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With the integration of connected devices, artificial intelligence, and heterogeneous networks in IoT-driven cyber-physical systems, our society is evolving as a smart, automated, and connected community. In such dynamic and distributed environments, various operations are carried out considering different contextual factors to support the automation of connected devices and systems. These devices often perform long-lived operations or tasks (referred to as activities) to fulfill larger goals in the connected environment. These activities are usually mutable (change states) and interdependent. They can influence the execution of other activities in the ecosystem, requiring active and real-time monitoring of the entire connected environment. Traditional access control models are designed to take authorization decisions at the time of access request and do not fit well in dynamic and connected environments, which require continuous active checks on dependent and mutable activities. Recently, a vision for activity-centric access control (ACAC) was proposed to enable security modeling and enforcement from the perspective and abstraction of interdependent activities. The proposed ACAC incorporates four decision parameters: Authorizations (A), oBligations (B), Conditions (C), and activity Dependencies (D) for an object agnostic continuous access control in smart systems. In this paper, we take a step further towards maturing ACAC by focusing on the mutability of activities (the ability of changing states of activities), activity dependencies (D) and developing a family of formal mathematically grounded models, referred to as ACAC D . We propose six practically suitable sub-models for ACAC D to support the state transition of a mutable activity incorporating the dependent activities' state-check and state-update procedures. These formal models consider the real-time mutability of activities as a critical factor in resolving active dependencies among various activities in the ecosystem. Activity dependencies can form a chain where it is possible to have dependencies of dependencies. In ACAC, we also consider the chain of dependencies while handling the mutability of an activity. We highlight the challenges (such as multiple dependency paths, race conditions, circular dependencies, and deadlocks) while dealing with a chain of dependencies, and provide solutions to resolve these challenges. We also present a proof of concept implementation of our proposed ACAC D models with performance analysis for a smart farming use case. This paper addresses the formal models' intended behavior while supporting activities' dependencies. Specifically, it focuses on developing and categorizing mathematically grounded activity dependencies into various ACAC sub-models without formal policy specification and analysis of theoretical complexities, which are intentionally kept out of the scope of this work. [ABSTRACT FROM AUTHOR]

The robustness of components/products/systems is a concern for both the company that sells them and the consumers who use them. Failure Modes and Effect Analysis (FMEA) which has evolved over 60 years, is a powerful and effective risk identification tool for both design and manufacturing, often combined with Multiple Criteria Decision-Making methods to increase its utility. However, most previous FMEA studies have neglected the interdependence of the failure modes. To address this issue, this study develops a novel method, the TEchnique for Defining the Influential Relationship of Failure Modes, to determine the risk prioritization of the failure modes. The interaction among failure modes is effectively identified and incorporated into the model. The primary analysis procedure can be divided into three parts: (i) the assessment of the initial risk scores of the failure modes; (ii) the definition of the degree of interdependence among the failure modes; and (iii) the integration of the final risk scores based on dependency. The model is used to conduct a case study for a multinational manufacturer of switch mode power supplies as a demonstration case. The practicality of the proposed model was validated through model comparisons and expert feedback. The results show that "an unstable output voltage", "no power-good signal", "recession in efficiency", "burning out of components", and "the cooling fan does not operate" are the top five risky failure modes. The research findings can be used as the basis for improvement strategies in R&D design and by quality assurance departments to enhance product reliability. [ABSTRACT FROM AUTHOR]

The objective of this study is to explore the association between community cohesion and dependency among elderly people. This is a community-based cross-sectional study, and data were obtained from a face-to-face questionnaire survey including 2017 elderly people aged ≥ 60 years from 27 locations in China. The community cohesion was measured by the Neighborhood Cohesion Inventory. Logistic regression models were created to evaluate the association between community cohesion and dependency, and stratified logistic regression analyses were performed to identify the association of important community healthcare service resources with community cohesion at different income levels. The results of the logistic regression analyses show a significant positive association between community cohesion and dependency after adjusting for sociodemographic and health-related variables, and the odds ratio (OR) was 2.42 (95%CI:1.43–4.08). Logistic regression analyses showed that the high community cohesion for the low-income group was associated with the satisfaction with the community physicians' technical expertise, daycare service, rehabilitation equipment rental services, and health records management. In the high-income group, community cohesion showed a positive association with the satisfaction with the community physicians' attitude, regular health assessment, and chronic disease care service. Community cohesion was positively associated with dependency among elderly people. Findings indicate that community cohesion may be an important accessible resource for elderly people with dependency, and the targeted provision of health resources and services are the most effective strategies to enhance community cohesion. [ABSTRACT FROM AUTHOR]

The usage of digital devices has increased rapidly in recent times due to the expansion of online learning platforms, leading to greater reliance on them. As a result, people forget simple information, dates, and appointments that might lead to digital amnesia. Hence, we aimed to develop and validate a digital amnesia scale (DAS). The study was carried out in two studies. In the first study, we collected data from 616 college students to examine the factor structure of the model and its underlying dimensions for a large pool of items. These analyses showed that the scale formed a three-dimensional structure: digital distraction, digital dependency, and digital detox. In the second study, we collected data from 383 college students to confirm the three-factor structure of the DAS. A satisfactory level of reliability was demonstrated by McDonald's ω value for the dimensions. The test–retest reliability was found to be 0.76. The DAS had satisfactory convergent and discriminant validity. This scale could be useful for both researchers and educators to assess digital amnesia among college students. [ABSTRACT FROM AUTHOR]

This study aimed to explore the association between dependency and cognitive function among older adults. A combined cross-sectional and longitudinal study was conducted in 26 locations in China. A total of 1160 participants aged ≥ 60 years were selected using a complex multistage sampling design, and 152 participants completed data collection after one year follow-up observation. A questionnaire was administered by face-to-face interviews. Dependency was measured using the standardized Chinese version of the Minnesota Multiphasic Personality Inventory-II. Logistic regression analysis was conducted to assess the association between dependency and cognitive function. Cox proportional hazards analysis was performed to identify causality between cognition function and dependency. The results of logistic regression analysis showed that the orientation and outdoor instrumental activities of daily living (IADL) domains were significantly associated with dependency, with odds ratios of 1.45 (95% CI, 1.26–1.67; p < 0.001) and 1.16 (95% CI, 1.06–1.26; p < 0.001), respectively. In the Cox proportional hazards analysis, the DASC-21 score was significantly associated with dependency, with hazard ratio of 1.32 (95% CI, 1.03–1.69). The causality between cognition impairment and dependency was identified, and the orientation and outdoor IADL domains were significantly associated with dependency. [ABSTRACT FROM AUTHOR]

Copyright of Berliner Journal für Soziologie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

While Free and Open Source (F/OSS) coding has traditionally been described as a separate commons linked to values of openness and sharing, recent research suggests an increasing integration of private corporations into F/OSS practices, blurring the boundaries between F/OSS and commodified coding. However, there is a dearth of empirical, and especially quantitative studies exploring this phenomenon. To address this gap, we model the power dynamics and infrastructural aspects of software production within GitHub, a central hub for F/OSS development, using a large-scale, directed network. Using various network statistics, we detect the ecosystem's most impactful actors and find a nuanced picture of the influence of individuals, open source organizations, and private corporations in F/OSS practices. We find that the majority of public repositories on GitHub depend on a small core of specialized repositories and users. In accordance with expectations, individuals and open source organizations are more prevalent in this core of elite GitHub users, however, we also find a significant amount of private organizations with an indirect, yet consistent influence within GitHub. In addition, we find that directly influential individuals tend to facilitate sponsorship methods more often than indirectly or non-influential individuals. Our research highlights a hybridization of F/OSS and sheds light on the complex interplay between influence, power, and code production in the multi-language dependency ecosystem of GitHub. [ABSTRACT FROM AUTHOR]

Background: Tobacco is consumed mainly as smoking or smokeless tobacco [SLT]. "Smokeless tobacco" (SLT) term is used for the consumption of tobacco mixed with other constituents in form of chewing, spitting and dipping. Consumers of smokeless tobacco chew the products and spit out the juice that builds up in oral cavity which leads to various malignant and pre malignant lesions of oral cavity. Methods: Descriptive observational study was conducted in the city of Jodhpur through department of ENT, Head & Neck Surgery, Dr. SN medical college, Jodhpur. Results: Male to female ratio of smokeless tobacco usage was almost same. Increasing age was associated with occurrence of oral lesions and 43% patients developed oral lesions in the group > 64 yrs of age. Duration was another associating factor and 66% developed symptoms within < 10 years of usage. Oral submucous fibrosis is the most common lesion. Malignant lesions were seen in 0.3% cases. Around 78% cases developed dependency. Diabetic patients were seen more prone to development of oral lesions. Conclusions: Development of lesions in the oral cavity by smokeless tobacco depends on various factors such as quantity of tobacco usage per day, place of putting tobacco and duration. Awareness regarding its fatal effects and timely diagnosis and management can save many lives. [ABSTRACT FROM AUTHOR]

Personality vulnerabilities (i.e., dependency and self-criticism) have been established as critical risk factors for psychopathology in general and for depression in particular. However, research does not address ways of treating those who score high on both dependency and self-criticism, or mixed-vulnerability individuals. To benefit these individuals, we developed an online, group-administered, multi-component positive psychology intervention (MPPI) and tested its effects and mechanisms. Participants (N = 70) were randomly assigned to either receive the MPPI or an active placebo control. The six-session intervention took place over three weeks, and measures were completed at baseline, midtest, posttest, and one-month follow-up stages. Compared to the control condition, the MPPI significantly attenuated self-criticism and dependency for up to one month. The intervention also decreased depression and promoted self-esteem and subjective well-being (SWB). Parallel mediation analyses revealed that lower self-criticism mediated the intervention’s effects on depression, self-esteem, and SWB, while lower dependency mediated effects on self-esteem. This study highlights how an MPPI can decrease personality vulnerability in mixed-vulnerability individuals, and how this change can have further positive effects. [ABSTRACT FROM AUTHOR]

Abstract Meaning Representation (AMR) parsing aims to translate sentences to semantic AMR graphs and has recently been empowered by pre-trained Transformer models (e.g., BART). We argue that explicitly encoding syntactic knowledge is beneficial for AMR parsing, since the AMR graph of a sentence has similar substructures to those of its corresponding syntactic dependency tree. However, the effect of integrating syntactic dependency knowledge into pre-trained Transformer-based AMR parsers, as well as how to better infuse them, remains unclear. Therefore, we conduct a systematic study to explore the utility of incorporating dependency trees into pre-trained Transformers for AMR parsing. Specifically, we propose and compare two distinct syntax-infused AMR parsers for injecting dependency structures: the Syntax-Aware Self-Attention (SASA) network, which extends the self-attention mechanism of the Transformer encoder with syntax-aware constraints, and the Syntax-Aware Graph Attention (SAGAT) network, which augments the pre-trained Transformer by encoding the syntax with a graph attention network. Extensive experiments conducted on different benchmarks demonstrate that both proposed syntax-infused AMR parsers achieve remarkable and explainable improvements. Specifically, SASA significantly outperforms the strong baseline by up to 1.2% and 0.9% Smatch scores on the AMR2.0 and AMR3.0 datasets, respectively. Furthermore, the proposed models alleviate the performance degradation caused by long-distance dependencies (LDDs), particularly in complex and long sentences. In addition, our proposed models achieve a new state-of-the-art performance level on out-of-distribution and low-resource benchmarks. The source code is available at https://github.com/Hi-ANONYMOUS/Syntax-Aware_AMR. [ABSTRACT FROM AUTHOR]

Dependency is a common personality disorder among elderly people, and there is currently no good evidence to recommend an intervention strategy for this disorder. This study aimed to assess the risk factors of dependency on the basis of a social ecological model. This is a community-based cross-sectional study. A total of 1276 participants aged ≥ 60 years were selected through a complex multistage sampling design from 27 locations in China and found eligible to participate in the study. All data were collected using questionnaires by face-to-face interviews. Multiple linear regression analysis was used to identify the association between dependency and related risk factors. Logistic regression analysis was conducted to assess the protective factors of dependency among individuals with high risk factors of dependency. The results of multiple linear regression analysis showed that the individual, family, community, and social factors were significantly associated with dependency. Logistic regression analysis showed that good social connection and social support were the most important protective factors for individuals with a high risk of dependency. We identify that dependency is associated with protection and risk factors from the individual, family, community, and social factors among elderly individuals. Based on resilience theory, our results suggest that using a social ecological model to assess the risk factors of dependency may be an effective way to develop intervention strategies of dependency among older people. [ABSTRACT FROM AUTHOR]

Differential access to life-saving COVID-19 vaccines reveals the inequitable distribution of wealth and power in the global system. While several countries have developed homegrown vaccines to avoid being priced out of markets dominated by transnational drug companies, Brazil—a country with a significant research and pharmaceutical base—lagged behind those of other middle-income countries. Why? This paper blends insights from dependency theory and the theory of global capitalism to demonstrate how political coalitions, leadership, and normative frameworks negatively affect state capacity and technological development. First, austerity in public investment in research, development, and innovation prior to and during the pandemic limited the amount of resources necessary to create homegrown vaccine candidates. Second, political leadership informed by science denialism did not prioritize the development of vaccines and even discouraged their use. The analysis of vaccine development in Brazil reveals that having a pharmaceutical base and strong leadership committed to scientific principles and backed by a political coalition seeking to expand social democratic rights play a vital role in developing treatments and responding to health crises. [ABSTRACT FROM AUTHOR]

In this study, a pseudo-maximization by parts method is introduced by developing the maximization by parts algorithm for the parameter estimation of pseudo-copula regression models. Sub- and main score equations are obtained from the pairwise log-likelihood function and solved by the proposed iterative algorithm. The pseudo-maximization by parts algorithm is an iterative algorithm to avoid having to calculate the second-order derivative of the full log-likelihood function as maximization by parts algorithm. Instead of the Gaussian copula function in maximization by parts algorithm, the pseudo-Gaussian copula function is included in the new algorithm. The mean square errors of the estimators found by the maximization by parts algorithm and the pseudo-maximization by parts algorithm are compared using real Turkish comprehensive insurance data taken from the Turkish Insurance Information and Monitoring Center for the year 2017, and it is notable that the proposed algorithm provided better results in terms of having lower errors. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) printing has been considered a sustainable and competitive tool for manufacturing products and their components in numerous industries. However, since there are more and more available 3D printing facilities providing unequal services, choosing a suitable 3D printing facility remains a challenging task to manufacturers. In addition, a decision maker also needs to make negotiation between selection criteria that may be conflicting and dependent. To overcome this challenge, this study proposes an evolving fuzzy big data analytics approach. In the proposed methodology, the modified evolving fuzzy assessment (MEFA) method is devised to improve the accuracy of deriving the fuzzy priorities of criteria efficiently. Subsequently, to remove the dependency between criteria, PCA is applied. Finally, the dependency-removed fuzzy technique for order preference via similarity to ideal solutions (FTOPSIS) (Dr-FTOPSIS) is proposed to assess and compare the 3D printing facilities under consideration. The evolving fuzzy big data analytics approach has been applied to a real case of choosing suitable 3D printing facilities in a prosthetic limb supply chain. The experimental results supported the effectiveness of the proposed methodology in improving the derivation process and making a more reasonable choice of suitable 3D printing facilities. The MEFA approach increased the efficiency of deriving fuzzy priorities by 80%. In addition, the overall performance of the best 3D printing facility recommended by the proposed methodology was about 7% better than those recommended by the existing methods. [ABSTRACT FROM AUTHOR]

This paper discusses the design of a novel hybrid bioinspired model for task-and-VM-dependency and deadline aware scheduling via dual service level agreements. The model uses a combination of grey wolf optimization with the league championship algorithm, to perform efficient scheduling operations. These optimization techniques model a fitness function that incorporates task make-span, task deadline, mutual dependencies with other tasks, the capacity of VMs, and energy needed for scheduling operations. This assists in improving its scheduling performance for multiple use cases. To perform these tasks, the model initially deploys a task-based service level agreement (SLA) method, which assists in enhancing task and requesting-user diversity. This is followed by the design of a VM-based SLA model, which reconfigures the VM's internal characteristics to incorporate multiple task types. The model also integrates deadline awareness along with task-level and VM-level dependency awareness, which assists in improving its scheduling performance under real-time task and cloud scenarios. The proposed model is able to improve cloud utilization by 8.5%, increase task diversity by 8.3%, reduce the delay needed for resource provisioning by 16.5%, and reduce energy consumption by 9.1%, making for a wide variety of real-time cloud deployments. [ABSTRACT FROM AUTHOR]

Universal vulnerability provides an alternative to a rights-based and social contract model for state responsibility by contextualizing the individual and revealing the ways in which we are all inherently and dynamically dependent on society and others throughout the life-course. Beginning from the body as an ontological concept, vulnerability theory shows the fallacy of the current obsession in legal and political theory with rationality, individual liberty, and autonomy as measures for assessing social justice. It compels us to ask different questions and emphasize different principles and values than current liberal legal modes of reasoning about state responsibility. [ABSTRACT FROM AUTHOR]

Copyright of Forensische Psychiatrie, Psychologie, Kriminologie is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Postsecondary institutions' responses to COVID-19 are a topic of immediate relevance. Emergent research suggests that partisanship was more strongly linked to institutions offering in-person instruction for Fall 2020 than was COVID-19. Using data from the College Crisis Initiative and a multiple group structural equation modeling approach, we tested the relationships between our outcome of interest (in-person instruction in Fall 2020) and state and county sociopolitical features, state and county COVID-19 rates, and state revenue losses. Our full-sample model suggested that County Political Preferences had the strongest association with in-person instruction, followed by Pandemic Severity and State Sociopolitical Features. Because institutional sectors may be uniquely sensitive to these factors, we tested our models separately on 4-year public, 4-year private, and 2-year public and 2-year private institutions. State Sociopolitical Features were significantly related to in-person instruction for 4-year private and 2-year public institutions but were strongest for 4-year public institutions. For 4-year private and 2-year public institutions, County Political Preferences' effect sizes were 2–3 times stronger than effects from State Sociopolitical Features. Pandemic Severity was significantly, negatively related to in-person instruction for 4-year private and 2-year public institutions–similar in magnitude to State Sociopolitical Features. Our analysis revealed that COVID-19 played a stronger role in determining in-person instruction in Fall 2020 than initial research using less sophisticated methods suggested—and while State Sociopolitical Features may have played a role in the decision, 4-year private and 2-year public institutions were more sensitive to county-level preferences. [ABSTRACT FROM AUTHOR]

Threat models and attack graphs have been used more than 20 years by enterprises and organizations for mapping the actions of potential adversaries, analyzing the effects of vulnerabilities and visualizing attack scenarios. Although efficient when describing high-level interactions in simpler enterprise networks, they fall short in modern decentralized systems, especially in microservices architectures and multi-cloud environments with increased complexity and interactions. Most current research focuses on automatically generating attach graphs for such complex environments and deals with scaling and mapping issues, while neglecting to address the overall complexity of actually analyzing and extracting useful information from these overly convoluted models. In this paper, we present a method for automatically analyzing complex attack graphs both in microservices-based and multi-cloud infrastructures. We piggyback on previous research to automatically create complex attack graphs for such enterprise networks and use it as input to relate microservices, virtual system states and cloud services (represented as graph nodes) with prioritization algorithms that use mathematical graph series and group clustering. Our tool prioritizes existing vulnerabilities, analyzes the effect of system states to the overall network and proposes which system states, vulnerabilities and configurations have the biggest overall risk to the ecosystem, while taking into consideration every potential sub-attack path and subliminal path on an attack graph. We test the efficiency of our software on two real-world use cases: one multi-cloud enterprise network and a NetFlixOSS microservices Docker architecture. [ABSTRACT FROM AUTHOR]

Copyright of Organisationsberatung, Supervision, Coaching is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Understanding human facial expressions is one of the key steps towards achieving human–computer interaction. Owing to the anatomic mechanism that governs facial muscular interactions, there exist powerful dependencies between expressions and action units (AUs) that are useful for exploiting such rules of knowledge to guide the model learning process. However, they have not yet been represented directly and integrated into a network. In this study, we propose a novel method for facial expressions and AUs recognition based on their dependencies on graph convolutional network. First, we train the conditional generative adversarial network to filter out identity information and extract expression information through a de-expression learning procedure. Thereafter, we apply graph convolutional network to represent dependency laying among AU nodes and embed the nodes by dividing the expression component into multi patches, corresponding to the AU-related regions. Finally, we use prior knowledge matrices to represent the dependencies between expressions and AUs and subsequently integrate them into a loss function to constrain the model. The results of our experiments indicate that such representation is effective for improving the recognition rate. They also reveal that our work achieves better performance than several popular approaches. [ABSTRACT FROM AUTHOR]

As they age, many people are afraid that they might become a burden to their families and friends. In fact, fear of being a burden is one of the most frequently cited reasons for individuals who request physician aid in dying. Why is this fear so prevalent, and what are the issues underlying this concern? I argue that perceptions of individual autonomy, dependency, and dignity all contribute to the fear of becoming a burden. However, this fear is misplaced; common conceptions of these values should be re-framed and re-examined. Practices that support a more community-centered type of autonomy can be found in dependency and dignity. This paper offers some practical examples of how to address common end-of-life situations that may cause anxiety to patients who are worried about being a burden. These practices include discussing expectations, both for care and how the relationship among the participants might change, and modeling respectful caregiving behaviors. Most difficult of all, though, includes cultural and societal attitude changes so that people recognize the good in receiving care and get used to the idea that they do not need to do anything to be valuable. [ABSTRACT FROM AUTHOR]

Purpose: Osteoarthritis (OA) pain is among the leading causes of disability worldwide in older people. Since its prevalence is growing in aging, a significant burden for society is expected. This work ascertained whether level of disability in self-reported functioning differs by pain severity and usual analgesic treatment among older OA patients in Spain. Methods: The Spanish-National-Health-Survey, a large, nationally representative, cross-sectional general health survey including 23,089 persons, was analyzed. Patients aged 65 + years with a self-reported physician OA diagnosis were classified according to severity of pain (no/mild, moderate or severe pain) and treated or untreated with analgesia. Assessment of function included basic and instrumental activities-of-daily-living (BADL, IADL), mental, social, and cognitive functions, scored on a 0% (no limitation) to 100% (complete limitation) standardized metric. Caregiver need for BADL and IADL was also recorded. Results: A total of 3526 patients were analyzed (women 73.3%; age 77.4 [SD: 7.5]). Adjusted functioning scores showed significant association with pain severity, and for BADL, IADL and social function. Patients with severe pain and treated with analgesia had higher limitation scores, ranging on average between 31.5% on BADL, 34.1% on IADL, 45.0% on mental, 42.2% on social, and 23.4% in cognitive domain. The proportions of patients needing a caregiver for BADL (43.4%) and IADL (56.2%) were also the highest in patients with severe pain and treated with analgesia. Conclusions: Regardless of usual utilization of analgesics, the severity of pain seemed to be the major determinant of functional impairment, and caregiving need, in all domains of functioning in older OA patients in Spain. Existing treatment strategies are analgesics based and do not meet patient needs for adequate pain management. [ABSTRACT FROM AUTHOR]

Key summary points: Aim: To evaluate sarcopenia risk in hospitalized older patients. Findings: The percentage of patients at risk of sarcopenia defined by the SARC-F was 48.8%. Sarcopenia risk was associated with unfavorable health care outcomes including dependency, malnutrition, and dysphagia. Message: Sarcopenia risk is related with unfavorable outcomes in hospitalized patients and it is important to recognize sarcopenia at an early stage and to prevent its progression, before dependency develops. Purpose: To investigate the risk of sarcopenia in hospitalized older patients and to assess the associations between sarcopenia risk and health care outcomes including dependency, malnutrition, and dysphagia. Methods: This multicenter cross-sectional study was a part of the annual National Prevalence Measurement of Quality of Care (LPZ) in Turkey. Hospitalized patients age 65 and older were included in the study. The SARC-F was used to assess risk of sarcopenia. Dependency was appraised according to the Care Dependency Scale (CDS). Nutritional status was established with respect to the Malnutrition Universal Screening Tool (MUST). Dysphagia was screened by two structured questions. Results: A total of 492 patients were included in the analysis. Two hundred and forty patients (48.8%) were at risk of sarcopenia. Sarcopenia risk was more prevalent among women (p = 0.007) and patients with risk of sarcopenia were older (p < 0.001). Hospital stay was longer and malnutrition and dysphagia were more prevalent in patients with sarcopenia risk than without (all p < 0.001). All nutritional interventions were applied mostly to patients with sarcopenia risk than without. In multivariate analysis, advanced age (OR: 1.068, CI 1.032–1.104, p < 0.001), female gender (OR: 2.414, CI 1.510–3.857, p < 0.001), and dependency (OR: 5.022, CI 2.922–8.632, p < 0.001) were independently associated with sarcopenia risk. Conclusions: Sarcopenia risk is related with unfavorable outcomes in hospitalized patients. Primarily older female patients are at risk for sarcopenia. It is important to recognize sarcopenia at an early stage and to prevent its progression, before dependency develops. The SARC-F may be a useful tool for screening sarcopenia risk in hospitalized patients. [ABSTRACT FROM AUTHOR]

Population ageing is one of the most significant challenges facing the world in the twenty-first century. Furthermore, people aged over 65 typically have a level of income below the national average, but the homeownership rate among those in this age group tends to be high. Equity release schemes, specifically reverse mortgages, can help cover increased care costs and ensure a reasonable level of income, thus guaranteeing the well-being of older adults. However, this product has not been greatly developed by private entities. If the State were to implement this financial operation through public administrations, it could obtain homes that might then be included in public housing stocks. Thus, our paper aims to contribute to the literature on government-based reverse mortgage systems. Under our assumptions, the results showed that if 313,833 homes were reverse-mortgaged, the investment by the public administration would be around 0.73% GDP, with this being a feasible proposal. This work helps to create alternative methods to finance problems related with the ageing of societies from a public perspective. [ABSTRACT FROM AUTHOR]

Introduction: To determine the disease burden and costs in moderate-to-severe chronic osteoarthritis (OA) pain refractory to standard-of-care treatment in the Spanish National Health System (NHS). Methods: Ancillary analysis of the OPIOIDS real-world, non-interventional, retrospective, 4-year longitudinal study including patients aged at least 18 years with moderate-to-severe chronic OA pain refractory to standard-of-care with sequential NSAIDs plus opioids. Burden assessment included measurement of analgesia, cognitive functioning, basic activities of daily living, severity and frequency of comorbidities, and all-cause mortality. Costs accounted for healthcare resource utilization and related costs (year 2018). Results: Records of 13,317 patients were analyzed; 68.9 (14.7) years old, 71.3% (70.5–72.1%) women, 58.1% refractory to NSAID plus weak opioid and 41.9% to NSAID plus strong opioid, accounting for 10.7% (10.5–10.8%) of patients with chronic OA pain. Mean number of comorbidities was 2.9 (1.8) and its severity was 1.8 (1.7). Pain decreased by 0.9 points (12.2%) and cognitive declined by 2.3 points (9.1%, with 4.3% more patients with cognitive deficit) and dependency worsened by 0.4 points (0.5%, with 2.3% more patients with severe-to-total dependence) over a mean treatment period of 188.6 (185.4–191.8) days on NSAIDs followed by 400.6 (393.7–407.5) days on opioids. The adjusted mortality rate was higher in patients with OA taking NSAID plus strong opioids; hazard ratio 1.44 (1.26–1.65; p < 0.001). The 4-year healthcare cost was €7350/patient (€7193–7507 or €1838/year) and was higher in those taking strong versus weak opioids; €9886 (€9608–10,164, €2472/year) vs. €5519 (€5349–5689, €1380/year), p < 0.001. Analgesia cost (16.0% of total cost, 70.2% opioids) was higher with strong versus weak opioids, 19.6% vs. 11.3%, p < 0.001. Conclusions: In routine clinical practice in Spain, patients with moderate-to-severe chronic OA pain refractory to standard analgesic treatment with NSAIDs plus opioids reported modest reductions in pain, while presenting a considerable burden of comorbidities, cognitive impairment, and dependency. Healthcare costs significantly increased for the NHS particularly with NSAIDs plus strong opioids. [ABSTRACT FROM AUTHOR]

Background and purpose: Current demographic changes indicate that more people will be care-dependent due to increasing life expectancy. Little is known about impact of preexisting dependency on stroke outcome after endovascular treatment (EVT). Methods: We compared prospectively collected baseline and outcome data of previously dependent vs. independent stroke patients (prestroke modified Rankin Scale score of 3–5 vs. 0–2) treated with EVT. Outcome measures were favorable 3-month outcome (mRS ≤ 3 for previously dependent and mRS ≤ 2 for independent patients, respectively), death and symptomatic intracranial hemorrhage (sICH). Results: Among 1247 patients, 84 (6.7%) were dependent before stroke. They were older (81 vs. 72 years of age), more often female (61.9% vs. 46%), had a higher stroke severity at baseline (NIHSS 18 vs. 15 points), more often history of previous stroke (32.9% vs. 9.1%) and more vascular risk factors than independent patients. Favorable outcome and mortality were to the disadvantage of independent patients (26.2% vs. 44.4% and 46.4% vs. 25.5%, respectively), whereas sICH was comparable in both cohorts (4.9% vs. 5%). However, preexisting dependency was not associated with clinical outcome and mortality after adjusting for outcome predictors (OR 1.076, 95% CI 0.612–1.891; p = 0.799 and OR 1.267, 95% CI 0.758–2.119; p = 0.367, respectively). Conclusion: Our study underscores the need for careful selection of care-dependent stroke patients when considering EVT, given a less favorable outcome observed in this cohort. Nonetheless, EVT should not systematically be withheld in patients with preexisting disability, since prior dependency does not significantly influence outcome. [ABSTRACT FROM AUTHOR]

Oropharyngeal dysphagia has features of geriatric syndromes and is strongly associated with sarcopenia. In this cross-sectional study, we aimed to evaluate the association between dysphagia and sarcopenia, in a practical way, accompanied by comprehensive geriatric assessment. Dysphagia and sarcopenia were defined by the EAT-10 and SARC-F questionnaires, respectively. Cognition and mood, was evaluated by the Mini-mental State Examination (MMSE) and Geriatric Depression Scale (GDS), respectively. Physical performance was assessed by the Timed up and Go Test (TUG) and muscle strength was determined by Hand Grip Strength (HGS). Functionality was stated by Katz and Lawton Indexes. Serum levels of hemoglobin, triglyceride, albumin, and total cholesterol were recorded. A total of 512 (151 male/361 female) patients age 60 and older were included in the study. Prevalences of dysphagia and sarcopenia were 23% and 40.6%, respectively. In multivariate analysis sarcopenia (OR:2.596, p = 0.008), depressive symptoms (OR:1.115, p < 0.001), and lower KATZ scores (OR:0.810, p = 0.036) were independently related with dysphagia. Dysphagic patients with sarcopenia had lower scores on the Katz and Lawton scales (p < 0.001, rpb = 0.380 and p < 0.001, rpb = 0.447 respectively) and TUG performances were worse (p = 0.009, rpb = − 0.254). Serum hemoglobin and albumin levels were significantly low in dysphagic patients with sarcopenia (p < 0.001, rpb = 0.345, p = 0.008, rpb = 0.243). Dysphagia is independently associated with sarcopenia, depressive symptoms, and functionality. Dysphagia coexist with sarcopenia is associated with worse clinical consequences than without sarcopenia. [ABSTRACT FROM AUTHOR]

This paper contributes to our understanding of farm data value chains with assistance from 54 semi-structured interviews and field notes from participant observations. Methodologically, it includes individuals, such as farmers, who hold well-known positionalities within digital agriculture spaces—platforms that include precision farming techniques, farm equipment built on machine learning architecture and algorithms, and robotics—while also including less visible elements and practices. The actors interviewed and materialities and performances observed thus came from spaces and places inhabited by, for example, farmers, crop scientists, statisticians, programmers, and senior leadership in firms located in the U.S. and Canada. The stability of "the" artifacts followed for this project proved challenging, which led to me rethinking how to approach the subject conceptually. The paper is animated by a posthumanist commitment, drawing heavily from assemblage thinking and critical data scholarship coming out of Science and Technology Studies. The argument's understanding of "chains" therefore lies on an alternative conceptual plane relative to most commodity chain scholarship. To speak of a data value chain is to foreground an orchestrating set of relations among humans, non-humans, products, spaces, places, and practices. The paper's principle contribution involves interrogating lock-in tendencies at different "points" along the digital farm platform assemblage while pushing for a varied understanding of governance depending on the roles of the actors and actants involved. [ABSTRACT FROM AUTHOR]

It is common sense that some subjects have strong relationships while others are perhaps almost mutually independent, but a quantitative and systematic approach to describe such sense is a deficiency. A technique called pointwise mutual information (PMI) from information science helps to fulfill the request, but the calculation through a large-scale database is computationally infeasible if one requires an instantaneous value. This work provides a two-step remedy via deep learning for estimating and predicting relationships among two subject types that are found in the large-scale citation database called the Web of Science. The resulting model successfully replicates existing PMI values among subject types, and it can be used for predicting PMI values of two subject types if one or both subject types does not exist in the database. [ABSTRACT FROM AUTHOR]

Machine learning algorithms reshape how people communicate, exchange, and associate; how institutions sort them and slot them into social positions; and how they experience life, down to the most ordinary and intimate aspects. In this article, we draw on examples from the field of social media to review the commonalities, interactions, and contradictions between the dispositions of people and those of machines as they learn from and make sense of each other. [ABSTRACT FROM AUTHOR]

The objective of this paper is to discuss the conditions of production and circulation of the book to understand the success and impact of Dependency and development in Latin America. Firstly, we highlight in which sense this book belongs to a broader intellectual tradition, i.e., the interpretative essays on Brazilian reality. Secondly, we investigate the transnational institutional trajectories of its authors that enable them to develop the comparative analytical perspective of the book. Finally, we reconstruct the publishing history of the book. [ABSTRACT FROM AUTHOR]

Software vendors aim to find, for a release of the software, an optimal subset of features that gives the highest value while respecting the resource limitations. The value of a feature subset, however, is determined by the values of the individual features within that subset—which are specified by the preferences of users. But user preferences for some features may change in the presence or absence of others. As such, the values of certain software features may be influenced, either positively or negatively, by other features. Such influences are widely recognized and referred to in the literature as value-related dependencies among software features. Value-related dependencies impact the overall value of a software product and, therefore, need to be considered in software release planning. To achieve this, we have proposed identifying value-related dependencies by mining user preferences for software features. We integrate these dependencies into an integer programming model, that finds an optimal subset of the features for a release of a software product. We have demonstrated the practicality of our proposed approach by studying a real-world software project and simulations. [ABSTRACT FROM AUTHOR]

In this study, we examine whether job control, job demands and job outcomes of 'dependent self-employed workers', i.e. the workers in this particular grey zone between employment and self-employment, are more similar to those of the self-employed or paid employed. To this end, we use microdata drawn from the 2010 wave of the European Working Conditions Survey for 34 European countries. First, we develop and validate a psychometrically sound multidimensional scale for these 3 key constructs by conducting both exploratory and confirmatory factor analysis. Then, multilevel (hierarchical) linear regressions are used to test the validity of our hypotheses. Our results suggest that these hybrid work relationships are endowed with the least favourable attributes of both groups: lower job control than self-employed workers, higher job demands than paid employees and, overall, worse job outcomes than both. [ABSTRACT FROM AUTHOR]

Dependence of stroke survivors regarding the ability to perform activities of daily living imposes a burden on family caregivers. The study evaluated the effect of the family-centered empowerment program on the ability of Iranian patients with stroke to perform activities of daily living, as well as on family caregiver burden. In this randomized controlled trial study, a total of 90 pairs of patients with stroke and their family caregivers was selected and randomly assigned to the intervention or control groups. Patients and their family caregivers participated in four family-centered empowerment program sessions over four consecutive days while the patient was hospitalized. The difference in the ability of patients with stroke in the intervention and control groups to perform activities of daily living was not significant 2 weeks after the intervention. However, the ability of patients with stroke in the intervention group to perform activities of daily living increased significantly 2 months after the intervention compared with the control group: 66 ± 35.95 and 51.31 ± 36.28, respectively (p = 0.047). Two weeks after the intervention, the family caregiver burden significantly decreased in the intervention group (29.55 ± 15.38) compared with the control group (38.77 ± 18.53 and p = 0.012). The burden in the intervention group also decreased 2 months after the intervention compared with the control group: 22.95 ± 15.68 and 36.11 ± 18.88, respectively (p < 0.001). Nurses can use the family-centered empowerment program to improve the quality of life of patients with stroke, and to reduce the burden of family caregivers. [ABSTRACT FROM AUTHOR]

Avoidable mortality (AM) is a health indicator used to examine trends in avoidable deaths amenable to public health and medical interventions. AM is more likely amongst marginalized populations. Our objective was to examine trends in AM rates by level of neighborhood marginalization. Decedents under age 75 years in Ontario from 1993 to 2014 (n = 691,453) were assigned to a quintile-level of each Ontario Marginalization (ON-Marg) Index dimension: material deprivation, residential instability, dependency, and ethnic concentration. We calculated ON-Marg Index dimension and quintile specific age- and sex-standardized AM incidence rates. We then calculated annual AM rate ratios between the most (Q5) and least (Q1) marginalized quintiles for each ON-Marg dimension. To describe the inequity gap in AM over time we calculated the absolute difference in the Q5/Q1 rate ratio between 2014 and 1993 for each dimension. AM rates in Ontario were almost halved (48.6%) from 1993 to 2014 (216 vs. 111 per 100,000 population). This decline was greater for treatable AM (75 vs. 36 per 100,000 population) than preventable AM (128 vs. 88 per 100,000 population). The inequity gap in AM Q5/Q1 rate ratios (RR) between 1993 and 2014 widened for all marginalization dimensions: dependency (RR 2.11–2.58), ethnic concentration (RR 0.59–0.48), material deprivation (RR 1.63–2.23), and residential instability (RR 2.01–2.43). To attain further declines in AM, policymakers and governments must address AM due to preventable deaths in neighborhoods highly marginalized by dependency, material deprivation, and residential instability. [ABSTRACT FROM AUTHOR]

Key summary points: Aim: This study aims to determine whether the combination of visiting frequency of the family caregiver and frailty status has an additive effect on the incidence of dependency among hospitalized older patients. Findings: The results of this study show that low visiting frequency and frailty affected the dependency after discharge among hospitalized older patients. Moreover, the coexistence of the low visiting frequency and frailty increased the incidence of dependency. Message: These findings may be useful to determine the need for discharge support. Purpose: This study aims to determine whether the combination of visiting frequency of the family caregiver and frailty status has an additive effect on the incidence of dependency among hospitalized older patients. Methods: We analyzed the prospective cohort data of hospitalized older patients (65 years and older) with internal medical problems. The main outcome showed patients' dependency from admission to a month after discharge. We investigated the visiting frequency of family caregivers and the frailty status and categorized respondents into 4 groups: group 1, visiting frequency 3–7 times a week and non-frailty; group 2, visiting frequency 0–2 times a week and non-frailty; group 3, visiting frequency 3–7 times a week and frailty; or group 4, visiting frequency 0–2 times a week and frailty. We used the Cox proportional hazards regression to estimate the hazard ratios (HR) and confidence intervals (95% CI) of relationships between the combination of visiting frequency and frailty status, and dependency. Results: A total of 182 participants who completed the follow-up were analyzed. During the follow-up period, 45 participants (24.7%) showed some dependency. The hazards regression showed that the low visiting frequency group with presence of frailty had the most increased dependency, compared to other groups (adjusted HR 8.61 [95% CI 3.38–21.98]). Conclusions: The coexistence of low visiting frequency and the presence of frailty influenced dependency more strongly than each factor alone. These findings suggest that the combination of visiting frequency and frailty status is a useful predictor for future dependency. [ABSTRACT FROM AUTHOR]

Multivariate storm frequency modeling would help to gain improved understanding of complex storm process, and provide useful information for regulating flooding risk. In this paper, the dependency between magnitudes and directional occurrence dates of storm events was investigated with copula models. Taking account of extreme storms under various return periods, the concurrence risks as well as temporal representations of the recurrence risk were evaluated by the exceedance probability levels. A case study was demonstrated through the selected storms out of a 53-year long daily rainfall time series in the Shenzhen bay area by using the annual maximum precipitation and peak-over-threshold sampling method. Based on multiple univariate probability functions, a mixed distribution was proposed to determine the most suitable marginal distribution of storm magnitudes and directional dates at three spatially separated stations. The goodness-of-fit tests and ordinary least squares criterion of root-mean-square error were then employed to determine the copula model from the Archimedean and Plackett copulas. According to the coincidence exceedance probabilities of 200, 100, 50 and 20 years return periods, results showed an increase in the conjunctive risk of extreme rainfall events for recent 30 years with regards to pair and triple station, implying the significance to further strengthen the regional flooding control measures. Besides, temporal variations of exceedance probabilities at each station revealed an increasingly concentrated risk during wet period and a shift of the risk peak to earlier dates during 1 year, which would indicate the flooding precautions should be prepared in advance. [ABSTRACT FROM AUTHOR]

Background: Dependency in older ages is increasing. Many older persons receive care while living in the community. We aimed to identify the predictive value of four clinical measurements to predict home care intensity in older patients following discharge from hospital to home care over 90 days. Methods: We included 425 inpatients from the "Frailty Department–Local Palliative Care Network" of the local social health authority (ASST) Lecco, Italy (mean age 75.4 years, SD 14.5; female 75.5%). Changes in Health, End-stage disease, and Signs and Symptoms, light version (CHESS-Lite), activities of daily living (ADL), frailty, and the Service Urgency Algorithm. Receiver operative curves were used to calculate the area under the curve (AUC) for predicting Home Care Intensity coefficient (ratio of the number of days when any home care was provided 90 days post-discharge). The interRAI Contact Assessment Instrument was used to calculate these measures. Results: Analysis was stratified using six different home care intensity score cut-offs. CHESS-Lite had a higher AUC for predicting home care intensity at all cut-off levels but was best for predicting the highest level of home care intensity (≥ 0.8) where the AUC was 0.71 (0.64–0.79). The frailty index also had an acceptable AUC. ADL had the lowest AUC. Conclusions: Health instability measured with CHESS-Lite has a high predictive value for identifying home care intensity in geriatric patients after discharge from hospital to home, especially in persons with higher home care intensity scores. Geriatric patients with high health instability should be focused on at discharge to prioritize assessment and initiate timely services for home care support. [ABSTRACT FROM AUTHOR]

According to Blatt's theory on personality development, adolescents with high levels of self-criticism and dependency are more vulnerable to diverse types of psychopathology. However, relatively little is known about intervening processes involved in this personality-based vulnerability. The goal of this study is to examine, on the basis of Self-Determination Theory, the explanatory role of the psychological needs for autonomy, competence, and relatedness in associations between self-criticism and dependency on the one hand and adolescents' internalizing and externalizing problems on the other hand. In this cross-sectional and multi-informant study, 284 adolescents (58,5% female; mean age = 14.15; SD =.93) and their parents reported about the adolescent's internalizing and externalizing problems. Adolescents also completed measures assessing self-criticism, dependency, and psychological needs experiences. Data were analyzed using structural equation modeling. Self-criticism and dependency were significantly related to higher levels of both internalizing and externalizing problems, with psychological need frustration fully mediating these associations. This study suggests that psychological need frustration is an important explanatory mechanism in personality-related vulnerability for adolescent psychopathology. More generally, it provides further evidence for the integration between two major theoretical approaches in the domain of adolescent development and psychopathology. [ABSTRACT FROM AUTHOR]

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Wireless sensor networks (WSNs) consist of smart nodes that observe a phenomenon of interest (POI) via several sensors. They are extensively used in environment surveillance and can be fit very well in fire detection where detecting fire correctly in real time while avoiding false alarms is crucial. Detection in each node is carried out by fusing the data of the sensors connected to that node. In this paper, a data fusion scheme is proposed in which the measurements of temperature and relative humidity sensors are fused while the correlation among them is resolved using the copula theory. The proposed scheme is validated using a practical data set. [ABSTRACT FROM AUTHOR]

Early phases of information systems engineering include the understanding of the enterprise's context and the construction of models at different levels of decomposition, required to design the system architecture. These time-consuming activities are usually conducted by relatively large teams, composed of groups of non-technical stakeholders playing mostly an informative role (i.e. not involved in documentation and even less in modelling), led by few experienced technical consultants performing most of the documenting and modelling effort. This paper evaluates the ability of non-technical stakeholders to create strategic dependency diagrams written with the i* language in the design of the context model of a system architecture, and find out which difficulties they may encounter and what the quality of the models they build is. A case study involving non-technical stakeholders from 11 organizational areas in an Ecuadorian university held under the supervision and coordination of the two authors acting as consultants. The non-technical stakeholders identified the majority of the dependencies that should appear in the case study's context model, although they experienced some difficulties in declaring the type of dependency, representing such dependencies graphically and applying the description guidelines provided in the training. Managers were observed to make more mistakes than other more operational roles. From the observations of these results, a set of methodological advices were compiled for their use in future, similar endeavours. It is concluded that non-technical stakeholders can take an active role in the construction of the context model. This conclusion is relevant for both researchers and practitioners involved in technology transfer actions with use of i*. [ABSTRACT FROM AUTHOR]

Safety and reliability analysis is an important issue to prevent an event which may to occurrence of catastrophic accident in process industries. In this context, conventional safety and reliability assessment technique like as fault tree analysis have been widely used in this regards; however, they still suffer in subjective uncertainty processing and dynamic structure representation which are important in risk assessment procedure. In this paper, a new framework based on 2-tuple intuitionistic fuzzy numbers and Bayesian network mechanism is proposed to evaluate system reliability, to deal with mentioned drawbacks, and to recognize the most critical system components which affects the system reliability. The reliability and safety guarantee of such system in the aspect of continuity operations and enhancing the safety of operators and vehicle drivers are crucial. The results revealed that the proposed model could be useful for diagnosing the systems' faults compared with listing approaches of safety and reliability analysis. [ABSTRACT FROM AUTHOR]

This paper is an attempt towards analysing the demand for domestic workers specifically in urban India, wherein we intend to verify a range of hypotheses pertaining to demand for domestic workers in urban households. The analysis exploits the information obtained in Unemployment and Employment Survey and Consumption Expenditure Survey provided by the National Sample Survey Organisation, to assess the significance of domestic work and to characterise the demand for domestic workers across Indian states. We supplement the discussion with insights from a micro-level enquiry. While it may be otherwise understood that rising economic affluence is the driving force behind this phenomenon, a critical analysis at the household level indicates the complex dynamic of economic affluence and rising dependency determines engagement of domestic workers in urban Indian households. A micro-level study conducted in the National Capital Region throws further light on the nature of demand for domestic workers in urban areas. A survey among employers reveals that employment of domestic workers has been customary for a class of population. However, other household characteristics like women's employment and life cycle of a household also shape the demand for a domestic worker. Nature of employment, broadly categorised as live-out/day work or live-in work, is also observed to be influenced by economic class and household specific needs. [ABSTRACT FROM AUTHOR]

Purpose: Taking charge of dependent people is a major challenge. Numerous studies focus on the congruence of the dyadic perceptions of the actors. This study looks into the congruence of perceptions concerning dependence (i.e., physical and mental losses that prevent carrying out everyday tasks) and pathologies affecting older people within the triad: the aged person living at home, the informal caregiver, and the in-home professional caregiver. Methods: A face-to-face questionnaire examining dependence and pathologies was administered separately to the three actors of 58 triads. This database has been analyzed mainly with techniques of data mining (MCA and AHC). Results: The perception of pathologies and dependence are perceivably different depending on the actors. Within a same triad, perceptions of these two points—taken together or individually—turn out to be very dispersed. We bring to light three factors that structure 94% (with Benzécri's correction) of the congruence in perception within triads, and we propose a typology in four clusters of triads on this theme. Conclusions: The congruence analyses of the triads showed that incongruence in cross-perceptions of older people, formal, and informal caregivers on pathologies and dependence is clearly structured. Four quite distinct clusters have emerged, which could be exploited in the framework of public policies on the management of dependency in the home setting, to effectively alleviate the incongruence in the triads. [ABSTRACT FROM AUTHOR]

The Dagum distribution plays an important role both in statistical theory and in economics as a model for income distribution. The main goal of this paper was to develop a bivariate extension of the Dagum distribution and study its distributional properties. Also we will study its dependence properties using copula function. Also we derive the cumulative distribution function and probability density function of the maximum and minimum of the bivariate Dagum order statistics. We estimate the parameters of the distribution and demonstrate it on a real data example. [ABSTRACT FROM AUTHOR]

Lavishly decorated wagons excavated from royal Xiongnu burials are generally regarded as tribute items from China offered to Xiongnu elites, symbolizing important political and economic interactions between the Xiongnu state (209 BC-155 AD) and the Han dynasty (206 BC-220 AD). This theory views such vehicles as having no relation to indigenous Xiongnu craftsmanship. Furthermore, specialized products delivered to the northern nomadic peoples from the Han state are often cited in support of the notion of Xiongnu dependency on foreign states for technological and political development. Expecting to find evidence of China’s traditional iron and bronze technology, we examined a number of key metallic components of these wagons excavated from the royal Xiongnu burial at Golmod 2 in central Mongolia, radiocarbon dated to 109 BC-AD 75. Surprisingly, the iron metallurgy in question was based primarily on the bloomery process while low tin bronze and arsenical copper alloys dominated the pertinent bronze production. These respective technological traditions are typical of Xiongnu manufacture but significantly different from traditional Han metallurgy. We interpret this evidence as suggesting the need for a more balanced evaluation of foreign influence on the rise and development of the Xiongnu state. [ABSTRACT FROM AUTHOR]

A line of research is emerging investigating the private sector impacts and dependencies on critical biodiversity and ecosystem services, and related business risks and opportunities. While the ecosystem services narrative is being forwarded globally as a key paradigm for promoting business sustainability, there is scarce knowledge of how these issues are considered at managerial level. This study thus investigates managerial views of corporate sustainability after the ecosystem services concept. We analyse interviews conducted with 20 managers from domestic and international forestry companies operating with a plantation-based business model in China. Content analysis was employed to analyse the data, with a focus on four key areas: (1) interviewee familiarity with the ecosystem services concept; (2) their views of corporate dependencies and impacts on ecosystem services; (3) related business risks and opportunities; and (4) viability of existing instruments and practices that can be employed in detecting and addressing business impacts and dependencies on ecosystem services. Through an inductive approach to the empirical findings, we refined a framework that holds operational value for developing company response strategies to ecosystem services impact/dependence assessment, ensuring that all issues are addressed comprehensively, and that related risks and opportunities are properly acknowledged. [ABSTRACT FROM AUTHOR]