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A multimodal device for assessing the metabolic status of tissues during minimally invasive surgeries is proposed. The hardware and software system and specially developed fine-needle fiber-optic probes support assessment of the fluorescence of the main tissue fluorophores, as well as tissue saturation. The approach proposed here addresses a number of clinical problems, including the differentiation of healthy and tumor tissues and determination of the metabolic status of neoplasms and the functional state of organs. The system can be used for intraoperative diagnostics in various areas of minimally invasive surgery. [ABSTRACT FROM AUTHOR]

This study addresses the development of a prototype device for studying cellular structures of various types, including spheroids consisting of tumor cells, in a microfluidic format. The work demonstrates that a microfluidic system (MFS) can be used for effective evaluation of the efficacies of antitumor pharmaceuticals. The MFS supports parallel analysis of small-volume samples obtained by from patients by biopsy and can also be used to study the movement and migration of tumor spheroids. The results obtained here lead to the conclusion that the system has promise for personalized and targeted therapy. [ABSTRACT FROM AUTHOR]

Background: The purpose of this report is to provide insight and details regarding the development and implementation of an injury and illness surveillance (IIS) system for the United States Olympic and Paralympic Committee (USOPC). Methods: The development and deployment of the IIS employed a multiphase approach. First, researchers determined variables to include in the IIS using the recommendations from the 2020 IOC consensus statement for reporting sport epidemiological data. Second, the hosting and deployment platforms were comprehensively evaluated for their suitability, ease of use, flexibility, and backend data structure (for both capture and aggregation). Third, focus groups consisting of the Sports Medicine department leadership and clinicians piloted the IIS system and revisions were made based on their feedback. Pilot testing of the IIS and follow-up focus groups were then conducted among all departmental clinicians to solicit additional feedback and drive further revisions. Finally, the IIS system was piloted among providers working during the 2023 Pan American and Parapan American Games to refine the system for future Games. After reviewing all potential software platform options (electronic medical record [EMR] system, athlete management systems, secure data collection platforms), Qualtrics (Qualtrics, Provo, UT, USA) was selected to host the IIS system. This choice was made due to the inability of the EMR and athlete-management systems to make frequent updates, modify existing questions, and provide the necessary form logic for the variety of scenarios in which the IIS system would be deployed. Feedback from the department's leadership and clinicians resulted in a number of changes, most notably being the ability to enter multiple diagnoses for a single injury event. Additionally, clinician feedback resulted in the creation of additional diagnostic codes not currently present in the OSIICS v14.0 diagnostic coding system, adding "non-sport" as an additional variable for injury setting, and developing a system for reporting return-to-sport date for time-loss injuries. Discussion: A multi-stage process of extensive planning, stakeholder feedback, and ongoing updates is required in order to successfully develop and implement an IIS system within a National Olympic and Paralynpic Committee. This process can be used to inform the development and implementation of IIS systems in other sporting organizations. [ABSTRACT FROM AUTHOR]

Middle-ear conditions are common causes of primary care visits, hearing impairment, and inappropriate antibiotic use. Deep learning (DL) may assist clinicians in interpreting otoscopic images. This study included patients over 5 years old from an ambulatory ENT practice in Strasbourg, France, between 2013 and 2020. Digital otoscopic images were obtained using a smartphone-attached otoscope (Smart Scope, Karl Storz, Germany) and labeled by a senior ENT specialist across 11 diagnostic classes (reference standard). An Inception-v2 DL model was trained using 41,664 otoscopic images, and its diagnostic accuracy was evaluated by calculating class-specific estimates of sensitivity and specificity. The model was then incorporated into a smartphone app called i-Nside. The DL model was evaluated on a validation set of 3,962 images and a held-out test set comprising 326 images. On the validation set, all class-specific estimates of sensitivity and specificity exceeded 98%. On the test set, the DL model achieved a sensitivity of 99.0% (95% confidence interval: 94.5–100) and a specificity of 95.2% (91.5–97.6) for the binary classification of normal vs. abnormal images; wax plugs were detected with a sensitivity of 100% (94.6–100) and specificity of 97.7% (95.0–99.1); other class-specific estimates of sensitivity and specificity ranged from 33.3% to 92.3% and 96.0% to 100%, respectively. We present an end-to-end DL-enabled system able to achieve expert-level diagnostic accuracy for identifying normal tympanic aspects and wax plugs within digital otoscopic images. However, the system's performance varied for other middle-ear conditions. Further prospective validation is necessary before wider clinical deployment. [ABSTRACT FROM AUTHOR]

When integrating AI tools in healthcare settings, complex interactions between technologies and primary users are not always fully understood or visible. This deficient and ambiguous understanding hampers attempts by healthcare organizations to adopt AI/ML, and it also creates new challenges for researchers to identify opportunities for simplifying adoption and developing best practices for the use of AI-based solutions. Our study fills this gap by documenting the process of designing, building, and maintaining an AI solution called SepsisWatch at Duke University Health System. We conducted 20 interviews with the team of engineers and scientists that led the multi-year effort to build the tool, integrate it into practice, and maintain the solution. This "Algorithm Journey Map" enumerates all social and technical activities throughout the AI solution's procurement, development, integration, and full lifecycle management. In addition to mapping the "who?" and "what?" of the adoption of the AI tool, we also show several 'lessons learned' throughout the algorithm journey maps including modeling assumptions, stakeholder inclusion, and organizational structure. In doing so, we identify generalizable insights about how to recognize and navigate barriers to AI/ML adoption in healthcare settings. We expect that this effort will further the development of best practices for operationalizing and sustaining ethical principles—in algorithmic systems. [ABSTRACT FROM AUTHOR]

To improve medication adherence, we co-developed a digital, artificial intelligence (AI)-driven nudge intervention with stakeholders (patients, providers, and technologists). We used a human-centred design approach to incorporate user needs in creating an AI-driven nudge tool. We report the findings of the first stage of a multi-phase project: understanding user needs and ideating solutions. We interviewed healthcare providers (n = 10) and patients (n = 10). Providers also rated example nudge interventions in a survey. Stakeholders felt the intervention could address existing deficits in medication adherence tracking and were optimistic about the solution. Participants identified flexibility of the intervention, including mode of delivery, intervention intensity, and the ability to stratify to user ability and needs, as critical success factors. Reminder nudges and provision of healthcare worker contact were rated highly by all. Conversely, patients perceived incentive-based nudges poorly. Finally, participants suggested that user burden could be minimised by leveraging existing software (rather than creating a new App) and simplifying or automating the data entry requirements where feasible. Stakeholder interviews generated in-depth data on the perspectives and requirements for the proposed solution. The participatory approach will enable us to incorporate user needs into the design and improve the utility of the intervention. Our findings show that an AI-driven nudge tool is an acceptable and appropriate solution, assuming it is flexible to user requirements. [ABSTRACT FROM AUTHOR]

China is making great efforts to build an ecological civilization. To reveal the effectiveness and spatial characteristics of the ecological civilization development in China, we constructed an Ecological Civilization Evaluation Index (ECI) based on the economic-social-natural complex system. We evaluated the development level of the ecological civilization in China from 2004 to 2020 and discussed the coupling and coordination relationship between subsystems. We found that the ecological civilization of China has achieved remarkable results. The relationship among the three subsystems has been improved to some extent, but the high-quality development of the economic system still requires effort. The development level of the ecological civilization in China presents spatial heterogeneity. From east to west, 30 provinces can be classified into four different types of development. On the whole, the development of China's ecological civilization has provided experiences for the world. [ABSTRACT FROM AUTHOR]

China's concept of "ecological civilization" can be understood as a new system of development and governance based on the perspective of political decision-making. Environmental management, ecological restoration, and green development are its primary principles—distinctly different from industrial and agricultural-oriented civilizations. In this paper, we evaluate the evolution of political connotations of the ecological civilization concept in China over the past 15 years through a textual analysis approach. Additionally, we systematically outline an ecological civilization indicator system and analyze its evolutionary process, applicable scales, and role in guiding the implementation of the ecological civilization concept. Eco-civilization demonstration sites and experiences are also discussed, followed by a review of academic research and policy-making responses. Finally, we propose different perspectives on the outlook for the future of ecological civilization development in China. [ABSTRACT FROM AUTHOR]

Models and methods have been developed to verify the achievability of goals and the feasibility of plans implemented when managing large-scale systems in their development. An algorithm for analyzing the achievability of a set of goals and plans implemented when managing these systems is proposed and justified. Statements and hypotheses that make it possible to machine-check the feasibility of plans have been generated. A model example is given that confirms the possibility of checking the feasibility of plans for eliminating the consequences of a flood using the developed models and methods. In managing large-scale systems development, it is advisable to use control loops that check the achievability of set goals and the feasibility of plans over a selected time interval. In the absence of this verification, the chosen trajectory of development of a large-scale system at specific points in time may turn out to be unrealizable, which will lead to disruption of the work being carried out, as well as to significant costs of the human, financial, technical and other types of resources for the implementation of obviously impracticable plans. [ABSTRACT FROM AUTHOR]

The relationships between metaverse applications and tourism can be categorized into two dimensions. One is about the effects of metaverse applications on the real entities in the tourism sector and the second is about the effects of metaverse applications on the meta entities in the tourism sector. These dimensions create a new ecosystem for tourism which encompass brand new stakeholders with new business models. Providing new and creative touristic products in the metaverse environment, revising existing touristic products in a way that will provide different experiences, and structuring beta tourist world are the ways of creating a very deep new touristic universe which is a combination of meta tourism universes. This study provides a framework for tourism businesses, especially hotels, aspiring to exist in the metaverse to host an event. The framework provides a system development life cycle model which explains step-by-step how to establish a concert world in the metaverse. The framework starts with the planning process, which includes personnel, software, hardware, data and objectives, and continues with the analysis process covering preparation, implementation and evaluation stages. The framework is complemented by the design, development and implementation processes. The case study is based on the organization of an event, namely a concert, in the metaverse within the context of a hotel. The new framework is significant in that it sheds light onto new business models and how stakeholder roles take place in the metaverse. [ABSTRACT FROM AUTHOR]

By affecting core neurobiological systems early in development, early life adversities (ELAs) might confer latent vulnerability to future psychopathologies. This coordinate-based meta-analysis aims to identify significant convergent alterations in functional connectivity of the amygdala related to ELAs across resting-state and task-based fMRI-studies. Five electronic databases were systematically searched until 22 October 2020, retrieving 49 eligible studies (n = 3162 participants). Convergent alterations in functional connectivity related to ELAs between the amygdala and the anterior cingulate cortex (ACC) and left hippocampus were found. Sub-analyses based on hemisphere and direction showed that connectivity seeded in the right amygdala was affected and, moreover, revealed that connectivity with ACC was decreased. Analyses based on paradigm and age showed that amygdala-ACC coupling was altered during resting state and that amygdala–left hippocampus connectivity was mostly affected during task-based paradigms and in adult participants. While both regions showed altered connectivity during emotion processing and following adverse social postnatal experiences such as maltreatment, amygdala-ACC coupling was mainly affected when ELAs were retrospectively assessed through self-report. We show that ELAs are associated with altered functional connectivity of the amygdala with the ACC and hippocampus. As such, ELAs may embed latent vulnerability to future psychopathologies by systematically affecting important neurocognitive systems. [ABSTRACT FROM AUTHOR]

Molecules that induce novel interactions between proteins hold great promise for the study of biological systems and the development of therapeutics, but their discovery has been limited by the complexities of rationally designing interactions between three components, and because known binders to each protein are typically required to inform initial designs. Here, we report a general and rapid method for discovering α-helically constrained (Helicon) polypeptides that cooperatively induce the interaction between two target proteins without relying on previously known binders or an intrinsic affinity between the proteins. We show that Helicons are capable of binding every major class of E3 ubiquitin ligases, which are of great biological and therapeutic interest but remain largely intractable to targeting by small molecules. We then describe a phage-based screening method for discovering "trimerizer" Helicons, and apply it to reprogram E3s to cooperatively bind an enzyme (PPIA), a transcription factor (TEAD4), and a transcriptional coactivator (β-catenin). Identification of molecules that induce novel interactions between proteins has been limited by the complexity of rationally designing interactions. The authors report a method to discover molecular glue-like "trimerizers" based on α-helically constrained peptides that can co-opt the surfaces of E3 ubiquitin ligases to bind therapeutically important proteins. [ABSTRACT FROM AUTHOR]

Whereas exercise training, as part of multidisciplinary rehabilitation, is a key component in the management of patients with chronic coronary syndrome (CCS) and/or congestive heart failure (CHF), physicians and exercise professionals disagree among themselves on the type and characteristics of the exercise to be prescribed to these patients, and the exercise prescriptions are not consistent with the international guidelines. This impacts the efficacy and quality of the intervention of rehabilitation. To overcome these barriers, a digital training and decision support system [i.e. EXercise Prescription in Everyday practice & Rehabilitative Training (EXPERT) tool], i.e. a stepwise aid to exercise prescription in patients with CCS and/or CHF, affected by concomitant risk factors and comorbidities, in the setting of multidisciplinary rehabilitation, was developed. The EXPERT working group members reviewed the literature and formulated exercise recommendations (exercise training intensity, frequency, volume, type, session and programme duration) and safety precautions for CCS and/or CHF (including heart transplantation). Also, highly prevalent comorbidities (e.g. peripheral arterial disease) or cardiac devices (e.g. pacemaker, implanted cardioverter defibrillator, left-ventricular assist device) were considered, as well as indications for the in-hospital phase (e.g. after coronary revascularisation or hospitalisation for CHF). The contributions of physical fitness, medications and adverse events during exercise testing were also considered. The EXPERT tool was developed on the basis of this evidence. In this paper, the exercise prescriptions for patients with CCS and/or CHF formulated for the EXPERT tool are presented. Finally, to demonstrate how the EXPERT tool proposes exercise prescriptions in patients with CCS and/or CHF with different combinations of CVD risk factors, three patient cases with solutions are presented. [ABSTRACT FROM AUTHOR]

The text discusses the work of German chemist Lothar Meyer in the development of the periodic system, which is often attributed solely to Russian chemist Dmitri Mendeleev. The text highlights Meyer's contributions and his publication of the first full periodic table in 1870. It explores the differences between Meyer's and Mendeleev's versions of the periodic system and the rivalry between the two chemists. The text also emphasizes Meyer's focus on physical properties and his use of atomic volume charts to deduce probable atomic weights. The edited volume by Gisela Boeck and Alan J. Rocke provides a comprehensive look at Meyer's work and its context in contemporary chemical theories. [Extracted from the article]

Evaluating the green development level (GDL) of a region will accelerate its economic transformation and promote ecological civilization. From the perspective of complex system, this study explores the green development level (GDL) of the Three Gorges Reservoir Area (TGRA) by constructing a novel and ecology-oriented evaluation system. The system is three-dimensional including indicators of environmental protection and utilization, green economy development, social harmony and prosperity. Resource elements are highly valued; inclusive society is fully considered. Overall entropy method and expert scoring method are integrated to assess the GDL of 26 regions in the TGRA from 2000 to 2020; the temporal and spatial characteristics of the GDL are examined through exploratory spatial data analysis (ESDA). The results show that (1) the GDL of the TGRA is at a medium level with the score fluctuating from 0.3 to 0.4 and the ecological protection with weight of 0.37 contributes greatly to the GDL. (2) Despite the high degree of coupling coordination, the complex ecosystem in the TGRA remains at a low level of coordinated development. (3) The GDL in the middle part of the TGRA is the highest, followed by the upper part and the lower part, and the gap is narrowing. (4) The global spatial correlation of the GDL is not obvious. The spatial spillover effect is not significant and clusters only appear in the upper part and the lower part. Finally, some reasonable suggestions are put forward for improving the GDL. [ABSTRACT FROM AUTHOR]

Based on China's new development philosophy, and following the idea of "assessing the overall levels firstly, then anchoring the subsystems contributions and finally identifying the obstacle factors", an evaluation system of high-quality development (HQD) levels is constructed from five subsystems of innovative development (ID), coordinated development (CD), green development (GD), open development (OD) and shared development (SD). In this paper, the entropy weight TOPSIS model is used to measure the HQD levels of 19 provincial units located in the Yellow River Basin (YRB) and the Yangtze River Economic Belt (YREB) in 2010–2019, and with the assistance of the Obstacle Degree Model, the obstacle factors affecting the HQD of both are depicted. The results show that: (1) between 2010 and 2019, the HQD indices in YRB and YREB have been on an increasing trend, and the subsystems indices all show a trend of "GD > CD > SD > ID > OD", but the overall levels of HQD in both is not high, and there is still much room for improvement. (2) YREB has a significantly higher HQD level than YRB. From 2010 to 2019, the average values of the HQD indices in YRB and YREB were 0.2886 and 0.4073, respectively, but the index in YRB improves at a faster pace than YREB, and the gap of HQD levels between the two show a trend of continuous reduction towards regional balance and coordination. (3) The analysis of obstacle factors shows that while OD and ID are the main obstacles to HQD in both basins, the impact of both on the resistance to HQD in both basins is on a decreasing trend. GD is another bottleneck for the HQD of YRB, and the pressure on GD in the middle and upper reaches of the provincial units in the basin is increasing, and the obstacles are on a rising trend. [ABSTRACT FROM AUTHOR]

Safety assurance cases (ACs) are structured arguments designed to comprehensively show that a system is safe. ACs are often model-based, meaning that a model of the system is a primary subject of the argument. ACs use reasoning steps called strategies to decompose high-level claims about system safety into refined subclaims that can be directly supported by evidence. Strategies are often informal and difficult to rigorously evaluate in practice, and consequently, AC arguments often contain reasoning errors. This has led to the deployment of unsafe systems, and caused severe real-world consequences. These errors can be mitigated by formalizing and verifying AC strategies using formal methods; however, these techniques are difficult to use without formal methods expertise. To mitigate potential challenges faced by engineers when developing and interpreting formal ACs, we present ForeMoSt, our tool-supported framework for rigorously validating AC strategies using the Lean theorem prover. The goal of the framework is to straddle the level of abstraction used by the theorem prover and by software engineers. We use case studies from the literature to demonstrate that ForeMoSt is able to (i) augment and validate ACs from the research literature, (ii) support AC development for systems with large models, and (iii) support different model types. [ABSTRACT FROM AUTHOR]

A highly purified and bioactive immunoglobulin G monoclonal antibody against receptor-binding domain of SARS-CoV-2 (RBD-IgG-MAb) has been accurately quantified by amino acid determination using isotope dilution liquid chromatography–mass spectrometry. Absolute quantification of RBD-IgG-MAb was achieved by averaging 4 amino acid certified reference materials, which allows the quantitative value (66.1 ± 5.8 μg/L) to be traced to SI unit (mol). Afterwards, the RBD-IgG-MAb was employed as control and calibration compound for the development of a point-of-care testing (POCT) system based on colloidal gold lateral flow immunoassay, which aimed to rapidly and accurately detect the level of protective RBD-IgG after vaccination. Under the detection parameters, a sigmoidal curve has been plotted between signal intensity and the logarithmic concentration for quantitative detection with the limit of detection of about 0.39 μg/mL. The relative standard deviations of intra-assay and inter-assay were lower than 2.3% and 14%, and the recoveries ranged from 87 to 100%, respectively. Fingertip blood samples from 37 volunteers after vaccination were analyzed by the POCT system; results showed that levels of RBD-IgG in 33 out of 37 samples ranged from 0.45 to 2.46 μg/mL with the average level of 0.91 μg/mL. The developed POCT system has been successfully established with the quantity-traceability RBD-IgG-MAb as control and calibration compound, and the scientific contribution of this work can be promoted to other areas. [ABSTRACT FROM AUTHOR]

In this work, the probe system developed by us earlier for plasma diagnostics under the conditions of plasma polymerization and synthesis of carbon nanostructures was constructively developed. The probe system is supplemented with a block that allows cleaning the probe with ion current, as well as obtaining the second derivative of the probe current-voltage characteristic by the harmonic method. The probe system was tested on the example of plasma diagnostics in a mixture of He + 0.1% CH4. [ABSTRACT FROM AUTHOR]

Exploring the synergy types and optimization paths between Poverty Alleviation Effectiveness and Rural Revitalization is necessary for achieving the two centenary goals. Taking poverty alleviation counties in Hunan Province, China as an example, our study proposed an indicator to measure the synergistic development between Poverty Alleviation Effectiveness and Rural Revitalization using the multi-index integrated evaluation method. Then, the coupling types were classified based on both the proposed indicator and regional characteristics. Besides, the corresponding optimization path for each coupling type was proposed to promote the synergistic development of Poverty Alleviation and Rural Revitalization. Results are as follows: 1) Lower synergy focused on the southwestern Hunan, while low synergy is widely distributed (such as the west, southwest, northwest, and midland). Moderate synergy is in the midland, such as Huaihua and Chenzhou cities. High synergy is distributed in Yongzhou, Huaihua, Xiangxi cities, etc. Besides, only Hecheng City belongs to the higher synergy. 2) This paper proposes corresponding development paths for different development characteristics and main problems from multiple perspectives of the protection system, industrial planning, and rural market. Continuously consolidate and enhance the effectiveness of Poverty Alleviation and Rural Revitalization to achieve coupled and synergistic development of the two systems. Our research results can provide theoretical support for implementing Poverty Alleviation and Rural Revitalization in Hunan Province, China. [ABSTRACT FROM AUTHOR]

More than 50% of pollen allergies in northern China are brought on by Artemisia pollen grains, which are significant aeroallergens worldwide. The diagnosis and prevention of allergy disorders can be enhanced by understanding the dispersal patterns and intervention effects of Artemisia pollen. In this study, Artemisia pollens were examined in two field plots in the suburbs of Hohhot, China. Artemisia pollen concentration in various horizontal and vertical ranges around the pollen plants was recorded every day in the autumn of 2020, and on the basis of this data, the Artemisia pollen release and dispersal pattern in the suburbs of Hohhot were analyzed, and the relationship between meteorological variables and pollen flow was determined during this time. In order to investigate the viability and efficiency of artificial interventions on pollen concentration, various treatments of shrub hedge interception and spraying on the canopy were experimented during the flowering season of Artemisia plants in 2020. This study's goal is to give concise, quantitative visualizations of the Artemisia pollen data dispersal pattern and the impact of meteorological conditions on pollen dispersal, as well as a summary of the implementation strategy for artificial interventions that are appropriate for the study area. The results can serve as a valuable reference for local allergy sufferers and as a foundation for the continued development of a prediction system for allergic Artemisia pollen as well as the management techniques that may assist lower the concentration of allergenic pollen in Hohhot. [ABSTRACT FROM AUTHOR]

Nervous system development is associated with extensive regulation of alternative splicing (AS) and alternative polyadenylation (APA). AS and APA have been extensively studied in isolation, but little is known about how these processes are coordinated. Here, the coordination of cassette exon (CE) splicing and APA in Drosophila was investigated using a targeted long-read sequencing approach we call Pull-a-Long-Seq (PL-Seq). This cost-effective method uses cDNA pulldown and Nanopore sequencing combined with an analysis pipeline to quantify inclusion of alternative exons in connection with alternative 3' ends. Using PL-Seq, we identified genes that exhibit significant differences in CE splicing depending on connectivity to short versus long 3'UTRs. Genomic long 3'UTR deletion was found to alter upstream CE splicing in short 3'UTR isoforms and ELAV loss differentially affected CE splicing depending on connectivity to alternative 3'UTRs. This work highlights the importance of considering connectivity to alternative 3'UTRs when monitoring AS events. In this study using a targeted long read RNA sequencing approach called PL-Seq, the authors uncover coordination of alternative splicing and alternative polyadenylation within individual genes in Drosophila melanogaster. [ABSTRACT FROM AUTHOR]

This paper reviews the research process conducted on developing a new system for industry wastewater treatment application to increase efficiency and sustainability by adopting industry 4.0 technology. The challenge of this project was to (a) utilize the design thinking methodology (human-centered design) entire process; (b) focus on heavy industry rather than the targeted user; and (c) adapt state of art technology. The objective was to revisit and invent new methods, such as metaphoric analysis, body thinking, and organization persona that would contribute to high-level innovative ideas: specifically, (a) the organization persona allowed to understand the dynamics of the complicated stakeholder structure; (b) the role of prototyping was mainly descriptive for communication; and (c) the case's idea generation was used to affect the entire process of the project as well as benchmarking other industries. This paper attempts to address whether it is possible to create a new methodology that would address innovative business opportunities in complicated and high-tech adapting industries. [ABSTRACT FROM AUTHOR]

Buffer overflow poses a serious threat to the memory security of modern operating systems. It overwrites the contents of other memory areas by breaking through the buffer capacity limit, destroys the system execution environment, and provides implementation space for various system attacks such as program control flow hijacking. That makes it a wide range of harms. A variety of security technologies have been proposed to deal with system security problems including buffer overflow. For example, No eXecute (NX for short) is a memory management technology commonly used in Harvard architecture. It can refuse the execution of code which residing in a specific memory, and can effectively suppress the abnormal impact of buffer overflow on control flow. Therefore, in recent years, it has also been used in the field of system security, deriving a series of solutions based on NX technology, such as ExecShield, DEP, StackGuard, etc. However, these security solutions often rely too much on the processor architecture so that the protection coverage is insufficient and the accuracy is limited. Especially in the emerging system architecture field represented by RISC-V, there is still a lack of effective solutions for buffer overflow vulnerabilities. With the continuous rapid development of the system architecture, it is urgent to develop defense methods that are applicable to different system application environments and oriented to all executable memory spaces to meet the needs of system security development. Therefore, we propose BOP, A new system memory security design method based on RISC-V extended instructions, to build a RISC-V buffer overflow detection and defense system and deal with the buffer overflow threat in RISC-V. According to this method, NX technology can be combined with program control flow analysis, and NX bit mechanism can be used to manage the executability of memory space, so as to achieve a more granular detection and defense of buffer overflow attacks that may occur in RISC-V system environment. In addition, The memory management and control function of BOP is not only very suitable for solving the security problems in the existing single architecture system, but also widely applicable to the combination of multiple heterogeneous systems. [ABSTRACT FROM AUTHOR]

Purpose: Preference-based measures have been increasingly recommended to measure health outcomes for economic evaluation. However, none of existing cardiovascular disease (CVD)-specific health-related quality of life (HRQoL) instruments are preference-based. This study aimed to develop the descriptive system of preference-based HRQoL instrument for Chinese patients with CVDs under the Initiative of China Health Related Outcomes Measures (CHROME). Methods: Qualitative face-to-face interviews were conducted with Chinese patients with CVDs. Content analysis was employed to generate candidate items for the instrument. Then expert consultation and cognitive debriefing interviews were conducted to guide further selection and revision of the items. Results: We interviewed 127 CVD patients with 67.7% being male and 63.8% living in the urban area. A hierarchical code book comprised of four themes, 20 categories, 62 sub-categories, and 207 codes, was developed. Candidate items were selected based on the criteria set by the Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) methodology and ISPOR PRO guidance. An online survey and meeting with an expert advisory panel (n = 15) followed by cognitive debriefing interviews with 20 patients and 13 physicians were conducted to further select and revise the candidate items. The descriptive system of CHROME-CVD consists of 14 items, namely frequency and severity of chest pain, chest tightness, palpitation, shortness of breath, dizziness, fatigue, appetite, sleeping, mobility, daily activities, depression, worry, and social relationship. Four or five level responses were selected based on cognitive debriefing results to each item. Conclusion: The current study developed the descriptive system (items and response options) of CHROME-CVD, the future CVD-specific preference-based HRQoL instrument for Chinese CVD patients. [ABSTRACT FROM AUTHOR]

Today, nanoparticles have promised a variety of applications in conjugation with biomolecules. Selenium nanoparticles (SeNPs) have shown to be potential candidates in a wide range of applications, and amyloid fibrils with well-known physicochemical stability and ability to mimic the extracellular matrix have been highlighted with possible use in tissue engineering. To exploit the dual properties of nano and bio components in biomedical applications, this research aimed to develop a nanohybrid system through assembling SeNPs on lysozyme amyloid fibrils and investigate possibility of incorporating two features of conductivity and antibacterial effect of SeNPs into the hybrid system. Spectroscopic and microscopy techniques including UV–Vis, far-UV circular dichroism spectropolarimetry, thioflavin-T assay, and transmission electron microscopy were used to characterize formation of the amyloid fibrils, selenium nanoparticles, and their hybrid form. Antibacterial activity of the individual components as well as the hybrid was determined against Escherichia coli and Staphylococcus aureus. Assembly of SeNPs on amyloid fibrils enhanced antibacterial activity as shown by the minimum inhibitory concentration method and improved conductivity using electrochemical impedance spectroscopy. Results of this investigation suggest that combination of nanoparticles with amyloid fibrils paves the way for the development of versatile nanohybrid systems with improved properties and promising application in regenerative medicine. [ABSTRACT FROM AUTHOR]

Catfish ranked 8th among seafoods consumed per capita in the United States (U.S.) in 2019. As a major catfish product, catfish fillets are often chilled or frozen for storage after filleting and trimming operations. When they are removed from storage for further processing, manual interference is required to separate and flatten all the catfish fillets that otherwise could agglomerate together. This is necessary for further processing operations such as breading and individual quick-freezing. Because of the shortage of labor force and rising labor costs, there is an urgent need to reduce labor dependence by developing automated singulation methods for catfish fillets manufacturing, to enhance the profitability of the U.S. catfish industry. This study presents a novel singulation system that enables separating catfish fillets by utilizing water buoyancy and underwater streams. Several operation parameters have been investigated and optimized to achieve better singulation performance and production rate. The continuous production mode with operation rules is defined to keep the total amount being processed in an appropriate range for maximizing the singulation effect and production rate. This study will be beneficial for developing more effective next-generation singulation technologies for catfish and other fish species. [ABSTRACT FROM AUTHOR]

This paper focuses on unpacking the United States Air Force's (USAF) instructional system development (ISD) model as it evolved over time to its present form. In post-World War II training, the USAF was a leader in the study and use of systematic instructional design procedures, with its early efforts often coinciding with the work of the Department of Audio-Visual Instruction (DAVI) and in collaboration with the scholars who shaped both military training and the Association of Educational Communications and Technology (AECT). This paper draws from the original research on USAF training design as well as official USAF publications, inspection reports, DAVI and AECT publications, and the Air Training Command's Instructors' Journal. This study revealed that three distinct ISD models have existed in ISD literature. As a framework for examining the evolution of the USAF ISD model, the seven attributes on idealized design posited by Smith and Boling (Educational Technology,49(4), 3–17, 2009) were used. [ABSTRACT FROM AUTHOR]

Earlier software development processes (SDPs), such as waterfall processes, were mainly focused on process steps and did not address people- and product-related issues. Emergence of Software development methodologies (SDM) has created a new paradigm for developing software systems. A SDM is a special kind of technically engineered framework for organizing SDPs; this framework is expected to specify three main interwoven elements, namely people, products, and process. It has since become evident that it is impossible to provide a general-purpose SDM for developing all the various kinds of software systems, and it has thus become essential to construct the most appropriate methodology for the system development situation in hand, a practice commonly called Situational Method Engineering (SME). The problem with existing SME methods is lack of adequate attention to the role of people who might seek or possess valuable knowledge about the project situation. This knowledge can be tacit information that is hidden in the developer's mind, or it might be explicitly available. This paper proposes a knowledge management (KM)-driven and DevOps-based SME method as a new integrated multi-view methodological paradigm that satisfies the need for sharing human experience in engineering SDMs. The method has been proposed by reusing general SME practices and complementing them by embedding appropriate KM and DevOps practices to alleviate the weaknesses of previous SME methods. Furthermore, the proposed method has been evaluated through four case studies and also by conducting a criteria-based comparison with eight prominent SME methods. [ABSTRACT FROM AUTHOR]

The supply chain is a complex network in healthcare that crosses organizational and geographical borders. The inherent complexity of such structures can introduce impurities inclusive of erroneous facts, lack of transparency, and restricted records provenance. In the healthcare business, counterfeit pills are one of the major reasons for the harmful impact on human health and also for financial losses. Thus, pharmaceutical supply chains and end-to-end tracking systems are the recent research in healthcare. In this paper, we propose blockchain based traceability of counterfeited drugs (BBTCD) that implements tracking of counterfeited drugs using smart contracts on the Ethereum blockchain. We propose a solution to fully decentralize the tracking in healthcare by storing BBTCD on IPFS (Inter Planetary File System) to provide transparency, cost-effectiveness. [ABSTRACT FROM AUTHOR]

This article presents a case study on perceived conflict and its outcomes on implementing a system of programs and services for child development support. A multi-level collaboration model is used to deeply examine aspects of conflicts perceived by professionals responsible for implementing the system at the national, state, and local levels. This research adopted a single case approach with qualitative methods using semi-structured interviews and exploratory thematic analysis. A total of 29 professionals working at social development and health ministries, state departments, and one municipality participated in this study. The results show that professionals perceive one main unresolved conflict at each of the ecological levels. These conflicts are related to an informalized collaboration agreement between the Ministry of Social Development and the Ministry of Education, an interrupted resource flow from the national level to local level, and an unmanageable internal pressure at the state level. Furthermore, the compensatory strategies they use to deal with these conflicts are ineffective and lead to negative implementation outcomes. We suggest that future research should explore systemic conflict for the collaboration processes among the professionals to improve, thus increasing the quality of system implementation. Highlights: Professionals perceive one main unresolved conflict at each of the three ecological levels examined. Conflicts are related to informalized agreements between ministries, interrupted resource flow from the national level, and pressure from the local level. Professionals use compensatory strategies to cope with unresolved conflicts. The compensatory strategies identified are ineffective and lead to negative implementation outcomes. Findings reveal opportunities for future research to explore systemic conflict to better understand and improve collaboration processes. [ABSTRACT FROM AUTHOR]

Healthcare prediction has been a significant factor in saving lives in recent years. In the domain of health care, there is a rapid development of intelligent systems for analyzing complicated data relationships and transforming them into real information for use in the prediction process. Consequently, artificial intelligence is rapidly transforming the healthcare industry, and thus comes the role of systems depending on machine learning and deep learning in the creation of steps that diagnose and predict diseases, whether from clinical data or based on images, that provide tremendous clinical support by simulating human perception and can even diagnose diseases that are difficult to detect by human intelligence. Predictive analytics for healthcare a critical imperative in the healthcare industry. It can significantly affect the accuracy of disease prediction, which may lead to saving patients' lives in the case of accurate and timely prediction; on the contrary, in the case of an incorrect prediction, it may endanger patients' lives. Therefore, diseases must be accurately predicted and estimated. Hence, reliable and efficient methods for healthcare predictive analysis are essential. Therefore, this paper aims to present a comprehensive survey of existing machine learning and deep learning approaches utilized in healthcare prediction and identify the inherent obstacles to applying these approaches in the healthcare domain. [ABSTRACT FROM AUTHOR]

Using the CRITIC method, comprehensive index evaluation method, VAR model, coupling coordination model and other methods, this paper evaluates the comprehensive development of the population economy and eco-geological environment composite system in the twin-city economic circle of Chengdu–Chongqing region from 2000 to 2020, verifies the dynamic coupling relationship between subsystems and measures the coupling coordination degree of complex system. Meanwhile, the differences in the development process of each subsystem are discussed and the spatial–temporal evolution characteristics and laws of coupling coordination of the composite system during the research period are analyzed. The results reveal the following: (1) There is a long-term coordinated relationship between population, economy and eco-geological environment in Chengdu–Chongqing region, which have the conditions for emergence and generation. (2) The subsystems of population, economy and eco-geological environment in Chengdu–Chongqing region show an overall upward trend, among which the Sichuan part obviously outperforms the Chongqing part. Besides, the growth rate of the economy subsystem is significantly higher than that of the population, eco-geological environment subsystem. (3) The coupling coordinated development of the composite system has shown a benign upward development trend, gradually changing from "composite spiral structure" to "two cores outstanding, peripheral collapse, the west superior to the east", while the main coordination state has developed from "Basic synergy—Economic lag" in 2000 to "Basic synergy—Population lag" in 2022. In addition, Cheng-De-Mian and Yuzhong districts with the better level of economic development have shown "Advanced synergy—Ecological lag". [ABSTRACT FROM AUTHOR]

The authors propose a typification of intraoceanic island‒arc systems according to the geodynamics of their development in the oceanic space. The currently existing and reconstructed (represented by terranes at the margins of the continents) Late Mesozoic–Cenozoic intraoceanic island-arc systems are subdivided into the expansive, accretionary, and stationary types. The expansive-type systems (Izu–Bonin–Mariana and Lesser Antilles) are advanced both towards the subducting oceanic plate and towards the free oceanic space. Their geodynamics is determined by processes in the oceanic plates. The mantle currents under the overhanging lithospheric plate are directed towards the subducting plate. Accretionary systems such as the Olyutor–East Kamchatka, Nemuro–Lesser Kuril, and Talkeetna systems completed their development as part of active continental margins. The paleotectonic reconstruction of such systems shows that they were reduced in the course of their development to relict terranes, tectonically aligned with continental margins. The geodynamics of intra-ocean systems of the accretion type also depends on processes in oceanic plates. However, this leads to the opposite result compared to expansive systems. This is due to the direction of mantle flows under the overhanging plate, which is opposite to the expansion type, i.e., coinciding in direction with the mantle flow under the absorbed plate. The stationary Aleutian island-arc system is intercontinental and its development in space and the formation of internal structures (the Paleogene island arc of the Bowers Ridge) are depended on the difference in the relative movement of the Eurasian and North American lithospheric plates. The most specific feature of this system is the absence of signs of back-arc basin opening, which is invariably characterizes expansive and accretionary island-arc systems. It is assumed that this specific feature of the system may be related to the mantle flow under the overhanging slab, which has a transverse direction with respect to the direction of the subducting plate. From the time of its formation the Aleutian system had remained autochthonous in relation to the North American and Eurasian continents. [ABSTRACT FROM AUTHOR]

We present results from an experimental study investigating pairs of helical vortices generated by a one-bladed rotor in hovering conditions. Time-resolved volumetric Lagrangian particle tracking measurements are conducted in a water tunnel to analyze the three-dimensional development of the vortex system. The vortex pairs are generated by a specific tip design, which allows splitting the single tip vortex into two vortices, whose characteristics depend on the geometric fin parameters. The objective of this procedure is the modification of the tip vortex structure, in order to minimize negative effects caused by fluid–structure interactions in applications involving rotors. Certain vortex configurations are affected by centrifugal instabilities, which result in an immediate pronounced growth of the vortex cores. As a consequence of the instability, secondary vortex structures are formed between the unstable cores. The presence of these structures results in an accelerated break-up of the cores, causing them to merge. In order to investigate the influence of the trailing vorticity layer shed from the inner part of the blade, two blade designs with different radial circulation distributions are considered. The measurements are able to track the evolution of the vorticity layer and the secondary structures, providing new insights into the instability of closely spaced vortex pairs with varying circulation ratios. [ABSTRACT FROM AUTHOR]

Low-carbon city (LCC) quality evaluation is getting increasingly attention in recent years. However, uncertainty decision-making processes and complicated indicators in LCC development have brought challenges to the evaluation, making it more difficult to reach a consensus during assessment. To address these issues, this study develops a novel comprehensive framework based technique for order of preference by similarity to ideal solution (TOPSIS) and Fermatean fuzzy hybrid weighted distance measure for LCC quality. Firstly, a new Fermatean fuzzy (FF) distance measure from hybrid weighted perspective, named as FF hybrid weighted distance (FFHWD) measured is proposed, and some of its merits and mathematical characteristics are also explored. An FFHWD–TOPSIS comprehensive evaluation framework is then presented, wherein the entropy model and best–worst method (BWM) are utilized to derive the weights of different indicators. In addition, based on the established LCC quality evaluation index system, the proposed FFHWD-TOPSIS approach is used to measure the level of development of LCC in five Chinese cities. Finally, a sensitivity and comparative analysis of the proposed framework are carried out in detail. This study not only contributes to enriching the evaluation index system for LCC development, but also to presenting researchers with a reference for scientific evaluation approach. [ABSTRACT FROM AUTHOR]

Smart homes are becoming increasingly popular in providing people with the services they desire. Activity recognition is a fundamental task to provide personalised home facilities. Many promising approaches are being used for activity recognition; one of them is data-driven. It has some fascinating features and advantages. However, there are drawbacks such as the lack of ability to providing home automation from the day one due to the limited data available. In this paper, we propose an approach, called READY (useR-guided nEw smart home ADaptation sYstem) for developing a personalised automation system that provides the user with smart home services the moment they move into their new house. The system development process was strongly user-centred, involving users in every step of the system's design. Later, the user-guided transfer learning approach was introduced that uses an old smart home data set to enhance the existing smart home service with user contributions. Finally, the proposed approach and designed system were tested and validated in the smart lab that showed promising results. [ABSTRACT FROM AUTHOR]

As luminescent nanomaterials, the carbon quantum dots (CQDs) research focused on emerging applications since their discovery. However, their toxicological effects on the natural environment are still unclear. The freshwater planarian Dugesia japonica is distributed extensively in aquatic ecosystems and can regenerate a new brain in 5 days after amputation. Therefore it can be used as a new model organism in the field of neuroregeneration toxicology. In our study, D. japonica was cut and incubated in medium treated with CQDs. The results showed that the injured planarian lost the neuronal ability of brain regeneration after treatment with CQDs. Its Hh signalling system was interfered with at Day 5, and all cultured pieces died on or before Day 10 due to head lysis. Our work reveals that CQDs might affect the nerve regeneration of freshwater planarians via the Hh signalling pathway. The results of this study improve our understanding of CQD neuronal development toxicology and can aid in the development of warning systems for aquatic ecosystem damage. [ABSTRACT FROM AUTHOR]

With the massive progress in science and technology, increasing populations, and urbanization demands, the need for newly developed urban areas raising. According to primary criteria, site suitability analysis provides a good way to identify and suggest the best and most appropriate sites. Multicriteria decision analysis (MCDA) is one of these techniques. This study applied a geospatial decision support system with a combination of MCDA and bivariate analysis to find the suitability map for urban development. The Multi-Influence Factor (MIF) is used to rank the input thematic maps according to their interaction, while the chi-square and Cramer's V-value (bivariate analysis) are used to determine pairwise comparisons in the Best Worst method (BWM). BWM is used to compute the weight of each thematic map. Fuzzy logic was used to renovate the classified layer values ​​into fuzzy values, after which the final site suitability map was derived using the fuzzy overlay. The study provides insights into optimizing the reliability and consistency of pairwise comparisons in BWM using bivariate analysis. [ABSTRACT FROM AUTHOR]

Science educators highlight the importance of developing systems thinking (ST) and futures thinking (FT) for students to make decisions and to be active citizens that address socioscientific problems. The dimensions related to FT take in this study were three implied in ST and two in the appropriation of the future. The aim of this study is to analyse the level of FT-related dimensions developed by a group of pre-service elementary teachers and how far different activities designed to foster them were effective. Written explanations presented by the participants about the origin of pandemics and possible ways to prevent them, as well as videos developed by small groups with the goal to present a campaign for avoiding future pandemics, were analysed. Based on the literature, five dimensions and up to four levels of performances were identified. After completing the activities, participants were able to relate the three spheres of the "One Health" notion to explain the causes of pandemics. Moreover, they established complex cause-effect relationships between the different factors, although they only constructed monocausal relationships when proposing measures. Participants improved their performance in anticipating the future and identifying themselves as agents of change. The elaboration of concept maps facilitated the development of components and behaviour ST dimensions, and the design of the campaign allowed participants to identify themselves as agents of change. The use of these strategies in science education can contribute to the development of a citizenry capable of understanding and acting on systems. [ABSTRACT FROM AUTHOR]

In CO2-EOR (Enhanced Oil Recovery) and storage projects, there is a high risk of CO2 leakage into groundwater, which will not only affect storage effectiveness, but also cause a variety of environmental consequences. A monitoring system of CO2 leakage is essential to the safety of CO2-EOR and storage projects. Previous monitoring systems have been proposed through theoretical analysis, field test and indoor experiment. In this study, a modeling approach based on simulation of CO2 migration coupled with water-rock interactions in groundwater is proposed to support monitoring system development for CO2-EOR and storage projects. The simulation is undertaken using TOUGHREACT and applied to a case study in the Ordos Basin in China. The case study results indicate that the developed monitoring system has the advantage of offering a precise, timely and comprehensive monitoring scheme based on the dynamics of CO2 leakage and its effects on groundwater composition. [ABSTRACT FROM AUTHOR]

Capparisspinosa L. (caper) is a halophytic plant that grows in semi-arid or arid environments. The current study used an integrated experimental and computational approach to investigate the network of inter-correlated effective variables on the activity of antioxidant enzymes, proline, and photosynthetic pigments in stressed caper. To investigate the possible relationships among intercorrelated variables and understand the possible mechanisms, predictive regression modelling, principal component analysis (PCA), Pearson's correlation, and path analysis were implemented. PCA successfully discerned different salt ratio- and drought-specific effects in data in the current study, and treatments with higher growth indices are easily recognizable. Different salt ratios did not have a significant effect on the activity of four antioxidant enzymes, proline and photosynthesis pigments content of caper. While at the mean level, the activity of four antioxidant enzymes of SOD, POD, CAT, and APX significantly increased under drought stress by 54.0%, 71.2%, 79.4%, and 117.6%, respectively, compared to 100% FC. The drought stress also significantly increased the content of carotemoid (29.3%) and proline (by 117.7%). Predictive equation models with highly significant R2 were developed for the estimation of antioxidant enzyme activity and proline content (> 0.94) as well as pigments (> 0.58) were developed. Path analysis studies revealed that proline is the most important regressor in four antioxidant enzyme activities, while leaf tissue density was the most effective variable in the case of chlorophylls. Furthermore, the network of intercorrelated variables demonstrated a close relationship between caper's antioxidant defence system, pigments, and morphological parameters under stress conditions. The findings of this study will be a useful guide to caper producers as well as plant ecophysiological researchers. [ABSTRACT FROM AUTHOR]

The recent increase in the frequency and intensity of disasters has damaged and disrupted transportation infrastructures, thereby significantly increasing the economic losses and slowing the pace of recovery. Resilient infrastructures ensure functionality with minimal discontinuity, but there currently exists rarely a tool for assessing the resilience level of existing transportation infrastructures so that the information can be used to make future constructions more resilient. This study aims to identify the significant dimensions for measuring the resilience of transportation infrastructures and to utilize the dimensions to develop a decision-making tool that can be used to assess the level of resilience. A survey supported by a comprehensive literature review was conducted, and statistical tests were performed on the collected data. It was found that network characteristics (length of the link, number of lanes, number of optional routes, etc.), organizational characteristics (time to start reconstruction work, knowledge of the employee, resilience measurement experience, etc.), and information related to data (previous data availability and data accessibility, etc.) have major impacts on the resilience of transportation infrastructures. Based on the impact of statistically significant indicators, a resilience measurement tool was developed that provides a relative resilience score for projects and reveals how each statistically significant dimension affects the resilience. The outcome of this study will help decision-makers and practitioners prioritize their projects for resilience enhancement activities and provide funding accordingly. [ABSTRACT FROM AUTHOR]

Subcutaneously administered drugs are growing in popularity for both large and small molecule drugs. However, development of these systems – particularly generics – is slowed due to a lack of formal guidance regarding preclinical testing and in vitro – in vivo correlations (IVIVC). Many of these methods, while appropriate for oral drugs, may not be optimized for the complex injection site physiologies, and release rate and absorption mechanisms of subcutaneous drugs. Current limitations for formulation design and IVIVC can be supported by implementing mechanistic, computational methods. These methods can help to inform drug development by identifying key drug and formulation attributes, and their effects on drug release rates. This perspective, therefore, addresses current guidelines in place for oral IVIVC development, how they may differ for subcutaneously administered compounds, and how modeling and simulation can be implemented to inform design of these products. As such, integration of modeling and simulation with current IVIVC systems can help in driving the development of subcutaneous injectables. [ABSTRACT FROM AUTHOR]

High-technology businesses face severe competition in their respective industries, necessitating constant innovation of their systems through the infusion of new technologies. To this end, these companies incorporate multiple technologies into new successful systems to improve key requirements that can ultimately affect the overall revenue and profitability of their systems. In many cases, comprehensive effects of infused technologies including improvements to the overall system performance, the extent of engineering design change, total investment cost, and profitability, are assessed a posteriori. In this study, a structured assessment framework was introduced for the infusion of multiple technologies into a parent system. The framework was conceived to address the requirements of companies for technology-based system development that need to assess the impact of infusing multiple technologies into their system. The proposed technology infusion framework is demonstrated through a printing system case study. [ABSTRACT FROM AUTHOR]

The advent of technology including big data has allowed machine learning technology to strengthen its place in solving different science and engineering complex problems. Conventional deep machine learning algorithms work as a black box while dealing with various complex physics-driven problems. This problem can be reduced by integrating the physical laws with machine learning algorithms to ensure the developed models are complied with the physics and are potentially more explainable. This physics-informed machine learning (PIML) approach allows the integration of physical laws in the form of PDEs into the loss function of the neural network, hence, constraining the training of the complex problems based on both the physical, experimental, and mathematical boundaries. This, hence, allows the development of a more general predictive model for different science, engineering, and optimization tasks. Considering such advancements in the machine learning domain, this review presents the systematic progress in the development of integrating physics into the neural networks and recent applications in solving various forward and inverse problems in science and engineering. This paper can serve as a reference for the researchers, developers, and users to get all information they need before developing, implementing, and deploying AI models and smart systems that are equipped with the PIML methodology. It highlights the benefits and points out its limitations and recommendations for further development. The review also compares the traditional data-driven machine learning and PIML approach in dealing with the physics of complex problems. In general, the PIML has been found to provide consistent results with the exact solutions and physical nature of the system. However, similar to other AI system development, a more robust and complex AI algorithm requires more computational power which is also the case in PIML development and implementation. It should be noted that different terminologies such as physics-informed neural networks (PINN), science-informed neural networks, physics-inspired neural networks, and physics-constrained neural networks have been used in the literature that describes the very similar concept of integrating physical laws with machine intelligence. For consistency, we use the PIML term throughout this paper which covers all listed terminologies in this regard. [ABSTRACT FROM AUTHOR]

In this work, zeolite catalysts having different porosity in nano range were synthesized. For this, a zeolite-containing rock with a mordenite content of 72 wt% was treated with hydrochloric acid solutions of various concentrations. Impregnation of acid-modified samples with nickel in an amount of 1–2.5 wt% was aimed at obtaining different isomerization activity of the catalysts. The catalysts were characterized using XRD, low-temperature N2 ad(de)sorption, TEM, and tested in micro pulse isomerization of linear hexane to estimate their selectivity in the formation of dimethyl-branched isomers. It has been shown that the low-concentrated acid increases the micropore volume by removing impurities from the zeolite micropores while the more concentrated acid also develops mesoporosity, especially the nanoscale pores ø ~ 2.3 nm. The upper limit of the Ni content (2 wt%) was found in the investigated catalysts providing the maximum efficiency of isomerization and formation of dimethylbutanes, and existence of the limit has been explained. It has been shown that upon isomerization of n-hexane on the acid-modified mordenite-containing rock, the formation of dimethylbutanes is not regulated by shape selectivity despite the larger kinetic diameter of the molecules as compared to mono-branched isomers. On the contrary, dimethylbutanes are more selectively formed inside zeolite micropores than in mesopores. The role of mesopores, mainly the regular system of nanoscale pores ø ~ 2.3 nm, is limited to providing transport routes for the reagents and reaction products. [ABSTRACT FROM AUTHOR]

Developing AI systems for automatic train operation (ATO) requires developers to have a deep understanding of the human tasks they are trying to replace. This paper fills this gap and translates the regulatory requirements from the context of German railways for the AI developer community. As a result, tasks such as train's path monitoring for collision prediction, signal detection, door operation, etc. are identified. Based on this analysis, a functionally justified sensor setup with detailed configuration requirements is presented. This setup was also evaluated by a survey within the railway industry. The evaluated sensors include RGB/IR cameras, LIDARs, radars and ultrasonic sensors. Calculations and estimates for the evaluated sensors are presented graphically and included in this paper. However, the ultimate sensor setup is still a subject of research. The results of this paper also address the lack of training and test datasets for railway AI systems. It is proposed to acquire research datasets that will allow the training of domain adaptation algorithms to transform other datasets, thus increasing the number of available datasets. The sensor setup is also recommended for such research datasets. [ABSTRACT FROM AUTHOR]

This paper presents a computational analysis of the evolution of mechanical characteristics in natural rock formations under the combined action of high-voltage electro-pulse and fluid injection. To solve the combined problem, a numerical solution based on a hydromechanical model is proposed. A system of anisotropic damage model is applied to capture tensile and shear damage. Innovative numerical simulations reveal that high-voltage electro-pulse can significantly enhance the effectiveness of rock-breaking in fluid injection. The simulation consists of two primary phases. First, high-voltage electro-pulse causes pre-damage and radial fissures in the rock formation, which creates a more favorable environment for subsequent fluid injection. The fluid flux is then conducted in the pre-damaged hole to fracture the rock formation further. The unique numerical method may have consequences for optimizing the rock-breaking strategy in geoengineering applications, such as the development of geothermal systems and the exploitation of oil/gas resources. Highlights: Presenting a novel method for rock-fracturing, high-voltage electropulse-assisted fluid injection. The hydro-mechanical coupled model is employed in the stage of electropulse and fluid injection. A system of tensile–shear mixed damage model is demonstrated and utilized to capture the tensile and shear damage. The in situ stress field and heterogeneity are considered to model natural rock formation. [ABSTRACT FROM AUTHOR]

An efficient system for the biosynthesis, isolation and purification of recombinant human neuroglobin has been developed and optimized, which makes it possible to produce protein in quantities sufficient to study its properties. According to UV-visible, IR-, CD-, and NMR spectroscopy data, recombinant neuroglobin is a structured protein in the holoform state. The data of chromato-mass-spectrometric analysis made it possible to conclude that there is a correctly formed disulfide bond in the structure of the oxidized form of the protein. Using Raman and surface-enhanced Raman spectroscopy with laser excitation at 532 nm, it was shown that heme in the reduced and oxidized forms of neuroglobin has vibrational degrees of freedom typical of b-type hemes, and the iron atom is hexacoordinated. Using Raman spectroscopy with laser excitation at 633 nm, it was found that reduced –SH-groups were present in reduced neuroglobin, while in oxidized neuroglobin a disulfide bridge was formed. The results obtained serve as the basis for detailed studies of the functioning of neuroglobin as a neuroprotector, in particular, during its interaction with oxidized cytochrome c, which is released from mitochondria in violation of their functioning and/or morphology. [ABSTRACT FROM AUTHOR]