bluuebunny/crossref_metadata_2025_split huggingface dataset:
Large group decision-making considering multiple classifications for participators: a method based on preference information on multiple elements of alternatives
Authors: Cao Ping-Ping , Zheng Jin , Wang Shuang , Li Ming-Yang , Wang Xin-Yan 
Published: August 2023

AbstractIn large group decision-making, participators with different knowledge structures, backgrounds, and other characteristics are unlikely to accurately evaluate alternatives. For this, it is necessary to decompose alternatives into several elements, and consider the participators’ preferences for elements of alternatives and the multiple classifications for participators according to their characteristics. However, related studies are still scarce. The objective of this paper is to propose a multi-elemental large group decision-making method, in which the desirable alternative(s) are selected from a set of feasible alternatives according to the preference information on multiple elements of alternatives provided by participators from multiple subgroups, and multiple classifications for participators are considered. In the method, according to the strict preference ordering of elements provided by participators, the percentage distributions on preferences of each subgroup concerning each element are firstly presented under each classification for participators. Secondly, the decision weight of each subgroup is determined by three factors, i.e., the consensus of preferences provided by each subgroup, the organizer’s preference for each subgroup, and the number of participators in each subgroup. Then, the comprehensive preference concerning each element is determined by combing the preference information from multiple subgroups and the decision weights of multiple subgroups, the overall preference vector can be obtained under each classification, and the virtual alternatives are determined by normalizing the overall preference vector. Further, considering multiple classifications for participators, the overall dominant degrees of alternatives can be obtained by calculating the similarity degrees between each virtual alternative and each alternative, thus the ranking order of alternatives can be obtained based on the overall dominant degrees of alternatives. Finally, an example is given to confirm the feasibility of the proposed method. The results of the sensitivity and comparative analyses show that the proposed method is applicable and effective. The proposed method can further enrich and improve the theory and approach of large group decision-making with multiple elements considering multiple classifications for participators.
Zinc–Bromine Rechargeable Batteries: From Device Configuration, Electrochemistry, Material to Performance Evaluation
Authors: Alghamdi Norah S. , Rana Masud , Peng Xiyue , Huang Yongxin , Lee Jaeho , Hou Jingwei , Gentle Ian R. , Wang Lianzhou , Luo Bin 
Published: August 2023

AbstractZinc–bromine rechargeable batteries (ZBRBs) are one of the most powerful candidates for next-generation energy storage due to their potentially lower material cost, deep discharge capability, non-flammable electrolytes, relatively long lifetime and good reversibility. However, many opportunities remain to improve the efficiency and stability of these batteries for long-life operation. Here, we discuss the device configurations, working mechanisms and performance evaluation of ZBRBs. Both non-flow (static) and flow-type cells are highlighted in detail in this review. The fundamental electrochemical aspects, including the key challenges and promising solutions, are discussed, with particular attention paid to zinc and bromine half-cells, as their performance plays a critical role in determining the electrochemical performance of the battery system. The following sections examine the key performance metrics of ZBRBs and assessment methods using various ex situ and in situ/operando techniques. The review concludes with insights into future developments and prospects for high-performance ZBRBs.
When things go wrong: the recall of AI systems as a last resort for ethical and lawful AI
Authors: Tartaro Alessio 
Published: August 2023

Abstract
This paper presents an initial exploration of the concept of AI system recall, primarily understood as a last resort when AI systems violate ethical norms, societal expectations, or legal obligations. The discussion is spurred by recent incidents involving notable AI systems, demonstrating that AI recalls can be a very real necessity. This study delves into the concept of product recall as traditionally understood in industry and explores its potential application to AI systems. Our analysis of this concept is centered around two prominent categories of recall drivers in the AI domain: ethical-social and legal considerations. In terms of ethical-social drivers, we apply the innovative notion of “moral Operational Design Domain”, suggesting AI systems should be recalled when they violate ethical principles and societal expectation. In addition, we also explore the recall of AI systems from a legal perspective, where the recently proposed AI Act provides regulatory measures for recalling AI systems that pose risks to health, safety, and fundamental rights. The paper also underscores the need for further research, especially around defining precise ethical and societal triggers for AI recalls, creating an efficient recall management framework for organizations, and reassessing the fit of traditional product recall models for AI systems within the AI Act's regulatory context. By probing these complex intersections between AI, ethics, and regulation, this work aims to contribute to the development of robust and responsible AI systems while maintaining readiness for failure scenarios.
A Deep Learning-Based Multi-objective Optimization Model for PM2.5 Prediction
Authors: Xu Wenkai , Fu Fengchen , Zhang Qingqing , Wang Lei 
Published: August 2023

AbstractAir pollution caused by particulate matter with a diameter of less than 2.5 μm (PM2.5) poses a serious threat to human health and the environment. Predicting PM2.5 concentrations and controlling emissions are crucial for pollution prevention and control. This study proposes a comprehensive solution based on weight-sharing deep learning and multi-objective optimization. The proposed approach first utilizes a model that combines the Convolutional Neural Network and Long Short-Term Memory Neural Network to analyze data from 13 air quality monitoring stations in Xi'an City. By simultaneously inputting data from different monitoring stations, the model can extract highly correlated spatiotemporal features, enabling accurate predictions of PM2.5 concentrations for specific monitoring stations using LSTM. In addition, a multi-objective optimization model is established with the primary goal of achieving maximum total emission reduction. This model takes into account four key factors: the total emission reduction, the task of emission reduction, the government subsidy, and the total cost of emission reduction. To obtain the emission reduction of PM2.5 concentration at 13 monitoring stations, 5 classical intelligence algorithms are employed to solve the model. Experimental results demonstrate the effectiveness of the proposed prediction model, with an average Root Mean Square Error (RMSE) of 12.820 and a fitting coefficient (R2) of 0.907, outperforming all comparison models. The proposed model exhibits strong generalization ability, making it applicable to different time and space conditions. Furthermore, it can be adapted for calculating emission reduction of other air pollutants. Lastly, the multi-objective optimization model achieves significant success in terms of total emission reduction. This study provides a new reference in the field of artificial intelligence and its application to air pollution control. The findings hold great significance for promoting public health and environmental protection.
Partisan Biases among the Unemployed
Authors: Urbatsch R. 
Published: August 2023

AbstractUnemployed people are relatively rarely studied in political science. Yet, with their economic significance and centrality to many political debates, they can provide insight on many questions, including just how far partisan biases – where opinions and even factual perceptions follow what reflects well on their holder's preferred political party – extend. The economic and emotional costs of joblessness make its evaluation an unlikely seeming case for partisan effects. Surveys in the United States and Great Britain nevertheless show that partisan alignment predicts unemployed individuals' evaluation of their economic situation: unemployed individuals identifying with parties represented in the national executive report more positively on their household finances (and on the national economic situation) than do non-partisans, while those identifying with the opposition report more negatively. These effects are especially substantial among people interested in politics. Even something as personal and affectively intense as unemployment is viewed through a partisan scrim.
The Impact of Government Participation on the Political Trust of Populist Party Supporters
Authors: Juen Christina-Marie 
Published: August 2023

AbstractCitizens are more trustful of politics if their preferred party is an electoral winner and becomes part of the government. However, there remains the question of whether this positive effect of joining the government also holds for supporters of populist parties. Populists show low levels of political trust, as they strongly criticize the political elite. This study argues that voters of populist parties perceive the political system as more responsive to their concerns when their preferred party becomes part of the government and so they become more trustful of politics. Drawing on the case of Austria, the analyses demonstrate that political trust among populist party voters is higher when their party is in government. In contrast, non-populist voters' level of political trust is more stable, even when their party is not in government.
Determinates of anemia among Human Immune Deficiency Virus positive children on Anti-retro Viral Therapy in selected health facilities, Northwest Ethiopia: A Case-Control Study
Authors: Tiruneh Misganaw Guadie , Kebede Bizuneh Fassikaw 
Published: August 2023

Abstract
Even though antiretroviral therapy (ART) access for human immunodeficiency virus (HIV)-infected children increased dramatically, anaemia has continued as a challenge regardless of a cluster of differentiation (CD4) count and viral load. Hence, the present study aimed to assess the determinants of iron deficiency anaemia among children living with HIV after the initiation of ART. An institution-based unmatched case–control study was conducted among consecutively selected 712 children on HIV care from 1 September to 30 October 2022 in the Metekel zone. A pre-tested and structured data extraction checklist was used to collect the data. Data were analysed using STATA version 16 software. Binary logistic regression was used to find the association between independent variables and anaemia. The level of statistical significance was declared at a value of P < 0⋅05. A total of 712 HIV-positive children (178 cases and 534 controls) were included in this study, with a completeness rate of 98⋅8 %. In multivariable analysis, variables that have a statistically significant association with anaemia were as follows: CD4 count <350 (Adjusted Odds Ratio [AOR] 2⋅76; 95 % CI 1⋅76, 4⋅34), World Health Organization (WHO) clinical stage III (AOR 7⋅9; 95 % CI 3⋅5, 17⋅91) and stage IV (AOR 7⋅8; 95 % CI 3⋅37, 18⋅1), cotrimoxazole prophylaxis therapy (AOR 0⋅5; 95 % CI 0⋅31, 0⋅8) and mid-upper arm circumference (MUAC) ≤11⋅5 mm (AOR 2⋅1; 95 % CI 1⋅34, 3⋅28). The present study found that CD4 count, WHO clinical stage, cotrimoxazole prophylaxis therapy and MUAC were significantly associated with anaemia in children on ART. Therefore, continuous screening of anaemia and nutritional treatment is essential in these patients.
Middle Visean (Mississippian) conodonts from shallow-water deposits in the Yashui section, Guizhou, South China, and their stratigraphic significance
Authors: Wang Qiulai , Qi Yuping , Yao Le 
Published: August 2023

AbstractThe typical Mississippian shallow-water deposits of the Jiusi and Shangsi formations are well exposed in the Yashui section in southern Guizhou, South China. The strata are composed mainly of platform limestones intercalated with shales and sandstones. Conodonts obtained from the limestones are dominated by two assemblages of cavusgnathids: the Cavusgnathus aff. Cav. unicornis and Clydagnathus windsorensis assemblage from the upper Jiusi Formation and the Cavusgnathus unicornis assemblage from the lowest Shangsi Formation. Vogelgnathus campbelli (Rexroad, 1957) is reported for the first time in Eastern Paleotethys and is characterized by small lateral denticles. The evolutionary first occurrence of Cavusgnathus unicornis Youngquist and Miller, 1949 is recognized as a marker for the regional Shangsian stage. This biostratigraphic datum is interpreted to be correlative with other shallow-water conodont zones marked by Cavusgnathus unicornis s.l. and similar species from North America and Europe.
The association of diet-dependent acid load with colorectal cancer risk: a case–control study in Korea
Authors: Tran Tao Thi , Gunathilake Madhawa , Lee Jeonghee , Oh Jae Hwan , Chang Hee Jin , Sohn Dae Kyung , Shin Aesun , Kim Jeongseon 
Published: August 2023

AbstractAcid–base disequilibrium is a contributor to cancer development because it affects molecular activities such as insulin-like growth factor 1 levels and adiponectin production. However, evidence of an association of diet-induced acid–base imbalance with colorectal cancer (CRC) is limited. We examined whether colorectal carcinogenesis is attributable to a diet with a high acid load. We recruited a total of 923 CRC cases and 1846 controls at the National Cancer Center in Korea for inclusion in a case–control study. We collected information on nutrient intake and specific clinical parameters of CRC by using a semiquantitative FFQ and medical records, respectively. Potential renal acid load (PRAL) and net endogenous acid production (NEAP) were used to estimate diet-dependent acid load. We used an unconditional logistic regression model to analyse the association. Dietary acid load scores had a positive association with the odds of CRC (OR = 2·31 (95 % CI 1·79, 2·99) and OR = 2·14 (95 % CI 1·66, 2·76) for PRAL and NEAP, respectively, Pfor trend < 0·001). A stronger positive association was observed for females (OR = 3·09, 95 % CI 1·93, 4·94) than for males (OR = 1·71, 95 % CI 1·27, 2·31). Furthermore, acidogenic diets appeared to affect rectal cancer more strongly than colon cancer in females. Our study contributes to reinforcing epidemiological evidence regarding a detrimental effect of acidogenic diets on colorectal carcinogenesis. Thus, it is important to pay attention to the balance of acidogenic (e.g. poultry and red meat) and alkalinogenic foods (e.g. fruits and vegetables) in CRC prevention, especially for females.
Peripheral inflammation associated with depression and reduced weight loss: a longitudinal study of bariatric patients
Authors: McLaughlin Anna P. , Lambert Ellen , Milton Rebecca , Mariani Nicole , Kose Melisa , Nikkheslat Naghmeh , Patsalos Olivia , Ferraro Luca , Chamseddine Ghassan , Panagiotopoulos Spyros , Chang Avril , Ramar Sasindran , Patel Ameet , Rubino Francesco , Mondelli Valeria 
Published: August 2023

AbstractBackgroundResearch implicates inflammation in the vicious cycle between depression and obesity, yet few longitudinal studies exist. The rapid weight loss induced by bariatric surgery is known to improve depressive symptoms dramatically, but preoperative depression diagnosis may also increase the risk for poor weight loss. Therefore, we investigated longitudinal associations between depression and inflammatory markers and their effect on weight loss and clinical outcomes in bariatric patients.MethodsThis longitudinal observational study of 85 patients with obesity undergoing bariatric surgery included 41 cases with depression and 44 controls. Before and 6 months after surgery, we assessed depression by clinical interview and measured serum high-sensitivity C-reactive protein (hsCRP) and inflammatory cytokines, including interleukin (IL)-6 and IL-10.ResultsBefore surgery, depression diagnosis was associated with significantly higher serum hsCRP, IL-6, and IL-6/10 ratio levels after controlling for confounders. Six months after surgery, patients with pre-existing depression still had significantly higher inflammation despite demonstrating similar weight loss to controls. Hierarchical regression showed higher baseline hsCRP levels predicted poorer weight loss (β = −0.28, p = 0.01) but had no effect on depression severity at follow-up (β = −0.02, p = 0.9). Instead, more severe baseline depressive symptoms and childhood emotional abuse predicted greater depression severity after surgery (β = 0.81, p < 0.001; and β = 0.31, p = 0.001, respectively).ConclusionsDepression was significantly associated with higher inflammation beyond the effect of obesity and other confounders. Higher inflammation at baseline predicted poorer weight loss 6 months after surgery, regardless of depression diagnosis. Increased inflammation, rather than depression, may drive poor weight loss outcomes among bariatric patients.
Behavioral public policy in practice: Misconceptions and opportunities
Authors: Hallsworth Michael 
Published: August 2023

Abstract
I greatly respect the authors of the target article. However, in contrast to the target article's assertion, practitioners of behavioral public policy are indeed involved in developing and promoting systemic solutions. Its “i-frame”/“s-frame” distinction is incoherent, unhelpful, and obscures promising future directions for behavioral public policy. Its content and presentation undermine its stated goals and encourage sweeping dismissals of the field.
The social sciences are increasingly ill-equipped to design system-level reforms
Authors: Jackson Michelle 
Published: August 2023

Abstract
Our social policy landscape is characterized by incrementalism, while public calls for more radical reform get louder. But the social sciences cannot be relied upon to generate a steady stream of radical, system-level policies. Long-standing trends in social science – in particular, increasing specialization, an increasing emphasis on causal inference, and the growing replication crisis – are barriers to system-level policy development.
Modeling and invariably horizontal control for the parallel mobile rescue robot based on PSO-CPG algorithm
Authors: Chen Wei , Cheng Hao , Zhang Wenchang , Wu Hang , Liu Xuefei , Men Yutao 
Published: August 2023

AbstractA walking robot consisting of double Stewarts parallel legs was designed by our research team in the past time, which was mainly used for the transportation of the wounded after the disaster. In order to promote stability of control locomotion and ensure invariably horizontal state of the robot platform in the process of motion, the central pattern generator (CPG) based on particle swarm optimization (PSO) is presented to optimize the kinematic model. The purpose of optimization is to solve the hysteresis problem of displacement variation among the electric cylinders. Moreover, the dynamic model of the robot is established, which can provide mechanical basis for the feedback of control signal and make the robot move stably. The simulation results show that the displacement hysteresis problem of the electric cylinders is solved well. Meanwhile, compared with simulation results based on GA-CPG method, it is demonstrated that the robot motion planned using PSO-CPG method has better motion stability and can avoid the impact of legs landing during the transition phase of the motion cycle. The experimental results show that the platform on the robot can maintain an invariably horizontal state, and the locomotion is more stable. It verifies the feasibility of PSO-CPG model and the correctness of the dynamic model of the parallel mobile rescue robot.
Empowering Through Law: Environmental NGOs as Regulatory Intermediaries in EU Nature Governance
Authors: Kingston Suzanne , Alblas Edwin , Callaghan Micheál , Foulon Julie 
Published: August 2023

AbstractPrivate ‘bottom-up’ enforcement has been central to the efforts of the European Union (EU) to promote effective compliance with its ambitious environmental laws. This approach is strengthened by the EU's implementation of the Aarhus Convention, which aims to democratize environmental enforcement by conferring citizens and environmental non-governmental organizations (ENGOs) with legal rights of access to environmental information, rights of public participation, and rights of access to justice (the so-called ‘Aarhus mechanisms’). This article empirically assesses the extent to which the Aarhus mechanisms empower ENGOs to take an active role in the private enforcement of the EU Habitats and Birds Directives. Based on 75 surveys and 30 interviews with ENGOs from three Member States (France, Ireland, the Netherlands), we apply regulatory intermediary theory to show how European ENGOs play a vital role in intermediating between (i) EU Member States and their citizens, (ii) the EU and individual citizens, and even (iii) the EU and its Member States. We bring new empirical insights into the role of law as an enabler of regulatory intermediaries, and its potential as a tool for orchestrating regulatory intermediaries.
At the gymnasium through your football buddy's aunt. Accessibility of classical education in the Netherlands
Authors: van Gils Lidewij 
Published: August 2023

AbstractHow accessible is the field of Latin and ancient Ancient Greek languages in the Dutch education system? In recent years this discussion has resurfaced in the light of societal developments which focus on equality of opportunities.1 Moreover, our field faces the challenge to explain in both international and national discussions what makes its study so relevant in the current times, both in secondary and tertiary education.2 This article provides a short overview of the current situation of Latin and ancient Ancient Greek education within the Dutch secondary education system before looking in more detail at its impact on Dutch students. It ends with directions for improving the accessibility of the field of Classics education. In order to illustrate the functioning and consequences of the current situation, in June 2021 a large-scale survey among 1,700 Dutch students of the gymnasium (secondary education with Latin and ancient Greek) provides us with interesting experiences, biases and thoughts about the accessibility of classical education. If we believe that knowledge of the ancient languages and literatures is a valuable resource for the younger generations of our modern society and in addition we see that our field, as any field, would profit from a more diverse group of researchers and teachers, the direction for future improvements is clear; but concrete steps in that direction should be taken at various levels. With this article, I hope to contribute to such improvements to the educational system and contemporaneously to our field.