bluuebunny/crossref_metadata_2025_split huggingface dataset:
Isolation, identification, and in vitro probiotic characterization of forty novel Bifidobacterium strains from neonatal feces in Erzurum province, Türkiye
Authors: Güler Muhammet Akif , Çetin Bülent , Albayrak Bülent , Meral‐Aktaş Hacer , Tekgündüz Kadir Şerafettin , Kara Mustafa , Işlek Ali 
Published: February 2024

AbstractBACKGROUNDNeonatal feces are one of the most important sources for probiotic isolation. The purpose of this study was the isolation and identification of Bifidobacterium spp. from neonatal feces and the evaluation of in vitro probiotic properties of strains including safety tests.RESULTSA total of 40 isolates were obtained from 14 healthy newborns' feces in Erzurum province, Türkiye. By their rep‐PCR patterns and 16S rRNA gene sequences, isolates were identified as 26 Bifidobacterium breve and 14 Bifidobacterium longum. Fifteen of the isolates tolerated bile salts and showed high resistance to simulated gastric juice. Isolates exhibited varying rates of auto‐aggregation and hydrophobicity. In addition, most of the isolates displayed antibacterial activity against Escherichia coli O157:H7, Staphylococcus aureus ATCC 29213, Salmonella Typhimurium RSHMB 95091, and Pseudomonas aeruginosa ATCC 9027. However, only one strain showed bile salt hydrolase activity and two strains showed the ability to produce H2O2. Bifidobacterium strains were generally sensitive to the tested antibiotics and lacked kanamycin, gentamicin, and streptomycin resistance genes, and hemolytic and DNAse activities. On the other hand, it was determined that five strains had various virulence genes including gelE, esp, efaAfs, hyl, and ace.CONCLUSIONResults of the present study suggested that B. longum BH28, B. breve BH4 and B. breve BH5 strains have the potential as probiotic candidates for further studies. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
Nutritional and physicochemical characteristics of Asiatic hard clam powder prepared by different cook‐drying processes: a comparative study
Authors: Viji Pankyamma , Binsi Puthanpurakkal Kizhakethil , Sireesha Senapathi , S. J. Laly , Ninan George 
Published: February 2024

AbstractBACKGROUNDAsiatic hard clam (Meretrix meretrix) is an underutilized bivalve resource. This study discusses dried clam powders prepared from this resource to enhance its utilization and improve nutritional security in protein‐deficient populations. Dried clam powder was prepared from Asiatic hard clam and the effects of different pre‐cooking methods (boil‐dried clam powder, BDCP; steam‐dried clam powder, SDCP; and microwave‐dried clam powder, MDCP) on nutritional (proximate composition, amino acid profiling, mineral profiling, fatty acid profiling) and physicochemical qualities were investigated.RESULTSDifferent pre‐cooking methods significantly influenced the characteristics of the clam powder. The MDCP sample showed the highest concentration of amino acids, polyunsaturated fatty acids, Na, K, Ca and Mg content compared to BDCP and SDCP. The boiling process led to a loss of nutritional quality in terms of amino acids and macrominerals. The MDCP displayed the highest solubility in water (30.10%) but its oil and water absorption characteristics were the lowest among all the samples. Boil‐cooked clam powder displayed the highest oil binding (2.03 mL g−1 protein) capacity. Boiling and steaming processes resulted in malondialdehyde generation compared to microwaving. Different pre‐cooking processes did not influence the colour attributes significantly, but the control sample prepared without pre‐cooking (CCP) had a significantly lower L* value (32.34), resulting in a darker product. In vitro digestibility of the clam powder varied in the order MDCP > SDCP > BDCP > CCP.CONCLUSIONThe study demonstrated that nutritionally rich protein powder can be prepared from Asiatic hard clam. Based on the results, microwave pre‐cooking is considered the best pre‐cooking method to preserve the nutritional qualities of clam powder. © 2024 Society of Chemical Industry.
Comparative analysis on the performance of different types of input‐ and command‐shaping controllers in minimizing payload residual vibration of an overhead crane with an inclined supporting track
Authors: Alfares Mohammed , Alhazza Khaled 
Published: February 2024

AbstractReducing the effects of external disturbance on overhead crane systems is crucial, as they can impair the controller performance and cause excessive vibrations or oscillations of the payloads. One such external disturbance is the inclination of the supporting track of the crane trolley, which causes the system dynamics model to change. An open‐loop control strategy is widely utilized to control the payload sway motion and generally does not require any alterations in the physical structure of a system or the installation of sensors and/or actuators. Input and command shaping are two common open‐loop control techniques applied to control overhead cranes. In this paper, the effect of moving an overhead crane system along an inclined supporting track is investigated. In addition, the ability of different types of input‐ and command‐shaping control schemes to suppress the residual vibrations due to trolley track inclination is demonstrated. Two types of input‐shaping controllers, which are double‐step, zero vibration, and one command waveform (WF) shaper based on a trigonometric function, are used and tested. A linear equation of motion of the overhead crane resting on an inclined surface is developed to simulate the overhead crane and payload motion. The effectiveness of the different types of open‐loop controllers to suppress residual vibrations is verified by both simulation and experimental results. In addition, a new WF command shaper is proposed and designed to overcome track inclination while eliminating payload residual vibration. A comprehensive comparative analysis, both numerically and experimentally, is performed on the new proposed shaper to measure its effectiveness in handling inclination when compared to other types of open‐loop controllers. The new shaper outperforms other controllers in eliminating payload residual vibration for a wider range of inclination angles.
Insight into hydration inhibition mechanism of amino trimethylene phosphonic acid on tricalcium silicate from first‐principles calculations
Authors: Zhang Yue , Xin Zhaorui , Ding Zhiheng , Wang Pan , Wang Muhan , Wang Xinpeng , Xu Qingqing , Xu Jing , Li Zhongjuan , Guan Jing , Hou Dongshuai 
Published: February 2024

AbstractAlthough amino trimethylene phosphoric acid (ATMP) has been widely used as a retarder for Portland cement, its effect on cement hydration is poorly understood at the atomic level. In this study, we combine static calculation and ab initio molecular dynamics (AIMD) simulation to reveal the mechanism of the effect of ATMP on the initial stage of C3S hydration from multiple perspectives, quantitatively analyze the structural reconstruction and charge migration at the ATMP/C3S interface in the aqueous environment. By adsorbing on the surface of C3S, ATMP occupies the adsorption site of water molecules. Compared with the pure C3S surface, the addition of ATMP delays the hydroxylation of the C3S surface and inhibits the formation of Ca‐Ow bonds. This work gives new insights into understanding the hydration of C3S with ATMP and offers new approach of designing new cement retarder at the molecular level.
Opportunities and challenges of interdisciplinarity in river water environmental ethics and integrated river basin management
Authors: Xia Jun , Xue Ying , Li Pengjun , Song Jiyun , Wang Gangsheng , Luo Wenguang 
Published: February 2024

AbstractThis paper examines the ethical issues of water environment in the context of river management in practical engineering and technological applications. In particular, three important issues are discussed in this paper referring to two actual engineering cases in ancient and modern China, that is, the construction of ancient Dujiangyan irrigation project in Sichuan, China, and the modern practice of integrated operation of flood control and pollution prevention in Huai River Basin. The three issues include how to consider the trade‐offs between flood control and irrigation, how to balance flood control and contamination prevention related to sudden water pollution incident, and how to ensure the protection of water environments and ecology in rivers under the grand challenges of natural environmental changes and high‐intensity human activities. Finally, this paper concludes by emphasizing the future development of water environmental ethics and its interdisciplinary integration with modern science & technology in smart river management in China.
Investigating the impact of transient hardware faults on deep learning neural network inference
Authors: Rahman Md Hasanur , Laskar Sabuj , Li Guanpeng 
Published: February 2024

SummarySafety‐critical applications, such as autonomous vehicles, healthcare, and space applications, have witnessed widespread deployment of deep neural networks (DNNs). Inherent algorithmic inaccuracies have consistently been a prevalent cause of misclassifications, even in modern DNNs. Simultaneously, with an ongoing effort to minimize the footprint of contemporary chip design, there is a continual rise in the likelihood of transient hardware faults in deployed DNN models. Consequently, researchers have wondered the extent to which these faults contribute to DNN misclassifications compared to algorithmic inaccuracies. This article delves into the impact of DNN misclassifications caused by transient hardware faults and intrinsic algorithmic inaccuracies in safety‐critical applications. Initially, we enhance a cutting‐edge fault injector,TensorFI, for TensorFlow applications to facilitate fault injections on modern DNN non‐sequential models in a scalable manner. Subsequently, we analyse the DNN‐inferred outcomes based on our defined safety‐critical metrics. Finally, we conduct extensive fault injection experiments and a comprehensive analysis to achieve the following objectives: (1) investigate the impact of different target class groupings on DNN failures and (2) pinpoint the most vulnerable bit locations within tensors, as well as DNN layers accountable for the majority of safety‐critical misclassifications. Our findings regarding different grouping formations reveal that failures induced by transient hardware faults can have a substantially greater impact (with a probability up to 4 higher) on safety‐critical applications compared to those resulting from algorithmic inaccuracies. Additionally, our investigation demonstrates that higher order bit positions in tensors, as well as initial and final layers of DNNs, necessitate prioritized protection compared to other regions.
Integration of machine learning for developing a prognostic signature related to programmed cell death in colorectal cancer
Authors: Xu Qi‐Tong , Qiang Jian‐Kun , Huang Zhi‐Ye , Jiang Wan‐Ju , Cui Xi‐Mao , Hu Ren‐Hao , Wang Tao , Yi Xiang‐Lan , Li Jia‐Yuan , Yu Zuoren , Zhang Shun , Du Tao , Liu Jinhui , Jiang Xiao‐Hua 
Published: February 2024

AbstractBackgroundColorectal cancer (CRC) presents a significant global health burden, characterized by a heterogeneous molecular landscape and various genetic and epigenetic alterations. Programmed cell death (PCD) plays a critical role in CRC, offering potential targets for therapy by regulating cell elimination processes that can suppress tumor growth or trigger cancer cell resistance. Understanding the complex interplay between PCD mechanisms and CRC pathogenesis is crucial. This study aims to construct a PCD‐related prognostic signature in CRC using machine learning integration, enhancing the precision of CRC prognosis prediction.MethodWe retrieved expression data and clinical information from the Cancer Genome Atlas and Gene Expression Omnibus (GEO) datasets. Fifteen forms of PCD were identified, and corresponding gene sets were compiled. Machine learning algorithms, including Lasso, Ridge, Enet, StepCox, survivalSVM, CoxBoost, SuperPC, plsRcox, random survival forest (RSF), and gradient boosting machine, were integrated for model construction. The models were validated using six GEO datasets, and the programmed cell death score (PCDS) was established. Further, the model's effectiveness was compared with 109 transcriptome‐based CRC prognostic models.ResultOur integrated model successfully identified differentially expressed PCD‐related genes and stratified CRC samples into four subtypes with distinct prognostic implications. The optimal combination of machine learning models, RSF + Ridge, showed superior performance compared with traditional methods. The PCDS effectively stratified patients into high‐risk and low‐risk groups, with significant survival differences. Further analysis revealed the prognostic relevance of immune cell types and pathways associated with CRC subtypes. The model also identified hub genes and drug sensitivities relevant to CRC prognosis.ConclusionThe current study highlights the potential of integrating machine learning models to enhance the prediction of CRC prognosis. The developed prognostic signature, which is related to PCD, holds promise for personalized and effective therapeutic interventions in CRC.
Phase 1 study of latozinemab in progranulin‐associated frontotemporal dementia
Authors: Ward Michael , Carter Lawrence P. , Huang Julie Y. , Maslyar Daniel , Budda Balasubrahmanyam , Paul Robert , Rosenthal Arnon 
Published: February 2024

AbstractINTRODUCTIONHeterozygous mutations in the GRN gene lead to reduced progranulin (PGRN) levels in plasma and cerebrospinal fluid (CSF) and are causative of frontotemporal dementia (FTD) with > 90% penetrance. Latozinemab is a human monoclonal immunoglobulin G1 antibody that is being developed to increase PGRN levels in individuals with FTD caused by heterozygous loss‐of‐function GRN mutations.METHODSA first‐in‐human phase 1 study was conducted to evaluate the safety, tolerability, pharmacokinetics (PK), and pharmacodynamics (PD) of multiple‐dose intravenous administration of latozinemab in eight symptomatic participants with FTD caused by a heterozygous loss‐of‐function GRN mutation (FTD‐GRN).RESULTSLatozinemab demonstrated favorable safety and PK/PD profiles. Multiple‐dose administration of latozinemab increased plasma and CSF PGRN levels in participants with FTD‐GRN to levels that approximated those seen in healthy volunteers.DISCUSSIONData from the first‐in‐human phase 1 study support further development of latozinemab for the treatment of FTD‐GRN.Highlights
GRN mutations decrease progranulin (PGRN) and cause frontotemporal dementia (FTD).
Latozinemab is being developed as a PGRN‐elevating therapy.
Latozinemab demonstrated a favorable safety profile in a phase 1 clinical trial.
Latozinemab increased PGRN levels in the CNS of symptomatic FTD‐GRN participants.
Evolution of Military Design
Authors: Trew Jason , Zweibelson Ben , Riggs Daniel 
Published: February 2024

AbstractThe origins of design are linked to humanity’s strategic ability to leverage imagination for advantages. Furthermore, the link between the design discipline and security affairs is reinforced by how design (in its various forms) co-evolved with military art and science. Their tangled relationship is particularly evident during the so-called modern period in which design became its own discipline, when military power and industrialization melded into the new character of politics, and all of it was reflected in the shifting character of warfare.
Open Battery Systems
Authors: Diéz Eduardo Sanchez , Poli Federico , Soavi Francesca 
Published: February 2024

AbstractGlobal battery demand for stationary storage is expected to increase up to more than 2500 GWh in the next 10 years. In this scenario, the redox flow batteries (RFBs) and metal–oxygen (air) batteries (MABs) represent a strategic alternative to LIBs.RFBs and MABs share a unique feature: unlike conventional LIBs and conventional batteries that are made by two solid electrodes, separated by an electrolyte/separator assembly, and that are hermetically sealed, RFBs and MABs can be considered as “open systems.” Besides the specific electrochemical processes that drive RFB and MAB operation and that will be discussed in the next sections, the open architecture of RFBs and MABs provides an inherent advantage vs. the closed batteries in terms of safety. Indeed, dangerous internal pressure and/or temperature rise that accidentally take place in case of battery failure can be mitigated.In the following, the most recent developments of novel open battery architectures are presented, while promises and challenges of these open systems are discussed.
Methodological Challenges of Prospective Assessments
Authors: Cerdas Felipe , Baars Joris , Ali Abdur-Rahman , von Drachenfels Nicolas 
Published: February 2024

AbstractTraditionally, environmental, economic, and social impact assessments of technological innovations have been conducted retrospectively, which means assessing the present or past impacts of products and services. However, for the evaluation of future aspects of technological developments, alternative assessment methods are needed. Prospective assessment is a future-oriented method that can be used to assess environmental, economic, and social impacts. Prospective assessments, like retrospective assessments, provide guidance to decision-makers, including technology developers, policymakers, and manufacturers. Despite the benefits offered by such assessments, a standard method to follow when conducting a prospective assessment presently does not exist.This section focuses on the methodological challenges of prospective assessments for the evaluation of the impacts of emerging technologies, with a particular focus on emerging battery technologies. Four key challenges of prospective assessments are defined and discussed, being data availability and quality, scaling issues, uncertainty management and variability, and comparability. Each of these challenges is described, and existing methods are suggested to mitigate the challenges. The section concludes by emphasising the need for harmonised and standardised methods when communicating results related to prospective LCAs. In addition, studies need to address the key challenges identified to improve the wider acceptance of results amongst stakeholders and decision-makers.
Batteries: Advantages and Importance in the Energy Transition
Authors: Colombo Cristian Giovanni , Longo Michela , Zaninelli Dario 
Published: February 2024

AbstractWith the growing push toward decarbonization of the electricity generation sector, more attention is paid to storage systems that can assist renewable energy sources (RES). Due to their variability, intermittent RES (such as wind or solar radiation) do not allow a power production distributed uniformly over the short term up to the mid- and long term. Storage of renewable electricity can significantly contribute to mitigate these issues, enhancing power system reliability and, thus, RES penetration. Among energy storage technologies, the potential applications of battery are discussed in this chapter. Focus is placed on applications related to battery energy systems integration in both power systems and electric transportation means.For grid integration, bulk energy services, transmission and distribution network support, and capacity firming coupled to highly variable RES plants are addressed. Regarding transportation applications, electric mobility and perspectives on the interaction of electric vehicles (EVs) with the electric infrastructure are presented and discussed. Finally, this chapter addresses issues related to EVs’ battery aging and their dismission and exploitation as second life batteries in stationary applications.
Battery Market Segmentation
Authors: Wolf Stefan , Olarte Javier 
Published: February 2024

AbstractBatteries play a key role in the electrification of many applications, covering a wide range from mobility to stationary (including grid-integrated utility) and portable batteries in consumer electronics. As different as these application areas are, the suitable battery technologies are also very different. It is hence not surprising that the battery market is highly fragmented into segments with different technological requirements and growth dynamics. This chapter provides an overview of the growing battery market and its segments and outlines the specific requirements for battery technology in each segment, including cost parameters. Also, the current technological advances and driving forces for market development (most of them connected to transformation of energy systems toward renewable-based electricity) in each segment are discussed.
Automatische Modellgenerierung für die Virtuelle Inbetriebnahme bei HOMAG
Authors: Albrecht Ludwig , Seeger Patrick , Kübler Lukas 
Published: February 2024

Zusammenfassung
Die HOMAG Group verwendet Digitale Zwillinge entlang des Entwicklungs- und Herstellungsprozesses ihrer Produkte. Hierbei werden unter anderem Digitale Zwillinge in Hardware-in-the-Loop Simulationen eingesetzt. Die Simulationsmodelle der HOMAG-Maschinen und -Anlagen werden in einen modularen, mechatronischen Engineering-Baukasten integriert und können aus diesem zur Anwendung gebracht werden. Zur massiven Reduzierung von Modellierungszeiten bei individuellen Kundenmaschinen und -anlagen werden für einen wirtschaftlichen Einsatz der Virtuellen Inbetriebnahme bei HOMAG Digitale Zwillinge von kundenindividuellen Maschinen und Anlagen über einen größtenteils automatisierten Produktionsprozess generiert und sind dadurch unmittelbar für verschiedene Anwendungsfälle einsetzbar.
Simulationsmodelle der Virtuellen Inbetriebnahme als Lernumgebung für Reinforcement Learning
Authors: Jaensch Florian , Verl Alexander 
Published: February 2024

ZusammenfassungDie steigenden Anforderungen der Produktionstechnik nach flexiblen und trotzdem wirtschaftlich effizienten Anlagen stellt die Automatisierungstechnik vor große Herausforderungen. Die Umstellung von beispielsweise einer Roboterzelle auf ein neues Produkt muss dabei schnell und aufwandsarm möglich sein. Die Steuerungssysteme, sowie die zugehörigen Engineering Methoden, müssen zunehmend intelligent und lernfähig werden, um möglichst viele der bisher manuellen Aufwände selbstständig zu übernehmen. Die Simulationsumgebung für eine Virtuelle Inbetriebnahme stellt eine geeignete Lernumgebung dar, in der das Steuerungssystem, mit Methoden des maschinellen Lernens, automatisch trainiert werden kann. Dafür müssen die Simulationswerkzeuge erweitert und möglichst standardisierte Schnittstellen geschaffen werden.
Digital Twin as a Service
Authors: von Bergen Timm , Schnierle Marc , Röck Sascha 
Published: February 2024

ZusammenfassungIm mechatronischen Entwicklungsprozess des Maschinen- und Anlagenbaus entstehen Digitale Zwillinge, die zur Entwicklungsunterstützung und Virtuellen Inbetriebnahme von Steuerungssoftware sowie -hardware eingesetzt werden. Jedoch werden die Digitalen Zwillinge über den Entwicklungsprozess hinaus bislang kaum einer systematischen Weiterverwendung zugeführt. Dies ist auf die hohen Anforderungen einer standort- und endgeräteunabhängigen Verfügbarkeit und Vernetzungsfähigkeit der Digitalen Zwillinge zurückzuführen. Paradigmen der Cloud- und Webtechnologien bieten in diesen Anforderungsfeldern Lösungen an, die neue Anwendungspotenziale eröffnen. In diesem Beitrag wird dazu das Konzept des Digital Twin as a Service präsentiert, das die Grundprinzipien der Cloud- und Webtechnologien auf die Anwendung und Bereitstellung von Digitalen Zwillingen überträgt.