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Performance measurement refers to the systematic evaluation and analysis of the performance and results of business processes, initiatives, or strategies. This study discusses the crucial role of communication using signaling theory in employer branding in the context of the social economy organization (SEO). The aim is to measure employee satisfaction in concrete terms and to determine the status quo of the communication culture of the organization under investigation in order to develop an employer branding strategy based on the results. The authors use an employee survey as a quantitative research method and limit the data collection to the EU member state of Germany considering the research background. The results provide insights into the specific communication policy in relation to employer branding. The focus here is on (digital) communication. Organizations need to understand how communication strategies directly influence the perception of the employer brand in the social economy. Furthermore, practical implications are derived in order to increase employer attractiveness. Concrete recommendations of action for SEOs should help them be successful in the competition for qualified specialists and talent. [ABSTRACT FROM AUTHOR]

This paper will explicate ways in which Aboriginal Australian economy can inform, augment, and vindicate Catholic social teaching and related scholarship on work, the use of technology, and leisure. Collaterally, Aboriginal Australian economy gives an example of what could happen if key parts of Catholic social teaching were to be implemented concretely. That is, we can argue that Aboriginal economy gives an indication of what a society would be like if it adopted these parts of Catholic social teaching. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic presented what, on both global and national levels, has arguably so far been the most extensive health, economic and social challenge of the 21st century. Responding to this challenge, it soon became clear that, while having a vital role in the contextual provision of necessary services, public authorities also needed to engage with organizations in the voluntary, community sector, including Faith-Based Organizations (FBOs). This article presents and discusses and analyzes a digest of research and resource evidence from the beginning of 2020–to the end of 2023 concerning the organizational, financial and human contributions of and impacts of the COVID-19 pandemic on, in particular, Christian FBOs in Great Britain. It goes on to analyze these contributions and impacts within the analytical framework of what it calls a wider "Christian ecology" as the context within which such FBOs live, to which they contribute, and, as argued by this review, apart from which they cannot be properly understood. Finally, in exploring some of the lessons to be learned from the evidence and analysis presented, the article identifies and considers some key opportunities and issues that arise at the interface between the work of (especially, but not only, Christian) FBOs and the structures and processes of the governmental powers-that-be. [ABSTRACT FROM AUTHOR]

Today's work market is both unsteady and unpredictable, and this requires taking urgent and practical actions aiming at creating work opportunities and "better" jobs, promoting a social and solidarity economy, and encouraging the development of moral strength in the workplace. From the Life Design approach perspective, our study examines two variables necessary to cope with the current labor market, courage, and career adaptability, and their role in life satisfaction. Through courage, a full mediational model between life satisfaction and career adaptability was tested in the 525 (291 men and 234 women) employees involved in the present study. Results support the mediational model. Mainly, life satisfaction was predicted indirectly by career adaptability through courage. Such outcome has important implications for practice and highlights the need to support workers in planning their life design by developing career adaptability and workers' voluntary feeling to act, according to different levels of fear, when facing a threat to the achievement of a significant result or objective, which in turn will positively influence their feelings of life satisfaction. [ABSTRACT FROM AUTHOR]

Additive manufacturing has garnered significant attention as a versatile method for fabricating green and complex composite materials. This study delves into the fabrication of polymer composites by employing polylactic acid (PLA) in conjunction with rice husk as a reinforcing filler. The filaments were made by an extruded filament maker and then were used to make tensile and impact samples by another extrusion technology, fused deposition modeling (FDM). The structural and morphological characteristics of the composite materials were analyzed using scanning electron microscopy SEM. Results show that both the filament and samples are very reliable in producing polymer parts with this rice husk solid waste. This research contributes to increasing materials' circularity and potentially creating a local social economy around rice production, where this waste is not much used. [ABSTRACT FROM AUTHOR]

With the development of social economy, using lithium-ion batteries in energy storage in industries such as large-scale electrochemical energy storage systems will cause lithium resources to no longer meet demand. As such, sodium ion batteries have become one of the effective alternatives to LIBs. Many attempts have been carried out by researchers to achieve this, among which F-doping is widely used to enhance the electrochemical performance of SIBs. In this paper, we reviewed several types of transition metal oxide cathode materials, and found their electrochemical properties were significantly improved by F-doping. Moreover, the modification mechanism of F-doping has also been summed up. Therefore, the application and commercialization of SIBs in the future is summarized in the ending of the review. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has deeply influenced the economy of all nations, and Mexico is no exception. This effect is distinct for different groups of the population, with variable socio-economic and demographic characteristics, that live in regions of contrasting features. An efficient apparatus for measuring expenditure variations and tendency is the National Household Income and Expenditure Survey performed by the National Institute of Statistics and Geography in accordance with the international standardization established at the Canberra Conference; the latter permits, every two years, for different surveys to be comparable in time and space. Hence, in Mexico, there are three surveys for 2018, 2020, and 2022. The results of the comparison indicate that different groups of the Mexican population have experienced the pandemic with multiple impacts, apparently without large proportional variation regarding expenditure but with greater variation in time-use conditions. Moreover, it became apparent that even though the lower strata of Mexico's population have fewer proportional variations concerning income after the COVID-19 outburst, they must incorporate more family members into working activities to achieve a survival line; the latter results in the abandonment of school from various young household members that will negatively impact the quality of their lives in the long term. [ABSTRACT FROM AUTHOR]

This article centers on the nonprofit landscape in Vancouver, Canada, a city that occupies the territories of the xʷməθkʷəy̓əm (Musqueam), sḵwx̱wú7mesh (Squamish), and səlilwətaɬ (Tsleil-Waututh) nations, which have never been ceded to the colonial occupation of Canada. Vancouver has a competitive nonprofit field, with an estimated 1600+ nonprofits operating within city limits. This descriptive review starts by defining what a nonprofit industrial complex (NPIC) is, then outlines an abbreviated history of the nonprofit sector on the aforementioned lands. The article then explores issues related to colonialism, anti-poor legislation, neoliberal governance, the fusing of the public and private sectors, and the bureaucratization of social movements and care work as mechanisms to uphold the status quo social order and organization of power. Focusing on under-examined issues related to the business imperatives of nonprofit organizations in the sectors of housing, health and social services, community policing, and research, this work challenges the positive default framing of nonprofits and charities. Instead, we contend that Vancouver's NPIC allows the government and the wealthy to shirk responsibility for deepening health and social inequities, while shaping nonprofits' revenue-generating objectives and weakening their accountability to the community. [ABSTRACT FROM AUTHOR]

Drought monitoring ensures the Yangtze River Basin's social economy and agricultural production. Developing a comprehensive index with high monitoring precision is essential to enhance the accuracy of drought management strategies. This study proposes the standardized comprehensive drought index (SCDI) using a novel approach that utilizes the joint distribution of C-vine copula to effectively combine three critical drought factors: precipitation, NDVI, and runoff. The study analyzes the reliability and effectiveness of the SCDI in detecting drought events through quantitative indicators and assesses its applicability in the Yangtze River Basin. The findings are as follows: (1) The SCDI is a highly reliable and applicable drought index. Compared to traditional indices like the SPI, VCI, and SRI, it has a consistency rate of over 67% and can detect drought events in more sensitive months by over 51%. It has a low false negative rate of only 2% and a false positive rate of 0%, making it highly accurate. The SCDI is also applicable to all the third-level sub-basins of the Yangtze River Basin, making it a valuable tool for regional drought monitoring. (2) The time lag effect of the NDVI can affect the sensitivity of the SCDI. When the NDVI time series data are shifted forward by one month, the sensitivity of the SCDI in detecting agricultural drought improves from 47.8% to 53%. (3) The SDCI can assist in monitoring drought patterns in the Yangtze River Basin. From 2001 to 2018, the basin saw fluctuations in drought intensity, with the worst in December 2008. The western region had less frequent but more intense and prolonged droughts, while the eastern part had more frequent yet less severe droughts. [ABSTRACT FROM AUTHOR]

The last decade has seen keen interest among governments, businesses, academe, and the nonprofit sector in the role religions can play in the implementation of the UN Sustainable Development Goals 2030. In China, until the outbreak of COVID-19 in early 2020, there were conferences and debates about this that increasingly involved the religious sector. This study looks at Christian social practice among faith-based organizations in China, especially its transformative potential, in contributing to sustainable development. It will highlight some of the best practices of the Amity Foundation, a Chinese FBO headquartered in Nanjing, to illustrate how, through a combination of service delivery and advocacy (Chinese style), FBOs in China can help shift official and religious perspectives and attitudes toward a more participatory and sustainable approach to development. Although the term "transformative diaconia" has not been explicitly used by Amity to describe its work, the values embedded in its practice and the impact it has made on stakeholders and policies can be considered transformative. The UN SDGs 2030, which have been strongly supported by Amity's ecumenical partners and the Chinese government, provide an important frame of reference for Amity's advocacy work as well as help to identify some of the content for diaconal capacity building for churches in China. Some of the opportunities and challenges confronting FBOs as they transition from service delivery to advocacy will be explored. [ABSTRACT FROM AUTHOR]

The special terrain of Urumqi (in the valley area) often triggers strong foehn winds, causing huge losses to local people's lives and social economies. By using the surface observation data of the hourly temperature, pressure, humidity, and wind from the downwind Urumqi Meteorological Station and the upwind Dabancheng Meteorological Station in the Middle Tianshan Canyon and the NCEP/NCAR reanalysis data during 2008–2022, this paper establishes the dataset of foehn processes at Urumqi Station in the past 15 years and analyzes the variation rules of the associated meteorological variables during the foehn processes. In addition, based on the physical mechanism of the occurrence of foehn, a three-element identification criterion (i.e., 94° ≤ 2 min average wind direction ≤ 168°, 2 min average wind speed ≥ 2.0 m/s, and Δθ between Urumqi station and Dabancheng station ≥ 0.29 K) for foehn in Urumqi is established by comparing and analyzing the variations of wind direction (WD), wind speed (WS), and the potential temperature difference (Δθ) between the two weather stations during the periods of foehn and non-foehn winds from 2013 to 2022. In addition, the performance of the three-element identification criterion is verified, and the results suggest that this criterion has an accuracy of 82.96% and a hit rate of 89.50% for the 2008–2012 foehn events in Urumqi. Moreover, the hit rate of this criterion for foehn wind of gale or above level (i.e., a 2 min wind ≥ 10.8 m/s on average) is 100%. In addition, combined with two predictors of sea-level pressure difference (ΔP) and Δθ between downwind stations and upwind stations, the foehn forecast can be more accurate than that provided by a single predictor. With ΔP ≤ −12 hPa and Δθ ≥ 5 K, the chances for foehn to occur are over 90%. This finding would have some reference and application values for the foehn forecasting. [ABSTRACT FROM AUTHOR]

The energy sector is essential to a country's economy and social life. In recent years, the energy market in Romania has experienced a certain dynamism, influenced by multiple factors such as regional conflicts, national and EU energy legislation, liberalization of the energy market, and increasing demand for energy products. These factors determined a sharp increase in electricity, gas, and oil prices in Romania in recent years. Based on the above, the present study aims to analyze Romanian energy companies' financial performances and determine whether there is any correlation between their governance and their performance. In order to fulfill the research objectives, financial performance data were extracted and analyzed for a number of 43 energy companies in Romania, considering the financial statements prepared up to 31 December 2021. Using the scoring method, governance indices were determined for each company. Finally, using a linear regression model, we analyzed the correlation between governance and performance of the 43 companies. The results of the study indicate that there is a direct correlation of moderate intensity between the two variables, with the performance of energy companies being higher if they have implemented a governance system. [ABSTRACT FROM AUTHOR]

The net primary productivity (NPP) of vegetation is an important indicator used to evaluate the quality of terrestrial ecosystems and characterize the carbon balance of ecosystems. In this study, the spatiotemporal distribution and dynamic change in NPP in Africa from 1981 to 2018 were analyzed using the long time series data of NPP. The results of the trend and fluctuation analysis showed that the NPP in the Sahara arid region in northern Africa and the arid region in South Africa exhibited a significant reduction and a high degree of fluctuation; most of the NPP in the tropical rainforests in central Africa and the deciduous broadleaved forests and deciduous needle-leaved forests on the north and south sides of the tropical rainforests increased and showed a low degree of fluctuation; the Congo basin, Gabon, Cameroon, Ghana, Nigeria, Tanzania, and other regions were affected by human activities, while the NPP in these regions exhibited a significant reduction and a high degree of fluctuation. Anomaly analysis showed that the NPP in Africa generally exhibited a slow upward trend during the period from 1981 and 2018. The trend was basically consistent in different seasons, and can be segmented into three phases: (1) a phase of descent from 1981 to 1992, with the NPP below the average value in most years; (2) a phase of steady growth from 1993 to 2000, reaching a peak in 2000; (3) a phase of fluctuations from 2001 to 2018, where the NPP value was above the average value in all years except 2015 and 2016, when the NPP value was low due to abnormally high temperatures and drought. The Mann–Kendall test further showed that the annual and seasonal NPP in Africa exhibited a significant upward trend, and the mutation time points occurred around 1995. The wavelet time series analysis revealed obvious periodic changes in the time series of NPP in Africa. The annual and seasonal NPP showed clear oscillations on time scales of 7, 20, 29, and 55 years. The 55-year period had the strongest signal, and was the first main period. The study can provide a scientific gist for the sustainable development of environmental ecology, agricultural production, and the social economy in Africa. [ABSTRACT FROM AUTHOR]

Simple Summary: Despite traditional reports on the ability of female dromedaries to modulate pregnancy length in response to environmental conditions, no empirical study has been developed. According to the present results, female dromedaries would adjust the onset of parturition to give birth around darker and, therefore, safer nights since social communication and interaction between congeners are increased under dim light conditions, mostly mediated by hormonal signals. Furthermore, the time of delivery, a highly energy-demanding process, may also be modulated by mean wind speed and its transient increases since these weather variables affect the thermal comfort and, thus, the heat transfer between an animal and its environment and the individual energy budget. Gravid females may be more energetically compromised when the offspring is a male; hence, the onset of parturition for the newborns of the male sex will be more probable to occur on slightly brighter nights and when mean wind speed is lower when compared to their female counterparts. Such specific phenology would favor a proper multisensory interaction between the mother and the more immature male young at neonatal stages so that thermoregulatory demands are minimized for these reproductive tasks, and then the fitness of parents and the survival of offspring are improved. Given energy costs for gestating and caring for male offspring are higher than those of female newborns, external environmental conditions might be regarded as likely to affect the timing of delivery processes differentially depending on the sex of the newborn calf to be delivered. The aim of the present paper is to evaluate the association between environmental stressors such as the moon phase and weather-related factors and the onset of labor in female dromedaries. A binary logistic regression model was developed to find the most parsimonious set of variables that are most effective in predicting the probability for a gravid female dromedary to give birth to a male or a female calf, assuming that higher gestational costs and longer labor times are ascribed to the production of a male offspring. Although the differences in the quantitative distribution of spontaneous onset of labor across lunar phases and the mean climate per onset event along the whole study period were deemed nonsignificant (p > 0.05), a non-negligible prediction effect of a new moon, mean wind speed and maximum wind gust was present. At slightly brighter nights and lower mean wind speeds, a calf is more likely to be male. This microevolutionary response to the external environment may have been driven by physiological and behavioral adaptation of metabolic economy and social ecology to give birth to cooperative groups with the best possible reduction of thermoregulatory demands. Model performance indexes then highlighted the heterothermic character of camels to greatly minimize the impact of the external environment. The overall results will also enrich the general knowledge of the interplay between homeostasis and arid and semi-arid environments. [ABSTRACT FROM AUTHOR]

With the accelerating urbanization process in China, the extensive economic growth model with high energy consumption and high pollution aggravates atmospheric environmental pollution and restricts the sustainable development of the social economy. The Beijing–Tianjin–Hebei region has the most severe haze pollution and the most acute contradiction between resources, environment and economic development. Based on the physical coupling theory, this paper constructs a coupling coordination degree model of the economy, environment and high haze pollution industries, such as the thermal power industry. Through literature analysis and expert investigation of the economic, industrial and environmental data of the Beijing–Tianjin–Hebei region from 2006 to 2018, the coordinated development of the economy, environment and high haze pollution industries, such as the thermal power industry, in the above region, was dynamically monitored. The monitoring results show that the development level of the Beijing, Tianjin and Hebei region is significantly different, and the three subregions have not entered the stage of coordinated development. Moreover, since 2015, they have been in a bottleneck period of development and have not achieved a higher level of progress. The three subregions have different advantages and restraining factors. For example, the backward level of Hebei's economy and high haze pollution industries, such as the thermal power industry, restrict the coordinated development of the region as a whole. Only by accelerating the high-quality development of the Hebei economy can we break through the bottleneck of the development of Beijing, Tianjin and Hebei. [ABSTRACT FROM AUTHOR]

Social work (SW) is criticized for its (i) inconsistent ontology, epistemology, and methodology and (ii) co-dependency with the capitalist hegemony, which is the main cause of multiple crises that primarily affect the most vulnerable. Addressing these issues is of paramount importance if SW is to achieve its core mandate of promoting social change, social development, social cohesion, and the empowerment and liberation of people. The purpose of this paper is to assert that SW can address these issues by learning from the (i) Settlement House Movement (SHM), especially the Hull-House tradition of SW; and (ii) current endeavors of the Social Solidarity Economy (SSE). We were led to this assertion because we noticed in our research, in the area of SSE of vulnerable groups and SW, remarkable similarities and potentials of these two approaches to help transform SW. Our argument is based on data and insight gained from (i) a narrative literature review on the history of SW and the nature of SSE; and (ii) a systematic scoping review of the SSE of People of African Descent (PAD) in Europe. In this paper, we elaborate on our key arguments and provide examples and recommendations. [ABSTRACT FROM AUTHOR]

Using the Survey of Income and Program Participation panel data, this study compares women's and men's pay increase trajectories and patterns of job mobility in the nonprofit and for-profit sectors. As recent studies suggested that industry-specific rather than economy-wide analysis is more appropriate in nonprofit/for-profit comparison, this study only focuses on the human services field. The results indicate that: (1) there was a selection in workers' choices regarding staying or changing sector of employment; (2) nonprofit workers who chose to move to the for-profit sector tended to be those worse off in the nonprofit sector, whereas for-profit workers who chose to move to the nonprofit sector tended to be those better off in the for-profit sector, and both of the mover groups gained by moving; (3) in both nonprofits and for-profits, men enjoyed a steeper pay increase curve by occupying more managerial positions, having higher levels of education, and working longer hours; (4) on average, there was no statistically significant difference in pay increase trajectories between workers who chose to stay in their sector of employment. Consistent with previous studies, the regression analyses further support the argument that, within human services, there is not necessarily a sectoral difference in the gender pay gap—in other words, nonprofits are not necessarily more equitable than for-profits. [ABSTRACT FROM AUTHOR]

This study describes the implementation of an energy sector community to examine the practice of cybersecurity for operational technology environments and their supply chains. Evaluating cybersecurity from the perspectives of different actors participating in the energy sector, the progress and challenges of operators and suppliers in delivering cybersecurity for the sector are explored. While regulatory frameworks incentivize individual organizations to improve their cybersecurity, operational services contain contributions from many organizations, and this supply chain of activity needs to be influenced and managed to achieve desired security and resilience outcomes. Through collaborations and systems engineering approaches, a reference model is created to facilitate improvements in managing the cybersecurity of supply chains for different actors, including service operators, maintainers, manufacturers, and systems integrators. This study provides an illustration of implementing a common vision of cybersecurity improvement across a community of actors. It utilizes a collaborative framework that has facilitated the co-production of cybersecurity guidance for energy sector participants. [ABSTRACT FROM AUTHOR]

A forest fire is a destructive disaster that is difficult to handle and rescue and can pose a significant threat to ecosystems, society, and humans. Since driving factors and their effects on forest fires change over time and space, exploring the spatiotemporal patterns of forest fire occurrence should be addressed. To better understand the patterns of forest fire occurrence and provide valuable insights for policy making, we employed the Geographically and Temporally Weighted Regression (GTWR) model to investigate the varying spatiotemporal correlations between driving factors (vegetation, topography, meteorology, social economy) and forest fires in Anhui province from 2012 to 2020. Then we identified the dominant factors and conducted the spatiotemporal distribution analysis. Moreover, we innovatively introduced nighttime light as a socioeconomic driving factor of forest fires since it can directly reflect more comprehensive information about the social economy than other socioeconomic factors commonly used in previous studies. This study applied remote sensing data since the historical statistic data were not detailed. Here, we obtained the following results. (1) There was a spatial autocorrelation of forest fires in Anhui from 2012 to 2020, with high-high aggregation of forest fires in eastern cities. (2) The GTWR model outperformed the Ordinary Least Squares (OLS) regression model and the Geographically Weighted Regression model (GWR), implying the necessity of considering temporal heterogeneity in addition to spatial heterogeneity. (3) The relationships between driving factors and forest fires were spatially and temporally heterogeneous. (4) The forest fire occurrence was mainly dominated by socioeconomic factors, while the dominant role of vegetation, topography, and meteorology was relatively limited. It's worth noting that nighttime light played the most extensive dominant role in forest fires of Anhui among all the driving factors in the years except 2015. [ABSTRACT FROM AUTHOR]

A safe and stable operation power system is very important for the maintenance of national industrial security and social economy. However, with the increasing complexity of the power grid topology and its operation, new challenges in estimating and evaluating the grid structure performance have received significant attention. Complex network theory transfers the power grid to a network with nodes and links, which helps evaluate the system conveniently with a global view. In this paper, we employ the complex network method to address the cascade failure process and grid structure performance assessment simultaneously. Firstly, a grid cascade failure model based on network topology and power system characteristics is constructed. Then, a set of performance evaluation indicators, including invulnerability, reliability, and vulnerability, is proposed based on the actual functional properties of the grid by renewing the power-weighted degree, medium, and clustering coefficients according to the network cascade failure. Finally, a comprehensive network performance evaluation index, which combines the invulnerability, reliability, and vulnerability indicators with an entropy-based objective weighting method, is put forward in this study. In order to confirm the approach's efficacy, an IEEE-30 bus system is employed for a case study. Numerical results show that the weighted integrated index with a functional network could better evaluate the power grid performance than the unweighted index with a topology network, which demonstrates and validates the effectiveness of the method proposed in this paper. [ABSTRACT FROM AUTHOR]

Particulate matter (PM) pollution has caused several environmental problems and damaged human health. To understand the different driving forces of PM2.5 and PM10, we investigated the spatial distribution of PM2.5, PM10, and the ratio of PM2.5 to PM10 (PM2.5/PM10), and simulated how they respond to socioeconomic, natural conditions and pollutant transmission in 336 cities across Chinese mainland in 2017. The results indicated that 35.4% and 49.7% of cities in Chinese mainland satisfied the national level II standard for PM2.5 (35 μg/m3) and PM10 (70 μg/m3), respectively. The average PM2.5/PM10 was 57.5 ± 9.4%, which is a relatively high value across the world. Global spatial regression results revealed that the transport of pollutants emitted from neighboring regions was the most important factor for local PM concentrations, while population density was the dominant local variable. The influence of socioeconomic factors and the neighboring pollution level on PM2.5 was greater than that on PM10, while the effect of precipitation was greater on PM10. Cluster analysis revealed that 336 Chinese cities could be classified into three groups. The regions with a high PM concentration and a high level of social economy were included in Group 1 (G1). Group 2 (G2) was predominantly observed in southern China, while Group 3 (G3) was seen in western China. Furthermore, population density significantly affected the PM in G2 and PM2.5 in G3, and PM levels in G1 and G3 had a sensitive response to the variation in precipitation, especially PM10. [ABSTRACT FROM AUTHOR]

Increasing energy usage efficiency requires enhanced heat energy recuperation between process streams in the industry and civic sector with waste heat utilization. The condensation of different vapours is the process encountered in many industrial applications. Increasing the heat recuperation in this process is possible with efficient heat transfer equipment, among which a Plate Heat Exchanger (PHE) is at the leading position. A number of research works have been conducted in recent years concerning construction development and heat transfer enhancement in conditions of limited pressure drop to increase PHE performance in condensation processes. The results of studies on heat transfer and pressure drop in the two-phase condensing flow inside channels of PHE with different geometries of corrugations are discussed. In many implementations, the total pressure drop allowable for gaseous streams in heat exchangers is relatively small. The structure of two-phase flow in PHE channels of complex geometry is very different than in tubes and flat wall channels. The relative differences in approaches to enhance PHE performance in condensation processes based on its modelling, optimisation and design are analyzed. The directions and prospects for future developments are formulated, and potential savings for the economy and the environmental footprint is presented. [ABSTRACT FROM AUTHOR]

Simple Summary: This study was conducted to ascertain the challenges in dog welfare and the future needs of dog welfare organisations (DWOs) in Ireland, as perceived by the DWOs themselves. Minimal previous research into dog welfare in Ireland was identified. Using interviews and focus groups, this study aimed to highlight previously unknown challenges and opportunities, to improve future dog welfare. DWOs perceived a need for greater education of the public on dogs, increased enforcement of current legislation for welfare, action on dog breeding establishments and puppy farms, and the financial challenges in dog welfare. The study also identified the current principles applied in dog rehoming procedures by DWOs and the desire amongst DWOs to improve standards across the sector. Greater communication between voluntary and statutory organisations and reducing volunteer burden were identified by DWOs as potential solutions. The findings, while consistent with research findings in other international jurisdictions, also provide greater depth and interrogation of the Irish context. In conclusion, this study is the first step in identifying the challenges faced by the sector and provides recommendations from those deeply involved in dog welfare. This novel qualitative study identifies challenges and opportunities to improve dog welfare in Ireland, as perceived by dog welfare organisations (DWOs), a previously underutilised stakeholder. This study sought the views of this predominantly voluntary sector of the next steps for policy and action in dog welfare, in light of the effects of the "puppy pandemic", increased costs and COVID-19 restrictions. An integrated online focus group and interview design involving DWOs was analysed using inductive thematic analysis. Thematic analysis identified 2 key themes: (1) Key challenges and solutions in general dog welfare and (2) Challenges and opportunities in the welfare organisation sector. DWOs perceived poor public awareness of appropriate dog-husbandry, inadequate legislation enforcement, negative impact of puppy farms, and increased financial and volunteer burden. DWOs helped construct a best practice rehoming pathway, identified how overall standards could be improved and recommendations to enhance dog welfare. The DWOs perceived an increased numbers of households acquiring dogs, difficulties in rehoming, and financial challenges as threatening their viability as organisations and Irish dog welfare. Greater enforcement of legislation, greater communication between organisations and the government, and more media awareness were seen as helpful by the DWOs to improve dog welfare standards and their organisations. [ABSTRACT FROM AUTHOR]

Land urbanization has reduced the amount of area for natural ecosystem assets. However, with the development of the social economy, will the quality of natural ecosystem assets be improved? If one comprehensively considers the changes in the area and quality of natural ecosystem assets, is the dominant impact of urbanization on natural ecosystem assets positive or negative? In this study, detailed research is conducted on the area, pattern, quality, and overall situation of the ecosystem assets in the Beijing–Tianjin–Hebei urban agglomeration during the rapid urbanization process. The impact of urbanization on the overall situation of ecosystem assets is also analyzed. The research methods used to generate statistics, accounting, and analysis of the ecosystem assets include ArcGIS, satellite remote sensing images, R language programming, and other data analysis tools. The research results show that: (1) The ecosystem area was dominated by degradation, and the landscape pattern became increasingly fragmented, with the exception of farmland and wetland areas. (2) However, the quality of the natural ecosystem assets was significantly improved, and the overall situation of the natural ecosystem assets was optimized. (3) In addition to the population urbanization rate, the growth in the population density, land urbanization rate, and GDP per unit area had a significant negative impact on the overall situation of natural ecosystem assets. This reminds people that the improvement in asset quality can compensate for the reduction in area to some extent, and, in addition to the population urbanization rate, the levels of population density, land urbanization, and economic density should be appropriately controlled. [ABSTRACT FROM AUTHOR]

In recent decades, the waters off the Antarctic Peninsula and surrounding region have undergone a significant transformation due to global climate change affecting the structure and distribution of pelagic fauna. Here, we present the results of our study on the taxonomic composition and quantitative distribution of plankton communities in Bransfield Strait, Antarctic Sound, the Powell Basin of the Weddell Sea, and the waters off the Antarctic Peninsula and South Orkney Islands during the austral summer of 2022. A slight warming of the Transitional Zonal Water with Weddell Sea influence (TWW) and an increase in its distribution area was detected. Among the pelagic communities, three groups were found to be the most abundant: copepods Calanoides acutus, Metridia gerlachei, and Oithona spp., salpa Salpa thompsoni, and Antarctic krill Euphausia superba. Euphausiids were found in cases of low abundance, species diversity, and biomass. In the studied region, an increase in the amount of the salpa S. thompsoni and the euphausiid Thysanoessa macrura and the expansion of their distribution area were observed. Significant structural shifts in phytoplankton communities manifested themselves in changes in the structure of the Antarctic krill forage base. The composition and distribution of pelagic fauna is affected by a combination of environmental abiotic factors, of which water temperature is the main one. The obtained results have allowed us to assume that a further increase in ocean temperature may lead to a reduction in the number and size of the Antarctic krill population and its successive replacement by salps and other euphausiids that are more resistant to temperature fluctuations and water desalination. [ABSTRACT FROM AUTHOR]

Under the background of intensifying global change, the frequent occurrence of agrometeorological disasters has an adverse impact on the social economy. Low-temperature weather in spring is one of the main agrometeorological disasters in Xinjiang. Studying the spatial and temporal characteristics of low temperatures in spring in Xinjiang is of great significance. However, research on the spatiotemporal variation of spring frost in arid areas is currently lacking, which limits our understanding of the occurrence and development mechanism of typical disastrous weather events in arid areas. Therefore, on the basis of the daily meteorological data of 40 meteorological stations in the Xinjiang Province of China from 1971 to 2020, we studied the spatiotemporal heterogeneity of spring frost in Xinjiang through trend analysis, the Mann–Kendall test, Kriging interpolation, and wavelet analysis. Results showed that the frequency of spring frost had the spatial trend from Northern Xinjiang to Southern Xinjiang. The occurrence frequency of spring frost in the entire and northern region of Xinjiang had an upward trend, whereas that in Southern Xinjiang showed a downward trend. Severe and moderate spring frost events mainly occurred in Xinjiang. The duration of spring frost had the characteristics of Northern Xinjiang to Southern Xinjiang. The spring frost in Northern Xinjiang mainly occurred in April, and that of Southern Xinjiang was in March. Obvious 15-, 10-, and 20-year oscillation cycles were observed in the occurrence frequency of spring frost in the entire, southern, and northern regions of Xinjiang, respectively. This study can provide a useful reference for the prediction and research corresponding to the occurrence mechanism of spring frost in arid areas. [ABSTRACT FROM AUTHOR]

In the European energy market, the community energy sector is earmarked to make a significant contribution to the transition from fossil fuels to sustainable sources. Based on the diffusion of innovation model, large-scale development of community energy requires that the concept and the success of existing energy communities be widely communicated to potential participants and that user confidence be developed over time. In this paper, we present the architecture, design, prototyping, and testing of a digital support platform, co-designed with EU-wide energy communities, to support this process. The platform has been designed to engage early-stage or ongoing groups to progress projects and to connect and share experiences with other communities. This "community of communities" creates the necessary communication channel defined in the Diffusion of Innovation model. A transactional architecture for such a platform is outlined with clear links to all community energy actors. Based on this architecture, a prototype one-stop-shop (OSS) implementation is presented. Feedback gathered and lessons learned from beta testing with a representative group of end-users are outlined. The OSS architecture shows potential as a communications channel to expand the community energy concept and as a monitoring tool to track the progress of the energy community sector. [ABSTRACT FROM AUTHOR]

The non-profit sector plays an important role in the American and European continents, as non-profit organizations support the development of civil society and help people in need. However, most non-profit organizations (NPO) are financially dependent on various donors from the private sector. Nowadays, non-profit organizations focus on improving their non-profit financial management. This research aims to assess the financial status of Slovak non-profit organizations, using binary logistic regression. The initial sample includes 351 Slovak NPOs, which are divided into a training and test sub-sample. The data were obtained from Amadeus, FinStat, the Ministry of Finance of the Slovak Republic, and the Ministry of Interior of the Slovak Republic. The logit model shows that the significant variables are equity ratio, debt ratio, operating margin, and type of NPO using the statistical–analytical program IBM SPSS 25. The model also implies that non-profit organizations should focus on the revenue structure and revenues from the sale of products. The prediction model correctly classifies 97.03% of NPOs in the training sub-sample and 96.61% of NPOs in the test sub-sample. Moreover, more than 70% of vulnerable NPOs are correctly classified. [ABSTRACT FROM AUTHOR]

Measuring social capital has been a challenging task over the past few decades, and, still, many of its dimensions and manifestations have not been thoroughly or evidently explored. The possible causes may be the ever-changing evolutionary perspectives that take place within the various levels of analysis—micro, meso, and macro—or within the various settings, where some of its core dimensions—bonding, bridging, and linking—are developed, or even among the contexts where its core determinants and features—trust, norms, connections, ties, etc.—are observed. Having in mind the various streams of research and theoretical discourses on social capital formation, this paper aims to surface the identification of the possible evidence on the formation of social capital among social economy organizations, and particularly among social enterprises. In doing so, it aims to explore the relational and cognitive features that drive social enterprises in their interorganizational cooperation with other social enterprises and third-sector organizations. The findings suggest that the central components of social capital, such as the sharing of common values, trust, reciprocity, and trustworthiness, are among those features that were valued most among the participants in the survey during their cooperation and engagement in common activities with other organizations. [ABSTRACT FROM AUTHOR]

Individual, micro-level attitudes towards nonprofit organizations (NPOs) can have many potential determinants. In this study, we explore the impact of three categories of potential determinants of attitudes towards NPOs: Political cleavages (the cultural integration vs. demarcation cleavage and the economic integration vs. demarcation cleavage); religiosity and spirituality; and values (the survival vs. self-expression value dimension). Based on a representative survey in Switzerland, we estimate the impact of those factors for five different attitudinal dimensions and six different NPO types. The Bayesian model estimates show that all three categories of determinants have small to moderate impact. The effects of religiosity, spirituality, the self-expression value dimension, and of economic integration are generally positive. The effects of the survival value dimension and of cultural demarcation are generally negative, with the exception of the NPO type of professional associations. [ABSTRACT FROM AUTHOR]

Understanding historical and future drought patterns is crucial to acclimation and the mitigation of drought. The negative impact of China's droughts on the social economy has attracted attention; however, there is still no comprehensive or long-term monitoring pattern for future droughts. Here we evaluated the precipitation and temperature simulation capability of Coupled Model Intercomparison Project Phase 6 (CMIP6) and evaluated the temporal and spatial pattern of droughts during 1961–2099 across China. The results show that the multi-model ensemble mean (MME) is more representative of the observed precipitation and temperatures across China than the single climate model. China experienced an overall drying trend in the historical period. After 1991, the drought frequency (DF), drought duration (DD), and drought intensity (DI) in the northwest of the Inland River Basin and in the Yangtze River Basin increased significantly. Compared with the historical period, China will suffer more frequent drought events, although the DD and DI will be weakened under SSP1-2.6 and SSP2-4.5, while China will experience longer DD and more serious drought events under SSP3-7.0 and SSP5-8.5. The Hai River Basin and Huai River Basin are expected to have more serious drought trends in summer. Compared with historical periods, the drought trend will increase by 2.9–5.7 times and 1.1–4.2 times, respectively. The results can be used for decision making regarding future drought control. [ABSTRACT FROM AUTHOR]

The cooperative is one of the most important forms of business in the agricultural sector, due to its special characteristics for small farmers and livestock producers in order to gain access to greater comparative advantages. In addition, cooperatives are a driving force in the social economy, which means that investment in agricultural cooperatives can be seen as a sustainable investment. The aim of this paper is to analyse the preferences of investors in agricultural company cooperatives, looking in depth at the role of the cooperative as a business form. In order to achieve this objective, the choice experiment methodology was applied by carrying out a questionnaire to a total of 282 investors. Latent class models were also used to identify possible groups of investors. Two classes of investors have been identified based on their preferences: owners (return seeking) and workers (risk averse). [ABSTRACT FROM AUTHOR]

For the twenty years that mixed race has been on the United Kingdom (UK) censuses, the main story of mixed race in the UK remains one notable for its nominal presence and widespread absence in national discourses on race and ethnicity, racialisation, and racisms. The article explores reasons for this through connecting the continued presence/absence of mixed race in public discursive spheres to the role that White supremacy continues to play at systemic, structural, and institutional levels within UK society. As technologies of White supremacy, the article argues that continued marginalisation of mixed race has a direct connection to systemic, structural, and institutional aspects of race, racialisation, and racisms. Using three case studies, the article will use race-critical analyses to examine the ways that mixed race is present and—more often—absent at three societal levels: the state, institution, and civil society and voluntary and community sector. The paper will conclude by exploring key broad consequences for the persistent and common presence/absence of mixed race within race and racisms discourses as a technology of political power. Working in tandem, the paper exposes that presence/absence continues to affect mixed race people—and all racialised people—living in and under White supremacy. [ABSTRACT FROM AUTHOR]

With the development of the social economy and an enlarged volume of information, the application of multiple-criteria decision making (MCDM) has become increasingly wide and deep. As a brilliant MCDM technique, the best–worst method (BWM) has attracted many scholars' attention because it can determine the weights of criteria with less comparison time and higher consistency between judgments than analytic hierarchy process. However, the effectiveness of the BWM is based on complete comparison information among criteria. Considering the fact that the decision makers may have limited time and energy to study all criteria, they cannot construct a complete comparison system. In this paper, we propose a novel MCDM method named BW-MaxEnt that combines BWM and the maximum entropy method (MaxEnt) to identify the weights of unfamiliar criteria with incomplete decision information. The model can be translated into a convex optimization problem that can be solved effectively and has an overall optimal solution. Finally, a practical application concerning the procurement of GPU workstations illustrates the feasibility of the proposed BW-MaxEnt method. [ABSTRACT FROM AUTHOR]

With the rapid development of the social economy in China, numerous Chinese cities are facing high levels of particulate matter (PM) pollution problems. In this study, high-resolution ZY-3 images and GIS techniques were used to establish the emission inventory of total suspended particle (TSP), particulate matter 10 (PM10) and particulate matter 2.5 (PM2.5) from fugitive dust sources in May 2016, and a spatial grid of 3 km × 3 km resolution was established to demonstrate the spatial distribution of PM emission. Results showed that the total emissions of TSP, PM10 and PM2.5 in Zhengzhou city were 237.5 kt·a−1, 103.7 kt·a−1 and 22.4 kt·a−1, respectively. Construction dust source was the main fugitive dust emission source in Zhengzhou city—the TSP, PM10 and PM2.5 emission of which account for 76.42%, 89.68% and 88.39%, respectively, of the total emission, followed by road dust source and soil dust source. PM emission was higher in Zhongyuan, Huiji, Jinshui and Zhengdong New District, while Zhongmou, Xingyang, Dengfeng and other remote areas had low PM emissions. Compared to other Chinese cities or regions, the PM emission from the construction dust source was at a high level in Zhengzhou city, while the PM emissions from the soil dust source and road dust source were at moderate levels. [ABSTRACT FROM AUTHOR]

Landslides cause huge damage to social economy and human beings every year. Landslide susceptibility mapping (LSM) occupies an important position in land use and risk management. This study is to investigate a hybrid model which makes full use of the advantage of supervised learning model (SLM) and unsupervised learning model (ULM). Firstly, ten continuous variables were used to develop a ULM which consisted of factor analysis (FA) and k-means cluster for a preliminary landslide susceptibility map. Secondly, 351 landslides with "1" label were collected and the same number of non-landslide samples with "0" label were selected from the very low susceptibility area in the preliminary map, constituting a new priori condition for a SLM, and thirteen factors were used for the modeling of gradient boosting decision tree (GBDT) which represented for SLM. Finally, the performance of different models was verified using related indexes. The results showed that the performance of the pretreated GBDT model was improved with sensitivity, specificity, accuracy and the area under the curve (AUC) values of 88.60%, 92.59%, 90.60% and 0.976, respectively. It can be concluded that a pretreated model with strong robustness can be constructed by increasing the purity of samples. [ABSTRACT FROM AUTHOR]

Precipitation is an essential climate variable in the hydrologic cycle. Its abnormal change would have a serious impact on the social economy, ecological development and life safety. In recent decades, many studies about extreme precipitation have been performed on spatio-temporal variation patterns under global changes; little research has been conducted on the regionality and persistence, which tend to be more destructive. This study defines extreme precipitation events by percentile method, then applies the spatio-temporal scanning model (STSM) and the local spatial autocorrelation model (LSAM) to explore the spatio-temporal aggregation characteristics of extreme precipitation, taking China in July as a case. The study result showed that the STSM with the LSAM can effectively detect the spatio-temporal accumulation areas. The extreme precipitation events of China in July 2016 have a significant spatio-temporal aggregation characteristic. From the spatial perspective, China's summer extreme precipitation spatio-temporal clusters are mainly distributed in eastern China and northern China, such as Dongting Lake plain, the Circum-Bohai Sea region, Gansu, and Xinjiang. From the temporal perspective, the spatio-temporal clusters of extreme precipitation are mainly distributed in July, and its occurrence was delayed with an increase in latitude, except for in Xinjiang, where extreme precipitation events often take place earlier and persist longer. [ABSTRACT FROM AUTHOR]

Demand response has been noted as a major element of future smart energy systems. However, there is still a lack of knowledge about the demand response actions in different conditions—including climate, dynamic energy price, and building types. This study examines energy and cost saving potential of the rule-based demand response in district heating network, in three different building types, in Germany and Finland. The studied building types are apartment buildings, cultural centers, and office buildings. The real-time pricing-based demand response is applied to space heating under the climate conditions of Helsinki, Finland and Hamburg, Germany. Moreover, the typical synthetic dynamic price data, which are based on both counties' district heating production structure, is applied separately for each countries' cases. Simulations of this study are conducted with validated simulation tool IDA ICE. The results present that the demand response can provide energy and cost savings around 0.5–7.7% and 0.7–8.1% respectively, depending on the building type and country. The results indicate that marginal value of the control signal, climate conditions, and the dynamic price of the district heating have effect on the demand response saving potential. Flatter district heating price profile provides less savings than a more fluctuating profile. [ABSTRACT FROM AUTHOR]

Recent years have seen the big growth of app-based taxi services by not only competing for rides with street-hailing taxi services but also generating new taxi rides. Moreover, the innovation in dynamic pricing also makes it competitive in both passenger and driver sides. However, current literature still lacks better understandings of induced changes in spatiotemporal variations in multiple taxi ridership after app-based taxi service launch. This study develops two study cases in New York City to explore impacts of presence of app-based taxi services on daily total and street-hailing taxi rides and impacts of dynamic pricing on hourly app-based taxi rides. Considering the panel data and treatment effect measurement in this problem, we introduce a mixed modeling structure with both geographically weighted panel regression and difference-in-difference estimator. This mixed modeling structure outperforms traditional fixed effects model in our study cases. Empirical analyses identified the significant spatiotemporal variations in impacts of presence of app-based taxi services; for instance, impacts daily total taxi rides in 2014 and 2016 and impacts on street-hailing taxi rides from 2012 to 2016. Moreover, we capture the spatial variations in impacts of dynamic pricing on hourly app-based taxi rides, as well as significant impacts of time of day, day of week, and vehicle supply. [ABSTRACT FROM AUTHOR]

Decarbonisation of heat and transport will cause congestion issues in distribution networks. To avoid expensive network investments, demand flexibility is necessary to move loads from peak to off-peak periods. We provide a method and metric for assessing and selecting the optimal demand response strategy for a given network congestion scenario and applied it to a case study network in Coleraine, Northern Ireland. We proposed a Price Approximation/Mean Grouping strategy to deal with the issue of congestions occurring at the lowest-price period in real-time pricing schemes. The Mean Grouping strategy increased the average lowest-price hours from 1.32 to 3.76. We show that a three-cluster tariff is effective in solving medium congestion issues in Northern Ireland and could save consumers an average of £117/year on their heating bill. However, for networks with low headroom suffering from serious congestion issues, a smart control strategy is needed. [ABSTRACT FROM AUTHOR]

Decarbonisation of heat and transport will cause congestion issues in distribution networks. To avoid expensive network investments, demand flexibility is necessary to move loads from peak to off-peak periods. We provide a method and metric for assessing and selecting the optimal demand response strategy for a given network congestion scenario and applied it to a case study network in Coleraine, Northern Ireland. We proposed a Price Approximation/Mean Grouping strategy to deal with the issue of congestions occurring at the lowest-price period in real-time pricing schemes. The Mean Grouping strategy increased the average lowest-price hours from 1.32 to 3.76. We show that a three-cluster tariff is effective in solving medium congestion issues in Northern Ireland and could save consumers an average of £117/year on their heating bill. However, for networks with low headroom suffering from serious congestion issues, a smart control strategy is needed. [ABSTRACT FROM AUTHOR]

With the rapid development of the social economy, high-voltage transmission lines as power supply infrastructure are increasing, subsequently presenting a new challenge to the effective monitoring of transmission lines. The dynamic sensor network integrated with robots can effectively solve the elastic monitoring of transmission lines, but the problems of real-time performance, energy consumption and economy of the network need to be solved. To solve this problem, a dynamic network deployment method based on the hybrid hierarchical network (HHN) is proposed to realize a low-cost, energy-saving and real-time dynamic sensing system for overhead high-voltage transmission lines. Through case analysis and simulation, combined with the vague set multi-attribute decision-making method (MADM) with scheme preference, the network deployment and optimization results under multi-parameter constraints are obtained. [ABSTRACT FROM AUTHOR]

A rapidly growing number of vehicles in recent years cause long traffic jams and difficulty in the management of traffic in cities. One of the most significant reasons for increased traffic jams on the road is random parking in unauthorized and non-permitted places. In addition, managing of available parking places cannot achieve the expected reduction in traffic congestion related problems due to mismanagement, lack of real-time parking guidance to the drivers, and general ignorance. As the number of roads, highways and related resources has not increased significantly, a rising need for a smart, dynamic and effective parking solution is observed. Accordingly, with the use of multiple sensors, appropriate communication network and advanced processing capabilities of edge and cloud computing, a smart parking system can help manage parking effectively and make it easier for the vehicle owners. In this paper, we propose a multi-layer architecture for smart parking system consisting of multi-parametric parking slot sensor nodes, latest long-range low-power wireless communication technology and Edge-Cloud computation. The proposed system enables dynamic management of parking for large areas while providing useful information to the drivers about available parking locations and related services through near real-time monitoring of vehicles. Furthermore, we propose a dynamic pricing algorithm to yield maximum possible revenue for the parking authority and optimum parking slot availability for the drivers. [ABSTRACT FROM AUTHOR]

The integration of Demand-Side Management (DSM) in the planning of Isolated/Islanded Microgrids (IMGs) can potentially reduce total costs and customer payments or increase renewable energy utilization. Despite these benefits, there is a paucity in literature exploring how DSM affects the planning and operation of IMGs. The present work compares the effects of five different strategies of DSM in the planning of IMGs to fulfill the gaps found in the literature. The present work embodies a Disciplined Convex Stochastic Programming formulation that integrates the planning and operation of IMGs using three optimization levels. The first level finds the capacities of the energy sources of the IMG. The second and third levels use a rolling horizon for setting the day-ahead prices or the stimulus of the DSM and the day-ahead optimal dispatch strategy of the IMG, respectively. A case study shows that the Day-Ahead Dynamic Pricing DSM and the Incentive-Based Pricing DSM reduce the total costs and the Levelized Cost of Energy of the project more than the other DSMs. In contrast, the Time of Use DSM reduces the payments of the customers and increases the delivered energy more than the other DSMs. [ABSTRACT FROM AUTHOR]

Community energy (CE) initiatives have been progressively spreading across Europe and are increasingly proposed as innovative and alternative approaches to guarantee higher citizen participation in the transition toward cleaner energy systems. This paper focuses the attention on Italy, a Southern European country characterized by relatively low CE sector development. It fills a gap in the literature by eliciting and presenting novel and comprehensive evidence on recent Italian CE sector developments. Through a stepwise approach it systematically maps and reviews Italian CE initiatives, to then focus the attention on three specific case studies to further explore conditions for development as well as of success within the Italian energy system. The analysis presents an Italian CE sector still at its niche level, characterized by small initiatives largely dependent on national photovoltaics (PV) policy support. It also points out how only larger initiatives, able to operate at national scale, developing multiple projects and differentiating their activities have managed to continue growing at the time of discontinuity of policy support and contraction of the national renewable energy market. Recent EU and national legislative development might support revived development of CE initiatives in Italy. [ABSTRACT FROM AUTHOR]

Las Santas Casas de Misericórdias (The Holy Houses of Mercy) are institutions of Portuguese origin that emerged in the late fifteenth century and that, over time, have expanded beyond the territories of the Portuguese Empire, including to Spain, where various Casas de Misericordia were created in their image and with similar purposes to the original. The Misericórdias continue to be relevant and present throughout Portugal, in various decolonized countries of the former Portuguese Empire, and in other territories that have been influenced by Portuguese emigration, and have always played an important role in the social care of citizens. In Spain, the Santas Casas de Misericordia do not have the same long history, nor the same social relevance as their Portuguese counterparts. However, even today, there are some Casas de Misericordia in Spain that provide social care services, having adopted various legal structures such as foundations, associations, and public entities. [ABSTRACT FROM AUTHOR]

The smart robot is playing an increasingly important role in the social economy, and multi-robot systems will be an important development in robotics. With smart sensing systems, the communications between sensors, actuators, and edge computing systems and robots are prone to be attacked due to the highly dynamic and distributed environment. Since smart robots are often distributed in open environments, as well as due to their limited hardware resources and security protection capabilities, the security requirements of their keys cannot be met with traditional key distribution algorithms. In this paper, we propose a new mechanism of key establishment based on high-order polynomials to ensure the safe key generation and key distribution. Experiments show that the key establishment mechanism proposed in this paper guarantees the security of keys; its storage cost and communication cost are smaller than state-of-the-art mechanisms; and it allows robot components to join and leave the network dynamically, which is more suitable for multi-robot systems. [ABSTRACT FROM AUTHOR]

Alleviating traffic congestion is one of the main challenges for the Internet of Vehicles (IoV) in smart cities. Many congestion pricing systems have been proposed recently. However, most of them focus on punishing the vehicles that use certain roads during peak hours, neglecting the proven fact that rewards can encourage drivers to follow the rules. Therefore, in this paper, we propose a new congestion pricing system based on reward and punishment policies for the IoV in a smart city environment, where the vehicles are rewarded for voluntarily choosing to take an alternative path to alleviate traffic congestion. The proposed system is implemented using vehicular ad hoc networks, which eliminate the need for installing a costly electronic toll collection system. We propose a new virtual currency called T-Coin (traffic coin), that is used to reward the vehicles for their positive attitude. T-Coin is also used in the tender between vehicles to manage the road reservation process. The proposed system uses dynamic pricing to adapt to peak-hour traffic congestion. Using simulated traffic on a real map of Beijing city, we prove the usefulness of T-Coin as a traffic congestion pricing system. [ABSTRACT FROM AUTHOR]

Time-varying pricing is seen as an appropriate means for unlocking the potential flexibility from electric vehicle users. This in turn facilitates the future integration of electric vehicles and renewable energy resources into the power grid. The most complex form of time-varying pricing is dynamic pricing. Its application to electric vehicle charging is receiving growing attention and an increasing number of different approaches can be found in the literature. This work aims at providing an overview and a categorization of the existing work in this growing field of research. Furthermore, user studies and the modeling of user preferences via utility functions are discussed. [ABSTRACT FROM AUTHOR]

Previous studies have attempted to disaggregate census data into fine resolution with multisource remote sensing data considering the importance of fine-resolution population distribution in urban planning, environmental protection, resource allocation, and social economy. However, the lack of direct human activity information invariably restricts the accuracy of population mapping and reduces the credibility of the mapping process even when external facility distribution information is adopted. To address these problems, the present study proposed a novel population mapping method by combining International Space Station (ISS) photography nighttime light data, point of interest (POI) data, and location-based social media data. A similarity matching model, consisting of semantic and distance matching models, was established to integrate POI and social media data. Effective information was extracted from the integrated data through principal component analysis and then used along with road density information to train the random forest (RF) model. A comparison with WordPop data proved that our method can generate fine-resolution population distribution with higher accuracy ( R 2 = 0.91 ) than those of previous studies ( R 2 = 0.55 ). To illustrate the advantages of our method, we highlighted the limitations of previous methods that ignore social media data in handling residential regions with similar light intensity. We also discussed the performance of our method in adopting social media data, considering their characteristics, with different volumes and acquisition times. Results showed that social media data acquired between 19:00 and 8:00 with a volume of approximately 300,000 will help our method realize high accuracy with low computation burden. This study showed the great potential of combining social sensing data for disaggregating fine-resolution population. [ABSTRACT FROM AUTHOR]