Local System Research Articles

A novel microfluidic tool for the evaluation of local drug delivery systems in simulated in vivo conditions.

A 3D-printed microfluidic tool for assessing local drug delivery systems (LDD) in simulated in vivo conditions was developed and evaluated. The device was designed considering the oral environment and dental applications, and it was fabricated with a high-precision resin 3D printer. Chitosan scaffolds loaded with different concentrations of doxycycline were used for evaluating our device. The concentration of the released drug was measured through in-line UV-VIS spectroscopy, and to verify the repeatability and accuracy of our measurements, comparisons with standard HPLC results were made (5% deviation). Cumulative drug release profiles in steady-state conditions were obtained and compared to the Weibull model. The behaviour of the LDD system in a dynamic environment was also evaluated during experiments where step changes in pH were introduced. It was demonstrated that under infection-like conditions, there is an immediate response from the polymer and a clear increase in the concentration of the released drug. Continuous flow and recirculation experiments were also conducted, revealing significant differences in the drug release profiles. Specifically, in the case of continuous flow, the quantity of the released drug is much higher due to the higher driving force for diffusion (concentration gradient). Overall, the proposed microfluidic tool proved to be ideal for evaluating LDD systems, as the in vivo microenvironment can be replicated in a better way than with currently used standard systems.

Thermal Performance of Solar Ground Source Heat Pump System for Rural Buildings in Chinese Cold Zone

In response to China's national policy of "achieving carbon peak by 2030 and carbon neutrality by 2060", and to promote the heating system of rural buildings in China's severe cold zone. Two heating schemes of the GSHP (Ground Source Heat Pump) system and the SGSHP (Solar Ground Source Heat Pump) system are designed and simulated for a single rural residential building in Harbin city. The results present that the outlet temperature of buried pipe in SGSHP system is 13.86% higher than that in GSHP system, and coefficient of performance (COP) correspondingly increases 9.2%. There is a better comprehensive performance for the SGSHP system in cold climates. The standard coal consumption of SGSHP system is about 72.35% less than that of biomass boiler system, showing a greater energy efficiency. Compared to the local conventional biomass boiler system, the dynamic cost payback period of the SGSHP system amounts to 11 years, while yielding a net present value (NPV) of 10,800 CNY throughout the project’s life cycle. The emissions of CO2, SO2, and dust are reduced by 2617.13kg, 19.38kg, and 14.535kg respectively. The results indicate a great overall performance of the SGSHP system for residential heating in the cold climate zone. This research offers an energy efficient and eco-friendly alternative for the space heating of Chinese rural buildings in cold climates.

LSGDDN-LCD: An appearance-based loop closure detection using local superpixel grid descriptors and incremental dynamic nodes

Loop Closure Detection (LCD) is an essential component of visual Simultaneous Localization and Mapping (SLAM) systems. It enables the recognition of previously visited scenes to eliminate pose and map estimate drifts arising from long-term exploration. However, current appearance-based LCD methods face significant challenges, including high computational costs, viewpoint changes, and dynamic objects in scenes. This paper introduced an online appearance based LCD using Local Superpixel Grids Descriptor (LSGD) and Dynamic Nodes (DN), i.e., LSGDDN-LCD, to find similarities between scenes via handcrafted features extracted from the LSGD. Additionally, we proposed the adaptive mechanism to group similar scenes called DynamicNodes, which incrementally adjusted the database in an online manner, allowing for efficient and online retrieval of previously viewed images without need of the pre-training. Experimental results confirmed that the LSGDDN-LCD significantly improved LCD precision–recall and efficiency, and outperformed several state-of-the-art (SOTA) approaches on public and our own datasets, indicating its great potential as a generic LCD framework. Our implementation of the LSGDDN-LCD approach and the datasets were open-sourced on GitHub (https://github.com/BaoshengZhang0/LSGDDN-LCD.git).

AFO-SLAM: an improved visual SLAM in dynamic scenes using acceleration of feature extraction and object detection

Abstract In visual simultaneous localization and mapping (SLAM) systems, traditional methods often excel due to rigid environmental assumptions, but face challenges in dynamic environments. To address this, learning-based approaches have been introduced, but their expensive computing costs hinder real-time performance, especially on embedded mobile platforms. In this article, we propose a robust and real-time visual SLAM method towards dynamic environments using acceleration of feature extraction and object detection (AFO-SLAM). First, AFO-SLAM employs an independent object detection thread that utilizes YOLOv5 to extract semantic information and identify the bounding boxes of moving objects. To preserve the background points within these boxes, depth information is utilized to segment target foreground and background with only a single frame, with the points of the foreground area considered as dynamic points and then rejected. To optimize performance, CUDA program accelerates feature extraction preceding point removal. Finally, extensive evaluations are performed on both TUM RGB-D dataset and real scenes using a low-power embedded platform. Experimental results demonstrate that AFO-SLAM offers a balance between accuracy and real-time performance on embedded platforms, and enables the generation of dense point cloud maps in dynamic scenarios.

The Efficacy of Local Antibiotic Delivery Systems Therapy in the Management of Diabetic Foot Osteomyelitis: A Systematic Review and Meta-Analysis.

We aim to evaluate the efficacy of local antibiotic delivery systems in patients with diabetic foot osteomyelitis (DFO). The Web of Science, PubMed, and Embase databases were searched for relevant publications until March 2024. All studies evaluating the efficacy of local antibiotic delivery systems in patients with DFO were included. We calculated pooled risk ratio (RR) with 95% CIs for binary outcomes and mean difference (MD) for continuous outcomes. The Cochrane's risk of bias tool and methodological index for non-randomized studies (MINORS) assessment were used to evaluate the quality of studies. A total of 9 studies with 491 patients were included in this analysis. The overall healing rate in antibiotic group was 0.85 (95% CI: 0.67, 0.97). Healing rates were significantly higher in the antibiotic group compared to the control group (RR: 1.18, 95% CI: 1.01, 1.38). Furthermore, recurrence rates and amputation rates have no significantly difference between the antibiotic group and the control group (RR: 0.30, 95% CI: 0.04, 2.12 and RR: 0.22, 95% CI:0.03, 1.91), along with no significantly difference in healing time and hospital stays(MD: -7.87, 95% CI: -20.81, 5.07 and MD:-2.33, 95% CI:-5.17, 0.50). No obvious publication bias was observed in the funnel plot (Egger's test, P = .99). Our meta-analysis found that diabetic foot osteomyelitis patients treated with local antibiotic delivery systems had better healing rates than the control group. However, no significant differences were found in healing time, recurrence, hospital stays, or amputation rates. Larger randomized controlled trials are necessary in the future.

Hydro–Solar Hybrid Plant Operation in a Hydropower Plant Cascade: Optimizing Local and Bulk System Benefits

A hydro–solar hybrid system is an important solution for expanding renewable generation capacity under the percepts of the energy transition. This type of association allows for the coordinated dispatch of solar and hydropower plants, resulting in operational benefits in terms of energy generation and reservoir management, that is, the better use of available water and energy resources. As in this case, the operation of the hydropower plant is associated with the cascade in which it operates, when it is hybridized (for example, by associating with a solar power plant), in addition to local changes, there are impacts on the operating conditions of the other hydropower plants in the same cascade. From such a perspective, this study presents an energy system management model for hybrid power plants composed of hydro and solar sources, aiming to optimize the joint operation and measure the operational consequences at the local level and in the cascade. The results from a case study of a hydro–solar power plant hybridization in the Tietê River (Brazil) revealed increased energy production and improvement in the operating conditions of the cascade’s reservoirs, while the grid capacity was found to be an important constraint that limits the capture of synergies resulting from the generation sources complementarity and thus on the benefits to the cascade.

Carbon balance analysis of agricultural production systems in oasis areas

China is the biggest emitter of greenhouse gases (GHGs) in the world, and agricultural GHG emission accounts for nearly a fifth of the total emission in China. To understand the carbon absorption and emission characteristics of agricultural production systems in those arid oasis areas, a typical representative city in northwestern China, Zhangye City, was selected for study.The emission factor method was used to analyze and calculate the characteristics of changing carbon emission dynamics in the whole agricultural production system in Zhangye city region (38,592 km2) from 2010 to 2021.The results revealed that carbon emissions during agricultural planting mainly come from fertilizers, which account for the highest proportion (47.9%) of total carbon emissions in agricultural planting. Animal enteric fermentation emissions from local livestock farming are the main contributor (86%) to GHG emissions. The annual average carbon absorption intensity is 4.4 t C-eq ha−1 for crop and 2.6 t C-eq ha−1 for the agricultural production system. The ratio of total carbon emissions from agricultural production to carbon sequestration of crops is 1:1.7. We find that the total carbon sequestration slightly exceeds its total carbon emissions in the study region, with an annual average of 41% for its sustainable development index. Carbon emissions of the agricultural production system in this oasis area are mainly driven by the livestock industry, mostly CH4 emissions from cattle raising.Reducing the local carbon emissions from the livestock industry, typically the cattle raising, will play a crucial role in reducing carbon emissions from this local agricultural production system and maintaining its net positive carbon balance.

Nonlinear mechanism for paradoxical facilitation of spike induced by inhibitory synapse in auditory nervous system for sound localization

Nonlinear mechanism for paradoxical facilitation of spike induced by inhibitory synapse in auditory nervous system for sound localization

DOT-SLAM: A Stereo Visual Simultaneous Localization and Mapping (SLAM) System with Dynamic Object Tracking Based on Graph Optimization

DOT-SLAM: A Stereo Visual Simultaneous Localization and Mapping (SLAM) System with Dynamic Object Tracking Based on Graph Optimization

Internal and external spatial analysis of trace elements in local crayfish

ABSTRACT Pollution in urban environments is a major health concern for humans as well as the local wildlife and aquatic species. Anthropogenic waste and discharge from storm drainage accumulate nutrients and environmental contaminants in local water systems. Locating contaminated sites using water samples over the vast landscape is a daunting task. Crayfish thrive in urban environments and have been used for biomonitoring pollutants. This study aimed to use crayfish as sentinels to monitor for elements in local environments. In this study, crayfish were used to measure metals and metalloids in lotic environments using ICP-OES analysis of abdominal and exoskeletal tissue. Using cluster analysis, geographical zones of trace element accumulation were determined. Eighteen total elements were analysed providing baseline data on local genera, biometric data, and element concentrations averaging 267.3 mg/kg Mn in the exoskeleton and with Zn averaging 6.88 mg/kg being significantly higher in the abdomen. Correlations of elements with biometric data allowed for internal analyses of elements. The elements As, Cr, Hg, Ni, and Tl demonstrated equivalent concentrations in both tissues. The crayfish locations with high abundance of elements allowed for the determination of contaminated areas with higher accumulations being areas of active urban development. These analyses gave measurable results of metal and metalloid to pinpoint potential sources of pollutants. Since crayfish are consumed globally as a food source, these methods can be used to determine the risk of toxic metals being passed through the food chain to the public.

Optimal design of renewable energy communities (RECs) in Italy: Influence of composition, market signals, buildings, location, and incentives

In Europe the concept of Renewable Energy Communities (RECs) renovates the need for decentralized energy generation among citizens and companies. The corresponding legal framework enables the creation of business models that shall support environmental, economic and social benefits, provided that adequate planning accounting for the local conditions is executed. The present work is focused on a thermal-electric co-simulation approach for the analysis of the energy exchanges within an Italian REC, aimed at sizing photovoltaics (PV) and energy storage systems. EnergyPlus is used to estimate the thermal and electric needs of the community, whose results are fed into the “EnergyCommunity.jl” tool for the design of the local power system. The influence of REC composition (prosumers/consumers), the building energy demands for heating, cooling, and appliances, the geography of the REC in Italian regions, the market data, and the total peak power of PV are examined. The self-consumed electricity, the energy shared among the community, and the social costs are evaluated in different scenarios, suggesting significant environmental and economic benefits for Energy Communities.

Modeling of a “Hydrogen Valley” to investigate the impact of a regional pipeline for hydrogen supply

Introduction: The transition towards electrolysis-produced hydrogen in refineries and chemical industries is expected to have a potent impact on the local energy system of which these industries are part. In this study, three urban areas with hydrogen-intense industries are studied regarding how the energy system configuration is affected if the expected future hydrogen demand is met in each node individually, as compared to forming a “Hydrogen Valley,” in which a pipeline can be used to trade hydrogen between the nodes.Method: A technoeconomic, mixed-integer, linear optimization model is used to study the investments in and dispatch of the included technologies with an hourly time resolution, while minimizing the total system cost. Four cases are investigated based on the availability of offshore wind power and the possibility to invest in a pipeline.Results: The results show that investments in a pipeline reduces by 4%–7% the total system cost of meeting the demands for electricity, heating, and hydrogen in the cases investigated. Furthermore, investments in a pipeline result in greater utilization of local variable renewable electricity resources, as compared to the cases without the possibility to invest in a pipeline.Discussion: The different characteristics of the local energy systems of the three nodes in local availability of variable renewable electricity, grid capacity and available storage options compared to local demands of electricity, heating and hydrogen, are found to be the driving forces for forming a Hydrogen Valley.

Robust Bluetooth AoA Estimation for Indoor Localization Using Particle Filter Fusion

With the growing demand for positioning services, angle-of-arrival (AoA) estimation or direction-finding (DF) has been widely investigated for applications in fifth-generation (5G) technologies. Many existing AoA estimation algorithms only require the measurement of the direction of the incident wave at the transmitter to obtain correct results. However, for most cellular systems, such as Bluetooth indoor positioning systems, due to multipath and non-line-of-sight (NLOS) propagation, indoor positioning accuracy is severely affected. In this paper, a comprehensive algorithm that combines radio measurements from Bluetooth AoA local navigation systems with indoor position estimates is investigated, which is obtained using particle filtering. This algorithm allows us to explore new optimized methods to reduce estimation errors in indoor positioning. First, particle filtering is used to predict the rough position of a moving target. Then, an algorithm with robust beam weighting is used to estimate the AoA of the multipath components. Based on this, a system of pseudo-linear equations for target positioning based on the probabilistic framework of PF and AoA measurement is derived. Theoretical analysis and simulation results show that the algorithm can improve the positioning accuracy by approximately 25.7% on average.

Local systems in diffeology

Local systems in diffeology

Tape-Shaped, Multiscale, and Continuous-Readable Fiducial Marker for Indoor Navigation and Localization Systems

The present study proposes a fiducial marker for location systems that uses computer vision. The marker employs a set of tape-shaped markers that facilitate their positioning in the environment, allowing continuous reading to cover the entire perimeter of the environment and making it possible to minimize interruptions in the location service. Because the marker is present throughout the perimeter of the environment, it presents hierarchical coding patterns that allow it to be robust against multiple detection scales. We implemented an application to help the user generate the markers with a floor plan image. We conducted two types of tests, one in a 3D simulation environment and one in a real-life environment with a smartphone. The tests made it possible to measure the performance of the tape-shaped marker with readings at multiple distances compared to ArUco, QRCode, and STag with detections at distances of 10 to 0.5 m. The localization tests in the 3D environment analyzed the time of marker detection during the journey from one room to another in positioning conditions (A) with the markers positioned at the baseboard of the wall, (B) with the markers positioned at camera height, and (C) with the marker positioned on the floor. The localization tests in real conditions allowed us to measure the time of detections in favorable conditions of detections, demonstrating that the tape-shaped-marker-detection algorithm is not yet robust against blurring but is robust against lighting variations, difficult angle displays, and partial occlusions. In both test environments, the marker allowed for detection at multiple scales, confirming its functionality.

Wernicke Encephalopathy: Typical and Atypical Findings in Alcoholics and Non-Alcoholics and Correlation with Clinical Symptoms.

Clinical diagnosis of Wernicke encephalopathy (WE) can be challenging due to incomplete presentation of the classical triad. The aim was to provide an update on the relevance of standard MRI and to put typical and atypical imaging findings into context with clinical features. In this two-center retrospective observational study, the local radiology information system was searched for consecutive patients with clinical or imaging suspicion of WE. Two independent raters evaluated T2-weighted imaging (WI), fluid-attenuation inversion recovery (FLAIR), diffusion WI (DWI), T2*WI and/or susceptibility WI (SWI), and contrast-enhanced (CE)-T1WI, and noted the involvement of typical (i.e., mammillary bodies (MB), periaqueductal grey (PAG), thalamus, hypothalamus, tectal plate) and atypical (all others) lesion sites. Unusual signal patterns like hemorrhages were also documented. Reported clinical features together with the diagnostic criteria of the latest guidelines of the European Federation of Neurological Societies (EFNS) were used to test for relationships with MRI biomarkers. 47patients with clinically confirmed WE were included (Jan '99-Apr '23; mean age, 53yrs; 70% males). Interrater reliability for imaging findings was substantial (κ = 0.71), with lowest agreements for T2WI (κ = 0.85) compared to all other sequences and for PAG (κ = 0.65) compared to all other typical regions. In consensus, 77% (n = 36/47) of WE cases were rated MRI positive, with FLAIR (n = 36/47, 77%) showing the strongest relation (χ2 = 47.0; P < 0.001) compared to all other sequences. Microbleeds in the MB were detected in four out of ten patients who received SWI, not visible on corresponding T2*WI. Atypical findings were observed in 23% (n = 11/47) of cases, always alongside typical findings, in both alcoholics (n = 9/44, 21%) and non-alcoholics (n = 2/3, 67%). Isolated involvement of structures, explicitly PAG (n = 4/36; 11%) or MB (n = 1/36; 3%), was present but observed less frequently than combined lesions (n = 31/36; 86%). Acut-off width of 2.5 mm for the PAG on 2D axial FLAIR was established between cases and age- and sex-matched controls. An independent association was demonstrated only between short-term memory loss and changes in the MB (OR = 2.2 [95% CI: 1.1-4.5]; P = 0.024). In retrospect, EFNS criteria were positive (≥ 2out of4) in every case, but its count (range, 2-4) showed no significant (P = 0.427) relationship with signal changes on standard MRI. The proposed sequence protocol (FLAIR, DWI, SWI and T1WI + CE) yielded good detection rates for neuroradiological findings in WE, with SWI showing microbleeds in the MB with superior detectability. However, false negative results in about aquarter of cases underline the importance of neurological alertness for the diagnosis. Awareness of atypical MRI findings should be raised, not only in non-alcoholics. There is limited correlation between clinical signs and standard MRI biomarkers.

Federated learning for biometric recognition: a survey

Recently, deep learning (DL) has achieved great success in biometric recognition. The application of DL has also led to a high demand for biometric data. However, as people attach more importance to privacy protection, biometric data have become increasingly difficult to obtain and access, leading to significant limitations in the development and application of DL-based biometric recognition. Federated learning (FL), a distributed learning technique with privacy protection, provides a potential solution to this problem. Several researchers have attempted to integrate FL into biometric recognition. These studies have shown that the introduction of FL not only solves the conflict between privacy and accessibility of biometric data but also improves the accuracy and generalizability of local recognition systems. Therefore, the combination of FL and biometric recognition techniques has become a new research hotspot. In this survey, we comprehensively review the latest advances regarding the application of FL to biometric recognition, biometric presentation attack detection and the related fields to provide new researchers with a quick and systematic overview of this emerging cross-disciplinary field. This paper also summarizes the future opportunities and challenges of this field. To our knowledge, this is the first survey that systematically organizes and analyses federated biometric recognition and related fields to provide suggestions and references for future research.

Information features of management decisions in the system of public authority

The article considers the formation of two management systems after the adoption of the Constitution of the Russian Federation — the system of public administration and the system of local government. The conceptual peculiarities of managerial decision-making in both systems are investigated, and the conclusion is made about the differences in the configurations of the channels of their information links. The advantages and disadvantages of the public administration system as a centralized system based on cybernetic principles, as well as the positive and negative aspects of the synergetic nature of the local government system are analyzed. As public administration systems need a certain decentralization of management, so local government systems cannot do without orientation on a number of issues on centralized commands. It is concluded that in Russia for a long period of time there was no proper information interaction between the system of public administration and the system of local government. It is noted that the appearance in the Constitution of the Russian Federation of part 3 of Article 122 of the Constitution of the Russian Federation determined not only the existence of a unified system of public power, but also the existence of an integral system of governance, the capacity of which to make effective management decisions is higher than the total capacity of the previously existing self-sufficient systems.

Long-Term Performance of Natural Stone Cobbles for Paving Raised Junctions: Findings from over a Decade of Use

Raised junctions (RJs) are chosen more and more frequently by town planners and road designers in traffic calming (TC) projects. This choice is supported by analyses of the existing transport systems in question. Where a few raised junctions have been designed for the project, use of different paving options may be worth consideration. This article describes a situation where a few RJs were placed on a short street section, all of which were provided with a cobblestone or cobblestone pavement (SBP). In order to verify the commercial viability of this option, we examined the traffic conditions, assessed the severity of condition of the pavements under analysis, and estimated the vehicle accelerations (ACs) and decelerations (DEs) in two chosen study areas, further referred to as the first and second study area. Two noise surveys were also carried out for the purposes of this research: the first one after a few years of operation and the second one after another ten years. Considering the problems of sustainable road construction, many environmental factors were taken into account in the studies. Based on the experimental results, we could assess the effectiveness of using RJs as the only TC measure in 30 km/h zones and check whether the severity of pavement condition depended on the AC and DE values and if SBP can be recommended to mitigate environmental impacts of street traffic. Finally, two pavement structures are proposed to choose from, depending on the local transport system conditions and streetscape characteristics. In addition, the authors recommend the use of solar-power elements at RJs to enhance their visibility and increase the traffic slowing effect.

Sensor Fusion-Based UAV Localization System for Low-Cost Autonomous Inspection in Extremely Confined Environments

Sensor Fusion-Based UAV Localization System for Low-Cost Autonomous Inspection in Extremely Confined Environments