Local System Research Articles

A Polyurethane Electrospun Membrane Loaded with Bismuth Lipophilic Nanoparticles (BisBAL NPs): Proliferation, Bactericidal, and Antitumor Properties, and Effects on MRSA and Human Breast Cancer Cells.

Electrospun membranes (EMs) have a wide range of applications, including use as local delivery systems. In this study, we manufactured a polyurethane Tecoflex™ EM loaded with bismuth-based lipophilic nanoparticles (Tecoflex™ EMs-BisBAL NPs). The physicochemical and mechanical characteristics, along with the antitumor and bactericidal effects, were evaluated using a breast cancer cell line and methicillin-susceptible and resistant Staphylococcus aureus (MRSA). Drug-free Tecoflex™ EMs and Tecoflex™ EMs-BisBAL NPs had similar fiber diameters of 4.65 ± 1.42 µm and 3.95 ± 1.32 µm, respectively. Drug-free Tecoflex™ EMs did not negatively impact a human fibroblast culture, indicating that the vehicle is biocompatible. Tecoflex™ EMs-BisBAL NPs increased 94% more in size than drug-free Tecoflex™ EMs, indicating that the BisBAL NPs enhanced hydration capacity. Tecoflex™ EMs-BisBAL NPs were highly bactericidal against both methicillin-susceptible S. aureus and MRSA clinical isolates, inhibiting their growth by 93.11% and 61.70%, respectively. Additionally, Tecoflex™ EMs-BisBAL NPs decreased the viability of MCF-7 tumor cells by 86% after 24 h exposure and 70.1% within 15 min. Regarding the mechanism of action of Tecoflex™ EMs-BisBAL NPs, it appears to disrupt the tumor cell membrane. In conclusion, Tecoflex™ EMs-BisBAL NPs constitute an innovative low-cost drug delivery system for human breast cancer and postoperative wound infections.

Individual, community and health systems factors influencing time to notification of tuberculosis: situating software and hardware bottlenecks in local health systems

BackgroundDespite several global interventions, tuberculosis (TB) remains a leading cause of death affecting millions of people globally. Many TB patients either have no access to quality care or go undetected by national health systems. Several multilevel factors account for under-detection of persons with TB. This study sought to explore patient-related software, community and health systems software and hardware factors influencing time to notification of TB in Lusaka District, Zambia.MethodsThis was an exploratory qualitative case study that adopted a software and hardware lens of conceptualizing health systems. Data were collected from across three sites – urban and peri-urban areas: Chongwe, Kafue, and Lusaka – within Lusaka Province, Zambia. Sixteen key informants - TB corner nurses, community TB treatment supporters, and TB program managers - were interviewed. Six focus groups were held with TB patients. Data were analyzed using thematic analysis.ResultsThe study identified factors influencing timely TB notification, categorized into software and hardware elements.Patient-related software elements, including TB knowledge and awareness, and health-seeking behavior, are crucial for prompt notification among TB patients.In the community health system, software elements like social stigma and undesirable community attitudes towards contact tracing, and hardware elements such as unbalanced schedules, excessive workload and limited capacity of community TB treatment supporters contribute to delayed TB notification.In the formal health system, software elements like negative attitudes of health providers towards TB patients and demotivation of TB staff, and hardware elements such as high diagnostics and transportation costs, outdated diagnostics in primary care facilities, and slow referral mechanisms, can also delay TB notification.ConclusionDelays in time to TB notification are influenced by a combination of software (attitudinal and behavioral) and hardware (resource-related) elements across TB patients, community health systems, community TB treatment supporters, health providers, and TB staff. Addressing these factors, particularly social stigma, negative attitudes, and resource constraints, is crucial to improving timely TB detection and treatment.

Recentring the Political in Education for Sustainable Development: Participatory Photovoice Research as Prefigurative Politics Towards Social-ecological Transformation

Abstract Based on the critique of education for sustainable development (ESD) as a socio-political control element of ecological modernisation, we discuss the prefigurative potential of participatory photovoice research in schools in light of social-ecological transformation. We argue that engaging students in prefigurative practices of change in which (sustainable) counter-futures are explored in the (unsustainable) present can help to re-politicise ESD, and we view photovoice as a way to guide this transformative process. Drawing on examples from a participatory research project on the transformation of local food systems in Graz, Austria, we critically explored photovoice as a method of transformative education that creates power-critical spaces of possible futures in which (un)sustainable hegemony and collectively internalised patterns of thought and action can be questioned to envision and negotiate liveable futures for all.

Adaptive sensor attack detection and defense framework for autonomous vehicles based on density

The security of autonomous vehicles heavily depends on localization systems that integrate multiple sensors, which are vulnerable to sensor attacks and increase the risk of accidents. Given the diversity of sensor attacks and the dynamic changing of driving scenarios of autonomous vehicles, an adaptive and effective attack detection and defense framework faces a considerable challenge. This paper proposes a novel real-time adaptive attack detection and defense framework based on density, which can detect and identify attacked sensors and effectively recover data. We first develop a reinforcement learning multi-armed Bandit-based Density-Based Spatial Clustering of Applications with Noise (BDBSCAN) algorithm that selects hyperparameters adaptively. The Adaptive Extended Kalman Filter (AEKF) combines with the vehicle dynamic model on the localization system and extracts data features used for the BDBSCAN algorithm to monitor potential sensor attacks. If attack detection indicates possible system compromise, AEKF is further employed on localization sensors with anomalies identified through the BDBSCAN algorithm of the attacked sensors. To ensure precision and reliability, the data recovery incorporates a redundancy mechanism to apply a decision tree to select the optimal state estimation between AEKF and Extended Kalman Filter (EKF) to replace corrupted sensor data. To evaluate the effectiveness and adaptability of the proposed framework, we conducted 15,000 experiments using the real-world KITTI and V2V4Real datasets across various driving and sensor attack scenarios. The results demonstrate that our proposed framework achieves 100% accuracy and 0% false alarm rate in various driving scenarios for attack detection within 0.15 s, with a recovery time of 0.08 s.

Thermalization propagation front and robustness against avalanches in localized systems

Thermalization propagation front and robustness against avalanches in localized systems

IN VIVO APPLICATION OF LOCAL DRUG DELIVERY SYSTEMS AGAINST MEDULLOBLASTOMA GROUP 3 AND ATYPICAL/TERATOID/RHABOID TUMOURS

Abstract AIMS Local drug delivery systems (LDDSs) applied during neurosurgery offer a means of overcoming poor blood brain barrier (BBB) permeability and have been extensively investigated for the treatment of adult gliomas, but to the best of our knowledge, not for the treatment of paediatric cerebellar tumours. Here we report the applicability of an LDDS against medulloblastoma group 3 (MB3) and atypical teratoid/rhaboid tumours (AT/RT), both of which are associated with poor prognoses. METHOD We prepared and characterised an injectable and biodegradable poly(ethyleneglycol)-poly(caprolactone)- poly(ethyleneglycol) (PECE) hydrogel, which has been investigated with an array of therapeutic agents against numerous cancer types. Here, we loaded the PECE hydrogel with chemotherapeutics previously identified as being effective against primary MB3 and AT/RT in vitro, but which do not cross the BBB in vivo, namely CHIR99021, ribavirin and PG545. Biocompatibility and cytotoxicity of drug loaded hydrogels was assessed in vitro. LDDSs safety and efficacy was evaluated using patient derived MB3 and AT/RT intracranial xenograft surgical resection models. RESULTS The hydrogel was both biocompatible and effected cytotoxicity following drug release. In vivo efficacy experiments against MB3 indicated a comparable median survival in treatment arms receiving radiotherapy or CHIR99021 and PG545 loaded LDDS. However, combined radiotherapy and LDDS conferred a significant survival enhancement, including long-term survivors. Against AT/RT, the median survival of arms receiving radiotherapy was comparable to that of the CHIR99021 and ribavirin loaded LDDS, with long-term survivors observed only in the latter arm. CONCLUSION The application of LDDSs against cerebellar brain tumours offers a promising novel therapeutic alternative. For MB3, the combination of radiotherapy and a LDDS significantly enhances survival compared to radiotherapy alone. For AT/RT, the comparable survival of the LDDS and radiotherapy alone is encouraging and indicates the possibility of circumventing radiation-induced adverse effects for young children impacted by this disease.

A Comprehensive Overview on Sustainable Vegetable Gardening: Eco-friendly Approaches to Home Grown Production

Sustainable vegetable gardening is an eco-friendly practice that integrates organic farming principles, resource conservation, and biodiversity promotion to produce nutritious, chemical-free food while minimizing environmental impact. This approach emphasizes soil health through the use of organic amendments, crop rotation, composting, and mulching to improve fertility and water retention. Water conservation techniques, such as drip irrigation and rainwater harvesting, are employed to optimize water use, especially in arid regions. Pest and disease management relies on integrated pest management (IPM), biological controls, companion planting, and the use of organic pesticides to reduce chemical input while maintaining crop health. Sustainable homegrown produce has been shown to have superior nutritional content compared to commercially grown produce, and the avoidance of synthetic chemicals reduces the risk of pesticide residue exposure. Gardening fosters healthy eating habits by connecting individuals to their food sources, encouraging the consumption of fresh, unprocessed vegetables, and contributing to food security. The mental and physical health benefits of gardening, including reduced stress, increased physical activity, and improved mental well-being, further highlight its holistic value. However, challenges such as the initial setup costs, time investment, pest management, and knowledge gaps can hinder widespread adoption. Addressing these challenges requires greater access to resources, educational initiatives, and the development of climate-resilient practices tailored to specific regions. Future trends in sustainable gardening include the adoption of technological innovations, such as smart irrigation systems, automation, and vertical farming, which offer scalable solutions for urban and small-scale gardeners. The COVID-19 pandemic has underscored the importance of resilient, local food systems, and sustainable gardening is poised to play a critical role in addressing future food security concerns.

Aligning local governance with SDGs: a study of local government systems in Pakistan

ABSTRACT This study examines the experiences of local government councilors between 2013–2020 in four provinces of Pakistan. The study addresses three key questions: Firstly, it investigates the differences and commonalities in the local government structures across provinces and explores the potential for synchronization to enhance the implementation of Sustainable Development Goals (SDGs) at the local level. Secondly, it examines the main challenges local councilors face in effectively delivering basic services, including water, sanitation, health, education, waste management, and transport, within both rural and urban contexts. Lastly, the study analyses the necessary changes or reforms at the provincial level within the existing local government system in rural and urban areas to ensure the delivery of basic services in alignment with SDGs. The findings reveal that a powerful bureaucracy and political influence at the intermediate to upper levels of the government hierarchy exert significant control over administrative, fiscal, and political.

Sinus vein thrombosis conundrum: Persistent empty sella vs. flexible optic nerve sheath

IntroductionOur objective was to investigate the potential effect of thrombotic burden on pituitary gland height, bony sella and optic sheath width, taking into consideration the various venous sites and dominant drainage pattern. Patients and MethodsThis retrospective cohort study followed patients diagnosed with cerebral sinus vein thrombosis in a single primary healthcare center between the years 2000 and 2022. Data was collected from both CT/V and MR/V scans available on the local PACS system. Dural sinuses were divided into main anatomical sites and scored for patent, partially or totally blocked lumen. Dominant drainage flow was noted for each patient. For most scans, pituitary mid height, maximal depth and AP width of the bony sella and dorsum sella to tuberculum sella distance were assessed. Optic sheath width was measured for both sides at the maximal retrobulbar diameter. Regression methods, including linear mixed models, and non-parametric tests were used to analyze the data. Results90 patients (mean age, 44 years ±16.8, 54 women) were evaluated. Overall thrombus burden did not correlate with pituitary mid-height, however a relationship was observed between the change (from presentation) in the superficial thrombus score and the average width of the optic nerve sheath; the width of the optic sheath tended to decrease as thrombus burden improved and vice versa (p = 0.010). ConclusionsThrombus recanalization had a favorable effect on the optic nerve sheath diameter but did not appear to reverse the flattening of the pituitary gland, regardless of temporal improvement.

Object Detection for Indoor Localization System

Indoor localization systems have gained significant attention in recent years due to their applications in various fields such as smart homes, retail environments, and healthcare facilities. This paper presents an innovative approach to indoor localization through the integration of object detection techniques, aiming to enhance accuracy and efficiency in identifying and locating objects within indoor spaces. We explore the use of advanced deep learning algorithms, particularly convolutional neural networks (CNNs), to detect and classify objects in real-time. Our methodology involves collecting a comprehensive dataset of indoor environments, training a robust object detection model, and implementing it in a localization framework that utilizes both visual and spatial data. The experimental results demonstrate that our proposed system achieves high detection accuracy and reduced localization errors, outperforming traditional methods. Furthermore, we discuss the potential of leveraging object recognition to improve user experience and navigation in complex indoor settings. This research contributes to the evolving field of indoor localization and offers a foundation for future developments in intelligent indoor navigation systems.

Graph-Neural-Network-Based WiFi Indoor Localization System With Access Point Selection

Graph-Neural-Network-Based WiFi Indoor Localization System With Access Point Selection

Ultrasonic Array-Based Multi-Source Fusion Indoor Positioning Technology

Underground mining involves numerous risks, such as collapses, gas leaks, and explosions, posing significant threats to worker safety. In this work, we develop an indoor localization system that uses Bluetooth for coarse positioning and ultrasonic arrays for precision calibration. This system is particularly useful for automated mining operations in underground environments where satellite positioning signals are unavailable. The indoor localization system consists of ultrasonic receiver arrays and an improved multi-transmitter-multi-receiver algorithm, enabling accurate localization within the mining environment. Geometric Dilution of Precision (GDOP) analysis is incorporated to optimize the network layout, and an inertial navigation module is integrated to track the posture of moving objects, enabling precise trajectory determination over large areas, such as coal mines. In the experiment, three traditional methods were compared, and the proposed tracking approach demonstrated a positioning accuracy within 10 cm, reducing error by 20% compared to conventional techniques. This high-precision indoor localization method proves beneficial for underground mining applications.

Intelligent recognition and automatic localization of pipeline welds based on multi-vision system

Abstract Currently, the leakage detection of spacecraft pipeline welds relies on manual point-by-point inspection using a detection gun, which is inefficient and inadequate for the automation needs of spacecraft production. However, the accurate recognition and precise localization of widely distributed and small pipeline welds are crucial for automated detection. Therefore, this paper proposes a multi-vision detection and localization system that integrates global and local information, considering both comprehensive global 3D search and high-precision local 3D measurement. The improved YOLOv8 model is employed for pipeline weld recognition, which improves the recognition rate of welds. Based on the deep learning recognized and segmented welds, this paper proposes stereo matching and segmentation extraction methods for 3D localization and pipeline orientation determination. Additionally, the system integrates a robot to perform automated point-by-point inspection of welds within the area without collisions. The experimental results demonstrate the effectiveness of the improved YOLOv8 and the proposed methods for 3D weld localization and pipeline orientation determination. The maximum deviation of the spatial distance of fine weld positioning is 0.20 mm, and the repeatability of the 3D coordinates is around 0.1 mm. The system can perform precise localization and detection, meeting the requirements for automatic weld recognition and localization.

Look at this! Radical right-wing populist information sharing practices on Twitter in Portugal, Spain, and Brazil

Politicians communicate on social media not only by direct utterances, but also by where they choose to direct followers’ attention using strategic interaction, audiovisual content and outlinks, i.e. their information sharing practices. Political communication research has focused on the former, but the latter is a relevant way to foster advantageous informational environments and interact with media systems. This is especially important for radical right-wing populists, due to their reliance on social media and adjacency to disinformation. Portugal, Spain, and Brazil provide important research cases due to media system characteristics and the different positions within the political system of the relevant leaders, which generates different opportunity structures. This article approaches relevant radical right-wing populist leaders’ information sharing practices by analysing the non-textual content of tweets ( n = 6087), emphasizing how they reflect relations with local media systems.

Design a novel algorithm for enhancing UWB positioning accuracy in GPS denied environments

Accurate indoor positioning is the key to the development of the Internet of Things and intelligent devices. In view of GPS-denied indoor environments, we propose to build the indoor local positioning system by using ultra-wide band (UWB) system. In order to enhance the localization accuracy of UWB system, we propose a novel algorithm which integrates the Maximum Correntropy Criterion (MCC) and unscented Kalman filter (UKF) method to reconstruct the measurement distance by using the maximum entropy principle to reduce the influence of outliers and unknown process noise on the smooth effect. Subsequently, the least square (LS) method is implemented to attain the target node (TN) initial position coordinates, and the Taylor algorithm is then performed to further optimize the localization results of the LS method. Lastly, the experimental investigation is conducted to assess the effectiveness and applicability of the developed method via the UWB system in indoor scenarios. The experimental outcomes demonstrate that the developed MCCUKF-LS method can achieve the lowest root mean square error (RMSE), and enhance the positioning accuracy of the TN compared with the LS, KF-LS, and UKF-LS methods. The overall average RMSE of MCCUKF-LS method is reduced by 45.7% contracted with the LS algorithm. The average error of x-, y- and z-axis orientation for the LS method is reduced from 0.074 m, 0.067 m, 0.098 m to 0.036 m, 0.034 m, 0.044 m, and the achieved accuracy in the orientation of the three axes is increased by 51.4%, 49.3% and 55.1% respectively, which reveals that the designed fusion technique is capable of enhancing the positioning accuracy of the TN effectively, providing a new positioning methodology and reference for indoor positioning in GPS-denied environments.

An adaptive acceleration scheme for phase-field fatigue computations

Abstract Phase-field models of fatigue are capable of reproducing the main phenomenology of fatigue behavior. However, phase-field computations in the high-cycle fatigue regime are prohibitively expensive due to the need to resolve spatially the small length scale inherent to phase-field models and temporally the loading history for several millions of cycles. As a remedy, we propose a fully adaptive acceleration scheme based on the cycle jump technique, where the cycle-by-cycle resolution of an appropriately determined number of cycles is skipped while predicting the local system evolution during the jump. The novelty of our approach is a cycle-jump criterion to determine the appropriate cycle-jump size based on a target increment of a global variable which monitors the advancement of fatigue. We propose the definition and meaning of this variable for three general stages of the fatigue life. In comparison to existing acceleration techniques, our approach needs no parameters and bounds for the cycle-jump size, and it works independently of the material, specimen or loading conditions. Since one of the monitoring variables is the fatigue crack length, we introduce an accurate, flexible and efficient method for its computation, which overcomes the issues of conventional crack tip tracking algorithms and enables the consideration of several cracks evolving at the same time. The performance of the proposed acceleration scheme is demonstrated with representative numerical examples, which show a speedup reaching up to four orders of magnitude in the high-cycle fatigue regime with consistently high accuracy. Graphical abstract

Long-term climate-based sizing and economic assessment of air-water heat pumps for residential heating

This study presents a novel methodology for sizing air–water heat pumps (ASHP) for space heating and hot water supply in buildings. Utilizing long-term local climatic data, the developed tool determines the coefficient of performance (COP) and feasibility of ASHP. The sizing algorithm incorporates peak heat demand, unitary final energy demand, and seasonal heat demand across various detached house sizes. Annual local heating system operation time and key economic indicators are derived for each case across 3 European countries. A new approach is precise investigation of 10-year outdoor temperatures and apply it to heat pump (HP) modeling, which enabled a distinction between so-called warm and cold years. The results underscore substantial variations in net present value (NPV) between warm and cold years, illustrating the critical influence of precise climate data on the performance of HPs. The study revealed that for a 160 m2 house in Poland, annual electricity consumption by HPs ranged from 3736 kWh during warm years to 12,908 kWh during cold years, showing a significant variation in performance based on climate conditions. The comprehensive tool allows for precise adjustments of heating systems to actual local climate conditions, improving both economic and environmental outcomes. This comparative assessment aids in the optimal selection of HPs, ensuring energy efficiency and sustainability in residential heating systems. Building on studies from various climatic regions, this work addresses the knowledge gap in performance and explores the feasibility of HP in a changing climate using precise modeling techniques.

A Guideline for Local Elderly Policy Development in Thailand

In previous local elder policy research, most studies were fragmented with only some subjects or some steps in the policy process and attention to the local policy process not included explicitly. This article aims to analyze Thai local elderly policy formulation, implementation and evaluation and to propose guidelines for Thai local elderly policy development. This was a qualitative study. Data were collected using in-depth interviews with 40 key informants from 5 local case studies and 8 national organizations, as well as observations and documentary studies. Data were analyzed using thematic analysis and analytic induction. For the policy content dimensions, the guidelines of policy content development of the case studies aim to make senior citizens happy, self-sufficient, and physically and mentally healthy. The means to achieve this are comprised of the following:1) an economic, career, and income stability dimension; 2) a health dimension; and 3) a social dimension. For the policy process dimensions, the guideline of policy formulation comprises of the following: the related national policy dimension, including developing the mindset of policy actors, developing the content of policies with clarity that is up-to-date and congruent with key agreements or related principles, and developing a participation process and communication of the policy. The local policy dimension is locally aged society strategic planning based on strategic management and objectives and key results (OKRs) derived from the results of data analysis, integration of public policy theory, resource-based view in strategic management theory, and objective and key results to reduce the limitations of the public policy theory and model. This comprises developing policy actors’ mindsets, competencies, and motivations, collecting information, creating participation for analyzing and formulating direction, and making local elderly society strategic plans. The guidelines of policy implementation comprise the following: creating knowledge and understanding, organizing a central organization, implementing a strategic plan, formulating strategies for implementing and integrating amicable coordination of networks, seeking and allocating tangible and intangible resources, developing competencies of local government personnel, network partners, and target groups, creating and developing a culture supporting the aged society, and creating internal and external motivation. The guidelines of policy evaluation comprise the following: the development of the evaluation competency, the growth and ethical mindset, and the development of a participatory local policy evaluation system. Based on the results of this study, the guidelines focus on the intangible resources, the internal motivation, the mindset of policy actors, the coordination and strength of networks, and the upper-level policy factors.

Creating a learning health system to include environmental determinants of health: The GroundsWell experience.

Policies aiming to prevent ill health and reduce health inequalities need to consider the full complexity of health systems, including environmental determinants. A learning health system that incorporates environmental factors needs healthcare, social care and non-health data linkage at individual and small-area levels. Our objective was to establish privacy-preserving household record linkage for England to ensure person-level data remain secure and private when linked with data from households or the wider environment. A stakeholder workshop with participants from our regional health board, together with the regional data processor, and the national data provider. The workshop discussed the risks and benefits of household linkages. This group then co-designed actionable dataflows between national and local data controllers and processors. A process was defined whereby the Personal Demographics Service, which includes the addresses of all patients of the National Health Service (NHS) in England, was used to match patients to a home identifier, for the time they are recorded as living at that address. Discussions with NHS England resulted in secure and quality-assured data linkages and a plan to flow these pseudonymised data onwards into regional health boards. Methods were established, including the generation of matching algorithms, transfer processes and information governance approvals. Our collaboration accelerated the development of a new data governance application, facilitating future public health intervention evaluations. These activities have established a secure method for protecting the privacy of NHS patients in England, while allowing linkage of wider environmental data. This enables local health systems to learn from their data and improve health by optimizing non-health factors. Proportionate governance of health and linked non-health data is practical in England for incorporating key environmental factors into a learning health system.

The role of geographic distances in green industrial pilot policies evaluation: A sustainability transition perspective.

Green industrial policies (GIPs) aim to promote the adoption ofgreen technology within a sustainability framework. While previous evaluations of GIP have focused more on the policy itself and the impacts within the policy boundaries, this paper further introduces the geographical factor to analyze the impact of different spatial geographic distances on implementing GIP. By integrating geographic distances into a spatial difference-in-differences analysis to assess the effects of municipal green industry policies (referred to as green industry pilot policies in this paper) enacted in 11 cities in China from 2006 to 2010, we find that these policies not only improve environmental and economic outcomes in targeted regions but also have spillover effects that may affect neighboring areas negatively, highlighting the importance of geographic considerations. The effectiveness of green industrial policies varies across cities, influenced by local socio-technical systems and regional characteristics such as infrastructure and information technology. These findings suggest that policy impacts are complex and multifaceted, requiring a comprehensive understanding of geographic interdependencies. By incorporating geographic factors, this research contributes to sustainability transition theory by offering insights into the spatial and temporal dynamics of socio-technical systems. The results underscore the need for policymakers to consider spatial-temporal aspects and potential secondary effects on adjacent regions when designing and implementing green industrial policies.