Local Objectives Research Articles

The efficacy and safety of stereotactic body radiotherapy combined with systematic therapy for metastatic renal cell carcinoma: a systematic review and meta-analysis.

There is considerable interest in the potential of stereotactic body radiation therapy (SBRT) combined with systemic therapy such as tyrosine kinase inhibitors (TKIs) or immune checkpoint inhibitors (ICIs). However, its efficacy and safety remain unclear. The purpose of this study was to evaluate the efficacy and safety of conducting SBRT during ICI or TKI treatment in different disease settings for patients with metastatic renal cell carcinoma (mRCC). A total of 16 studies were ultimately included. Under the random effects model, the pooled 1-year local control rate (1-yr LCR) and objective response rate (ORR) were 90% (95% confidence interval [CI]: 80%-95%, I 2=67%) and 52% (95% CI: 37%-67%, I 2=90%), respectively. SBRT concomitant with different systemic therapy yield significant different 1-yr LCR (p<0.01) and ORR (p=0.02). Regarding survival benefits, the pooled 1-year progression-free survival (1-yr PFS) and 1-year overall survival (1-yr OS) rates were 45% (95% CI: 29%-62%, I 2=91%) and 85% (95% CI: 76%-91%, I 2=66%), respectively. 1-yr PFS and 1-yr OS in different disease settings demonstrated significant difference (p<0.01). As for toxicity, the pooled incidence of grade 3-4 adverse events was 14% (95% CI: 5%-26%, I 2=90%). This study highlights the feasibility of utilizing these strategies in mRCC patients, especially those with a low metastatic tumor burden.

Baseline assessment and early effects of a network of marine protected areas

AbstractMarine protected areas (MPAs) can be a useful tool to manage coastal ecosystems, delivering both social and ecological outcomes. However, in many instances, relevant data is missing to conduct proper impact assessments, which is key to identifying ecological and social synergies and potential trade‐offs, and to adapting management according to local objectives. The ecological effects of an MPA established in Palawan, Philippines, in 2016, were assessed. The most common species targeted by fisheries were identified by local fishers. Species size and number were collected through underwater visual census with n = 288 belt transects assigned in different sites and locations to ensure to provide both protected and control (fished) sites for the MPA assessment, and baseline data for three new MPAs that were created in 2022. 91 coral‐reef fish species belonging to 12 families were recorded. Mixed effect linear regression was used to compare target fish populations in protected and control sites. Compared to control locations, 5 years after its implementation, the MPA showed significantly higher species richness, abundance, mean size, and biomass while no significant difference was found on the average trophic level between MPA and control sites. Monitoring the early effects of an MPA and collecting baseline data prior the implementation of an MPA network is key for adaptive management.

Fixed-time cluster optimization of multi-agent systems on directed detail-balanced networks

This paper investigates the fixed-time cluster optimization problem of first-order multi-agent systems (MASs) under directed detail-balanced networks, in which the optimization objective is a linear combination of local objective functions. Two piecewise distributed control protocols are proposed to solve the optimization problem with time-invariant and time-varying objective functions, respectively. Under the two proposed piecewise control protocols, the fixed-time cluster optimization problem can be solved on the basis of maintaining the cluster consensus unchanged. Furthermore, the initial states of all the agents need not be restricted to the minimum of their local cost functions. Finally, we provide two examples to illustrate the effectiveness of the proposed control protocols.

Distributed optimization for discrete time‐varying linear multi‐agent systems with event‐triggered communication

AbstractThis paper studies the distributed optimization problem (DOP) of discrete time‐varying linear multi‐agent systems (MASs), in which the global objective function is formed by a sum of local convex objective functions. Firstly, a DOP with discrete time‐varying MASs is considered, in which the time‐varying linear matrix satisfies a certain equality constraint. To solve this problem, a novel discrete‐time distributed optimization algorithm (DOA) with event‐triggered communication mechanism (ETCM) is proposed. Secondly, by constructing the error dynamical system and using a series of inequality techniques, some sufficient conditions for achieving consensus and obtaining the optimal solution are established. It is found that the considered MAS has generality and the proposed DOA has the advantage of reducing communication burden. Finally, a numerical simulation is presented to verify the validity of theoretical results.

A toolkit for planning and implementing acute febrile illness (AFI) surveillance.

Acute febrile illness (AFI) is a broad clinical syndrome with a wide range of potential infectious etiologies. The lack of accessible, standardized approaches to conducting AFI etiologic investigations has contributed to significant global gaps in data on the epidemiology of AFI. Based on lessons learned from years of supporting AFI sentinel surveillance worldwide, the U.S. Centers for Disease Control and Prevention developed the toolkit for planning and implementing AFI surveillance, described here. This toolkit provides a comprehensive yet flexible framework to guide researchers, public health officials, and other implementers in developing a strategy to identify and/or monitor the potential causes of AFI. The toolkit comprises a cohesive set of planning aids and supporting materials, including an implementation framework, generic protocol, several generic forms (including screening, case report, specimen collection and testing, and informed consent and assent), and a generic data dictionary. These materials incorporate key elements intended to harmonize approaches for AFI surveillance, as well as setting-specific components and considerations for adaptation based on local surveillance objectives and limitations. Appropriate adaptation and implementation of this toolkit may generate data that expand the global AFI knowledge base, strengthen countries' surveillance and laboratory capacity, and enhance outbreak detection and response efforts.

Recife park city: the role of the Recife local climate action plan and the Pernambuco decarbonization plan

This article explores the convergence between Recife and Pernambuco's climate plans and the "Recife Park City" vision. The objectives include the analysis of the goals of the Recife Local Climate Action Plan, the investigation of the guidelines of the Pernambuco Decarbonization Plan in relation to the urban context of Recife and the evaluation of the initiatives of the Recife Park City Project in accordance with local climate objectives and regional. The methodology of the research will be bibliographical review, together with documentary analysis of these plans. We address the intersection between urban sustainability, climate resilience and development, providing valuable insights to promote more sustainable urban practices, respecting the specific environmental and social characteristics of the region. Understanding these strategies is crucial to guide public policies and urban practices towards a more sustainable and environmentally conscious future. According to research, climate plans reflect a comprehensive commitment to sustainable urban development, highlighting the importance of social inclusion, active mobility, cultural identity and environmental conservation to ensure a resilient and equitable future.

Rancang Bangun Sistem Informasi Wisata Budaya (Studi Kasus Kabupaten Bandung)

This Cultural Tourism Information System is constructed with the purpose of seeking information about cultural tourism and cultural objects in the Bandung Regency area. Besides providing cultural tourism information, this cultural tourism information system is employed to discover various cultural tourism events within the Bandung Regency region. Through this research, it is anticipated that it will be beneficial for cultural tourism promotion and aiding in the advancement of local cultural objects in the Bandung Regency. The research method applied is the Rational Unified Process with the utilization of Unified Modeling Language in modeling, while testing is conducted through the BlackBox Testing method. This application is developed using the Laravel Framework and Bootstrap, The results of the implementation show that the overall constructed information system aligns with user requirements. From the conducted User Acceptance Test (UAT), the average parameter results were as follows: design 3.89 (77.9%), features 3.76 (75.3%), and user satisfaction 4.20 (84.2%).

Distributed Event-Triggered Algorithm with Network Independent Step-Size for Constraint-Coupled Optimization Problems

In this study, we introduce a distributed algorithm that is specifically designed to address optimization problems featuring a decomposable objective function and equality constraints. To minimize the amount of communication required, we incorporate an event-triggered mechanism that enables information exchange only when variable values exceed predefined thresholds. Importantly, our proposed algorithm possesses a distinctive characteristic where the determination of step size is solely based on the properties of the objective function, regardless of the structure of the communication network. Even in situations where changes occur in the network structure, our algorithm remains valid without necessitating any updates to its step size. Assuming strong convexity and smoothness in local objective functions, along with appropriate event-triggered thresholds, our algorithm achieves a convergence rate that is linear. Several numerical experiments provide evidence supporting the effectiveness and superiority of our proposed approach.

School Food Policy through a Project Financing

In recent years, the scientific community has focused more on urban food policies adopted by big cities and less on the local food policies adopted by small municipalities. Furthermore, the empirical evidence on school food policy initiatives is quite fragmented, and the management of the canteen service is not directly addressed by the studies carried out. In this work, the school food policy implemented in a small municipality (Corciano in the province of Perugia, Centre Italy) of about 22,000 inhabitants, through the application of project financing with the participation of local social cooperatives is presented and discussed. This paper aims to reflect on the capability of the alternative food networks developed through the project financing mechanism to identify and implement the uses of the resources concerning the local food policy objectives and the project capacity of the network. The analysis is conducted using a methodological approach based on agricultural economics and anthropology. Results from economic data analysis, collective interviews, and participant observation show that: the financial balance of the project financing is positive but quite precarious and very sensitive to market variations, both regarding the overall demand for canteen meals, and the procurement of raw materials and workforce; the project’s organizational model through a local network not only can combine the environmental, social, and health dimensions of food, but it can also reshape the local concept of community, as well as new opportunities for the circulation of food products.

Dense Contrastive-based Federated Learning for Dense Prediction Tasks on Medical Images.

Deep learning (DL) models have achieved remarkable success in various domains. But training an accurate DL model requires large amounts of data, which can be challenging to obtain in medical settings due to privacy concerns. Recently, federated learning (FL) has emerged as a promising solution that shares local models instead of raw data. However, FL in medical settings faces challenges of client drift due to the data heterogeneity across dispersed institutions. Although there exist studies to address this challenge, they mainly focus on the classification tasks that learn global representation of an entire image. Few have been studied on the dense prediction tasks, such as object detection. In this study, we propose dense contrastive-based federated learning (DCFL) tailored for dense prediction tasks in FL settings. DCFL introduces dense contrastive learning to FL, which aligns the local optimization objectives towards the global objective by maximizing the agreement of representations between the global and local models. Moreover, to improve the performance of dense target prediction at each level, DCFL applies multi-scale contrastive representation by utilizing multi-scale representations with dense features in contrastive learning. We evaluated DCFL on a set of realistic datasets for pulmonary nodule detection. DCFL demonstrates an overall performance improvement compared with the other federated learning methods in heterogeneous settings-improving the mean average precision by 4.13% and testing recall by 6.07% in highly heterogeneous settings.

Distributed Event-Triggered Algorithm Designs for Resource Allocation Problems via a Universal Scalar Function-Based Analysis.

In this article, we are concerned with distributed algorithm designs for resource allocation problems via event-triggered communication. The target is to search an optimal resource allocation scheme such that the summation of objective functions is minimized. Due to communication efficiency and privacy concerns, distributed algorithms with event-triggered communications are proposed in this article. The communication is only permitted or triggered if variation of gradient of the local objective function exceeds a threshold. By constructing a novel technical lemma and a universal scalar function, the convergence and linear convergence rates are established under some mild assumptions. Extensive numerical experiments on the IEEE 118-bus power system demonstrate that: Compared to the periodic algorithms, such as ADMM and Mirror-P-EXTRA, the proposed algorithms not only remarkably reduce the communication times but also have competitive convergence speed. The latter is striking that it implies there exist useless communications in the periodic algorithms that are censored by the proposed event-triggered strategy.

The Development of a Multi-Modal Cancer Rehabilitation (Including Prehabilitation) Service in Sheffield, UK: Designing the Active Together Service.

Cancer patients undergoing major interventions face numerous challenges, including the adverse effects of cancer and the side effects of treatment. Cancer rehabilitation is vital in ensuring cancer patients have the support they need to maximise treatment outcomes and minimise treatment-related side effects and symptoms. The Active Together service is a multi-modal rehabilitation service designed to address critical support gaps for cancer patients. The service is located and provided in Sheffield, UK, an area with higher cancer incidence and mortality rates than the national average. The service aligns with local and regional cancer care objectives and aims to improve the clinical and quality-of-life outcomes of cancer patients by using lifestyle behaviour-change techniques to address their physical, nutritional, and psychological needs. This paper describes the design and initial implementation of the Active Together service, highlighting its potential to support and benefit cancer patients.

Особенности теплового поля города Ростова-на-Дону по данным дистанционного зондирования Земли

Thermal fields of natural and anthropotechnogenic origin are an integral part of the urban habitat, which influences the functioning of its components, as well as determines the conditions of existence of living organisms including humans. Settlements act as areas of formation of extensive temperature anomalies, mainly positive ones, known as urban heat island. This phenomenon was discovered more than 200 years ago and is currently being investigated in detail. However, the study of smaller anomalies - neighbourhood-scaled and local - is also a subject of scientific and practical interest. These heterogeneities in the distribution of thermal energy are caused by the presence or functioning of individual objects, and therefore, on the one hand, have a direct impact on the state of the environment and human living conditions, and on the other hand, are a promising area for the development of environmental engineering and settlement rational arrangement. As part of the conducted research, the main patterns of spatial distribution of the Earth&amp;#x27;s surface temperature within the Rostov-on-Don city district were identified, as well as the areas of formation of anomalies of local and neighbourhood scale and objects and processes contributing to their formation were identified. The results and conclusions can be used for further study of ecological and geophysical features of urban landscapes, and also have an applied value in determining the direction and consequences of the impact of the advancement of specific types of urban development of the territory.

Federated X-armed Bandit

This work establishes the first framework of federated X-armed bandit, where different clients face heterogeneous local objective functions defined on the same domain and are required to collaboratively figure out the global optimum. We propose the first federated algorithm for such problems, named Fed-PNE. By utilizing the topological structure of the global objective inside the hierarchical partitioning and the weak smoothness property, our algorithm achieves sublinear cumulative regret with respect to both the number of clients and the evaluation budget. Meanwhile, it only requires logarithmic communications between the central server and clients, protecting the client privacy. Experimental results on synthetic functions and real datasets validate the advantages of Fed-PNE over various centralized and federated baseline algorithms.

The sustainability of developmental programs by the U.S. and China in Sub-Saharan Africa: a comparison of effectiveness

This descriptive comparative qualitative case study examines the sustainability of development programs in Sub-Saharan Africa. We evaluated economic, social, environmental, and institutional development programs from the People’s Republic of China (PRC) and the U.S. to Sub-Saharan Africa for sustainable development to fill the research gap on these technique’s success and effects on Sub-Saharan Africa. Using purposive sampling, we chose eight Sub-Saharan African countries representing distinct geographies and economies. The College of William & Mary’s AID Data-GeoCoded Chinese Official Finance Dataset, China Africa Research Initiative, and USAID’s Foreign Aid Explorer provided data. Results revealed a complex view of Sub-Saharan Africa’s development policy success. Proposition 1, which claims China’s economic tactics exceed those of the U.S., is supported by significant infrastructure investments but presents sustainability problems. Proposition 2, praising the social development initiatives of the U.S., is supported by gains in healthcare and education in other countries. However, context-specific issues persist. Proposition 3 shows that U.S. conservation collaborations have improved environmental preservation. Proposition 4 claims that both countries’ institutional development plans fail. The results highlight local government buy-in issues and the need for adaptation. Some of the ideas find support in recent research; however, country and context differences require unique tactics. Development efforts in Sub-Saharan Africa should focus on long-term sustainability, local objectives, and environmental implications. Effective institutional growth requires adaptation and a strong awareness of local governing dynamics, and policymakers, development practitioners, and scholars may gain insight into sustainability and development projects in Sub-Saharan Africa from this research. A holistic approach that balances economic, social, environmental, and institutional factors is needed to attain sustainable development goals.

Fine-grained image classification based on TinyVit object location and graph convolution network

Fine-grained image classification is a branch of image classification. Recently, vision transformer has made excellent progress in the field of image recognition. Its self-attention mechanism can extract very effective image feature information. However, feeding fixed-size image blocks into the network introduces additional noise, which is detrimental to extract discriminative features for fine-grained images. The vision transformer's network model is large, making it difficult to utilize in practice. Moreover, many of today's fine-grained image classification methods focus on mining discriminative features while ignoring the connections within the image. To address these problems, we propose a novel method based on the lightweight TinyVit backbone network. Our approach utilizes the self-attention weight values of TinyVit as a guide to construct an effective object location (OL) module that cuts and enlarges the object area, providing the network with the opportunity to concentrate on the local object. Additionally, we employ the graph convolutional network (GCN) to create a spatial relationship feature learning (SRFL) module that captures spatial context information between image blocks in TinyVit with the help of the transformer's self-attention weights. OL and SRFL collaborate to jointly guide the classification task. The experimental results show that the proposed method achieved competitive performance, with the second-highest classification faccuracy on both the CUB-200–2011 and NABirds datasets. When tested on the Stanford Dogs dataset, our approach outperformed many popular methods. Our code is uploaded on https://github.com/hhhj1999/SRFL_OL.

Justification of the approach to searching for and exploring productive objects: a case study of the Krasnoleninsk and Angaro-Lena oil and gas regions

The article provides a rationale for the approach to the search and exploration of local productive zones based on the analysis of geographically distant objects of different geological structures: the Tyumen and Chora formations. The need for a joint study of the problem of localizing oil and gas deposits has been identified by comparing the patterns of location of local productive objects in remote territories that differ in their geological structure. The relevance of the study is determined by the significant degree of depletion of reserves of hydrocarbon deposits, characterized by the simplest development conditions and the need to find an approach to the study of deposits, within which the establishment and description of the patterns of deposit structure cause difficulties. The primary information for the study was drilling data, geophysical well survey results, description of core material, petrophysical survey data, information on testing and well performance dynamics, 2D seismic interpretation materials, as well as published articles. Methods of analysis and comparison were adopted as a basis in order to highlight common features of the distribution of hydrocarbon deposits in the studied areas. In the course of the study, the prerequisites were formed for the development of a comprehensive methodology for studying the structure of hydrocarbon deposits of Tyumen and Chora formations from the perspective of an approach to the exploration of complex objects, implying a joint study of the possibilities of processes described separately by both organic and inorganic hypotheses of oil and gas generation. The need to introduce an approach to geological modeling that takes into account the fractal structure of geological systems is formulated.

Quasi-local masses and cosmological coupling of black holes and mimickers

Motivated by the recent heated debate on whether the masses of local objects, such as compact stars or black holes (BHs), may be affected by the large-scale, cosmological dynamics, we analyze the conditions under which, in a general relativity framework, such a coupling small/large scales is allowed. We shed light on some controversial arguments, which have been used to rule out the latter possibility. We find that the cosmological coupling occurs whenever the energy of the central objects is quantified by the quasi-local Misner-Sharp mass (MS). Conversely, the decoupling occurs whenever the MS mass is fully equivalent to the (nonlocal) Arnowitt-Deser-Misner (ADM) mass. Consequently, for singular BHs embedded in cosmological backgrounds, like the Schwarzschild-de Sitter or McVittie solutions, we show that there is no cosmological coupling, confirming previous results in the literature. Furthermore, we show that nonsingular compact objects couple to the cosmological background, as quantified by their MS mass. We conclude that observational evidence of cosmological coupling of astrophysical BHs would be the smoking gun of their nonsingular nature.

Combination of intrahepatic TARE and extrahepatic TACE to treat HCC patients with extrahepatic artery supply: A case series

PurposeThe aim of this study was to report the safety and tumor response rate of combined transarterial radioembolization (TARE) through the intrahepatic arteries and transarterial chemoembolization (TACE) through the extrahepatic feeding arteries (EHFA) in patients with hepatocellular carcinoma (HCC). MethodsPatients with HCC, who had both intrahepatic and extrahepatic arterial supply visible on preinterventional multiphase CT and were treated between 2016 and 2021 with a combination of TACE and TARE on the same nodule, were retrospectively included. Epidemiological, clinical, biological, and radiological characteristics were recorded. Safety and tumor response were assessed at 6 months. ResultsNine patients (8 men, median age 62 years [IQR: 54–72 years]) were included. Seven patients had previous treatments on the target nodule (TARE: 5; TACE: 2). The median longest axis (LA) of the lesion was 70 mm (IQR: 60–79 mm). Three patients had portal vein invasion (VP3). The EHFA originated from the right diaphragmatic artery (n = 6), the right adrenal artery (n = 2), and the left gastric artery (n = 1). The LA of the tumor portion treated with TACE was 47 mm (range: 35–64 mm). The ratio between the LA of the entire lesion and the LA treated with TACE was 1.44 (range: 1.27–1.7). One major complication occurred: acute on chronic liver failure. Median follow-up was 23 months (range: 16–29 months). Seven patients underwent further treatment: on the same lesion (n = 2), on newly appeared nodules (n = 2), and systemic treatment (n = 3). At 6-month follow-up, seven patients showed a local objective response. Time-to-progression was 13 (3.5–19) months. ConclusionThe combination of TARE and extrahepatic TACE for HCC with both intrahepatic and extrahepatic arterial supplies seems feasible and safe. Further studies are needed to validate the effectiveness of these preliminary results.

Current Issues Problems of Geoinformatics

Geoinformatics is a scientific discipline that focuses on natural, technical, and socioeconomic spatial systems studied through computer modeling of localized objects and phenomena. The main goals of geoinformatics as a science are visualization, localization, and decision-making regarding spatial transformations of the environment. The structure of geoinformatics includes such sections as geosystem modeling, spatial analysis, and applied geoinformatics itself. The development of technologies for collecting, storing, converting and exchanging spatial and temporal data has led to the rapid development of GIS technologies and the emergence of a wide variety of industrial GIS aimed at processing geodata in order to make informed decisions. Currently, geoinformatics in many industries is perceived as a geoinformation industry, which implies the presence of its own equipment, the development of commercial software products such as GIS, a staff of experienced expert analysts and the organization of marketing. The paper highlights three of the most pressing problems faced by researchers in the field of geoinformatics over the past two decades: interoperability, digital transformation, and geodata fusion. The characteristic features of these problems and some aspects of their solution are considered.