Groundwater Age and Origin and Its Relation with Anthropogenic and Climatic Factors

Data Availability Statement: The data used in this study includes spatial data, isotopic data of precipitation, and water bodies. This is freely available and can be accessed from the websites given in the data section of the manuscript. The isotopic data on groundwater is the property of the Center of Excellence in Water Resources Engineering (CEWRE), Lahore, and the Pakistan Council of Research in Water Resources (PCRWR), which can be retrieved by making a request to the corresponding author. However, the climatic data is the property of the Pakistan Meteorological Department (PMD) and can be requested via official channels.Groundwater plays a major role in addressing the worldwide problem of water scarcity and food security. With a growing population and increasing urbanization, there is a rising demand for groundwater to meet agricultural and domestic water needs. A variety of advanced approaches are necessary to sustain groundwater management. This study investigated the age and origin of groundwater, as well as its relationship with anthropogenic and climatic factors. Stable isotopes were used, namely oxygen-18 (18O) and deuterium (2H) for the estimation of groundwater origin and radioactive isotopes of Tritium (3H) for the estimation of its age. The investigation of stable isotopes revealed that the aquifer is predominantly influenced by river water, with a minor contribution from rainwater. Furthermore, the analysis of radioactive isotopes revealed that the groundwater age ranges from 5 to 50 years old in most areas. Older groundwater is predominantly found in urban areas, while younger groundwater is present in agricultural and woodland regions. However, the presence of “old” water in the upper groundwater layers in urban areas is attributed to over-abstraction and limited natural recharge. The primary climatic factor that governs the age and origin of groundwater is rainfall upstream of the study area, which directly contributes to the river flows. The rainfall is high in the east but, due to urbanization, recharge is decreased. Consequently, old and river recharge groundwater is found in this area. These observations underscore the unsustainable and alarming use of groundwater in urban areas.Center of Excellence in Water Resources Engineering; Pakistan Institute of Nuclear Science and Technology (PINSTECH), Pakistan; Pakistan Council of Research in Water Resources

An examination of work-life balance policies and practices: A case analysis of Ghanaian judges

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonWork-life balance (WLB) is an emerging concept in Africa and currently not much is known about the WLB experiences of judges, particularly in Africa. Based on this, the study explored the WLB policies and practices of judges in Ghana. In addition, many studies have neglected the experiences of judges in WLB research. Specifically, the study critically examined the notion of work-life balance among Ghanaian judges, identified the available work-life balance policies and practices adopted by the Ghanaian judiciary; investigated the factors that facilitate or constrain the utilisation of work-life balance policies and practices in the Ghanaian judiciary and the coping strategies adopted by Ghanaian judges. The study adopted a qualitative research method based on an interpretivist philosophy. The research approach adopted was inductive and the research strategy was a case study considering Ghanaian judges. Primary data was collected from 32 judges in Ghana using a semi-structured interview guide. The sample for this study was drawn from the population of Ghanaian judges in the Supreme Court, Court of appeal, High Court of justice, Circuit court and District court. The data collected were analysed using thematic analysis based on the recommendations of Braun and Clarke (2012). The findings indicate that the judges had different notions of WLB: managing work and non-work demands, increased autonomy and control, absence of work-life conflict, healthy work and non-work experience and time for family. There was variance in the judges’ perception of WLB and their experience. The range of WLB initiatives in the Ghanaian judiciary were limited to flexible leave arrangements. Flexible working arrangements, flexible locations, and other arrangements were not prominent. The prevailing employment legislation was found to be reactive, and not reflective of the current realities in the workplace. Factors that facilitate the uptake of WLB initiatives are career stage, gender stereotype, marital status/dependants, health, support, and awareness. Factors that constrained the uptake of WLB initiatives are perceived career damage, lack of information, cultural stereotypes, organisational culture, economic factors, lack of support, and politics/corruption. Assistance seeking approach such as Family/spousal support, psychologists, spiritual/religious activities, and paid workers/house helps were the major coping strategies employed by judges. Other personal strategies included weekend travels, and rest and leisure activities. Strategies to transform WLB in the Ghanaian judiciary were digital transformation, expanding the workforce, introducing the rota and court sharing system and setting up more courts. The study concluded that WLB is socially constructed and varies depending on the individual’s perspective and experiences. The scope of WLB initiatives in the Ghanaian judiciary is streamlined to leave arrangements, and this connects with the fact that the concept is still emerging. The study also concludes that the factors that constrain the uptake of WLB initiatives in the judiciary outweigh those that facilitate the uptake of WLB initiatives. The study hence recommended the need to address the WLB experiences of judges in Ghana in terms of their workload and long working hours. There is also the need for regulatory and supervisory frameworks to be established or strengthened as the case may be to assist public and private organisations in Ghana (re)design work more humanely and in line with globally accepted standards. Issues like support and awareness need to be addressed to mitigate the notion of perceived career damage, lack of information and cultural stereotypes

New laminar flame speed correlation for lean mixtures of hydrogen combustion with water addition under high pressure conditions

Hydrogen may become a substitute for liquid fossil fuels, contributing to greenhouse gas emissions reductions in internal combustion engines. Numerical simulations play a critical role in the advancement of these engines, with laminar flame speed being the main input. Experimental data of hydrogen flame speed at elevated pressures are scarce, due to the instability of the flames. Nonetheless, stable hydrogen flames can be predicted using chemical kinetics models. Moreover, the injection of water into the hydrogen fuelled engine could offer several benefits to engine combustion and emission performance, as it modulates the laminar flame speed within the combustion chamber and this effect has not been completely understood. Currently, no correlation exists to predict the laminar flame speed of hydrogen-air combustion with water addition under lean mixture engine operating conditions. In this study, we have extended the newly developed laminar flame speed correlation of hydrogen-air combustion to account for the effects of water addition under engine relevant conditions by using chemical kinetic laminar flame speed values. The laminar flame speed correlation was derived for pressures from 10 to 70 bar, temperatures from 400 to 800 K, equivalence ratios from 0.35 to 1 and water addition by mole from 0 to 20%. The hydrogen laminar flame speed correlation was expressed using polynomial forms with reduced order and number of terms with optimized values of coefficients. Additionally, a new exponential term was proposed to the power term α of the laminar flame speed correlation to capture the coupled effects of pressure and temperature on laminar flame speeds under engine-relevant lean burn water-diluted operating conditions

MDEmoNet: A Multimodal Driver Emotion Recognition Network for Smart Cockpit

The automotive smart cockpit is an intelligent and connected in-vehicle consumer electronics product. It can provide a safe, efficient, comfortable, and enjoyable human-machine interaction experience. Emotion recognition technology can help the smart cockpit better understand the driver's needs and state, improve the driving experience, and enhance safety. Currently, driver emotion recognition faces some challenges, such as low accuracy and high latency. In this paper, we propose a multimodal driver emotion recognition model. To our best knowledge, it is the first time to improve the accuracy of driver emotion recognition by using facial video and driving behavior (including brake pedal force, vehicle Y-Axis position and Z-Axis position) as inputs and employing a multi-Task training approach. For verification, the proposed scheme is compared with some mainstream state-of-The-Art methods on the publicly available multimodal driver emotion dataset PPB-Emo.10.13039/501100001809-National Natural Science Foundation of China; 10.13039/100006190-Research and Development; 10.13039/501100003009-Science and Technology Development Fund

Improved Adversarial Transfer Network for Bearing Fault Diagnosis under Variable Working Conditions

Data Availability Statement: Data are contained within the article.Bearings are one of the critical components of rotating machinery, and their failure can cause catastrophic consequences. In this regard, previous studies have proposed a variety of intelligent diagnosis methods. Most existing bearing fault diagnosis methods implicitly assume that the training and test sets are from the same distribution. However, in real scenarios, bearings have been working in complex and changeable working environments for a long time. The data during their working processes and the data used for model training cannot meet this condition. This paper proposes an improved adversarial transfer network for fault diagnosis under variable working conditions. Specifically, this paper combines an adversarial transfer network with a short-time Fourier transform to obtain satisfactory results with the lighter network. Then, this paper employs a channel attention module to enhance feature fusion. Moreover, this paper designs a novel domain discrepancy hybrid metric loss to improve model transfer learning performance. Finally, this paper verifies the method’s effectiveness on three datasets, including dual-rotor, a Case Western Reserve University dataset and the Ottawa dataset. The proposed method achieves average accuracy, surpassing other methods, and shows better domain alignment capabilities.This work was supported in part by the Natural Science Foundation of China (No. 52175116), Major Research Programs of the Natural Science Foundation of China (No. 92060302), the Research Foundation of the Higher Educational Key Laboratory for Flexible Manufacturing Equipment Integration of Fujian Province, the Xiamen Institute of Technology, the National Key Science and Technology Infrastructure Opening Project Fund for Research and Evaluation facilities for Service Safety of Major Engineering Materials and the Aeronautical Science Foundation (No. 2019ZB070001). Also, this work was supported in part by the Royal Society award (number IEC\NSFC\223294) to Asoke K. Nandi. Jun Wang acknowledges the financial support from the Innovative Leading Talents Scholarship and Brunel University London

Changes in social norms during the early stages of the COVID-19 pandemic across 43 countries

Data availability: The data generated in this study have been deposited in the Open Science Framework (https://doi.org/10.17605/OSF.IO/STKFR). Non-experimental data included in our datasets (i.e., intensity of government response to COVID-19 is the Stringency Index, COVID-19 deaths and cases per million) are taken from the Oxford COVID−19 Government Response Tracker [22 Hale, T. et al. A global panel database of pandemic policies (Oxford COVID−19 Government Response Tracker). Nat. Human Behav. https://doi.org/10.1038/s41562-021-01079-8 (2021).] and Our World in Data [38 Ritchie, H. et al. Coronavirus Pandemic (COVID-19). Our World in Data. https://ourworldindata.org/coronavirus (2020).] (downloaded November 2020). Wave 0 data are from [3 Gelfand, M. J. et al. Differences between tight and loose cultures: a 33-nation study. Science 332, 1100–1104 (2011).[ and Wave 1 data are from [5 Eriksson, K. et al. Perceptions of the appropriate response to norm violation in 57 societies. Nat. Commun. 12, 1481 (2021).].Code availability: The survey and analysis code are available at the Open Science Framework (https://doi.org/10.17605/OSF.IO/STKFR).Supplementary information is available online at: https://www.nature.com/articles/s41467-024-44999-5#Sec40 .The emergence of COVID-19 dramatically changed social behavior across societies and contexts. Here we study whether social norms also changed. Specifically, we study this question for cultural tightness (the degree to which societies generally have strong norms), specific social norms (e.g. stealing, hand washing), and norms about enforcement, using survey data from 30,431 respondents in 43 countries recorded before and in the early stages following the emergence of COVID-19. Using variation in disease intensity, we shed light on the mechanisms predicting changes in social norm measures. We find evidence that, after the emergence of the COVID-19 pandemic, hand washing norms increased while tightness and punishing frequency slightly decreased but observe no evidence for a robust change in most other norms. Thus, at least in the short term, our findings suggest that cultures are largely stable to pandemic threats except in those norms, hand washing in this case, that are perceived to be directly relevant to dealing with the collective threat.Knut and Wallenberg Grant “How do human norms form and change?” 2016.0167. (G.An.). The Swedish Research Council grant “Norms & Risk: Do social norms help dealing with collective threats” 2021-06271 (G.An.). Ministero dell’Istruzione dell’Università e della Ricerca, PRIN 2017, prot. 20178TRM3F (D.B.). Universidad de Los Andes, Fondo Vicerrectoría de Investigaciones (J.-C.C.). Ministry of Innovation and Technology of Hungary, National Research, Development and Innovation Fund NKFIH-OTKA K135963 (M.F.). Grant 23-061770 S of the Czech Science Foundation (M.H. and S.G.). RVO: 68081740 of the Institute of Psychology, Czech Academy of Sciences (M.H. and S.G.). RA Science Committee, research project N.20TTSH-070 (A.Gr. and N.Khac.). Open University of Israel, 511687 (R.N.). HSE University Basic Research Program (E.O.). Project BASIC (PID2022-141802NB-I00) funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe” (A.Sá.). US Army Research Office Grant W911NF-19-1-910281 (B.S.). Netherlands Organisation for Scientific Research, 019.183SG.001 (E.S.). Netherlands Organisation for Scientific Research, VI.Veni.201 G.013 (E.S.). European Commission, Horizon 2020-ID 870827 (E.S.). UKRI Grant “Secret Power” No. EP/X02170X/1 awarded under the European Commission’s “European Research Council - STG” Scheme (G.A.T.)

Renewable energy sources integration via machine learning modelling: A systematic literature review

The use of renewable energy sources (RESs) at the distribution level has become increasingly appealing in terms of costs and technology, expecting a massive diffusion in the near future and placing several challenges to the power grid. Since RESs depend on stochastic energy sources —solar radiation, temperature and wind speed, among others— they introduce a high level of uncertainty to the grid, leading to power imbalance and deteriorating the network stability. In this scenario, managing and forecasting RES uncertainty is vital to successfully integrate them into the power grids. Traditionally, physical- and statistical-based models have been used to predict RES power outputs. Nevertheless, the former are computationally expensive since they rely on solving complex mathematical models of the atmospheric dynamics, whereas the latter usually consider linear models, preventing them from addressing challenging forecasting scenarios. In recent years, the advances in machine learning techniques, which can learn from historical data, allowing the analysis of large-scale datasets either under non-uniform characteristics or noisy data, have provided researchers with powerful data-driven tools that can outperform traditional methods. In this paper, a systematic literature review is conducted to identify the most widely used machine learning-based approaches to forecast RES power outputs. The results show that deep artificial neural networks, especially long-short term memory networks, which can accurately model the autoregressive nature of RES power output, and ensemble strategies, which allow successfully handling large amounts of highly fluctuating data, are the best suited ones. In addition, the most promising results of integrating the forecasted output into decision-making problems, such as unit commitment, to address economic, operational and managerial grid challenges are discussed, and solid directions for future research are provided

Into the purple ocean: The formation and dynamics of a transcultural fandom as a result of cultural diffusion through K-pop

Within the context of cultural exchange, research into the impact of Korean pop (K-pop) music and its idols largely focuses on their marketability rather than the psychological effects this exchange may have on their fandom. The aim of this research, therefore, is to investigate the formation and dynamics of a transcultural fandom as a result of cultural diffusion through K-pop through the relationship between Bangtan Sonyeondan (a K-pop group) and their fandom, Adorable Representative Master of Ceremonies for Youth (ARMY). Through this research we hope to examine the formation of a new transcultural fandom “in-group” as a function of cultural diffusion, as well as the role of the idol in this process. A quantitative design was employed, consisting of a cross-sectional survey with 116 participants completing measures of identification with all of humanity, universal values, online group identification, knowledge of in-group norms, and remote acculturation levels. Results revealed that stronger identification with the in-group, ARMY, was a significant predictor of ability to detect and use in-group cues to predict target identities successfully, increased remote acculturation, and increased identification with all of humanity. Overall, the research provides insights into the relationships between idol and fan, the levels of remote acculturation experienced by ARMY, and the subsequent identities that are constructed within the new transcultural context of their global community

Corporate credit default swap systematic factors

Data Availability: All data used is obtained from third-party data providers. Data will be made available on request with the permission of the data providers.JEL: G12, G13, G23.Supporting Information is available online at: https://onlinelibrary.wiley.com/doi/10.1002/fut.22505#support-information-section .We examine a comprehensive set of systematic and firm-specific determinants of the credit default swap (CDS), using a two-step approach to explore the factor's effect on CDS spread changes. We show that systematic factors are important and account for the most changes in the CDS spreads (with average R2 of 35%), while firm-specific factors are limited (with R2 of 5% in panel regression) with only 4 out of 28 firm-specific factors being significant. It implies that the systematic factors are overlooked in the literature, and they can provide many implications for practitioners in CDS pricing and the firm's credit risk management

Green Human Resource Management, Green Supply Chain Management and Regulation and Legislation and its Effects on Sustainable Development Goals in Jordan

Data Availability Statement: No new data were created or analyzed in this study. Data sharing is not applicable to this article.A preprint version of this article is available at: https://www.preprints.org/manuscript/202312.1706/v1 - it has not been certified by peer review.In recent decades, sustainability and environmental concerns have become increasingly significant topics of discussion. This article aims to propose a conceptual framework of a research model including the correlations between government regulations and legislations, Green Human Resource Management (GHRM), Green Supply Chain Management (GSCM), and Sustainable Development Goals (SDGs). The methodological approach adopted in this study included conducting a review of the relevant literature and accessing databases and search engines to gather information. The current article presents a novel approach to understanding how organizations and regulators can collaborate to drive sustainable development in this domain. This study also adds significant value due to its unique contribution in connecting GHRM, GSCM, and government regulation and legislation, particularly in the context of sustainable development and its link to promoting decent work and economic growth (SDG8), responsible consumption and production (SDG12), and addressing climate action (SDG13). The rarity of articles addressing these interrelated topics, especially within the specific context of Jordan, where such research has been largely absent, underscores the distinctive nature of this study. Furthermore, this article stands out for its comprehensive incorporation of legal and regulatory aspects into the discourse on organizational GHRM and GSCM practices and their alignment with the pursuit of SDGs. By providing valuable insights for decision makers and organizations, including a thorough examination of the barriers involved, this article serves as an essential resource for understanding and navigating the complex interplay between environmental sustainability, GHRM, GSCM, and governmental regulations. Based on the analysis of the findings, a conceptual framework is proposed based on three environmental dimensions and six green practices that have discernible effects. Finally, it is envisaged that this study will offer directions for future research work to use another approach and another environment.This research received no external funding