bluuebunny/crossref_metadata_2025 huggingface dataset:
Neuroanatomical photogrammetric models using smartphones: a comparison of apps
Authors: Piazza Amedeo , Corvino Sergio , Ballesteros Daniel , Campeggi Alice , Agosti Edoardo , Serioli Simona , Corrivetti Francesco , Bortolotti Carlo , De Notaris Matteo
Published: September 2024

Objectives

A deep knowledge of the surgical anatomy of the target area is mandatory for a successful operative procedure. For this purpose, over the years, many teaching and learning methods have been described, from the most ancient cadaveric dissection to the most recent virtual reality, each with their respective pros and cons. Photogrammetry, an emergent technique, allows for the creation of three-dimensional (3D) models and reconstructions. Thanks to the spreading of photogrammetry nowadays it is possible to generate these models using professional software or even smartphone apps. This study aims to compare the neuroanatomical photogrammetric models generated by the two most utilized smartphone applications in this domain, Metascan and 3D-Scanner, through quantitative analysis.

Methods

Two human head specimens (four sides) were examined. Anatomical dissection was segmented into five stages to systematically expose well-defined structures. After each stage, a photogrammetric model was generated using two prominent smartphone applications. These models were then subjected to both quantitative and qualitative analysis, with a specific focus on comparing the mesh density as a measure of model resolution and accuracy. Appropriate consent was obtained for the publication of the cadaver's image.

Results

The quantitative analysis revealed that the models generated by Metascan app consistently demonstrated superior mesh density compared to those from 3D-Scanner, indicating a higher level of detail and potential for precise anatomical representation.

Conclusion

Enabling depth perception, capturing high-quality images, offering flexibility in viewpoints: photogrammetry provides researchers with unprecedented opportunities to explore and understand the intricate and magnificent structure of the brain. However, it is of paramount importance to develop and apply rigorous quality control systems to ensure data integrity and reliability of findings in neurological research. This study has demonstrated the superiority of Metascan in processing photogrammetric models for neuroanatomical studies.
Longitudinal associations between prenatal internalizing symptoms and mindfulness traits with postnatal bonding difficulties
Authors: Garon-Bissonnette Julia , Bean Christian A. L. , Cárdenas Emilia F. , Jackson Maya , Abitante George , Humphreys Kathryn L. , Kujawa Autumn
Published: September 2024

Purpose

Mothers’ reported connection, or bond, with their infants develops across the early postnatal period and is relevant to mother and offspring functioning. Little is known, however, about early predictors of bonding difficulties over time. The present study examined prenatal anxiety, depressive symptoms, and trait mindfulness and variation in bonding difficulties in mothers across the first two months postnatal.

Methods

Participants were 120 pregnant women (Mage=31.09 years, SD = 4.81; 80% White). Measures of anxiety, depression, and five facets of mindfulness were administered mid-pregnancy (approximately 20 weeks gestation) and bonding difficulties were assessed every two weeks from approximately 1 to 7 weeks postnatal.

Results

Using multilevel modeling to account for within-person repeated assessments, we found an inverted U-shaped pattern across time such that bonding difficulties initially worsened before improving around five weeks postnatal. Prenatal anxiety and depressive symptoms were longitudinally associated with greater bonding difficulties overall and were unrelated to the trajectory of change. The mindfulness facets of acting with awareness and being nonjudging of one’s own experience were longitudinally associated with less bonding difficulties overall, weaker initial increases in bonding difficulties, and earlier improvements.

Conclusions

Prenatal anxiety and depression may be risk factors for bonding difficulties that are persistent across the early postnatal period. In contrast, mindfulness tendencies before childbirth, specifically acting with awareness and being nonjudging towards oneself, may support early feelings of bonding over time.
Surface roughness measurement in the notch area for estimating dynamic component load bearing capacity
Authors: Becker Nils , Tunsch Paul , Ulrich Carsten , Schlecht Berthold
Published: September 2024

The surface of a part can have an essential influence on its dynamic load bearing capacity as grooves and scratches act as more or less significant imperfections or additional micro-notches, depending on the interpretation. In order to accurately predict the fatigue strength, detailed knowledge of the surface structure in critical areas is essential but cannot always be established due to geometric constraints. To overcome these restrictions, a method utilizing impressions and a laser scanning microscope to take surface topography measurements in critical notch areas is used in this work. It enables precise and reproducible measurements to be taken. The method is used to conduct surface roughness measurements on fatigue strength specimens made of four different materials. Several roughness influence factors are calculated based on the results and their influence on the result of a recalculation using a fatigue strength assessment is shown as example. The calculated fatigue limit is compared against experimental results. The comparison shows significant scatter in prediction accuracy and no optimal surface influence factor can be recommended so far. It has to be noted that only a small sample of specimens, which were not designed for researching surface roughness influence in particular, were available for this work. The effects of roughness in the notch may not be completely captured by the available roughness influence factors. Furthermore, issues arise in the correct implementation of stress concentration factor based roughness influence factors. Further research is required to provide a more comprehensive understanding of the effects of surface roughness on the fatigue limit.
Amending “A note on solving the fleet quickest routing problem on a grid graph”
Authors: Andreatta Giovanni , De Francesco Carla , De Giovanni Luigi
Published: September 2024

A recent paper (Di Giacomo et al. Cent Eur J Oper Res 28:1069–1090, 2020) on the Fleet Quickest Routing Problem on Grid graphs (FQRP-G) claims that eight levels guarantee that a fleet of vehicles, simultaneously starting from the bottom level of the grid, can reach the top level by moving on Manhattan paths without ever stopping and without collisions, independently of the number of vehicles and columns of the grid and the configuration of vehicles’ origins and destinations. In this amending note, we will analyse the results in Di Giacomo et al. (Cent Eur J Oper Res 28:1069–1090, 2020) and show that the routing rule leading to this claim cannot be applied to all instances of FQRP-G, and that it can cause collisions. The analysis points out sufficient conditions under which the proposed rule draws proven collision-free routes for FQRP-G using no more than eight levels. Computational experiments demonstrate the relevance of the eight-levels bound and the functionality of the routing rule in practice, showing that it correctly solves the majority of instances up to one thousand vehicles. From a theoretical perspective, the claim that eight (or any constant number of) levels are sufficient to solve any instance of FQRP-G remains an open issue.
An assessment of the implications of distribution remuneration and taxation policies on the final prices of prescription medicines: evidence from 35 countries
Authors: Leon Giovanny , Carbonel Christophe , Rampuria Aparajit , Rajpoot Ravindra Singh , Joshi Parth , Kanavos Panos
Published: September 2024

This paper analyses the structure of and variability in taxation and prescription drug distribution policies and quantifies the impact of such policies on the cost of prescription drugs to health systems in 35 countries. Taxes on prescription drugs remain highly prevalent (83% of the sample) although 63% of the sample countries implement a lower than standard VAT rate. Three remuneration types of the wholesale and retail distribution chain have been identified. Wholesale and retail distributors are remunerated on a regressive mark-up basis, which is price-dependent, although fixed fees and fixed percentages, which are non-price dependent, are also highly prevalent. Price component analysis for three groups of products classed as high-, medium- and low-priced suggests that mark-ups plus taxes varied significantly across countries and products, and ranged from 5% to 187% of ex-factory prices. Average margins also vary significantly by countries and products ranging 5–65% of retail prices. The cost of distribution and taxation contributes significantly to prescription drug costs for health systems. Although distribution chain remuneration raises efficiency and overall affordability questions, these need to be considered together with the regulatory framework shaping market structure of the distribution chain, as well as any prevailing horizontal and vertical integration policies. The overall cost of prescription drugs could be reduced immediately by eliminating taxation; this could go some way to alleviate fiscal pressures on health budgets, whilst avoiding resource re-allocation from health to other sectors.
Autistic and non-autistic adults use discourse context to determine a speaker’s intention to request
Authors: Frost Faith , Nagano Marisa , Zane Emily
Published: September 2024

The current study focuses on how autistic adults utilize context to determine whether ambiguous utterances (e.g., “I’m thirsty”) are intended as indirect requests or as literal comment/questions. Two questions are addressed: (1) How do autistic adults compare to neurotypical adults in using context to interpret an utterance’s intention as either literal or a request? (2) What cognitive mechanisms correlate with indirect request interpretation, and are these different for participants in each group? Twenty-six autistic and 26 neurotypical college students participated, engaging in an online experiment where they read narratives that ended with utterances open to literal or request interpretations, based on context. After each narrative, participants selected the best paraphrase of the utterance from two options, literal versus request. Following this task, participants completed two mentalizing measures (a false belief and emotion-identification task) and several executive functioning tests. The best model for predicting paraphrase choice included scores on the emotion-identification task and context as main effects, along with the interaction between both. Participants with higher emotion-identification test scores were more likely to provide correct paraphrases. Models including group as a main effect and/or interaction were not better at fitting the data, nor were any models that included executive functioning measures as main effects or interactions. Emotion-identification test scores, but not autism diagnosis, predict how adults infer whether an utterance is a request. Findings suggest that autistic adults use context similarly to neurotypical adults when interpreting requests, and that similar processes underlie performance for each group.
Modification of the lesser curvature incision line enhanced gastric conduit perfusion as determined by indocyanine green fluorescence imaging and decreased the incidence of anastomotic leakage following esophagectomy
Authors: Zhao Hongbo , Koyanagi Kazuo , Ninomiya Yamato , Kazuno Akihito , Yamamoto Miho , Shoji Yoshiaki , Yatabe Kentaro , Kanamori Kohei , Tajima Kohei , Mori Masaki
Published: September 2024

Aim

This study aimed to investigate the effectiveness of a modified incision line on the lesser curvature for gastric conduit formation during esophagectomy in enhancing the perfusion of gastric conduit as determined by indocyanine green fluorescence imaging and reducing the incidence of anastomotic leakage.

Methods

A total of 272 patients who underwent esophagectomy at our institute between 2014 and 2022 were enrolled in this study. These patients were divided based on two different types of cutlines on the lesser curvature: conventional group (n = 141) following the traditional cutline and modified group (n = 131) adopting a modified cutline. Gastric conduit perfusion was assessed by ICG fluorescence imaging, and clinical outcomes after esophagectomy were evaluated.

Results

The distance from the pylorus to the cutline was significantly longer in the modified group compared with the conventional group (median: 9.0 cm vs. 5.0 cm, p < 0.001). The blood flow speed in the gastric conduit wall was significantly higher in the modified group than that in the conventional group (median: 2.81 cm/s vs. 2.54 cm/s, p = 0.001). Furthermore, anastomotic leakage was significantly lower (p = 0.024) and hospital stay was significantly shorter (p < 0.001) in the modified group compared with the conventional group. Multivariate analysis identified blood flow speed in the gastric conduit wall as the only variable significantly associated with anastomotic leakage.

Conclusions

ICG fluorescence imaging is a feasible, reliable method for the assessment of gastric conduit perfusion. Modified lesser curvature cutline could enhance gastric conduit perfusion, promote blood circulation around the anastomotic site, and reduce the risk of anastomotic leakage after esophagectomy.
The unexpected power of linear programming: an updated collection of surprising applications
Authors: Golden Bruce , Schrage Linus , Shier Douglas , Apergi Lida Anna
Published: September 2024

Linear programming has had a tremendous impact in the modeling and solution of a great diversity of applied problems, especially in the efficient allocation of resources. As a result, this methodology forms the backbone of introductory courses in operations research. What students, and others, may not appreciate is that linear programming transcends its linear nomenclature and can be applied to an even wider range of important practical problems. The objective of this article is to present a selection, and just a selection, from this range of problems that at first blush do not seem amenable to linear programming formulation. The exposition focuses on the most basic models in these selected applications, with pointers to more elaborate formulations and extensions. Thus, our intent is to expand the modeling awareness of those first encountering linear programming. In addition, we hope this article will be of interest to those who teach linear programming and to seasoned academics and practitioners, alike.
Explainable cognitive decline detection in free dialogues with a Machine Learning approach based on pre-trained Large Language Models
Authors: de Arriba-Pérez Francisco , García-Méndez Silvia , Otero-Mosquera Javier , González-Castaño Francisco J.
Published: September 2024

Cognitive and neurological impairments are very common, but only a small proportion of affected individuals are diagnosed and treated, partly because of the high costs associated with frequent screening. Detecting pre-illness stages and analyzing the progression of neurological disorders through effective and efficient intelligent systems can be beneficial for timely diagnosis and early intervention. We propose using Large Language Models to extract features from free dialogues to detect cognitive decline. These features comprise high-level reasoning content-independent features (such as comprehension, decreased awareness, increased distraction, and memory problems). Our solution comprises (i) preprocessing, (ii) feature engineering via Natural Language Processing techniques and prompt engineering, (iii) feature analysis and selection to optimize performance, and (iv) classification, supported by automatic explainability. We also explore how to improve Chatgpt’s direct cognitive impairment prediction capabilities using the best features in our models. Evaluation metrics obtained endorse the effectiveness of a mixed approach combining feature extraction with Chatgpt and a specialized Machine Learning model to detect cognitive decline within free-form conversational dialogues with older adults. Ultimately, our work may facilitate the development of an inexpensive, non-invasive, and rapid means of detecting and explaining cognitive decline.
Linearly convergent nonoverlapping domain decomposition methods for quasilinear parabolic equations
Authors: Engström Emil , Hansen Eskil
Published: September 2024

We prove linear convergence for a new family of modified Dirichlet–Neumann methods applied to quasilinear parabolic equations, as well as the convergence of the Robin–Robin method. Such nonoverlapping domain decomposition methods are commonly employed for the parallelization of partial differential equation solvers. Convergence has been extensively studied for elliptic equations, but in the case of parabolic equations there are hardly any convergence results that are not relying on strong regularity assumptions. Hence, we construct a new framework for analyzing domain decomposition methods applied to quasilinear parabolic problems, based on fractional time derivatives and time-dependent Steklov–Poincaré operators. The convergence analysis is conducted without assuming restrictive regularity assumptions on the solutions or the numerical iterates. We also prove that these continuous convergence results extend to the discrete case obtained when combining domain decompositions with space-time finite elements.
CAR T-cells for pediatric solid tumors: where to go from here?
Authors: Trautmann Tina , Yakobian Natalia , Nguyen Rosa
Published: September 2024

Despite the great success that chimeric antigen receptor (CAR) T-cells have had in patients with B-cell malignancies and multiple myeloma, they continue to have limited efficacy against most solid tumors. Especially in the pediatric population, pre- and post-treatment biopsies are rarely performed due to ethical reasons, and thus, our understanding is still very limited regarding the mechanisms in the tumor microenvironment by which tumor cells exclude effectors and attract immune-suppressive cells. Nevertheless, based on the principles that are known, current T-cell engineering has leveraged some of these processes and created more potent CAR T-cells. The recent discovery of new oncofetal antigens and progress made in CAR design have expanded the potential pool of candidate antigens for therapeutic development. The most promising approaches to enhance CAR T-cells are novel CAR gating strategies, creative ways of cytokine delivery to the TME without enhancing systemic toxicity, and hijacking the chemokine axis of tumors for migratory purposes. With these new modifications, the next step in the era of CAR T-cell development will be the clinical validation of these promising preclinical findings.
Sense through time: diachronic word sense annotations for word sense induction and Lexical Semantic Change Detection
Authors: Schlechtweg Dominik , Zamora-Reina Frank D. , Bravo-Marquez Felipe , Arefyev Nikolay
Published: September 2024

There has been extensive work on human word sense annotation, i.e., manually labeling word uses in natural texts according to their senses. Such labels were primarily created for the tasks of Word Sense Disambiguation (WSD) and Word Sense Induction (WSI). However, almost all datasets annotated with word senses are synchronic datasets, i.e., contain texts created in a relatively short period of time and often do not provide the creation date of the texts. This ignores possible applications in diachronic-historic settings, where the aim is to induce or disambiguate historical word senses or changes in senses across time. To facilitate investigations into historical WSD and WSI and to establish connections with the task of Lexical Semantic Change Detection (LSCD), there is a crucial need for historical word sense-annotated data. Hence, we created a new reliable diachronic WSD/WSI dataset ‘DWUG DE Sense’. We describe the preparation and annotation and analyze central statistics. We then describe a thorough evaluation of different prediction systems for jointly solving both WSI and LSCD tasks. All our systems are based on a state-of-the-art architecture that combines Word-in-Context models and graph clustering techniques with different hyperparameter settings. Our findings reveal that using the WSI task as optimization criterion yields better results for both tasks even when the LSCD task is the focal point of optimization. This underscores that although both tasks are related, WSI seems to be more general and able to incorporate the LSCD task.
A comparative analysis of the ethics of gene editing: ChatGPT vs. Bard
Authors: Burright Jack , Al-khateeb Samer
Published: September 2024

Recently, there has been a growing trend in using large language models (LLMs) to develop diverse applications suitable for a wide range of tasks. These tasks range from solving programming bugs to helping teach elementary school students how to enhance their writing. Even with all these beneficial use cases, researchers worry about the potential bias these tools could produce and their effect on society. In this research, we compared responses that resulted from prompting two chatbots, namely OpenAI ChatGPT and Google Bard, about the issue of gene editing. Twelve prompts that are part of two subgroups were used to generate responses (text) about the issue of gene editing when the political affiliation (Democrat, Republican, and Communist) or geographical areas (United States, China, and Europe) of the prompter is provided. The Twelve responses were then analyzed semantically using three dictionary-based tools, i.e., Linguistic Inquiry and Word Count, the Moral Foundation Theory and Biblical Ethics dictionary, and Google’s Perspective API, to test and analyze the semantic and linguistic differences (measured via the Mann–Whitney U test) in the responses returned from the two chatbots. The results suggest that there are semantic and linguistic differences in responses per chatbots and prompts.
Quality of institutions, rent-seeking, and inter-jurisdictional cooperation
Authors: Di Liddo Giuseppe , Giuranno Michele G.
Published: September 2024

The differing fiscal needs of municipalities introduce bias into yardstick competition among local administrators driven by pure rent-seeking motives. The influence of institutional quality on this bias varies across cases, sometimes alleviating it, while in other instances exacerbating it. Inter-municipal cooperation provides incumbents with control over political yardstick competition. However, this alliance compromises the quality of public services when rent extraction is a priority. To address the issue of collusion and enhance accountability, the central government may find it counterproductive to uniformly improve institutional quality across all districts. Instead, a more effective approach may involve targeted policy interventions in specific districts, considering the varying levels of fiscal and institutional disparities. By doing so, the central government can disrupt the incentive for collusion and rent extraction among local incumbents.
Introduction of a Framework for the Integration of a Kinematic Robot Arm Model in an Artificial Neural Network - Extended Kalman Filter Approach
Authors: Horvath Sabine , Neuner Hans
Published: September 2024

The aim of this paper is to introduce a model in which systematic effects can be assigned according to their origin or mode of action. The approach intends to improve the positional accuracy of a robot arm. We show the impact of unaccounted model biases on estimated parameters when applying sequential approaches and conclude the necessity of jointly determining all influencing variables. Therefore, we propose a simultaneous estimation of transformation parameters, robot’s kinematic parameters and non-geometric parameters modelled by an artificial neural network (ANN) in further consequence. Thus, the main contribution of this paper is a new approach of the simultaneous estimation of the geometric and non-geometric components of a robot arm model. The integration of the geometric model (transformations, kinematic robot model) with the non-geometric one (ANN) is realised in the extended Kalman filter. The functionality of the algorithm has been proven on simulated data. The adaptive behaviour of machine learning approaches is made possible by an additional iteration of the ANN. The initialisation of the ANN parameters must not deviate from the nominal parameters by more than 10% so that the ANN can learn the non-geometric part. In this setup, the robot arm position corrections are reduced by 32.5%. A final sensitivity analysis proves the estimability of most kinematic parameters in the course of a future adaptive extension of the approach.
Older Adult Family Homicide in Victoria, Australia 2001–2015: A Description of Family and Family Violence Homicide Victimisation
Authors: Kennedy Briohny , Ibrahim Joseph Elias , Koppel Sjaan , Bugeja Lyndal
Published: September 2024

Purpose

This study examined factors present among older adult family homicide victims and their offenders compared to younger adult family homicide using the social-ecological model.

Method

The study used a population-based single-jurisdiction cross-sectional design of consecutive homicide cases of adults (aged 18 years and older) reported to the coroner in Victoria, Australia for the period 2001–2015. Included were homicides involving an intimate or familial relationship. The data source was the Victorian Homicide Register, maintained by the Coroners Court of Victoria. Descriptive and multivariate analysis was performed to compare the presence of factors between younger and older adult family homicides.

Results

During the study period 37/283 (13.1%) family homicides occurred among older adult victims (aged 65 years and older) and 246/283 (86.9%) occurred among younger adults (aged 18–64 years). The deceased older adult was often male (57%), with a documented physical illness (54%). Offenders against the older adult were frequently male (68%), non-intimately related (73%), with diagnosed mental illness, a history of substance use and/or historical exposure to violence (all 57%). There were 15 older adult family violence (FV) homicide victims, eight that were previously victims of the homicide offender, primarily enduring emotional, physical and psychological violence as well as the perpetrator assaulting another family member. Seven older adults had perpetrated FV against their offender.

Conclusions

The history of violence perpetration in the deceased and mental health factors in their offender, as well as the greater proportion of parent-child and other familial relationships offer interesting focal points for future prevention research.
Exploring Therapists’ Perspectives on Acute Dynamic Risk Factors in Intimate Partner Violence by Family-Only Perpetrators: A Qualitative Study
Authors: Serno Carlijn , Bouman Yvonne H. A. , Hoed Joseline J. den , Kip Hanneke , de Ruiter Corine
Published: September 2024

Purpose

Intimate partner violence (IPV) is a common problem with severe consequences for perpetrators, their families, and society. IPV perpetrators are a heterogeneous group of which family-only (FO) perpetrators constitute the largest subgroup. Previous research suggests that FO perpetrators have a different risk profile than other subgroups, implying that they may require different treatment programs. Most studies have focused on static and stable risk factors; however, acute dynamic risk factors (ADRFs) – i.e., factors that constitute an immediate risk for offending behavior and can rapidly change over hours, days, or weeks – help to explain offending behavior. This study explored ADRFs for FO perpetration according to therapists to improve our understanding of FO perpetration, which could help in intervention planning for this group.

Methods

Ten semi-structured interviews were conducted with therapists in a community setting. Each interview included one FO case. Data were analyzed using a combination of inductive and deductive thematic analysis.

Results

ADRFs were categorized into personal and situational factors. Six ADRFs for FO perpetration were identified: mental exhaustion, perceived cheating/abandonment, psychological hurt, uncertainty, feelings of inadequacy, and intoxication. According to therapists, the dyadic relationship between the perpetrator and their partner plays an important role. Additionally, ADRFs were found to be often interconnected with each other and with static and stable risk factors.

Conclusions

This exploratory study revealed which types of ADRFs might play a role in FO perpetration. Future research should focus on the interrelationships between ADRFs and their relation to static and stable dynamic risk factors.
Impacts of generative AI on user contributions: evidence from a coding Q &A platform
Authors: Li Xinyu , Kim Keongtae
Published: September 2024

This study investigates the short-term impact of generative AI, exemplified by the introduction of ChatGPT, on user contributions in a coding Q&A platform. We find that the introduction of ChatGPT led to a reduction in the number of high-quality answers provided by users, particularly among highly engaged contributors, despite an overall increase in answers. We identify two key mechanisms: (1) increased perceived question sophistication despite no actual change in content and (2) reduced motivation of loyal users in providing answers in the face of AI-generated alternatives. The findings suggest that while generative AI can facilitate value creation on user-generated content (UGC) platforms, it also poses challenges in retaining core contributors and managing content quality. The paper contributes to the literature on the impact of AI adoption on platforms and suggests practical implications for UGC platform management, such as the need for AI content disclosure measures to retain engaged users.
Multimodal emotion recognition based on a fusion of audiovisual information with temporal dynamics
Authors: Salas-Cáceres José , Lorenzo-Navarro Javier , Freire-Obregón David , Castrillón-Santana Modesto
Published: September 2024

In the Human-Machine Interactions (HMI) landscape, understanding user emotions is pivotal for elevating user experiences. This paper explores Facial Expression Recognition (FER) within HMI, employing a distinctive multimodal approach that integrates visual and auditory information. Recognizing the dynamic nature of HMI, where situations evolve, this study emphasizes continuous emotion analysis. This work assesses various fusion strategies that involve the addition to the main network of different architectures, such as autoencoders (AE) or an Embracement module, to combine the information of multiple biometric cues. In addition to the multimodal approach, this paper introduces a new architecture that prioritizes temporal dynamics by incorporating Long Short-Term Memory (LSTM) networks. The final proposal, which integrates different multimodal approaches with the temporal focus capabilities of the LSTM architecture, was tested across three public datasets: RAVDESS, SAVEE, and CREMA-D. It showcased state-of-the-art accuracy of 88.11%, 86.75%, and 80.27%, respectively, and outperformed other existing approaches.
Silencing Osa-miR827 via CRISPR/Cas9 protects rice against the blast fungus Magnaporthe oryzae
Authors: Bundó Mireia , Val-Torregrosa Beatriz , Martín-Cardoso Héctor , Ribaya María , Campos-Soriano Lidia , Bach-Pages Marcel , Chiou Tzyy-Jen , San Segundo Blanca
Published: September 2024

MicroRNAs (miRNAs) are short, non-coding RNAs that regulate gene expression at the post-transcriptional level. In plants, miRNAs participate in diverse developmental processes and adaptive responses to biotic and abiotic stress. MiR827 has long been recognized to be involved in plant responses to phosphate starvation. In rice, the miR827 regulates the expression of OsSPX-MFS1 and OsSPX-MFS2, these genes encoding vacuolar phosphate transporters. In this study, we demonstrated that miR827 plays a role in resistance to infection by the fungus Magnaporthe oryzae in rice. We show that MIR827 overexpression enhances susceptibility to infection by M. oryzae which is associated to a weaker induction of defense gene expression during pathogen infection. Conversely, CRISPR/Cas9-induced mutations in the MIR827 gene completely abolish miR827 production and confer resistance to M. oryzae infection. This resistance is accompanied by a reduction of leaf Pi content compared to wild-type plants, whereas Pi levels increase in leaves of the blast-susceptible miR827 overexpressor plants. In wild-type plants, miR827 accumulation in leaves decreases during the biotrophic phase of the infection process. Taken together, our data indicates that silencing MIR827 confers resistance to M. oryzae infection in rice while further supporting interconnections between Pi signaling and immune signaling in plants. Unravelling the role of miR827 during M. oryzae infection provides knowledge to improve blast resistance in rice by CRISPR/Cas9-editing of MIR827.
The stratified effect of extreme temperatures on birth weight: the role of energy prices
Authors: Rubio-Cabañez Maria
Published: September 2024

This paper fills a notable gap in the existing literature on birth outcomes and extreme temperatures by examining the causal moderating effect of energy prices on the impact of extreme temperatures during pregnancy on birth weight. It uses a sharp increase in energy prices that occurred in Spain in March 2021 as an identification strategy and incorporates a new weather dataset that increases the number of monitors from which temperature information is derived in previous research by more than sixfold. The results show that the negative effects of extreme temperatures on birth weight are amplified at higher energy prices, especially for mothers of lower socioeconomic status. By focusing on how energy prices moderate the impact of extreme temperatures on birth outcomes, opportunities arise for policy interventions aimed at reducing health inequalities at birth. Moreover, given the critical role that events in utero play in individuals’ later development, such policies have the potential not only to reduce health inequalities at birth, but also to address broader inequalities in long-term outcomes.
Heterogeneous Treatment Effects in the Incredible Years Teacher Classroom Management Programme - A Latent Profile Approach
Authors: Tveit Håvard Horndalen , Stenseng Frode
Published: September 2024

Heterogeneous effects from interventions often remain hidden in between-group analyses, risking overgeneralized conclusions of treatment effects. In this exploratory study, we performed latent profile analysis to unveil differential treatment effects among children in The Incredible Years Teacher Classroom Management Programme (IY TCMP). This program has previously been shown to reduce behavioral problems in preschools and schools in total samples and subgroups. A total of 726 children (48.7% girls; Mage = 4.21 years; SDage = 0.86) from 92 childcare centers in Norway participated in either the intervention (n = 338) or the matched control condition (n = 388). First, by conducting latent profile analysis on baseline levels of child-teacher relationship (closeness, conflict), behavioral problems, and social competence, three distinct profiles were identified: High Risk (26.4%), Moderate Risk (42.8%), and Low Risk (30.7%) – each profile with unique characteristics. Second, we tested for within-profile, condition-by-time interactions following the intervention, showing distinct treatment responses for each profile. High-risk profiles profited most from the IY TCMP, with a substantial decrease in externalizing problems, more teacher closeness, and less teacher conflict. Moderate-risk profiles also gained better teacher-child relationships and improved social competence. The Low-Risk profiles showed no effects from the intervention. It is argued that latent profile analysis presents a feasible approach for examining within-sample heterogeneity in intervention research. It also reveals crucial information on treatment variability, as demonstrated in the Incredible Years Programme.
Applying queueing theory to evaluate wait-time-savings of triage algorithms
Authors: Thompson Yee Lam Elim , Levine Gary M. , Chen Weijie , Sahiner Berkman , Li Qin , Petrick Nicholas , Delfino Jana G. , Lago Miguel A. , Cao Qian , Samuelson Frank W.
Published: September 2024

In the past decade, artificial intelligence (AI) algorithms have made promising impacts in many areas of healthcare. One application is AI-enabled prioritization software known as computer-aided triage and notification (CADt). This type of software as a medical device is intended to prioritize reviews of radiological images with time-sensitive findings, thus shortening the waiting time for patients with these findings. While many CADt devices have been deployed into clinical workflows and have been shown to improve patient treatment and clinical outcomes, quantitative methods to evaluate the wait-time-savings from their deployment are not yet available. In this paper, we apply queueing theory methods to evaluate the wait-time-savings of a CADt by calculating the average waiting time per patient image without and with a CADt device being deployed. We study two workflow models with one or multiple radiologists (servers) for a range of AI diagnostic performances, radiologist’s reading rates, and patient image (customer) arrival rates. To evaluate the time-saving performance of a CADt, we use the difference in the mean waiting time between the diseased patient images in the with-CADt scenario and that in the without-CADt scenario as our performance metric. As part of this effort, we have developed and also share a software tool to simulate the radiology workflow around medical image interpretation, to verify theoretical results, and to provide confidence intervals for the performance metric we defined. We show quantitatively that a CADt triage device is more effective in a busy, short-staffed reading setting, which is consistent with our clinical intuition and simulation results. Although this work is motivated by the need for evaluating CADt devices, the evaluation methodology presented in this paper can be applied to assess the time-saving performance of other types of algorithms that prioritize a subset of customers based on binary outputs.
The earned income tax credit (EITC) and time spent helping and caring for adults
Authors: Wiersma Strauss Anna
Published: September 2024

This is the first study to examine the effect of the Earned Income Tax Credit (EITC) on unpaid caregiving for adults, which could operate through the credit’s effects on labor supply and household income. Using a sample of unmarried mothers and data from the American Time Use Survey (ATUS), I employ a simulated benefit approach to generate causal estimates of the effect of EITC generosity on time use. I find that increases in average EITC benefits have differential effects on assisting adults by both the age of the EITC recipient and the relationship between the EITC recipient and the care recipient. No effect is estimated for the youngest group of unmarried mothers (ages 25–34), who increase employment without reducing time spent assisting adults. In contrast, the oldest group of unmarried mothers (ages 45–54) responds by increasing their propensity to assist their parents while maintaining their labor supply. Unmarried mothers aged 35–44 both increase their labor supply and spend more time assisting adult family members on the intensive margin, even as they are less likely to assist parents on the extensive margin, especially with chore help. Results for other types of time use (home production, leisure, childcare, education, sleep), as well as probability of multigenerational co-residence, help explain these shifts. For example, for the oldest group of unmarried mothers, increased co-residence with parents is estimated to occur and may facilitate this labor-caregiving balance. These results add to a growing body of evidence that the EITC affects recipients’ time allocation beyond paid work and that the effects of the EITC span across generations and households.
Investment bank reputation and issuance fees: evidence from asset-backed securities
Authors: Karimov Nodirbek , Kara Alper , Downing Gareth
Published: September 2024

We examine the relationship between investment bank (IB) reputation and fees paid in ABS issuance. We compile an extensive instrument level dataset of over 35,000 ABS issued between 1997 and 2018 in the US and the European market. We find that reputation of IBs is influential in determining the compensation they are paid for their services in ABS issuance. On average, reputable IBs receive 3.74% higher fees in comparison to others. Moreover, our results show IBs’ ability to obtain lower initial yield spreads in ABS issuance. Overall, our findings provide evidence to the arguments that reputable IBs with high market presence offer high-quality services and assurance to the market participants (i.e., certification effect) leading to better deals. In return, they are able to charge higher fees.
Inequalities in Water Insecurity in Kenya: A Multidimensional Approach
Authors: Njoroge Cecilia , Smith Anja , von Fintel Marisa
Published: September 2024

Water insecurity is a global concern likely to be compounded by increases in population and climate change. Existing water insecurity measurement methods capture multidimensional deprivation only at regional or sub-regional levels. Such estimates do not capture heterogeneous household experiences of water supply, proximity to water sources and affordability, which can vary substantially from regional averages. Accurate measurement requires a method that captures the incidence and intensity of a household’s simultaneous deprivation in dimensions of water accessibility, affordability, sufficiency and safety. We propose such a method and assess related inequalities using an approach analogous to the Alkire–Foster methodology for multidimensional poverty. Using household-level data from the Kenya Integrated Household Budget Survey 2015/16, we find that 63% of the Kenyan population experience multiple deprivation in water access. The dimensions of water affordability and sufficiency contribute most to multidimensional water insecurity, highlighting the need to ensure an adequate supply of affordable water. Disparities by household place of residence, dwelling type, and socio-economic status are evident. The estimates of multidimensional water insecurity are robust to different deprivation and poverty cutoffs. Our analysis is an invitation to rethink water insecurity metrics, allowing water deprivation to be measured more frequently and with greater precision to understand its impact clearly.
How ideas connect to the world
Authors: Brown Andrew
Published: September 2024

The celebrated Russian philosopher, Evald Ilyenkov, draws on Spinoza to solve a key philosophical problem: how exactly does the mind connect to the real world? However, the proposed solution has come under much criticism, for example in a recent special issue of Studies of East European Thought (74, 3). This paper aims to clearly explain the solution, overcoming misunderstandings that are evident in the special issue. The kernel of the solution is an argument that human cognition rests on practical activity. In practical activity humans do not act on a fixed structure within their own bodies, in the manner, say, that the activity of water is determined by its fixed structure, H2O. Instead, human practical activity directly connects with and continually adapts to the structures and causal powers of external bodies. Awareness of practical activity thereby gives the human mind access to a mode of activity that is in direct contact and ever-greater accordance with the objects of the real world. The paper will elaborate and develop this kernel, with particular attention to the notion of ‘causal powers’ that it contains, by drawing from the revival in philosophy and the social sciences of what has been termed ‘causal powers realism’. The paper thereby opens new insights and connections regarding the Spinoza-Ilyenkov solution, alleviating the potential for misunderstandings evident in the special issue.
Neuroidealism, perceptual acquaintance and the Kantian roots of predictive processing
Authors: Britten-Neish George
Published: September 2024

Perception, according to advocates of the predictive processing (PP) framework in cognitive science, is a kind of controlled hallucination. Philosophers interested in PP, however, differ on how best to interpret this slogan. Does it suggest a new kind of idealism about perceptual objects or is it just a useful metaphor, illustrating something about how PP systems work without entailing a radical shakeup of mainstream realist views in the philosophy of perception? In this paper, I take a historically informed approach to this question, drawing on the Kantian roots of the contemporary framework. What perception reveals, according to PP, is a world shaped by the neurocomputational capacities and limitations of perceiving creatures. This means that the properties of perceived objects are, in an important and surprising sense, perceiver-dependent. Nonetheless, thanks to the integration of perceptual and agential capacities envisioned by PP, we should also accept a central claim of realism: in encountering this world we also encounter—come to be acquainted with—mind-independent particulars. PP thus supports a promising next step in the development of a Kantian argument linking the unity of agency to the objectivity of perception. The argument was advanced in its modern form by P.F. Strawson and has later been developed by Susan Hurley and others. In the revised form presented here, it says that PP-perceivers must be practically self-aware agents and that practically self-aware agents embedded in an environment can be acquainted with objects it contains.
Morphological, cytogenetic, and phytochemical estimation of Lychnis flos-cuculi L. cell cultures: can cell biomass be a source of bioactive compounds?
Authors: Hermosaningtyas Anastasia Aliesa , Kruszka Dariusz , Juszczyk Katarzyna , Rewers Monika , Budzianowska Anna , Yanti Yanti , Kikowska Małgorzata
Published: September 2024

The ragged robin (Lychnis flos-cuculi L.) from the Caryophyllaceae family contains flavonoids, phenolic acids, flavonoids, triterpenoid saponins, and ecdysteroids, making it potential for biological and medicinal application. Plant cell culture technologies could be beneficial for obtaining low-cost biomass sources with valuable phytochemicals sustainably. The current study reports the induction and proliferation of ragged robin cell culture and evaluation of various plant growth regulators (PGRs) impact on the secondary metabolites profile using UPLC-HRMS/MS. Callus was initiated from different explants on the Murashige and Skoog medium with various combinations and concentrations of PGRs. It was found that prolonged proliferation on MS medium enriched with a combination of 1.0 mg l− 1 2,4-Dichlorophenoxyacetic acid and 0.1 mg l− 1 N6-furfuryl adenine (Kinetin) yields the maximum biomass with 504.05% growth index. The results of flow cytometric analysis suggested no genetic alteration between differentiated and dedifferentiated cultures. Furthermore, the UPLC-HRMS/MS result distinguished 101 significant signals that were manually identified as ecdysteroids (16 metabolites), flavonoids (11 metabolites), phenolic acids (10 metabolites), triterpene saponins and sapogenins (53 metabolites), and some primary metabolites. Our study demonstrates that the cell culture of L. flos-cuculi displays significant differences in its phytochemical makeup to plants cultivated in vitro. Moreover, the type of growth regulators used for callus cultures was identified to cause substantial shifts in the identified metabolites.

Graphical Abstract