bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assembly theory explains and quantifies selection and evolution
Authors: Sharma Abhishek , Czégel Dániel , Lachmann Michael , Kempes Christopher P. , Walker Sara I. , Cronin Leroy 
Published: October 2023

AbstractScientists have grappled with reconciling biological evolution1,2 with the immutable laws of the Universe defined by physics. These laws underpin life’s origin, evolution and the development of human culture and technology, yet they do not predict the emergence of these phenomena. Evolutionary theory explains why some things exist and others do not through the lens of selection. To comprehend how diverse, open-ended forms can emerge from physics without an inherent design blueprint, a new approach to understanding and quantifying selection is necessary3–5. We present assembly theory (AT) as a framework that does not alter the laws of physics, but redefines the concept of an ‘object’ on which these laws act. AT conceptualizes objects not as point particles, but as entities defined by their possible formation histories. This allows objects to show evidence of selection, within well-defined boundaries of individuals or selected units. We introduce a measure called assembly (A), capturing the degree of causation required to produce a given ensemble of objects. This approach enables us to incorporate novelty generation and selection into the physics of complex objects. It explains how these objects can be characterized through a forward dynamical process considering their assembly. By reimagining the concept of matter within assembly spaces, AT provides a powerful interface between physics and biology. It discloses a new aspect of physics emerging at the chemical scale, whereby history and causal contingency influence what exists.
A SISO FMCW radar based on inherently frequency scanning antennas for 2-D indoor tracking of multiple subjects
Authors: Sacco Giulia , Mercuri Marco , Hornung Rainer , Visser Huib , Lorato Ilde , Pisa Stefano , Dolmans Guido 
Published: October 2023

AbstractThe contextual non-invasive monitoring and tracking of multiple human targets for health and surveillance purposes is an increasingly investigated application. Radars are good candidates, since they are able to remotely monitor people without raising privacy concerns. However, radar systems are typically based on complex architectures involving multiple channels and antennas, such as multiple-input and multiple-output (MIMO) or electronic beam scanning, resulting also in a high power consumption. In contrast with existing technologies, this paper proposes a single-input and single-output (SISO) frequency-modulated continuous wave (FMCW) radar in combination with frequency scanning antennas for tracking multiple subjects in indoor environments. A data processing method is also presented for angular separation and clutter removal. The system was successfully tested in five realistic indoor scenarios involving paired subjects, which were either static or moving along predefined paths varying their range and angular position. In all scenarios, the radar was able to track the targets, reporting a maximum mean absolute error (MAE) of 20 cm and 5.64$$^\circ$$∘in range and angle, respectively. Practical applications arise for ambient assisted living, telemedicine, smart building applications and surveillance.
Structural studies of local environments in high-symmetry quasicrystals
Authors: Sosa Alan Rodrigo Mendoza , Kraemer Atahualpa S. , Oğuz Erdal C. , Schmiedeberg Michael 
Published: October 2023

AbstractThe statistics of how the local environment of a particle looks like, e.g., given by the distribution of nearest neighbor distances or the sizes of Voronoi cells, is important as a starting point for the calculation of many material properties like electronic or photonic band structures. Here we study local environments that occur in quasicrystals with large rotational symmetry. Both with analytical considerations based on geometric arguments and with an analysis of a large number of numerically created patches of high-symmetry quasicrystals we find that the Voronoi area’s distribution reaches a bimodal curve and that in the limit of large rotational symmetries the distribution of nearest neighbor distance converges against a universal curve, where $$27.7\%$$

27.7
%

of the vertices have their nearest neighbor at a normalized distance equal to 1, while for the other $$72.3\%$$

72.3
%

the nearest neighbor is at a distance less than 1. Therefore, the statistics of local environments is non-trivial but independent of the specific rotational symmetry. Thus properties that only depend on local environments are expected to be universal for all high-symmetry quasicrystals.
Down regulation of Cathepsin W is associated with poor prognosis in pancreatic cancer
Authors: Khojasteh-Leylakoohi Fatemeh , Mohit Reza , Khalili-Tanha Nima , Asadnia Alireza , Naderi Hamid , Pourali Ghazaleh , Yousefli Zahra , Khalili-Tanha Ghazaleh , Khazaei Majid , Maftooh Mina , Nassiri Mohammadreza , Hassanian Seyed Mahdi , Ghayour-Mobarhan Majid , Ferns Gordon A. , Shahidsales Soodabeh , Lam Alfred King-yin , Giovannetti Elisa , Nazari Elham , Batra Jyotsna , Avan Amir 
Published: October 2023

AbstractPancreatic ductal adenocarcinoma (PDAC) is associated with a very poor prognosis. Therefore, there has been a focus on identifying new biomarkers for its early diagnosis and the prediction of patient survival. Genome-wide RNA and microRNA sequencing, bioinformatics and Machine Learning approaches to identify differentially expressed genes (DEGs), followed by validation in an additional cohort of PDAC patients has been undertaken. To identify DEGs, genome RNA sequencing and clinical data from pancreatic cancer patients were extracted from The Cancer Genome Atlas Database (TCGA). We used Kaplan–Meier analysis of survival curves was used to assess prognostic biomarkers. Ensemble learning, Random Forest (RF), Max Voting, Adaboost, Gradient boosting machines (GBM), and Extreme Gradient Boosting (XGB) techniques were used, and Gradient boosting machines (GBM) were selected with 100% accuracy for analysis. Moreover, protein–protein interaction (PPI), molecular pathways, concomitant expression of DEGs, and correlations between DEGs and clinical data were analyzed. We have evaluated candidate genes, miRNAs, and a combination of these obtained from machine learning algorithms and survival analysis. The results of Machine learning identified 23 genes with negative regulation, five genes with positive regulation, seven microRNAs with negative regulation, and 20 microRNAs with positive regulation in PDAC. Key genesBMF,FRMD4A,ADAP2,PPP1R17, andCACNG3had the highest coefficient in the advanced stages of the disease. In addition, the survival analysis showed decreased expression ofhsa.miR.642a,hsa.mir.363,CD22,BTNL9, andCTSWand overexpression ofhsa.miR.153.1,hsa.miR.539,hsa.miR.412reduced survival rate.CTSWwas identified as a novel genetic marker and this was validated using RT-PCR. Machine learning algorithms may be used to Identify key dysregulated genes/miRNAs involved in the disease pathogenesis can be used to detect patients in earlier stages. Our data also demonstrated the prognostic and diagnostic value ofCTSWin PDAC.
Optimal selection of daily satellite precipitation product based on structural similarity index at 1 km resolution for the Pra catchment, Ghana
Authors: Gyasi-Agyei Yeboah , Obuobie Emmanuel , Yu Bofu , Addi Martin , Yahaya Bashiru 
Published: October 2023

AbstractThirteen satellite precipitation products (SPPs), re-gridded to 1 km resolution, were evaluated in terms of the structural similarity index (SSI) over the Pra catchment in Ghana. Three SPP scenarios were considered: Scenario one (S1) was the original SPPs; Scenario two (S2) was bias-corrected SPPs; and Scenario three (S3) was the better of S1 and S2 for each wet day. For each scenario, the best SPP was selected to constitute the 14th SPP referred to as the BEST SPP. Each SPP was evaluated in terms of SSI against the rain gauge rainfield for each wet day. For S1, the top three SPPs were TMPA, GSMAP and CMORPH; for S2, CMORPH, PERCCS and MSWEP were the top three; and for S3, CMORPH, PERCCS and TMPA came out on top in order of decreasing performance. Bias correction led to improvement in the overall SSI measure (SSIM) for 73% of wet days. The BEST SPP increased the SSIM of the best individual SPP by over 50% for S1, and over 30% for both S2 and S3. Comparing the BEST SPP of the three scenarios, S2 increased the SSIM statistic by 20% over that for S1, and SSIM was further improved by 4% for S3. It is highly recommended to use BEST SPP (S3) to generate the required 1 km × 1 km rainfields for the Pra, or other catchments around the world with a sparse rain gauge network, through conditional merging with rain gauge data as demonstrated.
National and regional trends in the prevalence of type 2 diabetes and associated risk factors among Korean adults, 2009–2021
Authors: Oh Jiyeon , Kim Soeun , Lee Myeongcheol , Rhee Sang Youl , Kim Min Seo , Shin Ju-Young , Lim Hyunjung , Lee Seung Won , Rahmati Masoud , Kim Sunyoung , Yon Dong Keon 
Published: October 2023

AbstractDisproportionate impact of COVID-19 on socioeconomic and behavioral variables may have impacted the prevalence of diabetes. We utilized nationwide long-term serial study from the 2009 to 2021 Korea Community Health Survey (KCHS). We explored national and regional prevalence and trends of diabetes according to the socioeconomic and behavioral factors before and during the pandemic. Also, we interpreted which groups became more vulnerable to the prevalence of diagnosed diabetes during the pandemic. A total of 2,971,349 adults aged (19 to 39, 40 to 59, and ≥ 60 years) were included in the analysis. The prevalence of diagnosed diabetes increased slowly during the pandemic (11.6% [95% CI 11.5–11.7] in 2020 and 12.4% [95% CI 12.3–12.6] in 2021), compared to the pre-pandemic era (7.9% [95% CI 7.8–7.9] in 2009–2011 and 11.3% [95% CI 11.3–11.4] in 2018–2019). Also, women, low-income group, low-educational group, and infrequent walking group showed less prevalence of diagnosed diabetes than the others. The diabetic population increased slowly than expected during the pandemic. The pandemic seems to contribute to an unanticipated increase in under-diagnosis of diabetes among the already minority. This study may suggest reinforcing access to healthcare services among the minority during the pandemic.
Biomechanical investigation of tasks concerning manual materials handling using response surface methodology
Authors: Adhaye Amit M. , Jolhe Dhananjay A. , Loyte Akshay R. , Devarajan Yuvarajan , Thanappan Subash 
Published: October 2023

AbstractIn typical manual material handling, the variations in walking pattern are decided by various factors, such as load being handled, frequency of handling, walking surface, etc. Traditional gait analysis protocols commonly evaluate individual factor within specified ranges associated with particular activities or pathologies. However, existing literature underscores the concurrent impact of multiple factors on gait. This study identifies five pivotal factors—walking speed, surface slope, load carried, carrying method, and footwear—as contributors to gait alterations. To address risk factors in manual material handling activities, we propose a unique design-of-experiment-based approach for multi-task gait analysis. Unraveling the relationship between manual handling attributes and human gait holds paramount importance in formulating effective intervention strategies. We optimized the five input factors across a cohort of 15 healthy male participants by employing a face-centered central composite design experimentation. A total of 29 input factor combinations were tested, yielding a comprehensive dataset encompassing 18 kinematic gait parameters (such as cadence, step length etc., measured using inertial measurement system), the isolated impacts of factors, and the interplay of two-factor interactions with corresponding responses. The results illuminate the optimal scenarios of input factors that enhance individual gait performance—these include wearing appropriate footwear, employing a backpack for load carriage, and maintaining a moderate walking pace on a medium slope with minimal load. The study identifies walking speed and load magnitude as primary influencers of gait mechanics, followed by the chosen carrying method. In consequence, the insights gained advocate for the refinement of manual material handling tasks based on the outcomes, effectively mitigating the risk of musculoskeletal disorders by suggesting the interventions for posture correction.
Xenopus Ssbp2 is required for embryonic pronephros morphogenesis and terminal differentiation
Authors: Cervino Ailen S. , Collodel Mariano G. , Lopez Ivan A. , Roa Carolina , Hochbaum Daniel , Hukriede Neil A. , Cirio M. Cecilia 
Published: October 2023

AbstractThe nephron, functional unit of the vertebrate kidney, is specialized in metabolic wastes excretion and body fluids osmoregulation. Given the high evolutionary conservation of gene expression and segmentation patterning between mammalian and amphibian nephrons, the Xenopus laevis pronephric kidney offers a simplified model for studying nephrogenesis. The Lhx1 transcription factor plays several roles during embryogenesis, regulating target genes expression by forming multiprotein complexes with LIM binding protein 1 (Ldb1). However, few Lhx1-Ldb1 cofactors have been identified for kidney organogenesis. By tandem- affinity purification from kidney-induced Xenopus animal caps, we identified single-stranded DNA binding protein 2 (Ssbp2) interacts with the Ldb1–Lhx1 complex. Ssbp2 is expressed in the Xenopus pronephros, and knockdown prevents normal morphogenesis and differentiation of the glomus and the convoluted renal tubules. We demonstrate a role for a member of the Ssbp family in kidney organogenesis and provide evidence of a fundamental function for the Ldb1–Lhx1-Ssbp transcriptional complexes in embryonic development.
Bio‐inspired structure constraints following control for enhancing hunting stability of high‐speed trains
Authors: Zhao Jingyu , Zhang Heng , Ling Liang , Zhang Zheshuo , Wang Kaiyun , Zhai Wanming 
Published: October 2023

AbstractHigh‐speed trains (HSTs) often face challenges associated with car‐body hunting, resulting from factors such as complex operating environments and wheel‐rail contact degradation. These issues have a significant impact on the ride quality and operational safety. Passive suspension systems are inadequate to provide satisfactory dynamic performance for HSTs in such circumstances. However, active suspension systems can provide an effective solution. To address the car‐body hunting stability of HSTs, this study proposes a novel control approach called displacement inequality constraint following control (ICFC‐BIS) for the active suspension of HSTs. The ICFC‐BIS leverages the beneficial nonlinearity of bio‐inspired structures (BIS) to indirectly achieve excellent dynamic characteristics of the BIS through actuators installed in the suspension of HSTs, eliminating the need for actual BIS installation. Numerical simulation results demonstrate that the proposed ICFC‐BIS can effectively suppress car‐body hunting motion, thereby enhancing the ride comfort of HSTs. Consequently, the operational safety and ride comfort indices of HSTs equipped with active suspension systems are significantly improved.
Bird's nest defect detection of transmission lines based on domain knowledge and occlusion reasoning
Authors: Dong Na , Zhang Wenjing , Chen Ze , Feng Haiyan , Jia Jiandong 
Published: October 2023

AbstractBird's nest defect is an important cause of transmission line faults. To achieve accurate detection of bird nest defects in complex scenarios, a bird nest defect detection model for transmission lines was proposed that combines domain knowledge and occlusion reasoning networks. On the one hand, the model utilized the domain knowledge of the location of the bird's nest, using edge detection to obtain tower area information to constrain the location of candidate frames. This helps to reduce the false detection caused by complex backgrounds. On the other hand, on the basis of analyzing the occlusion characteristics of bird nests, the model employed occlusion reasoning networks that randomly erase features at the feature level to simulate the occlusion of bird nests in real scenes and improve the model's detection capability for occluded targets. Additionally, a multi‐scale feature fusion algorithm was designed in this paper to adapt the model to the scale variations of bird nests in aerial images. Experimental results demonstrate that the model outperforms advanced target detection models and other bird nest defect detection methods, with an AP50 of 78.8% and an AR10 of 72.4% for defect detection.
Performance analysis of ground‐based long baseline radar distributed systems for space situational awareness
Authors: Díaz Riofrío Sebastián , Da Graça Marto Simão , Ilioudis Christos , Vasile Massimiliano , Clemente Carmine 
Published: October 2023

AbstractDetection of space objects is a key component of space situational awareness, which could help prevent and minimise space collisions. While there have been lots of radar systems designed to detect space objects, few of them have dealt with long baseline distributed bistatic pairs. The authors focus on the feasibility of long baseline bistatic radars, which can be extended for the multistatic case; and the performance of the multistatic system for a target at different altitudes assuming one transmitter over three different scenarios: a cluster of receivers, receivers spread throughout the world and the combination of the two previous cases. To analyse the performance the multiple‐input‐multiple‐output (MIMO) ambiguity function (AF) will be employed. The results of the MIMO AF show how the fusion of different bistatic pairs improves the detection capabilities. Moreover, when the different radar measurements are coherently summed in the MIMO AF, the uncertainty on the location of the target is reduced.
Photon-counting computed tomography – clinical application in oncological, cardiovascular, and pediatric radiology
Authors: Hagen Florian , Soschynski Martin , Weis Meike , Hagar Muhammad Taha , Krumm Patrick , Ayx Isabelle , Taron Jana , Krauss Tobias , Hein Manuel , Ruile Philipp , von zur Muehlen Constantin , Schlett Christopher L. , Neubauer Jakob , Tsiflikas Ilias , Russe Maximilian Frederik , Arnold Philipp , Faby Sebastian , Froelich Matthias F. , Weiß Jakob , Stein Thomas , Overhoff Daniel , Bongers Malte , Nikolaou Konstantin , Schönberg Stefan O. , Bamberg Fabian , Horger Marius 
Published: October 2023

Background Photon-counting detector computed tomography (PCD-CT) is a promising new technology with the potential to fundamentally change workflows in the daily routine and provide new quantitative imaging information to improve clinical decision-making and patient management.
Method The contents of this review are based on an unrestricted literature search of PubMed and Google Scholar using the search terms “photon-counting CT”, “photon-counting detector”, “spectral CT”, “computed tomography” as well as on the authors’ own experience.
Results The fundamental difference with respect to the currently established energy-integrating CT detectors is that PCD-CT allows for the counting of every single photon at the detector level. Based on the identified literature, PCD-CT phantom measurements and initial clinical studies have demonstrated that the new technology allows for improved spatial resolution, reduced image noise, and new possibilities for advanced quantitative image postprocessing.
Conclusion For clinical practice, the potential benefits include fewer beam hardening artifacts, a radiation dose reduction, and the use of new or combinations of contrast agents. In particular, critical patient groups such as oncological, cardiovascular, lung, and head & neck as well as pediatric patient collectives benefit from the clinical advantages.
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Characteristics and Outcomes of Obstetric Sepsis by Three Sets of Clinical Diagnostic Criteria: A Retrospective Study
Authors: Pohl Nicole , Bauer Melissa , Pancaro Carlo , Cassidy Ruth , Engoren Milo 
Published: October 2023

Objective Pregnancy-related mortality in the United States is the highest of all developed nations with a reported rate of 17 deaths per 100,000 live births in 2014 to 2017. Sepsis-related mortality is a major component of pregnancy-related mortality. Similar to nonpregnancy-related sepsis, the criteria for pregnancy-related sepsis are evolving. The purposes of this study were to compare three criteria for sepsis (Sepsis-2, Sepsis-3, California Maternal Quality Care Collaborative [CMQCC]) with one another and to determine patient outcomes using those three sets of criteria.
Study Design Using the electronic medical record, we obtained granular data on all patients at University of Michigan Medical Center from July 10, 2009 to September 4, 2019 with suspected sepsis (blood cultures and administration of antibiotics) during pregnancy until the 42nd postpartum day. Agreement between the three criteria were assessed with kappa and shown by a Venn diagram. Groups were compared using standardized differences and chi square, rank sum, or independent t-tests.
Results Of the 228 patients having sepsis by any criteria, 191 (83%) patients met the criteria for Sepsis-2, 131 (57%) for Sepsis-3, and 62 (27%) met criteria according to CMQCC. Agreement between the three criteria ranged from kappa = 0.13 (95% confidence interval [CI]: 0.09, 0.18) to kappa = 0.31 (95% CI: 0.23, 0.39). Patients who met CMQCC criteria tended to have more comorbidities and higher APACHE II (Acute Physiology And Chronic Health Evaluation) scores. Mortality (by 90 days) among the groups was low with 10 (4%) patients dying. Patients meeting criteria for CMQCC sepsis had higher mortality than the non-CMQCC patients with sepsis (10 vs. 2%, standardized difference = 0.31, p = 0.027).
Conclusion The agreement among Sepsis-2, Sepsis-3, and CMQCC diagnostic criteria is weak. CMQCC criteria identifies patients with sepsis at higher risk of death.
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