bluuebunny/crossref_metadata_2025 huggingface dataset:
Conclusion: Better Cancer Care and Greater Local Health Security: Lessons, Opportunities and Ways Forward
Authors: Banda Geoffrey , Mackintosh Maureen , Njeru Mercy Karimi , Srinivas Smita , Chataway Joanna , Makene Fortunata Songora
Published: January 2024

In pulling together the book’s analytical themes and practical lessons in the conclusion, this chapter emphasises as a core theme the scope for bringing together health, industrial development and innovation to build greater local health security, for cancer care, across the spectrum of health need and pandemic preparedness. The pandemic and our study of cancer care reinforced the importance of simultaneous co-resolution of challenges pertaining to health systems strengthening, development of broad industrial capabilities and improvements in planning, organisational, funding and institutional capabilities. This is critical for building agile and resilient local health security, a critical pre-condition for global health security.
Beyond “Late Presentation”: Explaining Delayed Cancer Diagnosis in East Africa
Authors: Cross Charlotte , Mokua Sharon , Ngilangwa Richard , Santos Cristina , Ngoma Twalib , Mujinja Phares G. M.
Published: January 2024

This chapter considers the health system “maze” from the perspective of health professionals aiming to create smoother managed pathways to and through cancer care. The authors argue that the wider cancer literature’s concept of “late presentation” can be misleading in directing too much attention to patients’ delays before presenting symptoms, while by contrast, most diagnostic delays faced by our interviewees occurred after their first arrival at a facility. The chapter identifies key bottlenecks faced by patients before diagnosis; assesses the scope for feasible improvements in the speed of diagnosis—central to survival chances—and identifies points of leverage for feasible improvement.
Cupboard Full, Cupboard Empty: The Industrial Building Blocks of Covid-19 and Cancer Systems
Authors: Srinivas Smita
Published: January 2024

Industrial organization is central to cancer care and local health security. This chapter shows why that is so, starting from the experiences of the author of working across health/industrial boundaries under pressure during the pandemic in India. India has a much stronger local industrial base and innovative capabilities than Kenya or Tanzania, yet it struggles to build on that advantage to improve access to timely cancer care for its population. The chapter’s framing challenges the reader to grasp the complexity of responsibility in designing viable policy to address the linkages and gaps between the industrial sector and the ﻿health system that uses the products.
Oncology Drug Production in Sub-Saharan Africa: The Challenge and Opportunity, with Evidence from India
Authors: Mackintosh Maureen , Chaudhuri Sudip , Mohamed Nazeem , Wangwe Samuel , Ngoma Twalib , Manduku Veronica
Published: January 2024

This chapter focuses on the scope for local production in East Africa of essential oncology medication, drawing on evidence of local clinical need; on Indian data on markets for generic oncology medication; and on industrial and regulatory experience. Import-dependence in oncology is almost complete across Sub-Saharan Africa, while India is a key exporter. The chapter documents competition failures in generic oncology markets and demonstrates the huge affordability impact of effective procurement of these medicines within India. Challenges for local oncology manufacturing are identified. The chapter argues that active health-industrial research linkages can build a local African oncology industry.
Soft theorems in de Sitter spacetime
Authors: Mao Pujian , Zhang Kai-Yu
Published: January 2024

Abstract

In this paper, we derive a soft photon theorem and a soft gluon theorem in the de Sitter spacetime from the Ward identity of the near cosmological horizon large gauge transformation. Taking the flat limit of the de Sitter spacetime, the soft theorems naturally recover the corresponding flat spacetime soft theorems.
IGF2BP3-mediated enhanced stability of MYLK represses MSC adipogenesis and alleviates obesity and insulin resistance in HFD mice
Authors: Huang Xiuji , He Wuhui , Fan Shuai , Li Hui , Ye Guiwen
Published: January 2024

Mesenchymal stem cells (MSCs) hold immense potential as multipotent stem cells and serve as a primary source of adipocytes. The process of MSC adipogenesis plays a crucial role in maintaining systemic metabolic homeostasis and has garnered significant attention in tissue bioengineering. N6-methyladenosine (m6A), the most prevalent RNA modification, is known to regulate cell fate and disease. However, the precise involvement of m6A readers in MSC adipogenesis remains unclear. In this study, we investigated the impact of IGF2BP3, a prominent m6A reader, on MSC adipogenesis. Our findings revealed a decrease in IGF2BP3 expression during the natural adipogenic differentiation of MSCs. Furthermore, IGF2BP3 was found to repress MSC adipogenesis by augmenting the levels of MYLK, a calcium/calmodulin-dependent kinase. Mechanistically, IGF2BP3 interacted with MYLK mRNA in an m6A-dependent manner, extending its half-life and subsequently inhibiting the phosphorylation of the ERK1/2 pathway, thereby impeding the adipogenic differentiation of MSCs. Additionally, we successfully achieved the overexpression of IGF2BP3 through intraperitoneal injection of adeno-associated virus serotype Rec2, which specifically targeted adipose tissue. This intervention resulted in reduced body weight and improved insulin resistance in high-fat diet mice. Overall, our study provides novel insights into the role of IGF2BP3 in MSC adipogenesis, shedding light on adipocyte-related disorders and presenting potential targets for related biomedical applications.
Stein–Weiss type inequality on the upper half space and its applications
Authors: Li Xiang , Shen Zifei , Squassina Marco , Yang Minbo
Published: January 2024

In this paper, we establish some Stein–Weiss type inequalities with general kernels on the upper half space and study the extremal functions of the optimal constant. Furthermore, we also investigate the regularity, asymptotic estimates, symmetry and non-existence results of positive solutions of corresponding Euler–Lagrange system. As an application, we derive some Liouville type results for the Hartree type equations on the half space.
Dissolving-grade pulp: a sustainable source for fiber production
Authors: Quintana Elisabet , Valls Cristina , Roncero M. Blanca
Published: January 2024

The global textile fiber output increased five times from 1975 to 2020. Also, in 2010, the combined demand for man-made and natural fibers was projected to increase by 84% within 20 years. Clothing materials are largely made from cotton or petroleum-based synthetic fibers; both sources, however, have adverse environmental impacts. Thus, cotton requires vast amounts of land, water, fertilizers and pesticides, and synthetic fibers are not biodegradable. This scenario has raised the need for further exploration of cellulose polymers as sustainable sources for the textile industry. Cellulose, the most abundant renewable organic material on earth, is an outstanding polymer that by chemical derivatization or modification can offer a broad range of applications. Dissolving-grade pulp (DGP), which consists of highly pure cellulose, is the most suitable material for manufacturing cellulose derivatives and regenerated fibers. The latter are typically obtained by using the viscose process, which has considerable adverse environmental impacts. Although the textile industry has progressed substantially, further efforts are still needed to make its entire production chain more sustainable. This article provides an in-depth introduction to the potential of fibers with a high cellulose content, known as dissolving-grade pulps. It reviews the properties of DGP, the cooking and purifying methods typically used to obtain it, and the process by which paper-grade pulp can be converted into dissolving-grade pulp. Also, it discusses traditional and recently developed technologies for producing regenerated cellulose fibers. Finally, it examines the potential for recovering cellulose from textile waste as a novel sustainable practice.
Downhill running increases markers of muscle damage and impairs the maximal voluntary force production as well as the late phase of the rate of voluntary force development
Authors: Coratella Giuseppe , Varesco Giorgio , Rozand Vianney , Cuinet Benjamin , Sansoni Veronica , Lombardi Giovanni , Vernillo Gianluca , Mourot Laurent
Published: January 2024

Purpose

To examined the time-course of the early and late phase of the rate of voluntary force development (RVFD) and muscle damage markers after downhill running.

Methods

Ten recreational runners performed a 30-min downhill run at 10 km h−1 and −20% (−11.3°) on a motorized treadmill. At baseline and each day up to 4 days RVFD, knee extensors maximum voluntary isometric force (MVIC), serum creatine kinase (CK) concentration, quadriceps swelling, and soreness were assessed. The early (0–50 ms) and late (100–200 ms) phase of the RVFD, as well as the force developed at 50 and 200 ms, were also determined.

Results

MVIC showed moderate decrements (p < 0.05) and recovered after 4 days (p > 0.05). Force at 50 ms and the early phase were not impaired (p > 0.05). Conversely, force at 200 ms and the late phase showed moderate decrements (p < 0.05) and recovered after 3 and 4 days, respectively (p > 0.05). CK concentration, quadriceps swelling, and soreness increased (p < 0.05) were overall fully resolved after 4 days (p > 0.05).

Conclusion

Downhill running affected the knee extensors RVFD late but not early phase. The RVFD late phase may be used as an additional marker of muscle damage in trail running.
Covalent immobilization of β-galactosidase using a novel carrier alginate/tea waste: statistical optimization of beads modification and reusability
Authors: Abdella Mohamed A. A. , Hassan Mohamed E.
Published: January 2024

β-galactosidase has been immobilized onto novel alginate/tea waste gel beads (Alg/TW) via covalent binding. Alg/TW beads were subjected to chemical modification through amination with polyethyleneimine (PEI) followed by activation with glutaraldehyde (GA). Chemical modification parameters including PEI concentration, PEI pH, and GA concentration were statistically optimized using Response Surface methodology (RSM) based on Box–Behnken Design (BBD). Analysis of variance (ANOVA) results confirmed the great significance of the model that had F value of 37.26 and P value < 0.05. Furthermore, the R2 value (0.9882), Adjusted R2 value (0.9617), and predicted R2 value (0.8130) referred to the high correlation between predicted and experimental values, demonstrating the fitness of the model. In addition, the coefficient of variation (CV) value was 2.90 that pointed to the accuracy of the experiments. The highest immobilization yield (IY) of β-galactosidase (75.1%) was given under optimized conditions of PEI concentration (4%), PEI pH (9.5), and GA concentration (2.5%). Alg/TW beads were characterized by FT-IR, TGA, and SEM techniques at each step of immobilization process. Moreover, the immobilized β-galactosidase revealed a very good reusability as it could be reused for 15 and 20 consecutive cycles keeping 99.7 and 72.1% of its initial activity, respectively. In conclusion, the environmental waste (tea waste) can be used in modern technological industries such as the food and pharmaceutical industry.
The effects of injectable platelet-rich fibrin application on wound healing following gingivectomy and gingivoplasty operations: single-blind, randomized controlled, prospective clinical study
Authors: Bahar Şeyma Çardakcı , Karakan Nebi Cansın , Vurmaz Ayhan
Published: January 2024

Objectives

The aim of this study was to evaluate the effects of wound healing using injectable platelet-rich fibrin (IPRF) after gingivectomy and gingivoplasty.

Materials and methods

In this clinical study, 46 systemically healthy patients with chronic inflammatory gingival enlargement were randomly treated with gingivectomy-gingivoplasty + I-PRF (n=23) or gingivectomy-gingivoplasty alone (n=23). The primary outcome was to evaluate the effect of I-PRF on wound healing over a 3-week follow-up period. Samples collected from gingival crevicular fluid (GCF) were processed using enzyme-linked immunosorbent assay (ELİSA) to measure VEGF and FGF-10 biomarkers. The surgical areas were stained with Mira-2 tone and evaluated in ImageJ. Wound healing was evaluated with Modified Manchester Scar (MMS) scale and Landry, Turnbull, and Howley (LTH) index.

Results

VEGF values of the control group at baseline, week 2, and week 3 were significantly higher than the test group. In weeks 2 and 3, FGF-10 values were found to be significantly higher in the control group than the test group. The amount of staining was found to be significantly higher in the control group than in the test group on days 3, 7, and 14. LTH values of the control group were significantly lower than the test group and MMS values were significantly higher than those of the test group.

Conclusions

I-PRF applications revealed positive effects on epithelial wound healing after gingivectomy and gingivoplasty operations.

Clinical relevance

Platelet concentrates such as I-PRF accelerate wound healing and contribute to the patient’s comfort and quality of life. I-PRF application may have positive effects on wound healing after gingivectomy and gingivoplasty operations.
Deep Learning–based Diagnosis of Pulmonary Tuberculosis on Chest X-ray in the Emergency Department: A Retrospective Study
Authors: Wang Chih-Hung , Chang Weishan , Lee Meng-Rui , Tay Joyce , Wu Cheng-Yi , Wu Meng-Che , Roth Holger R. , Yang Dong , Zhao Can , Wang Weichung , Huang Chien-Hua
Published: January 2024

Prompt and correct detection of pulmonary tuberculosis (PTB) is critical in preventing its spread. We aimed to develop a deep learning–based algorithm for detecting PTB on chest X-ray (CXRs) in the emergency department. This retrospective study included 3498 CXRs acquired from the National Taiwan University Hospital (NTUH). The images were chronologically split into a training dataset, NTUH-1519 (images acquired during the years 2015 to 2019; n = 2144), and a testing dataset, NTUH-20 (images acquired during the year 2020; n = 1354). Public databases, including the NIH ChestX-ray14 dataset (model training; 112,120 images), Montgomery County (model testing; 138 images), and Shenzhen (model testing; 662 images), were also used in model development. EfficientNetV2 was the basic architecture of the algorithm. Images from ChestX-ray14 were employed for pseudo-labelling to perform semi-supervised learning. The algorithm demonstrated excellent performance in detecting PTB (area under the receiver operating characteristic curve [AUC] 0.878, 95% confidence interval [CI] 0.854–0.900) in NTUH-20. The algorithm showed significantly better performance in posterior-anterior (PA) CXR (AUC 0.940, 95% CI 0.912–0.965, p-value < 0.001) compared with anterior–posterior (AUC 0.782, 95% CI 0.644–0.897) or portable anterior–posterior (AUC 0.869, 95% CI 0.814–0.918) CXR. The algorithm accurately detected cases of bacteriologically confirmed PTB (AUC 0.854, 95% CI 0.823–0.883). Finally, the algorithm tested favourably in Montgomery County (AUC 0.838, 95% CI 0.765–0.904) and Shenzhen (AUC 0.806, 95% CI 0.771–0.839). A deep learning–based algorithm could detect PTB on CXR with excellent performance, which may help shorten the interval between detection and airborne isolation for patients with PTB.
Application of artificial intelligence technology in the field of orthopedics: a narrative review
Authors: Liu Pengran , Zhang Jiayao , Liu Songxiang , Huo Tongtong , He Jiajun , Xue Mingdi , Fang Ying , Wang Honglin , Xie Yi , Xie Mao , Zhang Dan , Ye Zhewei
Published: January 2024

Artificial intelligence (AI) was a new interdiscipline of computer technology, mathematic, cybernetics and determinism. These years, AI had obtained a significant development by the improvement of core technology Machine Learning and Deep Learning. With the assistance of AI, profound changes had been brought into the traditional orthopedics. In this paper, we narratively reviewed the latest applications of AI in orthopedic diseases, including the severity evaluation, triage, diagnosis, treatment and rehabilitation. The research point, relevant advantages and disadvantages of the orthopedic AI was also discussed combined with our own research experiences. We aimed to summarize the past achievements and appeal for more attentions and effective applications of AI in the field of orthopedics.
A novel approach to fuzzy N-soft sets and its application for identifying and sanctioning cyber harassment on social media platforms
Authors: Korkmaz Esra , Riaz Muhammad , Deveci Muhammet , Kadry Seifedine
Published: January 2024

This study proposes a novel approach to fuzzy N-soft sets for handling cases where membership degree and grade are not related. In the standard model of fuzzy N-soft sets, membership degree and grade are assumed to be directly proportional. This assumption may not hold true in real-world situations, so a more flexible and nuanced approach is necessary. The proposed approach includes two novel algorithms for decision-making problems involving fuzzy N-soft sets. As a result, it is able to be adaptable and sensitive when addressing uncertainties in real-world scenarios, with a particular focus on identifying and sanctioning cyber harassment on social media platforms. Additionally, an innovative perspective and approach to decision-making problems involving fuzzy N-soft sets is introduced by extending an established selection process that prioritizes the dominant parameter, resulting in more precise and dependable outcomes. Our study offers an effective tool for decision-making in various fields, including e-commerce, social media, and product reviews.
DiscoLQA: zero-shot discourse-based legal question answering on European Legislation
Authors: Sovrano Francesco , Palmirani Monica , Sapienza Salvatore , Pistone Vittoria
Published: January 2024

The structures of discourse used by legal and ordinary languages share differences that foster technical issues when applying or fine-tuning general-purpose language models for open-domain question answering on legal resources. For example, longer sentences may be preferred in European laws (i.e., Brussels I bis Regulation EU 1215/2012) to reduce potential ambiguities and improve comprehensibility, distracting a language model trained on ordinary English. In this article, we investigate some mechanisms to isolate and capture the discursive patterns of legalese in order to perform zero-shot question answering, i.e., without training on legal documents. Specifically, we use pre-trained open-domain answer retrieval systems and study what happens when changing the type of information to consider for retrieval. Indeed, by selecting only the important parts of discourse (e.g., elementary units of discourse, EDU for short, or abstract representations of meaning, AMR for short), we should be able to help the answer retriever identify the elements of interest. Hence, with this paper, we publish Q4EU, a new evaluation dataset that includes more than 70 questions and 200 answers on 6 different European norms, and study what happens to a baseline system when only EDUs or AMRs are used during information retrieval. Our results show that the versions using EDUs are overall the best, leading to state-of-the-art F1, precision, NDCG and MRR scores.
A framework to support the identification of critical habitat for wide-ranging species at risk under climate change
Authors: Leston Lionel , Dénes Francisco V. , Docherty Teegan D. S. , Tremblay Junior A. , Boulanger Yan , Van Wilgenburg Steven L. , Stralberg Diana , Sólymos Peter , Haché Samuel , Laurent Kathy St. , Weeber Russ , Drolet Bruno , Westwood Alana R. , Hope David D. , Ball Jeff , Song Samantha J. , Cumming Steven G. , Bayne Erin , Schmiegelow Fiona K. A.
Published: January 2024

To recover species at risk, it is necessary to identify habitat critical to their recovery. Challenges for species with large ranges (thousands of square kilometres) include delineating management unit boundaries within which habitat use differs from other units, along with assessing any differences among units in amounts of and threats to habitat over time. We developed a reproducible framework to support identification of critical habitat for wide-ranging species at risk. The framework (i) reviews species distribution and life history; (ii) delineates management units across the range; (iii) evaluates and compares current and (iv) potential future habitat and population size and (v) prioritizes areas within management units based on current and future conditions under various scenarios of climate change and land-use. We used Canada Warbler (Cardellina canadensis) and Wood Thrush (Hylocichla mustelina) in Canada as case studies. Using geographically weighted regression models and cluster analysis to measure spatial variation in model coefficients, we found geographic differences in habitat association only for Canada Warbler. Using other models to predict current habitat amount for each species in different management units, then future habitat amount under land use and climate change, we projected that: (1) Canada Warbler populations would decrease in Alberta but increase in Nova Scotia and (2) Wood Thrush populations would increase under most scenarios run in Quebec, New Brunswick and Nova Scotia, but not in Ontario. By comparing results from future scenarios and spatial prioritization exercises, our framework supports identification of critical habitat in ways that incorporate climate and land-use projections.
Localization and characterisation of brown rot in two types of acetylated wood
Authors: Ponzecchi Andrea , Alfredsen Gry , Fredriksson Maria , Thybring Emil E. , Thygesen Lisbeth G.
Published: January 2024

Acetylation is a commercialised chemical wood modification technology that increases the durability of wood against microbial attack. However, the details of how acetylation protects the wood structure from fungal degradation are still unclear. In this study, we tested the hypothesis that the resistance against microbial attack depends on the localisation of acetylation within the cell wall. The methodology involved two types of acetylation (uniform and lumen interface modification), which were analysed by lab-scale degradation with Rhodonia placenta, chitin quantification, infrared spectroscopy, and Raman microspectroscopy. The location of the acetylation did not affect overall mass loss during degradation experiments. Instead, the mass loss was related to the intensity of the treatment. However, chemical imaging of the interface acetylated specimens showed that degradation primarily took place in cell wall regions that were less acetylated. It was also observed that the fungus required more fungal biomass (i.e., fungal mycelia) to degrade acetylated wood than untreated wood. Based on dimensions and comparison to a reference spectrum, several cross-sections of hyphae located within lumina were discovered in the Raman images. These hyphae showed presence of chitin, water and chelated metals within their walls, and could be separated into an inner and an outer part based on their chemistry as seen in the spectra. The outer part was distinguished by a relatively higher amount of water and less chelated iron than the inner part.
Agricultural activities and risk of Alzheimer’s disease: the TRACTOR project, a nationwide retrospective cohort study
Authors: Petit Pascal , Gondard Elise , Gandon Gérald , Moreaud Olivier , Sauvée Mathilde , Bonneterre Vincent
Published: January 2024

Data regarding Alzheimer’s disease (AD) occurrence in farming populations is lacking. This study aimed to investigate whether, among the entire French farm manager (FM) workforce, certain agricultural activities are more strongly associated with AD than others, using nationwide data from the TRACTOR (Tracking and monitoring occupational risks in agriculture) project. Administrative health insurance data (digital electronic health/medical records and insurance claims) for the entire French agricultural workforce, over the period 2002–2016, on the entire mainland France were used to estimate the risk of AD for 26 agricultural activities with Cox proportional hazards model. For each analysis (one for each activity), the exposed group included all FMs that performed the activity of interest (e.g. crop farming), while the reference group included all FMs who did not carry out the activity of interest (e.g. FMs that never farmed crops between 2002 and 2016). There were 5067 cases among 1,036,069 FMs who worked at least one year between 2002 and 2016. Analyses showed higher risks of AD for crop farming (hazard ratio (HR) = 3.72 [3.47–3.98]), viticulture (HR = 1.29 [1.18–1.42]), and fruit arboriculture (HR = 1.36 [1.15–1.62]). By contrast, lower risks of AD were found for several animal farming types, in particular for poultry and rabbit farming (HR = 0.29 [0.20–0.44]), ovine and caprine farming (HR = 0.50 [0.41–0.61]), mixed dairy and cow farming (HR = 0.46 [0.37–0.57]), dairy farming (HR = 0.67 [0.61–0.73]), and pig farming (HR = 0.30 [0.18–0.52]). This study shed some light on the association between a wide range of agricultural activities and AD in the entire French FMs population.
What Does ‘(Non)-absoluteness of Observed Events’ Mean?
Authors: Adlam Emily
Published: January 2024

Recently there have emerged an assortment of theorems relating to the ‘absoluteness of emerged events,’ and these results have sometimes been used to argue that quantum mechanics may involve some kind of metaphysically radical non-absoluteness, such as relationalism or perspectivalism. However, in our view a close examination of these theorems fails to convincingly support such possibilities. In this paper we argue that the Wigner’s friend paradox, the theorem of Bong et al and the theorem of Lawrence et al are all best understood as demonstrating that if quantum mechanics is universal, and if certain auxiliary assumptions hold, then the world inevitably includes various forms of ‘disaccord,’ but this need not be interpreted in a metaphysically radical way; meanwhile, the theorem of Ormrod and Barrett is best understood either as an argument for an interpretation allowing multiple outcomes per observer, such as the Everett approach, or as a proof that quantum mechanics cannot be universal in the sense relevant for this theorem. We also argue that these theorems taken together suggest interesting possibilities for a different kind of relational approach in which interaction states are relativized whilst observed events are absolute, and we show that although something like ‘retrocausality’ might be needed to make such an approach work, this would be a very special kind of retrocausality which would evade a number of common objections against retrocausality. We conclude that the non-absoluteness theorems may have a significant role to play in helping converge towards an acceptable solution to the measurement problem.
Redefining the role of doctoral supervisors: a multicultural examination of labels and functions in contemporary doctoral education
Authors: Guarimata-Salinas Génesis , Carvajal Joan Josep , Jiménez López M. Dolores
Published: January 2024

This study focuses on the changes that doctoral education has experienced in the last decades and discusses the role of doctoral supervisors. The figure of doctoral supervisor continues to be a subject of much debate; therefore, the aim of this study is to provide a universal, global, and common definition that clearly establishes the roles and functions of doctoral supervisors. Employing a multi-method approach, the study utilized the perspectives of linguistic relativism and prototype theory to understand how linguistic and label diversity may influence the perception and approach to supervisory tasks. We examine a corpus of 55 different labels to refer to “doctoral supervisor.” Data was collected from 116 countries, encompassing 47 different languages and 55 distinct labels from Europe, Africa, America, Asia, and Oceania, forming a unique corpus of information. The results reveal a total of 18 functions to be fulfilled by the doctoral supervisor. Additionally, the findings underscore the significance of linguistic influence in conceptualizing the functions associated with the supervisor in various cultural contexts and highlight the necessity for redefining the role of the thesis supervisor. The results hold potential benefits for doctoral schools and supervisors, serving as guidelines for standardizing the functions of the doctoral supervisor.
Corporate income tax, IP boxes and the location of R&D
Authors: Shehaj Pranvera , Weichenrieder Alfons J.
Published: January 2024

We discuss corporate tax effects on multinationals’ R&D. Theoretically, we find that a host country’s tax increase may boost local R&D expenditure: while R&D becomes deductible at a higher rate, this higher rate may not apply to all R&D returns. First, as R&D creates a public good within the MNE, some R&D returns are taxed at other countries’ tax rates. Second, some of the R&D returns are taxed at a lower IP regime tax rate. The positive tax rate effect is empirically supported by country-by-country R&D data of U.S.-owned subsidiaries for countries that have an IP regime.
The ultra-high electric breakdown strength and superior energy storage properties of (Bi0.2Na0.2K0.2La0.2Sr0.2)TiO3 high-entropy ferroelectric thin films
Authors: Yang Wentao , Ullah Sana , Zheng Guangping
Published: January 2024

The electric breakdown strength (Eb) is an important factor that determines the practical applications of dielectric materials in electrical energy storage and electronics. However, there is a tradeoff between Eb and the dielectric constant in the dielectrics, and Eb is typically lower than 10 MV/cm. In this work, ferroelectric thin film (Bi0.2Na0.2K0.2La0.2Sr0.2)TiO3 with a dielectric constant of 115 is found to exhibit an ultra-high Eb = 10.99 MV/cm, attributing to the high-entropy effects that could result in dense nanostructures with refined grains, low concentration of oxygen vacancies, low leakage current and small polar nano-regions in the thin film. A recoverable energy storage density of 5.88 J/cm3 with an excellent energy storage efficiency of 93% are obtained for the dielectric capacitor containing the thin-film dielectrics. Remarkably, the dielectric capacitor possesses a theoretical energy storage density of 615 J/cm3 compatible to those of electrochemical supercapacitors. The high-entropy ferroelectric thin films with ultra-high Eb and superior energy storage properties are much promising dielectrics used in next-generation energy storage devices and power electronics.
Longitudinal Effects of Employees’ Big Five Personality Traits on Internal Promotions Differentiated by Job Level in a Multinational Company
Authors: Kordsmeyer Tobias L. , Speer Andrew B. , Wilms Rafael , Kurz Rainer
Published: January 2024

Promotions are central to individual career success. For organisations, it is crucial to identify and develop employees capable of higher-level responsibility. Previous research has shown that personality traits as inter-individual differences predict promotions. However, effects have mostly been examined on a broad factor level. This study investigated longitudinal effects of Big Five personality traits on both factor (neuroticism, extraversion, openness to experience, agreeableness, conscientiousness) and more detailed facet levels on promotions in employees of a multinational wholesale company (N = 1774, n = 343 promoted). We also explored how personality differentially impacts promotional likelihood as a matter of target job level (individual contributor vs. first- or senior-level manager roles). Overall, associations with promotions were detected for neuroticism (negative) and conscientiousness (positive). At the more nuanced facet level, all Big Five factors had at least one personality facet that was significantly related to promotions. Additionally, personality-promotion relationships were generally stronger for lower- rather than higher-level promotions. Taken together, our findings demonstrate that employee personality traits have a meaningful impact on who will be promoted and should hence be considered in organisational personnel selection, personnel development, and performance management practices.
Principled diverse counterfactuals in multilinear models
Authors: Papantonis Ioannis , Belle Vaishak
Published: January 2024

Machine learning (ML) applications have automated numerous real-life tasks, improving both private and public life. However, the black-box nature of many state-of-the-art models poses the challenge of model verification; how can one be sure that the algorithm bases its decisions on the proper criteria, or that it does not discriminate against certain minority groups? In this paper we propose a way to generate diverse counterfactual explanations from multilinear models, a broad class which includes Random Forests, as well as Bayesian Networks.
Explaining neural networks without access to training data
Authors: Marton Sascha , Lüdtke Stefan , Bartelt Christian , Tschalzev Andrej , Stuckenschmidt Heiner
Published: January 2024

We consider generating explanations for neural networks in cases where the network’s training data is not accessible, for instance due to privacy or safety issues. Recently, Interpretation Nets ($$\mathcal {I}$$
I
-Nets) have been proposed as a sample-free approach to post-hoc, global model interpretability that does not require access to training data. They formulate interpretation as a machine learning task that maps network representations (parameters) to a representation of an interpretable function. In this paper, we extend the $$\mathcal {I}$$
I
-Net framework to the cases of standard and soft decision trees as surrogate models. We propose a suitable decision tree representation and design of the corresponding $$\mathcal {I}$$
I
-Net output layers. Furthermore, we make $$\mathcal {I}$$
I
-Nets applicable to real-world tasks by considering more realistic distributions when generating the $$\mathcal {I}$$
I
-Net’s training data. We empirically evaluate our approach against traditional global, post-hoc interpretability approaches and show that it achieves superior results when the training data is not accessible.
A new listener-centered directional attenuation sound model for augmented reality environments
Authors: Martínez-Cabrejas Marina , Portalés Cristina , Gimeno Jesús , Pérez Manolo , Casas-Yrurzum Sergio
Published: January 2024

Augmented Reality (AR) involves the combination of synthetic and real stimuli, not being restricted to visual cues. For the inclusion of computer-generated sound in AR environments, it is often assumed that the distance attenuation model is the most intuitive and useful system for all users, regardless of the characteristics of the environment. This model reduces the gain of the sound sources as a function of the distance between the source and the listener. In this paper, we propose a different attenuation model not only based on distance, but also considering the listener orientation, so the user could listen more clearly the objects that they are looking at, instead of other near objects that could be out of their field of view and interest. We call this a directional attenuation model. To test the model, we developed an AR application that involves visual and sound stimuli to compare the traditional model versus the new one, by considering two different tasks in two AR scenarios in which sound plays an important role. A total of 38 persons participated in the experiments. The results show that the proposed model provides better workload for the two tasks, requiring less time and effort, allowing users to explore the AR environment more easily and intuitively. This demonstrates that this alternative model has the potential to be more efficient for certain applications.
Software sensors in the monitoring of microalgae cultivations
Authors: Porras Reyes Luis , Havlik Ivo , Beutel Sascha
Published: January 2024

Microalgae are well-known photosynthetic microorganisms used as cell factories for the production of relevant biotechnological compounds. Despite the outstanding characteristics attributed to microalgae, their industrial-scale production still struggles with scale-up problems and economic feasibility. One important bottleneck is the lack of suitable online sensors for the reliable monitoring of biological parameters, mostly concentrations of intracellular components, in microalgae bioprocesses. Software sensors provide an approach to improving the monitoring of those process parameters that are difficult to quantify directly and are therefore only indirectly accessible. Their use aims to improve the productivity of microalgal bioprocesses through better monitoring, control and automation, according to the current demands of Industry 4.0. In this review, a description of the microalgae components of interest as candidates for monitoring in a cultivation, an overview of software sensors, some of the available approaches and tools, and the current state-of-the-art of the design and use of software sensors in microalgae cultivation are presented. The latter is grouped on the basis of measurement methods used as software sensor inputs, employing either optical or non-optical techniques, or a combination of both. Some examples of software sensor design using simulated process data are also given, grouped according to their design, either as model-driven or data-driven estimators.
Benefits of international collaboration in computer science: a case study of China, the European Union, and the United States
Authors: Gómez-Espés Alberto , Färber Michael , Jatowt Adam
Published: January 2024

Co-authored publications can bring positive results for those who participate, such as gaining additional expertise, accessing more funding or increasing the publication impact. China, the European Union, and the United States have been collaborating between each other throughout the years in the field of Computer Science. These collaborations varied over time, as well as they impacted the regions in different ways. In this paper, we collected the publications from these territories across 31 years on the topic of Computer Science and studied them focusing on how the regions have approached co-authorship. In particular, we have analyzed the number of collaborations during that period, the impact of those papers measured as the number of citations, and the topics that have been researched. We conclude that China’s focus on Computer Science fields has led it to be the most productive region in recent years; plus, it has benefited from the American and European reputation, by increasing its citation rates when collaborating with them. On the other hand, the EU and the US have benefited from Chinese interest in computer science, increasing the number of publications together.
Distributed order estimation for continuous-time stochastic systems
Authors: Zhu Xinghua , Liu Zhixin , Hu Xiaoming
Published: January 2024

In this paper, we investigate the distributed estimation problem of continuous-time stochastic dynamic systems over sensor networks when both the system order and parameters are unknown. We propose a local information criterion (LIC) based on the $$L_0$$

L
0

penalty term. By minimizing LIC at the diffusion time instant and utilizing the continuous-time diffusion least squares algorithm, we obtain a distributed estimation algorithm to simultaneously estimate the unknown order and the parameters of the system. By dealing with the effect of the system noises and the coupling relationship between estimation of system orders and parameters, we establish the almost sure convergence results of the proposed distributed estimation algorithm. Furthermore, we give a simulation example to verify the effectiveness of the distributed algorithm in estimating the system order and parameters.
Cuplength estimates for time-periodic measures of Hamiltonian systems with diffusion
Authors: Fabert Oliver
Published: January 2024

We show how methods from Hamiltonian Floer theory can be used to establish lower bounds for the number of different time-periodic measures of time-periodic Hamiltonian systems with diffusion. After proving the existence of closed random periodic solutions and of the corresponding Floer curves for Hamiltonian systems with random walks with step width 1/n for every $$n\in \mathbb {N}$$

n
∈
N

, we show that, after passing to a subsequence, they converge in probability distribution as $$n\rightarrow \infty $$

n
→
∞

. Besides using standard results from Hamiltonian Floer theory and about convergence of tame probability measures, we crucially use that sample paths of Brownian motion are almost surely Hölder continuous with Hölder exponent $$0<\alpha <\frac{1}{2}$$

0
<
α
<

1
2

.
Vulnerability and resilience among farmers and market actors in local agri-food value chains in the face of COVID-19 disruptions: findings from Uganda and Kenya
Authors: Bitzer Verena , Kruijssen Froukje , Mugisha Johnny , Waswa Lydiah , Aliso Judith , Nakazzi Betty
Published: January 2024

Countries which imposed strict containment measures in response to the COVID-19 pandemic are thought to have faced particular socio-economic challenges. This study assesses the implications of COVID-19 disruptions on local agri-food value chain actors in Kenya and Uganda, as both countries enacted strict lockdowns to limit the spread of the virus. Using survey data from 527 smallholder farmers and 107 small-scale market actors, the study analyses these actors’ vulnerability and resilience. This is operationalised as (1) the exposure of respondents to COVID-19 containment measures, (2) effects of these measures as observed by respondents (e.g. on production or trade and income), and (3) (short-term) coping strategies used by respondents to deal with such impacts. Our results show how containment measures have restricted personal movement and transport options and have limited access to agricultural inputs and markets. This led to a decrease in agricultural production and local trading activities. While both farmers and market actors experienced massive negative income effects, market actors were being hit particularly hard as their livelihoods depend on free movement which was severely curtailed during the pandemic. Actors from both categories often tried to cope by selling livestock, using savings and lowering both food intake and food diversity. Coping strategies were thus short-term and further reduced actors’ resilience by exhausting their buffering capacity and exposing them to the risk of food insecurity.
Does spirea aphid (Aphis spiraecola Patch, Homoptera: Aphididae) overwinter on apple in Central Europe?
Authors: Borbély Csaba , Nagy Csaba , Markó Viktor
Published: January 2024

The native green apple aphid (Aphis pomi DeGeer) and the invasive green spirea aphid (Aphis spiraecola Patch) share apple as a common host plant during the summer months in Central Europe. Various studies suggest that, under certain conditions, the originally host-alternating A. spiraecola is able to overwinter on apple as a winter host, following a similar life history to A. pomi. In this study, we collected stem mothers (fundatrices) and aphids of the second generation (fundatrigeniae) from ten localities throughout Hungary for nine consecutive springs to assess whether A. spiraecola can overwinter on apple as a winter host. All the collected aphid individuals (1126 aphids from 114 stem colonies during the nine years of the study) belonged to A. pomi, indicating that A. spiraecola does not, or very rarely can, overwinter on apple under Central European conditions.
Perfectionism as a moderator of the relationship between orthorexia nervosa and obsessive–compulsive symptoms
Authors: Huynh Phillipa Ann , Miles Stephanie , Nedeljkovic Maja
Published: January 2024

Purpose

Orthorexia nervosa (ON), a proposed disorder describing an obsessive focus on “healthy” eating, is characterised as having overlapping symptoms with obsessive–compulsive disorder. However, ON/obsessive–compulsive (OC) symptom relationships are inconsistently reported. The current study aimed to investigate if the contribution of OC symptoms and beliefs explain variability in ON symptoms and determine if perfectionism, a transdiagnostic factor, moderates the ON/OC symptom relationship.

Methods

The study comprised 190 participants (Mage = 28.63, SDage = 9.88; 80% female) recruited via an undergraduate research programme, social media, advocacy organisations, and a participant registry. Participants completed an online questionnaire assessing ON, OC, and perfectionism symptoms.

Results

A linear regression analysis found OC symptoms and beliefs explained 22.9% variability in ON symptoms (p < 0.001, f2 = 0.38) and perfectionism moderated the ON/OC symptom relationship, where higher levels of perfectionism with higher levels of OC symptoms was associated with higher levels of ON symptoms, explaining 2.2% variability (p = .01, f2 = 0.03).

Conclusion

OC symptoms appear more common in ON than previous studies indicate. However, the interaction between perfectionism and OC symptoms may drive obsessions in ON. Findings help refine our current understanding of ON phenomenology with implications for ON treatment development. Future research should further explore perfectionism in ON phenomenology.

Level of evidence: Level V (Opinions of respected authorities, based on descriptive studies, narrative reviews, clinical experience, or reports of expert committees).
Prediction of contact resistance of electrical contact wear using different machine learning algorithms
Authors: Cai Zhen-bing , Li Chun-lin , You Lei , Chen Xu-dong , He Li-ping , Cao Zhong-qing , Zhang Zhi-nan
Published: January 2024

H62 brass material is one of the important materials in the process of electrical energy transmission and signal transmission, and has excellent performance in all aspects. Since the wear behavior of electrical contact pairs is particularly complex when they are in service, we evaluated the effects of load, sliding velocity, displacement amplitude, current intensity, and surface roughness on the changes in contact resistance. Machine learning (ML) algorithms were used to predict the electrical contact performance of different factors after wear to determine the correlation between different factors and contact resistance. Random forest (RF), support vector regression (SVR) and BP neural network (BPNN) algorithms were used to establish RF, SVR and BPNN models, respectively, and the experimental data were trained and tested. It was proved that BP neural network model could better predict the stable mean resistance of H62 brass alloy after wear. Characteristic analysis shows that the load and current have great influence on the predicted electrical contact properties. The wear behavior of electrical contacts is influenced by factors such as load, sliding speed, displacement amplitude, current intensity, and surface roughness during operation. Machine learning algorithms can predict the electrical contact performance after wear caused by these factors. Experimental results indicate that an increase in load, current, and surface roughness leads to a decrease in stable mean resistance, while an increase in displacement amplitude and frequency results in an increase in stable mean resistance, leading to a decline in electrical contact performance. To reduce testing time and costs and quickly obtain the electrical contact performance of H62 brass alloy after wear caused by different factors, three algorithms (random forest (RF), support vector regression (SVR), and BP neural network (BPNN)) were used to train and test experimental results, resulting in a machine learning model suitable for predicting the stable mean resistance of H62 brass alloy after wear. The prediction results showed that the BPNN model performed better in predicting the electrical contact performance compared to the RF and SVR models.