bluuebunny/crossref_metadata_2025_split huggingface dataset:
Visual attentional guidance during smooth pursuit eye movements: Distractor interference is independent of distractor‐target similarity
Authors: Stolte Moritz , Kraus Leon , Ansorge Ulrich 
Published: July 2023

AbstractIn the current study, we used abrupt‐onset distractors similar and dissimilar in luminance to the target of a smooth pursuit eye‐movement to test if abrupt‐onset distractors capture attention in a top‐down or bottom‐up fashion while the eyes track a moving object. Abrupt onset distractors were presented at different positions relative to the current position of a pursuit target during the closed‐loop phase of smooth pursuit. Across experiments, we varied the duration of the distractors, their motion direction, and task‐relevance. We found that abrupt‐onset distractors decreased the gain of horizontally directed smooth‐pursuit eye‐movements. This effect, however, was independent of the similarity in luminance between distractor and target. In addition, distracting effects on horizontal gain were the same, regardless of the exact duration and position of the distractors, suggesting that capture was relatively unspecific and short‐lived (Experiments 1 and 2). This was different with distractors moving in a vertical direction, perpendicular to the horizontally moving target. In line with past findings, these distractors caused suppression of vertical gain (Experiment 3). Finally, making distractors task‐relevant by asking observers to report distractor positions increased the pursuit gain effect of the distractors. This effect was also independent of target‐distractor similarity (Experiment 4). In conclusion, the results suggest that a strong location signal exerted by the pursuit targets led to very brief and largely location‐unspecific interference through the abrupt onsets and that this interference was bottom‐up, implying that the control of smooth pursuit was independent of other target features besides its motion signal.
Once NEET, always NEET? A synthetic panel approach to analyze the Moroccan labor market
Authors: Alfani Federica , Clementi Fabio , Fabiani Michele , Molini Vasco , Valentini Enzo 
Published: July 2023

AbstractIn many regions of the world, the persistent, and growing, proportion of young people who are currently Not in Employment, Education or Training—a group increasingly referred to as NEET—is of global concern. This is no less true of Morocco: about 30% of the Moroccan population between age 15 and 24 are currently NEET. Drawing from various rounds of Moroccan Labor Force Surveys, this paper contributes to understanding the complex dynamics of labor markets in developing countries. First, it identifies the socioeconomic determinants of Morocco's NEETs. Second, employing a synthetic panel (SP) methodology in the context of labor market analysis, the paper describes how the condition of NEETs changes over time. One striking, and worrisome, pattern that emerges from the 2010 SP data is that, even after 8 years, a majority of the NEETs remained outside either the labor market or education, with very little chance of moving out of their situation. Their chronic stagnancy confirms the powerful effect that initial conditions have on determining young people's future outcomes. It also highlights the absence of corrective mechanisms and policy interventions within the Moroccan political economy landscape that could help to change NEETs' outcomes along the line.
Phase I evaluation of CycloSam® (Sm‐153‐DOTMP) bone seeking radiopharmaceutical in dogs with spontaneous appendicular osteosarcoma
Authors: Selting Kim A. , Simon Jaime , Lattimer Jim C. , Ketring Alan , Axiak‐Bechtel Sandra , Frank Keith , Wendt Richard E. , Bryan Jeffrey N. , Tate Deborah , Maitz Charles , Lunceford Joni , Donnelly Lindsay , Keegan Kevin , Henry Carolyn J. 
Published: July 2023

Abstract153Sm‐DOTMP (CycloSam®) is a newly‐patented radiopharmaceutical for bone tumor treatment. DOTMP (1,4,7,10‐tetraazacyclododecane‐1,4,7,10‐tetramethylene‐phosphonate) is a macrocyclic chelating agent with superior binding properties to 153Sm when compared with EDTMP (Quadramet™, used for palliative treatment of bone cancer). CycloSam® was administered at 1 mCi/kg (37 MBq/kg) in a prospective pilot study to seven dogs with bone cancer resulting in no myelosuppression. Then, 13 dogs were enrolled in a prospective clinical trial study using traditional 3+3 dose escalation and starting at 1.5 mCi/kg. Baseline evaluation included hematologic and biochemical testing, diagnosis confirmation, thoracic and limb radiographs, technetium‐99 m‐HDP bone scintigraphy, and 18F‐FDG PET scan (SUVmax). Toxicity (primary endpoint) was assessed through weekly blood counts and adverse events. Dogs received 1.5 mCi/kg (n = 4), 1.75 mCi/kg (n = 6), and 2 mCi/kg (n = 3) of 153Sm‐DOTMP. Dose‐limiting neutropenia and thrombocytopenia were seen at 2 mCi/kg. No dose‐limiting nonhematologic toxicities occurred. Efficacy (secondary endpoint) was assessed by objective lameness measurement (body‐mounted inertial sensors), owner quality‐of‐life (QoL) questionnaire, and repeat PET scan. Objective lameness measurement improved in four dogs (53%–60% decrease) was equivocal in three dogs, and worsened in four dogs (66%–115% increase); two dogs were not evaluable. Repeat 18F‐FDG PET scan results varied and change in lameness did not consistently correlate with SUVmax changes. QoL score worsened (n = 5) or was improved/stable (n = 7). Carboplatin chemotherapy (300 mg/m2 IV every 3 weeks ×4) started 4 weeks after 153Sm‐DOTMP injection. No dog died of chemotherapy‐related complications. All dogs completed study monitoring. The recommended dose for CycloSam® in dogs is 1.75 mCi/kg, which resulted in some pain control with minimal toxicity and was safely combined with chemotherapy.
Enterprise Architecture for Equipment Performance Analysis Based on Internet of Things (IoT) Technology in the Semiconductor Manufacturing Industry
Authors: Tengku Putri Nurain  , Hasan Al-Kubati Marwan Abdullah , Abu Bakar Nur Azaliah 
Published: July 2023

This study proposes a concept for establishing an Enterprise Architecture in the semiconductor manufacturing industry for equipment performance analysis using Internet of Things (IoT) technology. The plan is to implement The Open Group Framework approach as Enterprise Architecture in the manufacturing analytics department. The TOGAF approach improves data governance in the business process and analytics department. Manufacturing focuses on providing excellent and high-quality products to customers. As a result, the manufacturer must use a data analytics application to monitor the performance of the equipment. The performance of the equipment is monitored around the clock to ensure that it meets the requirements and does not exceed the threshold. The business process, data from the warehouse, and how it is processed will be discussed. Implementing Enterprise Architecture in manufacturing will also be discussed, focusing on the three layers of the TOGAF Architecture Development Method (ADM). The three layers are business, technology, and application. The Enterprise Architecture framework is a blueprint for the architecture used to align the business and information technology. Enterprise architecture optimises business processes and structures processes and functions to integrate information technology into the business. The proposed Enterprise Architecture for equipment performance analysis in the semiconductor manufacturing industry can be used as a guideline for implementing a comprehensive framework for tool performance monitoring.
Counter-Narrative Cyber Security Model to Address the Issues of Cyber Terrorism
Authors: Ahmad Tamerin Ahmad Syafiq , Bakar Nur Azaliah Abu , Hassan Noor Hafizah , Maarop Nurazean 
Published: July 2023

Terrorism is the imminent threat that Malaysia and the entire world are facing nowadays. This has become a severe threat to Malaysia’s national security as extremist groups such as ISIS and DAESH are leveraging cyberspace to gain more supporters and sympathisers. These extremists used social media to disseminate their narratives among the Malaysian Armed Force (MAF) personnel to recruit them for their excellent military skills. Nevertheless, the current MAF counter-narrative is still using traditional media operations like roadshows, brochures dissemination, articles, and short videos in combating the terrorism agenda, which are less effective and time-consuming. Therefore, this study proposes an enhanced counter-terrorism approach to fight this terrorism narrative by utilising the MAF IT infrastructure to focus on the social media platform. The model was built based on ISO / IEC 27032:2012 standard, concerning three cyber-terrorism models. Six military IT experts then verified this new enhanced model. They agreed that it is crucial to establish such a model and emphasise that counter-terrorism effort needs full cooperation with other services and collegiality. This study’s final output is the Counter-Narrative Information Technology Model, which will later potentially be adopted to the MAF environment in line with the national inspiration in fighting terrorism.
The Role of Deep Learning in Manufacturing Applications: Challenges and Opportunities
Authors: Malhan Rishi , Gupta Satyandra K. 
Published: July 2023

Abstract
There is a growing interest in using deep learning technologies within the manufacturing industry to improve quality, productivity, safety, and efficiency, while also reducing costs and cycle time. This position paper discusses the applications of deep learning currently being employed in manufacturing, including identifying defects, optimizing processes, streamlining the supply chain, predicting maintenance needs, and recognizing human activity. This paper aims to provide a description of the challenges and opportunities in this area to beginning researchers. The paper offers a brief summary of the various components of deep learning technology and their roles. Additionally, the paper draws attention to the current challenges and limitations that need to be addressed to fully realize the potential of deep learning technology in manufacturing. Lastly, several future directions for research within the field are proposed to further improve the use of deep learning in manufacturing.
Uncertainty Reduction in Fatigue Life Validation Testing for Drilling Tools with a Universal Runout Compensator
Authors: Du Michael , Song Fei , Li Ke 
Published: July 2023

Abstract
Rotating bending fatigue (RBF) life is a critical performance index for oil drilling equipment. It can be measured via cantilever-type RBF testing, with a sideload applied on the specimen to generate the required bending moment at the point of interest. Multiple factors cause runout or eccentricity of the test specimen at the sideload point, leading to deviations in the effective sideload acting on the specimen and, consequently, deviations in the bending moment at the point of interest. Runout generates greater uncertainty in fatigue life test results.
A Universal Runout Compensator (URC) was developed to reduce this uncertainty by mitigating the test specimen runout. It consists of two eccentric bushings, one assembled inside the other. Depending on the relative orientation of the two bushings, the total eccentricity of the URC can be adjusted. With the properly set URC installed on the specimen, the final runout at the URC where the sideload is applied becomes negligible.
Finite element analysis (FEA) was used to confirm the URC structural integrity. Full-scale RBF tests were conducted to validate the URC design and FEA studies. With the URC used in the tests, bending moment variation decreased by up to 15%, reducing life cycle uncertainty by up to 44%.
Training and Interpretability of Deep-Neural Methods for Damage Calibration in Copper.
Authors: Hickmann Kyle , Callis Skylar , Andrews Stephen 
Published: July 2023

Abstract
We present an application of convolutional neural networks for calibration of a tensile plasticity (TePla) damage model simulating the spallation in copper under high-explosive shock loading. Using a high-fidelity, multi-physics simulation developed by the Advanced Simulation and Computing program at Los Alamos National Laboratory (LANL), we simulate hundreds of variations of a high-explosive shock experiment involving a copper coupon. From this synthetic data, we train neural networks to learn the inverse mapping between the coupon’s late-time density field, or an associated synthetic radiograph, and the simulation’s TePla damage parameters. It is demonstrated that, using a simple convolutional architecture, we can train networks to infer damage parameters from density fields accurately. Neural network inference directly from synthetic radiographs is significantly more challenging. Application of machine-learning methods must be accompanied by an analysis of how they are making inferences in order to build confidence in predictions and to identify likely shortcomings of the technique. To understand what the model is learning, individual layer outputs are extracted and examined. Each layer in the network identifies multiple features. However, each of these features are not necessarily of equal importance in the network’s final prediction of a given damage parameter. By examining the features overlaid on the input hydrodynamic fields, we assess the question of whether or not the model’s accuracy can be attributed to human-recognizable characteristics. In this work we give a detailed description of our data-generation methods and the learning problem we address. We then outline our neural architecture trained for damage calibration and discuss considerations made during training and evaluation of accuracy. Methods for human interpretation of the network’s inference process are then put forward, including extraction of learned features from the trained network and techniques to assess sensitivity of inferences to the learned features.
Acute and Long-Term Changes in Blood-Borne Biomarkers in Response to Dynamic Standing in Nonambulant Children With Cerebral Palsy
Authors: Varga Tibor V. , Andersson Åsa , Lauruschkus Katarina , Tornberg Åsa B. 
Published: July 2023

Purpose: To investigate acute and long-term changes in hormonal and inflammatory biomarkers in nonambulant children with cerebral palsy in response to dynamic standing exercise. Methods: Fourteen children with severe cerebral palsy were recruited. Anthropometrics and body composition measures were obtained. Physical activity levels before the study were assessed using hip-worn accelerometry. All children underwent a 30-minute dynamic standing exercise using the Innowalk standing aid. Respiratory data during exercise were collected using indirect calorimetry. Blood samples were collected before and after exercise. Blood samples were also obtained after two 16-week exercise protocols, in a resting state. Hormonal and inflammatory metabolites were measured from blood serum/plasma, and acute and long-term changes in biomarker levels were assessed using Wilcoxon signed-rank tests. Results: Of the 14 children at baseline, all had slightly/moderately/severely elevated C-reactive protein and cortisol levels. C-reactive protein levels were decreased following a 30-minute bout of dynamic standing (before exercise: 53 mg/L [interquartile range: 40–201]; after exercise: 39 mg/L [interquartile range: 20–107]; P = .04). Conclusions: We show that several hormonal and inflammatory biomarkers are dysregulated in children with cerebral palsy. Our preliminary results from a small, but deep-phenotyped prospective cohort indicate acute and long-term alterations of several biomarkers in response to exercise.
Single-strain behavior predicts responses to environmental pH and osmolality in the gut microbiota
Authors: Ng Katharine M. , Pannu Sagar , Liu Sijie , Burckhardt Juan C. , Hughes Thad , Van Treuren Will , Nguyen Jen , Naqvi Kisa , Nguyen Bachviet , Clayton Charlotte A. , Pepin Deanna M. , Collins Samuel R. , Tropini Carolina 
Published: July 2023

ABSTRACT

Changes to gut environmental factors such as pH and osmolality due to disease or drugs correlate with major shifts in microbiome composition; however, we currently cannot predict which species can tolerate such changes or how the community will be affected. Here, we assessed the growth of 92 representative human gut bacterial strains spanning 28 families across multiple pH values and osmolalities
in vitro
. The ability to grow in extreme pH or osmolality conditions correlated with the availability of known stress response genes in many cases, but not all, indicating that novel pathways may participate in protecting against acid or osmotic stresses. Machine learning analysis uncovered genes or subsystems that are predictive of differential tolerance in either acid or osmotic stress. For osmotic stress, we corroborated the increased abundance of these genes
in vivo
during osmotic perturbation. The growth of specific taxa in limiting conditions in isolation
in vitro
correlated with survival in complex communities
in vitro
and in an
in vivo
mouse model of diet-induced intestinal acidification. Our data show that
in vitro
stress tolerance results are generalizable and that physical parameters may supersede interspecies interactions in determining the relative abundance of community members. This study provides insight into the ability of the microbiota to respond to common perturbations that may be encountered in the gut and provides a list of genes that correlate with increased ability to survive in these conditions.

IMPORTANCE
To achieve greater predictability in microbiota studies, it is crucial to consider physical environmental factors such as pH and particle concentration, as they play a pivotal role in influencing bacterial function and survival. For example, pH is significantly altered in various diseases, including cancers, inflammatory bowel disease, as well in the case of over-the-counter drug use. Additionally, conditions like malabsorption can affect particle concentration. In our study, we investigate how changes in environmental pH and osmolality can serve as predictive indicators of bacterial growth and abundance. Our research provides a comprehensive resource for anticipating shifts in microbial composition and gene abundance during complex perturbations. Moreover, our findings underscore the significance of the physical environment as a major driver of bacterial composition. Finally, this work emphasizes the necessity of incorporating physical measurements into animal and clinical studies to better understand the factors influencing shifts in microbiota abundance.
Mrs4 loss of function in fungi during adaptation to the cystic fibrosis lung
Authors: Murante Daniel , Demers Elora G. , Kurbessoian Tania , Ruzic Marina , Ashare Alix , Stajich Jason E. , Hogan Deborah A. 
Published: July 2023

ABSTRACT

The genetic disease cystic fibrosis (CF) frequently leads to chronic lung infections by bacteria and fungi. We identified three individuals with CF with persistent lung infections dominated by
Clavispora
(
Candida
)
lusitaniae
. Whole-genome sequencing analysis of multiple isolates from each infection found evidence for selection for mutants in the gene
MRS4
in all three distinct lung-associated populations. In each population, we found one or two unfixed, non-synonymous mutations in
MRS4
relative to the reference allele found in multiple environmental and clinical isolates including the type strain. Genetic and phenotypic analyses found that all evolved alleles led to loss of function (LOF) of Mrs4, a mitochondrial iron transporter. RNA-seq analyses found that Mrs4 variants with decreased activity led to increased expression of genes involved in iron acquisition mechanisms in both low iron and replete iron conditions. Furthermore, surface iron reductase activity and intracellular iron were much higher in strains with Mrs4 LOF variants. Parallel studies found that a subpopulation of a CF-associated
Exophiala dermatitidis
infection also had a non-synonymous LOF mutation in
MRS4
. Together, these data suggest that
MRS4
mutations may be beneficial during chronic CF lung infections in diverse fungi, perhaps, for the purposes of adaptation to an iron-restricted environment with chronic infections.

IMPORTANCE

The identification of
MRS4
mutations in
Clavispora
(
Candida
)
lusitaniae
and
Exophiala dermatitidis
in individuals with cystic fibrosis (CF) highlights a possible adaptive mechanism for fungi during chronic CF lung infections. The findings of this study suggest that loss of function of the mitochondrial iron transporter Mrs4 can lead to increased activity of iron acquisition mechanisms, which may be advantageous for fungi in iron-restricted environments during chronic infections. This study provides valuable information for researchers working toward a better understanding of the pathogenesis of chronic lung infections and more effective therapies to treat them.
Relation between duration of dual antiplatelet therapy and risk of ischemic stroke after stent-assisted treatment of cerebral aneurysm (DAPTS ACE-registry)
Authors: Ozaki Tomohiko , Yamagami Hiroshi , Morimoto Masafumi , Imamura Hirotoshi , Hatano Taketo , Oishi Hidenori , Haraguchi Koichi , Yoshimura Shinichi , Satow Tetsu , Sugiu Kenji , Iihara Koji , Matsumaru Yuji , Hayakawa Mikito , Matsumoto Yasushi , Sakai Chiaki , Miyamoto Susumu , Kitagawa Kazuo , Kagimura Tatsuo , Sakai Nobuyuki 
Published: July 2023

BackgroundThe optimal duration of dual antiplatelet therapy (DAPT) in patients with cerebral aneurysm who undergo stent-assisted coil embolization (SACE) has not been established. We aimed to clarify the association between duration of DAPT and incidence of ischemic stroke in patients with cerebral aneurysm.MethodsWe registered patients with cerebral aneurysm who underwent SACE in 27 hospitals in Japan. Those treated with DAPT (aspirin and clopidogrel) were eligible for inclusion in a previously reported randomized control trial (RCT). Patients who were ineligible or refused to participate to the RCT were followed-up for 15 months after SACE as the non-RCT cohort. Our study examined both the RCT and non-RCT cohorts. The primary and secondary outcomes were ischemic stroke and hemorrhagic events.ResultsAmong the 313 patients registered, 296 were included for analysis (of these, 136 were RCT patients and 160 were non-RCT patients). Patients who were treated with DAPT for more than 6 months (n=191) were classified as the long-term DAPT group. Those treated less than 6 months (n=105) were classified as the short-term group. The incidence of ischemic stroke did not significantly differ between the long-term group (2.5 per 100 person-years) and the short-term group (3.2 per 100 person-years); nor did incidence of hemorrhagic events (0.8 and 3.2 per 100 person-years, respectively). The period of DAPT was not significantly associated with incidence rates of ischemic stroke or hemorrhagic events.ConclusionsDuration of DAPT was not associated with the incidence of ischemic stroke in the first 15 months after SACE.