bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization of process parameters for the development of Ni–Al-Ti-Mn-Co-Fe–Cr high entropy alloy system via spark plasma sintering
Authors: Olorundaisi Emmanuel , Babalola Bukola Joseph , Bayode Bamidele Lawrence , Teffo Linda , Olubambi Peter A. 
Published: April 2023

AbstractA novel equal atomic Ni–Al-Ti-Mn-Co-Fe–Cr high entropy alloy (HEA) was developed via the spark plasma sintering (SPS) process. This study investigates the influence of the sintering parametric processes, which consist of the sintering temperature (ST) and heating rate (HR) at constant pressure and dwelling time (DT) on the Microhardness (MH) and relative density (RD) of the developed HEA. Response surface methodology (RSM) was used to develop a predictive model. The design of experiment (DOE) approach was adopted to reduce the number of experiments and eliminate trial by error. ST and HR were considered model variables in developing the model. The user-defined design (UDD) under RSM was used to predict the optimal sintering parameters, and an experiment was conducted to validate the result. The result indicates that ST and HR play a significant role in achieving high densification and hardness. The developed alloy shows the highest MH value of 136.3 HV at 850 °C and an HR of 100 °C/min. Equally, the least crystallite size of 2.05 µm was realized at the maximum ST. However, the modeling response suggested that full densification of about 99% can be achieved at an ST of 850 °C, a pressure of 50 MPa, a DT of 5 min, and an HR of 100 °C/min.
Critical analysis of the prescription and evaluation of protein kinase inhibitors for oncology in Germany
Authors: Obst Caecilia S. , Seifert Roland 
Published: April 2023

AbstractThe prices of oncology drugs have been rising progressively in recent years. Despite accounting for only a small share of prescriptions, oncology drugs are the most expensive drugs on the market. However, the association between drug price and clinical benefit often remains questionable. Therefore, we set out to analyze the development of prescription and benefit assessment of protein kinase inhibitors. We identified 20 protein kinase inhibitors with oncological indications that were newly approved by theEuropean Medicines Agency(EMA) between 2015 and 2019, based on theArzneiverordnungsreport(AVR,Drug Prescription Report). For these 20 drugs, the number of prescriptions, sales, defined daily dose (DDD), and DDD costs were identified for the year of approval and for 2020, respectively, based on data from theWissenschaftliches Institut der Ortskrankenkassen(WIdO,Scientific Institute of the General Local Health Insurance Fund, AOK). Moreover, the additional benefit assessments by theGemeinsamer Bundesausschuss(GBA,Federal Joint Committee) were considered for each drug. It is shown that the share of a drug in prescriptions, sales, and DDD does not correlate with the clinical benefit of the drug as measured by the additional benefit assessment by the GBA. Lastly, the advertisement pattern of protein kinase inhibitors in a representative oncology journal does not correlate with drug benefit. In conclusion, the immense costs of oncology drugs are therefore largely caused by drugs for which no additional benefit has been proven by the GBA. In order to ensure the long-term stability of health care systems, price-regulation measures are urgently needed, especially for drugs whose additional benefit has not been proven.
Immune checkpoint inhibition combined with targeted therapy using a novel virus-like drug conjugate induces complete responses in a murine model of local and distant tumors
Authors: Huis in ‘t Veld Ruben V. , Ma Sen , Kines Rhonda C. , Savinainen Anneli , Rich Cadmus , Ossendorp Ferry , Jager Martine J. 
Published: April 2023

AbstractMetastases remain the leading cause of cancer-related death worldwide. Therefore, improving the treatment efficacy against such tumors is essential to enhance patient survival. AU-011 (belzupacap sarotalocan) is a new virus-like drug conjugate which is currently in clinical development for the treatment of small choroidal melanoma and high-risk indeterminate lesions in the eye. Upon light activation, AU-011 induces rapid necrotic cell death which is pro-inflammatory and pro-immunogenic, resulting in an anti-tumor immune response. As AU-011 is known to induce systemic anti-tumor immune responses, we investigated whether this combination therapy would also be effective against distant, untreated tumors, as a model for treating local and distant tumors by abscopal immune effects. We compared the efficacy of combining AU-011 with several different checkpoint blockade antibodies to identify optimal treatment regimens in an in vivo tumor model. We show that AU-011 induces immunogenic cell death through the release and exposure of damage-associated molecular patterns (DAMPs), resulting in the maturation of dendritic cells in vitro. Furthermore, we show that AU-011 accumulates in MC38 tumors over time and that ICI enhances the efficacy of AU-011 against established tumors in mice, resulting in complete responses for specific combinations in all treated animals bearing a single MC38 tumor. Finally, we show that AU-011 and anti-PD-L1/anti-LAG-3 antibody treatment was an optimal combination in an abscopal model, inducing complete responses in approximately 75% of animals. Our data show the feasibility of combining AU-011 with PD-L1 and LAG-3 antibodies for the treatment of primary and distant tumors.
Körperpsychotherapeutische Gruppentherapie für jugendliche Patientinnen mit Anorexia nervosa
Authors: Graute Lea Anna , Wessing Ida , Dalhoff Anke 
Published: April 2023

Zusammenfassung
Hintergrund
Ansätze zur Behandlung der Körperbildstörung, Kernsymptom der Anorexia nervosa (AN), fokussieren unterschiedliche Komponenten (perzeptiv, kognitiv-affektiv). Auf Basis der Beobachtung massiver Störungen der ganzheitlichen Körperwahrnehmung bei jugendlichen AN-Patientinnen wurde eine störungsspezifische körperpsychotherapeutische Gruppentherapie entwickelt, die gezielt Aspekte des Körpererlebens integriert.

Ziel der Arbeit
Evaluation und Untersuchung von Zusammenhängen mit Veränderungen des perzeptiven Körperbildes.

Material und Methoden
Am Ende der Gruppenteilnahme füllten 52 AN-Patentinnen (Alter: Mittelwert = 15,35 Jahre) den Therapiebeurteilungsfragebogen zur Konzentrativen Bewegungstherapie im Gruppen-Setting (TBF-KBT-G) aus. Körpermaßschätzungen mithilfe des Test for Body Image Distortion in Children and Adolescents (BID) zu Beginn und Ende der Gruppenteilnahme wurden verglichen. Korrelationen wurden genutzt, um Zusammenhänge zwischen Therapiebeurteilung und Veränderung der Körpermaßschätzung zu untersuchen.

Ergebnisse
Patientinnen berichteten von einer positiven Beziehung zur Therapeutin, einer positiven Gruppenatmosphäre sowie teils von positiven körperbezogenen Erfahrungen und vertieftem Selbstzugang anhand der KBT-Methode. Die Patientinnen überschätzten ihre Körpermaße, und dies bestand am Ende der Gruppenteilnahme fort. Patientinnen mit positiven körperbezogenen Erfahrungen zeigten eher eine bessere Körpermaßschätzung.

Diskussion
Trotz des Fokus auf den aversiv erlebten Körper beschrieben die jugendlichen AN-Patientinnen ein positives Beziehungserleben in der Gruppe und können die KBT-Methode teilweise gut für sich nutzen. Störungen des perzeptiven Körperbildes erscheinen relativ persistent; eher mit einer Verbesserung assoziiert waren positive körperbezogene Erfahrungen. Insgesamt sind diese Ergebnisse als ermutigend zu interpretieren.
Local and Overall Deviance R-Squared Measures for Mixtures of Generalized Linear Models
Authors: Di Mari Roberto , Ingrassia Salvatore , Punzo Antonio 
Published: April 2023

AbstractIn generalized linear models (GLMs), measures of lack of fit are typically defined as the deviance between two nested models, and a deviance-based R2 is commonly used to evaluate the fit. In this paper, we extend deviance measures to mixtures of GLMs, whose parameters are estimated by maximum likelihood (ML) via the EM algorithm. Such measures are defined both locally, i.e., at cluster-level, and globally, i.e., with reference to the whole sample. At the cluster-level, we propose a normalized two-term decomposition of the local deviance into explained, and unexplained local deviances. At the sample-level, we introduce an additive normalized decomposition of the total deviance into three terms, where each evaluates a different aspect of the fitted model: (1) the cluster separation on the dependent variable, (2) the proportion of the total deviance explained by the fitted model, and (3) the proportion of the total deviance which remains unexplained. We use both local and global decompositions to define, respectively, local and overall deviance R2 measures for mixtures of GLMs, which we illustrate—for Gaussian, Poisson and binomial responses—by means of a simulation study. The proposed fit measures are then used to assess, and interpret clusters of COVID-19 spread in Italy in two time points.
Discrimination between Gaussian process models: active learning and static constructions
Authors: Yousefi Elham , Pronzato Luc , Hainy Markus , Müller Werner G. , Wynn Henry P. 
Published: April 2023

AbstractThe paper covers the design and analysis of experiments to discriminate between two Gaussian process models with different covariance kernels, such as those widely used in computer experiments, kriging, sensor location and machine learning. Two frameworks are considered. First, we study sequential constructions, where successive design (observation) points are selected, either as additional points to an existing design or from the beginning of observation. The selection relies on the maximisation of the difference between the symmetric Kullback Leibler divergences for the two models, which depends on the observations, or on the mean squared error of both models, which does not. Then, we consider static criteria, such as the familiar log-likelihood ratios and the Fréchet distance between the covariance functions of the two models. Other distance-based criteria, simpler to compute than previous ones, are also introduced, for which, considering the framework of approximate design, a necessary condition for the optimality of a design measure is provided. The paper includes a study of the mathematical links between different criteria and numerical illustrations are provided.
Systemic oxidative stress associates with disease severity and outcome in patients with new-onset or worsening heart failure
Authors: de Koning Marie-Sophie L. Y. , Emmens Johanna E. , Romero-Hernández Esteban , Bourgonje Arno R. , Assa Solmaz , Figarska Sylwia M. , Cleland John G. F. , Samani Nilesh J. , Ng Leong L. , Lang Chim C. , Metra Marco , Filippatos Gerasimos S. , van Veldhuisen Dirk J. , Anker Stefan D. , Dickstein Kenneth , Voors Adriaan A. , Lipsic Erik , van Goor Harry , van der Harst Pim 
Published: April 2023

Abstract
Background
Oxidative stress may be a key pathophysiological mediator in the development and progression of heart failure (HF). The role of serum-free thiol concentrations, as a marker of systemic oxidative stress, in HF remains largely unknown.

Objective
The purpose of this study was to investigate associations between serum-free thiol concentrations and disease severity and clinical outcome in patients with new-onset or worsening HF.

Methods
Serum-free thiol concentrations were determined by colorimetric detection in 3802 patients from the BIOlogy Study to TAilored Treatment in Chronic Heart Failure (BIOSTAT-CHF). Associations between free thiol concentrations and clinical characteristics and outcomes, including all-cause mortality, cardiovascular mortality, and a composite of HF hospitalization and all-cause mortality during a 2-years follow-up, were reported.

Results
Lower serum-free thiol concentrations were associated with more advanced HF, as indicated by worse NYHA class, higher plasma NT-proBNP (P < 0.001 for both) and with higher rates of all-cause mortality (hazard ratio (HR) per standard deviation (SD) decrease in free thiols: 1.253, 95% confidence interval (CI): 1.171–1.341, P < 0.001), cardiovascular mortality (HR per SD: 1.182, 95% CI: 1.086–1.288, P < 0.001), and the composite outcome (HR per SD: 1.058, 95% CI: 1.001–1.118, P = 0.046).

Conclusions
In patients with new-onset or worsening HF, a lower serum-free thiol concentration, indicative of higher oxidative stress, is associated with increased HF severity and poorer prognosis. Our results do not prove causality, but our findings may be used as rationale for future (mechanistic) studies on serum-free thiol modulation in heart failure.

Graphical abstract
Associations of serum-free thiol concentrations with heart failure severity and outcomes
Mitotic phosphorylation of Tau/MAPT modulates cell cycle progression in prostate cancer cells
Authors: Clementi Letizia , Sabetta Samantha , Zelli Veronica , Compagnoni Chiara , Tessitore Alessandra , Mattei Vincenzo , Angelucci Adriano 
Published: April 2023

Abstract
Purpose
Tau/MAPT (microtubule associated protein tau) protein is actively studied for the pathologic consequences of its aberrant proteostasis in central nervous system leading to neurodegenerative diseases. Besides its ability to generate insoluble toxic oligomers, Tau homeostasis has attracted attention for its involvement in the formation of the mitotic spindle. This evidence, in association with the description of Tau expression in extra-neuronal tissues, and mainly in cancer tissues, constitutes the rationale for a more in-depth investigation of Tau role also in neoplastic diseases.

Methods
In our study, we investigated the expression of phosphorylated Tau in prostate cancer cell lines with particular focus on the residue Thr231 present in microtubule binding domain.

Results
The analysis of prostate cancer cells synchronized with nocodazole demonstrated that the expression of Tau protein phosphorylated at residue Thr231 is restricted to G2/M cell cycle phase. The phosphorylated form was unable to bind tubulin and it does not localize on mitotic spindle. As demonstrated by the use of specific inhibitors, the phosphorylation status of Tau is under the direct control of cdk5 and PP2A, while cdk1 activation was able to exert an indirect control. These mechanisms were also active in cells treated with docetaxel, where counteracting the expression of the dephosphorylated form, by kinase inhibition or protein silencing, determined resistance to drug toxicity.

Conclusions
We hypothesize that phosphorylation status of Tau is a key marker for G2/M phase in prostate cancer cells and that the forced modulation of Tau phosphorylation can interfere with the capacity of cell to efficiently progress through G2/M phase.
Mental health care use and related factors in adolescents and young adults with cancer
Authors: Hirayama Takatoshi , Ikezawa Satoru , Okubo Ryo , Mizuta Tomoko , Iwata Shintaro , Suzuki Tatsuya 
Published: April 2023

Abstract
Purpose
The actual state of mental health care use and related factors in adolescent and young adult (AYA) patients with cancer is not well understood in Japan. This study aimed to (1) examine the actual state of mental health care use among AYA patients with cancer and (2) describe socio-demographic and related factors associated with mental health care use.

Methods
We retrospectively reviewed the medical records of AYA patients with cancer aged 15–39 who first visited the National Cancer Center Hospital in Japan (NCCH) between January 2018 and December 2020. Logistic regression was used to analyze the association between social background characteristics and mental health care use. The association between the patient's course of cancer treatment and mental health care use was analyzed to help identify which patients might benefit from early mental health intervention.

Results
Among 1,556 patients, 945 AYA patients with cancer were registered. The median age at the time of the study was 33 years (range, 15–39 years). The prevalence of mental health care use was 18.0% (170/945). Age 15–19 years, female gender, urogenital cancer, gynecological cancer, bone or soft tissue cancer, head and neck cancer, and stage II–IV disease were associated with mental health care use. Regarding treatment, palliative treatment, chemotherapy, and hematopoietic stem cell transplantation were associated with mental health care use.

Conclusion
Factors associated with mental health care use were identified. Our findings potentially contribute to psychological support interventions for AYA patients with cancer.
Comparison of discrete- and continuous-time models for scheduling waste wood processing facilities
Authors: Ősz Olivér , Dávid Balázs , Hegyháti Máté 
Published: April 2023

AbstractWith the growing significance of environmental awareness, the role of renewable materials and their reuse and recycling possibilities have become increasingly important. Wood is one of the best examples for this, as it is a material that has a variety of primary uses, while also being a prime candidate for reuse and recycling. An important phase in most waste wood value chains is the processing of bulk waste from various sources, usually by means of shredding. This paper presents methods for scheduling the machines in such a waste wood processing facility, where incoming deliveries of different types of wood are processed by a series of treatment and transformation steps to produce shredded wood. Two mathematical models are developed for the problem that both allow overlaps between consecutive steps to optimize resource flow through the system. One of these is a more traditional discrete-time model, while the other is precedence-based and uses continuous-time variables for the timing of the various tasks. Both modeling techniques have their advantages and shortcomings with regard to the ease of integration of further problem-specific parameters and requirements. Next to providing a sound approach for the identified problem class, another aim is to evaluate, which technique suits better for this problem class, and should be used as a basis for extended and integrated cases in the future. Thus, the performance of these models is compared on instances that were randomly generated based on real-world distributions from the literature.
A combined approach for improving humanoid robots autonomous cognitive capabilities
Authors: Madani Kurosh , Rinaldi Antonio M. , Russo Cristiano , Tommasino Cristian 
Published: April 2023

AbstractRecent technologies advancements promise to change our lives dramatically in the near future. A new different living society is progressively emerging, witnessed from the conception of novel digital ecosystems, where humans are expected to share their own spaces and habits with machines. Humanoid robots are more and more being developed and provided with enriched functionalities; however, they are still lacking in many ways. One important goal in this sense is to enrich their cognitive capabilities, to make them more “intelligent” in order to better support humans in both daily and special activities. The goal of this research is to set a step in bridging the gap between symbolic AI and connectionist approaches in the context of knowledge acquisition and conceptualization. Hence, we present a combined approach based on semantics and machine learning techniques for improving robots cognitive capabilities. This is part of a wider framework that covers several aspects of knowledge management, from representation and conceptualization, to acquisition, sharing and interaction with humans. Our focus in this work is in particular on the development and implementation of techniques for knowledge acquisition. Such techniques are discussed and validated through experiments, carried out on a real robotic platform, showing the effectiveness of our approach. The results obtained confirmed that the combination of the approaches gives superior performance with respect to when they are considered individually.
MORGAN: a modeling recommender system based on graph kernel
Authors: Di Sipio Claudio , Di Rocco Juri , Di Ruscio Davide , Nguyen Phuong T. 
Published: April 2023

AbstractModel-driven engineering (MDE) is an effective means of synchronizing among stakeholders, thereby being a crucial part of the software development life cycle. In recent years, MDE has been on the rise, triggering the need for automatic modeling assistants to support metamodelers during their daily activities. Among others, it is crucial to enable model designers to choose suitable components while working on new (meta)models. In our previous work, we proposed MORGAN, a graph kernel-based recommender system to assist developers in completing models and metamodels. To provide input for the recommendation engine, we convert training data into a graph-based format, making use of various natural language processing (NLP) techniques. The extracted graphs are then fed as input for a recommendation engine based on graph kernel similarity, which performs predictions to provide modelers with relevant recommendations to complete the partially specified (meta)models. In this paper, we extend the proposed tool in different dimensions, resulting in a more advanced recommender system. Firstly, we equip it with the ability to support recommendations for JSON schema that provides a model representation of data handling operations. Secondly, we introduce additional preprocessing steps and a kernel similarity function based on item frequency, aiming to enhance the capabilities, providing more precise recommendations. Thirdly, we study the proposed enhancements, conducting a well-structured evaluation by considering three real-world datasets. Although the increasing size of the training data negatively affects the computation time, the experimental results demonstrate that the newly introduced mechanisms allow MORGAN to improve its recommendations compared to its preceding version.
A study on the optimal condition of ground truth area for liver tumor detection in ultrasound images using deep learning
Authors: Tosaki Taisei , Yamakawa Makoto , Shiina Tsuyoshi 
Published: April 2023

Abstract
Purpose
In recent years, efforts to apply artificial intelligence (AI) to the medical field have been growing. In general, a vast amount of high-quality training data is necessary to make great AI. For tumor detection AI, annotation quality is important. In diagnosis and detection of tumors using ultrasound images, humans use not only the tumor area but also the surrounding information, such as the back echo of the tumor. Therefore, we investigated changes in detection accuracy when changing the size of the region of interest (ROI, ground truth area) relative to liver tumors in the training data for the detection AI.

Methods
We defined D/L as the ratio of the maximum diameter (D) of the liver tumor to the ROI size (L). We created training data by changing the D/L value, and performed learning and testing with YOLOv3.

Results
Our results showed that the detection accuracy was highest when the training data were created with a D/L ratio between 0.8 and 1.0. In other words, it was found that the detection accuracy was improved by setting the ground true bounding box for detection AI training to be in contact with the tumor or slightly larger. We also found that when the D/L ratio was distributed in the training data, the wider the distribution, the lower the detection accuracy.

Conclusions
Therefore, we recommend that the detector be trained with the D/L value close to a certain value between 0.8 and 1.0 for liver tumor detection from ultrasound images.