bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Review of Studies Using Machine Learning to Detect Voice Biomarkers for Depression
Authors: Donaghy Philip , Ennis Edel , Mulvenna Maurice , Bond Raymond , Kennedy Niamh , McTear Mike , O’Connell Henry , Blaylock Nate , Brueckner Raymond 
Published: December 2024

AbstractVoice biomarkers developed using machine learning are a promising potential biomarker for mental disorders, including depression. This paper presents a narrative review with a systematic search of the evidence surrounding the efficacy of voice biomarkers as indicators of depression. The review considers two research questions: (i) What is the efficacy of voice biomarkers as potential biomarkers for depression? (ii) What are the variations in the samples and design methodologies employed? Nineteen papers were identified as examining voice biomarkers for depression using machine learning methods between January 2019 and February 2022. A subset of guidelines recommended in a previous systematic review was selected and adapted to investigate aspects of the field since that review. Seventeen studies used classification methods, and two used regression methods. Within the papers that examined classification, sensitivity (recall) was used by 76% of papers, accuracy by 65%, AUC by 59%, and F1 score by 59%. From these papers, the average performance achieved for the following metrics was 0.78 for sensitivity (recall), 0.76 for F1 score, and 0.78 for AUC. This review found that the efficacy of vocal biomarkers as indicators for depression is below that of the PHQ-9 form, a tool commonly used in psychology. The PHQ-9 can serve as a benchmark against which to compare these models. Difficulties were observed in comparing these models due to the variety of performance metrics used. Recommendations are presented as to how the generalisability of these models may be strengthened, e.g., testing on unseen data after models are developed.
The contribution of biophysical and biochemical CO2 concentration mechanisms to the carbon fixation of the green macroalga Ulva prolifera
Authors: Zhang Xiaohua , Gao Guang , Gao Zhengquan , Gao Kunshan , Liu Dongyan 
Published: December 2024

AbstractCO2 concentration mechanisms (CCMs) are important in maintaining the high efficiency of photosynthesis of marine algae. Aquatic photoautotrophs have two types of CCMs: biophysical CCMs, based on the conversion of inorganic carbon, and biochemical CCMs, based on the formation of C4 acid intermediates. However, the contribution of biophysical and biochemical CCMs to algal carbon fixation remains unclear. Here, we used ethoxyzolamide (EZ) inhibitors of carbonic anhydrase and 3-mercaptopicolinic acid (MPA) inhibitors for phosphoenolpyruvate carboxykinase to examine the importance of biophysical and biochemical CCMs in photosynthesis of the green macroalga Ulva prolifera. The culture experiments showed that the carbon fixation of the species declined when EZ inhibited the biophysical CCM, while the increase in cyclic electron flow around the photosystem I indicated a more active biochemical CCM, contributing to ~ 50% of total carbon fixation. The biophysical CCM was also reinforced when MPA inhibited the biochemical CCM. In a comparison, the biophysical CCM can compensate for almost 100% of total carbon fixation. The results indicate that biophysical CCMs dominate the process of carbon fixation of U. prolifera while biochemical CCM plays a supporting role. Our results provide evidence of a complementary coordination mechanism between the biophysical and biochemical CCMs that promotes the efficiency of photosynthesis of U. prolifera, an efficient mechanism to boost the alga’s bloom.
Dictamnine Reduces Gestational Diabetic Complications in Streptozotocin-Induced Diabetic Pregnant Rats via Regulating Inflammation and NOX-2, MCP-1/AGE–RAGE Pathway
Authors: Wang Lan , Gao Ji , Zhang Juan , Liu Songchun , Zhao Jing 
Published: December 2024

Abstract
Gestational diabetes mellitus is a type of diabetes that arises during pregnancy. Around 15–25% of pregnancies are affected by gestational diabetes mellitus, which involves hyperglycemia, insulin resistance, and abnormal fetal development. The present work was conducted to reveal the therapeutic potentials of dictamnine against streptozotocin-induced gestational diabetes mellitus in rats. To induce gestational diabetes mellitus, pregnant rats were administered the streptozotocin, and subsequently, the gestational diabetes mellitus rats were given dictamnine for 14 days. Following the end of treatments, the body weight, blood glucose, and fetus and placental weights were measured. The concentrations of biochemical markers, including fasting insulin, HbA1c, and hepatic glycogen, were analyzed. The lipid profiles, antioxidant levels, apoptotic proteins, and inflammatory cytokine levels were measured using the test kits. A histopathological investigation was conducted on the pancreatic tissues obtained from the experimental rats. Dictamnine treatment at concentrations of 15 and 30 mg/kg successfully reduced glucose levels, increased body weight, and regulated insulin and other biochemical marker levels in rats with gestational diabetes mellitus. The treatment of dictamnine resulted in an increase in the antioxidant levels, successfully lowered the lipid markers in the rats with gestational diabetes mellitus. The treatment with dictamnine also reduced the inflammatory cytokines, apoptotic proteins, and other molecular markers in the gestational diabetes mellitus rats. The histological study of pancreatic tissues likewise confirmed the therapeutic capabilities of dictamnine. The results of the current study emphasize that dictamnine has a positive effect on reducing gestational diabetes mellitus in rats.

Graphical Abstract
Enhancing Personalized Service Development with Virtual Agents and Upcycling Techniques
Authors: Nakata Takuya , Chen Sinan , Saiki Sachio , Nakamura Masahide 
Published: December 2024

AbstractIn this study, aimed at achieving Society 5.0, we explore efficient development methods for services tailored to individual user needs. The diversification of user demographics has led to swiftly changing service demands, increasing the necessity for personalized adaptation. However, developing services tailored to individual users requires specialized knowledge and incurs high costs. This research focuses on developing technologies that enable service development through a concrete understanding of user needs. Utilizing an interactive needs extraction system with a virtual agent (VA) developed in prior studies, along with the Sharing Upcycling Cases with Context and Evaluation for Efficient Software Development (SUCCEED) system, we aim to automate the extraction of user needs and provide developers with relevant insights. Prior research has found it challenging to grasp the outline of services to be developed from user statements. However, a new method using large language models (LLM) has enabled the automatic extraction of novel service needs. Experiments have shown the potential to automatically provide development insights for 67% of ideal needs.
Testing a proposed mathematical model of weight loss in women enrolled on a commercial weight-loss programme: the LighterLife study
Authors: Egan Aoife M. , Rayman John F. , Collins Adam L. 
Published: December 2024

Abstract
Weight loss results in obligatory reductions in energy expenditure (EE) due to loss of metabolically active fat-free mass (FFM). This is accompanied by adaptive reductions (i.e. adaptive thermogenesis) designed to restore energy balance while in an energy crisis. While the ‘3500-kcal rule’ is used to advise weight loss in clinical practice, the assumption that EE remains constant during energy restriction results in a large overestimation of weight loss. Thus, this work proposes a novel method of weight-loss prediction to more accurately account for the dynamic trajectory of EE. A mathematical model of weight loss was developed using ordinary differential equations relying on simple self-reported inputs of weight and energy intake to predict weight loss over a specified time. The model subdivides total daily EE into resting EE, physical activity EE, and diet-induced thermogenesis, modelling obligatory and adaptive changes in each compartment independently. The proposed model was tested and refined using commercial weight-loss data from participants enrolled on a very low-energy total-diet replacement programme (LighterLife UK, Essex). Mathematical modelling predicted post-intervention weight loss within 0.75% (1.07 kg) of that observed in females with overweight or obesity. Short-term weight loss was consistently underestimated, likely due to considerable FFM reductions reported on the onset of weight loss. The best model agreement was observed from 6 to 9 weeks where the predicted end-weight was within 0.35 kg of that observed. The proposed mathematical model simulated rapid weight loss with reasonable accuracy. Incorporated terms for energy partitioning and adaptive thermogenesis allow us to easily account for dynamic changes in EE, supporting the potential use of such a model in clinical practice.
Gut parasites of alpacas (Vicugna pacos) raised in Poland
Authors: Szopieray K. , Templin J. , Osten-Sacken N. , Jaśkowski J.M. , Żbikowska E. 
Published: December 2024

Summary
This study aimed to determine the prevalence of gastrointestinal parasites in alpacas on selected farms in Poland. In July and August 2019 and August 2021, 223 samples from six commercial farms were examined using coproscopic techniques. The total percentage of alpacas infected with intestinal parasites was 57.7%. Eggs of Nematodirus sp. were found in 28.9%, Trichostrongylus sp. in 15.5%, Strongyloides sp. in 13.4%, Camelostrongylus sp. in 11.3%, other strongyle-type in 12.4%, Trichuris sp. in 3.1%, Capillaria spp. in 2.1%, Oesophagostomum sp. in 1.0% and eggs of Moniezia sp. in 1.0% of individuals. Oocysts of Eimeria macusaniensis were found in 8.2%, Eimeria sp. in 4.1%, and Cryptosporidium sp. in 3.1% of animals. Redundancy analysis showed that parasites and their number in faeces were related to the individual’s country of origin, sex and age. Females had significantly more eggs of parasites than males. More significant parasite infection was recorded in younger individuals. Moreover, the most infected were individuals from Germany. Some of the described parasites in tested alpacas have zoonotic potential. Due to the possibility of introducing parasites native to alpacas and acquiring species parasitising wild and farmed animals in Europe, permanent veterinary monitoring of animals imported from other regions is necessary.
First report of the pygmy slipper lobster Biarctus sordidus (Crustacea, Decapoda) in the Red Sea following the finding of its phyllosoma larva
Authors: Guy-Haim Tamar , Farstey Viviana , Iakovleva Anastasiia , Spanier Ehud , Morov Arseniy R. 
Published: December 2024

Abstract
The advent of integrative taxonomy in plankton research, employing molecular and morphology-based identification, promotes the discovery of new biodiversity records, especially of larval stages. The slipper lobster family Scyllaridae consists of planktonic phyllosoma larvae, persisting weeks to many months in the water column. High interspecific larval similarities and inconsistent delineation of stages have hindered the identification of scyllarid phyllosomata to the species level using morphological characteristics. Here we report the first record of the pygmy slipper lobster, Biarctus sordidus, in the Red Sea following the finding of its phyllosoma larva, extending its known distribution from the Persian Gulf to Australia and southern China. We identified the phyllosoma collected from the Northern Gulf of Aqaba as B. sordidus using the mitochondrial 16S and 18S rRNA genes, and described its morphology to determine the larval stage. We further discuss the potential factors contributing to the delayed detection of this species.
Maternal input, not transient elevated depression and anxiety symptoms, predicts 2-year-olds’ vocabulary development
Authors: Xu Rattanasone Nan , Brookman Ruth , Kalashnikova Marina , Grant Kerry-Ann , Burnham Denis , Demuth Katherine 
Published: December 2024

Abstract
Both the quantity and quality of the maternal language input are important for early language development. However, depression and anxiety can negatively impact mothers’ engagement with their infants and their infants’ expressive language abilities. Australian mother-infant dyads (N = 30) participated in a longitudinal study examining the effect of maternal language input when infants were 24 and 30 months and maternal depression and anxiety symptoms on vocabulary size. Half the mothers had elevated depression and anxiety symptoms during at least one point in the study (at 6, 12, 18, 24, or 30 months). The results showed that only maternal input measures (word tokens, types, and mean length of utterance) predicted vocabulary size. While no evidence was found that brief periods of maternal depression and anxiety negatively impacted early vocabulary development, the findings highlight the critical importance and possible mitigating effects of maintaining good quality mother–infant interactions during early development.
Emerging trends: evaluating general purpose foundation models
Authors: Church Kenneth Ward , Alonso Omar 
Published: December 2024

AbstractWe suggest that foundation models are general purpose solutions similar to general purpose programmable microprocessors, where fine-tuning and prompt-engineering are analogous to coding for microprocessors. Evaluating general purpose solutions is not like hypothesis testing. We want to know how well the machine will perform on an unknown program with unknown inputs for unknown users with unknown budgets and unknown utility functions. This paper is based on an invited talk by John Mashey, “Lessons from SPEC,” at an ACL-2021 workshop on benchmarking. Mashey started by describing Standard Performance Evaluation Corporation (SPEC), a benchmark that has had more impact than benchmarks in our field because SPEC addresses an import commercial question: which CPU should I buy? In addition, SPEC can be interpreted to show that CPUs are 50,000 faster than they were 40 years ago. It is remarkable that we can make such statements without specifying the program, users, task, dataset, etc. It would be desirable to make quantitative statements about improvements of general purpose foundation models over years/decades without specifying tasks, datasets, use cases, etc.
Characterising the extent and nature of digital food and beverage marketing in Singapore: a descriptive study
Authors: Chua Xin Hui , Whitton Clare , Vandevijvere Stefanie , Kelly Bridget , van Dam Rob M , Rebello Salome A 
Published: December 2024

Abstract

Objective:

To characterise the nature of digital food and beverage advertising in Singapore.

Setting:
Food and beverage advertisements within twenty clicks on the top twelve non-food websites and all posts on the Facebook and Instagram pages of fifteen major food companies in Singapore were sampled from 1 January to 30 June 2018.

Design:
Advertised foods were classified as being core (healthier), non-core or mixed dishes (e.g. burger) using the WHO nutrient profile model and national guidelines. Marketing techniques were assessed using published coding frameworks.

Participants:
NA

Results:
Advertisements (n 117) on the twelve non-food websites were largely presented as editorial content. Food companies posted twice weekly on average on social media sites (n 1261), with eatery chains posting most frequently and generating the largest amount of likes and shares. Key marketing techniques emphasised non-health attributes, for example, hedonic or convenience attributes (85 % of advertisements). Only a minority of foods and beverages advertised were core foods (non-food website: 16·2 %; social media: 13·5 %).

Conclusions:
Top food and beverage companies in Singapore actively use social media as a platform for promotion with a complex array of marketing techniques. A vast majority of these posts were unhealthy highlighting an urgent need to consider regulating digital food and beverage advertising in Singapore.
Walk the green talk? A textual analysis of pension funds' disclosures of sustainable investing
Authors: Bauer Rob , Broeders Dirk , van Ool Annick 
Published: December 2024

Abstract
We analyze the disclosures of sustainable investing by Dutch pension funds in their annual reports by introducing a novel textual analysis approach using state-of-the-art natural language processing techniques to measure the awareness and implementation of sustainable investing. We find that a pension fund's size increases both the awareness and implementation of sustainable investing. Moreover, we analyze the role of signing a sustainable investment initiative. Although signing this initiative increases the specificity of pension fund statements about sustainable investing, we do not find an effect on the implementation of sustainable investing.
The incidence of Social Security taxes on teacher wages and employment
Authors: Kim Dongwoo , Koedel Cory , Gorina Eugenia , Harrington James 
Published: December 2024

Abstract
We study the incidence of Social Security taxes on teacher wages and employment. On average, we estimate teachers with Social Security coverage take home 9.6 percent less in wages than observationally similar teachers in similar districts without Social Security coverage. This accounts for about three-fourths of the 12.4-percent total Social Security tax. Moreover, our analysis suggests this is likely a lower-bound estimate of the true incidence of Social Security taxes – under reasonable assumptions, we cannot rule out full (100%) tax incidence on teacher wages. We find no evidence of tax incidence on teacher staffing levels.
US public opinion about interior border checkpoints and health care access for undocumented immigrants
Authors: Crudo Blackburn Christine , Haeder Simon F. 
Published: December 2024

Abstract
Legal status is an important social determinant of health. Immigration enforcement policies may be an important contributor to health disparities in the form of interior border checkpoints (IBCs). These checkpoints may prevent immigrants and their families from seeking needed medical care. Currently, we do not know how these barriers are perceived by the public. We administered a survey of 6,178 respondents from 13 November to 19 November of 2023 that contained a survey experiment to assess public attitudes on the issue. Respondents were generally not supportive of detaining individuals at IBCs or medical facilities for emergencies regardless of characteristics of the care-seeking individual. A majority was supportive of detention when medical treatment was complete. Respondents were generally more sympathetic towards children and pregnant women. Partisanship and sympathy expressed towards immigrants influenced attitudes towards detention. Findings based on race and ethnicity showed inconsistencies. A majority of Americans did not believe that IBCs should impede undocumented immigrants from accessing medical care, especially in emergency situations and for children and pregnant women. Our findings indicate that there is broad public support for expanding existing policies to allow for undocumented individuals to pass through IBCs to access medical care.
Vetoes, deadlock and deliberative umpiring: Toward a proportionality doctrine for power-sharing constitutions
Authors: Levy Ron , O’Flynn Ian 
Published: December 2024

Abstract
This article addresses power-sharing constitutions that include powers of veto wielded by discrete ethnonational groups. Such constitutional arrangements – seen, for example, in Northern Ireland and Bosnia – have often prompted severe deadlock, a problem that in turn threatens democratic functioning and raises the risk of renewed communal violence. We consider the use of ‘umpires’ of power-sharing constitutional systems to vet the use of vetoes and (potentially) to prevent their overuse or misuse. Power-sharing umpires are not uncommon in practice. However, as yet there is little scholarship evaluating how, in substance, power-sharing veto umpires should approach their task. Relying on deliberative democracy theory, the article outlines three forms of ‘deliberative agreement’ that, in principle, deeply divided groups may reach in the course of policymaking. It goes on to explain how existing proportionality doctrines drawn from federalism and rights cases can be imported into the power-sharing context to ‘scaffold’ these broad ideals. This approach, it is argued, may provide a more detailed, coherent and practically workable approach to umpiring power-sharing constitutions.
Improving GCM‐Based Decadal Ocean Carbon Flux Predictions Using Observationally‐Constrained Statistical Models
Authors: Gooya P. , Swart N. C. , Landschützer P. 
Published: December 2024

AbstractAn essential step toward meeting agreed climate targets and policies is the ability to understand and predict near‐term changes in global carbon cycle, and importantly, ocean carbon uptake. Initialized climate model simulations have proven skillful for near‐term predictability of the key physical climate variables, for example, temperature, precipitation, etc. By comparison, predictions of biogeochemical fields like ocean carbon flux, are still emerging. Initial studies indicate skillful predictions are possible for lead‐times up to 6 years at global scale for some CMIP6 models. However, unlike core physical variables, biogeochemical variables are not directly initialized in existing decadal prediction systems, and extensive empirical parametrization of ocean‐biogeochemistry in Earth System Models introduces a significant source of uncertainty. Here we propose a new approach for improving the skill of decadal ocean carbon flux predictions using observationally‐constrained statistical models, as alternatives to the ocean‐biogeochemistry models. We use observations to train multi‐linear and neural‐network models to predict the ocean carbon flux. To account for observational uncertainties, we train using six different observational estimates of the flux. We then apply these trained statistical models using input predictors from the Canadian Earth System Model (CanESM5) decadal prediction system to produce new decadal predictions. Our hybrid GCM‐statistical approach significantly improves prediction skill, relative to the raw CanESM5 hindcast predictions over 1990–2019. Our hybrid‐model skill is also larger than that obtained by any available CMIP6 model. Using bias‐corrected CanESM5 predictors, we make forecasts for ocean carbon flux over 2020–2029. Both statistical models predict increases in the ocean carbon flux larger than the changes predicted from CanESM5 forecasts. Our work highlights the ability to improve decadal ocean carbon flux predictions by using observationally‐trained statistical models together with robust input predictors from GCM‐based decadal predictions.