Local System Research Articles

Virtual Vectors for Vision-Based Simultaneous Localization and Mapping System

Virtual Vectors for Vision-Based Simultaneous Localization and Mapping System

Geometric descriptors for beta turns.

Beta turns, in which the protein backbone abruptly changes direction over four amino acid residues, are the most common type of protein secondary structure after alpha helices and beta sheets and play key structural and functional roles. Previous work has produced classification systems for turn geometry at multiple levels of precision, but these operate in backbone dihedral-angle (Ramachandran) space, and the absence of a local Euclidean-space coordinate system and structural alignment for turns, or of any systematic Euclidean-space characterization of turn backbone shape, presents challenges for the visualization, comparison and analysis of the wide range of turn conformations and the design of turns and the structures that incorporate them. This work derives a turn-local coordinate system that implicitly aligns turns, together with a set of geometric descriptors that characterize the bulk BB shapes of turns and describe modes of structural variation not explicitly captured by existing systems. These modes are shown to be meaningful by the demonstration of clear relationships between descriptor values and the electrostatic energy of the beta-turn H-bond, the overrepresentations of key side-chain motifs, and the structural contexts of turns. Geometric turn descriptors complement Ramachandran-space classifications, and they can be used to select turn structures for compatibility with particular side-chain interactions or contexts. Potential applications include protein design and other tasks in which an enhanced Euclidean-space characterization of turns may improve understanding or performance. The web-based tools ExploreTurns, MapTurns, and ProfileTurn, available at www.betaturn.com, incorporate turn-local coordinates and turn descriptors and demonstrate their utility.

Why don't Chinese college students seek help from the National Health Service (NHS)? Chinese college students' use of medical services in the UK

BackgroundInternational students have a lower utilization rate of the local medical service system for studying abroad, and it has been found that there may be multiple reasons behind this phenomenon. This study explores the usage of medical service systems by international students and the underlying logical factors through a study of the usage of National Health Service (NHS) of Chinese students in the UK. MethodsTo address the research questions, this study employed an online survey methodology that ran between 1st May and August 20, 2019 facing the Chinese students in the UK. A total of 1,050 questionnaires were distributed and 1,001 questionnaires were recovered, of which 977 contained valid responses (questionnaire response rate was 95.3 % and validity rate was 97.6 %). Before the questionnaire was designed and after it was issued, two focus group interviews were conducted to provide reliable and detailed information to inform the questionnaire design and to supplement the questionnaire survey data with more profound psychological qualitative data. The two focus groups consisted of 10 and 12 Chinese students studying in the UK and each lasted more than 3 h. ResultsThe survey data showed that the medical services utilization rate of Chinese students in the UK is relatively low compared to UK residents and domestic Chinese students. Their decisions and behaviours around medical services usage in the UK are not significantly related to age, gender, and monthly income, but are instead related to their current education status, types of disease suffered, and information acquisition about the UK medical services before coming to the UK. When getting sick, in addition to seeking help from official medical services, Chinese students studying in the UK tend to self-diagnose and self-medicate; seeking help from social networks based on friendship and domestic relatives are also alternatives to accessing medical services. ConclusionCombining the theories of ‘sick role’ and ‘illness experience’, the decisions and behaviours related to medical services usage by Chinese students in the UK are significantly influenced by their understanding of medical services, which is socially and culturally learned in China. Understanding the perspective of the ‘sick role’ and the ‘illness experience’ of Chinese students may help to better think about how improvements can be made to their utilization rate of medical services and their health status during their studies in the UK. This study not only provides us with specific information and understanding on the usage of medical services for Chinese students in the UK, but the research results may also provide a reference for other similar research on the health and medical service use of other international students studying in the cross-cultural contexts.

Elucidating the Role of Pro-renin Receptors in Pancreatic Ductal Adenocarcinoma Progression: A Novel Therapeutic Target in Cancer Therapy.

Pancreatic cancer is a highly aggressive malignancy with a very poor prognosis. The 5- year survival in these patients is very low, and most patients develop drug resistance to current therapies, so additional studies are needed to identify the potential role of new drug targets for the treatment of pancreatic cancer. Recent investigations have been performed regarding the roles of pro-renin receptors (PRR) in the initiation and development of cancers. PRR is a component of the local renin-angiotensin system (RAS). Local tissue RAS has been known in diverse organ systems, including the pancreas. Various investigations have implicated that PRRs are associated with the upregulation of various signaling pathways, like the renin-angiotensin system pathway, PI3K/Akt/mTOR, and the Wnt-signaling pathways, to contribute to pathological conditions, including cancer. In this review, we presented an overview of the role of PRR in the progression of pancreatic adenocarcinoma.

Bridges to care: A collaborative, community-based model of rehabilitation in Dominican Republic using the World Health Organization’s framework of community engagement

Background: The most recent national population survey of the Dominican Republic (DR) estimated that ∼12.4% of all people in the country live with a disability. Ischemic heart disease is the number one cause of death in the DR, followed by stroke and road accidents, all of which, if survived, can cause significant suffering, disability, and need for rehabilitation. Methods: This study describes a sustainable, culturally responsive collaboration between the local health systems of the DR and the Rehabilitation Department of a U.S. medical school. Results: Over a period of 7 years, 855 patients were seen around 10 locations within a regional health area in teh DR. The majority of patients reported musculoskeletal pain, which reflects global health trends. Conclusion: The described collaborative work fosters a bidirectional partnership as well as enhanced rehabilitation access in a global context.

The application of non-Latin language data in traditional cross-border payments : A discussion

During the rapid development of globalisation observed over the last few decades, the English language has emerged as the default language for the communication of cross-border payments. Concurrently, the Latinisation of communication has resolved most of the problems related to the use of non-Latin languages. However, with the G20 cross-border payment roadmap promoting connectivity with local payment systems, this paper suggests that supporting the use of non- Latin language data in certain scenarios and transaction channels could improve the efficiency of cross-border payments and help enhance financial inclusion. This paper examines the use of language data in cross-border payments, reflects on how cross-border payments might support non-Latin language data, and makes relevant suggestions.

Assessing the environmental impact and advantages of a commercial aquaponic system in Taiwan through life cycle assessment

Taiwan highly depends on food imports and has only limited arable land available as an island. Food production is projected to decrease due to climate change, while food demand is expected to increase on account of ongoing population growth. Current agriculture practices negatively affect the environment and human health, mainly by utilizing fossil fuels, chemical fertilizers, and pesticides. Hence, the development and optimization of innovative agriculture are necessary to address the adverse effects of conventional food production systems, such as nutrient pollution, to improve sustainability.Aquaponics, the combination of hydroponics and aquaculture, potentially serves as a sustainable food production method. It has become increasingly popular in recent years, as aquaponics can have a lower environmental impact than other agriculture types. Therefore, exploring the environmental impact of local aquaponic systems can contribute to food security in Taiwan.In this regard, the current study used the life cycle assessment (LCA) tool to evaluate the environmental impact of the production of fish and lettuce in an aquaponic farm in Yilan, Taiwan. From a cradle-to-farmgate perspective, two functional units, 1 kg fish and 1 kg lettuce, were investigated.The results were compared with literature studies on traditional agriculture, hydroponics, aeroponics, and aquaculture. The LCA found that aquaponics had a higher impact in almost all categories regarding lettuce production and performed comparably to other aquaculture systems, except for showcasing higher GWP and CED. However, the analysis of environmental sustainability scenarios suggested that the environmental impact could be significantly reduced for both functional units, respectively. As shown in this study, potential reductions could be achieved by replacing fertilizer with aquaponic sludge (−23 % FWE), introducing Black Soldier Fly larvae as fish feed (−11 % MWE, −14 % LU, and − 5 % WC), and integrating a solar power system (−70 % GWP, −35 % TA & FWE, and − 16 % MWE) on the greenhouse rooftop. By implementing these sustainability measures, fish production in aquaponics would outperform most aquaculture systems considered. Therefore, aquaponics represents a promising sustainable alternative to other aquaculture systems, thus potentially contributing to Taiwan's food security.

Stock Monitoring and Localization Systems for FIFO Method Using RFID Based Pressure Sensing Tag and AI

Stock Monitoring and Localization Systems for FIFO Method Using RFID Based Pressure Sensing Tag and AI

The role of local institutional quality for the digital and environmental transitions in Italy

In this paper we analyze the effect of institutional quality on the so-called Twin transition at provincial level in Italy. To carry out the analysis, we use two proxies for the ecological transition, namely waste management and air pollution, and two proxies for the digital transition, namely ultra-wide band connections and provincial innovative start-ups. All the models are estimated on a panel of 103 provinces with a time dimension that varies for the different dependent variables. We employ Spatial Durbin Model estimator to take into account spatial dependence across provinces. Our findings indicate that the quality of local institutions may have an important role for the ecological transition, but not for the digital transition. Higher levels of institutional quality increase the performance in waste management and reduce the level of local air pollution. Conversely, the estimated coefficient of institutional quality is not statistically significant neither for ultra-wide band (UWB) nor for innovative start-ups (ISs). Institutional quality turns to be significant but negative for the digital transition when dummy variable controlling for the presence of science-oriented university is added in the model specification. These results confirm that the green transition is largely policy-driven and the local ‘institutional environment’ is an essential ingredient for its effectiveness. The driving forces of the digital transition, instead, can be better found in socio-economic factors that depend on the ‘economic quality’ of the local system and its propensity to innovate within larger-scale innovation trajectories.

Satellite-based positioning enhanced by quantum synchronization

This study focuses on the innovative field of quantum synchronization for satellite-based navigation systems including Global Navigation Satellite Systems (GNSSs) and the Non-Terrestrial Network (NTN) component of future 6G networks integrating both communication and navigation services.By combining a four-qubit system with the theoretical approach of the Lindblad master equation, we transcend the inherent limits of standard synchronization techniques. This achievement represents a quantum leap in satellite-based positioning, highlighting the scalability and cost-effectiveness of our technique for smaller satellites. The study demonstrates the possibility of reducing synchronization errors to less than one meter, significantly improving the reliability and precision of satellite-based navigation systems.The results of this study may contribute to the future development of both user-centric localization systems (typically GNSS systems) and network-centric localization systems (typically through the NTN component of 6G networks), leading to better positioning performance, more flexible multi-functional systems with the potential to limit both cost and size of satellites.

Outstanding Potential for Treating Wastewater from Office Buildings Using Fixed Activated Sludge with Attached Growth Process

The application of fixed activated sludge with an attached growth process (FASAG) with optimal operating conditions (hydraulic retention time (HRT) of 7 h, dissolved oxygen (DO) of 6 mg/L, and alkalinity dosage of 7.14 mgCaCO3/mgN-NH4+) treats wastewater generated from office buildings to meet discharge requirements (as per the regulation in the nation where the study was conducted) with typical parameters such as pH of 6.87–7.56, chemical oxygen demand (COD) of 32–64 mg/L, suspended solids (SS) of 8–11 mg/L, N-NH4+ of 1–7 mg/L, and denitrification efficiency reaches 53%. In addition, the FASAG is an outstanding integration that makes both economic and environmental sense when applied in local wastewater treatment systems. In particular, this process combines aerobic and anoxic processes in a creation tank. This explains why this approach can save investment and operating costs, energy, and land funds. In office building regions, where land area is frequently limited, saving land funds presents numerous options to enhance the density of green cover. Furthermore, as a new aspect, investing in reusing wastewater after treatment to irrigate plants or flush toilets in office buildings contributes to a decrease in the quantity of wastewater released into the environment, saving water resources and supporting sustainable development.

LiDAR‐based place recognition for mobile robots in ground/water surface multiple scenes

AbstractLiDAR‐based 3D place recognition is an essential component of simultaneous localization and mapping systems in multi‐scene robotic applications. However, extracting discriminative and generalizable global descriptors of point clouds is still an open issue due to the insufficient use of the information contained in the LiDAR scans in existing approaches. In this paper, we propose a novel spatial‐temporal point cloud encoding network for multiple scenes, dubbed STM‐Net, to fully fuse the multi‐view spatial information and temporal information of LiDAR point clouds. Specifically, we first develop a spatial feature encoding module consisting of the single‐view transformer and multi‐view transformer. The module learns the correlation both within a single view and between two views by utilizing the multi‐layer range images generated by spherical projection and multi‐layer bird's eye view images generated by top‐down projection. Then in the temporal feature encoding module, we exploit the temporal transformer to mine the temporal information in the sequential point clouds, and a NetVLAD layer is applied to aggregate features and generate sub‐descriptors. Furthermore, we use a GeM pooling layer to fuse more information along the time dimension for the final global descriptors. Extensive experiments conducted on unmanned ground/surface vehicles with different LiDAR configurations indicate that our method (1) achieves superior place recognition performance than state‐of‐the‐art algorithms, (2) generalizes well to diverse sceneries, (3) is robust to viewpoint changes, (4) can operate in real‐time, demonstrating the effectiveness and satisfactory capability of the proposed approach and highlighting its promising applications in multi‐scene place recognition tasks.

Mental health of the Pacific Island Nation communities: What the rest in the world can contribute to and learn from?

Creating Futures initiative has established a network of mental health professionals, researchers, and community members from the Pacific Island Nations (PIN), Australia, and New Zealand to address the growing challenges of mental health conditions compounded by the climate change crisis. The enormous amount of work done in Global Mental Health can be particularly helpful to improve population-level mental health. However, translation of this evidence base into practice poses several challenges. This perspective paper discusses the role of local culture and health systems context in determining the feasibility and acceptability of implementing and scaling up evidence-based interventions designed in an American-European context. The paper also advocates development (and evaluation) of mental health interventions in the PIN communities particularly and Global South generally and exporting these interventions to the rest of the world. COVID-19 crisis underlined the role of global cooperation as well as national level 'self-reliance'. In this post COVID-19 world, it will be desirable for the mental health community to cooperate and collaborate to scale up evidence-based interventions through rigorous contextualization and at the same time main-stream mental health interventions developed in the Global South by incorporating them in the Global Mental Health discourse.

“Planeterranean” diet: the new proposal for the Mediterranean-based food pyramid for Asia

Background and objectivesThe Mediterranean Diet (MD) has been recognized for its benefits for human health and sustainability for the planet, but it has considered not easy to reproduce in other populations. The United Nations Educational, Scientific and Cultural Organization (UNESCO) Chair on Health Education and Sustainable Development is fostering a research project (Planeterranea), aiming to identify a healthy dietary pattern based on local foods with the same MD features. The aim of our study is to develop a MD-based food pyramid for Asian populations.MethodsAsia was stratified into six areas according to pedo-climatic conditions. For each region a comprehensive scoping review of local crops and typical foods was conducted on several databases such as the US Department of Agriculture (USDA)’s database, the Food and Agriculture Organization of the United Nations (FAO) website, and PubMed, focusing on both plant-based and animal-based foods. Narrative review was then conducted on the identified foods to determine their nutritional composition and planetary health impact. Finally, the collected information was used to build up the Asian food pyramid with details for each respective region.ResultsWe proposed a food pyramid for Asian countries, guaranteeing the same nutritional intake and health benefits as MD, by considering dietary habits and typical foods of this population. From the bottom to the top, Asian fruits and vegetables present similar nutritional profile as those in MD. Whole grains (barley) may represent valid alternative to white rice. Sesame oil represents a source of unsaturated fats and an alternative to olive oil. Legumes (soybean), edible insects, mushrooms and algae, guarantee an adequate intake of plant-based proteins with a complete amino-acid profile and a low environmental impact with respect to animal-based ones.ConclusionsThis work is a new insight of healthy and sustainable local food system based on MD principles for the Asian population.

Prediction of long-term photovoltaic power generation in the context of climate change

Accurate long-term prediction of power generation in photovoltaic (PV) power stations is crucial for preparing generation plans and future planning. Quantitative prediction of future power generation from PV stations not only contributes to the stable operation of the local power system but also assists managers in formulating regional energy policies to promote renewable energy consumption. We utilized the NEX-GDDP-CMIP6 high-resolution climate dataset and employed the Vine Copula method for post-downscaling. This approach enabled high-resolution forecasts of key meteorological factors under different shared socioeconomic pathways (SSPs) scenarios (SSP245 and SSP585) for a PV power station in Yunnan, China. Additionally, we developed the KM-PSO-SVR power generation prediction model, which enables future accurate long-term PV power generation prediction. The results show that the Vine Copula multi-model ensemble downscaling model can effectively simulate the changes in key meteorological factors in the PV power station area. The KM-PSO-SVR model exhibited good simulation performance, with a mean absolute error of 0.843, root mean square error of 1.136, and correlation coefficient of 0.874 during the validation period. The results indicate that during the decade spanning from January 1, 2025, to December 31, 2034, radiation and wind speed will be decrease, while the temperature is expected to increase. In the SSP245 scenario, there is a 1.585 % increase in the average annual power generation during the future carbon peaking period (2025–2034). However, the SSP585 scenario, representing higher future emissions, shows a lower increase of 1.479 %.

Wirelessly Powered Visible Light-Emitting Implant for Surgical Guidance during Lumpectomy.

Achieving negative surgical margins, defined as no tumor found on the edges of the resected tissue, during lumpectomy for breast cancer is critical for mitigating the risk of local recurrence. To identify nonpalpable tumors that cannot be felt, pre-operative placements of wire and wire-free localization devices are typically employed. Wire-free localization approaches have significant practical advantages over wired techniques. In this study, we introduce an innovative localization system comprising a light-emitting diode (LED)-based implantable device and handheld system. The device, which is needle injectable and wire free, utilizes multiple wirelessly powered LEDs to provide direct visual guidance for lumpectomy. Two distinct colors, red and blue, provide a clear indication of tissue depth: blue light is absorbed strongly in tissue, visible within a close range of <1 cm, while red light remains visible through several centimeters of tissue. The LEDs, integrated with an impedance-matching circuit and receiver coil, are encapsulated in biocompatible epoxy for injection with a 12 G needle. Our findings demonstrate that the implant exhibits clearly perceivable depth-dependent color changes and remains visible through >2 cm of ex vivo chicken breast and bovine muscle tissue using less than 4 W of transmitted power from a handheld antenna. These miniaturized needle-injectable localization devices show promise for improving surgical guidance of nonpalpable breast tumors.

Ada-LT IP: Functional Discriminant Analysis of Feature Extraction for Adaptive Long-Term Wi-Fi Indoor Localization in Evolving Environments.

Wi-Fi fingerprint-based indoor localization methods are effective in static environments but encounter challenges in dynamic, real-world scenarios due to evolving fingerprint patterns and feature spaces. This study investigates the temporal variations in signal strength over a 25-month period to enhance adaptive long-term Wi-Fi localization. Key aspects explored include the significance of signal features, the effects of sampling fluctuations, and overall accuracy measured by mean absolute error. Techniques such as mean-based feature selection, principal component analysis (PCA), and functional discriminant analysis (FDA) were employed to analyze signal features. The proposed algorithm, Ada-LT IP, which incorporates data reduction and transfer learning, shows improved accuracy compared to state-of-the-art methods evaluated in the study. Additionally, the study addresses multicollinearity through PCA and covariance analysis, revealing a reduction in computational complexity and enhanced accuracy for the proposed method, thereby providing valuable insights for improving adaptive long-term Wi-Fi indoor localization systems.

An efficient and lightweight banana detection and localization system based on deep CNNs for agricultural robots

Accurate detection and localization of fruits in natural environments is a key step for fruit picking robots to achieve precise harvesting. However, existing banana detection and positioning methods have two main limitations in practical applications: a large number of model parameters that make deployment difficult, and a need for performance improvement. To tackle the above issues, a high-precision and lightweight banana bunch recognition and localization method was proposed and deployed on edge devices for application. First, a Slim-Banana model was proposed based on the improvement of YOLOv8l. In order to reduce the model calculation amount and maintain high performance, GSConv was introduced in the Slim-Banana model to replace the standard convolution, and combined with grouped convolution and spatial convolution. At the same time, the cross-stage local network (GSCSP) module was designed to reduce the computational complexity and the complexity of the network structure through a single-stage aggregation method. Then, the RealSense depth sensor is combined with TOF technology to perform image registration and 3D localization of the banana. Finally, the pipeline is deployed on the Nvidia Orin NX edge device and its performance and resource consumption in actual work are deeply analyzed. Experimental results show that the detection precision, recall, mAP and inference time of our method are 0.947, 0.948, 0.98 and 113.6ms respectively, the network memory size required is 4449MiB, and the average localization errors in the X-axis, Y-axis and Z-axis directions are 13.47mm, 12.87mm and 13.87mm respectively. To our knowledge, this is the first work that implements banana detection and localization on edge devices. Experimental results show that compared with existing methods, our method achieves better performance in complex orchard environments, achieving efficient and lightweight banana recognition and localization.

Mission, (self)-perception and role in localized food systems of Italian biodistricts: insights from a Delphi survey

Mission, (self)-perception and role in localized food systems of Italian biodistricts: insights from a Delphi survey

Intraoperative Cavity Local Delivery System with NETs-Specific Drug Release for Post-Breast Cancer Surgery Recurrence Correction.

Postoperative breast cancer recurrence is tricky due to the limited therapeutic options. Transforming growth factors-β (TGF-β) is vital in promoting postoperative tumor recurrence. However, conventional blocking strategies fail to satisfy both bio-safety and sufficient relapse correction. Neutrophil extracellular traps (NETs) are essential for the spatiotemporal dynamics of TGF-β at tumor-resection sites, whose unique mechanism for local TGF-β amplification could remarkably increase the risk of relapse after surgery. Herein, the principle of NETs formation is ingeniously utilized to construct a surgical residual cavity hydrogel that mimics NETs formation. The hydrogel is prepared based on the electrostatic interaction between histidine (His) and sodium alginate (Alg). Then, arginine deiminase 4 (PAD4) protein is released during NETs formation. Simultaneously, the electrical property of His in hydrogel changes automatically, which further lead to promising localized release of anti-TGF-β. The hydrogel system can realize specific and selective drug release at targeted NETs site over a prolonged period while exhibiting excellent biocompatibility. Superior breast cancer recurrence inhibition is achieved by suppressing TGF-β and related indicators, impeding epithelial-mesenchymal transition (EMT) progression, and rectifying the locally exacerbated immunosuppressive environment within NETs. The novel NETs local microenvironment drug release functional hydrogel will provide inspiration for postoperative recurrence correction strategies.