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The relationship between environmental regulation and firm productivity has been widely debated but inconsistencies in findings across different studies. Using detailed firm-level micro-data from 2000 to 2007, this paper employs difference-in-difference combined with matching based on entropy balancing method to explore the effect of environmental regulation on firm total factor productivity (TFP) in pulp and paper industry in China. Our main findings are as following: Firstly, stricter environmental regulation, as represented by the Wastewater Discharge Standards for Pulp and Paper Industry in Shandong province, increases firm TFP significantly. Moreover, the coefficients of interest are robust to multiple robustness checks. Secondly, dynamic effects estimates reveal that when faced with this phase-in environmental regulation, firms take the foreseeably increasing strictness into account from the very beginning and prefer to take one-step adjustment to reach full compliance. Thirdly, potential mechanism analysis finds that the positive effect mainly comes from the improvement of resource allocation efficiency within firms. Fourthly, the heterogeneity test indicates that the effect of environmental regulation on firm TFP is heterogeneous across firms with different sizes, ages, ownerships, capital intensity, and export status. Finally, this paper provides convincing and insightful evidence that environmental regulation has the potential to achieve the dual goals of environmental sustainability and economic growth and is thus of broader significance for understanding the enforcement of environmental regulation in developing countries. [ABSTRACT FROM AUTHOR]

Predictive maintenance strategies are becoming increasingly more important with the increased needs for automation and digitalization within pulp and paper manufacturing sector. Hence, this study contributes to examine the most efficient pre-processing approaches for predicting sensory data trends based on Gated Recurrent Unit (GRU) neural networks. To validate the model, the data from two paper pulp presses with several pre-processing methods are utilized for predicting the units' conditions. The results of validation criteria show that pre-processing data using a LOWESS in combination with the Elimination of discrepant data filter achieves more stable results, the prediction error decreases, and the predicted values are easier to interpret. The model can anticipate future values with MAPE, RMSE and MAE of 1.2, 0.27 and 0.30 respectively. The errors are below the significance level. Moreover, it is identified that the best hyperparameters found for each paper pulp press must be different. [ABSTRACT FROM AUTHOR]

The Continental Congress foray into printed money during the American Revolution was so disastrous that the United States printed no more money for nearly a century, the one exception being a brief period during the War of 1812. After that Congress chartered and unchartered its national bank twice. The American economy henceforth (1816–1836) was often structurally short of coins, and without any national coinage Americans had to find substitute forms of currency to finance the burgeoning economy. The Supreme Court ruled that sovereign States and individuals could authorize both State and private banks to issue their own notes. In consequence, nearly all paper money in circulation was either State or private banknotes based on a limited reserve of gold. This generally proved insufficient to adequately fund major infrastructure projects. The federal government also had no institution for raising or transferring large amounts of money to fund these national improvements. Nonetheless, Hamilton's U.S. Bank, without the help of a national currency, was an institutional precursor for what would not take final form until 1913. There would be no Federal Reserve today without the Whig-Republican agenda institutionally incarnated in the First and Second U.S. Bank. [ABSTRACT FROM AUTHOR]

Publications in Renal Failure in Science Citation Index Expanded (SCI-EXPANDED) between 1992 and 2021 were analyzed. Six publication indicators: total, independent, collaborative, first author, corresponding author, and single author publications as well as their related citation indicators, were used to compare performances of countries, institutes, and authors. Comparison of the highly cited papers and journal's impact factor (IF) contributors was discussed. In addition, the main research topics in the journal were presented. Results show that China published the most total articles and reviews, as well as the first-author papers and corresponding-author papers in the journal. The Chang Gung Memorial Hospital in Taiwan ranked the top in five publication indicators: total, single-institution, inter-institutionally collaborative, first author, and corresponding-author papers. A low percentage of productive authors emerged as a journal IF contributor. Similarly, only a limited relationship between highly cited papers and IF contributing papers was found. Publications related to hemodialysis, chronic kidney disease, and acute kidney injury were the most popular topic, while meta-analysis was new focus in the last decade in the journal. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Natural Fibers is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Quantitative geographical methods have played an important role in COVID-19 research. To complement and extend previous review studies, we conduct a scoping review of COVID-19 studies employing quantitative geographical approaches by focusing on 331 papers published in 45 journals in geography, urban studies, and planning. We identify four major research themes (clusters): (1) how SARS-CoV-2 viruses spread in cities, (2) the COVID-19 mortality (death) rates and their association with socioeconomic variables, (3) how the COVID-19 pandemic changed people's mobilities, and (4) how the COVID-19 pandemic affects air pollution. We conclude that spatial models play a key role in COVID-19 quantitative geographical approaches, and human mobility is an important and widely studied topic. We also reveal a lack of research focusing on environmental pollution (other than air pollution) that potentially worsened during the pandemic. [ABSTRACT FROM AUTHOR]

Introduction: Freezing cold injuries (FCI) are a common risk in extreme cold weather operations. Although the risks have long been recognised, injury occurrences tend to be sparse and geographically distributed, with relatively few cases to study in a systematic way. The first challenge to improve FCI medical management is to develop a common nomenclature for FCI classification. This is critical for the development of meaningful epidemiological reports on the magnitude and severity of FCI, for the standardisation of patient inclusion criteria for treatment studies, and for the development of clinical diagnosis and treatment algorithms. Methodology: A scoping review of the literature using PubMed and cross-checked with Google Scholar, using search terms related to freezing cold injury and frostbite, highlighted a paucity of published clinical papers and little agreement on classification schemes. Results: A total of 74 papers were identified, and 28 were included in the review. Published reports and studies can be generally grouped into four different classification schemes that are based on (1) injury morphology; (2) signs and symptoms; (3) pathophysiology; and (4) clinical outcome. The nomenclature in the different classification systems is not coherent and the discrete classification limits are not evidence based. Conclusions: All the classification systems are necessary and relevant to FCI medical management for sustainment of soldier health and performance in cold weather operations and winter warfare. Future FCI reports should clearly characterise the nature of the FCI into existing classification schemes for surveillance (morphology, symptoms, and appearance), identifying risk-factors, clinical guidelines, and agreed inclusion/exclusion criteria for a future treatment trial. [ABSTRACT FROM AUTHOR]

This article presents a case study of how the Renminbi won the currency war in Shanghai between 1949 and 1950. This case study supports the proposition of chartalism and MMT that money is a creature of the state, and in two ways deepens our understanding of the role of the state in the sovereign currency system. First, taxation is not the only way to drive money. The Shanghai government also drove money by supplying goods. Second, the outcome of a currency war depends on many historical factors, and the government plays an important role by changing the conventions that shape people's monetary behavior. The Shanghai government adopted anti-inflation policies to transform the conventions of valuing commodities and metallic currencies over paper currencies. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Natural Fibers is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Natural Fibers is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Prophylaxis with emicizumab, a bispecific monoclonal antibody that mimics FVIII function, has shown encouraging results in clinical trials in terms of efficacy and safety. However, current experience is limited, and many areas of concern to clinicians have yet to be reviewed. This paper reviews the experience of hemophilia A patients treated with emicizumab based on the results of clinical trials and real-life studies. The authors place special emphasis on issues such as the management of these patients in situations of hemorrhage and/or surgical interventions, joint health or laboratory monitoring. Treatment with emicizumab has been shown to improve joint health and reduce bleeding, of particular interest to patients with inhibitors and high bleeding rates. However, there are still concerns about its administration in neonates and previously untreated patients due to limited reported experience. Laboratory monitoring is not strictly necessary due to the stable pharmacokinetics emicizumab has been shown to exhibit, however, tests that globally assess hemostasis may be useful especially in cases of bleeding or surgery. The authors are also of the opinion that prophylaxis before minor surgery is not necessary and that major surgeries can be safely performed with additional prophylactic coagulation factor. [ABSTRACT FROM AUTHOR]

In Ethiopia, the dairy cows' major feed resources are natural pasture and crop residues, both of which are nutritionally low and do not even satisfy the maintenance requirement. Consequently, dairy productivity per head is low in the country. This paper reviews the existing knowledge of negative energy balance (NEB) and summarizes its implication on production and reproduction parameters, as well as the monitoring tools as a means of intervention in minimizing the effect on dairy cows. The presence of NEB in late gestation and early lactation of dairy cows could contribute to both short and long-term negative effects on production and reproduction ability. Lower body condition, reduced milk production, a change in the milk fat to protein ratio, an increasing incidence of health problems, a late time to become estrus, delayed ovarian cycle, and a lower conception rate are the common implications. Through the knowledge created so far, it can be concluded that NEB is almost a common phenomenon in transitional high milking dairy animals, but there is a possibility to shorten its persistence through strategic supplementation using the NEB monitoring tools. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Natural Fibers is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For an academic field to remain vital, it is necessary to reflect upon its conceptual foundations and learn from adjacent disciplines. On that note, aesthetics can provide significant insights into advertising. While aesthetic elements have received attention in advertising research, no systematic attempts have been made to provide a comprehensive overview of this literature. The purpose of this conceptual article is to bring different branches of aesthetic theory into advertising studies. Marketers have historically focused on product functionality and often appeal to consumers through explicit messages. This article fills an important gap by delineating and advocating the conceptual foundation of advertising aesthetics as a research area worthy of further attention. In short, we understand advertising aesthetics as the artlike properties of and sensory responses to ads. A review of 309 papers provides the thematic outline of the study. Seven key themes are identified: (1) the nature of advertising aesthetics, (2) advertising creativity, (3) textuality, (4) social aesthetics, (5) cross-cultural differences, (6) the role of media in creating aesthetic opportunities, and (7) aesthetic categories beyond the beautiful and sublime. These themes offer a novel way of exploring contemporary issues in advertising. The article concludes with suggestions for future research. [ABSTRACT FROM AUTHOR]

Copyright of Neotropical Biodiversity is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Creative media advertising is a specific type of unconventional advertising in which a regular physical object serves as a medium to carry an advertising message. To better understand the workings of this type of advertising, we conducted a meta-analysis. In this study, we explore the direct effects of creative media advertising, several moderators, and the possible underlying mechanisms. The results show that exposure to creative (versus traditional) media advertising has an overall positive effect on brand association strength and persuasion (i.e., ad attitude, brand attitude, purchase intentions, and electronic word of mouth [eWOM]). Both these effects are moderated by metaphor use, meaning that the effects are stronger when the physical object is a good metaphor for the message it carries. Furthermore, indirect (e.g., social media, printed picture) exposure to the message positively moderates the effect of creative media advertising on brand association strength but not on persuasion. Brand familiarity does not play a moderating role. Finally, a meta-analytic structural equation modeling (SEM) procedure was used to show that the main underlying mechanism of creative media advertising persuasiveness is surprise—and not perceived persuasive intent. For practitioners, this study shows that creative media ads are more effective when leveraging surprise and metaphors. [ABSTRACT FROM AUTHOR]

Industry 4.0 (I4.0) brings a set of challenges that need to be settled to enable the expected industrial revolution. Cyber-Physical Systems (CPS) and Autonomous Robots are two of mainstream I4.0 technologies and can be combined with other Enabling Technologies to overcome main I4.0 challenges. This Systematic Literature Review (SLR) aimed to understand how these Enabling Technologies were combined with CPS and Autonomous Robots to achieve fully featured I4.0 solutions. The 5C is a CPS architecture which was used as a measurement to CPS compliance. After filtering and processing 15,144 papers from six different academic search engines, it was found that full 5C compliant solutions are rare to find; that not all enabling technologies were integrated; and most of existing research focused in implementing practical solutions, but comparison to conventional approaches is scarce. We conclude that there is a need for further research to accomplish full 5C I4.0. [ABSTRACT FROM AUTHOR]

Less effective information is obtained by the object detection network, due to the small size of the detection object in the entire image, the complex background, and the dense object in unmanned aerial vehicle (UAV) images. In response to the difficulties encountered, a small object detection method in UAV images is proposed as an improved YOLOv5-based algorithm in this paper. First, the space-to-depth(SPD) conv module is introduced into the basic feature extraction network, to improve significant loss of image information during downsampling. Then, various attention mechanisms are added, to intensify the acquisition of regions of interest in UAV images. Finally, the multiscale detection module is improved, to enhance the network's ability to detect small objects in UAV images. By conducting experiments on the VisDrone-DET2019 dataset, the test results of the established model show. The improved algorithm achieved a Mean Average Precision (mAP) of 41.8%, which is 7.8% better than the baseline network. In addition, the detection performance is better than most current mainstream target detection algorithms and is of some practical value. [ABSTRACT FROM AUTHOR]

The relationship between environmental regulation and firm productivity has been widely debated but inconsistencies in findings across different studies. Using detailed firm-level micro-data from 2000 to 2007, this paper employs difference-in-difference combined with matching based on entropy balancing method to explore the effect of environmental regulation on firm total factor productivity (TFP) in pulp and paper industry in China. Our main findings are as following: Firstly, stricter environmental regulation, as represented by the Wastewater Discharge Standards for Pulp and Paper Industry in Shandong province, increases firm TFP significantly. Moreover, the coefficients of interest are robust to multiple robustness checks. Secondly, dynamic effects estimates reveal that when faced with this phase-in environmental regulation, firms take the foreseeably increasing strictness into account from the very beginning and prefer to take one-step adjustment to reach full compliance. Thirdly, potential mechanism analysis finds that the positive effect mainly comes from the improvement of resource allocation efficiency within firms. Fourthly, the heterogeneity test indicates that the effect of environmental regulation on firm TFP is heterogeneous across firms with different sizes, ages, ownerships, capital intensity, and export status. Finally, this paper provides convincing and insightful evidence that environmental regulation has the potential to achieve the dual goals of environmental sustainability and economic growth and is thus of broader significance for understanding the enforcement of environmental regulation in developing countries. [ABSTRACT FROM AUTHOR]

"Wayfaring Strangers: The Musical Voyage from Scotland and Ulster to Appalachia" is a book by Fiona Ritchie and Doug Orr that explores the cultural pathways of traditional Scottish and Irish folk music as it traveled to Appalachia. The book examines the influences of Welsh, English, German, Dutch, French, African American, and Cherokee cultures on these songs. It is structured into three main sections and includes photographs, maps, and sidebars covering various topics related to folk music. The authors also exchange letters discussing their perspectives on Old and New World music. The book sheds light on the history of American folk music and its connection to immigrant experiences. It includes a contextual timeline, resource centers, a discography, and a bibliography for further exploration. Scholars and music enthusiasts will find this book to be a valuable resource. [Extracted from the article]

"Decolonizing Geography: An Introduction" by Sarah A. Radcliffe explores the decolonization of Anglophone geographical curricula. The book emphasizes the importance of approaching fieldwork with humility, respecting local knowledge, and avoiding the imposition of Western paradigms. It calls for action to avoid blinders, respect counternarratives, question official histories, acknowledge privilege, employ collaborative research, and entertain alternative epistemologies. The book also highlights the significance of indigenous environmental knowledge in physical geography and addresses the lack of diversity in the discipline. Overall, "Decolonizing Geography" offers a comprehensive exploration of decolonial approaches in geography and provides practical examples and suggestions for further research. [Extracted from the article]

The global biodiversity crisis and constantly growing human impact on the natural environment call for more evidence where conservation actions are the most urgent. As the agricultural lands are under increased pressure of growing human food needs here the literature survey on farmland bird conservation (FBC) was conducted to reveal geographical distribution in research intensity, the topics addressed and to identify potential drivers for the worldwide scientific effort. The Scopus database search has revealed 2290 papers dedicated to FBC from the period 1990-2020. The distribution was spatially uneven with most papers published in Western Europe and North America. Scientific collaboration was also spatially biased in favor of countries located close to each other and having high scientific capacity. The analysis also revealed 139 terms representing main topics raised in FBC research. The number of FBC papers per country was positively correlated with Gross Domestic Production (GDP), the total number of scientific papers, and number of threatened species, and negatively with the GDP from agricultural production, whereas it was not related to area of agricultural lands or bird species richness. Spatial and thematic biases in studies of farmland birds may have important consequences since uneven scientific evidence constrains development of proper conservation solutions and limits their implementation. We conclude that research on FBC should be globally coordinated and flexible enough to undertake burning conservation problems adjusted to regional differences in agriculture, socio-economy, and bird diversity. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Natural Fibers is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Nowadays, an increasing number of crises worldwide, triggered by climate extremes, natural and human-made hazards, the coronavirus pandemic, and more, pose a high pressure on crisis, emergency, and disaster management. Spatial data and Volunteered Geographic Information (VGI) are key issues in the successful and immediate response to crises. This paper aims to explore the use of VGI in crisis management, including emergency and disaster management, based on a scoping review of existing literature in English for five years (2016–2020). Specifically, the research intends to answer Scoping Review Questions (SRQ) regarding the use of VGI in crisis, emergency, and disaster management, and the verified cases' spatial distribution, the VGI sources utilized (e.g. OpenStreetMap – OSM, Crowdsourcing, Twitter), the types of hazards (e.g. natural and human-made hazards, pandemic), the specific tasks in crisis, emergency or disaster management and VGI use in the management of actual crisis events, e.g. COVID-19 pandemic, Hurricane Katrina, etc. Eligible papers on VGI use in crisis, emergency, and disaster management are geolocated based on first-author affiliation, and as a result, a spatial bibliography is provided. Thus, the term Spatial Scoping Review is introduced. Scoping Review Questions are answered, and the results are analyzed and discussed. Finally, implementing the "VGICED Atlas", a web atlas, permits the publication of the research results to a broad audience and the visualization of the analysis with several interactive maps. [ABSTRACT FROM AUTHOR]

Reproducibility, the ability to reproduce the results of published papers or studies using their computer code and data, is a cornerstone of reliable scientific methodology. Studies where results cannot be reproduced by the scientific community should be treated with caution. Over the past decade, the importance of reproducible research has been frequently stressed in a wide range of scientific journals such as Nature and Science and international magazines such as The Economist. However, multiple studies have demonstrated that scientific results are often not reproducible across research areas such as psychology and medicine. Statistics, the science concerned with developing and studying methods for collecting, analyzing, interpreting and presenting empirical data, prides itself on its openness when it comes to sharing both computer code and data. In this article, we examine reproducibility in the field of statistics by attempting to reproduce the results in 93 published papers in prominent journals using functional magnetic resonance imaging (fMRI) data during the 2010–2021 period. Overall, from both the computer code and the data perspective, among all the 93 examined papers, we could only reproduce the results in 14 (15.1%) papers, that is, the papers provide both executable computer code (or software) with the real fMRI data, and our results matched the results in the paper. Finally, we conclude with some author-specific and journal-specific recommendations to improve the research reproducibility in statistics. [ABSTRACT FROM AUTHOR]

In Nazi Germany (1933–45), reclaiming waste became an intrinsic component of the regime's economy as well as its ideological, racial, and expansionist ambitions. National Socialist interventions into waste streams began in 1934 with salvage campaigns. The state then brought urban waste policies and municipal waste services under its control, restructuring and 'Aryanising' the waste salvage trade. Moreover, both consumers and producers were prompted to collect and reprocess waste. Over time, the gradual expansion of the Nazi waste recovery policies and campaigns – here referred to as the 'Nazi waste exploitation regime' – brought forth a determined vision of a circular economy in which no waste whatsoever should escape its reclamation for the national community or Volksgemeinschaft. This article sketches the actors, structures, and objectives of this waste exploitation regime for the case of rags and paper and uncovers its entanglement with Nazi racist and genocidal ideology and expansionism. [ABSTRACT FROM AUTHOR]

A literature review on the order picking process in warehouses is presented for delineating the trends in time of research topics in this field. A total of 269 journal papers published between 2007 and 2022 were retrieved from Scopus. After a methodological classification, descriptive analyses were performed on authors, journals, subject area and top publishing countries. Bibliometric tools were used to map the topics covered by the reviewed studies, categorise them and determine possible relationships. Papers' contents were evaluated in terms of eight categories, including five typical issues of order picking systems, plus three aspects dealing with the characteristics of the application. Insights about the extent to which these aspects have been covered in the literature are derived; relationships between the various aspects of the picking process are also delineated. Suggestions for future research activities are finally deducted, offering researchers and practitioners strong bases for works on order picking systems. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Natural Fibers is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article examines Soviet paper reuse as an ideological, economic daily practice, implemented through the advanced, but hitherto undescribed Soiuzutil'waste collecting system by the early 1930s as the reverse side of Stalinist industrialization. It argues that Soiuzutil'waste paper handling attempted to form a new socialist collective by reworking old print while cultivating citizens as classless scrap-collectors, for the sake of an (ir)rational resource optimization. While World War II intensified recycling efforts among the Allied and Axis powers, invasion and evacuation damaged Soviet waste collection to a point where no return of paper into a centralized system was possible. War forced printers and consumers to retreat to local self-supply networks, as paper remained a crucial, yet scarce resource. By analyzing technical-educational literature and correspondence of the reutilization offices, the article demonstrates the changing attitudes in the Stalinist war economy, the industries, and the population towards mobilizing and saving paper. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Natural Fibers is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This document is an editorial that pays tribute to the late Samir Amin, a prominent African scholar and activist. Amin was known for his Marxist perspective and his critique of capitalism and Eurocentrism. He advocated for delinking from capitalism and imperialism as a means of achieving inclusive development. The editorial highlights Amin's contributions to various fields, including development economics, political economy, and decolonization in Africa. It also introduces a special issue dedicated to Amin's legacy, which includes papers on topics such as Africa's socio-economic development, alternative development theories, and decolonization. The editorial emphasizes the continued relevance of Amin's ideas for Africa's development and the importance of implementing his recommendations. [Extracted from the article]

Background: In order to obtain their medical degree, medical students in Morocco are required to carry out a research project and provide a thesis outlining its methodology and findings. However, little is known about the scientific output of these theses. The aim of the present study was to explore and evaluate the characteristics and publication patterns in scientific-indexed journals of medical theses written by medical students in Morocco. Methods: Data was extracted from registered theses between 2011 and 2021 in four medical schools that have an open-source documents archiving platform. Publication of these theses was assessed in 2022 using a search strategy in three indexed databases; Pubmed, Scopus and Web of science. Results: 9807 theses were registered between 2011 and 2021, 41% of them in the faculty of medicine of Rabat. 99.1% of these theses were written in French, 61.7% were reporting a retrospective case series, and 38.9% of them covered surgical disciplines. 83 (0.8%) of the registered theses were published in a scientific-indexed journal, and half of the papers (49.4%) was written in French. The graduate student was the paper's lead author in 54.2% of the papers. The articles driven from the theses were published after a mean delay of 1.49 ± 1.34 years and the targeted journals had a mean SJR score of 0.69 ± 1.21. The total number of detected citations of the 83 published papers was 216. Conclusion: The publication rate of Moroccan medical theses is very low when compared to other countries, which leads to question the real benefit of this time and resources consuming educational activity. [ABSTRACT FROM AUTHOR]

Climate change is becoming a defining factor for communities in South Asia. Forming one-fifth of the world population, the region increasingly faces climate-induced disasters such as floods, droughts, heatwaves, cyclones etc. This region also has one of the world's poorest people who struggle to cope with the rapidly changing climatic conditions. Agriculture still employs many people in the region, one of the worst-hit sectors. Agriculture will become untenable in some parts of the region due to climate change. Monsoon patterns have changed, and agriculture does not guarantee sustainable income for the vast majority. Many climate change adaptations have been initiated in the region in response to the threat of climate change. Scholars and practitioners feel that these adaptations must be transformative to be effective. In this paper, we examine eight such adaptations from three South Asian Countries – Bangladesh, India, and Nepal, from the lens of transformative adaptation. We found that no single adaptation initiative meets all the criteria for sustainable socio-ecological transformations. However, there is a significant overlap between different typologies of transformation as envisaged in the paper and literature. We conclude that the concept of socio-ecological transformation is new for South Asia, so integrating it into the programmes and policies is the need of the hour. [ABSTRACT FROM AUTHOR]

Object detection technology is a popular research direction which is widely used in areas such as autonomous driving and medical diagnosis. At this stage mobile devices often have limited storage resources to deploy large object detection networks and need to meet real-time requirements. This paper proposes a lightweight and efficient object detection model based on YOLOv4, first using the lightweight network GhostNet to extract image features and reduce the number of parameters and computation of the backbone structure; then combining AFmodule and Meta-ACON activation function to enhance the feature extraction capability of the backbone network, which strengthen the mode's ability to capture image spatial feature information; this paper also designs the RL-PAFPN feature fusion structure is with the Reslayer module to further improve the model's ability to extract and fuse image features. By comparing other mainstream object detection models, the YOLOv4-Ghost-AMR network in this paper has less computation and fewer parameters, and the accuracy of the model reaches 86.83%, which is suitable for deployment in mobile devices with limited storage. The model proposed in this paper can be applied to medical, traffic and fault detection fields, which changes the traditional manual detection method and saves manpower and time costs, achieving high precision real-time object detection. [ABSTRACT FROM AUTHOR]

Environmental sustainability urgently needs to be embraced as a driver of development for society and industry. While researchers and practitioners herald numerous benefits when adopting eco-efficiency and circular economy approaches, these green solutions are yet to become pervasive principles for designing and operating industrial systems. This study reviews the last ten years of research contributions from the International Federation for Information Processing Working Group 5.7 (IFIP WG5.7) on Advances in Production Management Systems (APMS) through its dedicated annual conference. A systematic literature review method was employed to map the APMS conference papers against eco-efficiency principles and to identify how these principles have been addressed by this research community. A cross-thematic analysis further describes the trends around dominant themes in production research. Finally, the paper concludes with an update on eco-efficiency principles applied to manufacturing and a proposed framework to consider more systematically the environmental implications of advances in production research. [ABSTRACT FROM AUTHOR]

"Settler Colonial City: Racism and Inequity in Postwar Minneapolis" by David Hugill examines the history of racism, inequity, and settler-colonial structures in Minneapolis, particularly focusing on the post-World War II era. The book explores the impact of urban change, racialized policing, and American imperialism on marginalized communities, with a particular emphasis on Indigenous peoples. Hugill highlights the structural barriers faced by marginalized groups and the need to dismantle white supremacist and settler-colonial structures. While the book primarily focuses on the violent aspects of settler-colonial urban policy, it also touches on the need to examine more subtle elements such as access to education, healthcare, and legal services. Overall, the book provides a critical perspective on the history of Minneapolis and challenges the perception of the city as progressive and inclusive. [Extracted from the article]

Measuring influence of one person on another has applications in advertising and marketing and across the sciences. Most approaches involve inferring influence based on speech and social media. In contrast, this paper takes existing spending data and attributes influence on to the spenders and those likely to have caused their spending. The resulting metric, Social Value, is expressed in units of behavior over time. While a person's total influence on others is called their Social Value, a person's behavior caused by someone else is called their Following Value. These metrics can also be used across an entire community, customer base, or audience, allowing an objective measure of how much spending or other behavior is social versus nonsocial. These measures in turn open up the potential to test interventions and campaigns to measure viral spread as well as overall shifts in social influence. This article presents a computational model for estimating Social Value, as well as validation of the estimation approach in a study involving players of an online game. A noncommercial open-source implementation of the computational model accompanies this paper. [ABSTRACT FROM AUTHOR]

Poverty has always been a global concern that has restricted human development. The first goal (SDG 1) of the United Nations Sustainable Development Goals (SDGs) is to eliminate all forms of poverty all over the world. The establishment of a scientific and effective localized SDG 1 evaluation and monitoring method is the key to achieving SDG 1. This paper proposes SDG 1 China district and county-level localization evaluation method based on multi-source remote sensing data for the United Nations Sustainable Development Framework. The temporal and spatial distribution characteristics of China's poverty areas and their SDG 1 evaluation values in 2012, 2014, 2016, and 2018 have been analyzed. Based on the SDGs global indicator framework, this paper first constructed SDG 1 China's district and county localization indicator system and then extracted multidimensional feature factors from nighttime light images, land cover data, and digital elevation model data. Secondly, we establish SDG 1 China's localized partial least squares estimation model and SDG 1 China's localized machine learning estimation model. Finally, we analyze and verify the spatiotemporal distribution characteristics of China's poverty areas and counties and their SDG 1 evaluation values. The results show that SDG 1 China's district and county localization indicator system proposed in this study and SDG 1 China's localized partial least squares estimation model can better reflect the poverty level of China's districts and counties. The estimated model R2 is 0.65, which can identify 72.77% of China's national poverty counties. From 2012 to 2018, the spatial distribution pattern of SDG evaluation values in China's districts and counties is that the SDG evaluation values gradually increase from western China to eastern China. In addition, the average SDG 1 evaluation value of China's districts and counties increased by 23% from 2012 to 2018. This paper is oriented to the United Nations SDGs framework, explores the SDG 1 localized evaluation method of China's districts and counties based on multisource remote sensing data, and provides a scientific and rapid regional poverty monitoring and evaluation program for the implementation of the 2030 agenda poverty alleviation goals. [ABSTRACT FROM AUTHOR]

Human error estimating food intake is a major source of bias in nutrition research. Artificial intelligence (AI) methods may reduce bias, but the overall accuracy of AI estimates is unknown. This study was a systematic review of peer-reviewed journal articles comparing fully automated AI-based (e.g. deep learning) methods of dietary assessment from digital images to human assessors and ground truth (e.g. doubly labelled water). Literature was searched through May 2023 in four electronic databases plus reference mining. Eligible articles reported AI estimated volume, energy, or nutrients. Independent investigators screened articles and extracted data. Potential sources of bias were documented in absence of an applicable risk of bias assessment tool. Database and hand searches identified 14,059 unique publications; fifty-two papers (studies) published from 2010 to 2023 were retained. For food detection and classification, 79% of papers used a convolutional neural network. Common ground truth sources were calculation using nutrient tables (51%) and weighed food (27%). Included papers varied widely in food image databases and results reported, so meta-analytic synthesis could not be conducted. Relative errors were extracted or calculated from 69% of papers. Average overall relative errors (AI vs. ground truth) ranged from 0.10% to 38.3% for calories and 0.09% to 33% for volume, suggesting similar performance. Ranges of relative error were lower when images had single/simple foods. Relative errors for volume and calorie estimations suggest that AI methods align with – and have the potential to exceed – accuracy of human estimations. However, variability in food image databases and results reported prevented meta-analytic synthesis. The field can advance by testing AI architectures on a limited number of large-scale food image and nutrition databases that the field determines to be adequate for training and testing and by reporting accuracy of at least absolute and relative error for volume or calorie estimations. These results suggest that AI methods are in line with – and have the potential to exceed – accuracy of human estimations of nutrient content based on digital food images. Variability in food image databases used and results reported prevented meta-analytic synthesis. The field can advance by testing AI architectures on a limited number of large-scale food image and nutrition databases that the field determines to be accurate and by reporting accuracy of at least absolute and relative error for volume or calorie estimations. Overall, the tools currently available need more development before deployment as stand-alone dietary assessment methods in nutrition research or clinical practice. [ABSTRACT FROM AUTHOR]

Providing personalized recommendation service for users and improving the accuracy of recommendation and user satisfaction are the main research tasks of current travel recommendation systems. The intelligent recommendation model of tourist places requires the algorithm to be able to accurately recommend tourist attractions according to the user's interests. Big data and artificial intelligence technologies have driven the development of intelligent recommendation systems. However, realistic data are often sparse, and the lack of common rating items among users makes some traditional similarity measures impossible to calculate. In addition, traditional collaborative filtering algorithms ignore the issue of user preferences, which can cause a decrease in recommendation accuracy. To address these issues, this paper analyzes the factors affecting users' interest preferences in terms of their global and local rating information. The interest preferences of users are calculated by computing the probability distribution of user rating information globally and using Hamming approach degree. A similarity algorithm about user preferences is derived using Jeffries-Matusita distance. The similarity algorithm is effectively combined with the traditional similarity algorithm to propose a model of collaborative filtering recommendation algorithm for tourist attractions based on user preferences under sparse data. The paper aims to improve the accuracy of tourist attraction recommendation systems by incorporating user preferences and addressing the issue of sparse data and the lack of common rating items among users that traditional similarity measures cannot calculate. The experimental results show that the improved algorithm model outperforms the traditional collaborative filtering algorithm and other algorithms. And it also has high accuracy rate on more sparse tourism data set. [ABSTRACT FROM AUTHOR]

Human resource management was of great significance for enterprises to formulate development strategies and improve competitiveness. With the rapid development of new technologies such as knowledge economy and big data, the traditional human resource performance appraisal model had certain limitations and was not objective, which had been difficult to adapt to the increasingly highly integrated development needs of modern enterprises. Therefore, this paper used big data analysis and new technical means to put forward the study of human resource performance evaluation model based on Bayesian network, aiming to provide some theoretical reference for modern enterprise human resource management. First of all, it summarized the related concepts of performance appraisal and its important position in enterprise management, analyzed the characteristics of human resources performance appraisal indicators and their mutual relations, and expounded the common methods and characteristics needed to build a performance appraisal system. Secondly, it summarized the relevant theory of Bayesian network and its advantages in solving complex random problems, and proposed a performance appraisal model based on Bayesian network for the needs of enterprise human resources management. Finally, the balanced scorecard method was used to build a performance appraisal system, and the performance appraisal model proposed in this paper was tested by experiments, and compared with the traditional method. The results showed that the performance appraisal model proposed in this paper had significant advantages and could be better applied to the performance appraisal management of enterprise human resources. The research of this paper can not only provide theoretical guidance for further research on enterprise human resource allocation and management, but also provide reference for performance appraisal in other fields. [ABSTRACT FROM AUTHOR]

This paper investigates ethnic inequity in cycling to work in London, as ethnic minorities in London cycle to work less frequently than white Londoners. The study adopts three methods: spatial statistics, linear regression and spatial econometrics based on recent UK census and official statistical data (2011–17) of 33 London regions. Spatial analysis shows that cycling networks and bike schemes are concentrated around Inner London. Regions with less cycling infrastructure tend to have a greater proportion of residents of ethnic minorities. The paper highlights the spatial dependence between ethnic inequalities and cycling to work at a regional level in London. There is also evidence of spatial spillovers between neighbouring regions. The paper highlights the need to shift the policy focus from the provision of cycling infrastructure to mobility justice. This means recognizing the needs of distinct groups of cyclists coming from various ethnic minorities. Overall, this paper expands the transportation policies approach by linking it with the concepts of mobilities and regional inequalities. This study of London demonstrates the mechanisms responsible for regional ethnic inequalities in cycling to work that could be relevant in other large urban agglomerations. [ABSTRACT FROM AUTHOR]

Researchers have sought to understand how Indigenous and Western knowledge systems can be bridged for development research to be (a) more inclusive of local actors and knowledge and (b) more relevant to the problems it aims to address. Research in Amazonian Indigenous contexts remains dominated by a 'Western' science struggling to accommodate bottom-up development research. This paper examines how Indigenous and Western knowledge is bridged in knowledge co-production with Amazonian Indigenous communities, and what outcomes such bridging incurs. The paper uses a systematic realist review analysing 22 studies. It finds that the bridging of Indigenous and Western knowledge, in co-production with Amazonian Indigenous communities, was based on partnership between Indigenous and scholarly communities. Emphasising mutual respect, power-sharing, and empowerment of Indigenous communities, this bridging contributes to generation of knowledge that is more legitimate and beneficial for all actors involved in the co-production process. However, the paper also observes a gap between knowledge co-production in theory and practice. Power-relations between Western scientists and Indigenous communities need to be further addressed in development research. More work is needed to enhance the legitimacy of knowledge, in order to further empower Indigenous communities to address local challenges according to their own contexts and needs. [ABSTRACT FROM AUTHOR]

As humanity pushes deeper into the Anthropocene, Social-Ecological Systems (SESs) across the world are facing mounting pressures. Managing, protecting and understanding these systems require research into their complex and interlinked nature. One area that has been met with increased research in recent times is Sense of Place (SoP), broadly defined as the emotional bond that people have with a 'place'. There has been substantial growth in the number of studies seeking to understand and quantify SoP across different contexts to help integrate it into decision-making processes. This targeted scoping review aims to explore the environmental literature for examples of applied studies that measure SoP in social-ecological contexts with a focus on how SoP has been quantified and measured. Our results show a growing body of literature as well as a number of clear knowledge gaps. The majority of studies to date have focussed on the Global North (accounting for 79% of the published papers), particularly the USA and Australia, with the distribution of authors closely mirroring this same pattern. Marine and freshwater ecosystems were understudied in comparison to terrestrial ecosystems. Mixed methods were most commonly used to collect data, with interviews and surveys being the most common instruments. Further research into why SoP is being measured is required, but preliminary investigations indicate there is a perceived applicability to policy and planning. We explore these findings and identify research directions. [ABSTRACT FROM AUTHOR]

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Image processing algorithms based on time-frequency analysis are frequently used in testing and researching the mechanical properties of high-temperature materials, especially in aerospace, engines, and ships. However, due to the complexity of the high temperature environment itself, there are many factors that affect the measurement accuracy, among which the existence of thermal airflow disturbance has a particularly significant impact on the digital image correlation method. This paper mainly focuses on two aspects of high temperature edge detection and digital image correlation. On the one hand, the existing algorithm is improved to make it suitable for material property detection in high temperature environment. And relevant experiments are carried out to verify the feasibility and accuracy of the algorithm. The full-field coefficient caching method for fitting initial values proposed in this paper has the premise that the accuracy is comparable to that of the reverse combined Gauss-Newton matching algorithm, but the running speed is improved by about 10%, and the matching accuracy of both is obviously higher than that of the surface fitting algorithm. [ABSTRACT FROM AUTHOR]

The study of business performance has a substantial impact on improving the internal management and economic performance of companies. By analysing the previous literature, this paper chooses to measure the factors affecting business performance at four levels, including R&D investment intensity, human capital, patents, and brand value. The purpose of the study is to find out whether these selected factors work equally well for small and medium-sized enterprises. The sample size was 846 Chinese small and medium enterprises from different industries. The firm performance indicators were ROA and ROE. The data has been collected through National Equities Exchange and Quotations platforms based on updated annual reports in 2019. Finally, a stepwise descriptive analysis and multiple linear regression were conducted and predicted the tendency of business performance. The analysis provided the linear combination of four independent variables (R&D, human capital, patents, and brand value) which are significantly related to the dependent variable (business performance). In conclusion, we found that there is a positive impact of patents and brand value on business performance. In detail, we concluded that only production and highly educated personnel show a positive influence. For R&D intensity, there is no strong connection could be observed. In practical terms, this paper allows SME firms to appreciate the importance of human capital, patents, and brand value. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to assess the non-linearities between the ESG activities and firm performance in case of an emerging market. China is identified as a case study for the present examination. Even though this research objective has been explored by past researcher, the evidence presented in literature is not conclusive. The paper hypothesizes that such conflicting or inconclusive results can potentially be attributed to wrong modeling, datasets that include both developing and the developed markets, and the prevalent endogeneity issue in corporate governance literature. For the purpose of this paper, the author uses the dynamic panel approach of First difference and the System Generalized Method of Moments. The findings from the analysis of 232 Chinese listed firm show a positive association between ESG activities and the firm performance. However, the relationship is nonlinear. In other words, the relationship between ESG activities and the firm performance is inverted U-shaped. This indicates the relationship is positive up to a certain threshold and once the ESG activities cross that threshold it start to have negative effect. The key insight from this research is that the firm has to find their threshold of ESG activities to gain maximum benefits from such activities. [ABSTRACT FROM AUTHOR]

This paper investigates the impact of Internet infrastructure construction on enterprise transformation and upgrading and the underlying mechanisms using a progressive double difference model based on a quasi-natural experiment of the Chinese government's "broadband China" policy by matching A-share listed companies and city panel data from 2008–2019 in Shanghai and Shenzhen. The conclusions show that the "broadband China" policy can significantly promote the transformation and upgrading of enterprises in pilot cities. However, its effect shows a diminishing marginal contribution, and the policy is more effective for traditional manufacturing industries during the implementation period. Enhancing human capital and reducing internal transaction costs are two important channels for Internet infrastructure construction to help enterprises transform and upgrade. Combined with the life cycle theory, we find that the "broadband China" policy has the most significant impact on changing and upgrading enterprises in the growth and maturity stages, especially those in the manufacturing industry, but not those in the maturity and decline stages of the service industry. Finally, a series of robustness tests using Monte Carlo simulation, entropy balance method, and instrumental variables method, excluding other factors, show that the findings are still robust. [ABSTRACT FROM AUTHOR]