bluuebunny/crossref_metadata_2025 huggingface dataset:
The influence of the physicochemical processes on the electrical response of Al/p-Si structure with etched surface
Authors: Badali Yosef , Azizian-Kalandaragh Yashar
Published: March 2024

In this paper, the electrochemical etching process is used for surface modification of the p-Si wafer, named as porous silicon (PS), in the metal–semiconductor (MS) type Schottky diode (SD) with a structure of Al/p-Si. Five regions of PS wafer with different etching rates are selected for comparison of them which are called P2, P3, P4, and P5 (P1 is the reference area without porosity). The morphological, structural, and electrical properties of the PS used in the MS-type SD are investigated using field-emission scanning electron microscope (FE-SEM) images, energy dispersive X-ray (EDX) analysis, and current–voltage (I–V) characteristics, respectively. The FE-SEM images show a meaningful effect on the porosity. The EDX spectrum demonstrates the importance of the chemical effects in addition to the physical changes in the porosity process of the p-Si wafer. The reverse-saturation current (I0), ideality factor (n), barrier height at zero-bias (ΦB0), and series/shunt electrical resistances are also computed and compared. Some of these parameters (n, Rs, BH) are determined using different methods, namely Thermionic emission (TE), Cheung functions, and modified Norde, and they exhibit strong agreement with each other. The energy-dependent profiles of surface states (Nss) are estimated from the I–V data by considering the voltage dependence of ΦB (V) and n(V). All the experimental findings indicate that the etching process of the p-Si wafer significantly influences the electrical performance of the Al/p-Si Schottky diode by increasing the extent of etching.
Fluorescence guidance using near-infrared fluorescent clips in robotic rectal surgery: a case series
Authors: Narihiro Satoshi , Nakashima Syunsuke , Kazi Mutsumi , Kumamoto Tomotaka , Kitagawa Kazuo , Toya Naoki , Eto Ken
Published: March 2024

Purpose

Tattoo markings are often used as preoperative markers for colorectal cancer. However, scattered ink markings adversely affect tumor site recognition intraoperatively; therefore, interventions for rectal cancer may lead to an inaccurate distal resection margin (DRM) and incomplete total mesorectal excision (TME). This is the first case series of fluorescence-guided robotic rectal surgery in which near-infrared fluorescence clips (NIRFCs) were used to localize rectal cancer lesions.

Methods

We enrolled 20 consecutive patients who underwent robotic surgery for rectal cancer between December 2022 and December 2023 in the current study. The primary endpoints were the rate of intraoperative clip detection and its usefulness for marking the tumor site. Secondary endpoints were oncological assessments, including DRM and the number of lymph nodes.

Results

Clip locations were confirmed in 17 of 20 (85%) patients. NIRFCs were not detected in 3 out of 7 patients who underwent preoperative chemoradiation therapy. No adverse events, including bleeding or perforation, were observed at the time of clipping, and no clips were lost. The median DRM was 55 mm (range, 22–86 mm) for rectosigmoid (Rs), 33 mm (range, 16–60 mm) for upper rectum (Ra), and 20 mm (range, 17–30 mm) for low rectum (Rb). The median number of lymph nodes was 13 (range, 10–21).

Conclusion

The rate of intraoperative clip detection, oncological assessment, including DRM, and the number of lymph nodes indicate that the utility of fluorescence-guided methods with NIRFCs is feasible for rectal cancer.
“Dirty Dry Eye”– A waste volume analysis from topical therapy in keratoconjunctivitis sicca
Authors: Schilcher Alexandra V. , Roth Mathias , Steindor Friedrich A. , Helweh Ranya , Geerling Gerd
Published: March 2024

Purpose

The healthcare system is responsible for around 5% of CO2 emissions globally and in Germany. So far, there are no data on the amount of waste from dry eye disease (DED) therapy in ophthalmology. The aim of this project was to evaluate the amount and type of waste from single- and multi-dose units (SDU/MDU) generated by eyedrops used to treat DED in Germany.

Methods

The net waste weight (outer/inner packaging, instruction leaflet, empty container) from factory-sealed products was determined using a precision scale. Based on prescription data from PharMaAnalyst, a database of medical prescriptions from over 70 million patients in Germany, the total annual waste volume for 2016–2021 and the net weight of a 30-day treatment were calculated.

Results

The total annual waste volume increased significantly (p < 0.0001) from 7.13 tons in 2016 to 20.64 tons in 2021. A 30-day treatment with MDUs (without/with filter) results in a significantly lower mean waste volume (paper: SDU 24.3 ± 18.7 g; MDU 4.8 ± 1.7 g/8.8 g ± 1.7 g; SDU/MDU p = 0.0003, with filter p = 0.0034; plastic: SDU 35.0 ± 4.0, MDU 6.6 ± 0.7 g/ 15.1 g ± 5.8 g, SDU/MDU p < 0.0001, with filter p < 0.0001).

Conclusion

Prescription-based treatment of DED in Germany causes an increasing and substantial waste volume. The use of SDUs is considerably more resource-intensive than MDUs. Due to the large and rising number of patients suffering from DED improvements in packaging could considerably reduce the CO2 footprint of DED treatment.
An AI-based approach driven by genotypes and phenotypes to uplift the diagnostic yield of genetic diseases
Authors: Zucca S. , Nicora G. , De Paoli F. , Carta M. G. , Bellazzi R. , Magni P. , Rizzo E. , Limongelli I.
Published: March 2024

Identifying disease-causing variants in Rare Disease patients’ genome is a challenging problem. To accomplish this task, we describe a machine learning framework, that we called “Suggested Diagnosis”, whose aim is to prioritize genetic variants in an exome/genome based on the probability of being disease-causing. To do so, our method leverages standard guidelines for germline variant interpretation as defined by the American College of Human Genomics (ACMG) and the Association for Molecular Pathology (AMP), inheritance information, phenotypic similarity, and variant quality. Starting from (1) the VCF file containing proband’s variants, (2) the list of proband’s phenotypes encoded in Human Phenotype Ontology terms, and optionally (3) the information about family members (if available), the “Suggested Diagnosis” ranks all the variants according to their machine learning prediction. This method significantly reduces the number of variants that need to be evaluated by geneticists by pinpointing causative variants in the very first positions of the prioritized list. Most importantly, our approach proved to be among the top performers within the CAGI6 Rare Genome Project Challenge, where it was able to rank the true causative variant among the first positions and, uniquely among all the challenge participants, increased the diagnostic yield of 12.5% by solving 2 undiagnosed cases.
The illegal trade in rosewood in Indonesia
Authors: Nijman Vincent
Published: March 2024

Rosewoods are among the most valuable traded hardwoods, and there is a significant illegal trade. From 2017 onwards the international trade in all species of Dalbergia rosewood is regulated through the Convention on International Trade in Endangered Species of Wild Fauna and Flora. I focus on two species of rosewood that occur in parts of Indonesia, Dalbergia latifolia and D. sissoo, to assess the extent of the illegal trade and to analyse geographical and temporal patterns of wildlife crime. Based on 67 seizure reports from 2014 to 2022 I show that (a) 117 logs of D. sissoo and 4,285 logs of D. latifolia were confiscated, (b) seizures occurred on the islands of Sumatra (16 seizures; 1,190 logs), Java (43; 1,780 logs), and Bali, Lombok, Sumbawa and Timor (8; 1,408 logs), (c) while there was an increase in the number of seizures per year, there were no seasonal differences in seizure activities. For 10% of the logs there was supporting evidence that they were taken from State managed forests and 18% was taken from conservation areas, thus causing more damage than just the removal of individual trees. Seizures in Indonesia over this period equals 0.12 ± 0.04% of the legal rosewood export. The illegal trade is dominated by Indonesians rather than foreign nationals and the direction of trade is towards Java from where > 95% will be exported to China. While policies are in place concerning rosewood seizures and stockpiling (including auctioning or destruction) in practise it is unclear where seized rosewood ends up. When used with caution, analysis of seizure data offers a valuable means to gain insights in illicit activities that normally remain hidden from view.
A review of convolutional neural networks in computer vision
Authors: Zhao Xia , Wang Limin , Zhang Yufei , Han Xuming , Deveci Muhammet , Parmar Milan
Published: March 2024

In computer vision, a series of exemplary advances have been made in several areas involving image classification, semantic segmentation, object detection, and image super-resolution reconstruction with the rapid development of deep convolutional neural network (CNN). The CNN has superior features for autonomous learning and expression, and feature extraction from original input data can be realized by means of training CNN models that match practical applications. Due to the rapid progress in deep learning technology, the structure of CNN is becoming more and more complex and diverse. Consequently, it gradually replaces the traditional machine learning methods. This paper presents an elementary understanding of CNN components and their functions, including input layers, convolution layers, pooling layers, activation functions, batch normalization, dropout, fully connected layers, and output layers. On this basis, this paper gives a comprehensive overview of the past and current research status of the applications of CNN models in computer vision fields, e.g., image classification, object detection, and video prediction. In addition, we summarize the challenges and solutions of the deep CNN, and future research directions are also discussed.
Review on PID, fuzzy and hybrid fuzzy PID controllers for controlling non-linear dynamic behaviour of chemical plants
Authors: Mohindru Pankaj
Published: March 2024

The chemical production process is tedious due to the integration of different types of equipment and variables. Designing the controller is crucial in the chemical industry due to the interactive and non-linear system behaviour. An intelligent autonomous controller can improve the operating efficiency of the industry. Although several controllers have been developed, different system failures are frequently reported. Hence, controllers such as proportional integral derivative (PID), fuzzy logic controller (FLC), and hybrid fuzzy PID (F-PID) applied in the chemical industries are critically reviewed in the paper. Initially, the PID controller-based approaches are reviewed for different purposes in the chemical industry. After that, the FLC-based controllers-based papers are reviewed. In order to satisfy the issues in both controllers, the H-PID controllers have been reviewed. This review paper will provide an effective solution for operation control in the chemical industry under different operating conditions.
Protecting commonplace biodiversity under international conservation law
Authors: Amos Rob
Published: March 2024

A contemporary appraisal of the extent to which international conservation law provides for the protection of commonplace biodiversity. It is argued that in light of the current extinction crisis, biodiversity would be better served if the law focused more on protecting common species rather than just the rare and endangered. Particular attention is paid to the rationales behind conservation regulation and how different understandings of the value have influenced the law’s development. Key conservation mechanisms, namely area-based management, species-focused mechanisms and the ecosystem approach, are analysed in relation to how they protect commonplace biodiversity, before a case study on the legal protection of plants is presented. What is suggested is that international conservation law has failed to keep pace with key developments in conservation science, resulting in a regulatory system that appears structurally incapable of halting biodiversity loss. Reforming the law so that it provides greater protection to commonplace biodiversity would be an important first step in responding to this.
Human disturbance and habitat structure drive eurasian otter habitat selection in heavily anthropized river basins
Authors: Tolrà Arnau , Ruiz-Olmo Jordi , Riera Joan Lluís
Published: March 2024

Assessing habitat selection is essential to protecting threatened species but also to understand what factors influence species that, although globally not currently in decline, act as flagships of their ecosystems and remain highly vulnerable to human impacts, such as the Eurasian otter. This paper examines otter habitat selection at the river reach scale in two heavily anthropized river basins. Both river basins encompass a wide spectrum of human pressures and biogeographic units, which offers an excellent opportunity to assess otter responses to anthropogenic activities in different scenarios. Through two modelling approaches (structure-agnostic way and a priori hypothesized habitat factors) we demonstrate that otters currently inhabiting these human-dominated landscapes show a trade-off between a preference for highly productive areas and for well-structured and safe areas. We suggest that habitat simplification and human disturbance, which were of minor relevance to the dramatic decline of otter populations in the 20th century, are emerging as potential threats in the context of worldwide increasing land use intensification. Furthermore, we found that otter habitat requirements were remarkably more stringent for breeding site selection than for occurrence, particularly concerning variables related to human disturbance. The results of this work provide tools for integrating ecological criteria oriented to effective otter conservation into river management in human-dominated landscapes, as well as serving as methodological support for lowland river restorations. Our results suggest that long-term otter conservation in anthropized rivers will depend on ensuring the availability of habitat patches that maintain sufficient structural complexity away from intensely outdoor recreational activities.
Soil nitrogen cycling in forests invaded by the shrub Rosa multiflora: importance of soil moisture and invasion density
Authors: Moore Eric R. , Pouyat Richard V. , Trammell Tara L. E.
Published: March 2024

Invasive plants often alter ecosystem function and processes, especially soil N cycling. In eastern United States forests, the shrub Rosa multiflora (“rose”) is a dominant invader, yet potential effects on N cycling are poorly understood. Moreover, invasive plant management can impact soil N cycling by decreasing plant N uptake and disturbing the soil. The objectives of this study were to evaluate N cycling along a gradient of rose invasion (observational) and investigate potential changes to N cycling (manipulative) under four different management strategies: (1) do nothing (the control), (2) invasive plant removal, (3) removal followed by native seed mix addition, (4) removal, native seed mix, and chipped rose stem addition. We selected three forest sites experiencing a Low, Medium, or High amount of shrub invasion, and measured N cycling in the early (June) and late (September) growing seasons. We found N was immobilized in June and mineralized in September. One year after experimental management, removal alone had no effect on N cycling compared to control plots, but addition of native seed mix and chipped stems reduced early-season nitrification in our Medium invasion site. Our findings suggest that rose invasion may increase N cycling rates when soils are dry, which may occur more frequently with future climate change. In addition, N cycling responds differentially to management in the year following invasive plant removal, but most noticeably under moderate rose invasion.
Discordance interpretation of left ventricular size between echocardiography and cardiac magnetic resonance in pediatric patients with aortic/mitral regurgitation
Authors: Barros Anastasia , Udine Michelle , Spurney Chris , Olivieri Laura , Loke Yue-Hin
Published: March 2024

Purpose

This study investigated discordance between echocardiography (echo) and cardiac magnetic resonance (CMR) measurements of the left ventricle (LV) in pediatric patients with aortic and/or mitral regurgitation (AR/MR).

Methods

Retrospective cohort study of pediatric patients. The cohorts were comprised of patients with AR/MR vs. non-AR/MR. Left ventricular end diastolic volume (LVEDV) by CMR and left ventricular internal diameter diastolic (LVIDd) by echo were obtained from clinical reports then echo images were reviewed to remeasure LVEDV by bullet method. Left ventricular internal diameter systolic (LVIDs) and left ventricular ejection fraction (LVEF) measurements by echo and LVEF by CMR were obtained from clinical reports. Fractional shortening (FS%) was recalculated. Z-scores were calculated using normative data. Correlation between echo and CMR LV measurements was assessed using correlation coefficients. Bland-Altman plots assessed bias between imaging modalities. Receiver operator characteristic (ROC) analysis was performed for detection of LV enlargement and LV dysfunction.

Results

AR/MR patients had greater discrepancy in LV size interpretation by Z-score compared to non-AR/MR patients. This discrepancy persisted when the bullet method short axis measurements were incorporated. There was negative bias in echo-based measurements compared to CMR. The diagnostic performance of echo in identifying moderate LV enlargement was worse for AR/MR pediatrics patients.

Conclusion

The discordant interpretation of LV size by echo compared to CMR is worse in pediatric patients with AR/MR when compared to patients without AR/MR even when short axis measurements are incorporated. This finding suggests non-uniform geometrical changes in the LV as it enlarges due to AR/MR.
Introducing the 3MT_French dataset to investigate the timing of public speaking judgements
Authors: Biancardi Beatrice , Chollet Mathieu , Clavel Chloé
Published: March 2024

In most public speaking datasets, judgements are given after watching the entire performance, or on thin slices randomly selected from the presentations, without focusing on the temporal location of these slices. This does not allow to investigate how people’s judgements develop over time during presentations. This contrasts with primacy and recency theories, which suggest that some moments of the speech could be more salient than others and contribute disproportionately to the perception of the speaker’s performance. To provide novel insights on this phenomenon, we present the 3MT_French dataset. It contains a set of public speaking annotations collected on a crowd-sourcing platform through a novel annotation scheme and protocol. Global evaluation, persuasiveness, perceived self-confidence of the speaker and audience engagement were annotated on different time windows (i.e., the beginning, middle or end of the presentation, or the full video). This new resource will be useful to researchers working on public speaking assessment and training. It will allow to fine-tune the analysis of presentations under a novel perspective relying on socio-cognitive theories rarely studied before in this context, such as first impressions and primacy and recency theories. An exploratory correlation analysis on the annotations provided in the dataset suggests that the early moments of a presentation have a stronger impact on the judgements.
"Approaches to sentiment analysis of Hungarian political news at the sentence level"
Authors: Ring Orsolya , Szabó Martina Katalin , Guba Csenge , Váradi Bendegúz , Üveges István
Published: March 2024

Automated sentiment analysis of textual data is one of the central and most challenging tasks in political communication studies. However, the toolkits available are primarily for English texts and require contextual adaptation to produce valid results—especially concerning morphologically rich languages such as Hungarian. This study introduces (1) a new sentiment and emotion annotation framework that uses inductive approaches to identify emotions in the corpus and aggregate these emotions into positive, negative, and mixed sentiment categories, (2) a manually annotated sentiment data set with 5700 political news sentences, (3) a new Hungarian sentiment dictionary for political text analysis created via word embeddings, whose performance was compared with other available sentiment dictionaries. (4) Because of the limitations of sentiment analysis using dictionaries we have also applied various machine learning algorithms to analyze our dataset, (5) Last but not least to move towards state-of-the-art approaches, we have fine-tuned the Hungarian BERT-base model for sentiment analysis. Meanwhile, we have also tested how different pre-processing steps could affect the performance of machine-learning algorithms in the case of Hungarian texts.
DILLo: an Italian lexical database for speech-language pathologists
Authors: Beccaria Federica , Cristiano Angela , Pisciotta Flavio , Usardi Noemi , Borgogni Elisa , Prayer Galletti Filippo , Corsi Giulia , Gregori Lorenzo , Gagliardi Gloria
Published: March 2024

A novel lexical resource for treating speech impairments from childhood to senility: DILLo—Database Italiano del Lessico per Logopedisti (i.e., Italian Database for Speech-Language Pathologists) is presented. DILLo is a free online web application that allows extraction of filtered wordlists for flexible rehabilitative purposes. Its major aim is to provide Italian speech-language pathologists (SLPs) with a resource that takes advantage of Information and Communication Technologies for language in a healthcare setting. DILLo’s design adopts an integrated approach that envisages fruitful cooperation between clinical and linguistic professionals. The 7690 Italian words in the database have been selected based on phonological, phonotactic, and morphological properties, and their frequency of use. These linguistic features are encoded in the tool, which includes the orthographic and phonological transcriptions, and the phonotactic structure of each word. Moreover, most of the entries are associated with their respective ARASAAC pictogram, providing an additional and inclusive tool for treating speech impairments. The user-friendly interface is structured to allow for different and adaptable search options. DILLo allows Speech-Language Pathologists (SLPs) to obtain a rich, tailored, and varied selection of suitable linguistic stimuli. It can be used to customize the treatment of many impairments, e.g., Speech Sound Disorders, Childhood Apraxia of Speech, Specific Learning Disabilities, aphasia, dysarthria, dysphonia, and the auditory training that follows cochlear implantations.
A comprehensive environmental exposure indicator and respiratory health in asthmatic children: a case study
Authors: Cilluffo Giovanna , Sottile Gianluca , Ferrante Giuliana , Fasola Salvatore , Malizia Velia , Montalbano Laura , Ranzi Andrea , Badaloni Chiara , Viegi Giovanni , La Grutta Stefania
Published: March 2024

The primary goal of asthma management is to achieve and maintain asthma control, which can be influenced by environmental factors. This longitudinal study aimed to construct a comprehensive environmental indicator to predict asthma control in children with asthma in Palermo, Italy. The study included 179 asthmatic children aged 5–16 years. The Normalized Difference Vegetation Index (NDVI) was used to measure green cover, and the Coordination of Information on the Environment (CORINE) framework was used to assess land use based on each home address. A land use regression (LUR) model centered on the home address estimated NO2 exposure for each child using GIS. An environmental indicator, including environmental and personal exposure, was formulated using an additive value model approach. A logistic regression mixed model assessed the association between the environmental indicator and uncontrolled asthma. A probability map of uncontrolled asthma was constructed. In conclusion, a comprehensive environmental indicator proved effective in identifying areas at higher and lower risk of uncontrolled asthma.
ROBUST: 221 bugs in the Robot Operating System
Authors: Timperley Christopher S. , van der Hoorn Gijs , Santos André , Deshpande Harshavardhan , Wąsowski Andrzej
Published: March 2024

As robotic systems such as autonomous cars and delivery drones assume greater roles and responsibilities within society, the likelihood and impact of catastrophic software failure within those systems is increased. To aid researchers in the development of new methods to measure and assure the safety and quality of robotics software, we systematically curated a dataset of 221 bugs across 7 popular and diverse software systems implemented via the Robot Operating System (ROS). We produce historically accurate recreations of each of the 221 defective software versions in the form of Docker images, and use a grounded theory approach to examine and categorize their corresponding faults, failures, and fixes. Finally, we reflect on the implications of our findings and outline future research directions for the community.
Sustainability consciousness in primary schools: roles of leaders in the post/digital era
Authors: Uleanya Chinaza
Published: March 2024

Sustainability consciousness is pivotal to ensuring sustainability in schools. However, the roles of leaders are considered critical towards ensuring sustainability consciousness. Hence, this study explores the roles of school leaders in promoting sustainability consciousness considering scholarly submissions, using the case of South Africa. Systematic review method was adopted. Thus, Google search engine was adopted, and a search was done using identified key terms on SABINET as the selected database. The retrieved literature were sieved using inclusion and exclusion criteria as required by the adopted protocol of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses). From the analysed data, themes were generated. The findings of the study showed that educational changes are not capable of ensuring sustainability consciousness. Meanwhile, factors such as policy, curriculum and collaborative efforts are capable of hindering or promoting sustainability consciousness. Following the submission of scholars in the systematically analysed literature, the roles of leaders are put forward as recommendations towards ensuring sustainability consciousness in their various schools.
Evaluation of the performance of a CdZnTe-based soft $$\gamma $$-ray detector for CubeSat payloads
Authors: de Kuijper Kees , Diwan Rishank , Pal Partha Sarathi , Ritter Andreas , Parkinson Pablo M. Saz , Kong Andy C. T. , Parker Quentin A.
Published: March 2024

The low-energy $$\varvec{\gamma }$$

γ

-ray (0.1-30 MeV) sky has been relatively unexplored since the decommissioning of the COMPTEL instrument on the Compton Gamma-Ray Observatory (CGRO) satellite in 2000. However, the study of this part of the energy spectrum (the “MeV gap”) is crucial for addressing numerous unresolved questions in high-energy and multi-messenger astrophysics. Although several large MeV $$\varvec{\gamma }$$

γ

-ray missions like AMEGO and e-ASTROGAM are being proposed, they are predominantly in the developmental phase, with launches not anticipated until the next decade at the earliest. In recent times, there has been a surge in proposed CubeSat missions as cost-effective and rapidly implementable “pathfinder” alternatives. A MeV CubeSat dedicated to $$\varvec{\gamma }$$

γ

-ray astronomy has the potential to serve as a demonstrator for future, larger-scale MeV payloads. This paper presents a $$\varvec{\gamma }$$

γ

-ray payload design featuring a CdZnTe crystal calorimeter module developed by IDEAS. We report the detailed results of simulations to assess the performance of this proposed payload and compare it with those of previous $$\varvec{\gamma }$$

γ

-ray instruments.
Yet Another Lock-Free Atom Table Design for Scalable Symbol Management in Prolog
Authors: Moreno Pedro , Areias Miguel , Rocha Ricardo , Santos Costa Vítor
Published: March 2024

Prolog systems rely on an atom table for symbol management, which is usually implemented as a dynamically resizeable hash table. This is ideal for single threaded execution, but can become a bottleneck in a multi-threaded scenario. In this work, we replace the original atom table implementation in the YAP Prolog system with a lock-free hash-based data structure, named Lock-free Hash Tries (LFHT), in order to provide efficient and scalable symbol management. Being lock-free, the new implementation also provides better guarantees, namely, immunity to priority inversion, to deadlocks and to livelocks. Performance results show that the new lock-free LFHT implementation has better results in single threaded execution and much better scalability than the original lock based dynamically resizing hash table.
Health, Wellbeing and Empowerment E-workshops for Mothers of Children with Disabilities: A Non-randomised Comparison Study
Authors: Bourke-Taylor Helen M. , Leo Monica , Tirlea Loredana
Published: March 2024

Mothers of children with disabilities can experience compromised health. Targeted interventions require investigation to determine effectiveness. Healthy Mothers Healthy Families (HMHF) is a health, wellbeing and empowerment program that addresses mothers need to protect, and or, recover their own health due to caregiving impacts. This study compared the effectiveness of HMHF e-workshops online compared to no intervention. The HMHF e-workshops were delivered to 290 mothers across the 2020–2022 Covid-19 pandemic and 172 participated in research. The HMHF e-workshops included 3 online 2- hour workshops facilitated by credentialled peer-facilitators, closed online group chat, e-workbook and online learning package. Participants in both groups completed surveys pre and post the workshops (or control) over 8–10 weeks. Mothers who participated in HMHF significantly increased health help seeking behaviours (p < .001), and improved mental health and health behaviors over time: health behavior (p < .001), positive wellbeing (p < .004) and depression (p < .001) and stress symptoms (p = .005). Compared to controls, HMHF e-workshop participants significantly improved health behaviours (p < .001) and self-reported symptoms of depression (p = .002) and stress (p = .005) over 8–10 weeks. E-workshops were accessible and effective for mothers of children with high care needs and family responsibilities across the COVID-19 pandemic. Compared to no intervention, the HMHF intervention was more effective for improving healthy behaviours and mental health.
Non-equilibrium Dynamics of Vortices in Two-Dimensional Quantum Gases: Determining the Dynamical Scaling Region Using the Mahalanobis Distance
Authors: Tattersall Richard J. , Baggaley Andrew W. , Billam Thomas P.
Published: March 2024

When a system undergoes a rapid quench from a disordered to an ordered phase, it does not order instantly but instead relaxes towards equilibrium over time. During this relaxation, the dynamical scaling hypothesis predicts that the length scale of ordered regions increases, with later patterns statistically similar to earlier ones except for a change in global scale. Quantum gases are one of many systems in which such out of equilibrium behaviour is predicted to occur. Here, we present a method for systematically testing when dynamical scaling is taking place, by quantifying the similarity of the rescaled two-point correlation function over time using the Mahalanobis distance. Data on the velocity field of a two-dimensional quantum fluid, generated from point vortex simulations, are used to illustrate the application of this method.
Maximum a posteriori Bayesian methods out-perform non-compartmental analysis for busulfan precision dosing
Authors: Hughes Jasmine H. , Long-Boyle Janel , Keizer Ron J.
Published: March 2024

Dose personalization improves patient outcomes for many drugs with a narrow therapeutic index and high inter-individuality variability, including busulfan. Non-compartmental analysis (NCA) and model-based methods like maximum a posteriori Bayesian (MAP) approaches are two methods routinely used for dose optimization. These approaches vary in how they estimate patient-specific pharmacokinetic parameters to inform a dose and the impact of these differences is not well-understood. Using busulfan as an example application and area under the concentration–time curve (AUC) as a target exposure metric, these estimation methods were compared using retrospective patient data (N = 246) and simulated precision dosing treatment courses. NCA was performed with or without peak extension, and MAP Bayesian estimation was performed using either the one-compartment Shukla model or the two-compartment McCune model. All methods showed good agreement on real-world data (correlation coefficients of 0.945–0.998) as assessed by Bland–Altman plots, although agreement between NCA and MAP methods was higher during the first dosing interval (0.982–0.994) compared to subsequent dosing intervals (0.918–0.938). In dose adjustment simulations, both NCA and MAP estimated high target attainment (> 98%) although true simulated target attainment was lower for NCA (63–66%) versus MAP (91–93%). The largest differences in AUC estimation were due to different assumptions for the shape of the concentration curve during the infusion phase, followed by how the methods considered time-dependent clearance and concentration–time points collected in earlier intervals. In conclusion, although AUC estimates between the two methods showed good correlation, in a simulated study, MAP lead to higher target attainment. When changing from one method to another, or changing infusion duration and other factors, optimum estimated exposure targets may require adjusting to maintain a consistent exposure.
Neural Data Augmentation for Legal Overruling Task: Small Deep Learning Models vs. Large Language Models
Authors: Sheik Reshma , Siva Sundara K. P. , Nirmala S. Jaya
Published: March 2024

Deep learning models produce impressive results in any natural language processing applications when given a better learning strategy and trained with large labeled datasets. However, the annotation of massive training data is far too expensive, especially in the legal domain, due to the need for trained legal professionals. Data augmentation solves the problem of learning without labeled big data. In this paper, we employ pre-trained language models and prompt engineering to generate large-scale pseudo-labeled data for the legal overruling task using 100 data samples. We train small recurrent and convolutional deep-learning models using this data and fine-tune a few other transformer models. We then evaluate the effectiveness of the models, both with and without data augmentation, using the benchmark dataset and analyze the results. We also test the performance of these models with the state-of-the-art GPT-3 model under few-shot setting. Our experimental findings demonstrate that data augmentation results in better model performance in the legal overruling task than models trained without augmentation. Furthermore, our best-performing deep learning model trained on augmented data outperforms the few-shot GPT-3 by 18% in the F1-score. Additionally, our results highlight that the small neural networks trained with augmented data achieve outcomes comparable to those of other large language models.
Sensitivity to morphological spelling regularities in Chinese-English bilinguals and English monolinguals
Authors: Iwao Haruka Sophia , Andrews Sally , Veldre Aaron
Published: March 2024

Evidence of sensitivity to graphotactic and morphological patterns in English spelling has been extensively examined in monolinguals. Comparatively few studies have examined bilinguals’ sensitivity to spelling regularities. The present study compared late Chinese-English bilinguals and English monolinguals on their sensitivity to systematic inflectional and derivational spelling regularities. One hundred and twenty-nine undergraduate students completed a forced-choice spelling task, in which nonword pairs were presented in a sentence context requiring a choice of the relevant grammatical form. English ability measures were administered to examine possible inter-individual differences in morphological sensitivity. The results showed that both monolingual and bilingual participants demonstrated knowledge of spelling patterns, but the groups differed in their sensitivity to inflectional and derivational spelling regularities. Specifically, bilinguals showed more consistent use of morphological spelling regularities in guiding their decision on spelling choice compared to monolinguals. The results are argued to be consistent with the predictions of statistical learning accounts of spelling acquisition.
Is Generation Z more Inclined than Generation Y to Purchase Sustainable Clothing?
Authors: Masserini Lucio , Bini Matilde , Difonzo Marica
Published: March 2024

Increasing clothing (over)consumption, supported by the fast fashion industry, has caused a significant reduction in clothing costs, raised major sustainability challenges, and highlighted the need for engaging in more sustainable consumption behaviour to mitigate the negative environmental, social, and economic consequences. Although green purchase behaviour is now well understood, extant literature still lacks a comprehensive approach to explain consumers behaviour (especially that of the younger generations) with respect to sustainable clothing. Using survey data collected through a structured questionnaire, this study aims to assess whether Generation Z is more inclined to buy sustainable or eco-friendly clothing than Generation Y. Given the non-random selection of respondents, analysis was conducted using propensity score matching to correct for potential bias based on a set of observable confounders. The results show that Generation Z is more likely to buy second-hand clothing, whereas Generation Y is more interested in clothes made of organic and eco-sustainable fabrics.
Staggered deployment of gunshot detection technology in Chicago, IL: a matched quasi-experiment of gun violence outcomes
Authors: Connealy Nathan T. , Piza Eric L. , Arietti Rachael A. , Mohler George O. , Carter Jeremy G.
Published: March 2024

Objectives

We examine the potential effects of gunshot detection technology longitudinally in Chicago through a synthetic control quasi-experiment.

Methods

Police districts receiving gunshot detection technology were compared to a synthetic control unit via a staggered difference-in-difference design. Across eleven unique gunshot detection technology deployment phases, the analyses produce results for aggregate, initial versus expanded, and phase-specific deployment effects across five gun violence outcome measures.

Results

Gunshot detection technology had no effect on fatal shootings, non-fatal shootings, general part I gun crimes, or shots fired calls for service. Gun recoveries significantly increased in the aggregate, initial, and expanded models, and in several individual phases relative to controls.

Conclusions

The results align with prior literature that has found a procedural benefit, but not a crime prevention benefit, of gunshot detection technology. Law enforcement agencies seeking crime prevention or reduction solutions may be better served by investing in other options.
Development of sustainable hydromorphic Technosols within artificial wetlands in mining landscapes: the effects of wastewater and hydrothermal geological materials
Authors: Díaz-Ortega J. , Rivera-Uria Y. , López-Mendoza E. , Sedov S. , Romero F. , Solleiro-Rebolledo E. , Martínez-Jardines L. G.
Published: March 2024

Purpose

The Buenavista del Cobre mine is in a semiarid environment in NW Mexico. A part of the mine tailings dam has been flooded with wastewater from Cananea, generating an artificial wetland. The main objectives of this work were to evaluate the effect of wastewater on the pedogenesis of wetland Technosols developed on mine tailings and to compare them with the soil of non-irrigated tailings and with a natural soil profile.

Materials and methods

Three profiles were studied inside the dam as follows: a profile under waterlogging conditions, a profile under conditions of periodic sewage saturation, and a profile with no waterlogging conditions. Laboratory methods included the micromorphological analysis of the soil structure and pedo-features, fertility properties, identification of clay minerals, and analysis of bulk chemical composition.

Results and discussion

It was found that the biogenic structure and voids associated with organic materials were the main micromorphological features of the studied wetland Technosols. Primary sulfides remained unaltered in the Technosols irrigated with wastewater, whereas incipient sulfide oxidation was observed in the non-irrigated tailings. Chlorite and smectite were detected in the Technosols. Such mineral assemblage was found to be mostly generated by hydrothermal processes.

Conclusion

Irrigation of tailings with wastewater supported the biological aggregation and porosity formation within the soil matrix, supplied plant nutrients, and enhanced the ecological soil quality of the studied hydromorphic Technosols. Saturation with wastewater hampered the oxidation of primary sulfides in the hydromorphic Technosols, preventing soil acidification and the mobilization of heavy metal contaminants.
Abundance, distribution, and ecological/environmental risks of critical rare earth elements (REE) in phosphate ore, soil, tailings, and sediments: application of spectroscopic fingerprinting
Authors: Khelifi Faten , Batool Sadia , Kechiched Rabah , Padoan Elio , Ncibi Kaouther , Hamed Younes
Published: March 2024

Purposes

This research focuses on the characterization of phosphate ore, its solid effluents, and nearby contaminated soils in the southwest Tunisia (Gafsa-Metlaoui Basin). It aims also at evaluating the vertical distribution and abundance of critical rare earth elements (REE) in the different materials and their ecological and environmental risks.

Materials and methods

The sampled materials went through physical, chemical, and mineralogical characterization which involved XRF, XPS, XRD, and ICP-MS analyses. The REE anomalies and the environmental and ecological indices were calculated.

Results and discussions

Results show relatively high concentrations of nine rare REEs, following the sequence La > Ce > Nd > Y > Gd > Eu > Sm > Yb > Tb and trace metal elements (TME) such as Cd, Cr, Mn, Zn, Co, Fe, Sr, Cu, Ni, Pb, Ba that surpass, in some cases, international standards. The vertical distribution of the studied elements within a sediment, tailings, and soil profiles (beyond 20 cm of depth) indicates their likely in-depth migration. TME- and REE-bearing phosphate samples reflect mostly oxic conditions in the southern area with high positive Eu anomalies signifying possible mixing of sources. The environmental assessment indicate no contamination and a moderate enrichment of REEs, except for Eu, which displays significant contamination and extreme enrichment. Whereas, a deficiency of Y has been detected in most of the studied samples except for sludge sample which was also found significantly enriched with REE.

Conclusions

There are fundamental similarities between the different studied samples with high carbonate mineral concentrations. Statistical analysis confirmed the spectroscopic fingerprints demonstrating that the different materials share a similar composition. All of these similarities are most likely linked to the impact of mining activities on sediments and soils. Overall, our findings highlight the global effect of ore processing in determining the geochemical and the mineralogical characteristics of the surrounding environments of mines.
Opening Eyes on Seedling Tuber Quality in Potato: Size Matters
Authors: Stockem Julia E. , Bus Merijn D. , de Vries Michiel E. , Struik Paul C.
Published: March 2024

For potato, diploid hybrid breeding is a novel breeding technique that speeds up the development of new varieties. A consequence of hybrid breeding is the introduction of hybrid true potato seeds as starting material. From these seeds, seedling tubers can be produced in one field season, to use as starting material for a seed or a ware crop in the following year. For breeding purposes as well as for seed crop and ware crop production, it is essential to produce seedling tubers of high quality. The production of seedling tubers is a new step in the potato production chain; therefore, we investigated the effect of tuber quality traits on plant development and yield. With similar seedling tuber weight, more eyes per seedling tuber led to more stems per plant. This was compensated by a lower number of tubers per stem resulting in an equal total tuber number and weight per plant at the end of the growing season. A higher seedling tuber weight led to a higher soil cover in the field. Hybrid potato plants grown from larger seedling tubers produced a greater total tuber weight per plant than plants grown from smaller tubers, while number of eyes and stems per tuber had no effect on final yield when using equal seedling tuber weight.
Identifying the supportive care needs of people affected by non-muscle invasive bladder cancer: An integrative systematic review
Authors: Schubach Kathryn , Niyonsenga Theo , Turner Murray , Paterson Catherine
Published: March 2024

Purpose

To understand supportive care needs among people with non-muscle invasive bladder cancer (NMIBC).

Methods

An integrative systematic review was reported using the Preformed Reporting Items for Systematic Review and Meta-analyses (PRISMA) guidelines. Seven electronic databases were searched for relevant studies, including all quantitative, qualitative, and mixed methods studies, irrespective of research design. The review process was managed by Covidence systematic review software. Two reviewer authors independently performed data extraction using eligibility criteria. Quality appraisal was conducted, and a narrative synthesis was performed.

Results

A total of 1129 articles were screened, of which 21 studies met the inclusion criteria. The findings revealed that the frequency of supportive care needs reported by NMIBC participants included psychological/emotional (16/21:76%), physical (16/21:76%), practical (8/21:38%), interpersonal/intimacy (7/21:33%), family-related (7/21:33%), health system/information (5/21:23%), social (4/21:19%), patient-clinician communication (3/21:14%), spiritual (1/21:5%) and daily needs (1/21:5%).

Conclusion

People affected by NMIBC experience anxiety, depression, uncertainty, and fear of recurrence. The physical symptoms reported included urinary issues, pain, sleeping disorders and fatigue. These supportive care needs persist throughout the participants' treatment trajectory and can impact their quality of life.

Implications for Cancer Survivors

Identifying supportive care needs within the NMIBC population will help inform future interventions to provide patient-centred care to promote optimal well-being and self-efficacy for people diagnosed with NMIBC.