bluuebunny/crossref_metadata_2025_split huggingface dataset:
Revolutionizing waste from household plastics to eco-friendly diesel alternatives through catalytic degradation with biogas utilization
Authors: J Nishanth Jude Roy , P Premkumar , Iqbal Shajahan Mohamed , V Elangkathir 
Published: July 2024

Abstract
The study tackled the pressing environmental issue of managing both biodegradable and non-biodegradable household plastic waste, aiming to convert this waste into valuable hydrocarbons, thus addressing critical concerns over plastic pollution and the quest for renewable energy sources. In the context of escalating environmental degradation and the urgent need for sustainable alternatives to fossil fuels, the ability to transform various forms of waste into energy presents a significant stride towards ecological and energy sustainability. Utilizing an innovative methodology, the research employed catalytic degradation of mixed plastic waste, leveraging fly ash as a catalyst and biogas produced from a combination of cow dung and kitchen waste as a renewable and sustainable heat source. This process was fine-tuned across several catalyst-to-polymer (cat/pol) ratios, specifically 0.10, 0.15, and 0.20, with detailed documentation of the degradation temperatures and yields of liquid and gaseous hydrocarbons for each 1 kg batch of plastic waste. Notably, at a cat/pol ratio of 0.20, a remarkable 100% conversion rate was achieved, highlighting the efficiency of this method. Following this, the resultant oil was segmented based on boiling points for further analysis and evaluation of its utility as a diesel fuel substitute. Significant findings include the highest liquid hydrocarbon yield of 65.1% at 378 °C, achieved with the 0.20 cat/pol ratio. Moreover, fractions boiling above 100 °C were identified to possess superior heating values and cetane numbers compared to conventional diesel, particularly the fraction boiling at 100 °C–150 °C (C2), which demonstrated optimal performance and combustion qualities. This fraction achieved a maximum brake thermal efficiency of 32.92%, exhibited low smoke density and hydrocarbon emissions of 48 HSU and 32ppm, but it also resulted in a significant increase in NOx emission. Among all the fractions, diesel C2 was observed to be the best in terms of performance & combustion and was lower in emission. The conclusions drawn underscore the method’s potential to mitigate plastic pollution and reduce fossil fuel reliance by converting both biodegradable and non-biodegradable waste into useful energy. This study’s novelty lies in its comprehensive approach to waste management and energy recovery, significantly advancing over previous literature by achieving a 100% conversion rate at a specific cat/pol ratio and optimizing the output for use as a diesel alternative. It stands out by producing a fraction with both high efficiency and lower emissions, offering a scalable, sustainable solution to waste management challenges and paving the way for future innovations in sustainable energy production.
A physics based model for negative capacitance TFET considering variation in ferroelectric parameters
Authors: Chaudhary Shalini , Dewan Basudha , Singh Devenderpal , Yadav Menka 
Published: July 2024

Abstract
Here, an explicit analytical model of electrical properties like channel potential, electric field, drain current, and threshold voltage for a negative capacitance DGTFET structure is developed. The model properly calculates the channel potential profile by solving the Poisson equation using the Landau-Khalatnikov (LK) model (for incorporating the NC effect). The electric field expression is developed using a channel potential model. The drain current expression is obtained by mathematically integrating the rate of band-to-band tunneling generation over the channel thickness. The threshold voltage has been derived using a method called maximal trans-conductance. Furthermore, by varying the FE parameters like thickness (t
fe
), coercive field (E
C
), and residual polarization (P
R
), we improve capacitance matching and gate control of the device. All of the model results demonstrated a perfect alignment with those discovered by TCAD simulations. Designing devices and circuits for low-power applications can be more effective from these results.
Simulation-based inference on virtual brain models of disorders
Authors: Hashemi Meysam , Ziaeemehr Abolfazl , Woodman Marmaduke M , Fousek Jan , Petkoski Spase , Jirsa Viktor K 
Published: July 2024

Abstract
Connectome-based models, also known as virtual brain models (VBMs), have been well established in network neuroscience to investigate pathophysiological causes underlying a large range of brain diseases. The integration of an individual’s brain imaging data in VBMs has improved patient-specific predictivity, although Bayesian estimation of spatially distributed parameters remains challenging even with state-of-the-art Monte Carlo sampling. VBMs imply latent nonlinear state space models driven by noise and network input, necessitating advanced probabilistic machine learning techniques for widely applicable Bayesian estimation. Here we present simulation-based inference on VBMs (SBI-VBMs), and demonstrate that training deep neural networks on both spatio-temporal and functional features allows for accurate estimation of generative parameters in brain disorders. The systematic use of brain stimulation provides an effective remedy for the non-identifiability issue in estimating the degradation limited to smaller subset of connections. By prioritizing model structure over data, we show that the hierarchical structure in SBI-VBMs renders the inference more effective, precise and biologically plausible. This approach could broadly advance precision medicine by enabling fast and reliable prediction of patient-specific brain disorders.
Proton dose deposition matrix prediction using multi-source feature driven deep learning approach
Authors: Zhou Peng , Jiao Shengxiu , Zhao Xiaoqian , Yao Shuzhan , Xu Honghao , Chen Chuan 
Published: July 2024

Abstract
Proton dose deposition results are influenced by various factors, such as irradiation angle, beamlet energy and other parameters. The calculation of the proton dose deposition matrix (DDM) can be highly complex but is crucial in intensity-modulated proton therapy (IMPT). In this work, we present a novel deep learning (DL) approach using multi-source features for proton DDM prediction. The DL5 proton DDM prediction method involves five input features containing beamlet geometry, dosimetry and treatment machine information like patient CT data, beamlet energy, distance from voxel to beamlet axis, distance from voxel to body surface, and pencil beam (PB) dose. The dose calculated by Monte Carlo (MC) method was used as the ground truth dose label. A total of 40 000 features, corresponding to 8000 beamlets, were obtained from head patient datasets and used for the training data. Additionally, seventeen head patients not included in the training process were utilized as testing cases. The DL5 method demonstrates high proton beamlet dose prediction accuracy, with an average determination coefficient R
2 of 0.93 when compared to the MC dose. Accurate beamlet dose estimation can be achieved in as little as 1.5 milliseconds for an individual proton beamlet. For IMPT plan dose comparisons to the dose calculated by the MC method, the DL5 method exhibited gamma pass rates of γ(2 mm, 2%) and γ(3 mm, 3%) ranging from 98.15% to 99.89% and 98.80% to 99.98%, respectively, across all 17 testing cases. On average, the DL5 method increased the gamma pass rates to γ(2 mm, 2%) from 82.97% to 99.23% and to γ(3 mm, 3%) from 85.27% to 99.75% when compared with the PB method. The proposed DL5 model enables rapid and precise dose calculation in IMPT plan, which has the potential to significantly enhance the efficiency and quality of proton radiation therapy.
Repurposing coal plants into thermal energy storage—a techno-economic assessment in the Indian context
Authors: Patel Serena , Mallapragada Dharik , Ganesan Karthik , Stoner Robert 
Published: July 2024

Abstract
Substantial coal phase out initiatives have been growing as the world mobilizes to meet the Paris climate goals. However, the stranded asset risk associated with this critical transition could fall disproportionately on Asian economies with younger coal fleets, like India. Here, we undertake plant-level techno-economic analysis to explore the value of installing commercially available, molten-salt thermal energy storage (TES) systems for repurposing existing coal power plants in the Indian context. We combine process simulation and an economic optimization model to evaluate design and operations of TES systems for a variety of technology assumptions, coal plant archetypes, and electricity price scenarios. Key drivers of economic viability identified include longer remaining plant lifetime, increasing peak TES temperature, lower TES energy capacity cost, co-production of waste heat for end-uses, and increasing temporal variability of electricity prices. The plant-level analysis was then extended to screen for the potential of TES retrofits within the coal power fleet in Uttar Pradesh, the most populous Indian state with a significant share of India’s coal capacity. Analysis for a single electricity price scenario indicates that over 82% of the coal units in the state can be retrofitted and recover the installed costs of TES retrofits, provided that fixed operating and maintenance costs are excluded. These results reinforce the opportunity for decision-makers to consider TES retrofits of coal plants into cost-effective grid decarbonization strategies.
Sexual Orientation-Specific Policies Are Associated With Prenatal Care Use in the First Trimester Among Sexual Minority Women: Results From a Prospective Cohort Study
Authors: Everett Bethany G , Bergman Zoë , Charlton Brittany M , Barcelona Veronica 
Published: July 2024

Abstract

Background
Previous research has shown sexual minority women (SMW) are more likely to report multiple maternal and infant health outcomes compared to heterosexual women and that these outcomes are moderated by the policy environment. Little is known, however, about prenatal care use disparities or the social determinants of prenatal care use for SMW.

Purpose
To examine the relationship between sexual orientation-specific policies that confer legal protections (e.g., hate crime protections, housing discrimination, same-sex marriage) and prenatal care use among women using a prospective, population-based data set.

Methods
Using the National Longitudinal Study of Adolescent to Adult Health and logistic regression, we link measures of state policies to the use of prenatal care in the first trimester among women who had live births. The use of prospective data allows us to adjust for covariates associated with preconception care use prior to pregnancy (n = 586 singleton births to SMW; n = 4,539 singleton births to heterosexual women).

Results
Sexual orientation-specific policies that conferred protections were associated with increased use of prenatal care among pregnancies reported by SMW (OR = 1.86, 95% CI 1.16, 2.96). In fact, in states with zero protections, we found no differences in prenatal care use by sexual minority status; however, in states with two or more protective policies, SMW were more likely to access prenatal care in the first trimester than heterosexual women. There was no relationship between sexual orientation-specific policy environments and prenatal care use among pregnancies reported by heterosexual women.

Conclusions
Recent research has documented that SMW are more likely to have adverse perinatal and obstetrical outcomes than their heterosexual peers. These findings suggest that Lesbian/Gay/Bisexual-specific policy protections may facilitate the use of prenatal care among SMW, a potentially important pathway to improve reproductive health among this population.
Sexual Minority Women Report Higher Weight Stigma Levels Than Heterosexual Women in the National Weight Control Registry
Authors: Panza Emily , Olson KayLoni , Sall Kayla , Norris Alyssa , Lillis Jason , Thomas John Graham , Dunsiger Shira , Fowler Halle , Parent Hannah , Wing Rena R 
Published: July 2024

Abstract

Background
Little is known about weight stigma in sexual minority women, and even less is known about weight stigma in those who have attained substantial weight loss and maintenance.

Purpose
This study examined weight stigma experiences and internalization in sexual minority women from the National Weight Control Registry (NWCR) who had lost ≥30 pounds and maintained this weight loss for ≥1 year, and compared weight stigma levels between sexual minority women versus heterosexual women in the NWCR.

Methods
NWCR participants completed an electronic survey. Women who identified as a sexual minority (n = 64; 98% White; MBMI = 29 ± 8; Mage = 47 ± 13) and heterosexual women matched on body mass index (BMI), age, and race (n = 64; 98% White; MBMI = 28 ± 7; Mage = 51 ± 13) were included. Participants completed assessments of experienced and internalized weight stigma.

Results
Generalized linear models showed that a significantly larger proportion of sexual minority women in the NWCR reported experiencing weight stigma in the past year (24.2%) compared with heterosexual women (4.7%; p &lt; .05). Furthermore, sexual minority (vs. heterosexual) women reported significantly higher levels of internalized weight stigma (p &lt; .001), and a greater proportion of sexual minority women (35%) reported clinically significant internalized weight stigma relative to heterosexual women (2%; p &lt; .001).

Conclusions
Sexual minority women are at greater risk for experienced and internalized weight stigma than their heterosexual counterparts among women who have attained significant long-term weight loss. It is critical to expand research on weight stigma in sexual minority women.
Longitudinal changes in sodium concentration and in clinical outcome in mild traumatic brain injury
Authors: Gerhalter Teresa , Chen Anna M , Dehkharghani Seena , Peralta Rosemary , Gajdosik Mia , Zarate Alejandro , Bushnik Tamara , Silver Jonathan M , Im Brian S , Wall Stephen P , Madelin Guillaume , Kirov Ivan I 
Published: July 2024

Abstract
Ionic imbalances and sodium channel dysfunction, well-known sequelae of traumatic brain injury (TBI), promote functional impairment in affected subjects. Therefore, non-invasive measurement of sodium concentrations using 23Na MRI has the potential to detect clinically relevant injury and predict persistent symptoms. Recently, we reported diffusely lower apparent total sodium concentrations (aTSC) in mild TBI patients compared to controls, as well as correlations between lower aTSC and worse clinical outcomes. The main goal of this study was to determine whether these aTSC findings, and their changes over time, predict outcomes at 3- and 12-month from injury. Twenty-seven patients previously studied with 23Na MRI and outcome measures at 22 ± 10 days (average ± standard deviation) after injury (visit-1, v1) were contacted at 3- (visit-2, v2) and 12-month after injury (visit-3, v3) to complete the Rivermead post-concussion symptoms questionnaire (RPQ), the extended Glasgow outcome scale (GOSE), and the brief test of adult cognition by telephone (BTACT). Follow-up 1H and 23Na MRI were additionally scheduled at v2. Linear regression was used to calculate aTSC in global grey and white matters. Six hypotheses were tested in relation to the serial changes in outcome measures and in aTSC, and in relation to the cross-sectional and serial relationships between aTSC and outcome. Twenty patients contributed data at v2 and fifteen at v3. Total RPQ and composite BTACT z-scores differed significantly for v2 and v3 in comparison to v1 (each P &lt; 0.01), reflecting longitudinally reduced symptomatology and improved performance on cognitive testing. No associations between aTSC and outcome were observed at v2. Previously lower grey and white matter aTSC normalized at v2 in comparison to controls, in line with a statistically detectable longitudinal increase in grey matter aTSC between v1 and v2 (P = 0.0004). aTSC values at v1 predicted a subset of future BTACT subtest scores, but not future RPQ scores nor GOSE-defined recovery status. Similarly, aTSC rates of change correlated with BTACT rates of change, but not with those of RPQ. Tissue aTSC, previously shown to be diffusely decreased compared to controls at v1, was no longer reduced by v2, suggesting normalization of the sodium ionic equilibrium. These changes were accompanied by marked improvement in outcome. The results support the notion that early aTSC from 23Na MRI predicts future BTACT, but not RPQ scores, nor future GOSE status.
A rare case report of catecholaminergic polymorphic ventricular tachycardia with an uncommon CALM2 mutation
Authors: Ding Kimberly R , de la Rosa Angelo L , Do Duc , Shah Sonia 
Published: July 2024

Abstract

Background
Catecholaminergic polymorphic ventricular tachycardia (CPVT) is a primary arrhythmia disorder characterized by syncope or sudden cardiac death and typically caused by a gain-of-function of the Ryanodine Receptor Type 2 (RyR2) mutation. Calmodulin is a calcium-binding protein responsible for many intracellular signalling pathways and disruptions in function or regulation may lead to potentially fatal arrhythmias. We present a case of a young patient with CPVT found to have an unusual, potentially causative, Calmodulin 2—a protein coding gene (CALM2) mutation.

Case summary
A 21-year-old female with autism was brought to the ED following cardiac arrest. Bidirectional ventricular tachycardia was captured on electrocardiogram. Propranolol was initiated, and patient had no further episodes of ventricular arrhythmia. A subcutaneous implantable cardioverter defibrillator (ICD) was implanted, and further genetics testing was done. Rapid Whole Genome Sequencing (PGnome®—RAPID) resulted heterozygous variant of uncertain significance in CALM2 gene NM_001743.5 for variant c.136G&gt;A.

Discussion
To the authors’ knowledge, this is the third known record of such mutation in accordance with the International Calmodulin Registry (n = 74). Identification of CALM mutations can help advance the understanding of genetic underpinnings of arrhythmias and underscore necessity of genetic screening and personalized treatment strategies. Subcutaneous ICDs offer a promising therapeutic option while minimizing risks associated with traditional transvenous ICDs.
Comparison between remotely supported nurse-led electro-anatomic mapping and standard onsite engineer support for electrophysiological procedures
Authors: Müssigbrodt Andreas , Vergier Romain , Banydeen Rishika , Finoly Steeve , Mommarche Max , Bethencourt Maria Herrera , Monfort Astrid , Inamo Jocelyn 
Published: July 2024

Abstract

Aims
Catheter ablations of complex cardiac arrhythmias are currently guided by electro-anatomic mapping (EAM) systems. The aim of this study was to compare two different approaches: remotely supported nurse-led EAM with standard onsite engineer support.

Methods and results
In this retrospective observational study, 166 patients with complex and non-complex procedures were included. A total of 82 patients benefited from EAM with remotely supported nurse-led mapping (mean age: 62 ± 16 years), while the approach for 84 patients was with standard onsite engineer support (mean age: 56 ± 19 years). Procedural characteristics, acute results, and complication rates were compared between both groups and showed similar results. Complex and non-complex procedures were conducted in both groups, including left atrial and ventricular procedures. As ventricular tachycardia and accessory pathway ablations were more frequently conducted with standard onsite engineer support, we separately analysed the largest subgroup, 105 patients with atrial fibrillation, left atrial flutter, and left atrial tachycardia. Patients in this subgroup had comparable baseline characteristics, procedure times, and procedural success. Nevertheless, there were longer ablation times and more utilization of fluoroscopy in the onsite group, most likely due to more complex procedures.

Conclusion
Our results underline the practicality of remotely supported nurse-led EAM. The latter approach proved to be a safe alternative to onsite engineer support. Due to its advantages, particularly for insular settings, it will likely play a greater role in the future.
Evaluation of tricuspid valve regurgitation following transvenous rotational mechanical lead extraction
Authors: Migliore Federico , Pittorru Raimondo , De Lazzari Manuel , Dall’Aglio Pietro Bernardo , Cecchetto Antonella , Previtero Marco , Pergola Valeria , Thiene Gaetano , Masiero Giulia , Tarantini Giuseppe , Tarzia Vincenzo , Gerosa Gino 
Published: July 2024

Abstract

Aims
Transvenous lead extraction (TLE) is potentially complicated by significant tricuspid valve regurgitation increase (TRI). However, there are limited data on the effect of the bidirectional rotational mechanical sheaths on significant TRI. The aim of the present study was to investigate the rate of significant changes in tricuspid regurgitation (TR) severity following mechanical rotational TLE and their outcomes.

Methods and results
In 158 patients (mean age 66 ± 16.9 years) undergoing mechanical rotational TLE, acute changes in TR severity were assessed by echocardiography evaluation. A significant acute TRI was defined as an increase of at least one grade with a post-extraction severity at least moderate. A total of 290 leads were extracted (mean implant duration, 93 ± 65 months). Significant TRI was noted in 5.7% of patients, and it was linked to tricuspid valve damage, TLE infection indication, and longer lead implant duration. Univariate predictors of significant TRI included implant duration of all leads [odds ratio (OR) 1.01; 95% confidence interval (CI) 1.003–1.018; P = 0.001] and right ventricular leads (OR 1.01; 95% CI 1.004–1.017; P = 0.002). Severe increase of TR following TLE was an independent predictor of mortality [hazard ratio (HR) 5.20; 95% CI 1.44–18.73; P = 0.012 ] along with severe systolic dysfunction (HR 2.37; 95% CI 1.01–5.20; P = 0.032), and systemic infection (HR 2.28; 95% CI 1.06–4.89; P = 0.035).

Conclusion
Significant TRI was detected in 5.7% of patients following transvenous rotational mechanical lead extraction. The duration of lead implantation emerged as the sole predictor of significant TRI. Physicians engaged in TLE should exercise greater vigilance for this potential complication.