bluuebunny/crossref_metadata_2025 huggingface dataset:
Geniposide modulates GSK3β to inhibit Th17 differentiation and mitigate endothelial damage in intracranial aneurysm
Authors: Zhang Qian , Shi Lu‐Feng , Chen Run‐Dong , Zhao He‐He , Yu Cong , Wang Yi‐Rong , Lu Peng
Published: August 2024

Intracranial aneurysm (IA) is a common cerebrovascular disease. Immune system disorders and endothelial dysfunction are essential mechanisms of its pathogenesis. This study aims to explore the therapeutic effect and mechanism of Geniposide (Gen) on IA, which has a protective impact on endothelial cells and cardiovascular and cerebrovascular diseases. IA mouse models were administered intraperitoneal injections of geniposide for 2 weeks following elastase injection into the right basal ganglia of the brain for intervention. The efficacy of Gen in treating IA was evaluated through pathological testing and transcriptome sequencing analysis of Willis ring vascular tissue. The primary mechanism of action was linked to the expression of GSK3β in Th17 cells. The percentage of splenic Th17 cell differentiation in IA mice was significantly inhibited by Gen. GSK3β/STAT3, and other pathway protein expression levels were also significantly inhibited by Gen. Additionally, TNF‐α and IL‐23 cytokine contents were significantly downregulated after Gen treatment. These results indicated that Gen significantly inhibited the percentage of Th17 cell differentiation, an effect that was reversed upon overexpression of the GSK3B gene. Furthermore, Gen‐treated, Th17 differentiation‐inducing cell‐conditioned medium significantly up‐regulated the expression of tight junction proteins ZO‐1, Occludin, and Claudin‐5 in murine aortic endothelial cells. Administering the GSK3β inhibitor Tideglusib to IA mice alleviated the severity of IA disease pathology and up‐regulated aortic tight junction protein expression. In conclusion, Gen inhibits Th17 cell differentiation through GSK3β, which reduces endothelial cell injury and up‐regulates tight junction protein expression.
Machine learning methods for compound annotation in non‐targeted mass spectrometry—A brief overview of fingerprinting, in silico fragmentation and de novo methods
Authors: Russo Francesco F. , Nowatzky Yannek , Jaeger Carsten , Parr Maria K. , Benner Phillipp , Muth Thilo , Lisec Jan
Published: August 2024

Non‐targeted screenings (NTS) are essential tools in different fields, such as forensics, health and environmental sciences. NTSs often employ mass spectrometry (MS) methods due to their high throughput and sensitivity in comparison to, for example, nuclear magnetic resonance–based methods. As the identification of mass spectral signals, called annotation, is labour intensive, it has been used for developing supporting tools based on machine learning (ML). However, both the diversity of mass spectral signals and the sheer quantity of different ML tools developed for compound annotation present a challenge for researchers in maintaining a comprehensive overview of the field.

In this work, we illustrate which ML‐based methods are available for compound annotation in non‐targeted MS experiments and provide a nuanced comparison of the ML models used in MS data analysis, unravelling their unique features and performance metrics. Through this overview we support researchers to judiciously apply these tools in their daily research. This review also offers a detailed exploration of methods and datasets to show gaps in current methods, and promising target areas, offering a starting point for developers intending to improve existing methodologies.
Online LC‐Orbitrap MS method for the rapid molecular characterization of dissolved organic matter
Authors: Li Yuguo , He Chen , Zhang Yahe , Shi Quan
Published: August 2024

Rationale

High‐resolution mass spectrometry (HRMS) combined with electrospray ionization (ESI) has been the most useful technique for molecular characterization of dissolved organic matter (DOM) derived from diverse sources. However, the comprehensive detection of DOM composition was hindered by ionization suppression observed in ESI sources. HRMS coupled with liquid chromatography (LC) is a potential tool for comprehensive molecular characterization of DOM.

Methods

The Suwannee River fulvic acids (SRFAs) and two DOM samples from seawater and refinery wastewater extracted by solid phase extraction (SPE) were analyzed by LC‐Orbitrap MS coupled with ESI. The mobile phases, solvent composition, and gradient in the LC‐Orbitrap MS analysis were optimized.

Results

The number of detected molecular formulae of SRFAs by online LC‐Orbitrap MS was significantly increased by approximately 40% compared to direct injection. These additional detected compounds are mainly protein and lignin‐like compounds, with a low O/C ratio and high H/C ratio. For the SRFAs, the relative standard deviations (%) of reproducibility are 5.51, 2.33, 7.97, and 1.80 for average O/C, H/C, double bond equivalent, and modified aromaticity index, respectively.

Conclusions

This study proposed a simple and rapid method based on LC‐Orbitrap MS for an in‐depth analysis of the molecular composition of DOM, achieving a remarkable analysis time of only 5 min per sample. The rapid method provides a dependable and efficient approach for the molecular characterization of DOM, thereby advancing our comprehension and investigation of DOM across diverse ecosystems.
Consider diverse perspectives for improving affordability of on‐campus student housing
Authors: McCarthy Claudine
Published: August 2024

PHILADELPHIA — Housing affordability, or lack thereof, is increasingly impacting college students’ ability to succeed and complete their degree, according to Ryan Jensen, AICP, Project Manager with Brailsford & Dunlavey, a program management firm. He spoke on a panel of student housing experts with diverse perspectives at the Society for College and University Planning's annual conference.
Implement practical strategies to establish a reputation as a responsible leader
Authors: Cain Butler
Published: August 2024

Establishing a reputation as a responsible leader within higher education takes time, effort, and consideration.
Did court dismiss student's due process claim?
Authors: Lyerly Eric
Published: August 2024

John Doe, a medical student at Indiana University–Purdue University Indianapolis, had a romantic relationship with fellow student Jane Roe. Roe later accused him of physical abuse. The misconduct took place off campus.
Leading from reactive whirlwind to integrated strategy
Authors: McCarthy Claudine
Published: August 2024

PHILADELPHIA — In the midst of all the change and challenges facing higher education, it's common for student affairs professionals to feel like they’re running from the most urgent pressing task to the next, leaving little time to intentionally focus on strategizing for the future. It's a conundrum all‐too‐familiar to Lynn Akey, Ph.D., Chancellor at the University of Wisconsin Parkside. But she's found a better way, which she discussed in her presentation at the Society for College and University Planning's annual conference.
Squeezing Out Nanoparticles from Perovskites: Controlling Exsolution with Pressure
Authors: López‐García Andrés , Remiro‐Buenamañana Sonia , Neagu Dragos , Carrillo Alfonso J. , Serra José Manuel
Published: August 2024

Nanoparticle exsolution has emerged as a versatile method to functionalize oxides with robust metallic nanoparticles for catalytic and energy applications. By modifying certain external parameters during thermal reduction (temperature, time, reducing gas), some morphological and/or compositional properties of the exsolved nanoparticles can be tuned. Here, it is shown how the application of high pressure (<100 bar H2) enables the control of the exsolution of ternary FeCoNi alloyed nanoparticles from a double perovskite. H2 pressure affects the lattice expansion and the nanoparticle characteristics (size, population, and composition). The composition of the alloyed nanoparticles could be controlled, showing a reversal of the expected thermodynamic trend at 10 and 50 bar, where Fe becomes the main component instead of Ni. In addition, pressure drastically lowers the exsolution temperature to 300 °C, resulting in unprecedented highly‐dispersed and small‐sized nanoparticles with a similar composition to those obtained at 600 °C and 10 bar. The mechanisms behind the effects of pressure on exsolution are discussed, involving kinetic, surface thermodynamics, and lattice‐strain factors. A volcano‐like trend of the exsolution extent suggests that competing pressure‐dependent mechanisms govern the process. Pressure emerges as a new design tool for metallic nanoparticle exsolution enabling novel nanocatalysts and surface‐functionalized materials.
Ultralow Power, Cleft Size‐Adjustable and pH‐Sensitive Hyaluronic Acid (HA) Biodevices for Acid‐Sensing Ion Channels Emulation
Authors: Duan Xinqing , Li Lei , Peng Zehui , Wang Mingqiang , Liu Yanxin , Hsieh Dar‐Jen , Chang Kuan‐Chang
Published: August 2024

The burgeoning implantable biodevices have unlocked new frontiers in healthcare, promising personalized monitoring strategies tailored to specific needs. Herein, hyaluronic acid (HA) is harnessed to create fully biocompatible, acidity‐sensitivity and cleft‐adjustable neuromorphic devices. These HA‐biodevices exhibit remarkable sensitivity to pH variations, effectively mimicking biological acid‐sensing ion channels (ASICs) through protonation reactions between electronegative atoms and hydrogen ions, even at ultralow driving voltage (5 mV). They can monitor joint cartilage acidity by tracking changes in proton concentration and successfully diagnose the onset of arthritis. Furthermore, by adjusting the synaptic device's cleft distance, which determines responsiveness, power efficiency and plasticity, HA‐based neuromorphic devices can be tailored to meet the unique demands of various implantation sites, providing both high‐sensitivity and low‐heat dissipation, thus broadening their application scopes. Moreover, the HA‐biodevices maintain stable performance across various bending degrees, up to a curvature radius of 7.5 mm, with flexibility and deformation resilience enabling installation on joints of varying curvatures. The combination of all‐biocompatibility, high sensitivity, low heat dissipation, ultralow low power (2 pW), and extraordinary deformation tolerance paves the way for the development of versatile, multipurpose medical monitoring devices with immense potential in the field of healthcare.
Robust Sequence Design Space for the Isothermal Exponential Amplification of Short Oligonucleotides
Authors: Ang Yan Shan , Yung Lin‐Yue Lanry
Published: August 2024

Advances in isothermal amplification techniques have accelerated development in biosensing applications and the design of complex molecular devices. The exponential amplification reaction technique, or EXPAR, is uniquely positioned to process molecular information from short oligonucleotide strands (≈10 nucleotides length) typically encountered in molecular computing or microRNA detection. Despite its conceptual simplicity (requiring only a template strand and two enzymes), the issue of nonspecific background amplification has hindered broader adoption. In this work, a new system configuration is established at 37 °C to achieve significantly improved performance. Critical sequence motifs responsible for the excellent signal‐to‐background profile are identified and generalized as a universal adapter design framework. Orthogonal template sequences generated from the framework are implemented for a triplex reaction and successfully evaluated mixtures of multiple‐target inputs in a single‐step, one‐pot format without the need for exogenous agents.
Water‐Etched Porous Ti: Surface Manipulation of Ti Foam Fabricated by Liquid Metal Dealloying Technique
Authors: Yoon Kook Noh , Kato Hidemi , Park Eun Soo
Published: August 2024

The liquid metal dealloying (LMD) process enables the fabrication of porous metals with various chemical compositions. Despite its advantages, LMD still faces key challenges such as maintaining the high‐temperature molten metal bath for a prolonged time, avoiding the use of toxic etchants, and so on. To overcome these challenges, the study develops a water‐leachable and oxidation‐resistant alloy melt (AM) in Ca‐Mg binary system. Specifically, Ca72Mg28 eutectic AM is designed, which exhibits higher oxidation resistance and lower melting temperature compared to pure Mg, allowing LMD to be conducted in atmospheric conditions as well as temperatures >200 K lower. The AM also enables an innovative process to fabricate Ti foams with a hexagonal faceted surface structure by carefully manipulating the etching rate during the water etching process. This approach allows for the creation of foam with a surface area over 13% larger than that of foams with smooth surfaces via normal acid etching, potentially enhancing efficiency in applications such as electrodes for electrochemical systems or biomedical materials where increased cell adhesion can be beneficial. This study paves the way for efficiently manipulating the LMD process to fabricate metal foams with customized compositions and enhanced surface properties.
Guided and unguided approaches for quantum key distribution for secure quantum communication
Authors: Sihare Shyam R.
Published: August 2024

This research investigates the optimization of quantum key distribution for secure quantum communication. The paper conducts a systematic analysis of quantum error rates, transmission time, error correction rates, and the correlation between distance, time, and noise in quantum communication systems. The results reveal an inverse relationship between transmission time and distance, and demonstrate that quantum error rates are dependent on quantum noise. The research presents improved formulations for calculating the probability of success in quantum systems, taking into account the dynamic nature of success in quantum communication processes. The findings have significant implications for optimizing quantum communication channels and providing insights into strategies for enhancing reliability and mitigating errors. The article presents a new approach to classical cryptography that incorporates dynamic vulnerability scores that adapt to advancements in quantum computing. It addresses various challenges in quantum communication, such as signal strength, channel losses, regeneration criteria, and the placement of quantum repeaters. Additionally, the research introduces multi‐dimensional metrics for evaluating risks in quantum communication cybersecurity, laying the groundwork for future advancements. This paper improves understanding of quantum communication, cryptography, and cybersecurity, providing a strong foundation for future research and practical applications.
Optimization methods in water system operation
Authors: Becker Bernhard Peter Josef , Jagtenberg Caroline Jeanne , Horváth Klaudia , Mitchell Ailbhe , Rodríguez‐Sarasty Jesús Andrés
Published: August 2024

Operational water management is a critical global challenge, and decision making can be improved by using mathematical optimization. This paper provides an overview of optimization techniques, both exact and heuristic, used in water management. It focuses on the use of optimization techniques in the short term: operational planning in reservoir management, control of open channels, hydropower scheduling, and operation of polder drainage pumps. Principles of model predictive control, methods for optimization under forecast uncertainty, and approaches for conflict resolution are explained with the help of educational examples and practical cases. Challenges and research questions to be addressed in the future are presented as an outlook.

This article is categorized under:

Engineering Water > Methods

Science of Water > Water and Environmental Change

Water and Life > Conservation, Management, and Awareness
Confining strings in three-dimensional gauge theories beyond the Nambu-Gotō approximation
Authors: Caselle Michele , Magnoli Nicodemo , Nada Alessandro , Panero Marco , Panfalone Dario , Verzichelli Lorenzo
Published: August 2024

Abstract

We carry out a systematic study of the effective bosonic string describing confining flux tubes in SU(N) Yang-Mills theories in three spacetime dimensions. While their low-energy properties are known to be universal and are described well by the Nambu-Gotō action, a non-trivial dependence on the gauge group is encoded in a series of undetermined subleading corrections in an expansion around the limit of an arbitrarily long string. We quantify the first two of these corrections by means of high-precision Monte Carlo simulations of Polyakov-loop correlators in the lattice regularization. We compare the results of novel lattice simulations for theories with N = 3 and 6 color charges, and report an improved estimate for the N = 2 case, discussing the approach to the large-N limit. Our results are compatible with analytical bounds derived from the S-matrix bootstrap approach. In addition, we also present a new test of the Svetitsky-Yaffe conjecture for the SU(3) theory in three dimensions, finding that the lattice results for the Polyakov-loop correlation function are in excellent agreement with the predictions of the Svetitsky-Yaffe mapping, which are worked out quantitatively applying conformal perturbation theory to the three-state Potts model in two dimensions. The implications of these results are discussed.
A simple extension of Timoshenko beam model to describe dissipation in cementitious elements
Authors: Aretusi Giuliano , Cardillo Christian , Salvatori Antonello , Bednarczyk Ewa , Fedele Roberto
Published: August 2024

In this paper, an extension of the Timoshenko model for plane beams is outlined, with the aim of describing, under the assumption of small displacements and strains, a class of dissipative mechanisms observed in cementitious materials. In the spirit of micromorphic continua, the modified beam model includes a novel kinematic descriptor, conceived as an average sliding relevant to a density of micro-cracks not varying along time. For the pairs of rough surfaces, in which such a distribution of micro-cracks is articulated, both an elastic deformation and a frictional dissipation are considered, similarly to what occurs for the fingers of the joints having a tooth saw profile. The system of governing differential equations, of the second order, is provided by a variational approach, endowed by standard boundary conditions. To this purpose, a generalized version of the principle of virtual work is used, in the spirit of Hamilton–Rayleigh approach, including as contributions: (i) the variation of the inner elastic energy, generated by the linear elasticity of the sound material and, in a nonlinear way, by the mutual, reversible deformation of the asperities inside the micro-cracks; (ii) the virtual work of the external actions consistent with the beam model, i.e., the distributed transversal forces and the moments per unit lengths; besides these two contributions, constituting the conservative part of the system, (iii) the dissipation due to friction specified through a smooth Rayleigh potential, entering a nonlinear dependence of viscous and Coulomb type on the sliding rate. Through a COMSOL Multiphysics"Equation missing" implementation, 1D finite element analyses are carried out to simulate structural elements subjected to three- and four-point bending tests with alternating loading cycles. The dissipation of energy is investigated at varying the model parameters, and the predictions turn out to be in agreement with preliminary data from an experimental campaign. The present approach is expected to provide a valuable tool for the quantitative and comparative assessment of the hysteresis cycles, favoring the robust design of cementitious materials.
The pressure-wired Stokes element: a mesh-robust version of the Scott–Vogelius element
Authors: Gräßle Benedikt , Bohne Nis-Erik , Sauter Stefan
Published: August 2024

The Scott–Vogelius finite element pair for the numerical discretization of the stationary Stokes equation in 2D is a popular element which is based on a continuous velocity approximation of polynomial order k and a discontinuous pressure approximation of order $$k-1$$

k
-
1

. It employs a “singular distance” (measured by some geometric mesh quantity $$ \Theta \left( \textbf{z}\right) \ge 0$$

Θ

z

≥
0

for triangle vertices $$\textbf{z}$$
z
) and imposes a local side condition on the pressure space associated to vertices $$\textbf{z}$$
z
with $$\Theta \left( \textbf{z}\right) =0$$

Θ

z

=
0

. The method is inf-sup stable for any fixed regular triangulation and $$k\ge 4$$

k
≥
4

. However, the inf-sup constant deteriorates if the triangulation contains nearly singular vertices $$0<\Theta \left( \textbf{z}\right) \ll 1$$

0
<
Θ

z

≪
1

. In this paper, we introduce a very simple parameter-dependent modification of the Scott–Vogelius element with a mesh-robust inf-sup constant. To this end, we provide sharp two-sided bounds for the inf-sup constant with an optimal dependence on the “singular distance”. We characterise the critical pressures to guarantee that the effect on the divergence-free condition for the discrete velocity is negligibly small, for which we provide numerical evidence.
Navigating the maze of mass spectra: a machine-learning guide to identifying diagnostic ions in O-glycan analysis
Authors: Urban James , Joeres Roman , Thomès Luc , Thomsson Kristina A. , Bojar Daniel
Published: August 2024

Structural details of oligosaccharides, or glycans, often carry biological relevance, which is why they are typically elucidated using tandem mass spectrometry. Common approaches to distinguish isomers rely on diagnostic glycan fragments for annotating topologies or linkages. Diagnostic fragments are often only known informally among practitioners or stem from individual studies, with unclear validity or generalizability, causing annotation heterogeneity and hampering new analysts. Drawing on a curated set of 237,000 O-glycomics spectra, we here present a rule-based machine learning workflow to uncover quantifiably valid and generalizable diagnostic fragments. This results in fragmentation rules to robustly distinguish common O-glycan isomers for reduced glycans in negative ion mode. We envision this resource to improve glycan annotation accuracy and concomitantly make annotations more transparent and homogeneous across analysts.

Graphical Abstract
Semiclassical Quantization Conditions in Strained Moiré Lattices
Authors: Becker Simon , Wittsten Jens
Published: August 2024

In this article we generalize the Bohr–Sommerfeld rule for scalar symbols at a potential well to matrix-valued symbols having eigenvalues that may coalesce precisely at the bottom of the well. As an application, we study the existence of approximately flat bands in moiré heterostructures such as strained two-dimensional honeycomb lattices in a model recently introduced by Timmel and Mele.
Certolizumab-induced sarcoidosis in a patient with psoriatic arthritis – a case report and review of literature
Authors: Biernikowicz Małgorzata , Pilch Weronika , Wojturska Wiktoria , Korkosz Mariusz , Nowakowski Jarosław
Published: August 2024

Tumour necrosis factor-α (TNF- α) antagonists are considered a significant therapeutic option in the treatment of sarcoidosis. Nevertheless, their use can also paradoxically result in sarcoidosis-like reactions. Here, we present a case of a 56-year-old patient with psoriatic arthritis who after 3 months of certolizumab therapy developed pulmonary sarcoidosis. Therefore, certolizumab was discontinued and prednisone initiated. Subsequently, 4 months later a complete remission of interstitial lesions was observed. Due to insufficient control of psoriatic arthritis, upadacitinib and methotrexate were prescribed and despite initial improvement, a couple of months later a massive exacerbation of skin psoriasis occurred and the treatment was switched to secukinumab. As of today, no evidence of sarcoidosis recurrence has been noted. Drug-induced sarcoidosis-like reactions (DISR) appear to be less frequently associated with certolizumab rather than with other anti-TNF-α agents. However, specific mechanisms of this phenomenon remain unclear and require future investigation.
Towards inclusive collaboration in volcanology: guidelines for best-engagement protocols in international collaboration
Authors: IAVCEI-INVOLC International Network
Published: August 2024

The International Network for Volcanology Collaboration (INVOLC) is a network formalised by the International Association of Volcanology and Chemistry of the Earth’s Interior (IAVCEI) with the specific ambition to enhance volcanology globally through improved international collaboration. IAVCEI-INVOLC was created with a focus on volcano scientists working in resource-constrained contexts, including those based in low- or middle-income countries. After a community-wide online survey and inaugural workshop during which INVOLC’s ambitions were discussed, a series of challenges, as commonly experienced by those working in resource-constrained settings, were identified. These challenges may present barriers to participation in volcano science in an international context and are related to both organisational resources (financial, human, technical) and inclusion in research collaborations. In this perspectives paper, we present a series of 15 guidelines for best-engagement protocols in international collaboration in volcanology that may be adopted during times of quiescence, volcanic unrest and/or an eruption and its aftermath. Our aspiration is that these guidelines will help build more respectful, equitable and sustainable partnerships that will ultimately advance the science of volcanology.
Emotional text messages affect the early processing of emoticons depending on their emotional congruence: evidence from the N170 and EPN event related potentials
Authors: Aldunate Nerea , López Vladimir , Rojas-Thomas Felipe , Villena-González Mario , Palacios Ismael , Artigas Claudio , Rodríguez Eugenio , Bosman Conrado A.
Published: August 2024

Emoticons have been considered pragmatic cues that enhance emotional expressivity during computer-mediated communication. Yet, it is unclear how emoticons are processed in ambiguous text-based communication due to incongruences between the emoticon's emotional valence and its context. In this study, we investigated the electrophysiological correlates of contextual influence on the early emotional processing of emoticons, during an emotional congruence judgment task. Participants were instructed to judge the congruence between a text message expressing an emotional situation (positive or negative), and a subsequent emoticon expressing positive or negative emotions. We analyzed early event-related potentials elicited by emoticons related to face processing (N170) and emotional salience in visual perception processing (Early Posterior Negativity, EPN). Our results show that accuracy and Reaction Times depend on the interaction between the emotional valence of the context and the emoticon. Negative emoticons elicited a larger N170, suggesting that the emotional information of the emoticon is integrated at the early stages of the perceptual process. During emoticon processing, a valence effect was observed with enhanced EPN amplitudes in occipital areas for emoticons representing negative valences. Moreover, we observed a congruence effect in parieto-temporal sites within the same time-window, with larger amplitudes for the congruent condition. We conclude that, similar to face processing, emoticons are processed differently according to their emotional content and the context in which they are embedded. A congruent context might enhance the emotional salience of the emoticon (and therefore, its emotional expression) during the early stages of their processing.
Validation of the cutoff values for the number of metastatic lymph nodes for esophageal cancer staging: a multi-institutional analysis of 655 patients in Japan
Authors: Tanaka Koji , Fujita Takeo , Nakajima Yasuaki , Okamura Akihiko , Kawada Kenro , Watanabe Masayuki , Doki Yuichiro
Published: August 2024

Background

The number of metastatic lymph nodes (LNs) is an important prognostic factor for esophageal cancer, and N staging is important for prognostic stratification. The optimal cutoff values for clinical (cN) and pathologic N (pN) staging should be reconsidered following advances in neoadjuvant therapy.

Methods

The study included 655 patients who underwent esophagectomy between January 2014 and December 2016 in four high-volume centers in Japan. Optimal cutoff values for the number of metastatic LNs in cN and pN staging were examined using X-tile, and their prognostic performance was validated using the Kaplan–Meier method.

Results

The cutoff values were 1, 2, and 3 for cN staging and 1, 3, and 7 for pN staging. Prognosis was significantly better in patients with cN0 than in those with modified (m)-cN1 (p = 0.0211). However, prognosis was not significantly different among the patients with m-cN1, m-cN2, and m-cN3 disease. Prognosis was significantly different among the patients with pN0, pN1, pN2, and pN3 disease (pN0 vs pN1, p < 0.0001; pN1 vs pN2, p < 0.0001; pN2 vs pN3, p < 0.0001). In patients who received preoperative neoadjuvant therapy, prognosis, which was not significantly different among the patients with cN0, m-cN1, m-cN2, and m-cN3 disease (cN0 vs m-cN1, p = 0.5675; m-cN1 vs m-cN2, p = 0.4425; m-cN2 vs m-cN3, p = 0.7111), was significantly different among the patients with pN0, pN1, pN2, and pN3 disease (pN0 vs pN1, p = 0.0025; pN1 vs pN2, p = 0.0046; pN2 vs pN3, p = 0.0104).

Conclusions

cN has no prognostic impact in patients who underwent preoperative treatment followed by esophagectomy, despite the optimization of cN classification. The conventional TNM8th pN classification is useful for predicting prognosis even for patients who have undergone preoperative treatment. The conventional cutoffs for metastatic LNs in the International Union against Cancer tumor node metastasis staging system are valid and can be effectively used in clinical practice.
The horror of corporate harms: purdue pharma and the opioid epidemic
Authors: Crofts Penny , van Rijswijk Honni
Published: August 2024

There has been a great deal written about Purdue and the opioid epidemic in multiple disciplines, including dismay about the failure of the criminal legal system to adequately conceptualize and respond to Purdue’s responsibility for causing the epidemic. Rather than lingering on the failure of the criminal legal system, we read Purdue’s responsibility as and through horror. The harms caused by Purdue do not fit into criminal legal categories as they are currently written and, instead, are more analogous to harms portrayed in the horror genre. Moreover, Purdue could achieve these harms only through the failure and betrayal of people and institutions of authority, a classic trope of the horror genre. We develop a concept of routine horror to explore the ways in which corporate harms are inflicted through everyday practices and products, enabled by routine systems of regulations and laws. On this account, the routines enable the harms and are harmful in and of themselves, leaving us with no one to trust and no place to turn. In the absence of effective law, we remain stuck in a horror story.
Punjabi “housewives” in central Italy: navigating patriarchy, labor exploitation, and welfare exclusion
Authors: Laudini Annamaria
Published: August 2024

Who benefits from the exploitation of women’s work, and how? Marxist feminists in the 1970s–1980s and recently theorists of Social Reproduction argued that women’s work is exploited twice, or “super-exploited,” by capital and patriarchy. Such “super-exploitation” is sustained by the process of “housewifization,” which legitimizes the extraction and accumulation of surplus value from the social reproductive work of women. The housewife ideology not only mystifies social reproductive work as natural — thereby legitimizing it as free — but also frames women’s productive work as marginal — thereby legitimizing it as cheaper and more precarious. Building on Maria Mies’ (1981) famous study of women lacemakers in India, where the devaluation of women’s work is shown to serve both capital and patriarchy, I analyze the experiences of Punjabi “housewives” in central Italy, exploring them through the lens of one family and specifically its youngest and eldest daughters, whom I interviewed during ethnographic fieldwork. I show how, despite the essential role played by these women in their family mobility project, the housewife ideology — together with other patriarchal constructs of honor and caste endogamy — obscures the value of their social reproductive and productive work and imposes a number of restrictions on their freedom. I find, further, that their super-exploitation is aggravated in the context of migration: the labor exploitation and welfare exclusion that they face in Italy due to the country’s exclusionary immigration regime and unregulated capitalist market complicate their chances to challenge the oppressive relations they are involved in.
Tip-of-the-Tongue Experiences as Cognitive Phenomenology
Authors: Medeiros Darren
Published: August 2024

Whether metacognitive experiences should be considered evidence for or against cognitive phenomenology is controversial. In this paper I analyze one metacognitive experience, having a word at the tip of one’s tongue, and argue that this experience is an instance of cognitive phenomenology. I develop what I call a Cognitive view of tip-of-the-tongue (TOT) experience, supported by examining the prominent psychological explanation of tip-of-the-tongue states emerging from the science of language production, showing how psychological data suggests that the phenomenal character of tip-of-the-tongue experiences is constituted in part by conceptual representations, from which it follows that tip-of-the-tongue experiences are instances of cognitive phenomenology. This view contrasts with metacognitive embodied affect views of tip-of-the-tongue experiences, and I provide several clarifications and challenges that defenders of these views would have to address to situate their views within the cognitive phenomenology debate. Ultimately, I conclude that the Cognitive view of TOT is better supported by empirical data, and comports better with introspection, in comparison to embodied affect views.
Baby Logic – a Hinge Epistemology
Authors: Ohlhorst Jakob
Published: August 2024

Epistemologists have begun paying attention to the phenomenon of core cognition from developmental psychology. Core cognition posits innate automatic cognitive modules that enable children to quickly grasp and learn certain concepts. A key element of core cognition is sometimes named core knowledge because it encodes the constraints, parameters, and concepts that are required for core cognition modules to function. Until now, no successful epistemological account of it has been presented, and it is difficult to integrate into standard accounts of epistemology given that it is only implicitly believed, not accessible to explicit cognitive processing, and innate. In this paper I propose an account of the epistemology of core cognition, focussing on the epistemic status of this core knowledge. I argue that, rather than being knowledge, or some ordinary justified belief, it consists of Wittgensteinian hinge certainties. These are the implicit presupposition that we need for our epistemology to function. I illustrate the argument with the core cognition of causality. Finally, I propose that even though core knowledge consists of unjustified hinges, we are epistemically entitled to trust them to be accurate.
Aligning Digital Educational Policies with the New Realities of Schooling
Authors: Butler Deirdre , Leahy Margaret , Charania Amina , Gedara Peiris Meda , Keane Therese , Laferrière Thérèse , Nakamura Kohei , Ueda Hiroshi , Bocconi Stefania
Published: August 2024

To make sense of the changes provoked by the Covid-19 pandemic and its immediate aftermath, this paper critically examines digital education policy responses in the context of the ‘new realities’ faced by schooling. Based on seven case studies contributed by authors from Australia, India, Ireland, Italy, Japan, Canada, Sri Lanka, two key questions are addressed: (1) What are the ‘new realities’ of schooling post Covid-19? and (2) How have digital educational policies changed in response to the new realities of schooling? Findings highlight the complexity of the problem of aligning digital education policies at the macro level to the realities experienced at the meso and micro levels of schooling systems. The paper concludes with discussion of the need for, and challenges of, agile policy making at all levels (macro, meso and micro) that are necessary for schooling systems to meet the challenges and realities of a complex changing world.
The Health Status of Undocumented Immigrants from Asian Countries in the United States: A Scoping Review and Recommendations for Future Directions
Authors: Nayak Sameera S. , Cardone Amanda , Soberano Kina , Dhond Meghan
Published: August 2024

Immigrants from Asian countries are the fastest-growing undocumented population in the United States (U.S.), yet not much is known about their health. This scoping review identifies the nature and extent of scientific literature on the health of undocumented Asian immigrants in the U.S. We conducted a comprehensive search of six electronic databases in 2024. Inclusion criteria were empirical articles written in English, published in peer-reviewed scientific journals from 2010 to 2024, and focused on a health outcome or health-related issue involving undocumented Asian immigrants. Results are summarized narratively. We identified 13 peer-reviewed publications. Nine studies were quantitative, and four were qualitative. Eight studies were conducted in California; two studies used national secondary data sources. Studies were mixed in their research focus. They covered a range of health outcomes and issues, such as mental health (n = 4), health services and access (n = 2), contraceptive use (n = 1), COVID-19 (n = 2), and HIV (n = 1). Three studies measured self-rated health alongside other conditions, such as disability, health insurance coverage, chronic health conditions, and obesity. Scholarship on the health of undocumented Asian immigrants is a growing research area. Given the small number of studies identified, future research with larger diverse samples, more robust methodology, and greater topical variety are warranted to understand the health of this population better and reduce potential inequities.
Perspectives of Generative AI in Chemistry Education Within the TPACK Framework
Authors: Feldman-Maggor Yael , Blonder Ron , Alexandron Giora
Published: August 2024

Artificial intelligence (AI) has made remarkable strides in recent years, finding applications in various fields, including chemistry research and industry. Its integration into chemistry education has gained attention more recently, particularly with the advent of generative AI (GAI) tools. However, there is a need to understand how teachers’ knowledge can impact their ability to integrate these tools into their practice. This position paper emphasizes two central points. First, teachers technological pedagogical content knowledge (TPACK) is essential for more accurate and responsible use of GAI. Second, prompt engineering—the practice of delivering instructions to GAI tools—requires knowledge that falls partially under the technological dimension of TPACK but also includes AI-related competencies that do not fit into any aspect of the framework, for example, the awareness of GAI-related issues such as bias, discrimination, and hallucinations. These points are demonstrated using ChatGPT on three examples drawn from chemistry education. This position paper extends the discussion about the types of knowledge teachers need to apply GAI effectively, highlights the need to further develop theoretical frameworks for teachers’ knowledge in the age of GAI, and, to address that, suggests ways to extend existing frameworks such as TPACK with AI-related dimensions.
Wasserstein principal component analysis for circular measures
Authors: Beraha Mario , Pegoraro Matteo
Published: August 2024

We consider the 2-Wasserstein space of probability measures supported on the unit-circle, and propose a framework for Principal Component Analysis (PCA) for data living in such a space. We build on a detailed investigation of the optimal transportation problem for measures on the unit-circle which might be of independent interest. In particular, building on previously obtained results, we derive an expression for optimal transport maps in (almost) closed form and propose an alternative definition of the tangent space at an absolutely continuous probability measure, together with fundamental characterizations of the associated exponential and logarithmic maps. PCA is performed by mapping data on the tangent space at the Wasserstein barycentre, which we approximate via an iterative scheme, and for which we establish a sufficient a posteriori condition to assess its convergence. Our methodology is illustrated on several simulated scenarios and a real data analysis of measurements of optical nerve thickness.
Hybrid music recommendation with graph neural networks
Authors: Bevec Matej , Tkalčič Marko , Pesek Matevž
Published: August 2024

Modern music streaming services rely on recommender systems to help users navigate within their large collections. Collaborative filtering (CF) methods, that leverage past user–item interactions, have been most successful, but have various limitations, like performing poorly among sparsely connected items. Conversely, content-based models circumvent the data-sparsity issue by recommending based on item content alone, but have seen limited success. Recently, graph-based machine learning approaches have shown, in other domains, to be able to address the aforementioned issues. Graph neural networks (GNN) in particular promise to learn from both the complex relationships within a user interaction graph, as well as content to generate hybrid recommendations. Here, we propose a music recommender system using a state-of-the-art GNN, PinSage, and evaluate it on a novel Spotify dataset against traditional CF, graph-based CF and content-based methods on a related song prediction task, venturing beyond accuracy in our evaluation. Our experiments show that (i) our approach is among the top performers and stands out as the most well rounded compared to baselines, (ii) graph-based CF methods outperform matrix-based CF approaches, suggesting that user interaction data may be better represented as a graph and (iii) in our evaluation, CF methods do not exhibit a performance drop in the long tail, where the hybrid approach does not offer an advantage.
AROID: Improving Adversarial Robustness Through Online Instance-Wise Data Augmentation
Authors: Li Lin , Qiu Jianing , Spratling Michael
Published: August 2024

Deep neural networks are vulnerable to adversarial examples. Adversarial training (AT) is an effective defense against adversarial examples. However, AT is prone to overfitting which degrades robustness substantially. Recently, data augmentation (DA) was shown to be effective in mitigating robust overfitting if appropriately designed and optimized for AT. This work proposes a new method to automatically learn online, instance-wise, DA policies to improve robust generalization for AT. This is the first automated DA method specific for robustness. A novel policy learning objective, consisting of Vulnerability, Affinity and Diversity, is proposed and shown to be sufficiently effective and efficient to be practical for automatic DA generation during AT. Importantly, our method dramatically reduces the cost of policy search from the 5000 h of AutoAugment and the 412 h of IDBH to 9 h, making automated DA more practical to use for adversarial robustness. This allows our method to efficiently explore a large search space for a more effective DA policy and evolve the policy as training progresses. Empirically, our method is shown to outperform all competitive DA methods across various model architectures and datasets. Our DA policy reinforced vanilla AT to surpass several state-of-the-art AT methods regarding both accuracy and robustness. It can also be combined with those advanced AT methods to further boost robustness. Code and pre-trained models are available at: https://github.com/TreeLLi/AROID.
Non-thermal plasma-catalytic processes for CO2 conversion toward circular economy: fundamentals, current status, and future challenges
Authors: Mukhtar Ahmad , Saqib Sidra , Mohotti Dinithi , Ndeddy Aka Robinson , Hossain Mokter , Agyekum-Oduro Ekow , Wu Sarah
Published: August 2024

Practical and energy-efficient carbon dioxide (CO2) conversion to value-added and fuel-graded products and transitioning from fossil fuels are promising ways to cope with climate change and to enable the circular economy. The carbon circular economy aims to capture, utilize, and minimize CO2 emissions as much as possible. To cope with the thermodynamic stability and highly endothermic nature of CO2 conversion via conventional thermochemical process, the potential application of non-thermal plasma (NTP) with the catalyst, i.e., the hybrid plasma catalysis process to achieve the synergistic effects, in most cases, seems to promise alternatives under non-equilibrium conditions. This review focuses on the NTP fundamentals and comparison with conventional technologies. A critical review has been conducted on the CO2 reduction with water (H2O), methane (CH4) reduction with CO2 to syngas (CO + H2), CO2 dissociation to carbon monoxide (CO), CO2 hydrogenation, CO2 conversion to organic acids, and one-step CO2–CH4 reforming to the liquid chemicals. Finally, future challenges are discussed comprehensively, indicating that plasma catalysis has immense investigative areas.