Packaged water consumption has grown rapidly in urban areas of many low and middle income countries, but particularly in Ghana. However, the sources of water used by this growing packaged water industry and its implications for water resource management and transport-related environmental impacts have not been described. This study aimed to assess the spatial distribution of regulated packaged water production in Ghana, both in relation to demand and for natural mineral water, to hydrogeological characteristics. 764 addresses for premises licenced to produce packaged water from 2009-2015 were mapped and compared to regional sachet water consumption and beverage import/export data examined. We find evidence to suggest packaged water is transported shorter distances in Ghana than in developed countries. For natural mineral waters, producers should be able to address the most widespread water quality hazards (including high salinity, iron and nitrates) in aquifers used for production through reverse osmosis treatment. The study suggests there is scope to integrate beverage product and groundwater regulatory databases to support groundwater management.

A crewed mission to and from Mars may include an exciting array of enabling biotechnologies that leverage inherent mass, power, and volume advantages over traditional abiotic approaches. In this perspective, we articulate the scientific and engineering goals and constraints, along with example systems, that guide the design of a surface biomanufactory. Extending past arguments for exploiting stand-alone elements of biology, we argue for an integrated biomanufacturing plant replete with modules for microbial \textit{in situ} resource utilization, production, and recycling of food, pharmaceuticals, and biomaterials required for sustaining future intrepid astronauts. We also discuss aspirational technology trends in each of these target areas in the context of human and robotic exploration missions in the coming century.

We describe a dataset that contains job description published on a popular online website in the information and technology sector. As the website focus mainly on United Kingdom based jobs, the data have a specific focus on this country. It contains 11.501 job vacancies and 13 related meta data information. The dataset is suitable for HR analysis using machine learning techniques such as natural language processing and neural networks.

The 2019 Coronavirus pandemic which was initially referred to as 2019-nCoV, was first identified in Wuhan, China. Early response from the Chinese government included quarantine of infected persons, isolation and total lockdown of Wuhan province to prevent further spread. With the spread of the disease across national borders and declaration of the disease as a global pandemic, there has been a robust response by the international community to contain this deadly virus and prevent its further spread worldwide. Africa is not left out of this rampaging pandemic with documented cases in over 40 countries and still rising. Although extensive studies have been carried out on the novel SARS-CoV-2 on its pathogenesis, mode of infection and virulence but much is still unknown. However, potentially infectious samples are received routinely in the medical laboratory for analysis. This technical note reviews good laboratory practice (GLP) and processes across the different specialities of Medical Laboratory practice that should minimize the risk of infection to laboratory staff especially in resource-limited settings.

The question of the relevance of human and natural capital, as well as the potential adverse effect of natural capital on economic growth, has gained increased attention in development economics. The aim of this paper is to theoretically and empirically assess the relevance of several forms of capital on economic growth in small economies that are dependent upon tourism or natural resources. The empirical framework is based on Impulse Response Functions obtained from Vector Autoregressive models in which we focus on the model where economic growth is the dependent variable for ten small economies that are dependent upon either tourism or natural resources. We find that there is evidence of the ‘’natural resource curse’’, especially in the economies that have a strong dependence on resources that are easily substitutable and whose prices constantly fluctuate. We further find that in the majority of observed cases the type of capital these small economies are most dependent on for their economic growth causes negative impulses in the majority of the observed periods. The main policy recommendation should be to assure that even these small economies should strive towards further diversification and avoid dependence on only one segment of their economy.

As the natural resources are getting exhausted, the concept of sustainable development of region has received increasing attentions, especially for resource-dependent cities. In this paper an innovative method that emergy analysis and IPAT (Human Impact Population Affluence Technology) model were combined in order to analyze the quantitative relationship of economic growth and energy consumption and further to evaluate its overall sustainability level. Taiyuan, a traditional, resource-dependent city in China, is selected as the case study region. The main results show that total emergy of Taiyuan increased from 9.023× 1023 sej in 2007 to 9.116× 1023sej in 2014, with 38% reduction on non-renewable emergy and 125% growth on imported emergy. Regional emergy money ratio (RMB) was reduced by 48% from 5.31× 1013sej/$ in 2007 to 2.74× 1013sej/$ in 2014, indicating that the increasing speed of consuming resources and energy was faster than the increase of GDP, and that Taiyuan’s money purchasing power declined. The lower emergy sustainability index (ESI) indicates that Taiyuan was explored and produced large quantities of mineral resources, which puts more stress on the environment as a consequence, and that this is not sustainable in the long run. The IPAT analysis demonstrates that Taiyuan sticks to the efforts of energy conservation and environmental protection, in order to promote regional sustainable development, it is necessary to take an integrated effort. Policy insights suggest that resourceful regions should improve include energy and resource efficiency, optimizing energy and resourceful structure.

In January 2020, the World Health Organization declared a public health emergency and announced a new coronavirus disease (COVID-19), which would later go on to be declared as a pandemic, changing the global sphere and placing the economies of almost all countries under heavy stress. The airline industry, that had just begun recovering after facing crises one after another in the last two decades, from early 2000 due to 9/11, to the global financial crisis later, is now oce again facing an enormous challenge of closed borders and greater lockdowns due to the pandemic. Borders are closed, with very few planes are in the air, while the rest are grounded. The purpose of this paper is to give a conceptual understanding of the current pandemic situation and its consequences on the airline industry. The paper takes a unique perspective of human resource management (HRM) that is rarely used in the airline industry.

In training a deep learning system to perform audio transcription, two practical problems may arise. Firstly, most datasets are weakly labelled, having only a list of events present in each recording without any temporal information for training. Secondly, deep neural networks need a very large amount of labelled training data to achieve good quality performance, yet in practice it is difficult to collect enough samples for most classes of interest. In this paper, we propose factorising the final task of audio transcription into multiple intermediate tasks in order to improve the training performance when dealing with this kind of low-resource datasets. We evaluate three data-efficient approaches of training a stacked convolutional and recurrent neural network for the intermediate tasks. Our results show that different methods of training have different advantages and disadvantages.

Urbanization and industrialization processes in Mongolia have been significant and rapid for the last half-century. During this period, changes in political and economic systems, growth in the population, and the occasional harsh climate conditions were subject to fluctuations in the natural resource usage. The total Ecological Footprint (EF) in Mongolia has increased from 6.8 million global hectares (gha) in 1961 to 14.6 million gha in 2012. However, Biocapacity (BC) has decreased from 50.6 million gha in 1961 to 39.0 million gha in 2012. The study shows that grazing land Footprint and carbon uptake land Footprint are the two major contributors of the recent intensified use of biological resources. To ensure stable economic development and sustainable use of natural resources, environmental planning is required to consider both the population’s pressure on the environment and the ecosystem’s regeneration capacity, simultaneously. We have proposed a few possible strategies for sustainable utilization of grazing land Footprint and carbon Footprint. For grazing land Footprint, efficient management of both herding practice and number of animals should be considered. In case of carbon Footprint, it is estimated that with the improved combustion efficiencies of coal-based power plants and the maximum use of renewable energy, carbon dioxide (CO₂) emissions in Mongolia can be reduced up to 30% compared to the base line business as usual case in 2030.

Bio-molecular reagents like antibodies required in experimental biology are expensive and their effectiveness, among other things, is critical to the success of the experiment. Although such resources are sometimes donated by one investigator to another through personal communication between the two, there is no previous study to our knowledge on the extent of such donations, nor a central platform that directs resource seekers to donors. In this paper, we describe, to our knowledge, a first attempt at building a web-portal titled Bio-Resource Exchange that attempts to bridge this gap between resource seekers and donors in the domain of experimental biology. Users on this portal can request for or donate antibodies, cell-lines and DNA Constructs. This resource could also serve as a crowd-sourced database of resources for experimental biology. Further, in order to index donations outside of our portal, we mined scientific articles to find instances of donations of antibodies and attempted to extract information about these donations at the finest granularity. Specifically, we extracted the name of the donor, his/her affiliation and the name of the antibody for every donation by parsing the acknowledgements sections of articles. To extract annotations at this level, we propose two approaches – a rule based algorithm and a bootstrapped relation learning algorithm. The algorithms extracted donor names, affiliations and antibody names with average accuracies of 57% and 62% respectively. We also created a dataset of 50 expert-annotated acknowledgements sections that will serve as a gold standard dataset to evaluate extraction algorithms in the future. Contact: madhavi@pitt.edu, madhavi@cs.cmu.edu Database URL: http://tonks.dbmi.pitt.edu/brx Supplementary information: Supplementary data are available at Database online.

The 2030 Agenda for Sustainable Development, the SDGs, are high on the agenda for most countries of the world. In its publication of the SDGs, the UN has provided the goals and target descriptions that, if implemented at a country level, would lead towards a sustainable future. The IAEG (InterAgency Expert Group of the SDGs) was tasked with disseminating indicators and methods to countries that can be used to gather data describing the global progress towards sustainability. However 2030 Agenda leaves it to countries to adopt the targets with each government setting its own national targets guided by the global level of ambition but taking into account national circumstances. At present, guidance on how to go about this is scant, but it is clear that the responsibility is with countries to implement and that it is actions at a country level that will determine the success of the SDGs. SDG reporting by countries takes on two forms 1) global reporting using prescribed indicator methods and data; 2) National Voluntary Reviews where a country reports on its own progress in more detail but is also able to present data that are more appropriate for the country. For the latter, countries need to be able to adapt the global indicators to fit national priorities and context, thus the global description of an indicator could be reduced to describe only what is relevant to the country. Countries may also, for the National Voluntary Review, use indicators that are unique to the country but nevertheless contribute to measurement of progress towards the global SDG target. Importantly, for those indicators that relate to the security of natural resources security (e.g. water) indicators, there are no prescribed numerical targets/standards or benchmarks. Rather countries will need to set their own benchmarks or standards against which performance can be evaluated. This paper presents a procedure that would enable a country to describe national targets with associated benchmarks that are appropriate for the country. The procedure focusses on those SDG targets that are natural resource-security focussed e.g. extent of water-related ecosystems (6.6), desertification (15.3) etc., because the selection of indicator methods and benchmarks is based on the location of natural resources, their use and present state and how they fit into national strategies.

As renewed interest in human space-exploration intensifies, a coherent and modernized strategy for mission-design and planning has become increasingly crucial. Biotechnology has emerged as a promising approach to increase mission resilience, flexibility, and efficiency by virtue of its ability to efficiently utilize in situ resources and reclaim resources from waste streams. Since its infancy during the Apollo years, biotechnology, and specifically biomanufacturing, have witnessed significant expansions of scope and scale. Here we outline four primary mission classes, on Luna and Mars, that drive a staged and accretive biomanufacturing strategy. Each class requires a unique approach to integrate biomanufacturing into the existing mission architecture and so faces unique challenges in technology development.These challenges stem directly from the resources available in a given mission class – the degree to which feedstocks are derived from cargo and in situ resources – and the degree to which loop-closure is necessary. We see that as mission duration and distance from Earth increase, the benefits of specialized sustainable biomanufacturing processes increases. Here we present a strategic approach, guided by technoeconomics, to development, testing, and deployment of these technologies serves to nucleate the larger effort of supporting a sustained human presence in space. The processes needed for each scenario spans the technical breadth of synthetic biology to design engineering, from sophisticated genetic tailoring of chassis-organisms to building scalable, automated, easily operable bioreactors and processing systems. As space-related technology development often does, these advancements are likely to have profound implications for the creation of a stable, resilient bioeconomy on Earth.

Results-Based Funding (RBF) for Reducing Emissions from Deforestation and Forest Degradation (REDD+) has become an important instrument for channeling financial resources to forest conservation activities. At the same time, much literature on conservation funding is ambiguous about the effectiveness of existing RBF schemes. Many effectiveness evaluations follow a simplified version of the principal-agent model, although in practice the relation between aid providers and funding recipients is much more complex. As a consequence, intermediary steps of conservation funding are often not accounted for effectiveness studies. This research paper aims to provide a nuanced understanding of conservation funding by analyzing the allocation of financial resources for one of the largest RBF schemes for REDD+ in the world: the Brazilian Amazon Fund. As part of this analysis, this study has built a dataset of information on Amazon Fund projects at unprecedented detail in order to accurately reconstruct the allocation of financial resources across different stakeholders (i.e. governments, NGOs, research institutions), geographies and activities. The results show that stakeholders seem to hold preferences with respect to the type of activities that they support, thereby suggesting that project owners exert much influence on how deforestation reduction is to be attained. There are evidences that governmental organizations lack financial additionality of their projects, which renders the growing share of funding to this type of stakeholder particularly worrisome. By contrast, the geographical distribution of financial resources seemed to follow a more focused rationale as financial support tends to concentrate in areas where deforestation threats are highest. Overall, the allocation of the financial resources from the Amazon Fund reflects an arbitrary support of different projects that adopt very diverging theories of change that are not primarily concerned with attaining further deforestation reductions. As projects owners exert influence on funding effectiveness to some extent, the Amazon Fund may either seek to regulate the allocation of financial resources more actively or adopt funding effectiveness evaluations that account for this influence more comprehensively.

The potential of Sorghum bicolor L. (Moench) (Epuripur 1995) to phytoremediate petroleum oil-adulterated soils from an automobile repair workshop and the effect of enhancement factors: NPK fertilizer, cow dung and sewage sludge in in situ phytoremediation of the soil by the plant were assessed in this study. 50kg of petroleum oil-contaminated soil was collected from the workshop and divided into five equal portions. Four portions were potted with four sorghum plants with three subjected to equal amounts of enhancements (5%w/w) under normal growth conditions for 72 days. Representative soil samples were collected from spots at depths of 0–10 cm and 10–20 cm from the potted soils and subjected to Soxhlet oil extraction after 72 days. Experimental results revealed that S. bicolor survived in the petroleum oil-contaminated soils. Amendment of the petroleum oil-vitiated soils with cow dung, sewage sludge and NPK fertilizer augmented the remediation capacity of Epuripur 1995 by 12.5%, 6.3% and 9.1%. Addition of cow dung to crude oil contaminated soils could make such soils fully reestablished for agricultural activities. Further research aimed at determination of the phytoremediation potential of cereals such as corn, barley, rye, millet should be done.

The UK economy is overly reliant on unsustainable production and consumption practices, depleting finite resources at rates that will increase production costs, business risk and economic instability. This over-consumption produces emissions and waste that cause climate change and environmental degradation, impacting on the wellbeing of people in the UK and beyond. The Resource Recovery from Waste programme (RRfW) promotes a transition towards waste and resource management in a circular economy that restores the environment, creates societal benefits and promotes clean growth by engaging relevant actors in the transition process. RRfW collaborates with academia, government, and industry to co-produce a shared vision and approach to realise such a transition. Reflecting insights from RRfW’s government engagement, this article presents a positive outlook for changing the UK economy and society. It envisions a long-term future for waste and resource management that maximises the value of materials by circulating them in the economy for as long as possible. Four themes and an approach are proposed, including recommendations for regulatory instruments and a stable policy framework. It recommends further collaborative research to capitalise on opportunities for economic growth, innovation and resilient infrastructure whilst contributing to quality jobs and welfare in all four UK nations.

Allama Iqbal Open University (AIOU) is the largest distance learning institute of Pakistan and providing education to 1.4 million students. This is fairly a large setup across the country where students are geographically distributed. Currently the system works on a manual approach which is not efficient. Allocation of tutors and study centers to students plays a key role in distance learning for a better learning environment. Assigning tutors and study centers to distance learning students is a challenging task when there is huge geographical spread. The utilization of geospatial technologies in open and distance learning can fix allocation problems. This research analyzes the real data of twin cities Islamabad and Rawalpindi. The results show that the geospatial technologies can be used for efficient and proper resource utilization and allocation, which in turn can save the time and money. The overall idea fits into improved distance learning framework and related analytics.

Growing evidence about the negative socio-environmental consequences of plastic pollution led to various initiatives for better plastic scrap governance and its trade. At the same time, an examination of recent data shows that plastic scrap represents only a fraction of recyclable materials which are traded internationally and are also subject to similar problems of cross-border environmental governance. A limited analysis comparing plastics, textiles, paper and ferrous metals suggests that ongoing momentum for improvement of plastic scrap governance and circularity should also be framed to consider other types of secondary materiais.

Is it true that the nuclear technology applied to electric energy generation offers a clean, safe, reliable and affordable i.e. sustainable alternative? Yes it is, but its impact on the environment strongly depends on the implementation bearing residual risks due to a human factor, technical failures or natural catastrophes. A full response is therefore difficult and can first be given when the wicked multi-disciplinary problems get well formulated and “solved”. These problems have multi-dimensional nature lying at the interface between: necessary R&D effort, the industrial deployment and the technology impact in view of the environmental sustainability including the management of produced hazardous waste. This enormous complexity indicates that just a description of the problem might represent a problem. The paper proposes a holistic approach to assess the nuclear energy systems potential with respect to sustainable performance applying Multi-criteria decision analysis with a suitable objective tree and a multi-level criteria structure and examines the trading-off techniques for ranking of the alternatives. The framework proposes a multi-criteria and multi-stakeholders treatment which can be used as a pre-decisional support towards an implementation of nuclear fuel cycles adapted to national preferences and priorities. Proposed approach addresses some aspects of the environmental footprint of nuclear energy systems. Advanced nuclear fuel cycles, previously investigated by the NEA/OECD expert group WASTEMAN, are analyzed as a case study. Sustainability facets of waste management, resource utilization and economics are in focus.

Theory of the Thermal Response Testing (TRT) is a well-known part of sizing process of the geothermal exchange system. Multiple parameters influence accuracy of effective ground thermal conductivity measurement; like testing time, variable power, climate interferences, groundwater effect etc. To improve accuracy of the TRT we introduced procedure to additionally analyze falloff temperature decline after power test. Method is based on a premise of analogy between TRT and petroleum well testing, since origin of both procedures lies in diffusivity equation with solutions for heat conduction or pressure analysis during radial flow. Applying pressure build-up test interpretation technique to the borehole heat exchanger testing, greater accuracy could be achieved since ground conductivity could be obtained from this period. Analysis was conducted on coaxial exchanger with five different power steps, and with both direct and reverse flow regime. Each test was set with 96hr of a classical TRT, followed by 96hr of temperature decline, making it almost 2000 hours of cumulative borehole testing. Results showed that ground conductivity value could vary as much as 25% depending on test time, seasonal period and power fluctuations while thermal conductivity obtained from a falloff period gives more stable values with only 10% value variation.

The impact that new technologies have on all aspects of our lives, work, and businesses is significant and growing over time. Blockchain and artificial intelligence, among other innovative technologies, are having a profound effect on practically all business functions, including most human resources (HR) tasks. The HR sector is currently facing a variety of challenges as HR departments invest many hours in vetting candidates' applications and authenticating records to decrease the chances of imperfect recruiting. Nowadays, more technologically based processes are utilised for talent search, selection and management, as well as for accumulating, retaining, and integrating new talents into a company. These HR practices are far more effective compared to traditional methods but can also be more expensive if the transactional costs are considered. This paper consists of two parts. Following an introduction, the first part discusses the trust and confidentiality that can be attained, while the second part examines security, fraud prevention and the productivity gained from using blockchain technology in HR activities. Finally, there is a concluding section, discussing the implications of blockchain technology for firms who choose to employ it.

Over the past few decades, aircraft Ground Handling Operations (GHO) have been investigated by numerous researchers. Some aspects of GHO have been more focused on than others due to their importance in the GH processes. For instance, GHO performance has been tackled from different perspectives while workers and vehicles allocation suffer from the lack of research in the area. This paper is a literary review of the research that has been conducted in different areas of GHO. It sheds light on GHO performance, resource allocation and scheduling, operations scheduling, vehicle routing, and workers and vehicles allocation.

This article evaluates the macroeconomic implications of commercial bank seigniorage, which emerges from the commercial banks’ power to create money in a fractional reserves regime. After evaluating the impact on aggregate output of commercial bank money relative to alternative exchange arrangements, the article identifies the determinants of commercial bank seigniorage and analyzes how equilibrium prices are determined in an economy where commercial banks extract seigniorage. The article also identifies the conditions under which commercial banks extract seigniorage, clarifies the relationship between seigniorage from commercial bank money creation and profits from pure financial intermediation, and shows how commercial bank seigniorage changes with different types of interbank payments settlement.

The role of human resource management practices and organizational loyalty dealing with employee retention has been widely explored and examined in the existing literature. The majority of human resource management researchers have focused on the role of policies and practices in different sectors related to employee retention. However, less attention has been given to identifying the practices and procedures common across all industries and sectors. The present study attempts to determine and examine the most important constructs like HR practices and organizational loyalty of employee retention management and proposes a comprehensive structural equation model to measure the impact of these constructs on employee retention. After an extensive review of the literature, organizational loyalty, and human resources management practices like recruitment and selection, compensation and benefit, training and development, supervision and evaluation have been identified as four essential practices dealing with employee retention and are common across all industries. These practices constitute the component factors of an employee retention management predicting employee’s turnover intentions. The survey method was adopted, and the original data obtained through the self-administered questionnaire. The valid one hundred and eighty-nine (189) respondents analyzed by using Lisrel 8.7, Structural equation model (SEM) analysis results shows that human resource management practices and organizational loyalty have strong positive impact on employee retention. This study tends to assist human resource managers and decision makers in selecting the appropriate motivating factors to retain and satisfy their employees

This paper contributes to the debate on the impact of economic diversity and the resource curse on economic growth. We use dynamic panel data models on data on Canadian and US sub-national jurisdictions. We find evidence for a positive relationship between diversity and growth. Based on the Krugman Specialization Index, our analysis shows that the required threshold for not having the resource curse is 0.209. Above this threshold, the marginal contribution of natural resources to economic growth is lower for a more diversified regional economy than a less diversified one. We highlight the policy implications of these findings.

The key goal of the current study was to determine suitable areas of water pumping for drinking and agricultural harvest in Tabriz aquifer, locateed in East Azerbaijan province, northwest Iran. In the study area, groundwater is the key foundation of water for drinking and farming requirements. Groundwater compatibility study was conducted by analysing Electrical conductivity (EC), Total dissolved solids (TDS), Chloride (Cl), Calcium (Ca), Magnesium (Mg), Sodium (Na), Potassium (K), Sulfate (SO₄), Total hardness (TH), Bicarbonate (HCO₃), pH, carbonate (CO₃) and Sodium Adsorption Ratio (SAR) obtained from 39 wells in the period of 2003 to 2014. For this purpose, the Water Quality Index (WQI) and irrigation water quality (IWQ) index is respectively utilized. The WQI index zoning exposed that the groundwater of the study area for drinking purposes is categorized as excellent, good and poor water. Most drinking water harvested for urban and rural areas are in the class of "excellent water". IWQ index average for the study area was in the range of 25.9 to 34.55. The results revealed that about 37 percent (296 km²) of groundwater has high compatibility, and 63 percent of the study area (495 km²) has average compatibility for agricultural purposes. The trend of IWQ and WQI indexes demonstrates that the groundwater is getting worse over the time.

Many species of plants are found in regions to which they are alien. Their global distributions are characterised by a family of exponential functions of the kind that arise in elementary statistical mechanics (an example in ecology is MacArthur's broken stick). We show here that all these functions are quantitatively reproduced by a model containing a single parameter – some global resource partitioned at random on the two axes of species number and site number. A dynamical model generating this equilibrium is a two fold stochastic process and suggests a curious and interesting biological interpretation in terms of niche structures fluctuating with time and productivity; with sites and species highly idiosyncratic. Idiosyncrasy implies that attempts to identify a priori those species likely to become naturalized are unlikely to be successful. Although this paper is primarily concerned with a particular problem in population biology, the two fold stochastic process may be of more general interest.

The primary attraction of IaaS is providing elastic resources on demand. It becomes imperative that IaaS-users have an effective methodology for learning what resources they require, how many resources and for how long they need. However, the heterogeneity of resources, the diversity resource demands of different cloud applications and the variation of application-user behaviors pose IaaS-users big challenge. In this paper, we purpose a unified resource demand forecasting model suiting for different applications, various resources and diverse time-varying workload patterns. With the model, taking input from parameterized applications, resources and workload scenarios, the corresponding resources demands during any time interval can be deduced as output. The experiments configure concrete functions and parameters to help understanding the above model.

Natural capital is the wealth of nations that give them the economic status they represent. Worldwide, vulnerable people depend on natural capital for employment, salaries, wealth, and livelihoods and, in turn, determine the developmental index of the nation to which they belong. The availability of ecological services is crucial for clean water and air, food and fodder, and agricultural development. In this short commentary, we have tried to sum up the ideas and discussions over natural capital's role in ascribing economic status to countries. We have discussed how the prosperity of humans is intertwined with the services ecosystems provide and how poor natural resource management (NRM) has adversely cost human well-being. The paper concludes that to ensure the current and future human well-being, an in-depth understanding of the services ecosystems provide, is essential.

Human factors are the most relevant issues contributing to adverse events in obstetrics. Specific training of Crisis Resource Management (CRM) skills (i.e., problem solving and team management, resource allocation, awareness of environment, and dynamic decision-making) are now widespread and are often based on High Fidelity Simulation. In order to be used as a guideline in simulated scenarios, they need to be translated into specific and observable behavioral markers. To this purpose, we developed a set of observable behaviors related to the main elements of CRM in the delivery room. The observational tool was then adopted in a two-days seminar on obstetric hemorrhage where teams working in obstetric wards of six Italian hospitals took part to simulations. The tool was used as guide for the Io and as a peer-to-peer feedback. It was then rated for its usefulness in facilitating the reflection upon one’s own behavior, its ease of use, and its usefulness for the peer-to-peer feedback. The ratings were highly positive, around 4 in a 5-point scale. The CRM observational tool is therefore a useful, quick and easy solution to facilitate the debriefing, the peer-to-peer feedback and, most of all, the transfer of safe behavior from simulation to everyday practice.

The Baculoviridae, a family of insect-specific large DNA viruses, is widely used in both biotechnology and biological control. Its applied value stems from millions of years of evolution influenced by interactions with their hosts and the environment. To understand how ecological interactions, have shaped baculovirus diversification, we reconstructed a robust molecular phylogeny using 217 complete genomes and ~580 isolates for which at least one of four lepidopteran core genes was available. We then used a phylogenetic-concept-based approach (mPTP) to delimit 165 baculovirus species, including 38 species derived from new genetic data. Phylogenetic optimization of ecological characters revealed a general pattern of host conservatism punctuated by occasional shifts between closely related hosts and major shifts between lepidopteran superfamilies. Moreover, we found significant phylogenetic conservatism between baculoviruses and the type of plant growth (woody or herbaceous) associated with their insect hosts. In addition, we found that colonization of new ecological niches sometimes led to viral radiation. These macroevolutionary patterns show that besides selection during the infection process, baculovirus diversification was influenced by tritrophic interactions, explained by their persistence on plants and interactions in the midgut during horizontal transmission. This complete eco-evolutionary framework highlights the potential innovations that could still be harnessed from the diversity of baculoviruses.

Fifth Generation (5G) communication technology is intended to offer higher data rates, outstanding user exposure, power consumption, and extremely short latency. Such cellular networks will implement a diverse multi-layer model comprising of device-to-device networks, macro-cells, and dissimilar categories of small-cells to assist customers with desired quality-of-service (QoS). This multi-layer model affects several studies that confront utilizing interference management and resource allocation in 5G networks. With the growing need and the lack of resources, the resource distribution problem desires to be focused capably to accomplish the traffic and to enhance network working. One of the utmost serious problems is to alleviate the jamming from the network in support of having a better QoS. However, there are limited review papers written on resource distribution, there is no particularize and organized review carry out in 5G resource allocation. Hence, this article covers and evaluates the argument using a classification of existing developing resource allocation schemes in 5G thoroughly by classifying the schemes to enhance the service quality. This survey comprises the discussion based on metrics used to evaluate the performance. It would also permit ahead beyond evidence on resource allocation methods in 5G and empowers the scholars to meet the present research areas to focus on.

The COVID-19 pandemic forced the transition to emergency online learning without prior preparation or guidelines. This transition has been particularly challenging in developing countries and low-resource contexts and hindered student engagement. We aim to identify the engagement strategies which students, engaging in emergency online learning in low-resource contexts, perceive to be effective. We conducted a sequential mixed-methods study based on Moore’s interaction framework for distance education. First, we conducted a literature review and interviewed ten teachers and ten students to identify a list of engagement strategies. Then, we designed a questionnaire that examines student perceptions of these strategies. We administered the questionnaire to 313 students engaging in emergency online learning in low-resource contexts. Our analysis results showed that student-content engagement strategies, e.g. screen sharing, summaries, and class recordings, are perceived as the most effective, closely followed by student-teacher strategies, e.g. Q&A sessions and reminders. Student-student strategies, e.g. group chat and collaborative work, are perceived as the least effective. The perceived effectiveness of engagement strategies depends on the context and the students’ characteristics, e.g. gender, major, and technology access. To support instructors, instructional designers, and researchers we propose a ten-level guide for engaging students during emergency online classes in low-resource contexts.

In this paper, we discuss the most significant application opportunities and outline the challenges in performing a real-time and energy-efficient management of the distributed resources available at mobile devices and Internet-to-Data Center. We also present an energy-efficient adaptive scheduler for Vehicular Fog Computing (VFC) that operates at the edge of a vehicular network, connected to the served Vehicular Clients (VCs) through an Infrastructure-to-Vehicular (I2V) over multiple Foglets (Fls). The scheduler optimizes the energy by leveraging the heterogeneity of Fls, where the Fl provider shapes the system workload by maximizing the task admission rate over data transfer and computation. The presented scheduling algorithm demonstrates that the resulting adaptive scheduler allows scalable and distributed implementation.

Ecologists use the net biotic interactions among plants to predict fundamental ecosystem features. Following this approach, ecologists have built a giant body of theory founded on observational evidence. However, due to the limitations that a phenomenological approach raises both in empirical and theoretical studies, an increasing number of scientists claim the need for a mechanistic understanding of plant interaction outcomes, and a few studies have taken such a mechanistic approach. In this synthesis, we propose a modeling framework to study the plant interaction mechanistically. We first establish a conceptual ground to frame plant-plant interactions, and then, we propose to formalize this research line theoretically developing a family of individual-based, spatially-explicit models in which biotic interactions are an emergent property mediated by the interaction between plants’ functional traits and the environment. These models allow researchers to evaluate the strength and sign of biotic interactions under different environmental scenarios and thus constitute a powerful tool to investigate the mechanisms underlying facilitation, species coexistence, or the formation of vegetation spatial patterns.

Abstract: Purpose – In this article we lay out the change management practices adopted by financial firms in small states within the Eurozone. We determine whether these organisations have the ability to identify triggers for change (Red Flags) and subject them to eight thematic elements to understand whether management practices can continue to exist and support operational environments, even when unexpected circumstances affect their day to day operations and processes. In doing this we examine the extent to which the eight thematic elements from the model designed by Dalli Gonzi, (2019) (The Dali Model) can assist organisations in risk identification and business continuity planning. Design/methodology/approach – A self-administered questionnaire purposely designed for this study was administered to personnel working in internal controls within financial institutions of small Eurozone states. The participants were asked to grade statements using a 5-point Likert scale, ‘1’ being ‘totally disagree’ and ‘5’ being totally agree’ to the statement posed under the thematic elements forming the basis of the Dali Model. Findings – Factor analysis provided support for the eight hypothesised dimensions of the decision-making model: connection, capacity, governance, network, policy, training, process improvement, standards. Originality/value – The study provides a better understanding and support of “best practice” in change management through an understanding and assessment of the eight factors that are the basis of this model. It addresses practical recommendations to ensure application to a wider frame of use.

How perceptual limits can be overcome has long been examined by psychologists. This study investigated whether visual cues, blindfolding, visual-auditory synesthetic experience and music training could facilitate a smaller frequency difference limen (FDL) in a gliding frequency discrimination test. It was hoped that the auditory limits could be overcome through visual facilitation, visual deprivation, involuntary cross-modal sensory experience or music practice. Ninety university students, with no visual or auditory impairment, were recruited for this one-between (blindfold/visual cue) and one-within (control/experimental session) designed study. A MATLAB program was prepared to test their FDL by an alternative forced-choice task (gliding upwards/gliding downwards/no change) and two questionnaires (Vividness of Mental Imagery Questionnaire & Projector-Associator Test) were used to assess their tendency to synesthesia. Participants with music training showed a significantly smaller FDL; on the other hand, being blindfolded, being provided with visual cues or having synesthetic experience before could not significantly reduce the FDL. However, the result showed a trend of reduced FDLs through blindfolding. This indicated that visual deprivation might slightly expand the limits in auditory perception. Overall, current study suggests that the inter-sensory perception can be enhanced through training but not though reallocating cognitive resources to certain modalities. Future studies are recommended to verify the effects of music practice on other perceptual limits.

Reinvigorated public interest in human space exploration has led to the need to address the science and engineering challenges described by NASA's Space Technology Grand Challenges (STGCs) for expanding the human presence in space. Here we define Space Bioprocess Engineering (SBE) as a multi-disciplinary approach to design, realize, and manage a biologically-driven space mission as it relates to addressing the STGCs for advancing technologies to support the nutritional, medical, and incidental material requirements that will sustain astronauts against the harsh conditions of interplanetary transit and habitation offworld. SBE combines synthetic biology and bioprocess engineering under extreme constraints to enable and sustain a biological presence in space. Here we argue that SBE is a critical strategic area enabling long-term human space exploration; specify the metrics and methods that guide SBE technology life-cycle and development; map an approach by which SBE technologies are matured on offworld testing platforms; and suggest a means to train the next generation spacefaring workforce on the SBE advantages and capabilities. In doing so, we outline aspects of the upcoming technical and policy hurdles to support space biomanufacturing and biotechnology. We outline a perspective marriage between space-based performance metrics and the synthetic biology Design-Build-Test-Learn cycle as they relate to advancing the readiness of SBE technologies. We call for a concerted effort to ensure the timely development of SBE to support long-term crewed missions using mission plans that are currently on the horizon.

Unmanned Aerial Vehicles (UAVs) severing as the relay is an effective technology method to extend the coverage. It can also alleviate the congestion and increase the throughput, especially applied in UAV networks. However, since the energy of UAVs is limited and the resources in UAV networks are scarce, how to optimize the network delay performance under these constraints should be well investigated. Besides, the relationship among different resources, e.g. power and bandwidth, is coupled which makes the optimization more complex. This article investigates the problem of joint power and bandwidth allocation in UAV backhaul networks, which considers both the delay performance and the resource utilization efficiency. Considering the heterogeneous locations characteristics of different UAVs, we formulate the optimization problem as a Stackelberg game. The relay UAV acts as the leader and extended UAVs act as followers. Their utility functions take both the delay durance and the resource consumption into account. To capture the competitive relationship among followers, the sub-game is proved to be an exact potential game and exists Nash equilibriums (NE). The Stackelberg Equilibrium (SE) is proved afterwards. We utilize a hierarchical learning algorithm (HLA) to find out the best resource allocation strategies, which also reduces the computational complexity. Simulation results demonstrate the effectiveness of the proposed method.

Fog computing is a potential solution to overcome the shortcomings of the cloud computing processing of IoT tasks. These drawbacks can be high latency, location awareness and security, and it is attributed to the distance between IoT devices and servers, network congestion and other variables. Although fog computing has evolved as a solution to these challenges, it is known for having limited resources that need to be consciously utilised, or any of its ad-vantages would be lost. Computational offloading and resource management are critical concerns to be considered to get maximum benefit of the available resource at fog computing systems and benefit from its advantages. Computational offloading and resource management are important issues to be considered to get maximum benefit of the available resource at fog computing systems and benefit from its advantages. In this article, in vehicular traffic applications, we introduce a dynamic online offloading scheme that involves the execution of delay-sensitive ac-tivities. This paper proposes an architecture of a fog node that enables a fog node to adjust its offloading threshold dynamically (i.e., the criteria by which a fog node decides whether tasks should be offloaded rather than executed locally) using two algorithms: dynamic task scheduling (DTS) and dynamic energy control (DEC). These algorithms seek to solve an optimisation problem aimed at minimising overall delay, improving throughput, and minimising energy consumption at the fog layer, while maximising the use of resource-constrained fog nodes. Compared with other benchmarks, our approach can reduce the delay by up to 95.38% and reduce energy consumption by up to 67.71% in fog nodes. Additionally, this approach enhances throughput by 71.08%.

The In this paper, a universal method has been developed, which is a combination of an optimization method and a method for assessing the marginal utility. At present, the problem of optimal load distribution in the power system between a hydropower plant (HPP) and thermal power plants (TPP) is solved using the equality of the differential incremental rate characteristics of fuel consumption at TPP and water consumption at HPP by the Lagrangian multiplier method. In this case, the number of iterations can be five or more. The proposed approach is based, first of all, on the correct representation of the differential characteristics and calculation of a hydro resource price for the operational control of the HPP. Based on the comparison of water volume at a HPP and fuel amount at combined heat and power plants (CHPP) used for generation of 1 kW power, it is possible to determine a water price for a HPP. As a result of implementing the developed method for the HPP, a price of sold electricity in the flexible energy market will be comparable with the price for sold electricity produced at CHPPs, being equal to approximately 120 rubles/MW∙h.

Objective:The application of information technology (IT( is fundamental in the hospitals to stay competitive.In this regard, recognizing the main risks to the implementation of IT in hospitals can provide vastopportunities to improve its efficiency and help to make strategic decisions. This study aimed tosearch for the main risks of implementation of IT projects in the hospitals of Tehran. Methods: This was a practical and cross-sectional study which was conducted in the 18 hospitals of Tehran,Iran, 2018; in which a sample of 65 members were studied. The required data were collected using a questionnaire to examine seven main risks, including market, project management, human resources, technical, organizational, financial, strategic risks. The collected data were analyzed using SPSS 19.0. Additionally, the method used to test the risks in this study was structural equation modeling, which was ran using LISREL 9.30. Results: The results showed that among the seven main risks of to the implementation of IT in hospitals, the highest and lowest means were related to the human resource risks and the market risks, respectively. Also, according to the SEM, human resource risks and market risks had the highest and lowest effects, respectively. Conclusion: Announcing the use of IT in the hospitals, holding conferences about new IT developments with employees, suitable training, encouraging them to use IT tools, providing a motivating atmosphere to use IT tools for employees, are a few effective ways of overcoming the human resource risks.

As the embedded device and internet of things (IoTs) concept prevalent in today's world, there is an increasing demand for the security and performance requirements on deploying these devices to private and public sectors. The crucial part of it is to protect privacy, confidentiality and integrity, meanwhile, maintain an adequate level of performance during transmission, storage and access of critical information. While the conventional cryptography methods, such as the Advanced Encryption Standard (AES), SHA$-$2 hashing method and RSA and Diffie Hellman for message authentication and identification, work well on systems which have reasonable processing power and memory capabilities. These do not scale well into a world with embedded systems and sensor networks, in conjunction with their nature of smaller size and lower cost. Thus, in the context of resource constrained device, lightweight cryptography methods are proposed to overcome many of the problems of conventional cryptography possessed. This includes constraints related to physical size, processing requirement, memory limitation, energy drain and production cost. This paper provides a survey of the architectures that are defined as replacements for conventional ciphers within an IoTs space and discuss some trends in the design of future lightweight algorithms. The performance metrics are carefully chosen to reflect and assess the suitability for embedded devices. The aim of this research is to identify the various performance metrics applied on different types of symmetric block ciphers especially lightweight ciphers and compare the results on versatile platforms with stream ciphers and public key methods. The comparative analysis on efficient LW cipher will be tested against other similar block ciphers on both MacBook Pro with Intel core and resource constrained device Raspberry Pi with ARM processor.

The move towards a new Circular Economy (CE) economic model has been advocated and supported in Portugal, however, there is limited research on this topic. To address this gap, a quantitative research based on an online survey was carried out among 99 Portuguese organizations, encompassing a wide range of sectors and sizes. The results show that CE is regarded as a strategic and relevant issue for profitability and value creation. Furthermore, the perception that it requires the adoption of new business models in addition to the classical “reduce, reuse, and recycle” approach is growing. Moreover, based on the hypotheses raised, results suggest that the level of CE adoption is positively impacted by the status of the EMS (Environmental Management System) certification and the willingness to improve the environmental performance and achieve a sustainable business model. However, CE activities are still relatively modest and a friendlier context (fiscal, legal, organizational, etc.) and the stronger support from supply chain agents and consumers are required. Future research should focus on how to design and shape the transition from a linear to a CE economy, and to ascertain if the positive attitude towards CE is materialized in changing the way business is done.

This paper aims to propose a new approach of territorial competitiveness assessment revisited from the resource-based view, as the combination of location-specific resources and capabilities can improve the territorial socio-economic development. A territorial competitiveness index is calculated in order to assess the potential of renewable energy sources to improve the sustainable development in islands. Different sources of information and methodologies have been employed to measure the variables included in the model, thus ensuring a rigorous process in the index calculation. In order to quantify the basic resources, for example, a methodology based on a multicriteria analysis (MCA) with geographic information system (GIS) is suggested, with the objective of obtaining an indicator called index of available territorial resources. This index synthesizes the map information through a numerical value that allows integrating the territorial resource with other indicators of the model. The results of the study show that capability development is a key factor to better exploit the territorial resource endowment in order to achieve a competitive advantage.

In this review, we explore a broad-based view of technologies for supporting human activities on the Moon. Primarily, we assess the state of life support systems technology beginning with physicochemical processes, waste processing, bioregenerative methods, food production systems and the robotics and advanced biological technologies that support the latter. We observe that the Moon possesses in-situ resources but that these resources are of limited value in CELSS – indeed, CELSS technology is most mature in recycling water and oxygen, the two resources that are abundant on the Moon. This places a premium on developing CELSS that recycles other elements that are rarified on the Moon including C and N in particular but also other elements such as P, S and K which might be challenging to extract from local resources. Although we focus on closed loop ecological life support systems, we also consider related technologies that involve the application of biological organisms to bioregenerative medical technologies and bioregenerative approaches to industrial activity on the Moon as potential future developments.

The physical and economic sustainability of using Built Environment Wind Turbine (BEWT) systems depends on the wind resource potential of the candidate site. Therefore, it is crucial to carry out a wind resource assessment prior to deployment of the BEWT. The assessment results can be used as a referral tool for predicting the performance and lifespan of the BEWT in the given built environment. To date, there is limited research output on BEWTs in South Africa with available literature showing a bias towards utility-scale or conventional ground based wind energy systems. This study aimed to assess wind power generation potential of BEWT systems in Fort Beaufort using the Weibull distribution function. The results show that Fort Beaufort wind patterns can be classified as fairly good and that BEWTs can best be deployed at 15m for a fairer power output as roof height wind speeds require BEWT of very low cut-in speed of at most1.2ms⁻¹.

The concept of green energy is now at the forefront of development discourse, with the United Nations Sustainable Development Goals (SDGs) 7, 11, and 12 all aimed at promoting green energy consumption to combat the three planetary crises: climate change, biodiversity loss, and pollution. Similarly, issues regarding Africa’s natural resource curse have caused a stir in the growth and development literature for some time now and there is no sign that it will die out. This study, the first of its kind, simultaneously assesses the impact of green energy consumption and Africa’s natural resources rents on economic growth by applying the Feasible Generalized Least Square (FGLS) estimator and the dynamic panel models of the Pooled Mean Group (PMG) and Mean Group (MG) estimators on data from 1990 to 2020 for 24 selected African countries. The results show that green energy consumption has a short-run growth-limiting effect and a long-run growth-enhancing effect in Africa. The study also found evidence of the natural resource curse phenomenon in Africa. The study, therefore, calls for the advancement and usage of green energy for both domestic and industrial production in Africa. The study further calls for a revamp in the global tax policy to curb illicit financial activities and strengthening institutional quality for transparency and accountability in the entire value chain of natural resource management in Africa.

This data descriptor summarizes the process applied and data gathered from 50 publications/papers reporting on the use of photography generated by tourists, tour operators and members of the public, with a particular focus on the crowdsourcing of photographs through online platforms and social networking sites (SNSs) as a method of research for wildlife conservation and ecotourism. The papers were collected in a systematic literature review to inform a pilot study of the feasibility of using SNSs to crowdsource georeferenced photographs of endangered Bornean Pygmy Elephants (Elephas maximus borneensis) taken by ecotourists along the Lower Kinabatangan River region of Sabah, Malaysia. Papers were sourced using the Murdoch University Findit online-search tool to search over 100 databases, including Proquest, Scopus and Web of Science. The criteria for a paper to be included in the review (and shared via the dataset attached to this this data descriptor) were that it was peer-reviewed, published in English, between 1997 and the 31 December 2017, had the full text accessible online and reported on a study or studies that utilized photographs that tourists, tour operators and/or members of the public generated and shared via SNSs or online platforms.

Crop production is a major livelihood activity of smallholders in Ethiopia. However, it is often characterized by low performance. In an effort to improve crop production, a series of agricultural extension programs have been running in Ethiopia since the 1950s. Nevertheless, the performance of agriculture is still low. In this study, it is argued that the limited attention given to cropland allocation methodologies is one of the major causes of low performance of crop production and increased environmental degradation. This study used linear programming to examine the role and impacts of cropland allocation methods on performance of crop production. The data for this study was drawn from household survey of 75 randomly selected households combined with focus-grouped discussion, key informant interview, and secondary data. In the current conventional cropland allocation, households were not able to meet their household consumption. The average profitability of farms under current practice was found significantly below than estimated optimal level of profit that could be realized using linear programming. In addition, it uncovered that low performance of crop production (in terms of meeting household consumption demand and profitability) is the primary cause that limited the effort of households to participate in environmental and natural resource management. This study suggests the use of linear programming-based cropland allocation to enhance the profit performance of smallholder crop production, meeting household consumption requirement, and thereby promote sustainable utilization of natural and environmental resources.

In this study, the resource blocks (RB) are allocated to user equipment (UE) according to the evolutional algorithms for long term evolution (LTE) systems. Particle Swarm Optimization (PSO) algorithm is one of the evolutionary algorithms, based on the imitation of a flock of birds foraging behavior through learning and grouping the best experience. In previous work, the Simple Particle Swarm Optimization (SPSO) algorithm was proposed for RB allocation to enhance the throughput of Device-to-Device (D2D) communications and improve the system capacity performance. In simulation results, with less population size of M = 10, the SPSO can perform quickly convergence to sub-optimal solution in the 100^th generation and obtained sub-optimum performance with more 2 UEs than the Rand method. Genetic algorithm (GA) is one of the evolutionary algorithms, based on Darwinian models of natural selection and evolution. Therefore, we further proposed a Refined PSO (RPSO) and a novel GA to enhance the throughput of UEs and to improve the system capacity performance. Simulation results show that the proposed GA with 100 populations, in 200 generations can converge to suboptimal solutions. Therefore, with comparing with the SPSO algorithm the proposed GA and RPSO can improve system capacity performance with 1.8 and 0.4 UEs, respectively.

Shrinking farm size and fragile farm resources pose a significant challenge to the sustainability of small-scale farms. Efficient resource utilization in small-scale farms is crucial to achieving farm sustainability through endogenous mechanisms. However, the precise mechanisms to integrate physical resources to achieve farm sustainability are not very clear yet. By capturing the interaction among farm resources as a network phenomenon, we identify the discrete resource interactions (RIs) in different types of small-scale farms of Indian Sundarbans, which are associated with higher farm sustainability. Thirty-two linkages, 11 reciprocal linkages, 22 triads, and three ‘core elements’ that occurred and cooccurred on highly sustainable farms are found to be critical in achieving farm sustainability. Using the properties of resource interaction networks as explanators of farm sustainability, we anticipate that sustainability in small-scale farms can be achieved by strategically creating new RIs on the farm. However, there may be limitations to such achievement depending on the nature of RI and type of farm. The analytical approach helps to understand the structural basis of sustainability in small-scale farms, and this approach can be used to achieve farm sustainability through the strategic integration of existing farm resources in the smallholder systems.

Facing unprecedented global declines in the extent and integrity of ecosystems, the 15^th UN Biodiversity Conference (COP-15) in Kunming, China, presents an opportunity for transformative change. However, a lack of consensus on two key issues – resource mobilization and Access and Benefit Sharing (ABS) associated with Digital Sequence Information (DSI) – risks stalling negotiations for an ambitious ‘Post-2020 Global Biodiversity Framework’ as the next 10-year strategic plan under the Convention on Biological Diversity. We highlight systemic misconceptions concerning the financing of biodiversity and the burden this places on the ABS system. In the context of DSI, we caution that conflating ABS with resource mobilization risks disrupting modern science policy built on open access, with potentially severe ramifications for scientific research and innovation. To resolve these tensions, we call for a recalibration of discussions on ABS in order to maximize the value delivered by biodiversity for all of society, including indigenous peoples and local communities.

A Twi-English parallel corpus is certainly an important resource for Machine Translation of Twi (ISO 639-3), a Low-Resource African Language (LRAL) which is mainly spoken in Ghana and Ivory Coast. Currently large-scale multi-domain Twi-English parallel corpus is still unavailable partly due to the difficulties and the arduous efforts required in its design. In this paper, we present TWIENG: a large-scale multi-domain Twi-English parallel corpus. We crawled the sentences from the web using web crawlers, translated, aligned, tokenized and compiled to create the corpus. We crawled English sentences from Ghanaian indigenous electronic news portals, Ghanaian Parliamentary Hansards, Twi Bible and crowdsourcing via google forms. The sentences were translated by professional translators and linguists, they were then aligned, tokenized and compiled. The corpus was curated using the sketch engine, a corpus manager and analysis software developed by Lexical Computing Limited. The corpus was manually evaluated by Twi professional linguists. The Corpus has 5,419 parallel sentences.

Diagnostics is believed to drive about 70% of medical interventions, but this may not be true for all demographics. With more than 30% of the African population living in extreme poverty ($1.9 per day - 2022); and healthcare costs competing unfavorably against unbridled access to antibiotics and herbal concoctions, especially in Sub-Saharan Africa, how do you convince such a people to choose diagnostics first? More importantly, how do you design a medical device targeted at meeting the diagnostic needs of this demographic? In developing diagnostic devices for such a market, what is worth sacrificing? How dire is the need for advanced technologies in devices developed for such a demographic? These are questions that remain unaddressed by the technological breakthroughs and current research in medical device development, especially for infectious disease diagnostics. The objective of this paper is to underscore critical concerns which must be considered in the bid to successfully design medical diagnostic devices for Africa and perhaps, other limited-resource settings. It is also written as a suggestive guidance document for researchers whose interest is in the development of infectious disease diagnostic platforms for rural Africa and similar limited-resource environments.

We propose a novel transfer learning method for speech emotion recognition allowing us to obtain promising results when only few training data is available. With as low as 125 examples per emotion class, we were able to reach a higher accuracy than a strong baseline trained on 8 times more data. Our method leverages knowledge contained in pre-trained speech representations extracted from models trained on a more general self-supervised task which doesn’t require human annotations, such as the wav2vec model. We provide detailed insights on the benefits of our approach by varying the training data size, which can help labeling teams to work more efficiently. We compare performance with other popular methods on the IEMOCAP dataset, a well-benchmarked dataset among the Speech Emotion Recognition (SER) research community. Furthermore, we demonstrate that results can be greatly improved by combining acoustic and linguistic knowledge from transfer learning. We align acoustic pre-trained representations with semantic representations from the BERT model through an attention-based recurrent neural network. Performance improves significantly when combining both modalities and scales with the amount of data. When trained on the full IEMOCAP dataset, we reach a new state-of-the-art of 73.9% unweighted accuracy (UA).

Exploiting the linguistic knowledge of the source language for neural machine translation (NMT) has recently achieved impressive performance on many large-scale language pairs. However, since the Turkish→English machine translation task is low-resource and the source-side Turkish is morphologically-rich, there are limited resources of bilingual corpora and linguistic information available to further improve the NMT performance. Focusing on the above issues, we propose a multi-source NMT approach that models the word feature in parallel to external linguistic features by using two separate encoders to explicitly incorporate linguistic knowledge into the NMT model. We extend the word embedding layer of the knowledge-based encoder to accommodate for each word’s linguistic annotations in the context. Moreover, we share all parameters across encoders to enhance the representation ability of the NMT model on the source language. Experimental results show that our proposed approach achieves substantial improvements of up to 2.4 and 1.1 BLEU scores in Turkish→English and English→Turkish machine translation tasks, respectively, which points to a promising way to utilize the source-side linguistic knowledge for the low-resource NMT.

The study was conducted in north wollo, south wollo and orimiya zone, in Eastern Amhara with an aim to assess the resource potential of Acacia seyal in the selected sites. The data from the selected sites were collected using point center quarter method. A total of 90 quadrates from nine study areas with plot size 50m*50m, (22.5ha) were systematically located along each transect, 100 m apart, and was spatially captured with the aid of GPS. At every sampling point, four quadrants (90 degrees) were created, using the transect line and a line perpendicular to it. Species composition Acacia seyal structure and its regeneration status, at points along transects were taken to analyze diversity and target species structure of the sites. The highest and least density of Acacia seyal ha^-1 were attained by Mehale mecharie (148) and Alene sefer (52). The highest shannon weiner diversity and species richness was observed in Alene sefer(Kemessie). Acacia seyal structure in all study sites showed an inverted J shape except lastie gerdao (Gubalafeto). Therefore, Acacia seyal deserves immediate conservation and appropriate management measures in order to get sustainable product and services from the species. Based on the results, awareness creation on the values and management of Acacia seyal, study on the management options of Acacia seyal for firewood, fuel wood, charcoal production and also investigation of gum production techniques of Acacia seyal for the sustainable use of the resource are recommended.

The world is progressing towards a more advanced society where end-consumers have access to local renewable-based generation and advanced forms of information and technology. Hence, it is in a current state of transition between the traditional approach to power generation and distribution, where end-consumers of electricity have typically been inactive in their involvement with energy markets and a new approach that integrates their active participation. This new approach includes the use of distributed energy resources (DER) such as renewable-based generations and demand response (DR), which are being rapidly adopted by end-consumers, where incentives are strong. This paper presents the role of DR aggregator to effectively integrate DER technologies as a new source of energy capacity, into the electricity networks using information communication technology and industry knowledge. This framework based on DR aggregators will facilitate renewable energy integration and customer engagement in electricity market efficiently. To this aim, advantages and disadvantages of DR aggregators are discussed in this paper from political, economic, social and technological (PEST) point of views. Based on this analysis, a strengths, weaknesses, opportunities, and threats (SWOT) analysis for a typical DR aggregator is presented.

Thousands of antibodies for diagnostic and other analytical purposes are on the market. However, it is often difficult to identify duplicates, reagent changes, and to assign the correct original publications to an antibody. This slows down scientific progress and might even be a cause of irreproducible research and a waste of resources. Recently, activities were started to suggest the sole use of recombinant antibodies in combination with the open communication of their sequence. In this case, such uncertainties should be eliminated. Unfortunately, this approach seems to be rather a long-term vision since the development and manufacturing of recombinant antibodies remain quite expensive in the foreseeable future. Also, nearly all commercial antibody suppliers may be reluctant to publish the sequence of their antibodies, since they fear counterfeiting. De-novo sequencing of antibodies is also not feasible today for a reagent user without access to the hybridoma clone. Nevertheless, it seems to be crucial for any scientist to have the opportunity to identify an antibody undoubtedly to guarantee the traceability of any research activity using antibodies from a third party as a tool. For this purpose, we developed a method for the identification of antibodies based on a MALDI-TOF-MS fingerprint. To circumvent lengthy denaturation, reduction, alkylation, and enzymatic digestion steps, the fragmentation was performed with a simple formic acid hydrolysis step. Eighty-nine unknown monoclonal antibodies were used for this study to examine the feasibility of this approach. Although the molecular assignment of peaks was rarely possible, antibodies could be easily recognized in a blinded test, simply from their mass-spectral fingerprint. A general protocol is given, which could be used without any optimization to generate fingerprints for a database. We want to propose that in most scientific projects relying critically on antibody reagents, such a fingerprint should be established to prove and document the identity of the used antibodies and to assign a specific reagent to a datasheet of a commercial supplier, a public database record or an antibody ID.

Microfluidics technology has not impacted the delivery and accessibility of point of care health services like diagnosis of infectious disease diagnosis, monitoring health or delivering interventions. Most microfluidics prototypes from academic research are not easy to manufacture with industrial scale fabrication techniques and cannot be operated without complex manipulations of supporting equipment and additives such as labels or reagents. We propose a label- and reagent-free inertial spiral microfluidic device to separate red blood, white blood and dendritic cells from blood fluid for applications in health monitoring and immunotherapy. We demonstrate that using larger channel widths in the range of 200 to 600 µm allows separation of cells into multiple streams according to different size ranges and we utilize a novel technique to collect the closely separated focused cell streams without constricting the channel. When tested on actual human blood cells, 77% of dendritic cells were separated and 80% of cells remained viable after our assay. Our contribution is a method to adapt spiral inertial microfluidic designs to separate more than two cell types in the same device which is robust against clogging, simple to operate and suitable for fabrication and deployment in resource-limited populations.

Based on the institutional theory and resource-based theory and the "institution-strategy-performance" research paradigm, this research explores the mechanism of institutional support on the innovation performance of new ventures, focusing on the mediating role of entrepreneurs and the moderating role of innovative resource acquisition. An empirical analysis based on 278 survey samples shows that: ① (formal/informal) institutional support positively affects the innovation performance of new ventures; ② entrepreneurial orientation plays an intermediary role between institutional support and innovation performance of new ventures; ③ innovation resource acquisition not only positively regulates the relationship between entrepreneurial orientation and innovation performance of new ventures, but also enhances the mediation of entrepreneurial orientation between institutional support and innovation performance. The conclusion shows that institutional support plays an important role in the innovation practice of new ventures, and can provide guidance for the innovation management practices of new ventures.

Organ transplantation centers set criteria for candidate qualification, which has led to disparate healthcare resource allocation practices affecting those with a substance use history. These individuals are denied organ transplants by committees and healthcare providers who assign them lower priority status. The lower priority argument claims that healthcare resources should not be provided equally to individuals failing to share responsibility for not doing enough in addressing the diseases associated with substance use. The purpose of this work is to explore the interrelatedness between the ethics of a merit-based system of moral responsibility and lower priority setting involved in healthcare resource allocation pertaining to those with substance use histories. An integral approach to the argument against the lower prioritists with a focus on the relationship between different organ allocation practices affecting substance users and the justification for resource allocation practices in healthcare and transplant committees. Lower priority setting is challenged, and an argument offered in which substance users are assigned higher priority when relying on “doing enough” in a merit-based system of moral responsibility. It is determined that one cannot substantiate assigning a lower priority status since a lack of success in rehab does not imply a lack of effort. Additionally, neither to confirmatory behavior, nor to non-conforming behavior may freedom be justifiably ascribed in a merit-based system of responsibility because freedom to choose can neither be established a priori, nor a posteriori with respect to meritorious behavior.

The Energy Return on Energy Invested, EROEI, is known as an important parameter for evaluating the efficiency of energy-producing technologies. In this paper we examine the concept of EROEI from a general viewpoint, giving insights on a wider range of applications. In general, natural resources can be seen as energy stocks characterized by a “potential” that can be exploited by creating intermediate stocks. This transformation is typical of dissipative systems and for the first time we found that Lotka-Volterra model, usually confined to the study of biology of populations, can represent a powerful tool to estimate EROEI for some such systems, providing an understanding of the reason for the overexploitation phenomenon and, in some cases, the collapse of the exploiting system.

Though innovations for sustainable management of natural resources have emerged over time, the rising demand for nature based health solutions and integration of endemic flora into global value chains could have adverse impacts on ecosystems. The ecological risks in the exploitation of wild medicinal plant resources are exacerbated by a myriad of agrotechnological risks and challenges that highly constrain their domestication. Successful exploitation and commercialization of medicinal plants thus require a clear understanding of their demand and production systems or value chain analysis. Accordingly there is need for innovative approaches towards their integration into global value chains. Since quality and safety, traceability, certification, as well as, consumer tastes and preferences are critical drivers in purchasing decisions by global consumers, they are inadvertently exploited to weaken Indigenous knowledge (IK), undermine common property rights and entrench value chains that favour a few elite buyers. This tend to create pervasive incentives for overexploitation of medicinal plant resources and environmental degradation. Potential solution lies in the recognition of drivers of vulnerability to environmental degradation and the innovative use of policy bricolage, feedback loops and interactions between knowledge, power and agency on one hand, and collective action and property rights institutions on the other hand. We conceptualise a framework that can mediate a transformational agenda and enhance systematic understanding of sustainability lenses in endemic medicinal plant resources value chains. This could in turn strengthen IK, enhance collective action and promote participation of local actors with positive impact on the utilisation and integration of endemic medicinal plant resources into global value chains.

We consider a general problem of optimal allocation of limited resources in a wireless telecommunication network. The users are divided into several different groups (or classes), which correspond to different levels of service. The network manager must satisfy these different users requirements. This approach leads to a convex optimization problem with balance and capacity constraints. We present several decomposition type methods to find a solution of this problem, which exploit its special features. We suggest to apply first the dual Lagrangian method with respect to the total capacity constraint, which gives the one-dimensional dual problem. However, calculation of the value of the dual cost function requires solution of several optimization problems. Our methods differ in approaches of solution of these auxiliary problems. We compare the performance of the suggested methods on several series of test problems. They show rather satisfactory convergence. Nevertheless, proper decomposition technique enhance the convergence essentially.

Water management can improve the quality of valuable ecosystem services but can be costly to implement and the management costs are covered by national taxes collected by water users. Based on 30 valuation studies of water quality improvement from the Environmental Valuation Information System (EVIS) database provided by Korea Environment Institute (KEI), a meta-regression analysis was employed to measure the benefits that major river basins provided to the society. We compare these benefits to the costs, namely River Management Funds (RMFs) which are financial resources to support a variety of projects for managing and improving upstream water quality. Based on benefit-cost comparison, this study evaluates the efficiency of water resource management in South Korea. This study also provides policy options that are helpful to maintain the sustainability of water resource by improving the planning and performance of water management in the long run.

Wildfires have impacted thousands of acres of forests in Arizona and New Mexico in recent years. The extensive damage has been partially attributed to the current forest condition where many once open stands now consist of dense stands of younger, unhealthy trees and buildups of forest fuels. In Arizona, land managers and community organizations developed the Four Forests Restoration Initiative (4FRI) to attempt to rectify the situation by thinning the forest while protecting wildlife and watershed resources. Integrated resource information and research are particularly important today with society’s increased demands for high quality water, healthy forests, sound fire management, and viable wildlife populations. However, many managers are not familiar with previous integrated watershed research in the Southwest that could provide a strong basis for current management decisions or as a basis for future research. New and modified prescriptions to manage the Southwest’s forest resources are vital to answer the threats of wildfires and insect infestations. Integrated forest resource management is necessary to meet the diverse needs of society and the land. The 4FRI plan raised many questions about the effects of silvicultural prescriptions on tree, wildlife, and water resources. The Beaver Creek, Thomas Creek, and Castle Creek watershed experiments all had goals of evaluating integrated resource management options and of providing managers and scientists with useful management information. Much of the knowledge gained in these programs can provide forest managers with a better, more holistic basis for future integrated management of the Southwest USA’s forests and woodlands. This paper reviews research on three watershed areas in Arizona where integrated resource management was successful.

Globally, groundwater is the largest distributed storage of freshwater and plays an important role in an ecosystem’s sustainability in addition to aiding human adaptation to both climatic change and variability. However, groundwater resources are dynamic and often change as a result of land usage, abstraction, as well as variation in climate. To solve these challenges, many conventional solutions, such as certain numerical techniques, have been proffered for groundwater modelling. The global evolution of the Internet of Things (IoT) has enhanced the culture of data gathering for the management of groundwater resources. In addition, efficient data-driven groundwater resource management relies hugely on information relating to changes in groundwater resources as well as their availability. At the moment, some studies in the literature reveal that groundwater managers lack an efficient and real-time groundwater management system that is needed to gather the required data. Additionally, the literature reveals that the existing methods of collecting data lack the required efficiency to meet computational model requirements and meet management objectives. Unlike previous surveys, which solely focussed on particular groundwater issues related to simulation and optimisation management methods, this paper seeks to highlight the current groundwater management models as well as the IoT contributions.

The River Basin Management Plan (RBMP) is an essential component of the European Union Water Framework Directive that details an integrated approach required to protect, improve and sustainably manage water resources. RBMP were intended to be produced for the periods 2009-2015, 2016-2021 and 2022-2027. However, after two years of delays in the development processes, the Republic of Ireland produced its first RBMP in 2010. The second RBMP cycle was also implemented in 2018 and is expected to run until the end of 2021 to give way to the third RBMP, whose consultation processes have been ongoing since December 2019. This paper contributes to the forthcoming RBMP by assessing stakeholders’ perspectives on the second RBMP through a desk-based review and by conducting interviews with nine institutions (14 interviewees). The qualitatively analysed interviews reveal a broad spectrum of actors associated with water management and governance in the Republic of Ireland through a three-tier governance structure that has been delivered (with amendment) through the first two RBMPs. Organisations such as the An Fóram Uisce|The Water Forum, the Environmental Protection Agency, the Local Authority Waters, and the Agricultural Sustainability Support and Advisory Programme have responsibilities designated in the RBMPs to deliver improved water quality, integrated catchment management, community engagement and awareness-raising. Trust has also been building up among these organisations and other agencies in the water sector. Despite these responsibilities and progress, the interviews identified communication lapses, ineffective collaboration and coordination among stakeholders and late implementation to be hampering the successful delivery of the second RBMP, in addition to significant pressures acting on water bodies from agricultural activities and urban wastewater treatment. Towards the third RBMP, the paper concludes that optimised water sector finance, enhanced and well-resourced communications, and improved stakeholder collaboration are needed to foster effective and efficient water services delivery and quality. More so, given the cross-cutting impact of the Sustainable Development Goals on water resources and the interconnected relations among the goals, the paper further recommends the integration of the SDGs in the various plans of actions and a co-benefits approach to derive the triple benefits from biodiversity, climate change initiatives and water quality measures.

Data on the seasonally dry tropical forests of Mexico have been examined in the light of statistical mechanics. The results suggest a division into two classes of species. There are drifting populations of a cosmopolitan class capable of existing in most dry forest sites; these have a statistical distribution previously only observed (globally) for populations of alien species. A high proportion of species found only at a single site are endemic and these prefer sites comparatively low in species richness.

Based on the Organizational Support Theory, this study examines the relationship between human resource management practices and service performance of sharing workers by demonstrating the mediation role of work engagement. We tested this theoretical model using an in-person interview questionnaire survey of 318 downwind drivers. Results showed that: (1) the main effect of human resource management practices of sharing workers on service performance was significant; (2) work engagement played a prominent mediation role between human resource management practices and service performance of sharing workers; (3) the mediation role of employee vigor between the platform incentives and the performance of employee services was significant; (4) employee dedication had an obvious and indirectly positive mediating effect between sharing workers' dimensions of human resource management practice and their service performance; (5) employee absorption on the mediation role between the various dimensions of the sharing human resources management practices (platform support, platform incentives and platform constraints) and employee service performance was significant. This study has important value for the study on human resource management practices in the context of sharing economy, and provides practical enlightenment for employee management of the sharing economy platform.

The optimization of the production process of metal mines has been traditionally driven only by economic benefits while ignoring resource efficiency. However, it has become increasingly aware of the importance of resource efficiency since mineral resource reserves continue to decrease while the demand continues to grow. To better utilize the mineral resources for sustainable development, this paper proposes a multi-objective optimization model of the production process of metal mines considering both economic benefits and resource efficiency. Specifically, the goals of the proposed model are to maximize the profit and resource utilization rate. Then, the fast and elitist Non-Dominated Sorting Genetic Algorithm (NSGA-II) is used to optimize the multi-objective optimization model. The proposed model has been applied to the optimization of the production process of a stage in the Huogeqi Copper Mine. The optimization results provide a set of Pareto-optimal solutions that can meet varying needs of decision makers. Moreover, compared with those of the current production indicators, the profit and resource utilization rate of some points in the optimization results can increase respectively by 2.99% and 2.64%. Additionally, the effects of the decision variables (geological cut-off grade, minimum industrial grade and loss ratio) on objective functions (profit and resource utilization rate) were discussed using variance analysis. The sensitivities of the Pareto-optimal solutions to the unit copper concentrate price were studied. The results show that the Pareto-optimal solutions at higher profits (with lower resource utilization rates) are more sensitive to the unit copper concentrate prices than those obtained in regions with lower profits.

In the past decade, we have witnessed a dramatically increasing volume of data collected from varied sources. The explosion of data has transformed the world as more information is available for collection and analysis than ever before. To maximize the utilization, various machine and deep learning models have been developed, e.g. CNN [1] and RNN [2], to study data and extract valuable information from different perspectives. While data-driven applications improve countless products, training models for hyperparameter tuning are still time-consuming and resource-intensive. Cloud computing provides infrastructure support for the training of deep learning applications. The cloud service providers, such as Amazon Web Services [3], create an isolated virtual environment (virtual machines and containers) for clients, who share physical resources, e.g., CPU and memory. On the cloud, resource management schemes are implemented to enable better sharing among users and boost the system-wide performance. However, general scheduling approaches, such as spread priority and balanced resource schedulers, do not work well with deep learning workloads. In this project, we propose SpeCon, a novel container scheduler that is optimized for shortlived deep learning applications. Based on virtualized containers, such as Kubernetes [4] and Docker [5], SpeCon analyzes the common characteristics of training processes. We design a suite of algorithms to monitor the progress of the training and speculatively migrate the slow-growing models to release resources for fast-growing ones. Specifically, the extensive experiments demonstrate that SpeCon improves the completion time of an individual job by up to 41.5%, 14.8% system-wide and 24.7% in terms of makespan.

Starting from the fact that the units of local self-government of the Republic of Serbia are not sufficiently oriented towards innovations related to human resources and the environment, the application of quantitative research tradition examines the positioning and understanding of certain procedures and decisions of human resources management regarding the functioning of the environmental protection system, on the one hand, and future strategies for changing the given system, on the other. A series of 105 face-to-face interviews were conducted during the whole of 2016 in 105 of the 191 municipalities in the Republic of Serbia. Examination of the attitudes of the local self-government was carried out using a specially designed closed electronic questionnaire. The results of the multivariate regressions show that the most important predictor of the possible improvement of the environment is the size of the municipality. The remaining variables (e.g., human resources policy, human resources service) did not have significant effects on the ability to improve the environment. In more than half of local self-governments, there was no clearly defined human resources strategy in the field of environmental protection, an environmental protection service, an Environmental Action Plan, as well as an employment plan for waste management in local governments, etc. The research has shown that top managers of local governments agree that the management of human resources in environmental protection represents a significant opportunity to improve the quality of the environment. The results of the research can be used to improve the organization of human resource competence in environmental protection and the quality of a working and sustainable environment in the area of local self-government.

In this article, management control has been studied from the perspective of intention towards sustainable development of companies. The main idea focuses on the analysis of relations between sustainable management control and the system of performance appraisal using as a reference the resource-based theory. These relations have been assessed both theoretically by reviewing literature in the field, and empirically based on data collected in a questionnaire from top management, as well as data from Annual Reports from the main segment of Bucharest Stock Exchange. The authors have shown that financial performance has a significant influence on management control, and the return on capital employed is one of the most recommended indicators. The sustainable nature attributed to management control is the result of institutional theory evolution, provisions of Directive 2014/95/EU and Guide of Global Management Accounting Principles (2015) using stewardship. Consequently, profits are not the main element any more in the assessment of financial „health” of a company. To ensure the sustainable success, sustainable balanced scorecard is one of real measures for managing financial and non-financial performance.

This paper discusses the use of a participatory approach to assess the level of understanding of the Water-Energy-Climate Change nexus in South Africa. The aim is to facilitate the development of well-coordinated, systematic, and holistic strategies for efficient management of the nexus and its implications in the country. The assessment was guided by the broader Integrated Water Resource Management framework, which promotes a participatory approach in the administration of water resources. The paper argues that despite the reasonable level of understanding of WECC, there is still a lack of integrated policy development and planning among key stakeholders. This is exacerbated by limited coordination and consultation among these stakeholders, particularly policymakers. This necessitates the urgent adoption of holistic and systems thinking approaches, and the promotion of collaboration among different stakeholders mandated to manage WECC sectors. Until such approaches are adopted, the WECC nexus will continue to impede the country’s socio-economic development and environmental wellbeing.

The employee turnover literature to date is teeming with process models that assume only organizational and personal factors contribute to employees’ intentions to leave and stay. However, with the average percentage variance explained still only around 50%, it is clear that other factors play a substantial role in these decision-making processes. One possible explanation is to explore the unique role that clients play in employees’ intentions to stay or leave. This paper extends the conceptualization of the role that clients play on employee’s intentions to stay and leave their roles, particularly within service industries such as health care. This paper presents the results of two qualitative studies that examine employees’ decision-making process for turnover and retention intentions. The first study explores the factors influencing employees’ intentions to stay and leave the Australian aged care sector (N = 420) and the second study explores prison health care nurses in the United States (N = 175). The results of both studies reveal that client-related factors affect the choice to stay within a job and, in some cases, are the favoured aspect of the role. Therefore encouraging client-staff relationships will expand job satisfaction and therefore increase retention of employees within both contexts.

A nonrenewable resource extraction game model is analyzed in a differential game theory framework with random duration. If the c.d.f. of the final time is discontinuous, the related subgames are differentiated based on the position of the initial instant with respect to the jump. We investigate properties of optimal trajectories and of imputation distribution procedures if the game is played cooperatively.

It is known that the elastic characteristics of polyamides change with increasing temperature, in particular, the Young's modulus decreases significantly. This fact is practically not taken into account in design calculations of metal-polymer plain (MP) bearings, operating under conditions of the boundary and dry friction. The purpose of the study is the analysis of the effect of temperature on the change of the Young's modulus and, accordingly, the contact strength and triboresource according to the developed method of calculating MP bearings. MP bearings with a bushing made of polyamide PA6 reinforced with glass or carbon dispersed fibers were investi-gated. Quantitative and qualitative regularities of change of the maximum contact pressures and resource of the bearings at temperature increase under conditions of boundary and dry friction are established. The pressures in the bearing bushing made of PA6+30GF will be lower than for the bushing made of PA6+30CF. The resource of the bushing made of PA6+30CF will be significantly greater than for PA6+30GF. For thermoplastic polymers, the increase in temperature will have a useful practical effect due to the decrease in the rigidity of the polymer composites of the bearing bushing.

The goods and services produced by forest and vegetation ecology system is the power by which human society can be promoted fast in high-quality and sustainable way. With the increase of population and economic development in water-limited regions, there is an increasing demand for the quantity and variety of forest vegetation ecosystem products and services. To meet the demands of this situation, most of the original forest has changed into farmland, non-native forest and grass land. As a result, water-plant relationship changed from equilibrium to non-equilibrium, which led to soil drought, soil degradation and vegetation decline in dry years or waste of soil water in rainy years in most of water-limited regions. In order to solve the questions and realize the sustainable utilization of soil water resources and the high quality and sustainable development of social economy, it is necessary to apply the utilization limit theory of soil water resources by plants and the theory of soil water carrying capacity for vegetation to adjust the relationship between plant growth and soil moisture to obtain the maximum yield and benefit of vegetation and serve high-quality and sustainable development.

Wild Chinese prickly ash with elevated antioxidants is a valuable genetic resource for Zanthoxylum bungeanum Maxim improvement. There are rich wild germplasm resources in the Qinling Mountains. In a study with wild germplasm resources from different altitudes and six cultivated varieties, the phenolic and flavonoid compounds were analyzed by high performance liquid chromatography (HPLC). The chromatograms of them were basically the same, although their chemical composition content was greatly different. The thirty samples were divided into three categories through the hierarchical clustering analysis. And catechin, hyperoside and quercitrin were considered to be key compound for the quality evaluation, by contrast, the wild samples with an altitude of 2300±50 m (Ⅳ group) had the highest content of key compounds, and showed stronger antioxidant activity and antibacterial ability, indicating that these wild samples could be used as an excellent breeding resource. This is the first time to evaluate the quality of wild Chinese prickly ash in different altitude areas of Qinling Mountains. These excellent wild germplasm resources provided substantial potential accessions for use directly in Chinese prickly ash breeding programs.

The resource curse indicates that economic growth performs poorly in countries with significant natural resources. Nevertheless, certain countries rich in energy managed to protect their resource riches in the long run. It is necessary to enforce effective policies in resource-rich countries to fully leverage the advantages which can come from the abundance of natural resources. This study aimed to evaluate how oil-rich countries would avoid resource flows by successful fiscal and management policies. By taking the guidance of Norway and implementing fiscal policy focused on tax rules on its oil management, it is proposed that oil-exporting countries benefit significantly. The framework attempts to mitigate this resource curse and utilise oil revenues in the interest of the country.

An effective empirical statistical method is developed to improve the process of mineral resource estimation of seabed polymetallic nodules and is applied to analyse the abundance of seabed polymetallic nodules in the Clarion Clipperton Zone (CCZ). The newly proposed method is based on three hypotheses as the foundation for a model of “Idealized Nodules”, which was validated by analysing nodule samples collected from the seabed within the Tonga Offshore Mining Limited (TOML) exploration contract. Once validated, the “Idealized Nodule” model was used to deduce a set of empirical formulae for predicting the nodule resources, in terms of Percentage Coverage and Abundance. The formulae were then applied to analysing a total of 188 sets of nodule samples collected across the TOML areas, comprising box-core samples and towed camera images collected by one of the authors and detailed in [4]. The analysis also relies upon detailed box-core sample measurements from other areas reported by [7]. Numerical results for resource prediction were compared with field measurements, and reasonable agreement has been achieved. The new method has the potential to achieve more accurate mineral resource estimation with reduced sample numbers and sizes. They may also have application in improving the efficiency of design and configuration of mining equipment.

Market turbulence with fiscal investment influences has altered IT infrastructure performance as business pursue extravagant new technology adoption. Yet, few studies have examined how shareware solution goes beyond Medium Size Enterprise that pushes efficiency and sustainability. This PLS-SEM integrated with dual primary compilation approach lessens shallow perceptions coupled with outlooks that streamline each phenomenal activity that is worthy of the necessity for competitive innovation. This unified model was applied to sampling respondents and analyzed using an ordinal regression relationship that generates a robust association that triggers the hypothesis acceptance. The adopting of BOINC shareware mesh network towards unified processing designs that were employed to build the yield by promising financial possibility using coordinated interworks hence improved group accomplishment and establishing greater esteem. This paper showcases a flexible inner IT infrastructure alongside the economic uncertainty with the framework advancement for Exostructure as a Service. Associated theoretical and practical implications were discussed.

In scenarios such as natural disasters and military strike, it is common for unmanned aerial vehicles (UAVs) to form groups to execute reconnaissance and surveillance. To ensure the effectiveness of UAV communications, repeated resource acquisition issues and transmission mechanism design need to be addressed urgently. In this paper, we build an information interaction scenario in a Flying Ad-hoc network (FANET). The data transmission problem with the goal of throughput maximization is modeled as a coalition game framework. Then, a novel mechanism of coalition selection and data transmission based on group-buying is investigated. Since large-scale UAVs will generate high transmission overhead due to the overlapping resource requirements, we propose a resource allocation optimization method based on distributed data content. Comparing existing works, a data transmission and coalition formation mechanism is designed. Then the system model is classified into graph game and coalition formation game. Through the design of the utility function, we prove that both games have stable solutions. We also prove the convergence of the proposed approach with coalition order and Pareto order. Binary log-linear learning based coalition selection algorithm (BLL-CSA) is proposed to explore the stable coalition partition of system model. Simulation results show that the proposed data transmission and coalition formation mechanism can achieve higher data throughput than the other contrast algorithms.

The reversible computation paradigm aims to provide a new foundation for general classical digital computing that is capable of circumventing the thermodynamic limits to the energy efficiency of the conventional, non-reversible paradigm. However, to date, the essential rationale for and analysis of classical reversible computing (RC) has not yet been expressed in terms that leverage the modern formal methods of non-equilibrium quantum thermodynamics (NEQT). In this paper, we begin developing an NEQT-based foundation for the physics of reversible computing. We use the framework of Gorini-Kossakowski-Sudarshan-Lindblad dynamics (a.k.a. Lindbladians) with multiple asymptotic states, incorporating recent results from resource theory, full counting statistics, and stochastic thermodynamics. Important conclusions include that, as expected: (1) Landauer's Principle indeed sets a strict lower bound on entropy generation in traditional non-reversible architectures for deterministic computing machines when we account for the loss of correlations; and (2) implementations of the alternative reversible computation paradigm can potentially avoid such losses, and thereby circumvent the Landauer limit, potentially allowing the efficiency of future digital computing technologies to continue improving indefinitely. We also outline a research plan for identifying the fundamental minimum energy dissipation of reversible computing machines as a function of speed.

The aim of this study is to investigate “resource portfolios” and total capital, as well as the degree of those resources capitalization, which representatives of different social classes in the modern Latvia have at their disposal. The amount and structure of “resource portfolio” and total capital of different social classes studied using the resource-asset-capital approach. The article presents results of the sociological survey of social stratification in modern Latvia on the example of its one region – Latgale (2019, n = 798, representative sample of the adult population), identifying social classes based on two objective (income and education) and one subjective (self-identification of respondents) criteria. Based on the example of the lower working class and the middle class, the authors proved that representatives of these polar social classes have a total capital of different amount, which is determined by two main reasons: 1) the lower working class has statistically significantly smaller “resource portfolio” than the middle class; 2) the lower working class is not so successful as the middle class in activating the resources at their disposal, turning them into their capital. These statistically significant two-level differences have to be considered when pursuing social policies on reducing differences between social classes.

The search algorithm based on symbiotic organisms’ interactions is a relatively recent bio-inspired algorithm of the swarm intelligence field for solving numerical optimization problems. It is meant to optimize applications based on the simulation of the symbiotic relationship among the distinct species in the ecosystem. The modified SOS algorithm is developed to solve independent task scheduling problems. This paper proposes a modified symbiotic organisms search based scheduling algorithm for efficient mapping of heterogeneous tasks to access cloud resources of different capacities. The significant contribution of this technique is the simplified representation of the algorithm's mutualism process, which uses equity as a measure of relationship characteristics or efficiency of species in the current ecosystem to move to the next generation. These relational characteristics are achieved by replacing the original mutual vector, which uses an arithmetic mean to measure the mutual characteristics with a geometric mean that enhances the survival advantage of two distinct species. The modified symbiotic organisms search algorithm (G_SOS) aimed to minimize the task execution time (Makespan), response, degree of imbalance and cost and improve the convergence speed for an optimal solution in an IaaS cloud. The performances of the proposed technique have been evaluated using a Cladism toolkit simulator, and the solutions are found to be better than the existing standard (SOS) technique and PSO.

This study analyses the case study of a deconstruction project called the ‘Whole House Reuse’ (WHR) which aimed, firstly, to harvest materials from a residential house, secondly, to produce new products using the recovered materials, and thirdly, to organize exhibition for the local public to promote awareness on resource conservation and sustainable deconstruction practices. The study applies characterization of recovered materials through deconstruction. In addition to the material recovery, the study assesses the embodied energy saving and greenhouse gas emission abatement of the deconstruction project. Around twelve tonnes of various construction materials were harvested through a systematic deconstruction approach, most which would otherwise be disposed to landfill in the traditional demolition approach. The study estimates that the recovered materials could potentially save around 502,158MJ of embodied energy and prevent carbon emission of around 27,029kg (CO2e). Deconstruction could eventually contribute to New Zealand’s national emission reduction targets. In addition, the project successfully engages local communities and designers to produce 400 new products using the recovered materials and exhibited to the local people. The study concludes that there is a huge prospect in regard to resource recovery, emission reduction, employment and small business opportunities using deconstruction of the old house. The socio-cultural importance of the WHR project is definitely immense; however, the greater benefits of such projects are often ignored and remain unreported to wider audiences as most of the external and environmental costs have not been considered in the traditional linear economy. It is acknowledged that under a favourable market condition and with appropriate support from local communities and authorities, deconstruction could contribute significantly to resource conservation and environmental protection despite its requirement of labour intensive efforts.

Cloud computing nowadays is not an emerging topic, and virtualization is an indispensable technology to expedite cloud computing to become the next sign of the coming Internet revolution. In real life, scientists never stop at exploring the possibilities from such technology by investigating millions of experiments and applications to enhance the quality of virtual services. However, isolated construction for the virtual machine doesn’t save the technology from unwanted data volumes or insensitive processing time. Containers are created to address such problems, by distributing applications without initiating the entire virtual machine. Docker, as an important player in this game, is an open-source application of the container family. The management tool from Docker containers, Swamskit, does not take heterogeneities in either virtualized containers or physical nodes. There are different nodes in the cluster, and each node is different in configurations, resource availability, or concerning resource, etc. Furthermore, the requirements initiated by different services change all the time. The demand might be CPU-intensive (e.g. Clustering services) and also memory-intensive (e.g. Web services), or completely at the opposite. In this paper, we focus on exploring the Docker container cluster and designing, DRAPS, a resource-aware placement scheme, to improve the system performance in a heterogeneous cluster.

Petrochemicals, which convert oil and gas into products such as plastics, are fundamental to modern societies. Chemists recognize their role in the design of materials and the adverse effects that these may have on the environment, preventing sustainable development. Several methodological frameworks and sustainability assessment approaches have been developed to evaluate the resources used in the petrochemical sector in terms of environmental costs. A combination of Life Cycle Assessment and Emergy Accounting - to assess the environmental support for resource use - is applied in this study of the PET production chain in Europe. The Unit Emergy Values of several intermediates are calculated or updated to facilitate discernment of the quality of energy used and the processes' efficiency. Several routes for synthesizing renewable para-xylene and ethylene glycol from biomass are discussed and confronted with the efforts focused on recycling and recovering the final product providing concurrently a procedure and a valuable data set for future CP actions. The results show that understanding the efficiencies changing across the production chain may help stakeholders make wise choices as to where and when interventions to promote a circular economy are most effective along a petrochemical production chain.

We present improvements in n-best rescoring of code-switched speech achieved by n-gram augmentation as well as optimised pretraining of long short-term memory (LSTM) language models with larger corpora of out-of-domain monolingual text. In addition, we consider the application of large pretrained transformer-based architectures. Our experimental evaluation is performed on an under-resourced corpus of code-switched speech comprising four bilingual code-switched sub-corpora, each containing a Bantu language (isiZulu, isiXhosa, Sesotho, or Setswana) and English. We find in our experiments that, by combining n-gram augmentation with the optimised pretraining strategy, speech recognition errors are reduced for each individual bilingual pair by 3.51% absolute on average over the four corpora. Importantly, we find that even speech recognition at language boundaries improves by 1.14% even though the additional data is monolingual. Utilising the augmented n-grams for lattice generation, we then contrast these improvements with those achieved after fine-tuning pretrained transformer-based models such as distilled GPT-2 and M-BERT. We find that, even though these language models have not been trained on any of our target languages, they can improve speech recognition performance even in zero-shot settings. After fine-tuning on in-domain data, these large architectures offer further improvements, achieving a 4.45% absolute decrease in overall speech recognition errors and a 3.52% improvement over language boundaries. Finally, a combination of the optimised LSTM and fine-tuned BERT models achieves a further gain of 0.47% absolute on average for three of the four language pairs compared to M-BERT. We conclude that the careful optimisation of the pretraining strategy used for neural network language models can offer worthwhile improvements in speech recognition accuracy even at language switches, and that much larger state-of-the-art architectures such as GPT-2 and M-BERT promise even further gains.

Integrated landscape approaches (ILA) aim to reconcile multiple, often competing, interests across agriculture, nature conservation, and other land uses. Recognized ILA design principles provide guidance for their implementation, yet application remains challenging, and a strong performance evidence-base is yet to be formed. A comprehensive literature review and focus group discussions with practitioners identified considerable diversity of ILA in actors, temporal, and spatial scales, inter alia. This diversity hampers learning from and steering these integrated planning approaches because of its intractable nature. Therefore, we developed a tool—an ‘ILA mixing board’—to structure the complexity of ILA into selectable and scalable attributes in a replicable way to allow planning, diagnostics, and comparative assessment of ILA. The ILA mixing board tool presents seven qualifiers, each representing a key attribute of ILA design and performance such as project flexibility, inclusiveness of the dialogue, and the centrality of the power distribution. Each qualifier has five (non-normative) outcome indicators that can be registered as present or absent. This process in turn guides planners, evaluators and other participating stakeholders involved in landscape management to diagnose the ILA type, and or its performance. We apply the ILA mixing board as a diagnostic tool to three ILA cases in Nicaragua, Madagascar, and the Congo Basin to show some of the many possible configurations of qualifiers on the mixing board. Overall, the tool allows comparative analyses of the complexity of ILA in a structured and manageable way.

There is a balanced plant-water relationship in the primary vegetation of desert area. With the increase of population and social development in desert areas, people’s need for forest vegetation ecosystem’s goods and service have been changed. To meet the growing demand for plant community goods and services, more original vegetation has been changed into non-native vegetation such as in China loess plateau. However, with the plant growth, sometime soil drying happens and then becomes gradually serious with times in most of desert regions. Serious drying of soil eventually result in soil degradation, vegetation decline and agriculture failure，which influence the produce and supply of forest vegetation goods and service in market in dry year or waste of soil water resources in wet year, which wastes precious nature resources. In order to solve these problems, the soil water resources have to be used in sustainable way and plant-water relationship have to be regulated on Carrying Capacity of Soil Water for Vegetation in the key period of plant water relationship regulation, to carry out sustainable use of nature resources, high-quality and sustainable development of forest and grass or high-quality produce of fruit and crop in desert re-gions.

We examine how external triggers, including the digital imperative and the need for more sustainable resource and stakeholder employment, spark the development of transformative sustainable business models. Drawing on the resource-based view and the shared value approach we conceptualize a multifaceted framework that helps to identify key determinants and coherent layers of transformative sustainable businesses models. Our theoretical arguments integrate recent research findings on external dynamics, such as digital technological advances and rising global competitive dynamics, with internal capabilities on both the organizational and the individual level, allowing for a more complete understanding of transformative potentials on the firm level. We propose that key determinants of sustainable transformative business models adhere to both, innovative value-creating reconstructionist and sustainable shared-value logic, and include elements such as co-creation with customers, usage-based pricing, agile and adaptive behavior, closed-loop resource employment, asset-sharing, and collaborative business ecosystems. At the same time, organizational, economic, and environmental layers encompassing sustainable business models need to be both horizontally and vertically coherent to unfold their full potential.

In the design of multi-loop Networked Control Systems (NCSs) wherein each control system is characterized by heterogeneous dynamics and associated with certain set of timing specifications and constraints, appropriate metrics need to be employed for the synthesis of control and networking policies to efficiently respond to the requirements of each control loop. Majority of the design approaches for sampling, scheduling and control policies include either time-based or event-based metrics to perform pertinent actions in response to the changes of the parameters of interest. We specifically focus in this article on Age-of-Information (AoI) as a recently-developed time-based metric and threshold-based triggering function as a generic event-based metric. As the NCS model, we consider multiple heterogeneous stochastic linear control systems that close their feedback loops over a shared-resource communication network. We investigate the co-design across the NCS, and discuss the pros and cons with AoI and ET approaches in terms of asymptotic control performance measured by linear-quadratic Gaussian (LQG) cost functions. In particular, sampling and scheduling policies combining AoI and stochastic event-triggered metrics are proposed. It is argued that pure AoI functions that generate decision variables solely upon minimizing the average age irrespective of control systems dynamics may not be able to improve the overall NCS performance even compared with pure randomized policies. Our theoretical analyses are successfully validated through several simulation scenarios.

Recruitment is a fundamental aspect of Human Resource Management to drive organizational performance. Traditional recruitment processes, with manual stages, are time-consuming and inefficient. Artificial Intelligence (AI), which demonstrates its potential in various sectors such as healthcare, education and notable cases of ChatGPT, is currently reshaping recruitment by automating tasks to improve efficiency. However, in Thailand, where there is a growing demand for talents, the application of AI in recruitment remains relatively limited. This research focuses on human resources (HR) and recruitment professionals in Thailand, aiming to understand their perspectives on the integration of AI in recruitment. It extended the Unified Theory for Acceptance and Use of Technology (UTAUT) model, customized to suit the specific requirements of Thai recruitment practices. The study explores the factors influencing users' intention to adopt AI in recruitment. Survey questionnaire items were created based on prior literatures and refined with insights from HR and recruitment experts to ensure applicability in the context of recruitment in Thailand. A survey involving 364 HR and recruiting professionals in Bangkok metropolitan area supplied comprehensive responses. The research reveals that several factors, including Perceived Value, Perceived Autonomy, Effort Expectancy, and Facilitating Conditions, significantly impact the intention to adopt AI for recruitment. While Social Influence and Trust in AI Technology do not have a direct influence on intention, Social Influence directly affects Perceived Value. Trust in AI Technology positively influences Effort Expectancy. This study provides valuable benefits for HR and recruitment professionals, organizations and AI developers by offering insights into AI adoption and sustainability, enhancing recruitment processes and promoting the effective use of AI tools in this sector.

Project managers should balance a variety of resource elements in building projects while taking into account many major concerns, including time, cost, quality, risk, and the environment. This study presents a framework for resource trade-offs in project scheduling based on the Building Information Modeling (BIM) methodology and metaheuristic algorithms. First, a new metaheuristic algorithm called Fire Hawk Optimizer (FHO) is used. Using project management software and the BIM process, a 3D model of the construction is created. In order to maximize quality while minimizing time, cost, risk, and CO2 in the project under consideration, an optimization problem is created, and the FHO's capability for solving it is assessed. A predefined stopping condition is taken into account while doing 30 independent optimization runs to obtain the statistical metrics, such as the mean, standard deviation, and the required number of objective function evaluations. The results show that the FHO algorithm is capable of producing competitive and exceptional outcomes when it comes to trade-off various resource options in projects.

Background: With new challenges to the health system, many new competencies within the scope of teaching public health need to be addressed in medical schools’ curricula such as disaster risk management and health system science. The aims of this study were to identify the needs of public health competencies for medical doctors in Thailand and to assess the level of integration for technical collaboration in teaching public health. Method: A total of 17 out of 21 Thai medical schools participated in the national survey. Qualitative inquiries applied focus group interviews of community representatives from ten sample villages and in-depth interviews of representatives from stakeholder organizations particularly employers. The list of public health competencies framework recommended by WHO-SEARO was applied. Quantitative analysis applied descriptive analysis using STATA 15 and qualitative findings were validated by interrelating the meaning of themes from Word Clouds created in NVivo12. Data integration applied a mixed-method Quan-qual approach. Results: 17 medical schools returned the questionnaires (80.95 % yield). The most common regionally-defined public health competencies (in over 70% of schools) were shown to be: Biostatistics, Community Medicine, Epidemiology, Family Medicine, Medical Ethics and Professional Laws, Preventive Medicine, Health Promotion, Holistic Care, and Research. The curriculum in only one medical school lacked Health Economics, whilst Disaster Management was lacking in two other schools. Discipline-based subjects were found to be more prevalent than interdisciplinary competencies. A variety of methods were being applied for teaching public health. The majority of the schools applied lecture as the main teaching method and multiple-choice questions as the main assessment method. Thai communities expect the doctors to get in touch with the community more often, lead the primary health care team through training the health professionals and community health volunteers, and educate the community for better health. Conclusion: Human resource is the main challenge in addressing interdisciplinary competencies. It is necessary to establish a collaborating mechanism among the big and small medical schools and the faculties of public health to improve the teaching of public health to undergraduate students in medical schools. There is also a need to strengthen the health system science and leadership so that future MDs can lead health service delivery according to the needs of their employers such as the Ministry of Public Health and the Rural Doctors Association. The findings of this study may help to identify a national framework of public health core competencies for medical schools and create a common platform for interdisciplinary collaborations.

In the context of the pandemic caused by Covid-19, an important aspect that was affected and changed was the way people communicate. Communication efficiency can be improved by using modern technologies, for example: mobile devices, digital audio and video platforms, text platforms, social media and more. For further economic success, digital skills are needed not only for executives, but also for managers, in order to be able to lead teams and avoid situations of stress and tension in the virtual environment. This scientific paper includes a primary research of how the pandemic affected the communication at the workplace. For this a qualitative analysis was first performed, in which the interview was used as a working tool. Next, on the basis of a questionnaire, a hypothesis was formulated and validated afterwards through multiple linear regression. This research highlighted the particularly important role of communication and, in this context, the role of the remote team leader. In order to keep the team motivated and interested in the virtual environment, the manager must use modern tools to motivate, support and express his appreciation when the team, respectively the members of his team, achieve their goals successfully.