bluuebunny/crossref_metadata_2025_split huggingface dataset:
Experimental investigation on the potential of passive prechambers for use in 2S engines
Authors: Risaliti Edoardo , Ferrara Giovanni , Romani Luca , Pero Francesco Del , Arcidiacono Gabriele 
Published: May 2024

Abstract
Design improvement of Internal Combustion Engines (ICEs) is required by the continuous update of European exhaust emission standards and vehicle registration protocols. This has pushed research and industry efforts towards the development of Low Temperature Combustion (LTC) systems. Among various LTC technologies, the so called “jet ignition” is claimed to be well-suited for light engines, since it provides a more uniform and rapid combustion while ensuring the mixture ignition process. In this context, the adoption of prechambers was found well-suited for two-stroke engines, for which low-pressure direct injection technologies have been developed in the last decade to reduce the fuel short circuit phenomenon. The present paper experimentally investigates the use of different passive combustion prechambers in a Low-Pressure Direct Injection (LPDI) 2-stroke engine, with the main purpose to understand the relationship between prechamber geometrical parameters and engine performance. A 50-cc single cylinder LPDI motorcycle engine is chosen as the test case and it is re-arranged to run in jet ignition mode. The experimental analysis focuses on the evaluation of benefits provided by jet ignition combustion compared to the baseline LPDI propulsion unit at different engine operating points. Design criteria for prechambers development and the tuning process of engine combustion parameters (such as start of injection, ignition time and throttle valve opening) are described in detail. The results of experimental activity are finally shown and critically discussed, highlighting advantages and disadvantages of this application in terms of engine performance, efficiency and cycle-to-cycle variation.
Robotization of the IR-Thermographic technique – impact on the visualisation quality and considerations on the data workflow
Authors: Montinaro N , Mineo C , Pantano A , Cerniglia D 
Published: May 2024

Abstract
Quality control automation is becoming increasingly popular in industrial production lines. Active thermography techniques are well-regarded for their adaptability, providing fast, non-contact, and full-field non-destructive evaluation. Automating thermographic evaluation can increase assessment speed and repeatability without sacrificing inspection accuracy. By using a robot arm to manipulate the thermographic setup, it becomes possible to inspect large components and refine scans on suspicious zones, even in parts with complex geometries. In this study, the performance of a new thermographic inspection platform is compared with a conventional setup to showcase the potential improvements. A plastic curved-shaped sample with artificial flat bottom hole defects is used as a benchmark for the comparison. The advantages and disadvantages of robotizing the infrared non-destructive setup are analyzed, and the impact of the data workflow and future research activities are also discussed.
On the Compositional Step of the IC-GN Digital Image Correlation Algorithm
Authors: Baldi Antonio , Santucci Pietro Maria 
Published: May 2024

Abstract
Digital Image Correlation (DIC) is a well-known experimental optical technique for measuring the displacement field based on the assumption that pixel intensity does not change with motion.
DIC can be implemented using various alternative approaches. The most used in the Experimental Mechanics field are the Forward-Additive Gauss-Newton (FA-GN) and the Inverse-Compositional Gauss-Newton (IC-GN) formulations. The former corresponds to the original formulation proposed by Lucas and Kanade, while the latter was proposed by Baker and Matthews twenty years later. Although both formulations give the same results at the first order, their speed, convergency characteristic and noise robustness differ considerably. Nowadays, the IC-GN method is usually preferred because of its lower computational load and the significantly better noise sensitivity. However, the Inverse Compositional approach, as its name states, requires the inversion and composition of the displacement field, thus enforcing the use of invertible displacement fields. This can be a significant limitation because it may introduce an under-matching error in the solution.
This work shows that a simple modification of the viewpoint makes the compositional step simpler, thus giving a DIC formulation as fast as that of the IC-GN, with the same noise-bias characteristic and without requiring an invertible displacement field.
Material Characterization Augmented with Artificial Intelligence.
Authors: Vettori Matteo , Marchi Adriano , Bellocchio Enrico , Devo Alessandro , Belfiori Davide , Soncini Francesco , Musiari Francesco , Moroni Fabrizio , Pirondi Alessandro 
Published: May 2024

Abstract
The present paper investigates the application of artificial intelligence to improve the results from simple, non-instrumented, tensile tests, performed with a desktop-size MaCh3D smart universal testing machine. Non-instrumented tensile tests, performed on any testing machine, are affected by both deterministic and random factors that introduce errors in the test results. Specific features of the MaChh3D tester minimize random factors effects on test results while introducing a larger effect of deterministic factors. Artificial intelligence is identified as a novel approach to correct errors in non-instrumented tensile test, capable of simulating a direct strain measure onto the test, replacing traditional contact or non-contact instrumentations (like strain-gages, extensometer and optical measures) that introduce complexity into test procedure and require time for setup. The resulting AI model implementation is described and its performance evaluated in comparison with instrumented tests, also comparing different training strategies. The developed AI-extensometer (artificial intelligence virtual extensometer), is capable of a precise mechanical properties evaluation, with errors from 0 to 10% depending on the specific parameter.
Predictive sustainability analysis applied to an automotive design case study.
Authors: Antonacci A. , Del Pero F. , Innocenti E. , Giraldi A. , Pierini M. , Delogu M. 
Published: May 2024

Abstract
The paper deals with a predictive sustainability analysis applied to the design of automotive components in lightweight perspective. The analysis is conducted through the integration of the traditional Life Cycle Assessment (LCA) methodology with tailored forecasting algorithms able to provide a predictive evaluation of Climate Change (CC) by elaboration data contained in commercial environmental datasets. The comparison is referred to the entire Life Cycle (LC) of the system (including production, use and End-of-Life) according to a “from cradle to grave approach”.
A medium-class car rear crash management system is used as case study, assessing the potential benefits related to the substitution of conventional steel with 6000/7000 series aluminium alloys, along with other minor design changes. Particularly, the study compares the environmental profile of the two solutions based on the CC impact category in application to both an Internal Combustion Engine Vehicle (ICEV) and a Battery Electric Vehicle (BEV).
The results show the potentiality of the proposed methodology, highlighting possible improvements/worsenings: new materials and manufacturing technologies adopted in the lightweight rear crash management system entail contrasting environmental effects depending on LC phases, that is, increased CO2eq in production (around 125% - mainly due to the strong energy intensity of aluminium supply chain) and reduced burdens in use and EoL (primarily provided by component mass reduction). That said, the influence of different boundary conditions on the predictive models is significant only for the electricity produced to energize the BEV configuration, leading to an overall variability of comparison results ranging within 3-30% for the BEV case study.
Determination and analysis of stress concentration factor in finite plate with different polygonal discontinuities under uniaxial compression using finite element analysis (FEA)
Authors: Patel Bhaveshkumar P , Patel Rashmiben H 
Published: May 2024

Abstract
Stress concentration is the accumulation of stress in a body due to a sudden change in its geometry. Stresses and stress concentrations are created at the nearer area of the structural discontinuities. Any structural discontinuity compromises the strength of the structure. Numerical approaches can be used to determine the maximum stress concentration for various complex geometries without regard to time or cost constraints. The current study gives a thorough finite element analysis of stress concentration in a structural steel plate with a polygonal cutout. In contrast to orientation and area, this study looks at an isotropic finite plate for the stress concentration factor (SCF) with central polygonal cutouts (triangular, square, pentagonal, and hexagonal). ANSYS, a finite element program, calculates the von Mises stresses, and based on the results, stress concentrations are calculated. The orientation of polygonal cutouts in a square plate and the constant area of polygonal cutouts in a square plate are two parameters considered in the calculation. These results are verified by literature for the orientation of the hole, which concludes that a square hole position parallels the loading direction showing a 50% reduction in stress concentration factor.
Wives and Daughters
Authors: Brockliss Laurence , Smith Harry 
Published: May 2024

Abstract
Chapter 9 is the one specific chapter devoted to wives, daughters, and daughters-in-law. It examines similar themes to those explored in Chapters 2, 3, and 5. It looks at women’s education, their likelihood of ever being in paid employment, their role as philanthropists and political activists, and their wealth at probate. Most women had no income from employment at any time in their lives, and those who did gave up their occupation when they married. Hardly any, even among the granddaughters and granddaughters-in-law, ever practised a profession, though the number grows if nursing is included. A specific section explores the different ways in which widows in the more affluent families were protected from penury, and the extent to which legal mechanisms were used to limit a husband’s access to a wife’s inherited wealth. As a result, wives and daughters were frequently well-off when they died, and many spinsters would have enjoyed a very comfortable life.
Concluding Remarks
Authors: Brockliss Laurence , Smith Harry 
Published: May 2024

Abstract
The final chapter summarizes the conclusions reached at the end of each chapter and discusses whether the members of the mid-nineteenth century professions are better seen as a separate class or caste or as one of several components of the middle class. It concludes that the cohort and their families as a social group reveal few marks of a class or caste. That is not to say that there is no sign of social exclusivity or what might be called a ‘professional project’. A number of cohort families whose progenitors belonged to the traditional professions presented strong signs of marital endogamy and occupational reproduction, but this was not true of the large majority of cohort families. Nor is there any significant difference in this regard between the towns. While the cohort’s lives especially had a regional rather than a national focus, there is a striking consistency in the broad behaviour of the cohort families, wherever they were initially based.
Associations of Anxiety Symptoms With 6-Year Blood Pressure Changes and Incident Hypertension: Results From the Hispanic Community Health Study/Study of Latinos
Authors: Rosas Carlos E , Pirzada Amber , Durazo-Arvizu Ramon , Gallo Linda C , Talavera Gregory A , Elfassy Tali , Cai Jianwen , Llabre Maria M , Perreira Krista M , Wassertheil-Smoller Sylvia , Daviglus Martha L , Sanchez-Johnsen Lisa A P 
Published: May 2024

Abstract

Background
Despite the high burden of anxiety and hypertension in Hispanic/Latino adults, little is known about their association in this population.

Purpose
To examine the associations of anxiety symptoms with 6-year changes in blood pressure (BP) and incident hypertension in Hispanic/Latino adults.

Methods
We examined data from a probability sample of 10,881 Hispanic/Latino persons aged 18–74 who attended visits 1 (V1; 2008–2011) and 2 (V2; 2014–2017) of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a prospective cohort study. Anxiety symptoms were assessed at V1 using the 10-item Spielberger Trait Anxiety Scale (M = 17.1; Range = 10–40) and dichotomized using a cut-point of 20, the highest quartile in this cohort. BP was measured at both visits using a standardized protocol.

Results
Adults with elevated anxiety symptoms had a 1.02 mm Hg greater increase in systolic (p = .02) and a 0.75 mm Hg greater increase in diastolic BP (p = .02) over 6.1 years than those with lower symptoms, after adjusting for sociodemographic and clinical covariates. These associations differed by sex. Elevated anxiety was associated with a greater increase in systolic and diastolic BP in men only. Among persons without hypertension at V1 (N = 7,412), those with elevated anxiety symptoms at V1 had a 22% higher incidence of hypertension (p = .02) 6.1 years later.

Conclusions
Our findings underscore the importance of screening for and treating elevated anxiety symptoms to help prevent hypertension. Further research on the role of sex and underlying mechanisms is warranted.
A case study of a bispecific antibody manufacturability assessment and optimization during discovery stage and its implications
Authors: Wang Shuang , Zhang Weijie , Yang Baotian , Zhang Xudong , Fang Jing , Rui Haopeng , Chen Zhijian , Gu Jijie , Chen Zhiqiang , Xu Jianqing 
Published: May 2024

Abstract
The manufacturability assessment and optimization of bispecific antibodies (bsAbs) during the discovery stage are crucial for the success of the drug development process, impacting the speed and cost of advancing such therapeutics to the Investigational New Drug (IND) stage and ultimately to the market. The complexity of bsAbs creates challenges in employing effective evaluation methods to detect developability risks in early discovery stage, and poses difficulties in identifying the root causes and implementing subsequent engineering solutions. This study presents a case of engineering a bsAb that displayed a normal solution appearance during the discovery phase but underwent significant precipitation when subjected to agitation stress during 15 L Chemistry, Manufacturing, and Control (CMC) production Leveraging analytical tools, structural analysis, in silico prediction, and wet-lab validations, the key molecular origins responsible for the observed precipitation were identified and addressed. Sequence engineering to reduce protein surface hydrophobicity and enhance conformational stability proved effective in resolving agitation-induced aggregation. The refined bsAb sequences enabled successful mass production in CMC department. The findings of this case study contribute to the understanding of the fundamental mechanism of agitation-induced aggregation and offer a potential protein engineering procedure for addressing similar issues in bsAb. Furthermore, this case study emphasizes the significance of a close partnership between Discovery and CMC teams. Integrating CMC’s rigorous evaluation methods with Discovery’s engineering capability can facilitate a streamlined development process for bsAb molecules.
Guiding seed movement: environmental heterogeneity drives genetic differentiation in Plathymenia reticulata, providing insights for restoration
Authors: Conceição Taise Almeida , Santos Alesandro Souza , Fernandes Ane Karoline Campos , Meireles Gabriela Nascimento , de Oliveira Fernanda Ancelmo , Barbosa Rafael Marani , Gaiotto Fernanda Amato 
Published: May 2024

Abstract
Forest and landscape restoration is one of the main strategies for overcoming the environmental crisis. This activity is particularly relevant for biodiversity-rich areas threatened by deforestation, such as tropical forests. Efficient long-term restoration requires understanding the composition and genetic structure of native populations, as well as the factors that influence these genetic components. This is because these populations serve as the seed sources and, therefore, the gene reservoirs for areas under restoration. In the present study, we investigated the influence of environmental, climatic and spatial distance factors on the genetic patterns of Plathymenia reticulata, aiming to support seed translocation strategies for restoration areas. We collected plant samples from nine populations of P. reticulata in the state of Bahia, Brazil, located in areas of Atlantic Forest and Savanna, across four climatic types, and genotyped them using nine nuclear and three chloroplast microsatellite markers. The populations of P. reticulata evaluated generally showed low to moderate genotypic variability and low haplotypic diversity. The populations within the Savanna phytophysiognomy showed values above average for six of the eight evaluated genetic diversity parameters. Using this classification based on phytophysiognomy demonstrated a high predictive power for genetic differentiation in P. reticulata. Furthermore, the interplay of climate, soil and geographic distance influenced the spread of alleles across the landscape. Based on our findings, we propose seed translocation, taking into account the biome, with restricted use of seed sources acquired or collected from the same environment as the areas to be restored (Savanna or Atlantic Forest).
Uncover spatially informed variations for single-cell spatial transcriptomics with STew
Authors: Guo Nanxi , Vargas Juan , Reynoso Samantha , Fritz Douglas , Krishna Revanth , Wang Chuangqi , Zhang Fan 
Published: May 2024

Abstract

Motivation
The recent spatial transcriptomics (ST) technologies have enabled characterization of gene expression patterns and spatial information, advancing our understanding of cell lineages within diseased tissues. Several analytical approaches have been proposed for ST data, but effectively utilizing spatial information to unveil the shared variation with gene expression remains a challenge.

Results
We introduce STew, a Spatial Transcriptomic multi-viEW representation learning method, to jointly analyze spatial information and gene expression in a scalable manner, followed by a data-driven statistical framework to measure the goodness of model fit. Through benchmarking using human dorsolateral prefrontal cortex and mouse main olfactory bulb data with true manual annotations, STew achieved superior performance in both clustering accuracy and continuity of identified spatial domains compared with other methods. STew is also robust to generate consistent results insensitive to model parameters, including sparsity constraints. We next applied STew to various ST data acquired from 10× Visium, Slide-seqV2, and 10× Xenium, encompassing single-cell and multi-cellular resolution ST technologies, which revealed spatially informed cell type clusters and biologically meaningful axes. In particular, we identified a proinflammatory fibroblast spatial niche using ST data from psoriatic skins. Moreover, STew scales almost linearly with the number of spatial locations, guaranteeing its applicability to datasets with thousands of spatial locations to capture disease-relevant niches in complex tissues.

Availability and implementation
Source code and the R software tool STew are available from github.com/fanzhanglab/STew.
Prediction of tumor-specific splicing from somatic mutations as a source of neoantigen candidates
Authors: Lang Franziska , Sorn Patrick , Suchan Martin , Henrich Alina , Albrecht Christian , Köhl Nina , Beicht Aline , Riesgo-Ferreiro Pablo , Holtsträter Christoph , Schrörs Barbara , Weber David , Löwer Martin , Sahin Ugur , Ibn-Salem Jonas 
Published: May 2024

Abstract

Motivation
Neoantigens are promising targets for cancer immunotherapies and might arise from alternative splicing. However, detecting tumor-specific splicing is challenging because many non-canonical splice junctions identified in tumors also appear in healthy tissues. To increase tumor-specificity, we focused on splicing caused by somatic mutations as a source for neoantigen candidates in individual patients.

Results
We developed the tool splice2neo with multiple functionalities to integrate predicted splice effects from somatic mutations with splice junctions detected in tumor RNA-seq and to annotate the resulting transcript and peptide sequences. Additionally, we provide the tool EasyQuant for targeted RNA-seq read mapping to candidate splice junctions. Using a stringent detection rule, we predicted 1.7 splice junctions per patient as splice targets with a false discovery rate below 5% in a melanoma cohort. We confirmed tumor-specificity using independent, healthy tissue samples. Furthermore, using tumor-derived RNA, we confirmed individual exon-skipping events experimentally. Most target splice junctions encoded neoepitope candidates with predicted major histocompatibility complex (MHC)-I or MHC-II binding. Compared to neoepitope candidates from non-synonymous point mutations, the splicing-derived MHC-I neoepitope candidates had lower self-similarity to corresponding wild-type peptides. In conclusion, we demonstrate that identifying mutation-derived, tumor-specific splice junctions can lead to additional neoantigen candidates to expand the target repertoire for cancer immunotherapies.

Availability and implementation
The R package splice2neo and the python package EasyQuant are available at https://github.com/TRON-Bioinformatics/splice2neo and https://github.com/TRON-Bioinformatics/easyquant, respectively.
High fat diet-induced obesity and gestational DMBA exposure alter folliculogenesis and the proteome of the maternal ovary
Authors: Novbatova Gulnara , Fox Isabelle , Timme Kelsey , Keating Aileen F 
Published: May 2024

Abstract
Obesity and ovotoxicant exposures impair female reproductive health with greater ovotoxicity reported in obese relative to lean females. The mother and developing fetus are vulnerable to both during gestation. 7,12-dimethylbenz[a]anthracene (DMBA) is released during carbon combustion including from cigarettes, coal, fossil fuels, and forest fires. This study investigated the hypothesis that diet-induced obesity would increase sensitivity of the ovaries to DMBA-induced ovotoxicity and determined impacts of both obesity and DMBA exposure during gestation on the maternal ovary. Female C57BL/6 J mice were fed a control or a High Sugar High Fat (45% kcal from fat; 20% kcal from sucrose) diet until ~30% weight gain was attained before mating with unexposed males. From gestation Day 7, mice were exposed intraperitoneally to either vehicle control (corn oil) or DMBA (1 mg/kg diluted in corn oil) for 7 d. Thus, there were four groups: lean control (LC); lean DMBA exposed; obese control; obese DMBA exposed. Gestational obesity and DMBA exposure decreased (P &lt; 0.05) ovarian and increased liver weights relative to LC dams, but there was no treatment impact (P &gt; 0.05) on spleen weight or progesterone. Also, obesity exacerbated the DMBA reduction (P &lt; 0.05) in the number of primordial, secondary follicles, and corpora lutea. In lean mice, DMBA exposure altered abundance of 21 proteins; in obese dams, DMBA exposure affected 134 proteins while obesity alone altered 81 proteins in the maternal ovary. Thus, the maternal ovary is impacted by DMBA exposure and metabolic status influences the outcome.