High-level System Research Articles

Model Checking Distributed Protocols in Must

We describe the design and implementation of Must, a framework for modeling and automatically verifying distributed systems. Must provides a concurrency API that supports multiple communication models, on top of a mainstream programming language, such as Rust. Given a program using this API, Must verifies it by means of a novel, optimal dynamic partial order reduction algorithm that maintains completeness and optimality for all communication models supported by the API. We use Must to design and verify models of distributed systems in an industrial context. We demonstrate the usability of Must's API by modeling high-level system idioms (e.g., timeouts, leader election, versioning) as abstractions over the core API, and demonstrate Must's scalability by verifying systems employed in production (e.g., replicated logs, distributed transaction management protocols), the verification of which lies beyond the capacity of previous model checkers.

Dietary patterns related to attention and physiological function in high-altitude migrants.

High altitude exposure negatively affects human attentional function. However, no studies have explored the regulation of attentional and physiological functions from a dietary perspective. A total of 116 Han Chinese students from Tibet University who were born and raised in a plain area and had been living in Tibet for > 2 years were recruited. All participants were male migrants. A food frequency questionnaire, complete blood count, and attention network test were performed on the participants. Pearson's correlation was applied to assess the reliability and validity of the food frequency questionnaire. Principal component analysis was utilized to extract dietary patterns. A linear mixed model was employed to account for individual differences. The results showed that the five main dietary patterns were coarse grain, alcohol, meat, protein, and snacking dietary patterns. Furthermore, individuals who adhered to the coarse grain dietary pattern and had high mean corpuscular hemoglobin showed better attentional performance. Individuals with high alcohol consumption and systemic immune-inflammation index levels exhibited worse attentional performance. These findings imply that high-altitude migrants should include more coarse grains in their daily diet and avoid excessive alcohol consumption to improve attention.

Trust, regulation, and stewardship of the medical profession in India

In this paper we discuss the consequences of commercialisation of medicine and the associated shift in professional values, identity, and practices for patients, doctors, and health care organisations in India. We do so within the broader frame of the widely reported fall in trust in the health system in India, and with a view to reflect on how trust may be restored to a level which sustains a different but effective type of relationship between the medical profession and society. We draw on interviews with high-level health system and social actors in India to shed light on the key influences which shape the stewardship and governance of the health care system and the medical profession in the light of mounting evidence of and concerns around the erosion of public and patient trust in these institutions in India. Analysis is presented through four interrelated thematic articulations. Two themes highlight the practices of doctors and the actions of patients which contributed to changes in their relations and particularly a decline in trust. Two further themes focus on the policy and practice implications for regulation and stewardship of the health system and the medical profession.

Decreased Systemic Monocyte Colony Protein-1 (MCP-1) Levels and Reduced sCD14 Levels in Curcumin-Treated Patients with Moderate Anxiety: A Pilot Study.

Psychosocial stress may alter cortisol and/or affect the normal functioning of the immune system. Curcuminoids can promote beneficial effects in neuropsychiatric diseases. We evaluated whether curcumin supplementation for 15 consecutive days (1800 mg/day) would decrease systemic MCP-1, sCD14, and TNF alpha levels in patients with moderate anxiety (n = 81). A total number of 81 subjects were enrolled in this study, divided into the following groups according to their Hamilton scores: a control group including patients without anxiety who were not taking curcumin (Cont, n = 22) and an anxiety group including patients with moderate anxiety (Anx, n = 22). The curcumin-treated patients experienced moderate anxiety, and they take curcumin for 15 consecutive days (Anx-Cur (after), n = 15, 1800 mg/day). An evaluation of 128 patients was conducted, which allowed for their assignment to the study groups according to their scores on Hamilton scale II. The cortisol levels were quantified in salivary samples through ELISA (ng/mL), and malonaldehyde (MDA) levels were measured in plasma via the TBARS assay as an index of lipoperoxidation. Several systemic proinflammatory cytokines (pg/mL: MCP-1, TNF alpha, IL-1 beta) and mediators were quantified through ELISA (pg/mL), including systemic sCD14 levels as a marker of monocyte activation. A two-way bifactorial ANOVA was conducted to evaluate the contributions of the anxiety factor (Anx) and/or curcumin factor (Cur) in all the tested markers, including interactions between both factors. High systemic MCP-1 and elevated sCD14 levels were observed in patients with moderate anxiety, which were reduced with curcumin supplementation. In addition, curcumin prevented cortisol overexpression and decreased MDA levels as an antioxidant response in these patients. Collectively, curcumin presented anti-chemotactic effects by reducing systemic MCP-1 levels in anxiety. Curcumin decreased systemic MCP-1 as well as sCD14 levels in patients with moderate anxiety.

Altered co-stimulatory and inhibitory receptors on monocyte subsets in patients with visceral leishmaniasis.

Visceral leishmaniasis (VL) is a neglected tropical disease caused by parasites from the Leishmania (L.) donovani complex. VL is characterised by uncontrolled parasite replication in spleen, liver and bone marrow, and by an impaired immune response and high systemic levels of inflammation. Monocytes have been poorly characterised in VL patients. The aim of this study was to evaluate the expression levels of markers involved in the regulation of T cell responses on different subsets of monocytes from the blood of VL patients and healthy non-endemic controls (HNEC). Monocytes can broadly be divided into three subsets: classical, intermediate and non-classical monocytes. Our results show that the percentages of all three subsets stayed similar at the time of VL diagnosis (ToD) and at the end of anti-leishmanial treatment (EoT). We first looked at co-stimulatory receptors: the expression levels of CD40 were significantly increased on classical and intermediate, but not non-classical monocytes, at ToD as compared to EoT and HNEC. CD80 expression levels were also increased on intermediate monocytes at ToD as compared to EoT and HNEC, and on classical monocytes only as compared to HNEC. The levels of CD86 were similar at EoT and ToD and in HNEC on classical and intermediate monocytes, but significantly higher at EoT on non-classical monocytes. We also looked at an inhibitory molecule, PD-L1. Our results show that the expression levels of PD-L1 were significantly higher on all three monocyte subsets at ToD as compared to HNEC, and to EoT on classical and intermediate monocytes. These results show that monocytes from the blood of VL patients upregulate both co-stimulatory and inhibitory receptors and that their expression levels are restored at EoT.

Resection of the adipose fin from rainbow trout acutely alters the cerebral transcriptome and respiratory frequency

As many as 100 million salmonid fish are tagged annually by removing the adipose fin, usually for recovery statistics and the fishing industry. In a multi-parametrical approach, we evaluated the response to resection of the adipose fin in rainbow trout Oncorhynchus mykiss over the course of 72 h. Both the concentrations of lactate and the cerebral transcriptomes differed in rainbow trout early after adipose fin clipping compared to the matching intact controls. The number of differentially expressed genes significantly increased, first in the midbrain and later in the forebrain, in fin-clipped compared to intact trout. Several of these genes were predicted to be involved in pain-induced and synaptogenesis-related pathways, suggesting that adipose fin resection may affect the architecture of neuronal networks. In an experimental setup applying swimming tunnels, we tested whether removal of the adipose fin had any consequences on the behavior of fin-clipped versus intact trout exposed to a regularly recurring water flow. Concomitant with increased and prevailing breath frequencies after repeated exposure to water flows, we observed a marked transcriptional response in the forebrain of fin-clipped trout compared with intact unchallenged controls at later time points after the resection. The resulting list of differentially expressed genes was assigned to a broad range of signaling pathways involved in trans-synaptic signaling, neuronal interaction dynamics, and neuroplasticity. Taken together, our findings suggest that resection of the potentially flow-sensory adipose fin alters pathways related to pain perception and likely enhances the physiological response to the current, probably indicating increased physical effort. We also deduce from the transcriptomic data that amputation of the adipose fin leads to reorganization of the high-level integration system in the brain. The short-term effects observed in the present study require further validation to estimate the prevailing stress for the organism. Nevertheless, we propose considering alternative tagging methods for salmonid fish that do not conflict with fish welfare, as the amputation of the adipose fin may have more far-reaching physiological effects than previously assumed.

Lymphocyte Levels and Morbidity and Mortality in Cardiovascular Surgery With Cardiopulmonary Bypass.

A year ago, in a sample of 113 patients, our research group found that a high number of lymphocytes in the immediate postoperative period was correlated to a poor prognosis in cardiovascular surgeries. This study is an expansion of the initial study in order to confirm this finding. We analyzed the data of 338 consecutive patients submitted to cardiovascular surgeries with cardiopulmonary bypass performed at Hospital Universitário Ciências Médicas (Belo Horizonte/Brazil) from 2015 to 2017. We analyzed 39 variables with the outcomes death, hospital stay, and intensive care unit stay. The value of lymphocytes in the immediate postoperative period > 2175.0/mm³ was an indicator of poor prognosis in this sample (P<0.001). The variables female sex, age, high level of European System for Cardiac Operative Risk Evaluation II, increased stay in the intensive care unit and in the ward, elevation of creatinine in the preoperative period and at intensive care unit discharge, elevation of the percentage of immediate postoperative period segmented neutrophils, high immediate postoperative period neutrophil/lymphocyte ratio, fasting hyperglycemia, preoperative critical condition, reintubation, mild or transient acute renal failure, surgical infection, cardiopulmonary bypass, and aortic cross-clamping and mechanical ventilation durations also had an impact on the mortality outcome. The value of lymphocytes in the immediate postoperative period > 2175.0/mm3 was an indicator of poor prognosis in cardiovascular surgery with cardiopulmonary bypass.

IHR-PVS National Bridging Workshop for Somalia: An interactive and participatory approach for operationalizing the One Health roadmap

BackgroundNational Bridging Workshops (NBW) are a tool for reviewing collaboration gaps between line ministries relevant to the One Health framework. MethodsThe NBW for Somalia was held on November 11–13, 2023 in Nairobi, Kenya with support from WHO and WOAH. Participants included representatives from the Somali government both national and sub-national (including Ministry of Health; Ministry of Livestock, Forestry and Range; Ministry of Agriculture and Irrigation; and Ministry of Environment and Climate Change). Other participants included representatives from non-governmental organizations, academia and the quadripartite. Structured sessions guided participants through a step-by-step process, starting from identifying gaps to collectively developing solutions. The design of these sessions aimed to foster active engagement and collaboration with the outcomes of each session contributing to the subsequent one. ResultsA total of 60 participants partook in the exercise, representing human health (35%), animal health (27%), agriculture (13%), environmental health (7%) and other relevant sectors (18%). Eighty-three percent of participants represented the national level and 17% the sub-national level. The collaborative effort yielded a joint roadmap comprising 36 activities and 11 objectives. Priority objectives included: development of national joint surveillance systems for selected One Health threats (41/47 votes, or 87% of the total votes); establishment of a high-level ministerial system to govern and coordinate One Health activities (30/47; 64%); and establishment of emergency funding structures for priority zoonotic diseases along with development of a 5-year national investment plan for One Health (27/47; 57%). A total of 94% of activities required low or moderate cost to be implemented, and 90% of activities were identified to have a likely high impact on multisectoral collaboration. The timeline for implementing the activities is projected to span one to two years. ConclusionThe workshop promoted high-level engagement, national ownership, and leadership in addressing health threats at the human-animal-environment interface. The resulting co-created roadmap will be integrated into the National Action Plan for Health Security, supporting ongoing One Health efforts in Somalia.

Research on the Teacher Education Training System Under the Perspective of Deep Learning

In the context of informatization, deep learning has become an important way of education and teaching. In order to implement the requirements of the reform of the teacher education training system in the new era and meet the social demand for high-quality teachers, this paper explores the teacher education training system under the perspective of deep learning. Taking university teacher education as the research object, through a preliminary investigation of the university teacher education training system, the current status of the teacher education training system is grasped as a whole, and through literature combing and content analysis, the theoretical interpretation of deep learning is explored, and the research on the teacher education training system under the perspective of deep learning is explored, so as to establish and improve the teacher education training system and respond to national policies to build a high-level teacher training system.

ANALYSIS OF THE INVESTMENT CLIMATE OF DENMARK

The investment climate is a key factor for attracting capital, stimulating innovation and strengthening competitiveness. The purpose of the study is to analyze the current state of the in- vestment environment in the country, assess its attractiveness for foreign investors, and reveal the main factors affecting the development of business in Denmark as one of the leading countries of the European Union. The analysis of the investment attractiveness of the country is based on the research of available data, official reports and other sources of information. A general overview of the current investment climate in Denmark indicates that the country continues to be an attractive destination for investors. The country is known for its stable economy, high level of innovation and strong legal system, which creates a favorable environment for investment. The article carried out a thorough analysis of not only the main macroeconomic indicators, but also a comparative anal- ysis of investor protection, analyzed the dynamics of the corruption perception index, the level of education among the country’s population, and analyzed the innovative environment of Denmark. In addition, the article discusses the types of risk for investing in the Danish economy. Denmark’s successful competitiveness is due to a combination of several factors: emphasis on innovation and research, high quality education, flexible labor market, efficient infrastructure, state support for en- trepreneurship and a stable political and economic situation. The results of the study provide con- crete recommendations for government and business, promoting investment attraction and sustain- able economic growth in Denmark. The country has significant potential for further development of its investment climate thanks to numerous advantages, in particular in the fields of green energy and information technology. Denmark is pursuing an energy efficiency policy and phasing out fos- sil fuels, as well as investing in digital infrastructure. However, there are certain risks, such as po- litical and legislative changes, geopolitical factors, changes in international trade and market com- petition, which may affect investment activities in the country. Investors need to carefully analyze these risks and take them into account in their risk management strategies.

Digital Twin and Simulation Analyses for Process Optimization of an Automated Guided Vehicle System

Development in industrial companies aims to digitize processes, ensure traceability and advance automation. Systems with automated guided vehicles (AGVs) can help meet these objectives. A core element of these systems is the higher-level system controller. When an AGV system is operated, some dynamic aspects appear. It is then to identify, that the previous specified rules for scheduling and routing of vehicles are not always proper and practical, which may result in waiting time of AGVs. That means the static performance requirements and the specifications based on them often lead to suboptimal results. A methodical problem-solving approach is to develop a digital twin as a reflection of reality and to carry out strategy analyses using simulation. For this purpose, a digital twin of the concerned AGV system with five vehicles and its technological environment is created using software of plant simulation. Various simulation scenarios are developed to simulate material flows by using different routing and scheduling rules and strategies. Drawing from the insights gained through the digital twin and simulation analyses, this study identifies novel scheduling and routing rules for the AGV system. These rules improve the overall efficiency and effectiveness of the system operations by easing traffic congestion, reducing transit time, and minimizing production downtime.

Expression, Purification and Characterization of Recombinant Disintegrin from Gloydius Brevicaudus Venom in Escherichia Coli.

Disintegrins, a family of snake venom protein, which are capable of modulating the activity of integrins that play a fundamental role in the regulation of many physiological and pathological processes. The main purpose of this study is to obtain the recombinant disintegrin (r-DI) and evaluate its biological activity. In this study, we explored a high-level expression prokaryotic system and purification strategy for r-DI. Then, r-DI was treated to assay effects on cell growth, migration, and invasion. The affinity for the interactions of r-DI with integrin was determined using Surface plasmon resonance (SPR) analyses. The r-DI can be expressed in Escherichia coli and purified by one-step chromatography. The r-DI can inhibit B16F10 cells proliferation, migration, and invasion. Also, we found that r-DI could interact with the integrin αIIbβ3 (GPIIb/IIIa). The r-DI can be expressed, purified, characterized through functional assays, and can also maintain strong biological activities. Thus, this study showed potential therapeutic effects of r-DI for further functional and structural studies.

Roadmap for the increase of beam brilliance from ECRIS and Microwave Discharge Ion Sources

The requirements for future accelerator chains need to increase the injected beam brilliance significantly, still keeping high the beam quality in terms of reliability, reproducibility and stability. A roadmap for ion source development may consist of several steps: plasma simulation, multiphysics simulation of each system component, high-level control system, plasma characterization, beam characterization, data analysis and, again, plasma simulation. The cycle starts and ends with plasma simulation because it is the instrument that shows how different phenomena take part in the plasma and beam formation and because, in such a way, the accuracy grows with each cycle. Commercial multiphysics simulation tools are essential for adequately designing all ion source equipment: magnets, intense electrostatic field regions, microwave propagation and coupling, thermal dissipation and vacuum. The dependence of source performances from source parameters (magnetic field profile, gas pressure, microwave power) has been widely investigated using a high-level control system[1] able to test tens of thousands of source configurations without human interaction. This characterization technique allowed us to identify a new magnetic configuration, High Stability Microwave Discharge Ion Sources[2], that produces a beam with high stability, intensity and brilliance. The plasma simulation tool we developed discloses the role of two types of electrostatic waves in plasma formation and their correlation to stability. The simulation provides a complete view of ions and electrons energy and density distributions, the formation of the plasma meniscus and the beam extraction. The paper will present the results obtained with this development procedure on Microwave Discharge Ion Sources and how we started to apply it to the Electron Cyclotron Resonance Ion Sources development.

The landscape of inequalities in dementia across Europe: First insights from the INTERDEM taskforce.

Getting a diagnosis of dementia does not equate to equitable access to care. People with dementia and unpaid carers face many barriers to care, which can vary within, and across, different countries and cultures. With little evidence across different countries, the aim of this scoping exercise was to identify the different and similar types of inequalities in dementia across Europe, and provide recommendations for addressing these. We conducted a brief online survey with INTERDEM and INTERDEM Academy members across Europe, and with members of Alzheimer Europe's European Working Group of People with Dementia and Carers in February and March 2023. Members were asked about whether inequalities in dementia care existed within their country; if yes, to highlight three key inequalities. Responses on barriers were coded into groups, and frequencies of inequalities were calculated. Highlighted inequalities were discussed and prioritised at face-to-face and virtual consensus meetings in England, Ireland, Italy, and Poland, involving people with dementia, unpaid carers, health and social care providers, and non-profit organisations. Forty-nine academics, PhD students, people with dementia and unpaid carers from 10 countries (Belgium, Denmark, Germany, Greece, Ireland, Italy, Poland, Malta, Netherlands, UK) completed the survey. The most frequently identified inequalities focused on unawareness and lack of information, higher level system issues (i.e. lack of communication among care professionals), lack of service suitability, and stigma. Other barriers included workforce training and knowledge, financial costs, culture and language, lack of single-point-of-contact person, age, and living location/postcode lottery. There was general consensus among people living dementia and care providers of unawareness as a key barrier in different European countries, with varied priorities in Ireland depending on geographical location. These findings provide a first insight on dementia inequalities across Europe, generate cross-country learnings on how to address these inequalities in dementia, and can underpin further solution-focused research that informs policy and key decision makers to implement changes.

Systemic barriers hinder person-centered home and community based services (HCBS): Perspectives of service users and professionals

BackgroundIn response to the 2014 Final Settings Rule issued by the Centers for Medicaid and Medicare Services, home-and-community based services (HCBS) provider organizations strengthened person-centered (PC) planning for HCBS to improve participants' choice and control over their services. Despite the call for widespread adoption of PC services, systemic barriers influence service users’ and professionals' experiences in receiving and delivering PC services. ObjectiveThis study describes the perspectives of HCBS professionals and users on systemic barriers that affect PC HCBS delivery. MethodsSemi-structured interviews with 20 HCBS users and 22 HCBS professionals explored perspectives on providing and receiving PC HCBS as well as higher level systems challenges to providing PC services. Qualitative analysis focused on participants’ perspectives of system-level issues. ResultsQualitative analysis generated three themes: (1) Workforce considerations; (2) Resources and service access; and (3) Infrastructure for feedback. High direct service provider turnover rates, service-eligibility determination procedures, and waitlists affected service delivery. Participants highlighted a need for increased direct service provider compensation, access to higher-quality training, improved financial resources, and effective feedback infrastructures. Waiver flexibility due to the Covid-19 public health emergency allowed expanded service access and improved quality. ConclusionOrganizational and system-level issues hinder delivery of PC services. Increased flexibility and resource allocation for service provision, as demonstrated in the Covid-19 public health emergency response, should be sustained. HCBS users’ suggestions for service-delivery improvements are consistent with recent state and organizational initiatives. HCBS improvements benefit from user-identified solutions in program development and implementation.

Electric Vehicle Battery Disassembly Using Interfacing Toolbox for Robotic Arms

This paper showcases the integration of the Interfacing Toolbox for Robotic Arms (ITRA) with our newly developed hybrid Visual Servoing (VS) methods to automate the disassembly of electric vehicle batteries, thereby advancing sustainability and fostering a circular economy. ITRA enhances collaboration between industrial robotic arms, server computers, sensors, and actuators, meeting the intricate demands of robotic disassembly, including the essential real-time tracking of components and robotic arms. We demonstrate the effectiveness of our hybrid VS approach, combined with ITRA, in the context of Electric Vehicle (EV) battery disassembly across two robotic testbeds. The first employs a KUKA KR10 robot for precision tasks, while the second utilizes a KUKA KR500 for operations needing higher payload capacity. Conducted in T1 (Manual Reduced Velocity) mode, our experiments underscore a swift communication protocol that links low-level and high-level control systems, thus enabling rapid object detection and tracking. This allows for the efficient completion of disassembly tasks, such as removing the EV battery’s top case in 27 s and disassembling a stack of modules in 32 s. The demonstrated success of our framework highlights its extensive applicability in robotic manufacturing sectors that demand precision and adaptability, including medical robotics, extreme environments, aerospace, and construction.

Mechanism for ensuring risk resistance in the system of management of enterprises in crisis conditions

The article proposes the structure and relationship of the elements of the mechanism for ensuring risk resistance in the system of managing the activities of enterprises in crisis conditions, which includes three main components: resource, organizational, and support system, each of which contains several elements. It was established that the dual role of risk resistance in the enterprise management system is that, on the one hand, risk resistance contributes to purposeful functioning and development, affecting the overall results of operations. On the other hand, it is determined by the interaction of the enterprise with higher-level systems, as well as internal and external factors that can become sources of risk in crises. It is emphasized that the structure of the mechanism for ensuring risk resistance, being complex and dynamic, requires constant improvement. Regardless of operating conditions and strategic goals, an enterprise must have a mechanism for ensuring risk resistance that best meets its needs. It is justified that the resource component of the mechanism for ensuring the risk resistance of the enterprise includes financial resources of the enterprise; material and technical resources necessary for the organization and ensuring the continuity of the enterprise's risk activities; personnel resources, which are determined by the number of employees engaged in analysis, assessment, and risk management. The organizational component of the mechanism for ensuring risk resistance includes organizing the most effective use of the resources involved, namely methods of analysis, assessment, and management of risks, as well as socio-economic relations arising in the process of a risky situation. The third component of the mechanism for ensuring risk resistance – the security system – includes regulatory and legal, information security, and corporate culture. Keywords: risk resilience, uncertainty, crisis conditions, anti-crisis management, strategic enterprise management.

A novel approach for improving open scene text translation with modified GAN

AbstractText, as a vital tool for communication, is playing an imperative role in modern society. Precise high-level text translation systems are essential requirements in a wide range of real-world applications, such as robot navigation, industrial automation, image search, and instant translation. Regardless of improved research, a series of grand challenges may still become upon when translating text automatically in the real-world from open scene images. The difficulties mainly stem from multiplicity and inconsistency of text in open scenes, complication and obstruction of backgrounds, and deficient imaging conditions in uncontrolled circumstances for open scene images. The existing deep learning-based text translation systems do not eliminate the text for translation, and these applications just replace text on the reconstructed scene. To address the abovementioned shortcomings, this study proposed a novel approach for open scene text translation. Our system consists of five modules including scene text detection, text recognition, text elimination, text translation, and text insertion along with scene reconstruction. The novelty presented by our model lies in the idea of first eliminating the text from the open scene for accurate translation and then reconstructs the translated text on the image for its proper alignment. We specifically modified the existing generative adversarial network (GAN) architecture for improved performance of text elimination by introducing a novel strategy of text and scene concatenation to reduce the overall loss function. For this purpose, we created a synthetic dataset to train our GAN for text elimination module. Experiments on various standard text translation systems demonstrate that our integrated system is able to outperform state-of-the-art approaches in terms of result quality. We have achieved 90.87% of precision, 83.66% of recall, 87.116% of F1-score, and reduced both losses ($$l_1$$ l 1 and $$l_2$$ l 2 ) up to 50% which is remarkable upon state-of-the-art translation systems.

Estimating Accident Reduction Rate after Maritime Traffic Safety Assessment Using Synthetic Minority Oversampling Technique and Machine Learning Algorithm

This study was focused on deriving the MTSA-related accident reduction rate (ARR) required to calculate the safety benefits before and after expanding the scope of the system. By performing spatial analysis using geographic information system technology, MTSA-related accidents were identified on maritime routes near both assessed and unassessed project sites from 2010 to 2014. Subsequently, by applying the synthetic minority oversampling technique to balance the data, the algorithm learned from the random forest using the operational data of coastal passenger ship operations and accident data near unassessed locations where MTSA is not implemented. Then, the trained model was applied to predict accident occurrence in the absence of MTSA near the latest operational information of coastal passenger ship operations at the assessed project sites. The MTSA-related ARR was then calculated by applying the actual accident occurrences during operation near the assessed project sites where MTSA was implemented. The MTSA-marine ARR calculated at 17.41% can be applied to the calculation of safety benefit for MTSA. The results of this study can provide quantitative evidence for the application of higher-level systems considering the burden on regulatory targets when improving MTSA or similar systems.

The language network as a natural kind within the broader landscape of the human brain.

Language behaviour is complex, but neuroscientific evidence disentangles it into distinct components supported by dedicated brain areas or networks. In this Review, we describe the 'core' language network, which includes left-hemisphere frontal and temporal areas, and show that it is strongly interconnected, independent ofinput and output modalities, causally important for language and language-selective. We discuss evidence that this language network plausibly stores language knowledge and supports core linguistic computations related to accessing words and constructions from memory and combining them to interpret (decode) or generate (encode) linguistic messages. We emphasize that the language network works closely with, but is distinct from, both lower-level - perceptual and motor - mechanisms and higher-level systems of knowledge and reasoning. The perceptual and motor mechanisms process linguistic signals, but, in contrast to the language network, are sensitive onlyto these signals' surface properties, not their meanings; the systems of knowledge and reasoning (such as the system that supports social reasoning) are sometimes engaged during language use but are not language-selective. This Review lays a foundation both for in-depth investigations of these different components of the language processing pipeline and for probing inter-component interactions.