bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trustworthy machine learning in the context of security and privacy
Authors: Upreti Ramesh , Lind Pedro G. , Elmokashfi Ahmed , Yazidi Anis 
Published: April 2024

AbstractArtificial intelligence-based algorithms are widely adopted in critical applications such as healthcare and autonomous vehicles. Mitigating the security and privacy issues of AI models, and enhancing their trustworthiness have become of paramount importance. We present a detailed investigation of existing security, privacy, and defense techniques and strategies to make machine learning more secure and trustworthy. We focus on the new paradigm of machine learning called federated learning, where one aims to develop machine learning models involving different partners (data sources) that do not need to share data and information with each other. In particular, we discuss how federated learning bridges security and privacy, how it guarantees privacy requirements of AI applications, and then highlight challenges that need to be addressed in the future. Finally, after having surveyed the high-level concepts of trustworthy AI and its different components and identifying present research trends addressing security, privacy, and trustworthiness separately, we discuss possible interconnections and dependencies between these three fields. All in all, we provide some insight to explain how AI researchers should focus on building a unified solution combining security, privacy, and trustworthy AI in the future.
Unfair clause detection in terms of service across multiple languages
Authors: Galassi Andrea , Lagioia Francesca , Jabłonowska Agnieszka , Lippi Marco 
Published: April 2024

AbstractMost of the existing natural language processing systems for legal texts are developed for the English language. Nevertheless, there are several application domains where multiple versions of the same documents are provided in different languages, especially inside the European Union. One notable example is given by Terms of Service (ToS). In this paper, we compare different approaches to the task of detecting potential unfair clauses in ToS across multiple languages. In particular, after developing an annotated corpus and a machine learning classifier for English, we consider and compare several strategies to extend the system to other languages: building a novel corpus and training a novel machine learning system for each language, from scratch; projecting annotations across documents in different languages, to avoid the creation of novel corpora; translating training documents while keeping the original annotations; translating queries at prediction time and relying on the English system only. An extended experimental evaluation conducted on a large, original dataset indicates that the time-consuming task of re-building a novel annotated corpus for each language can often be avoided with no significant degradation in terms of performance.
The development and utilization of two SCAR markers linked to the resistance of banana (Musa spp. AAA) to Fusarium oxysporum f. sp. cubense race 4
Authors: Qv Mengran , Feng Guoen , Chen Shule , Chen Houbin , Chen Chengjie , Wang Fang , Lv Shun , Dai Longyu , Liu Hui , Huang Bingzhi , Li Xiaoquan , Su Zuxiang , Xu Chunxiang 
Published: April 2024

AbstractBanana (Musa spp.) production worldwide is seriously threatened by Fusarium wilt caused by Fusarium oxysporum f. sp. cubense (Foc). The best way to control this disease is to grow resistant cultivars. However, it requires large-scale field evaluations and labor- and time-consuming to obtain disease-resistant germplasm. Development of early, reliable, and reproducible selection strategies are considered as the efficient approach which could speed up the selection procedure. In this study, two pairs of sequence-related amplified polymorphism (SRAP) primers related to banana Foc resistance/susceptibility were screened from 100 pairs of random primers. Correspondingly, two pairs of sequence characterized amplified region (SCAR) markers (namely SC4-F/SC4-R and SC14-F/SC14-R, respectively) were successfully generated from these two SRAP markers using 30 cultivars either resistant or susceptible to Foc. Both SCAR markers were located in mitochondrion genome and showed discriminatory power of 96.67% and 100%, respectively. Mitochondrial proteins possibly play a very important role in banana resistance to Foc. In additional, these two SCAR markers were employed simultaneously to screen potential resistant germplasm from 53 accessions with unknown resistance to Foc, and the results revealed a consistency of 83.0% with each other, further indicating their high reliability and reproducibility. These results suggest that both SCAR markers could be used in molecular marker-assisted selection for banana germplasm resistant to Fusarium.
A machine learning framework for explainable knowledge mining and production, maintenance, and quality control optimization in flexible circular manufacturing systems
Authors: Koulinas Georgios K. , Paraschos Panagiotis D. , Koulouriotis Dimitrios E. 
Published: April 2024

AbstractIn the present study, we employed multiple decision tree algorithms to categorize cases and reflect the most efficient policies constructed by a reinforcement learning algorithm. These approaches treated a complex production, maintenance, and quality control optimization problem within a degrading manufacturing and remanufacturing system. The decision trees’ nodes represent the independent variables, while the trees’ leaves represent the set of function values. The reinforcement learning method revealed all optimization parameters and best policies, which were employed as the training sample for the tree algorithms. After constructing every decision tree, each resulting decision rule was used to solve the optimization problem, and its performance was assessed. Additionally, we performed a sensitivity analysis to determine if the pruning level impacts the objective function value and, generally, the effectiveness of the proposed approach.
International student mobility within Europe: responding to contemporary challenges
Authors: Brooks Rachel , Courtois Aline , Faas Daniel , Jayadeva Sazana , Beech Suzanne 
Published: April 2024

AbstractIn this article, we provide an introduction to the special issue on ‘Challenges to International Student Mobility within Europe’. We first discuss the current context of such mobility and justify our focus on Europe, in particular, by outlining some distinctive features of this geographical region. We then outline the contributions of the articles that make up the special issue—in terms of the challenges they identify, the ways in which they theorise international student mobility, and the responses they proffer. Throughout, we acknowledge the rich extant literature on international student mobility and weave this into our discussion as appropriate.
Research Ethics Committee and Integrity Board Members’ Collaborative Decision Making in Cases in a Training Setting
Authors: Löfström E. , Pitkänen H. , Čekanauskaitė A. , Lukaševičienė V. , Kyllönen S. , Gefenas E. 
Published: April 2024

AbstractThis research focuses on how research ethics committee and integrity board members discuss and decide on solutions to case scenarios that involve a dimension of research ethics or integrity in collaborative settings. The cases involved issues around authorship, conflict of interest, disregard of good scientific practice and ethics review, and research with vulnerable populations (children and neonates). The cases were set in a university, a hospital, or a research institute. In the research, we used a deductive qualitative approach with thematic analysis. Twenty-seven research ethics committee and research integrity board members from 16 European countries and one country outside Europe participated. Participants represented natural and life sciences, social sciences, and humanities. They worked on cases involving ethical/integrity issues in six different constellations. Results show that experts apply key elements of ethical decision making, namely identification of ethical issues, stakeholders, guidelines, solutions, and own positionality, in dealing collaboratively with ethics/ integrity problems, and the nature of the application depends on the complexity of the case. Understanding how individuals knowledgeable in research ethics and integrity, in this case, individuals serving on research ethics committees and integrity boards, approach ethical/ moral issues can help to identify strategies that may be useful in the development of research ethics and integrity training for junior researchers who may benefit from learning professional strategies.
Can serum progesterone concentration direct a fresh or freeze-all transfer strategy in the first in vitro fertilisation cycle?
Authors: Hunt Sarah , Liu Jing , Luo Pulin , Zhong Ying , Mol Ben W. , Chi Ling , Wang Rui 
Published: April 2024

Abstract
Purpose
To examine the interaction between serum progesterone concentration on the trigger day and choice of freeze-all and fresh transfer strategies on live birth in an unselected population as well as in patients over 35 years old.

Methods
We performed a retrospective cohort study of 26,661 patients commencing their first IVF cycle in a large fertility centre between 2015 and 2019, including 4687 patients over 35 years old. We performed a multivariable fractional polynomial interaction analysis within a logistic regression model to investigate the interaction between serum progesterone concentration and the choice of freeze-all or fresh transfer strategy following the first transfer.

Results
15,539 patients underwent a fresh embryo transfer and 11,122 underwent a freeze-all strategy in their first IVF cycle. The freeze-all group had a higher live birth rate compared to the fresh group (43.9% vs 40.3%). After adjusting for confounding factors, there was a positive interaction between serum progesterone concentrations and the choice of a freeze-all versus fresh embryo transfer on live birth (p for interaction 0.0001), with a larger magnitude of effect when progesterone concentration was higher. Such an interaction was also observed in patients over 35 years old (p for interaction 0.01), but the treatment effect curve over progesterone concentrations was almost flat.

Conclusions
In an unselected population, frozen transfer is associated with greater chances of live birth, especially in patients with higher serum progesterone concentration. In patients over 35 years old, the benefit of a freeze-all policy appears small across all serum progesterone concentrations.
Continuous dependence in thermopiezoelectricity of nonsimple materials
Authors: Nunziata Martina 
Published: April 2024

AbstractIn this paper, we consider the linear theory for a model of a thermopiezoelectric nonsimple body as presented in Passarella and Tibullo (Entropy, https://doi.org/10.3390/e24091229. 2022) in which the second displacement gradient and the second electric potential gradient are included in the set of independent constitutive variables, adopting an entropy production inequality model proposed by Green and Laws. We set a mixed initial-boundary value problem and starting from two solutions we establish a reciprocity relation for the general case, which extends the analogue in Ciarletta et al. (Mech Res Commun, https://doi.org/10.1016/j.mechrescom.2022.103969, 2022), and two continuous dependence theorems for centrosymmetric materials. Both theorems consider the difference of two solutions of the problem: the first one depends only from supply terms, which are the external body forces, electric charge density and heat supply and the second one only depends from initial data for displacement, velocity, relative temperature and entropy fields. All these data, together with the boundary conditions, are assigned.
Efficient information reconciliation in quantum key distribution systems using informed design of non-binary LDPC codes
Authors: Mitra Debarnab , Shreekumar Jayanth , Tauz Lev , Sarihan Murat Can , Wong Chee Wei , Dolecek Lara 
Published: April 2024

AbstractIn quantum key distribution (QKD), two users extract a shared secret key using a quantum communication channel in the presence of an eavesdropper. Among QKD protocols, the ones based on energy-time (ET) entanglement of photons have been studied extensively due to their ability to generate high key rates from the arrival times of entangled photons. For theinformation reconciliation(IR) stage of ET-QKD protocols (where the users communicate using a classical channel in order to reconcile differences in their data), a scheme calledmulti-level coding(MLC) was proposed by Zhou et al. in prior work. The MLC scheme splits the raw key symbols into bit layers and utilizes binary low-density parity check (LDPC) codes to encode each layer. Although binary LDPC codes are able to offer low complexity decoding for IR, they have poor error-correcting performance compared to their non-binary counterparts, thus leading to low key rates. Additionally, existing LDPC codes do not fully utilize the properties of the QKD channel to optimize the key rates. In this paper, we mitigate the above issues by proposing a flexible protocol for IR in ET-QKD systems called non-binary multi-level coding (a) which is parameterized by a positive integera. The (a) protocol is a generalization of the MLC scheme and utilizes NB-LDPC codes from a Galois field of size$$2^a$$2a. We show that by using a small value ofa, the (a) protocol significantly improves the key rate without much increase in complexity. To further improve the key rates of the (a) protocol, we propose (i) a joint rate and degree distribution optimization (JRDO) algorithm to design the NB-LDPC codes for the protocol and (ii) an interleaved decoding and communication (IDC) scheme to decode the different layers of the (a) protocol. The JRDO algorithm is designed to use the QKD channel information, and we show that it results in a higher key rate than codes used in prior work. Additionally, the IDC scheme improves the key rate compared to the decoding and communication methods utilized previously in literature. Overall, the (a) protocol that uses JRDO-LDPC codes and the IDC scheme results in a significant 40–60$$\%$$%improvement in key rates compared to prior work for ET-QKD systems.
EndoViT: pretraining vision transformers on a large collection of endoscopic images
Authors: Batić Dominik , Holm Felix , Özsoy Ege , Czempiel Tobias , Navab Nassir 
Published: April 2024

Abstract
Purpose
Automated endoscopy video analysis is essential for assisting surgeons during medical procedures, but it faces challenges due to complex surgical scenes and limited annotated data. Large-scale pretraining has shown great success in natural language processing and computer vision communities in recent years. These approaches reduce the need for annotated data, which is of great interest in the medical domain. In this work, we investigate endoscopy domain-specific self-supervised pretraining on large collections of data.

Methods
To this end, we first collect Endo700k, the largest publicly available corpus of endoscopic images, extracted from nine public Minimally Invasive Surgery (MIS) datasets. Endo700k comprises more than 700,000 images. Next, we introduce EndoViT, an endoscopy-pretrained Vision Transformer (ViT), and evaluate it on a diverse set of surgical downstream tasks.

Results
Our findings indicate that domain-specific pretraining with EndoViT yields notable advantages in complex downstream tasks. In the case of action triplet recognition, our approach outperforms ImageNet pretraining. In semantic segmentation, we surpass the state-of-the-art (SOTA) performance. These results demonstrate the effectiveness of our domain-specific pretraining approach in addressing the challenges of automated endoscopy video analysis.

Conclusion
Our study contributes to the field of medical computer vision by showcasing the benefits of domain-specific large-scale self-supervised pretraining for vision transformers. We release both our code and pretrained models to facilitate further research in this direction: https://github.com/DominikBatic/EndoViT.
Research progress and prospect of low-carbon biological technology for nitrate removal in wastewater treatment
Authors: Zheng Ru , Zhang Kuo , Kong Lingrui , Liu Sitong 
Published: April 2024

AbstractWastewater treatment plants are the major energy consumers and significant sources of greenhouse gas emissions, among which biological nitrogen removal of wastewater is an important contributor to carbon emissions. However, traditional heterotrophic denitrification still has the problems of excessive residual sludge and the requirement of external carbon sources. Consequently, the development of innovative low-carbon nitrate removal technologies is necessary. This review outlines the key roles of sulfur autotrophic denitrification and hydrogen autotrophic denitrification in low-carbon wastewater treatment. The discovered nitrate/nitrite dependent anaerobic methane oxidation enables sustainable methane emission reduction and nitrogen removal by utilizing available methane in situ. Photosynthetic microorganisms exhibited a promising potential to achieve carbon-negative nitrate removal. Specifically, the algal-bacterial symbiosis system and photogranules offer effective and prospective low-carbon options for nitrogen removal. Then, the emerging nitrate removal technology of photoelectrotrophic denitrification and the underlying photoelectron transfer mechanisms are discussed. Finally, we summarize and prospect these technologies, highlighting that solar-driven biological nitrogen removal technology is a promising area for future sustainable wastewater treatment. This review has important guiding significance for the design of low-carbon wastewater treatment systems.
Idiopathic Intracranial Hypertension After Abrupt Cessation of Medication: A Case Report of Abrupt Glucagon-Like Peptide-1 (GLP-1) Receptor Agonist Cessation and Review of the Literature
Authors: Heckel Brittany 
Published: April 2024

Abstract
Purpose of Review
The purpose of this review is two-fold: (1) to discuss a case report of idiopathic intracranial hypertension (IIH) after abrupt cessation of a glucagon-like peptide-1 (GLP-1) receptor agonist with resultant rapid weight gain and (2) to review the literature regarding the potential role of GLP-1 receptor agonists in the treatment of IIH as well as potential pitfalls.

Recent Findings
GLP-1 receptor agonists have become widely used to treat obesity. Obesity is a known risk factor for the development of IIH, though the precise pathophysiology is unclear. GLP-1 receptor agonists may help treat IIH by promoting weight loss, lipolysis of adipose tissue, and potentially decreasing the secretion of CSF, as was seen in rat models. Abrupt cessation of GLP-1 receptor agonists can result in regaining lost weight rapidly. In the case that we present, the patient stopped duraglutide abruptly due to lack of insurance coverage and regained the weight she had lost within a month. She subsequently developed IIH.

Summary
GLP-1 receptor agonists have the potential to help treat IIH; however, this class of medication needs to be used carefully, as cessation of the medication and resultant rapid weight gain can result in IIH.
Probiotic-derived silver nanoparticles target mTOR/MMP-9/BCL-2/dependent AMPK activation for hepatic cancer treatment
Authors: Elmetwalli Alaa , Abdel-Monem Mohamed O. , El-Far Ali H. , Ghaith Gehad S. , Albalawi Noaf Abdullah N. , Hassan Jihan , Ismail Nadia F. , El-Sewedy Tarek , Alnamshan Mashael Mashal , ALaqeel Nouf K. , Al-Dhuayan Ibtesam S. , Hassan Mervat G. 
Published: April 2024

AbstractRecent advances in nanotechnology have offered novel ways to combat cancer. By utilizing the reducing capabilities of Lactobacillus acidophilus, silver nanoparticles (AgNPs) are synthesized. The anti-cancer properties of AgNPs have been demonstrated in previous studies against several cancer cell lines; it has been hypothesized that these compounds might inhibit AMPK/mTOR signalling and BCL-2 expression. Consequently, the current research used both in vitro and in silico approaches to study whether Lactobacillus acidophilus AgNPs could inhibit cell proliferation autophagy and promote apoptosis in HepG2 cells. The isolated strain was identified as Lactobacillus acidophilus strain RBIM based on 16 s rRNA gene analysis. Based on our research findings, it has been observed that this particular strain can generate increased quantities of AgNPs when subjected to optimal growing conditions. The presence of silanols, carboxylates, phosphonates, and siloxanes on the surface of AgNPs was confirmed using FTIR analysis. AgNPs were configured using UV–visible spectroscopy at 425 nm. In contrast, it was observed that apoptotic cells exhibited orange-coloured bodies due to cellular shrinkage and blebbing initiated by AgNP treatment, compared to non-apoptotic cells. It is worth mentioning that AgNPs exhibited remarkable selectivity in inducing cell death, specifically in HepG2 cells, unlike normal WI-38 cells. The half-maximum inhibitory concentration (IC50) values for HepG2 and WI-38 cells were 4.217 µg/ml and 154.1 µg/ml, respectively. AgNPs induce an upregulation in the synthesis of inflammation-associated cytokines, including (TNF-α and IL-33), within HepG2 cells. AgNPs co-treatment led to higher glutathione levels and activating pro-autophagic genes such as AMPK.Additionally, it resulted in the suppression of mTOR, MMP-9, BCL-2, and α-SMA gene expression. The docking experiments suggest that the binding of AgNPs to the active site of the AMPK enzyme leads to inhibiting its activity. The inhibition of AMPK ultimately results in the suppression of the mechanistic mTOR and triggers apoptosis in HepG2 cells. In conclusion, the results of our study indicate that the utilization of AgNPs may represent a viable strategy for the eradication of liver cancerous cells through the activation of apoptosis and the enhancement of immune system reactions.