Individual Links Research Articles

On current problems of the mechanism of liability of judges for disciplinary misconduct: law enforcement practice, general approaches Part 4. Approaches to improving and improving the efficiency of the organizational and legal mechanism of disciplinary responsibility of judges (Continuation)

In the final, fourth part of the article, published in 2024 in the journal “State and Law”, certain results of the problems considered in its first three parts are summed up (part 1 – “Termination of the powers of a judge for a serious offense after the constitutional innovations of 2020 – constitutional or disciplinary responsibility?” (No. 3); part 2 – “On problems of disciplinary responsibility of court heads” (in two sections) (No. 4, 5); part 3 – “On the disciplinary responsibility of retired judges” (No. 6)). Conclusions are drawn about the imperfection of this mechanism with specific examples of law enforcement (and especially judicial) practice, including those caused by the imperfection of legislation in the area of public relations under consideration. Specific, including radical, proposals are being made aimed at improving and increasing the effectiveness of both the named mechanism as a whole and its individual links.

Time-evolving traffic resilience performance forecasting during hazardous weather toward proactive intervention

Transportation systems experience significant disruptions and loss during hazardous weather events, exhibiting great needs of timely intervention to effectively improve the resilience of the affected traffic systems. An informed and science-based proactive intervention strategy depends on accurate forecasting of the resilience performance of traffic systems with essential lead time during hazards. A new resilience performance forecasting methodology at both global and local scales is proposed for traffic networks under natural hazards by addressing unique challenges such as scarcity and time-evolving nature of hazard-specific data. The proposed methodology consists of two modules: the local traffic resilience performance short-term forecasting module based on the modified diffusion convolutional recurrent neural network (DCRNN) and transfer learning techniques, and the global traffic resilience performance forecasting module integrating percolation-based robustness assessment and SIR-based congestion propagation modeling. A case study of an urban traffic network during a major snowstorm hazard is conducted as a demonstration, followed by the feasibility investigation to guide proactive intervention during hazards. It is found the proposed methodology can forecast the time-evolving traffic resilience performance with good accuracy at both global and local scales. With sufficient lead time for the forecast, it bears promising potential to assist the stakeholders to make informed and timely decision about possible proactive intervention by providing key information to help identify the optimal moments and individual strategic links for possible intervention.

RESEARCH AND EVALUATION OF LOGISTICS SCHEMES EFFICIENCY FOR THE GRAIN LOADS TRANSPORTATION FOR EXPORT UNDER THE CONDITIONS OF THE MILITARY STATE

Purpose. The aim of the work is to study the effectiveness of various logistics schemes for the delivery of grain cargoes for export from production sites to its transshipment points - to sea ports and to border terminals on the border with the countries of the European Union. Methodology. In the research process analysis and synthesis methods were used to study the content and main provisions of scientific publications on the state of the logistic system of transporting Ukrainian grain for export, the theory of operational work of railways for the development of logistics schemes for the delivery of grain cargoes, methods of mathematical statistics for the analysis of tariffs for road transportation, methods of technical economic calculations and determination of transportation tariffs. Results. In order to evaluate the effectiveness of grain delivery logistics schemes, the routes from one of the areas with the largest concentration of grain loading to a large seaport and to a railway and road border checkpoint were considered. At the same time, the following logistics schemes of grain delivery were chosen: automobile transportation by grain trucks and in containers, railway transportation by wagons and route shipments in grain wagons and in containers on fitting platforms. Calculations showed that transportation costs in the direction of ports are 10...15% lower than for transportation to land checkpoints; rail transportation is generally 30...40% cheaper than road transportation, and transportation in containers allows to save 20...25% of the cost of transportation. Scientific novelty. The obtained results make it possible to provide a scientific and economic basis for the development and improvement of the grain cargo transportation system, as well as for the optimization of the parameters of its individual links. Practical significance. Analysis and improvement of grain transportation logistics schemes will increase the efficiency of grain export logistics, reduce the share of the logistics component in the final cost of Ukrainian grain and, accordingly, increase both its competitiveness on foreign markets and foreign currency revenues to the state budget.

Individually tunable tunnelling coefficients in optical lattices using local periodic driving

Abstract Ultracold atoms in optical lattices have emerged as powerful quantum simulators of translationally invariant systems with many applications in e.g. strongly-correlated and topological systems. However, the ability to locally tune all Hamiltonian parameters remains an outstanding goal that would enable the simulation of a wider range of quantum phenomena. Motivated by recent advances in quantum gas microscopes and optical tweezers, we here show theoretically how local control over individual tunnelling links in an optical lattice can be achieved by incorporating local time-periodic potentials. We propose to periodically modulate the on-site energy of individual lattice sites and employ Floquet theory to demonstrate how this provides full individual control over the tunnelling amplitudes in one dimension. We provide various example configurations realising interesting topological models such as extended Su–Schrieffer–Heeger models that would be challenging to realise by other means. Extending to two dimensions, we demonstrate that local periodic driving in a Lieb lattice engineers a two-dimensional (2D) network with fully controllable tunnelling magnitudes. In a three-site plaquette, we show full simultaneous control over the relative tunnelling amplitudes and the gauge-invariant flux piercing the plaquette, providing a clear stepping stone to building a fully programmable 2D tight-binding model. We also explicitly demonstrate how utilise our technique to generate a magnetic field gradient in 2D. This local modulation scheme is applicable to many different lattice geometries.

The mediating role of self-esteem in the relationship between hope and life satisfaction among university students during a global health crisis.

The worldwide health emergency sparked by the COVID-19 pandemic has deeply shaken educational environments, posing unprecedented challenges to university students' well-being. While individual links between self-esteem, hope, and well-being are established, their combined impacts during crises remain underexplored. Our study addresses this gap by investigating the interplay among hope, self-esteem, and life satisfaction within the context of university students navigating the challenges posed by the pandemic. Conducting an online cross-sectional self-administered survey during Hong Kong's third pandemic wave, we measured hope, self-esteem, and life satisfaction using validated scales. Three hundred and fifteen university students (211 females; mean age = 22.08; SD = 2.74) participated. Through multiple regression and mediation analyses, our findings indicate that university students with elevated hope and self-esteem scored higher on life satisfaction measures. Specifically, our analysis revealed that self-esteem may serve as a partial mediator in the relationship between hope and life satisfaction, highlighting how heightened hope indirectly enhances life satisfaction by strengthening self-esteem. This study reveals intricate relationships among hope, self-esteem, and life satisfaction in university students, particularly during external adversities like the COVID-19 pandemic. The implications extend to mental health interventions, emphasizing the potential benefits of cultivating hope and self-esteem to enhance life satisfaction among university students confronting formidable challenges.

A methodology for ranking of critical links in transportation networks based on criticality score distributions

Criticality of transportation networks links is calculated through utilizing criticality metric(s) for various disruption scenarios that generally include one link removal/degradation at a time or simultaneous removal/degradation of multiple links. As also shown in this paper, single link removals do not reveal the actual criticality of link(s) due to network dependencies. Multiple simultaneous link removal scenarios can capture the network interactions; however, the results relate to the criticality ranking of scenarios than the links, e.g., the links in scenario-1 are more critical than the links in scenario-2. This paper addressed the need for a methodology that provides individual link criticality rankings based on failure scenarios. The proposed approach utilizes the distribution of the criticality scores for each link based on running traffic assignment for each failure scenario, e.g., the distribution for link #X is composed of the criticality scores of all link failure combinations that include link #X. The criticality ranking for each link is identified based on its criticality distribution's mean, coefficient of variation and skewness. The use of the proposed approach is illustrated on test networks to show that it provides robust link criticality rankings that accounts for network interactions across varying scales of link failure scenarios.

Topology optimization of vertical shear links in eccentrically braced frames

The inclusion of additive manufacturing (AM) in the construction industry has opened new perspectives on the production of structural members. By coupling AM technologies with topology optimization (TO), significant reductions in material usage and weight can be achieved. Although TO has been applied to optimize simply supported beams, additional factors such as stress concentrations, buckling, and low-cycle fatigue from seismic loads require further investigation. This study presents a numerical approach for optimizing shear links subjected to monotonic and cyclic loading. The numerical models for conventional shear links were validated against experimental work, including cyclic loading tests on individual shear links and scaled eccentrically braced frames (EBF). The implementation of TO led to a 12 % volume reduction in the first optimized link. The optimized link demonstrated superior performance, exhibiting higher shear strength and energy dissipation capacity under both monotonic and cyclic loading. Another study examined EBFs with vertical links, achieving 12 % and 30 % reduction in material volume. The optimized links showed improvements that reached 25 % compared to the conventional link in terms of strength and energy dissipation with 12 % volume reduction, while 30 % volume reduction showed slightly less improvement over EBFs with conventional shear links.

Status and molecular genetic parameters of papillomavirus infection: individual characteristics and associative links with clinical and morphological factors of cervical cancer

Status and molecular genetic parameters of papillomavirus infection: individual characteristics and associative links with clinical and morphological factors of cervical cancer

Enhanced Security and Privacy via Fragmented Federated Learning.

In federated learning (FL), a set of participants share updates computed on their local data with an aggregator server that combines updates into a global model. However, reconciling accuracy with privacy and security is a challenge to FL. On the one hand, good updates sent by honest participants may reveal their private local information, whereas poisoned updates sent by malicious participants may compromise the model's availability and/or integrity. On the other hand, enhancing privacy via update distortion damages accuracy, whereas doing so via update aggregation damages security because it does not allow the server to filter out individual poisoned updates. To tackle the accuracy-privacy-security conflict, we propose fragmented FL (FFL), in which participants randomly exchange and mix fragments of their updates before sending them to the server. To achieve privacy, we design a lightweight protocol that allows participants to privately exchange and mix encrypted fragments of their updates so that the server can neither obtain individual updates nor link them to their originators. To achieve security, we design a reputation-based defense tailored for FFL that builds trust in participants and their mixed updates based on the quality of the fragments they exchange and the mixed updates they send. Since the exchanged fragments' parameters keep their original coordinates and attackers can be neutralized, the server can correctly reconstruct a global model from the received mixed updates without accuracy loss. Experiments on four real data sets show that FFL can prevent semi-honest servers from mounting privacy attacks, can effectively counter-poisoning attacks, and can keep the accuracy of the global model.

A scoping review on cycling network connectivity and its effects on cycling

ABSTRACT There is growing recognition of the importance of a well-connected cycling infrastructure. Common connectivity measures apply aggregate area-based metrics, such as the number of streets per transportation analysis zone or census area. However, such measures capture cyclist movement insufficiently, as cyclist movement easily extends beyond areas, and variations in the sizes and shapes of areas lead to inconsistent outcomes. In contrast to area-based connectivity, network connectivity considers the connectivity of the entire cycling network, capturing the continuity or discontinuity of routes. Certain measures can account for other important aspects, such as topology and the relative importance of individual links in large networks. Although previous reviews have covered several aspects of cycling infrastructure, no review has been dedicated to the measures, methods and models applied to assess network connectivity or the impact of increased network connectivity on cycling behaviour. We conduct a scoping review of measures, methods, models, and data sources to assess cycling network connectivity and review associations between network connectivity and travel behaviour. The findings suggest an increase in the number of publications on network connectivity up to 2019, followed by a plateau in the number of studies but with more complex methods. However, that complexity may constitute a barrier to practical implementation. We conclude that empirical verifications regarding the effects of network connectivity on travel behaviour remain a research gap, even in high-cycling countries, with evidence further limited by limited link-level travel data. Future research should also focus on developing more consistent and validated metrics.

Neurobiological aspects of pathogenesis and therapy of tension headache

The study presents an analysis of the literature devoted to the study of neurobiological processes of pathogenesis and therapy of tension headache. The characteristics of individual links of pathogenesis are given. Medicinal and non-medicinal methods of therapy of this pathological condition are considered.

ML-Enhanced Live Video Streaming in Offline Mobile Ad Hoc Networks: An Applied Approach

Live video streaming has become one of the main multimedia trends in networks in recent years. Providing Quality of Service (QoS) during live transmissions is challenging due to the stringent requirements for low latency and minimal interruptions. This scenario has led to a high dependence on cloud services, implying a widespread usage of Internet connections, which constrains contexts in which an Internet connection is not available. Thus, alternatives such as Mobile Ad Hoc Networks (MANETs) emerge as potential communication techniques. These networks operate autonomously with mobile devices serving as nodes, without the need for coordinating centralized components. However, these characteristics lead to challenges to live video streaming, such as dynamic node topologies or periods of disconnection. Considering these constraints, this paper investigates the application of Artificial Intelligence (AI)-based classification techniques to provide adaptive streaming in MANETs. For this, a software-driven architecture is proposed to route stream in offline MANETs, predicting the stability of individual links and compressing video frames accordingly. The proposal is implemented and assessed in a laboratory context, in which the model performance and QoS metrics are analyzed. As a result, the model is implemented in a decision forest algorithm, which provides 95.9% accuracy. Also, the obtained latency values become assumable for video streaming, manifesting a reliable response for routing and node movements.

Factors of pathogenicity of bacteria of the genus Campylobacter and their role in carcinogenesis

Bacteria of the genus Campylobacter are a known common cause of gastroenteritis. However, in recent years, there has been more and more evidence in the scientific literature that these bacteria play an essential role in the development of malignant tumors of the human digestive tract. The aim is to systemize data on pathogenicity/virulence factors of Campylobacter spp. and its role in human carcinogenesis. The review provides a general description of the representatives of the genus in question, indicating their current taxonomic position and importance in human infectious pathology. A detailed description of known pathogenicity/virulence factors, including those with species-specific and strain-specific affiliation, is given. The indirect role of Campylobacter spp. in the mechanism of carcinogenesis has been shown due to the effect on individual links of the immune defense of the human body (e.g., on a pool of proinflammatory cytokines), which supports a chronic focus of inflammation and provokes further malignant cell degeneration. The direct effect of cytolethal expanding toxin (CDT) of Campylobacter as an essential link in carcinogenesis is considered. The facts of tumor-associated interaction of Campylobacter spp. with other bacteria of the human digestive tract are presented. Conclusion. The available data indicate a significant contribution of individual factors of Campylobacter spp. pathogenicity to the mechanisms of malignant neoplastic transformation of human digestive tract cells. CDT plays an essential role among other pathogenesis links.

Decision support for improved construction traffic management and planning

Densifying cities continuously call for new construction, renovation and demolition projects, each generating vast amounts of heavy goods vehicle (HGV) transports. However, how construction transportation affects the urban traffic network remains largely unexplored. This study addresses spatiotemporal network impacts from construction transport, by leveraging traditional traffic and transport simulation. To this end, a framework is presented including (i) a simulation model to compute traffic effects caused by varying off-site construction site transport demands, and (ii) conceptual applications of the simulation model showing construction logistic planning strategies to mitigate congestion disturbances. Simulations are conducted in MATSim using detailed secondary datasets describing site-specific transport arrivals from a case of six projects in Norrköping, Sweden. Subsequently, increasing transport demands were assessed on various time-window arrival scenarios against the baseline schedule, which can be used as decision support in urban planning. Results highlight how rigorous construction transport planning avoiding peak-traffic hours can significantly alleviate traffic congestion. This study also emphasizes the need to combine all simultaneous construction projects’ demands when evaluating disturbances on city-level, alongside the impact on individual links and microenvironments. This study adds knowledge by visualizing the traffic impact during urban transformation.

Study of the effect of a drug from the macromycetes Ganoderma lucidum on the phagocytic activity of peripheral blood neutrophils in patients with year-round allergic rhinitis

Modern complex therapy of patients with persistent (year-round, chronic) allergic rhinitis (AR), based on the use of antihistamines and intranasal glucocorticosteroids, in many cases is not effective enough, since drug therapy acts only on individual links in the pathogenesis, without preventing the progression of the allergic disease. At the same time, the quantitative and reserve capabilities of neutrophil granulocytes are depleted, which increases the level of antigenic load in patients with AR. The aim of this study is to investigate the phagocytic activity of neutrophils in patients with AR who received basic therapy and patients who received basic therapy and a course of the drug from the macromycetes Ganoderma lucidum "Astmagan". We examined 40 patients of both sexes with AR, the duration of the disease ranged from 6 months to 2 years. Patients were divided into 2 equal groups: The 1st group consisted of patients who received basic therapy (oral Loratadine and intranasal Nasonex). The 2nd group consisted of patients who received basic therapy and a course of "Astmagan". The treatment course lasted 90 days. The control group consisted of 25 healthy individuals. After the treatment, patients in both groups showed a statistically significant positive dynamics of phagocytic system activity: in group 1, the phagocytic index (FI) increased by 30 % (p=0.001), in the second group this indicator reached the normal level. Also, in patients of group 1, the phagocytic number (PN) increased by 35 % (p=0.0001), but did not reach the normal level.
 According to the results of comparative evaluation, a greater efficacy of the treatment complex with the additional use of "Astmagan" was established, which is manifested in the restoration of phagocytic activity of peripheral blood neutrophils, the effect persists for 6 months after treatment.

The role of hematological coefficients of systemic inflammation in the diagnosis and risk assessment of affective disorders

The review article highlights the problem of using hematological coefficients of systemic inflammation in clinical practice, as well as the results of studies aimed at its use in the diagnosis and evaluation of therapeutic response in the treatment of mood disorders. The contribution of each individual link of the immune system to the pathogenesis of an inflammatory reaction is known, but currently of most interest are neutrophil-lymphocytic (NLR), monocyte-lymphocytic (MLR) and platelet-lymphocytic (PLR) ratios, as well as indices of systemic immune-inflammation (SII, platelet count x number of neutrophils / lymphocytes) and system inflammation response (SIRI, number of neutrophils x number of monocytes / lymphocytes). All coefficients are available for calculation based on a routine complete blood count. The analysis of the literature demonstrates the significance of these ratios, but emphasizes the need for further research. A more detailed study of these ratios will allow achieving their prognostic value and a more objective assessment of their validity and specificity for the diagnosis, prediction of risks and variants of the affective disorders course.

Evaluating density-weighted connectivity of black bears (Ursus americanus) in Glacier National Park with spatial capture–recapture models

BackgroundImproved understanding of wildlife population connectivity among protected area networks can support effective planning for the persistence of wildlife populations in the face of land use and climate change. Common approaches to estimating connectivity often rely on small samples of individuals without considering the spatial structure of populations, leading to limited understanding of how individual movement links to demography and population connectivity. Recently developed spatial capture-recapture (SCR) models provide a framework to formally connect inference about individual movement, connectivity, and population density, but few studies have applied this approach to empirical data to support connectivity planning.MethodsWe used mark-recapture data collected from 924 genetic detections of 598 American black bears (Ursus americanus) in 2004 with SCR ecological distance models to simultaneously estimate density, landscape resistance to movement, and population connectivity in Glacier National Park northwest Montana, USA. We estimated density and movement parameters separately for males and females and used model estimates to calculate predicted density-weighted connectivity surfaces.ResultsModel results indicated that landscape structure influences black bear density and space use in Glacier. The mean density estimate was 16.08 bears/100 km2 (95% CI 12.52–20.6) for females and 9.27 bears/100 km2 (95% CI 7.70–11.14) for males. Density increased with forest cover for both sexes. For male black bears, density decreased at higher grizzly bear (Ursus arctos) densities. Drainages, valley bottoms, and riparian vegetation decreased estimates of landscape resistance to movement for male and female bears. For males, forest cover also decreased estimated resistance to movement, but a transportation corridor bisecting the study area strongly increased resistance to movement presenting a barrier to connectivity.ConclusionsDensity-weighed connectivity surfaces highlighted areas important for population connectivity that were distinct from areas with high potential connectivity. For black bears in Glacier and surrounding landscapes, consideration of both vegetation and valley topography could inform the placement of underpasses along the transportation corridor in areas characterized by both high population density and potential connectivity. Our study demonstrates that the SCR ecological distance model can provide biologically realistic, spatially explicit predictions to support movement connectivity planning across large landscapes.

Optimizing spectrum efficiency in 6G multi-UAV networks through source correlation exploitation

In the context of 6G and 5G communication networks, particularly in disaster-stricken areas with a surging demand for connectivity and the rapid evolution of the internet of everything (IoE), the imperative for augmenting spectrum efficiency in unmanned aerial vehicles (UAVs) communication-enabled wireless networks becomes ever more pronounced. This work embarks on the mission of significantly enhancing spectrum efficiency by capitalizing on redundancies, such as correlations inherent in data sources like co-located video sensors. While the intuitive potential of exploiting redundancies for spectrum efficiency enhancement is apparent, our approach is systematically structured. We introduce a linear programming framework designed to meticulously allocate bandwidth to individual links based on their respective demands, while judiciously adhering to spatial spectrum reuse constraints. Subsequently, we employ this linear program to empirically quantify the improvements in spectrum efficiency engendered by source correlations. Furthermore, we elucidate various strategies for harnessing these correlations to maximize spectrum efficiency gains, while navigating the trade-off terrain between computational complexity and precision. Our findings resoundingly underscore the trans-formative power of identifying the precise set of source correlations, resulting in spectrum efficiency enhancements of up to two orders of magnitude. In terms of network performance, the judicious exploitation of source correlations grants admission to nearly 100% of delay-intolerant traffic, alongside substantial reductions in mean delay for delay-tolerant traffic.”

ТЕПЛОВАЯ ИШЕМИЯ ПОЧКИ: КОНЦЕПЦИЯ ПРЕОДОЛЕНИЯ ИШЕМИЧЕСКОГО ПОВРЕЖДЕНИЯ ПОЧКИ ПРИ ОПЕРАЦИЯХ НА ПОЧЕЧНОМ СЕГМЕНТЕ АОРТЫ

The article presents some aspects of acute kidney injury (AKI) during operations on the renal segment of the aorta and renal arteries. The terminology and individual links in the pathogenesis of ischemic-reperfusion injuries are considered. A brief review of methods for preventing ischemia-reperfusion injury during operations on the renal segment of the aorta and renal arteries is provided. Features of pharmacological nephroprotection, perfusion methods of kidney protection, and a brief historical review of bypass operations on the renal arteries are presented.

Link Prediction through Ensemble Techniques

Link prediction is significant in the field of network analysis which helps to determine the future or hidden connections between the entities in a network. Traditional link prediction methods typically utilize single algorithms to make predictions, which might not be optimal for diverse and complex networks. In this research paper, a new framework is proposed which utilizes the existing link prediction algorithms with ensemble techniques. We have explored three ensemble strategies: bagging, boosting, and voting classifier and four individual link prediction algorithms: Adamic Adar, Katz, CCPA, Accurate link prediction. Methods considering ensemble techniques combine multiple individual models to improve prediction accuracy and robustness. We have experimentally compared the performance of proposed framework using six real world datasets in terms of AUC and Accuracy. The results show the superiority of the proposed framework over individual link prediction algorithms.