bluuebunny/crossref_metadata_2025 huggingface dataset:
Willingness to wait outperforms delay discounting in predicting drinking severity
Authors: Miller Pazia , Kable Joseph W. , Lempert Karolina M.
Published: September 2024

Alcohol misuse ranks among the leading causes of preventable death worldwide. Therefore, discovering measures that can predict hazardous drinking is critical. The delay discounting paradigm—which assesses relative preference for immediate rewards over larger, later rewards—has frequently been used as a proxy for impulsive choice, but it does not capture how long someone is willing to wait for delayed rewards when the arrival time is uncertain. In contrast, a newer willingness‐to‐wait task measures how long someone is willing to wait for a delayed reward of uncertain timing before giving up. We hypothesized that performance in this willingness‐to‐wait task would be associated with drinking severity and that this task may even outperform delay discounting as a predictor of drinking severity. We pooled data from multiple studies of mostly college‐aged adult participants. Drinking severity was assessed with the Alcohol Use Disorders Identification Test. Willingness to wait under temporal uncertainty, but not delay discounting, was associated with severity of alcohol problems among participants who drank (n = 212). Individuals engaging in hazardous drinking were less willing to wait for rewards when delays were unknown than were individuals with low‐risk drinking habits. Thus, willingness to wait under temporal uncertainty may be an important predictor of problematic drinking.
Luxury value perceptions and consumer outcomes: A meta‐analysis
Authors: Akarsu Tugra , Shaikh Shayan , Maity Moutusi
Published: September 2024

Luxury value perception is a well‐researched, yet fragmented domain. Extant research reports several dimensions of luxury value perception, where different investigations identify varying dimensions and their impact on several consumer‐related outcomes. However, such findings are inconsistent across studies, which are carried out across various contexts using disparate samples. In this research, we use the Theory of Consumption Value and Economic Theory to provide a comprehensive understanding of the dimensions, outcomes, and moderators of luxury value perception. This investigation synthesizes extant literature through a meta‐analysis to explain the inconsistent findings and offer new insights. The meta‐analysis integrates findings from 64 papers that report 74 separate studies with 32,587 participants/consumers. The impact of the dimensions of luxury value perception (functional, social, emotional, conditional, epistemic, and economic) on consumer outcomes (affective, cognitive, and behavior), and the moderating effects of several moderators (industry type, culture, gender, and publication year) are conceptualized and examined through meta‐analytic techniques. Some relationships are under‐researched in literature and cannot be tested, which provides scope for future investigations. This research is valuable for theory as we offer novel insights and identify boundary conditions that advance theoretical understanding of the domain. Managers will benefit from this holistic understanding as they may apply the insights obtained to formulate nuanced marketing and branding strategies.
Monoubiquitinated H2B, a Main Chromatin Target of Formaldehyde, Is Important for S‐Phase Checkpoint Signaling and Genome Stability
Authors: Mishra Sasmita , Krawic Casey , Luczak Michal W. , Zhitkovich Anatoly
Published: September 2024

Formaldehyde (FA) is a human carcinogen with ubiquitous environmental exposures and significant endogenous formation. Genotoxic activity of FA stems from its reactivity with DNA‐NH2 groups. Histone lysines are another source of aldehyde‐reactive amino groups in chromatin, however, chromatin/histone damage responses to FA and their biological significance are poorly understood. We examined histone posttranslational modifications in FA‐treated human lung cells and found that the majority of the most prominent small lysine modifications associated with active or inactive chromatin were unchanged. FA moderately decreased H3K9 and H3K27 acetylation and H2A‐K119 monoubiquitination but caused surprisingly severe losses of H2B‐K120 monoubiquitination, especially in primary and stem‐like cells. H2Aub1 decreases reflected its slower ubiquitination linked to a lower ubiquitin availability due to K48‐polyubiquitination of FA‐damaged proteins. Depletion of H2Bub1 resulted from its rapid deubiquitination in part by ATXN7L3‐associated deubiquitinases and was independent on DNA damage signaling, indicating a direct chromatin damage response. Manipulations of H2Bub1 abundance showed that it was important for robust ATM and ATR signaling, efficient S‐phase checkpoint, and suppression of mitotic transmission of unreplicated DNA and formation of micronuclei. Our findings identified H2B deubiquitination as a major FA‐induced chromatin damage response that regulates S‐phase checkpoint signaling and genome stability.
Product integration techniques for fractional integro‐differential equations
Authors: Kumar Sunil , Yadav Poonam , Kumar Singh Vineet
Published: September 2024

This article presents an application of approximate product integration (API) to find the numerical solution of fractional order Volterra integro‐differential equation based on Caputo non‐integer derivative of order
, where
. Also, the idea is extended to a class of fractional order Volterra integro‐differential equation with a weakly singular kernel. For this purpose, two numerical schemes are established by utilizing the concept of the API method, and L1 and L1‐2 formulae. We applied L1 and L1‐2 discretization to approximate the Caputo non‐integer derivative. At the same time, Taylor's series expansion of an unknown function is taken into consideration when approximating the Volterra part in the considered mathematical model using the API method. Combination of API method with L1 and L1‐2 formula provided the order of convergence
and
for Scheme‐I and Scheme‐II, respectively. The derived techniques reduced the proposed model to a set of algebraic equations that can be resolved using well‐known numerical algorithms. Furthermore, the unconditional stability, convergence, and numerical stability of the formulated schemes have been rigorously investigated. Finally, we conducted some numerical experiments to validate our theoretical findings and guarantee the accuracy and efficiency of the recommended schemes. The comparison between the numerical outcomes obtained by proposed schemes and existing numerical techniques has also been provided through tables and graphs.
Comparative chemometric modeling of fresh and dry cannabis inflorescences using FT‐NIR spectroscopy: Quantification and classification insights
Authors: Birenboim Matan , Brikenstein Nimrod , Kenigsbuch David , Shimshoni Jakob A.
Published: September 2024

Introduction

Cannabis sativa L. inflorescences are rich in cannabinoids and terpenes. Traditional chemical analysis methods for cannabinoids and terpenes, such as liquid and gas chromatography (using UV or MS detectors), are expensive and time‐consuming.

Objectives

This study explores the use of Fourier transform near‐infrared (FT‐NIR) spectroscopy combined with chemometric approaches for classifying cannabis chemovars and predicting cannabinoid and terpene concentrations for the first time in freshly harvested (wet) cannabis inflorescence. The study also compares the performance of FT‐NIR spectroscopy on wet versus dry cannabis inflorescences.

Materials and methods

Spectral data from 187 samples across seven cannabis chemovars were analyzed using partial least squares‐discriminant analysis (PLS‐DA) and partial least squares‐regression (PLS‐R) models.

Results

The PLS‐DA models effectively classified chemovars and major classes using only two latent variables (LVs) with minimal overfitting risk, with sensitivity, specificity, and accuracy values approaching 1. Despite the high water content in wet cannabis inflorescence, the PLS‐R models demonstrated good to excellent predictive capabilities for nine cannabinoids and eight terpenes using FT‐NIR spectra for the first time, achieving cross‐validation and prediction R‐squared values greater than 0.7, ratio of performance to interquartile range (RPIQ) exceeding 2, and a RMSECV/RMSEC ratio below 1.24. However, the low‐cannabidiolic acid submodel and (−)‐Δ9‐trans‐tetrahydrocannabinol model showed poor predictive performance. Some cannabinoid and terpene prediction models in wet cannabis inflorescence exhibited lower predictive capabilities compared with previously published models for dry cannabis inflorescence.

Conclusions

These findings suggest that FT‐NIR spectroscopy can be a viable rapid on‐site analytical tool for growers during the inflorescence flowering stage.
Pandemic‐related stressors of school counselors: Implications for resilience and retention
Authors: Vera Elizabeth M. , Heineke Amy J.
Published: September 2024

This qualitative study examined 17 school counselors’ pandemic‐related experiences to identify demands, resources, and consequences to well‐being. Among the main demands were increases in student social‐emotional impairment, role confusion, and top‐down policy modifications that made it more challenging to do their jobs. The top resources were support from colleagues and individual limit‐setting. Consequences to well‐being were mixed, but exhaustion and recommitments to self‐care were the most frequently reported. Implications for retention of school counselors and training are discussed.
Multireflecting gas chromatography‐multireflecting time‐of‐flight mass spectrometer with high dynamic range
Authors: Vorobyev Aleksey V. , Khasin Yury I. , Makarov Vasily V. , Kirillov Sergey N. , Verenchikov Anatoly N.
Published: September 2024

Gas chromatography–mass spectrometry (GC–MS) is a cornerstone technique for analyses of volatile and semivolatile compounds, constantly evolving to meet new challenges. The adoption of time‐of‐flight mass spectrometers (TOFMS) has enhanced GC–MS with faster spectral acquisition and broader mass coverage, enabling rapid GC separations. Multireflecting TOFMS (MRT) further improves resolution compared to traditional single‐reflecting TOFMS, facilitating the detection of minor analytes within complex matrices. This paper presents a significant improvement in MRT sensitivity and dynamic range achieved through an ion beam compression within the ion guide and the use of a conventionally oriented orthogonal accelerator. Sensitivity is improved to 100 000 ion/pg at a resolution of R = 25,000, enabling the detection of low fg analyte quantities within 3 μg of matrix material into MS. The demonstrated linear dynamic range exceeding 6 orders of magnitude potentially enables even deeper exploration of complex mixtures with a bench top instrument.
Simulation‐Based Assessment of Fine Sediment Transport to Support River Restoration Measures
Authors: Pomázi Flóra , Baranya Sándor
Published: September 2024

A three‐dimensional coupled hydrodynamic and sediment transport model was employed to simulate the suspended sediment transport at a section of the Danube River, in Hungary. The case study is characterised by a highly complex hydromorphological system due to the nearby tributary inflow, the high number of river regulation structures as well as the several side‐arms connected to the Danube mainstem. The numerical model is set up, parameterised and validated against thorough field data of flow velocities and sediment concentrations measured at different hydrological regimes. Through the selected case study, the paper introduces (i) why 3D description is necessary at a reach‐scale analysis of complex hydromorphological systems; (ii) what sort of field data is needed to parameterise and validate a hydrodynamic and sediment transport model considering the spatial inhomogeneity of the flow and sediment features and (iii) an example for a quantitative impact assessment of side‐arm revitalisation measures on the sedimentation processes, playing a crucial role in the quality of riverine habitats.
Scenario Planning Management Actions to Restore Cold Water Stream Habitat: Comparing Mechanistic and Statistical Modeling Approaches
Authors: Fuller M. R. , Detenbeck N. E. , Leinenbach P. , Labiosa R. , Isaak D.
Published: September 2024

Under the United States Clean Water Act, states are required to periodically assess state waters to determine compliance with water quality criteria (including temperature) and then to develop total maximum daily loads (TMDLs) for impaired waters as necessary to bring them into compliance. We compared the performance of mechanistic stream temperature models (HeatSource, QUAL2K, and QUAL2Kw) applied to the mainstem of three TMDL watersheds (Middle Fork John Day, OR; Wind River, WA; South Fork Nooksack, WA) with that of spatial stream network (SSN) models applied to the full watersheds and used these to evaluate the potential effectiveness of restoration strategies. SSN models performed well with slightly lesser accuracy (RMSE = 0.47–0.87) for mainstem predictions than mechanistic models (RMSE = 0.4) but provided additional benefits to inform management, including information on spatial and temporal heterogeneity of restoration effectiveness throughout the watershed. Of the four scenarios considered (restoration of riparian zones to potential natural vegetation, channel narrowing, increasing flow by restricting irrigation withdrawals, and combined applications), riparian zone restoration was consistently the most effective in reducing temperatures at the outlet, mainstem, and throughout the watersheds. Predicted restoration effectiveness for thermal regimes varied significantly both within and among watersheds. A focus on water quality criteria exceedance only at the watershed outlet or along the mainstem reach can obscure knowledge of restoration potential for fish habitat in tributaries and headwaters, potential for creation of thermal refuge areas along the mainstem critical for maintaining migration corridors, and thermal regime heterogeneity across space and time.
Social‐ecological systems modeling for drought‐food security nexus
Authors: Roy Debashis , Gillespie Steven A. , Hossain Md Sarwar
Published: September 2024

Droughts pose severe threats to social systems, particularly to food security which is one of the priority targets in the UN's sustainable development goals (SDG 2). The drought‐food insecurity nexus entails the complex social‐ecological systems (SES) relationships (e.g., feedback) that underpin food insecurity, leading to disastrous consequence to society. To advance the knowledge on capturing the SES relationships of the drought‐food insecurity nexus, an SES model was employed (first attempt) to simulate these relationships to inform policies on food security in the context of climate change in Bangladesh. Different “what if” scenarios were examined determining the possible future trajectories of the system under socio‐economic and climate scenarios. Findings revealed that (i) with business‐as‐usual scenario, crop production and food security continue to increase at the expense of declining water resources over the simulation period; (ii) temperature changes (3.5–5.7°C) and surface water reduction due to dam and sustained groundwater decline may reduce food security (~55%); (iii) tipping risk increases due to severe reduction of food security when increasing temperature (>3.5°C) is combined with upstream water withdrawal (30%–50%), subsidy reduction (50%–100%), population growth and political instability. These indicate the need for an SES system perspective for increasing crop production and food security, simultaneously ensuring sustainable water resources and climate change adaptation. The model and findings are useful to achieve food security, and other related SDGs (1&6) in the context of climate change in Bangladesh and similar areas (e.g., Kenya), informed by the consequences of plausible alternative futures.
Illuminating the Devolution of Perovskite Passivation Layers
Authors: Giza Marcin , Kozikov Aleksey , Lalaguna Paula L. , Hutchinson Jake D. , Verma Vaibhav , Vella Benjamin , Kumar Rahul , Hill Nathan , Sirbu Dumitru , Arca Elisabetta , Healy Noel , Milot Rebecca L. , Kadodwala Malcolm , Docampo Pablo
Published: September 2024

Surface treatment of perovskite materials with their layered counterparts has become an ubiquitous strategy for maximizing device performance. While layered materials confer great benefits to the longevity and long‐term efficiency of the resulting device stack via passivation of defects and surface traps, numerous reports have previously demonstrated that these materials evolve under exposure to light and humidity, suggesting that they are not fully stable. Therefore, it is crucial to study the behavior of these materials in isolation and in conditions mimicking a device stack. Here, it is shown that perovskite capping layers templated by a range of cations on top of methylammonium lead iodide devolve in conditions commonly found during perovskite fabrication, such as exposure to light, solvent, and moisture. Photophysical, structural, and morphological studies are used to show that the degradation of these layered perovskites occurs via a self‐limiting, pinhole‐mediated mechanism. This results in the loss of whole perovskite sheets, from a few monolayers to tens of nanometers of material, until the system stabilizes again as demonstrated for exfoliated flakes of PEA2PbI4. This means that initially targeted structures may have devolved, with clear optimization implications for device fabrication.
“To prosper you must be willing to pivot”: The career construction journeys of language teacher educators in Hong Kong
Authors: Trent John
Published: September 2024

Considering the essential role of language teacher educators in shaping the views and practices of future generations of language teachers, the limited attention that has been given to how these educators construct their professional identities is surprising. This article reports the results of a qualitative study that contributes to addressing this gap in knowledge by exploring how three experienced language teacher educators construct their professional identities in Hong Kong. Drawing upon elements of career construction theory, the study used in‐depth interviews to investigate the responses of these educators to the complex and challenging demands they encounter in research, teaching, and institutional service throughout the pursuit of their professional identities construction goals. Results suggest that the three educators value career adaption and operationalize adaptability as the willingness to both constrain their concerns and accept the necessity for compromises and trade‐offs. Implications for leaders of higher education institutions concerned with supporting language teacher educators' identities construction are discussed. Suggestions for future research are also considered.
An equitable approach to leveraging multilingual paraprofessional learning
Authors: Pontier Ryan W. , del Pilar Delgado María , Medina Teresa J. , Peña Susanne , Chang Mido
Published: September 2024

This conceptual article focuses on how a National Professional Development grant through the Office of English Language Acquisition in the U.S. Department of Education supported multilingual paraprofessionals' equitable access to and participation in high‐quality, ongoing professional development aimed at supporting young multilingual learners, and how they leveraged both prior and newfound knowledge and experiences during their participation. We understood that paraprofessionals had been positioned as less white, less English‐speaking, and less knowledgeable than their teacher counterparts and knew that their engagement needed to be utilized as a resource. Thus, we broadly draw on the concept of equity but specifically on the notions of funds of knowledge, translanguaging, and raciolinguistics as we document our process of working with Pre‐K–second grade paraprofessionals.
Exploring genomic feature selection: A comparative analysis of GWAS and machine learning algorithms in a large‐scale soybean dataset
Authors: Al‐Mamun Hawlader A. , Danilevicz Monica F. , Marsh Jacob I. , Gondro Cedric , Edwards David
Published: September 2024

The surge in high‐throughput technologies has empowered the acquisition of vast genomic datasets, prompting the search for genetic markers and biomarkers relevant to complex traits. However, grappling with the inherent complexities of high dimensionality and sparsity within these datasets poses formidable hurdles. The immense number of features and their potential redundancy demand efficient strategies for extracting pertinent information and identifying significant markers. Feature selection is important in large genomic data as it helps in enhancing interpretability and computational efficiency. This study focuses on addressing these challenges through a comprehensive investigation into genomic feature selection methodologies, employing a rich soybean (Glycine max L. Merr.) dataset comprising 966 lines with over 5.5 million single nucleotide polymorphisms. Emphasizing the “small n large p” dilemma prevalent in contemporary genomic studies, we compared the efficacy of traditional genome‐wide association studies (GWAS) with two prominent machine learning tools, random forest and extreme gradient boosting, in pinpointing predictive features. Utilizing the expansive soybean dataset, we assessed the performance of these methodologies in selecting features that optimize predictive modeling for various phenotypes. By constructing predictive models based on the selected features, we ascertain the comparative prediction accuracies, thereby illuminating the strengths and limitations of these feature selection methodologies in the realm of genomic data analysis.
Stress and power as a response to harmonic excitation of a fractional anti‐Zener and Zener type viscoelastic body
Authors: Jelić Slađan , Zorica Dušan
Published: September 2024

The stress as a response to strain prescribed as a harmonic excitation is examined in both transient and steady state regime for the viscoelastic body modeled by thermodynamically consistent fractional anti‐Zener and Zener models by the use of the Laplace transform method. Assuming strain as a sine function, the time evolution of power per unit volume, previously derived as a sum of time derivative of a conserved term, which represents the rate of change of stored energy, and a dissipative term, which represents dissipated power, is investigated when expressed through the relaxation modulus and creep compliance. Further, two forms of energy and two forms of dissipated power per unit volume are examined in order to see whether they coincide.
Combining Classical and Probabilistic Independence Reasoning to Verify the Security of Oblivious Algorithms
Authors: Yan Pengbo , Murray Toby , Ohrimenko Olga , Pham Van-Thuan , Sison Robert
Published: September 2024

We consider the problem of how to verify the security of probabilistic oblivious algorithms formally and systematically. Unfortunately, prior program logics fail to support a number of complexities that feature in the semantics and invariants needed to verify the security of many practical probabilistic oblivious algorithms. We propose an approach based on reasoning over perfectly oblivious approximations, using a program logic that combines both classical Hoare logic reasoning and probabilistic independence reasoning to support all the needed features. We formalise and prove our new logic sound in Isabelle/HOL and apply our approach to formally verify the security of several challenging case studies beyond the reach of prior methods for proving obliviousness.
Getting Chip Card Payments Right
Authors: Basin David , Hofmeier Xenia , Sasse Ralf , Toro-Pozo Jorge
Published: September 2024

EMV is the international protocol standard for smart card payments and is used in billions of payment cards worldwide. Despite the standard’s advertised security, various issues have been previously uncovered, deriving from logical flaws that are hard to spot in EMV’s lengthy and complex specification. We have formalized various models of EMV in Tamarin, a symbolic model checker for cryptographic protocols. Tamarin was extremely effective in finding critical flaws, both known and new, and in many cases exploitable on actual cards. We report on these past problems as well as followup work where we verified the latest, improved version of the protocol, the EMV kernel C8. This work puts C8’s correctness on a firm, formal basis, and clarifies which guarantees hold for C8 and under which assumptions. Overall our work supports the thesis that cryptographic protocol model checkers like Tamarin have an essential role to play in improving the security of real-world payment protocols and that they are up to this challenge.
Bridging Dimensions: Confident Reachability for High-Dimensional Controllers
Authors: Geng Yuang , Baldauf Jake Brandon , Dutta Souradeep , Huang Chao , Ruchkin Ivan
Published: September 2024

Autonomous systems are increasingly implemented using end-to-end learning-based controllers. Such controllers make decisions that are executed on the real system, with images as one of the primary sensing modalities. Deep neural networks form a fundamental building block of such controllers. Unfortunately, the existing neural-network verification tools do not scale to inputs with thousands of dimensions—especially when the individual inputs (such as pixels) are devoid of clear physical meaning. This paper takes a step towards connecting exhaustive closed-loop verification with high-dimensional controllers. Our key insight is that the behavior of a high-dimensional vision-based controller can be approximated with several low-dimensional controllers. To balance the approximation accuracy and verifiability of our low-dimensional controllers, we leverage the latest verification-aware knowledge distillation. Then, we inflate low-dimensional reachability results with statistical approximation errors, yielding a high-confidence reachability guarantee for the high-dimensional controller. We investigate two inflation techniques—based on trajectories and control actions—both of which show convincing performance in three OpenAI gym benchmarks.
Formal Semantics and Analysis of Multitask PLC ST Programs with Preemption
Authors: Lee Jaeseo , Bae Kyungmin
Published: September 2024

Programmable logic controllers (PLCs) are widely used in industrial applications. Ensuring the correctness of PLC programs is important due to their safety-critical nature. Structured text (ST) is an imperative programming language for PLC. Despite recent advances in executable semantics of PLC ST, existing methods neglect complex multitasking and preemption features. This paper presents an executable semantics of PLC ST with preemptive multitasking. Formal analysis of multitasking programs experiences the state explosion problem. To mitigate this problem, this paper also proposes state space reduction techniques for model checking multitask PLC ST programs.
The Nonexistence of Unicorns and Many-Sorted Löwenheim–Skolem Theorems
Authors: Przybocki Benjamin , Toledo Guilherme , Zohar Yoni , Barrett Clark
Published: September 2024

Stable infiniteness, strong finite witnessability, and smoothness are model-theoretic properties relevant to theory combination in satisfiability modulo theories. Theories that are strongly finitely witnessable and smooth are called strongly polite and can be effectively combined with other theories. Toledo, Zohar, and Barrett conjectured that stably infinite and strongly finitely witnessable theories are smooth and therefore strongly polite. They called counterexamples to this conjecture unicorn theories, as their existence seemed unlikely. We prove that, indeed, unicorns do not exist. We also prove versions of the Löwenheim–Skolem theorem and the Łoś–Vaught test for many-sorted logic.
Integrating Loop Acceleration Into Bounded Model Checking
Authors: Frohn Florian , Giesl Jürgen
Published: September 2024

Bounded Model Checking (BMC) is a powerful technique for proving unsafety. However, finding deep counterexamples that require a large bound is challenging for BMC. On the other hand, acceleration techniques compute “shortcuts” that “compress” many execution steps into a single one. In this paper, we tightly integrate acceleration techniques into SMT-based bounded model checking. By adding suitable “shortcuts” on the fly, our approach can quickly detect deep counterexamples. Moreover, using so-called blocking clauses, our approach can prove safety of examples where BMC diverges. An empirical comparison with other state-of-the-art techniques shows that our approach is highly competitive for proving unsafety, and orthogonal to existing techniques for proving safety.
A Cross-Platform-Multi-user Virtual Training Environment for Waterproofing
Authors: Kaarlela Tero , Pitkäaho Tomi , Salo Sami
Published: September 2024

Virtual environments enable trainees to develop their skills in diverse tasks, independent of time and location. In the construction sector, virtual environments are primarily utilized for safety training, while there are fewer implemented applications for hands-on construction tasks. This publication presents a platform-independent virtual environment for waterproofing training to address the issue. The presented virtual environment is a cross-platform application enabling multi-user training experience. A pilot was organized to collect feedback on the usability of the implemented virtual waterproofing environment. Results of the user questionnaire are presented and discussed to evaluate the usability and provide insights into the challenges and benefits of virtual training environments for hands-on training in the construction sector. In conclusion, the results highlight the potential of the developed virtual environment for waterproofing training.
Almost classical de Sitter?
Authors: Horer Ludwig , Junghans Daniel
Published: September 2024

Abstract

The classical-dS scenario in the type II string theories proposes to search for dS vacua of orientifold flux compactifications in a regime where string corrections to the compactified effective field theory are negligible. We study a minimal extension of this scenario in which the leading string corrections to the O-plane/D-brane actions at the 4-derivative order are included but higher orders as well as string corrections in the bulk are self-consistently neglected. Our proposal is motivated by a recent debate about dS solutions with O8-planes which circumvent a classical no-go theorem due to unusual sources leading to so-called permissive boundary conditions for the 10D supergravity fields. We argue that such sources do not arise in classical supergravity but ask whether including the 4-derivative corrections leads to sources that have a similar effect. However, we find that the 4-derivative corrections do not allow meta-stable dS in a class of models with O8-planes and/or D8-branes we consider. We also study related models which in addition contain O6-planes/D6-branes and find that again no meta-stable dS is allowed, both classically and including the 4-derivative corrections. While some of the arguments in this work require the backreaction of the O-plane/D-brane sources to be small, others are valid including the full backreaction.
Neurobiological research on N,N-dimethyltryptamine (DMT) and its potentiation by monoamine oxidase (MAO) inhibition: from ayahuasca to synthetic combinations of DMT and MAO inhibitors
Authors: Egger Klemens , Aicher Helena D. , Cumming Paul , Scheidegger Milan
Published: September 2024

The potent hallucinogen N,N-dimethyltryptamine (DMT) has garnered significant interest in recent years due to its profound effects on consciousness and its therapeutic psychopotential. DMT is an integral (but not exclusive) psychoactive alkaloid in the Amazonian plant-based brew ayahuasca, in which admixture of several β-carboline monoamine oxidase A (MAO-A) inhibitors potentiate the activity of oral DMT, while possibly contributing in other respects to the complex psychopharmacology of ayahuasca. Irrespective of the route of administration, DMT alters perception, mood, and cognition, presumably through agonism at serotonin (5-HT) 1A/2A/2C receptors in brain, with additional actions at other receptor types possibly contributing to its overall psychoactive effects. Due to rapid first pass metabolism, DMT is nearly inactive orally, but co-administration with β-carbolines or synthetic MAO-A inhibitors (MAOIs) greatly increase its bioavailability and duration of action. The synergistic effects of DMT and MAOIs in ayahuasca or synthetic formulations may promote neuroplasticity, which presumably underlies their promising therapeutic efficacy in clinical trials for neuropsychiatric disorders, including depression, addiction, and post-traumatic stress disorder. Advances in neuroimaging techniques are elucidating the neural correlates of DMT-induced altered states of consciousness, revealing alterations in brain activity, functional connectivity, and network dynamics. In this comprehensive narrative review, we present a synthesis of current knowledge on the pharmacology and neuroscience of DMT, β-carbolines, and ayahuasca, which should inform future research aiming to harness their full therapeutic potential.
On the Monitoring of Small Islands Belonging to the Aeolian Archipelago by MT-InSAR Data
Authors: Polcari Marco , Palano Mimmo , Puliero Silvia , Silverii Francesca , Spinetti Claudia , Tolomei Cristiano
Published: September 2024

The aim of the present work is to evaluate the performance of several MT-InSAR techniques based on satellite SAR data in monitoring ground deformation phenomena affecting complex scenarios such as small islands of volcanic origin. To such purpose, PS, SBAS and IPTA approaches are applied in the study of Lipari, Salina and Vulcano islands belonging to the Aeolian archipelago, southern Tyrrhenian Sea, Italy. The outcomes retrieved from each technique are then discussed in terms of intrinsic features, spatial coverage, linear trend and coherence. Moreover, the accuracy of PS, SBAS and IPTA results are evaluated by comparison with in-situ measurements from the GNSS network managed by INGV-OE and private operators considering different metrics. Experimental results show that in this case there is no preferred MT-InSAR technique in an absolute way but each of them has strengths and drawbacks that have to be taken into account in the monitoring of complex scenarios.
Novel Teixobactin Analogues Show Promising In Vitro Activity on Biofilm Formation by Staphylococcus aureus and Enterococcus faecalis
Authors: Amer Ahmed M. , Charnock Colin , Nguyen Sanko
Published: September 2024

The treatment of infections caused by biofilm-forming organisms is challenging. The newly discovered antibiotic teixobactin shows activity against a wide range of biofilm-forming bacteria. However, the laborious and low-yield chemical synthesis of teixobactin complicates its further development for clinical application. The use of more easily synthesized teixobactin analogues may offer promise in this regard. In this article, three newly developed analogues were tested for efficacy against Staphylococcus aureus and Enterococcus faecalis. Minimum inhibitory and -bactericidal concentrations were investigated. MIC values for S. aureus and E. faecalis ranged from 0.5–2 and 2–4 μg/mL, respectively. Moreover, the ability of the analogues to prevent biofilm formation and to inactivate bacterial cells in already established S. aureus biofilm on medical grade materials (PVC and PTFE) used in the production of infusion tubing and catheters were also tested. The analogues showed an ability to prevent biofilm formation and inactivate bacterial cells in established biofilms at concentrations as low as 1–2 μg/mL. Confocal laser scanning microscopy showed that the most promising analogue (TB3) inactivated S. aureus cells in a preformed biofilm and gave a reduction in biovolume. The relative ease of synthesis of the analogues and their in vitro efficacy, makes them promising candidates for pharmaceutical development.

Graphical Abstract
ESR Essentials: imaging in fibrotic lung diseases—practice recommendations by the European Society of Thoracic Imaging
Authors: Larici Anna Rita , Biederer Juergen , Cicchetti Giuseppe , Franquet Casas Tomas , Screaton Nick , Remy-Jardin Martine , Parkar Anagha , Prosch Helmut , Schaefer-Prokop Cornelia , Frauenfelder Thomas , Ghaye Benoit , Sverzellati Nicola
Published: September 2024

Fibrotic lung diseases (FLDs) represent a subgroup of interstitial lung diseases (ILDs), which can progress over time and carry a poor prognosis. Imaging has increased diagnostic discrimination in the evaluation of FLDs. International guidelines have stated the role of radiologists in the diagnosis and management of FLDs, in the context of the interdisciplinary discussion. Chest computed tomography (CT) with high-resolution technique is recommended to correctly recognise signs, patterns, and distribution of individual FLDs. Radiologists may be the first to recognise the presence of previously unknown interstitial lung abnormalities (ILAs) in various settings. A systematic approach to CT images may lead to a non-invasive diagnosis of FLDs. Careful comparison of serial CT exams is crucial in determining either disease progression or supervening complications. This ‘Essentials’ aims to provide radiologists a concise and practical approach to FLDs, focusing on CT technical requirements, pattern recognition, and assessment of disease progression and complications. Hot topics such as ILAs and progressive pulmonary fibrosis (PPF) are also discussed.

Key Points

Chest CT with high-resolution technique is the recommended imaging modality to diagnose pulmonary fibrosis.

CT pattern recognition is central for an accurate diagnosis of fibrotic lung diseases (FLDs) by interdisciplinary discussion.

Radiologists are to evaluate disease behaviour by accurately comparing serial CT scans.
Takotsubo syndrome in a Sardinian amyotrophic lateral sclerosis cohort
Authors: Maccabeo A. , Pateri M. I. , Pili F. , Pilotto S. , Pierri V. , Muroni A. , Ercoli T. , Montisci R. , Marchetti M. F. , Martis A. , Fazzini L. , Defazio G. , Puligheddu M. , Borghero G.
Published: September 2024

Introduction

Amyotrophic lateral sclerosis (ALS) is known to be associated with varying degrees of autonomic and cardiovascular dysfunction. Recent case reports showed that ALS may be linked to Takotsubo syndrome (TTS). We assessed the frequency of TTS in an incident ALS cohort from Sardinia, Italy, and investigated the relationship of TTS with ALS course.

Methods

We retrospectively examined a 10-year (2010–2019) incident cohort of ALS patients of Sardinian ancestry, reported TTS frequency and patients’ clinical characteristics. Following, we checked for TTS among patients with ALS onset after 2019 and focused on the same features as for the incident cohort.

Results

Our incident cohort included 344 ALS patients and 5 of them (1.45%) developed TTS. All were female and their median onset age was 71.5 years (IQR 62.75–77). Two patients had spinal and three bulbar onset, though all patients had bulbar involvement and were at an advanced stage of disease (ALSFRS ≤ 25, King’s ≥ 3) at TTS diagnosis. We identified a potential TTS trigger in three patients (hospitalization for PEG placement, pneumonia). Among patients who had ALS onset after 2019, we identified a further TTS case and described it.

Conclusion

TTS is not a rare condition in ALS. Female sex, bulbar involvement, and later age of disease onset may be important risk factors for developing this cardiac condition and a physical or psychological trigger is often observed. Despite autonomic dysfunction in ALS has been already demonstrated, the precise physiopathological mechanism underlying TTS needs to be further clarified.
Challenges and opportunities in crowdsourced delivery planning and operations—an update
Authors: Savelsbergh Martin , Ulmer Marlin W.
Published: September 2024

How to best deliver goods to consumers has been a logistics question since time immemorial. However, almost all traditional delivery models involved a form of company employees, whether employees of the company manufacturing the goods or whether employees of the company transporting the goods. With the growth of the gig economy, however, a new model not involving company employees has emerged: relying on crowdsourced delivery. Crowdsourced delivery involves enlisting individuals to deliver goods and interacting with these individuals using the internet. In crowdsourced delivery, the interaction with the individuals typically occurs through a platform. Importantly, the crowdsourced couriers are not employed by the platform and this has fundamentally changed the planning and execution of the delivery of goods: the delivery capacity is no longer under (full) control of the company managing the delivery. We present the challenges this introduces, review how the research community has proposed to handle some of these challenges, and elaborate on the challenges that have not yet been addressed. In this update, we expand the literature review and discuss new challenges that have emerged in the past years. (This is an updated version of the paper “Challenges and Opportunities in Crowdsourced Delivery Planning and Operations” that appeared in 4OR, 20(1), 1-21 (2022)).
ERG-AI: enhancing occupational ergonomics with uncertainty-aware ML and LLM feedback
Authors: Sen Sagar , Gonzalez Victor , Husom Erik Johannes , Tverdal Simeon , Tokas Shukun , Tjøsvoll Svein O
Published: September 2024

Workers, especially those involved in jobs requiring extended standing or repetitive movements, often face significant health challenges due to Musculoskeletal Disorders (MSDs). To mitigate MSD risks, enhancing workplace ergonomics is vital, which includes forecasting long-term employee postures, educating workers about related occupational health risks, and offering relevant recommendations. However, research gaps remain, such as the lack of a sustainable AI/ML pipeline that combines sensor-based, uncertainty-aware posture prediction with large language models for natural language communication of occupational health risks and recommendations. We introduce ERG-AI, a machine learning pipeline designed to predict extended worker postures using data from multiple wearable sensors. Alongside providing posture prediction and uncertainty estimates, ERG-AI also provides personalized health risk assessments and recommendations by generating prompts based on its performance and prompting Large Language Model (LLM) APIs, like GPT-4, to obtain user-friendly output. We used the Digital Worker Goldicare dataset to assess ERG-AI, which includes data from 114 home care workers who wore five tri-axial accelerometers in various bodily positions for a cumulative 2913 hours. The evaluation focused on the quality of posture prediction under uncertainty, energy consumption and carbon footprint of ERG-AI and the effectiveness of personalized recommendations rendered in easy-to-understand language.
Breast cancer recurrence in relation to mode of detection: implications on personalized surveillance
Authors: Sartor Hanna , Hagberg Oskar , Hemmingsson Oskar , Lång Kristina , Wadsten Charlotta
Published: September 2024

Purpose

The effectiveness of current follow-up guidelines after breast cancer treatment is uncertain. Tailored surveillance based on patient age and tumor characteristics may be more adequate. This study aimed to analyze the frequency of ipsilateral locoregional recurrences (LR) and second primary breast cancers (SP) detected outside of scheduled surveillance and to analyze risk factors associated with these events.

Methods

Patients with surgically treated early-stage breast cancer from the Malmö Diet and Cancer Study (MDCS), 1991–2014 (n = 1080), and the Västernorrland region, 2009–2018 (n = 1648), were included. Clinical and pathological information on the primary tumor and recurrences was retrieved from medical records. The mode of recurrence detection was defined as detection within (planned) or outside (symptomatic) of scheduled surveillance.

Results

The median follow-up was 6.5 years. Overall, 461 patients experienced a recurrence. The most common initial event was distant metastasis (47%), followed by locoregional recurrence (LR) (22%) and second primary (SP) (18%). 56% of LR and 28% of SP were identified outside of scheduled surveillance. Logistic regression analysis revealed that younger age (under 50 years) (OR 2.57, 95% CI 1.04–6.88), lymph node-positive breast cancer (OR 2.10, 95% CI 1.03–4.39) and breast cancer of the HER2 positive subtype (OR 5.24, 95% CI 1.40–25.90) were correlated with higher odds of detecting a recurrence outside of planned surveillance.

Conclusion

Most recurrent events were detected outside of scheduled surveillance, particularly for locoregional recurrences. Risk-based surveillance, which takes into account patient and tumor characteristics, might be more suitable for specific patient subsets.
Modelling Residential Fire Vulnerability of Denmark
Authors: Crump Naomi , Markussen Bo , Oehmcke Stefan , Igel Christian , Skov-Petersen Hans , Karlsson Nyed Patrik
Published: September 2024

This study analyzes socio-economic demographics (including Geomatic conzoom® segmented demographic variables) as well as building and property registration information as risk factors in relation to the prevalence of residential building fires within 100 m × 100 m cells. The logistic regression model achieved a receiver operating curve (ROC) of 0.74 and a precision-recall curve of 0.12 on the testing dataset. The model identifies 19 significant variables related to the risk of residential fire. The top 5 highest performing variables in our model and their odds ratios are the following: number of people (OR 1.25), Multi/family residence-building type (OR 1.20), number of buildings (OR 1.18), conzoom® Type C—Country/Rural Communities (OR 0.85), construction year (OR 0.87). These results indicate that socio-economic factors play a large role in influencing fire vulnerability within residential areas and can help prioritize resource allocation to reduce fire vulnerability in the identified risk factor groups.