution based on a graph neural network

The practical security of a continuous-variable quantum key distribution (CV-QKD) system is vulnerable to various attack strategies due to the significant difference between the idealized theoretical model and the practical physical system. The existing countermeasures against these attacks involve exploiting different real-time monitoring modules, which presents a challenge in effectively classifying attacks. We investigate a graph neural network (GNN)-based attack detection scheme for CV-QKD, which models data as a graph structure using three different methods for various conditions. Particularly, one of the proposed methods requires no additional devices and can detect attacks with over 99% accuracy. The algorithm can be expanded to different scenarios without additional training and can achieve a detection efficiency of more than 95%. Furthermore, our proposed scheme incorporates anomaly detection algorithms into the detection module, enabling 85% effective detection of partially unknown attacks with minimal security data.

A Grading System for Assessing the Status of the Sphincter of Oddi During Intraoperative Choledochoscopy: A Surgeon's Perspective.

The aim of this study was to establish a simple and practical grading system for evaluating the status of the sphincter of Oddi (SO) during intraoperative choledochoscopy. This system helps identify relevant variables that influence the status of the SO and provides recommendations for preventing stone recurrence. Ninety-three patients were selected retrospectively from a total of 316 patients diagnosed with choledocholithiasis between July 2020 and June 2023. All patients underwent common bile duct (CBD) exploration surgery and intraoperative choledochoscopy. The status of the SO was assessed during choledochoscopy. According to the severity of the condition, the patients were categorized into 4 groups. Data from each group, grades 1, 2, 3, 4, was analyzed statistically. The number of patients in grade 1 was significantly lower than that of the other 3 groups. Except for grade 1, patients in grade 4 exhibited significant differences compared with the other 2 groups in terms of the diameter of the CBD, size of stones, presence of pneumobilia, and history of endoscopic retrograde cholangiopancreatography (ERCP) (P<0.05). There were no significant differences between the groups in terms of sex, age, liver function, number of stones, history of gastrectomy, cholecystectomy, or CBD exploration. The grading system helps us classify different sphincter functions and better understand the formation of choledocholithiasis by subdividing the status of the SO. Endoscopic sphincterotomy (EST) treatment can easily result in the loss of SO function, which increases the risk of stone recurrence.

Indicative mechanism of influence of judicial precedent and judicial practice on the modern legal system of Ukraine

The article examines, in practical and theoretical aspects, of influence of judicial practice and judicial precedent on the modern legal system of Ukraine. Since Ukraine has been granted candidate status for accession to the European Union, significant changes have been taking place in the legal system of Ukraine, particularly in international law norms, where international treaties have become not only obligatory for application within the legal system of Ukraine but also have priority in case of conflicts between national and international legislation. These changes are driven, in part, by the inclusion of judicial power and issues of justice in the negotiating process regarding Ukraine’s membership in the European Union, identified as the most important tasks for Ukraine. This cluster, which opens first and closes last, defines the fundamental aspects of legal and institutional alignment between Ukraine and the European Union. The importance of this cluster lies in the fact that the judicial system and justice play a key role in ensuring the rule of law, democracy, and the protection of human rights. This significantly influences modern judicial practice and envisages an even wider use of existing precedents or precedents being formed. Currently, in the judicial practice of Ukraine, there are processes that can be interpreted as an indicative mechanism influencing the legal system of Ukraine. It involves a qualitatively distinct set of characteristics that were not evident in previous years. This concerns the interrelation between the legal system of Ukraine and contemporary judicial practice with inherent features of normativity of a precedent-based type. There is a mutually conditioned process. On the one hand, judicial practice is becoming increasingly internationalized, meaning it increasingly employs principles, standards, and norms of international treaties, increasingly accepts judicial precedent of varying degrees of formation, and increasingly orients itself toward widely recognized judicial-legal ideas and principles. On the other hand, the legal system of Ukraine provides for the possibility of effective control over the implementation of international acts within the framework of judicial practice, including the use of judicial precedent to a certain extent and in certain areas of application. Thus, judicial practice, utilizing judicial precedents of national and international origin, serves as an indicative mechanism for analyzing the legal system. Actual judicial practice becomes an indicator of the development of the legal system and its adequacy to contemporary socio-legal and state-legal processes.

Safety and efficacy evaluation of Simo decoction and Arecae semen in herbal medicine practice

ObjectiveThe traditional Chinese patent medicine (TCPM), Simo decoction (Simo decoction oral solution), with its primary ingredient Arecae semen (Binglang, Areca catechu L.), known for its potential carcinogenic effects, is the subject of this study. The research aims to analyze the effectiveness and potential risks of Simo decoction, particularly as a carcinogen, and to suggest a framework for evaluating the risks and benefits of other herbal medicines. MethodsThe study is based on post-marketing research of Simo decoction and Arecae semen. It utilized a wide range of sources, including ancient and modern literature, focusing on the efficacy and safety of Simo decoction. The research includes retrospective data on the sources, varieties, and toxicological studies of Arecae semen from databases such as Pubmed, Clinical Trials, Chinese Clinical Trial Registry, China National Knowledge Infrastructure, WHO-UMC Vigibase, and China National Center for ADR Monitoring. ResultsCommon adverse drug reactions (ADRs) associated with Simo decoction include skin rash, nausea, vomiting, abdominal pain, and diarrhea. However, no studies exist reporting the severe ADRs, such as carcinogenic effects. Arecae semen is distributed across approximately 60 varieties in tropical Asia and Australia. According to the WHO-UMC Vigibase and the National Adverse Drug Reaction Monitoring System databases, there are currently no reports of toxicity related to Arecae semen in the International System for Classification of ADRs (ISCR) or clinical studies. ConclusionRisk-benefit analysis in TCPM presents more challenges compared to conventional drugs. The development of a practical pharmacovigilance system and risk-benefit analysis framework is crucial for marketing authorization holders, researchers, and regulatory bodies. This approach is vital for scientific supervision and ensuring the safety and efficacy of drug applications, thus protecting public health.

Reaction Environment Regulation for Electrocatalytic CO2 Reduction in Acids

AbstractThe electrocatalytic CO2 reduction reaction (CO2RR) is a sustainable route for converting CO2 into value‐added fuels and feedstocks, advancing a carbon‐neutral economy. The electrolyte critically influences CO2 utilization, reaction rate and product selectivity. While typically conducted in neutral/alkaline aqueous electrolytes, the CO2RR faces challenges due to (bi)carbonate formation and its crossover to the anolyte, reducing efficiency and stability. Acidic media offer promise by suppressing these processes, but the low Faradaic efficiency, especially for multicarbon (C2+) products, and poor electrocatalyst stability persist. The effective regulation of the reaction environment at the cathode is essential to favor the CO2RR over the competitive hydrogen evolution reaction (HER) and improve long‐term stability. This review examines progress in the acidic CO2RR, focusing on reaction environment regulation strategies such as electrocatalyst design, electrode modification and electrolyte engineering to promote the CO2RR. Insights into the reaction mechanisms via in situ/operando techniques and theoretical calculations are discussed, along with critical challenges and future directions in acidic CO2RR technology, offering guidance for developing practical systems for the carbon‐neutral community.