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The report is an environmental impact assessment of two conjoining water streams in the lower area of the Wembury catchment where freshwater meets the coast. The assessment was conducted as there were concerns that the streams may be causing exceedances of the Environmental Quality Standards (EQS) due to catchment-based inputs from anthropogenic activities.

Water, sediment samples, and other parameters were collected, measured, and treated to preserve the concentration of nutrients and metals at three sites. A comparison with the neighbouring river Erme was made to determine if the findings were coherent. The report includes recommendations and mitigation strategies needed to improve the environmental quality of the system.

Findings indicate several breaches of EQS: water nitrogen, copper and zinc, and sediment copper. The highest recorded concentrations were mainly at sites one and two, likely from point source inputs from Wembury town and pollution accumulation from upstream land use such as arable and agricultural land. A special precaution must be taken for sediment copper, increasing monitoring to ensure values do not exceed Probable Effects Level (PEL) possibly becoming dangerous for the fauna and flora but also for humans. River Erme showed to also have EQS breaches but to some degree displayed an overall better ecological status. Despite several breaches in the legal limits, Wembury displays an overall good ecological status supporting life above and below water and is therefore an appropriate model for promoting environmental stewardship. It is to be noted that the material of the coursework was further edited after its original submission.

The cash flow from government agencies to contractors, called progress payment, is a critical step in public projects. The delays in progress payments significantly affect the project performance of contractors and lead to conflicts between two parties in the Turkish construction industry. Although some previous studies focused on the issues in internal cash flows (e.g. inflows and outflows) of construction companies, the context of cash flows from public agencies to contractors in public projects is still unclear. Therefore, the primary objective of this study is to develop and test diverse machine learning-based predictive models on the progress payment performance of Turkish public agencies and improve the predictive performance of these models with two different optimization algorithms (e.g. first-order and second-order). In addition, this study explored the attributes that make the most significant contribution to predicting the payment performance of Turkish public agencies.

In total, project information of 2,319 building projects tendered by the Turkish public agencies was collected. Six different machine learning algorithms were developed and two different optimization methods were applied to achieve the best machine learning (ML) model for Turkish public agencies' cash flow performance in this study. The current research tested the effectiveness of each optimization algorithm for each ML model developed. In addition, the effect size achieved in the ML models was evaluated and ranked for each attribute, so that it is possible to observe which attributes make significant contributions to predicting the cash flow performance of Turkish public agencies.

The results show that the attributes “inflation rate” (F5; 11.2%), “consumer price index” (F6; 10.55%) and “total project duration” (T1; 10.9%) are the most significant factors affecting the progress payment performance of government agencies. While decision tree (DT) shows the best performance among ML models before optimization process, the prediction performance of models support vector machine (SVM) and genetic algorithm (GA) has been significantly improved by Broyden–Fletcher–Goldfarb–Shanno (BFGS)-based Quasi-Newton optimization algorithm by 14.3% and 18.65%, respectively, based on accuracy, AUROC (Area Under the Receiver Operating Characteristics) and F1 values.

The most effective ML model can be used and integrated into proactive systems in real Turkish public construction projects, which provides management of cash flow issues from public agencies to contractors and reduces conflicts between two parties.

The development and comparison of various predictive ML models on the progress payment performance of Turkish public owners in construction projects will be the first empirical attempt in the body of knowledge. This study has been carried out by using a high number of project information with diverse 27 attributes, which distinguishes this study in the body of knowledge. For the optimization process, a new hyper parameter tuning strategy, the Bayesian technique, was adopted for two different optimization methods. Thus, it is available to find the best predictive model to be integrated into real proactive systems in forecasting the cash flow performance of Turkish public agencies in public works projects. This study will also make novel contributions to the body of knowledge in understanding the key parameters that have a negative impact on the payment progress of public agencies.

This study aims to analyze the policies and strategies used by governmental organizations to address the impacts of climate change in informal neighborhoods, kampungs, such as Bukit Duri and Melayu in Jakarta, Indonesia, focusing on canal and river flooding mitigation and infrastructure development. The research examines the displacement of residents due to the demolition of informal settlements along riverbanks, the role of different governmental organizations and the implications of these policies on affected communities.

This study uses the theoretical framework of environmental injustice to evaluate the strategies used by the Indonesian Government to address climate change adaptation in Jakarta, with a specific focus on the problem of flooding and its impact on displacement. By analyzing the history and outcomes of flood mitigation policies, this paper assesses the government’s strategies related to infrastructure, evacuation and socialization. In doing so, the study examines the social impact of these policies on affected communities. Furthermore, social listening and media analysis of Twitter data and various news outlets are conducted to gain insights into the living conditions and experiences of displaced residents in two public housing projects.

The study revealed the challenges faced by the government in implementing policies for climate change adaptation and flood mitigation in Jakarta, including a lack of community engagement with residents of the Kampungs in the decision-making process for relocation. Despite government efforts and providing low-cost apartments (rusuwana), the analysis sheds light on the various forms of injustice that result from the government’s approach to climate change adaptation in Jakarta.

This study examines social justice issues in Jakarta’s informal neighborhoods and explores locally driven efforts vs government-mandated policies for managing natural hazards and adapting to climate change.

This study aims to understand how climatic drivers of change will affect rural communities living in the hot semiarid region of Bhokardan Taluka of Jalna district in the Indian state of Maharashtra. In the context of the economic and social change they are experiencing, the concern is to evolve ways that enable them to cope with, adapt to and benefit from these challenges.

The focus of most of the climate change studies is on the short- to long-term trends of weather parameters such as rainfall, temperature and extreme weather events. The impact of climate variability and changing patterns on the local communities, the local economy, livelihoods and social life in specific geographies is less explored.

As the impacts of climatic and nonclimatic drivers of change are cross-sectoral, diverse, multidimensional, interlinked and dynamic, this study has adopted a transdisciplinary “research-in-use” approach involving multidisciplinary teams covering the aspects such as changes in land use and land cover, surface and groundwater status, edaphic conditions, crops and livestock, climate analysis including projected changes, socioeconomic analysis, people’s experience of climate variability and their current coping strategies and resilience (vulnerability) analysis of communities and various livelihood groups.

The study was based on the peoples’ perspective and recommendation based on the local communities ability to cope up with climate change. However, a statistical analysis perspective is missing in the present study.

Based on these findings, a set of implementation-focused recommendations are made that are aimed at conserving and enhancing the resilience of the foundations that uphold and sustain the social and economic well-being of the rural communities in Bhokardan taluka, namely, land, water, agriculture, livestock, food and nutrition security, livelihoods, market access and social capital.

Customer lifetime value (CLV) is one of the key indicators to measure the success or health of an organization. How can an organization assess the organization's customers' lifetime value (LTV) and offer relevant strategies to retain prospective and profitable customers? This study offers an integrated view of different methods for calculating CLVs for both loyalty members and non-membership customers.

This study outlines eleven methods for calculating CLV considering (1) the deterministic aspect of NPV (Net present value) models in both finite and infinite timespans, (2) the geometric pattern and (3) the probabilistic aspect of parameter estimates through simulation modeling along with (4) the migration models for including “the probability that customers will return in the future” as a key input for CLV calculation.

The CLV models are validated in the context of complementary and alternative medicine (CAM)in the healthcare industry. The results show that understanding CLV can help the organization develop strategies to retain valuable customers while maintaining profit margins.

The integrated CLV models provide an overview of the mathematical estimation of LTVs depending on the nature of the customers and the business circumstances and can be applied to other business settings.

By focussing on the anticipated emotional reactions of volunteers and drawing on theories of motivation and identity, this study investigates how volunteers react to different options of the entrepreneurial model of Amigos for Children Foundation (ACF). The paper proposes a hypothetical model for volunteer’s emotional reactions to potential business model changes. We suggest the relative importance of intrinsic motivational factors, professional identity and attitudes towards business organisations as mediating variables. ACF works exclusively with university students as volunteers, so their specific characteristics may limit some of the conclusions and propositions of this qualitative research, but public policy consequences of supporting similar entrepreneurial transitions can be generally relevant.

Based on the qualitative analysis of semi-structured interviews with volunteers of ACF, a Hungarian non-profit organisation, we explore the challenges of transitioning into a social enterprise.

Previous research showed controversial results about the impact of pay on the motivations of volunteers. For a non-profit organisation that would like to utilise the competencies of its volunteers, introducing a market-based service may mean additional financial resources and the potential loss of human resources. Understanding the moderating factors of volunteers' reactions might help build better theories for managing the non-profit-social enterprise transition and designing public policies to support scaling up the impact of successful social purpose organisations.

For practitioners, the research underlines the importance of participatory mechanisms in volunteer management. By managing transitions better, non-profit organisations can expand their social impact by acquiring more financial resources through market-based activities closely related to their original activities and keeping their volunteers. The study elucidates the relevance of the crowding-out effect and indicates some hypothetical moderating variables influencing its potential degree.

This paper aims to inform the readers an overview of expected impacts of sea level rise (SLR) and climate change on rice crops area, yield and the urgent need to build climate responsive infrastructures to a coastal district, Alappuzha – a high-risk area which is already under mean sea level (MSL). This research carried out to understand the realities and impacts with respect to the exposures of rise in SLR and possible inundation extent of crop land. The extreme precipitation events have caused crop loss and damage, numerous casualties and enormous economic loss in this district during the recent past and project the likely impacts under anticipated climate change.

Global sea levels have already been risen noticeably as a result of climate change, and this trend is anticipated to continue. To reflect on the research objectives, the paper projects a climate change scenario analysis and impact assessment on the major crop grown, i.e. rice, using a crop simulation model, DSSAT 4.7 as the first part of the study. QGIS 3.28 version and Erdas Imagine software were used for land use land cover analysis and to delineate possible inundation in the major land use land cover, especially in agriculture area under SLR scenario. It points out the need to equip the district urgently with climate responsive agriculture strategies as majority of the area comes under 10 mts of elevation as per the Sentinel 2 data. For better adapting to the current and future climate change impacts in the aspects of built environment such as early warnings in farm sector in particular and forests, urban water management, transportation systems, building construction and operation and land use planning in general. Climate change is no longer a policy issue alone; now it is a common man’s nightmare. For a coastal state like Kerala, extreme climate events during 2018 and 2019 and 2021 have posed substantial impacts and damages on the environment and society. The impacts hit the vulnerable communities in multiple ways.

From the analysis, it was revealed that there is an increasing trend in rainfall observed over the past three decades in Alappuzha district. It is projected that day and night time temperatures may increase in Alappuzha by 2.5°C and 2.6°C by 2100, respectively, under RCP 4.5. With unchecked pollution or emission reduction actions, warming may further rise and hence the median projection when SLR reaches 2.4 meters (8 ft) at Alappuzha to Cochin coast is 2130s. The possible inundation analysis shows that around 53.48% of the coastal agriculture land may be likely inundated if SLR is only with mitigation measures such as extreme carbon cuts, SLR rise can be delayed till 2200. Alappuzha is known as the rice bowl of Kerala; however, it is highly exposed to climate vulnerability in terms of its unique environmental geographical settings like coastal wetlands, lagoons and sand beaches. DSSAT simulations shows that Uma rice, a major ruling variety in the region, may have yield reductions of up to 13% in the near century for Alappuzha.

This paper in general explains the projected climate change perspectives for Alappuzha, a climate change hotspot of Kerala with respect to SLR and coastal agriculture. and a review of the progression of DRR in the built environment and mainstreaming CCA and DRR by government and other agencies in the state.

This study underscores the urgent need for climate-responsive agricultural strategies in Alappuzha, Kerala, due to anticipated sea level rise, climate change, and land use changes. Equipping farmers with the knowledge and tools to adapt is essential for ensuring food security and sustainable livelihoods. Implementing climate-resilient practices and technologies will help mitigate adverse effects on rice crops, promoting economic stability and resilience in the region. Involving local stakeholders in the adaptation process is crucial, as their participation can enhance collaboration, increase awareness, and accelerate the adoption of sustainable agricultural practices, making the transition smoother and more effective.

It is the responsibility of the scientific community to inform the knowledge gained for the benefit of the society, especially on criticality of altering the existing land use pattern and building climate resilient coastal infrastructures. Studies such as this can stand as basis for implementing planned adaption actions. This is to conclude that instead of working in silos, mainstreaming climate change adaptation holistically across sectors is very necessary at this crucial hour. Participatory action plans and policies involving all local stakeholders can strengthen awareness and fasten the learning processes for adaptation including managed retreats.

At present, there are no specific studies, on the impacts of climate change and SLR on rice cropping systems in the district which specifically inform how to mainstream adaptation in the agriculture strategies in low lying coastal zones of Alappuzha.

We enquire whether short-time work (STW) avoids firings as intended by policymakers and is associated with unintended side effects by subsidising some establishments and locking in some employees. Additionally, where it was feasible, establishments used working from home (WFH) to continue working without risking an increase in COVID-19 infections and allowing employed parents to care for children attending closed schools.

Using 21 waves of German high-frequency establishment panel data collected during the COVID-19 crisis, we investigate how STW and WFH are associated with hirings, firings, resignations and excess labour turnover (or churning).

Our results show the important influences of STW and working from home on employment dynamics during the pandemic. By means of STW, establishments are able to avoid an increase in involuntary layoffs and hiring decreases significantly. In contrast, WFH is associated with a rise in resignations, as can be expected from a theoretical perspective.

While most of the literature on STW and WFH is unrelated and remains descriptive, we consider them in conjunction and conduct panel data analyses. We apply data and methods that allow for the dynamic pattern of STW and working from home during the pandemic. Furthermore, our data include relevant establishment-level variables, such as the existence of a works council, employee qualifications, establishment size, the degree to which the establishment was affected by the COVID-19 crisis, industry affiliation and a wave indicator for the period the survey was conducted.

The use of polysaccharides increases solubility and consistency and causes functions such as viscosity? Moisture and food emulsifier stabilizer. This study aims to enrich the formulation of low-fat mozzarella cheese using microcoated vitamin D3 (VD3).

This study investigates the addition of hydrocolloids to low-fat mozzarella cheese to enhance its properties and nutritional value. Tests were conducted on cheese samples with 0.05% and 0.25% hydrocolloid concentrations at various stages: before production and at three and six months’ postproduction. The samples were evaluated for elasticity, pH and solubility to select the best one, which was then fortified with VD3. The vitamin was microencapsulated using alginate and whey protein to shield it from light and oxygen, optimizing the formula using the response surface method. The fortified cheese was tested for VD3 content over its shelf life.

Results indicated that all hydrocolloids tested improved moisture and meltability of the cheese while higher protein levels increased stretchability two to threefold. Rice starch hydrocolloid at 0.05% concentration was chosen due to superior sensory scores and minimal oil separation. This study concluded that VD3 levels remained stable during the cheese’s shelf life, suggesting that this approach could enhance the nutritional value of low-fat cheese without compromising its quality. Therefore, after examining the obtained results and comparing the regression models, the results indicated that the Quadratic model was chosen to investigate the effect of independent variables on the response rate, which had a statistically significant difference with other models (p = 0.0019). Also the results of the area under the curve and using the encapsulation efficiency equation, the percentage of microencapsulated vitamin was obtained, and according to the simulation results, the encapsulation efficiency was reported as 89.02%.

Developing innovative functional dairy products fortified with VD3 could improve the vitamin D status in deficient populations. Therefore, these designs can be applied at industrial scales for functional cheese production.

This paper examines how different configurations of societal impact are pursued by purpose-driven organizations (PDOs) and how these configurations align with the application of varying supply chain design (SCD) practices.

This multi-method study uses quantitative data from 1588 B Corps and qualitative data from 316 B Corps to examine how PDOs align SCD with the pursuit of diverse types of societal impact. The authors first conduct a cluster analysis to group organizations based on the impact they create. Second, qualitative content analysis connects impact with enabling SCD elements.

The analysis of the five identified clusters provides detailed empirical insights on influencers, design decisions and building blocks adopted by PDOs to drive a range of societal impacts. Specifically, the nature of the impact pursued affects (1) whether a PDO will be more influenced by a need in the political environment or an opportunity in the industry environment, (2) the relative importance of the design of social flows versus material flows and (3) the need to develop new relational resources with beneficiaries versus leveraging existing capabilities to manage inter-firm processes.

This study responds to calls to disaggregate different dimensions of societal impact and examines the relationship between SCD and a breadth of sustainability impacts for different stakeholders. In doing so, the authors identify four SCD pathways organizations can follow to achieve specific societal impacts. This study is also the first to employ a supply chain perspective in the study of certified B Corps.