scholarly journals Regeneration of Post-Agricultural Brownfield for Social Care Needs in Rural Community: Is There Any Transferable Experience?

2021 ◽  
Vol 19 (1) ◽  
pp. 240
Author(s):  
Petr Klusáček ◽  
Klára Charvátová ◽  
Josef Navrátil ◽  
Tomáš Krejčí ◽  
Stanislav Martinát
Keyword(s):  
Rural Communities ◽  
Large Scale ◽  
Social Care ◽  
Good Governance ◽  
Local Development ◽  
Population Aging ◽  
Real Life ◽  
Care Facility ◽  
Care Needs ◽  
Agricultural Cooperative

In the 21st century, rural communities face many challenges, including implications of dynamic population aging, a lack of social care services, and the occurrence of abandoned post-agricultural brownfields. This paper is methodologically based on the findings derived from a set of qualitative in-depth interviews with the key rural stakeholders, explores the decisive factors and limits, accelerators, and barriers governing successful regeneration of the post-agricultural brownfield in the post-socialist environment. We are using the case of the regeneration project of a large-scale former communist agricultural cooperative, located in Vranovice, the Czech Republic, to illuminate how complex and challenging the redevelopment of a post-agricultural brownfield into a social care facility for elderly people is. A wide agreement among the experts in the field of community development exists that this regeneration project can serve as a model example for other rural municipalities that are sharing similar local development issues. Our findings illustrate how important and challenging at the same time are the matters of good governance, the active and long-term participation of stakeholders in the regeneration project, and the real-life introduction of the public–private partnership concept, particularly in immensely transforming the post-socialist countryside.

Who is vulnerable? Adult social care and modern slavery

2017 ◽  
Vol 19 (1) ◽  
pp. 21-32 ◽  
Author(s):  
Gary Craig ◽  
Stephen Clay
Keyword(s):  
Design Methodology ◽  
Social Care ◽  
Real Life ◽  
Care Needs ◽  
Content Type ◽  
Modern Slavery ◽  
History Of ◽  
Forced Labour ◽  
The Uk ◽  
Practical Implications

Purpose The 2015 Modern Slavery Act focusses attention forms of modern slavery (human trafficking and forced labour), within the UK. The contemporaneous 2014 Care Act, identifies modern slavery as a new form of risk within adult social care, listing forms of abuse and vulnerability. However, it does not consider whether those providing care may themselves be vulnerable to forms of modern slavery. The paper aims to discuss these issues. Design/methodology/approach The authors describe the history of the development of modern slavery legislation in the UK, outline key provisions of the Care Act, illustrated with real-life cases. The analysis suggests that adult social care – characterised by informality, fragmentation and vulnerability – is one where instances of modern slavery may be more common than considered to date. Findings The data collected, though relatively modest, suggests that a thorough investigation should be undertaken into the possibility of modern slavery taking place within the realm of adult social care. Research limitations/implications Data have been collected through a snowball process, rolling out a survey to relevant groups of individual and organisations. A more rigorous investigation is required to examine the extent of modern slavery within adult social care. Practical implications The training of those responsible for the regulation/management of adult social care needs to ensure that they are fully equipped to understand the nature of modern slavery and how to identify its symptoms and victims. Social implications There is also a need for heightened awareness of those close to people being cared for that they may also identify the symptoms of modern slavery. Originality/value This area has not been explored to date.

Tata kelola internal dan eksternal untuk mengatasi permasalahan pangan di Indonesia

2018 ◽  
Vol 13 (1) ◽  
Author(s):  
Reza Hendriyantore
Keyword(s):  
Good Governance ◽  
National Level ◽  
Open Government ◽  
Agricultural Cooperatives ◽  
Methodological Framework ◽  
Agricultural Cooperative ◽  
The Reformation ◽  
The Government ◽  
Good Access ◽  
Descriptive Method

The effort to put good governance in development in Indonesia is basically not new. Since the Reformation, the transformation of closed government into an open government (inclusive) has begun to be pursued. Highlighting the conflicts in the land sector that tend to strengthen lately, there are some issues that have intensified conflicts in the field, such as the lack of guaranteed land rights in various legal and policy products. In this paper, a descriptive method is considered important in identifying the applicable issue and methodological framework for addressing governance issues in Indonesia. To reduce such agrarian conflicts between farmers and the government, and as an effort to increase farmers' income, all farmers are incorporated into agricultural cooperatives. Agricultural cooperatives are structured down to the National Level. Thus, farmers participate in good access to the marketing of agricultural produce.Keywords:good governance, agrarian conflict, agricultural cooperative

Health Literacy and Long-Term Care Needs among Thai Elderly in Rural Communities

2020 ◽  
Vol 103 (12) ◽  
pp. 1315-1324
Keyword(s):  
Depressive Symptom ◽  
Health Literacy ◽  
Rural Communities ◽  
Long Term Care ◽  
Health Knowledge ◽  
Elderly Persons ◽  
Care Needs ◽  
Term Care ◽  
Study Results

Background: Factors related to long-term care needs have been studied widely, but there is limited research about the influence of health literacy on long-term care needs among the elderly in rural communities where the social context and care environment are uniquely different. Objective: To examine factors influencing long-term care needs among Thai elderly in rural communities. Materials and Methods: The present study used the cross-sectional design. The study sample included 477 elderly persons, who were members of the communities in Nakhon Ratchasima Province. Multi-stage random sampling was used to select participants. They were interviewed using the demographic and health information questionnaire, the Thai Geriatric Depression Scale (TGDS), the health literacy scale of Thai adults and long-term care needs questionnaire. The selected factors examined as independent variables included some demographic factors, depressive symptom, and health literacy. Results: The present study results revealed significant positive relationships existing between long-term care needs with age and depressive symptom, while negative relationships between income and health literacy were reported. A hierarchical multiple regression analysis indicated that four of nine determinants of long-term care needs: age, depressive symptom, health knowledge and understanding, and ability managing their health condition significantly predicted long-term care needs at a level of 18% (R² adjusted=0.18, p<0.001). Conclusion: The present study results showed associations between personal and health literacy factors with long-term care needs. These findings prove that it is vitally important for healthcare professionals to consider the rural elderly’s mental health status and health literacy when providing care and planning treatment. Keywords: Health literacy, Long-term care needs, Rural community

scholarly journals Neural methods for effective, efficient, and exposure-aware information retrieval

2021 ◽  
Vol 55 (1) ◽  
pp. 1-2
Author(s):  
Bhaskar Mitra
Keyword(s):  
Information Retrieval ◽  
Language Processing ◽  
Large Scale ◽  
Web Search ◽  
Real Life ◽  
Inverted Index ◽  
Information Need ◽  
Product Model ◽  
Performance Improvements ◽  
Deep Model

Neural networks with deep architectures have demonstrated significant performance improvements in computer vision, speech recognition, and natural language processing. The challenges in information retrieval (IR), however, are different from these other application areas. A common form of IR involves ranking of documents---or short passages---in response to keyword-based queries. Effective IR systems must deal with query-document vocabulary mismatch problem, by modeling relationships between different query and document terms and how they indicate relevance. Models should also consider lexical matches when the query contains rare terms---such as a person's name or a product model number---not seen during training, and to avoid retrieving semantically related but irrelevant results. In many real-life IR tasks, the retrieval involves extremely large collections---such as the document index of a commercial Web search engine---containing billions of documents. Efficient IR methods should take advantage of specialized IR data structures, such as inverted index, to efficiently retrieve from large collections. Given an information need, the IR system also mediates how much exposure an information artifact receives by deciding whether it should be displayed, and where it should be positioned, among other results. Exposure-aware IR systems may optimize for additional objectives, besides relevance, such as parity of exposure for retrieved items and content publishers. In this thesis, we present novel neural architectures and methods motivated by the specific needs and challenges of IR tasks. We ground our contributions with a detailed survey of the growing body of neural IR literature [Mitra and Craswell, 2018]. Our key contribution towards improving the effectiveness of deep ranking models is developing the Duet principle [Mitra et al., 2017] which emphasizes the importance of incorporating evidence based on both patterns of exact term matches and similarities between learned latent representations of query and document. To efficiently retrieve from large collections, we develop a framework to incorporate query term independence [Mitra et al., 2019] into any arbitrary deep model that enables large-scale precomputation and the use of inverted index for fast retrieval. In the context of stochastic ranking, we further develop optimization strategies for exposure-based objectives [Diaz et al., 2020]. Finally, this dissertation also summarizes our contributions towards benchmarking neural IR models in the presence of large training datasets [Craswell et al., 2019] and explores the application of neural methods to other IR tasks, such as query auto-completion.

scholarly journals Multi-GPU approach to global induction of classification trees for large-scale data mining

2021 ◽  
Author(s):  
Krzysztof Jurczuk ◽  
Marcin Czajkowski ◽  
Marek Kretowski
Keyword(s):  
Data Mining ◽  
Large Scale ◽  
Real Life ◽  
Population Based ◽  
Tree Structure ◽  
Global Approach ◽  
Data Parallel ◽  
Large Scale Data ◽  
The Impact ◽  
Scale Data

AbstractThis paper concerns the evolutionary induction of decision trees (DT) for large-scale data. Such a global approach is one of the alternatives to the top-down inducers. It searches for the tree structure and tests simultaneously and thus gives improvements in the prediction and size of resulting classifiers in many situations. However, it is the population-based and iterative approach that can be too computationally demanding to apply for big data mining directly. The paper demonstrates that this barrier can be overcome by smart distributed/parallel processing. Moreover, we ask the question whether the global approach can truly compete with the greedy systems for large-scale data. For this purpose, we propose a novel multi-GPU approach. It incorporates the knowledge of global DT induction and evolutionary algorithm parallelization together with efficient utilization of memory and computing GPU’s resources. The searches for the tree structure and tests are performed simultaneously on a CPU, while the fitness calculations are delegated to GPUs. Data-parallel decomposition strategy and CUDA framework are applied. Experimental validation is performed on both artificial and real-life datasets. In both cases, the obtained acceleration is very satisfactory. The solution is able to process even billions of instances in a few hours on a single workstation equipped with 4 GPUs. The impact of data characteristics (size and dimension) on convergence and speedup of the evolutionary search is also shown. When the number of GPUs grows, nearly linear scalability is observed what suggests that data size boundaries for evolutionary DT mining are fading.

scholarly journals Robots for Elderly Care in the Home: A Landscape Analysis and Co-Design Toolkit

2021 ◽  
Author(s):  
Gianluca Bardaro ◽  
Alessio Antonini ◽  
Enrico Motta
Keyword(s):  
Large Scale ◽  
Daily Life ◽  
Elderly Care ◽  
Real Life ◽  
Robotic Platform ◽  
Holistic View ◽  
Personal Assistants ◽  
Healthcare Interventions ◽  
The Impact ◽  
The Eu

AbstractOver the last two decades, several deployments of robots for in-house assistance of older adults have been trialled. However, these solutions are mostly prototypes and remain unused in real-life scenarios. In this work, we review the historical and current landscape of the field, to try and understand why robots have yet to succeed as personal assistants in daily life. Our analysis focuses on two complementary aspects: the capabilities of the physical platform and the logic of the deployment. The former analysis shows regularities in hardware configurations and functionalities, leading to the definition of a set of six application-level capabilities (exploration, identification, remote control, communication, manipulation, and digital situatedness). The latter focuses on the impact of robots on the daily life of users and categorises the deployment of robots for healthcare interventions using three types of services: support, mitigation, and response. Our investigation reveals that the value of healthcare interventions is limited by a stagnation of functionalities and a disconnection between the robotic platform and the design of the intervention. To address this issue, we propose a novel co-design toolkit, which uses an ecological framework for robot interventions in the healthcare domain. Our approach connects robot capabilities with known geriatric factors, to create a holistic view encompassing both the physical platform and the logic of the deployment. As a case study-based validation, we discuss the use of the toolkit in the pre-design of the robotic platform for an pilot intervention, part of the EU large-scale pilot of the EU H2020 GATEKEEPER project.

scholarly journals Factors impacting hospital avoidance program utilisation in the care of acutely unwell residential aged care facility residents

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Luke Testa ◽  
Tayhla Ryder ◽  
Jeffrey Braithwaite ◽  
Rebecca J. Mitchell
Keyword(s):  
Care Facility ◽  
Aged Care ◽  
Residential Aged Care ◽  
Nurse Specialist ◽  
Structured Interviews ◽  
Care Needs ◽  
Aged Care Facility ◽  
Enabling Factors ◽  
Clinical Nurse ◽  
Residential Aged Care Facility

Abstract Background An existing hospital avoidance program, the Aged Care Rapid Response Team (ARRT), rapidly delivers geriatric outreach services to acutely unwell or older people with declining health at risk of hospitalisation. The aim of the current study was to explore health professionals’ perspectives on the factors impacting ARRT utilisation in the care of acutely unwell residential aged care facility residents. Methods Semi-structured interviews were conducted with two Geriatricians, two ARRT Clinical Nurse Consultants, an ED-based Clinical Nurse Specialist, and an Extended Care Paramedic. Interview questions elicited views on key factors regarding care decisions and care transitions for acutely unwell residential aged care facility residents. Thematic analysis was undertaken to identify themes and sub-themes from interviews. Results Analysis of interviews identified five overarching themes affecting ARRT utilisation in the care of acutely unwell residents: (1) resident care needs; (2) family factors; (3) enabling factors; (4) barriers; and (5) adaptability and responsiveness to the COVID-19 pandemic. Conclusion Various factors impact on hospital avoidance program utilisation in the care of acutely unwell older aged care facility residents. This information provides additional context to existing quantitative evaluations of hospital avoidance programs, as well as informing the design of future hospital avoidance programs.

scholarly journals Understanding what matters most to patients in acute care in seven countries, using the flash mob study design

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Eva S. van den Ende ◽  
◽  
Bo Schouten ◽  
Marjolein N. T. Kremers ◽  
Tim Cooksley ◽  
...  
Keyword(s):  
Acute Care ◽  
Patient Perspective ◽  
Large Scale ◽  
Healthcare Professionals ◽  
Well Being ◽  
Good Health ◽  
Care Needs ◽  
Patient Centred Care ◽  
Trial Register ◽  
What Matters

Abstract Background Truly patient-centred care needs to be aligned with what patients consider important, and is highly desirable in the first 24 h of an acute admission, as many decisions are made during this period. However, there is limited knowledge on what matters most to patients in this phase of their hospital stay. The objective of this study was to identify what mattered most to patients in acute care and to assess the patient perspective as to whether their treating doctors were aware of this. Methods This was a large-scale, qualitative, flash mob study, conducted simultaneously in sixty-six hospitals in seven countries, starting November 14th 2018, ending 50 h later. One thousand eight hundred fifty adults in the first 24 h of an acute medical admission were interviewed on what mattered most to them, why this mattered and whether they felt the treating doctor was aware of this. Results The most reported answers to “what matters most (and why)?” were ‘getting better or being in good health’ (why: to be with family/friends or pick-up life again), ‘getting home’ (why: more comfortable at home or to take care of someone) and ‘having a diagnosis’ (why: to feel less anxious or insecure). Of all patients, 51.9% felt the treating doctor did not know what mattered most to them. Conclusions The priorities for acutely admitted patients were ostensibly disease- and care-oriented and thus in line with the hospitals’ own priorities. However, answers to why these were important were diverse, more personal, and often related to psychological well-being and relations. A large group of patients felt their treating doctor did not know what mattered most to them. Explicitly asking patients what is important and why, could help healthcare professionals to get to know the person behind the patient, which is essential in delivering patient-centred care. Trial registration NTR (Netherlands Trial Register) NTR7538.

scholarly journals Stacked Community Prediction: A Distributed Stacking-Based Community Extraction Methodology for Large Scale Social Networks

2021 ◽  
Vol 5 (1) ◽  
pp. 14
Author(s):  
Christos Makris ◽  
Georgios Pispirigos
Keyword(s):  
Social Networks ◽  
Graph Partitioning ◽  
Large Scale ◽  
Real Life ◽  
Information Networks ◽  
Digital Marketing ◽  
Partitioning Problems ◽  
Iterative Solutions ◽  
Community Extraction ◽  
Stability And Accuracy

Nowadays, due to the extensive use of information networks in a broad range of fields, e.g., bio-informatics, sociology, digital marketing, computer science, etc., graph theory applications have attracted significant scientific interest. Due to its apparent abstraction, community detection has become one of the most thoroughly studied graph partitioning problems. However, the existing algorithms principally propose iterative solutions of high polynomial order that repetitively require exhaustive analysis. These methods can undoubtedly be considered resource-wise overdemanding, unscalable, and inapplicable in big data graphs, such as today’s social networks. In this article, a novel, near-linear, and highly scalable community prediction methodology is introduced. Specifically, using a distributed, stacking-based model, which is built on plain network topology characteristics of bootstrap sampled subgraphs, the underlined community hierarchy of any given social network is efficiently extracted in spite of its size and density. The effectiveness of the proposed methodology has diligently been examined on numerous real-life social networks and proven superior to various similar approaches in terms of performance, stability, and accuracy.

Conservation of animal genetic resources: approaches and technologies for in situ and ex situ conservation

2008 ◽  
Vol 42 ◽  
pp. 71-85 ◽  
Author(s):  
J.A. Woolliams ◽  
O. Matika ◽  
J. Pattison
Keyword(s):  
Rural Communities ◽  
Genetic Resources ◽  
Large Scale ◽  
Production Systems ◽  
Regional Distribution ◽  
Livestock Production ◽  
Ex Situ ◽  
Animal Genetic Resources ◽  
The Face ◽  
Livestock Products

SummaryLivestock production faces major challenges through the coincidence of major drivers of change, some with conflicting directions. These are:1. An unprecedented global change in demands for traditional livestock products such as meat, milk and eggs.2. Large changes in the demographic and regional distribution of these demands.3. The need to reduce poverty in rural communities by providing sustainable livelihoods.4. The possible emergence of new agricultural outputs such as bio-fuels making a significant impact upon traditional production systems.5. A growing awareness of the need to reduce the environmental impact of livestock production.6. The uncertainty in the scale and impact of climate change. This paper explores these challenges from a scientific perspective in the face of the large-scale and selective erosion of our animal genetic resources, and concludes thai there is a stronger and more urgent need than ever before to secure the livestock genetic resources available to humankind through a comprehensive global conservation programme.

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