bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Intelligent Machine Learning Based Method for Tool Wear Estimation in the Vertical Broaching Process
Authors: Holgado Ibon , Pérez-Salinas Cristian , Ortega Naiara , de Lacalle L. N. López , del Olmo Ander 
Published: August 2023

AbstractThis work describes a machine vision system workflow to automatically estimate the broaching tool wear. The proposed system offers the possibility to evaluate the evolution of wear under different machining conditions and to decide when a tool should be replaced, guaranteeing the quality of the machined part and avoiding catastrophic tool breakage. In addition, the paper discusses the advantages of the proposed method over the traditional and widely used ISO 3685:1993 based methods, which are highly influenced by the operator. The proposed method uses a novel wear area segmentation technique based on Machine Learning artificial intelligence, generating highly reproducible values, saving technicians labor-intensive tasks, and obtaining values with high accuracy. The results show a strong relationship between the values obtained by the proposed automatic method and the experimental ones, with errors below 0.17% and 2.88% corresponding to the MSE and MAE respectively.
Light Scalars at FASER
Authors: Kling Felix , Li Shuailong , Song Huayang , Su Shufang , Su Wei 
Published: August 2023

Abstract
FASER, the ForwArd Search ExpeRiment, is a currently operating experiment at the Large Hadron Collider (LHC) that can detect light long-lived particles produced in the forward region of the LHC interacting point. In this paper, we study the prospect of detecting light CP-even and CP-odd scalars at FASER and FASER 2. Considering a model-independent framework describing the most general interactions between a CP-even or CP-odd scalar and SM particles using the notation of coupling modifiers in the effective Lagrangian, we develop the general formalism for the scalar production and decay. We then analyze the FASER and FASER 2 reaches of light scalars in the large tan β region of the Type-I two Higgs double model as a case study, in which light scalars with relatively long lifetime could be accommodated. In the two benchmark scenarios we considered, the light (pseudo)scalar decay length varies in (10−8, 105) meters. Both FASER and FASER 2 can probe a large part of the parameter space in the large tan β region up to 107, extending beyond the constraints of the other existing experiments.
Genomic prediction in hybrid breeding: I. Optimizing the training set design
Authors: Melchinger Albrecht E. , Fernando Rohan , Stricker Christian , Schön Chris-Carolin , Auinger Hans-Jürgen 
Published: August 2023

Abstract
Key message
Training sets produced by maximizing the number of parent lines, each involved in one cross, had the highest prediction accuracy for H0 hybrids, but lowest for H1 and H2 hybrids.

Abstract
Genomic prediction holds great promise for hybrid breeding but optimum composition of the training set (TS) as determined by the number of parents (nTS) and crosses per parent (c) has received little attention. Our objective was to examine prediction accuracy ($$r_{a}$$

r
a

) of GCA for lines used as parents of the TS (I1 lines) or not (I0 lines), and H0, H1 and H2 hybrids, comprising crosses of type I0 × I0, I1 × I0 and I1 × I1, respectively, as function of nTS and c. In the theory, we developed estimates for $$r_{a}$$

r
a

of GBLUPs for hybrids: (i)$$\hat{r}_{a}$$

r
^

a

based on the expected prediction accuracy, and (ii) $$\tilde{r}_{a}$$

r
~

a

based on $$r_{a}$$

r
a

of GBLUPs of GCA and SCA effects. In the simulation part, hybrid populations were generated using molecular data from two experimental maize data sets. Additive and dominance effects of QTL borrowed from literature were used to simulate six scenarios of traits differing in the proportion (τSCA = 1%, 6%, 22%) of SCA variance in σG2 and heritability (h2 = 0.4, 0.8). Values of $$\tilde{r}_{a}$$

r
~

a

and $$\hat{r}_{a}$$

r
^

a

closely agreed with $$r_{a}$$

r
a

for hybrids. For given size NTS = nTS × c of TS, $$r_{a}$$

r
a

of H0 hybrids and GCA of I0 lines was highest for c = 1. Conversely, for GCA of I1 lines and H1 and H2 hybrids, c = 1 yielded lowest $$r_{a}$$

r
a

with concordant results across all scenarios for both data sets. In view of these opposite trends, the optimum choice of c for maximizing selection response across all types of hybrids depends on the size and resources of the breeding program.
A hybrid patch decomposition approach to compute an enclosure for multi-objective mixed-integer convex optimization problems
Authors: Eichfelder Gabriele , Warnow Leo 
Published: August 2023

AbstractIn multi-objective mixed-integer convex optimization, multiple convex objective functions need to be optimized simultaneously while some of the variables are restricted to take integer values. In this paper, we present a new algorithm to compute an enclosure of the nondominated set of such optimization problems. More precisely, we decompose the multi-objective mixed-integer convex optimization problem into several multi-objective continuous convex optimization problems, which we refer to as patches. We then dynamically compute and improve coverages of the nondominated sets of those patches to finally combine them to obtain an enclosure of the nondominated set of the multi-objective mixed-integer convex optimization problem. Additionally, we introduce a mechanism to reduce the number of patches that need to be considered in total. Our new algorithm is the first of its kind and guaranteed to return an enclosure of prescribed quality within a finite number of iterations. For selected numerical test instances we compare our new criterion space based approach to other algorithms from the literature and show that much larger instances can be solved with our new algorithm.
Scalable monoids and quantity calculus
Authors: Jonsson Dan 
Published: August 2023

AbstractWe define scalable monoids and prove their fundamental properties. Congruence relations on scalable monoids, direct and tensor products, subalgebras and homomorphic images of scalable monoids, and unit elements of scalable monoids are defined and investigated. A quantity space is defined as a commutative scalable monoid over a field, admitting a finite basis similar to a basis for a free abelian group. Observations relating to the theory of measurement of physical quantities accompany the results about scalable monoids. We conclude that the algebraic theory of scalable monoids and quantity spaces provides a rigorous foundation for quantity calculus.
An evolutionary-based polynomial regression modeling approach to predicting discharge flow rate under sheet piles
Authors: Asr A. Ahangar , Johari A. , Javadi A. A. 
Published: August 2023

AbstractThe discharge flow rate beneath sheet plies is an essential parameter in designing these water retaining structures. This paper presents a unified framework for modeling and predicting discharge flow rate using an evolutionary-based polynomial regression technique. EPR (Evolutionary Polynomial Regression) is a data-driven method based on evolutionary computing to search for polynomial structures representing a system. The input parameters in the modeling procedure included the sheet pile height, upstream water head, and the hydraulic conductivity anisotropy ratio. Due to ever-increasing demand for water, a widely held view on predicting and controlling the available water behind reservoirs, dams, barrages, and weirs is of vital importance. To this end, the sheer novelty of the current study has been worn off through the development of a comprehensive model to predict the flow rate considering the most effective variables in the seepage issue. To the best of our knowledge, the research conducted in the literature has yet to cover the whole seepage problem using a comprehensive database extracted by numerical methods; thus, a comprehensive finite-element-based artificial database including 1000 data lines was created using the Scaled Boundary Finite Element Method (SBFEM) by simulating seepage beneath sheet plies covering a considerably wide range of seepage-related real-world values. The database was then employed to develop and validate the EPR flow rate prediction model. Data were divided into training (used for creating the models) and testing (for validating the developed models) data based on a statistical process. The procedure for preparing the data and developing and validating the models is presented in detail in this paper. The main advantage of the proposed models over a conventional and neural network and most GP (Genetic Programming)-based constitutive models is that they provide the optimum structure for the material constitutive model representation as well as its parameters, directly from raw experimental (or field) data. EPR can learn nonlinear and complex material behavior without any prior assumptions on the constitutive relationships. The proposed algorithm captures and transparently presents relationships between contributing parameters in polynomial expressions providing the user with a clear insight into the problem. EPR-based model predictions demonstrated an excellent agreement with the unseen simulated data used for validating the developed model. A parametric study on the presented models was conducted to investigate the effects of the contributing parameters on model predictions and the consistency of the parameter relationships with the database. Results of the parametric study showed that the effects of variations in the contributing parameters on EPR predictions are in line with the expected behavior. The merits and advantages of the proposed technique are discussed in the paper.
Spurenstoffmanagement im Donaueinzugsgebiet
Authors: Zoboli O. , Kovacs A. , Kittlaus S. , Clement A. , Kardos M. K. , Jolánkai Z. , Kaps R. , Gabriel O. , Broer M. , van Gils J. , Loos S. , Weber N. , Milacic R. , Dimova G. , Tonev R. , Nedelea I. , Marchidan E. , Zessner M. 
Published: August 2023

ZusammenfassungSpurenstoffe stellen eine der zentralen Herausforderungen für die Wasserwirtschaft im Donaueinzugsgebiet dar. Der vorliegende Artikel präsentiert das Konzept und einen Überblick zu den Ergebnissen des Projekts Danube Hazard m3c, welches im Rahmen des Interreg-Danube-Transnational-Programms der EU in den Jahren 2020 bis 2023 abgewickelt wurde. Im Zuge des Projekts konnten Spurenstoffkonzentrationen in unterschiedlichen Eintragspfaden und Gewässersystem aus verschiedenen nationalen und internationalen Monitoringprogrammen in einer umfassenden und harmonisierten Datenbank erfasst und diese Datenbasis durch ein gezieltes Monitoring in unterschiedlichen Umweltmedien erweitert werden. Auf diesen Daten aufbauend wurden eine einzugsgebietsweite Emissionsmodellierung umgesetzt und gewonnene Erkenntnisse für abgestimmte Politikempfehlungen genutzt. Trotz zum Teil großer Anstrengungen in Ländern des Donaueinzugsgebiets, den Monitoringerfordernissen der EU-WRRL nachzukommen, zeigen sich bei dem Versuch, die Daten unterschiedlicher Länder in harmonisierter Weise zu erfassen, einige Schwierigkeiten, die dieses Vorhaben behindern. Auch zeigt sich, dass es massiver zusätzlicher Anstrengungen der Donauländer bedürfen wird, um den enormen Herausforderungen gewachsen zu sein, die an ein zukünftiges Spurenstoffmanagement im Lichte vielfältiger Anforderungen und Veränderungen zu stellen sein wird. International abgestimmtes Monitoring, harmonisierte Datenerfassung und einzugsgebietsbezogene Emissionsmodellierung sollten grundlegende Elemente für ein wissensbasiertes Spurenstoffmanagement sein. Maßnahmen zur Verbesserung der Belastungssituation der Gewässer des Donaueinzugsgebiets sollten entsprechend der Hierarchie der Belastungskontrolle konzeptioniert werden. Dies bedeutet Kontrollen beim Einsatz von Spurenstoffen, um deren Freisetzung zu mindern, Kontrollen der Emissionen über technische Einrichtungen der Wasserwirtschaft und Minderung des Transports durch natürliche Barrieren wie z. B. Pufferstreifen.
Effect of repeatedly applied cold water immersion on subclinical atherosclerosis, inflammation, fat accumulation and lipid profile parameters of volunteers
Authors: Tóth Štefan , Barbierik Vachalcová Marianna , Kaško Dávid , Turek Martin , Guľašová Zuzana , Hertelyová Zdenka 
Published: August 2023

SummarySignificant acute cardiovascular, metabolic, and endocrine changes have been traced to short-lasting cold water immersion (CWI); however, the long-term impact of recurrent CWI on atherogenesis, lipid parameters, and fat distribution has not yet been studied. The goal of this study was to investigate the alleged protective effect. A total of 35 healthy volunteers were monitored for a period of 5 months during which the CWI was performed under standardized conditions (three times per week for 7–10 min, without neoprene equipment). Volunteers with measured weight or muscle mass increases of more than 5% were ineligible. An analogous control group (N = 30) was included. At the onset and completion of the study, blood samples were obtained, and clinical assessments took place. PCSK9 and hsCRP levels were measured together with other lipid-related and non-lipid-related indicators. Carotid intima-media thickness test (cIMT) and echo-tracking for the identification of arterial stiffness (PWV, AI, and β) were used to identify early vascular alterations. Hepatorenal index (HRI) calculations served to quantify liver steatosis, while changes in subcutaneous and visceral fat thickness were used to quantify fat distribution. The given protocol was successfully completed by 28 volunteers. Long-term repeated CWI resulted in a significant decline in cIMT (p = 0.0001), AI (p = 0.0002), Beta (p = 0.0001), and PWV (p = 0.0001). PCSK9 (p = 0.01) and hsCRP (p = 0.01) showed a significant decrease when compared to initial values. In comparison to the starting values, liver fat accumulation decreased by 11% on average (HRI p = 0.001). LDL, TC, TG, and VLDL levels all significantly decreased as well. We suggest that repeated CWI may have beneficial impact on lipid, non-lipid, and lipid-related indices, as well as atherogenesis and liver fat storage.
Altered functional connectivity of the hippocampus with the sensorimotor cortex induced by long-term experience of virtual hand illusion
Authors: Chen Shanshan , Hu Gang , Meng Xiangfeng , Guo Jie , Fang Hui , Jiang Haiyan , Weng Dongdong 
Published: August 2023

AbstractSynchronizing the movement of a virtual hand with an unseen real hand in a virtual environment is an effective method to induce a sense of ownership of the virtual hand. Although several neuroimaging studies have revealed neural mechanisms related to the ongoing process of ownership illusion, the effect of the long-term experience of ownership illusion on brain activity remains to be investigated. Here, we developed an apparatus based on real-time image matting and virtual reality technology which allowed us to use the image of participants’ real hands as their virtual hands and synchronize the movement of the virtual hands with the unseen real hands in a virtual scene. Resting-state functional imaging data were acquired immediately after participants completed several light office tasks with the virtual hands in either the virtual environment (virtual hand condition) or real environment (real hand condition). Significant positive functional connectivity of the hippocampus with the primary somatosensory and motor cortex was only observed in the virtual hand condition. The results provided novel evidence for the involvement of hippocampal-sensorimotor connection in the long-term experience of virtual hand ownership. The functional connection reorganization of the hippocampus might promote multi-sensory information integration into memory and updated the sense of body ownership, which offered important insights into the neural network underlying the availability of long-term use of VR technology in healthcare and rehabilitation.
A multi-way analysis of similarity patterns in longevity improvements
Authors: Cardillo Giovanni , Giordani Paolo , Levantesi Susanna , Nigri Andrea , Spelta Alessandro 
Published: August 2023

AbstractWith the increasing availability of temporal data, a researcher often analyzes information saved into matrices, in which entries are replicated in different occasions. Such multidimensional data can be stored in arrays or tensors in a way that relevant patterns among variables can be teased apart by retaining the time-varying nature of the data. In this work, we show how the nonnegative three-way DEcomposition into DIrectional COMponents (DEDICOM) model is able to extract meaningful relational patterns from multi-population mortality data. The dataset considered is provided by the human mortality database (HMD) and refers to three dimensions: countries, age groups and years. The three-dimensional decomposition technique identifies persistent groups of countries with homogeneous mortality behaviours related to the evolutionary process of longevity improvements. Moreover, we exploit both country group information and recurrent neural networks to forecast future trajectories of similarities among countries’ mortality. Our work, by specifically describing the mesoscale interactions between countries and their evolution in time, could help to design appropriate actions against longevity risk that may impact the stability conditions of life assurance and pensions.
Numerical analysis of nonlinear degenerate parabolic problems with application to eddy current models
Authors: Acevedo Ramiro , Gómez Christian , Navia Paulo 
Published: August 2023

AbstractThis paper deals with the numerical analysis for a family of nonlinear degenerate parabolic problems. The model is spatially discretized using a finite element method; an implicit Euler scheme is employed for time discretization. We deduce sufficient conditions to ensure that the fully discrete problem has a unique solution and to prove quasi-optimal error estimates for the approximation. Finally, we propose a nonlinear degenerate parabolic problem that arises from electromagnetic applications in conductive nonlinear magnetic media and deduce its solubility and convergence by using the developed abstract theory, including some numerical results to confirm the obtained theoretical results.
Prescribed mean curvature flow of non-compact space-like Cauchy hypersurfaces
Authors: Gentile Giuseppe , Vertman Boris 
Published: August 2023

AbstractIn this paper we consider the prescribed mean curvature flow of a non-compact space-like Cauchy hypersurface of bounded geometry in a generalized Robertson–Walker space-time. We prove that the flow preserves the space-likeness condition and exists for infinite time. We also prove convergence in the setting of manifolds with boundary. Our discussion generalizes previous work by Ecker, Huisken, Gerhardt and others with respect to a crucial aspects: we consider any non-compact Cauchy hypersurface under the assumption of bounded geometry. Moreover, we specialize the aforementioned works by considering globally hyperbolic Lorentzian space-times equipped with a specific class of warped product metrics.
Expanding Early Psychosis Care across a Large and Diverse State: Implementation Lessons Learned from Administrative Data and Clinical Team Leads in Texas
Authors: Cohen Deborah A. , Klodnick Vanessa V. , Reznik Samantha J. , Lopez Molly A. 
Published: August 2023

AbstractThe U.S. is facing an unprecedented youth mental health crisis. Translating the findings from mental health intervention trials into large scale, accessible community-based services poses substantial challenges. Examination of state actions as a result of research-informed federal policy to improve youth access to quality mental healthcare is necessary. This mixed-methods study examines the implementation of evidence-informed multidisciplinary coordinated specialty care (CSC) for first-episode psychosis (FEP) services across Texas. The study explores CSC service model components, site location and participant characteristics, and implementation barriers. This cross-sectional study analyzes State of Texas public mental health administrative data from 2015 to 2020, including CSC site (n = 23) characteristics and CSC participant (n = 1682) demographics. Texas CSC site contracts were compared to OnTrackNY, a leading CSC model in the U.S. for CSC service element comparison. In-depth interviews with CSC Team Leads (n = 22) were analyzed to further understand CSC service elements and implementation barriers using qualitative content analysis. CSC was implemented across three waves in 2015, 2017, and 2019—serving 1682 participants and families. CSC sites were located in adult mental health programs; approximately one third of CSC participants were under 18 years. CSC implementation challenges reported by Team Leads included: staff role clarification, collaboration and turnover, community outreach and referrals, child and adult service billing issues, and adolescent and family engagement. Study findings have implications for large state-wide evidence-based practice implementation in transition-to-adulthood community mental health.
Subsequent primary neoplasms after childhood cancer therapy – design and description of the German nested case–control study STATT-SCAR
Authors: Scholz-Kreisel Peter , Becker Cornelia , Kaiser Melanie , Mahmoudpour Seyed Hamidreza , Voigt Mathias , Ressing Meike , Blettner Maria , Calaminus Gabriele , Baust Katja , Scholtes Cathy , Zimmermann Martin , Zeissig Sylke Ruth , Schmidberger Heinz , Karle Heiko , Meyer-Oldenburg Sarah , Kaatsch Peter , Spix Claudia 
Published: August 2023

Abstract
Background
Subsequent primary neoplasms (SPN) are among the most severe late effects and the second most frequent cause of death in childhood cancer patients. In this paper we introduce method and properties of the STATT-SCAR study (Second Tumor After Tumor Therapy, Second Cancer After Radiotherapy), which is a joint nested matched case–control study to evaluate the impact of chemotherapy (STATT) as well as radiotherapy (SCAR) on the risk of developing a SPN.

Methods
Based on the cohort of the German childhood cancer registry (GCCR), we selected patients diagnosed with a first neoplasm before age 15 or younger between 1980 and 2014. We selected those with a SPN at least half a year after the first neoplasm, and matched up to four controls to each case. Therapy data were acquired from various sources, including clinical study centers and treating hospitals. To analyze the impact of radiotherapy, organ doses were estimated by using reconstructed treatment plans. The effect of chemotherapy was analyzed using substance groups summarized after isotoxic dose conversion.

Results
1244 cases with a SPN were identified and matched with 4976 controls. Treatment data were acquired for 83% of all match groups (one case and at least one control). Based on preliminary analyses, 98% of all patients received chemotherapy and 54% of all patients were treated with radiotherapy.

Conclusions
Based on our data, detailed analyses of dose response relationships and treatment element combinations are possible, leading to a deeper insight into SPN risks after cancer treatments.

Trial registration
The study is registered at the German clinical trial register (DRKS) under number DRKS00017847 [45].