bluuebunny/crossref_metadata_2025_split huggingface dataset:
Maintenance of Expanded Polystyrene Building Components in Mount Pleasant Housing Estate, Abuja, Nigeria
Authors: Oloke O. C. , Oluwatobi A. O. , Agboola O. , Adagunodo T. , Adewuyi F. 
Published: September 2022

Abstract
This study assessed user’s satisfaction as well as maintenance related issues associated with expanded polystyrene elements in a residential housing estate in the Federal Capital Territory. Residents of Mount Pleasant Housing Estate, Abuja constituted the study population. Questionnaires were administered to 310 adult residents of the housing estate out of which 267 were retrieved, constituting 86.1% rate of response and used for analysis. Data were analysed with basic descriptive tools of frequency, percentage and mean score derived from 5-Point Likert scale. Results were presented in tables and then discussed. The study established amongst others that expanded polystyrene materials are used for different components of housing units with partition walls, decorative finishes and window hoods having 79.4%, 68.2% and 64.4% of usage respectively. The study found amongst others that respondents generally agree that EPS elements are costlier in terms of maintenance and require special skill to fix. It was further observed that respondents are of the opinion that EPS elements do not breakdown easily or frequently. Concluding, the respondents ranked their satisfaction level with the aesthetics and moisture resistance above other qualities of EPS components. The study therefore recommended further research to discover how EPS materials can be used to build complete housing unit. Furthermore, developers and builders should as a matter of policy embrace the use of EPS while special awareness creation programme is organized to enlighten the general public on the benefits of EPS to housing development in Nigeria.
Experimental and numerical study of contact fatigue for 18CrNiMo7-6 and 20MnCr5 carburized gear tooth
Authors: Palma Calabokis Oriana , Núñez de la Rosa Yamid Enrique , de Moraes Samara Paulin , Antunes Estela Vicentim , Cousseau Tiago , da Silva Carlos Henrique 
Published: September 2022

Abstract
Gear manufacturers must make decisions about the manufacturing materials and superficial treatments. The best performance as to a type of failure should be evaluated. However, it is a time-demanding and costly process. The present work proposes a methodology for a comprehensive assessment (experimental and computational) of contact fatigue of gears in FZG test rig. The materials investigated were 18CrNiMo7-6 and 20MnCr5 alloy steels, widely used in industrial and automotive transmission systems, but with very different raw material costs, which can exceed twice the first compared to the second. The study evaluated the contact analysis between gears from the macroscopic point of view and the microscopic (inclusion of roughness). At the same time, the evolution of roughness and pit-damaged area after each test stage was monitored. The approach determined the stress field after each loading cycle and thus correlating the regions of higher stresses with surface and subsurface fatigue (micropitting and pitting). In addition, Weibull’s statistical analysis and SEM-EDS observations were executed. In many cases, the methodology correlated the increased roughness and pitting affected area with the regions submitted to the higher contact stress. Observations by SEM-EDS revealed that the occurrence of plastic deformation as a mechanism of wear should be considered in the equations of microscopic stress analysis. The similar fatigue life of such different materials may be correlated to the competitive mechanisms of higher mechanical strength of 18CrNiMo7-6 and better crack propagation characteristics of 20MnCr5. The methodology proved to be consistent for fatigue failure analysis of gears in FZG test rig.
Predicting respiratory motion using a novel patient specific dual deep recurrent neural networks
Authors: Yoganathan S A , Paloor Satheesh , Torfeh Tarraf , Aouadi Souha , Hammoud Rabih , Al-Hammadi Noora 
Published: September 2022

Abstract
Real-time tracking of a target volume is a promising solution for reducing the planning margins and both dosimetric and geometric uncertainties in the treatment of thoracic and upper-abdomen cancers. Respiratory motion prediction is an integral part of real-time tracking to compensate for the latency of tracking systems. The purpose of this work was to develop a novel method for accurate respiratory motion prediction using dual deep recurrent neural networks (RNNs). The respiratory motion data of 111 patients were used to train and evaluate the method. For each patient, two models (Network1 and Network2) were trained on 80% of the respiratory wave, and the remaining 20% was used for evaluation. The first network (Network 1) is a ‘coarse resolution’ prediction of future points and second network (Network 2) provides a ‘fine resolution’ prediction to interpolate between the future predictions. The performance of the method was tested using two types of RNN algorithms : Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU). The accuracy of each model was evaluated using the root mean square error (RMSE) and mean absolute error (MAE). Overall, the RNN model with GRU- function had better accuracy than the RNN model with LSTM-function (RMSE (mm): 0.4 ± 0.2 versus 0.6 ± 0.3; MAE (mm): 0.4 ± 0.2 versus 0.6 ± 0.2). The GRU was able to predict the respiratory motion accurately (<1 mm) up to the latency period of 440 ms, and LSTM’s accuracy was acceptable only up to 240 ms. The proposed method using GRU function can be used for respiratory-motion prediction up to a latency period of 440 ms.
Magnetic-field-modulated radiotherapy (MagMRT) in inhomogeneous medium and its potential applications
Authors: Chu Vivien W S , Kan Monica W K , Lee Louis K Y , Wong Kenneth C W , Chan Anthony T C 
Published: September 2022

Abstract

Objective. To study the effects of magnetic field gradients on the dose deposition in an inhomogeneous medium and to present the benefits offered by magnetic-field-modulated radiotherapy (MagMRT) under multiple radiation beams. Approach. Monte Carlo simulations were performed using the Geant4 simulation toolkit with a 7 MV photon beam from an Elekta Unity system. A water cuboid embedded with material slabs of water, bone, lung or air was used to study the effects of MagMRT within inhomogeneous medium. Two cylindrical water phantoms, with and without a toroidal lung insert embedded, were used to study the effects of MagMRT under single, opposing or four cardinal radiation beams. Optimized magnetic field variations in the form of a wavelet were used to induce dose modulation within the material slabs or at the iso-center of the phantoms. Main results. The magnitudes of the dose enhancement and reduction induced by the magnetic field gradients become more prominent in a medium of lower density. A maximum dose increase of 6.5% and a decrease of 4.8% were found inside bone, while an increase of 20.4% and a decrease of 13.9% were found in lung tissue. Under multiple radiation beams, the dose enhancement can be induced at the iso-center while the dose reduction occurs in regions around the tumor. For the case with four cardinal beams irradiating a homogeneous water cylinder, an 8.4% of dose enhancement and a 2.4% of dose reduction were found. When a toroidal lung insert was embedded, a maximum dose enhancement of 9.5% and a reduction of 17.0% were produced for anterior-posterior opposing fields. Significance. With an optimized magnetic field gradient, MagMRT can induce a dose boost to the target while producing a better sparing to the surrounding normal tissue, resulting in a sharper dose fall-off in all directions outside the target volume.
Tailoring mechanical properties of PμSL 3D-printed structures via size effect
Authors: Zhang Wenqiang , Ye Haitao , Feng Xiaobin , Zhou Wenzhao , Cao Ke , Li Maoyuan , Fan Sufeng , Lu Yang 
Published: September 2022

Abstract
Projection micro stereolithography (PμSL) has emerged as a powerful three-dimensional (3D) printing technique for manufacturing polymer structures with micron-scale high resolution at high printing speed, which enables the production of customized 3D microlattices with feature sizes down to several microns. However, the mechanical properties of as-printed polymers were not systemically studied at the relevant length scales, especially when the feature sizes step into micron/sub-micron level, limiting its reliable performance prediction in micro/nanolattice and other metamaterial applications. In this work, we demonstrate that PμSL-printed microfibers could become stronger and significantly more ductile with reduced size ranging from 20 μm to 60 μm, showing an obvious size-dependent mechanical behavior, in which the size decreases to 20 μm with a fracture strain up to ∼100% and fracture strength up to ∼100 MPa. Such size effect enables the tailoring of the material strength and stiffness of PμSL-printed microlattices over a broad range, allowing to fabricate the microlattice metamaterials with desired/tunable mechanical properties for various structural and functional applications.
Within-Person Blood Pressure Variability During Hospitalization and Clinical Outcomes Following First-Ever Acute Ischemic Stroke
Authors: Yousufuddin Mohammed , Murad M H , Peters Jessica L , Ambriz Taylor J , Blocker Katherine R , Khandelwal Kanika , Pagali Sandeep R , Nanda Sanjeev , Abdalrhim Ahmed , Patel Urvish , Dugani Sagar , Arumaithurai Kogulavadanan , Takahashi Paul Y , Kashani Kianoush B 
Published: September 2022

Abstract

BACKGROUND
Uncertainty remains over the relationship between blood pressure (BP) variability (BPV), measured in hospital settings, and clinical outcomes following acute ischemic stroke (AIS). We examined the association between within-person systolic blood pressure (SBP) variability (SBPV) during hospitalization and readmission-free survival, all-cause readmission, or all-cause mortality 1 year after AIS.

METHODS
In a cohort of 862 consecutive patients (age [mean ± SD] 75 ± 15 years, 55% women) with AIS (2005–2018, follow-up through 2019), we measured SBPV as quartiles of standard deviations (SD) and coefficient of variation (CV) from a median of 16 SBP readings obtained throughout hospitalization.

RESULTS
In the cumulative cohort, the measured SD and CV of SBP in mmHg were 16 ± 6 and 10 ± 5, respectively. The hazard ratios (HR) for readmission-free survival between the highest vs. lowest quartiles were 1.44 (95% confidence interval [CI] 1.04–1.81) for SD and 1.29 (95% CI 0.94–1.78) for CV after adjustment for demographics and comorbidities. Similarly, incident readmission or mortality remained consistent between the highest vs. lowest quartiles of SD and CV (readmission: HR 1.29 [95% CI 0.90–1.78] for SD, HR 1.29 [95% CI 0.94–1.78] for CV; mortality: HR 1.15 [95% CI 0.71–1.87] for SD, HR 0.86 [95% CI 0.55–1.36] for CV).

CONCULSIONS
In patients with first AIS, SBPV measured as quartiles of SD or CV based on multiple readings throughout hospitalization has no independent prognostic implications for the readmission-free survival, readmission, or mortality. This underscores the importance of overall patient care rather than a specific focus on BP parameters during hospitalization for AIS.
The mere presence of cuckoos in breeding area alters egg-ejection decisions in Daurian redstarts
Authors: Zhang Jinggang , Santema Peter , Li Jianqiang , Feeney William E , Deng Wenhong , Kempenaers Bart 
Published: September 2022

AbstractBrood parasitic cuckoos and their hosts serve as model systems for studying host–parasite coevolution. Egg-rejection behavior constitutes an effective defense against brood parasitism, but some host species show phenotypic plasticity in egg-rejection behavior. Direct exposure to a cuckoo near the nest can increase egg-rejection likelihood, and long-term studies have shown that increased the egg-rejection rates generally correlate with higher parasite prevalence. However, it remains unclear whether such increases result from interactions between parasites and hosts, as these can be surprisingly common, or whether the mere presence of cuckoos in the breeding area is sufficient. Daurian redstarts Phoenicurus auroreus are a common host of the common cuckoo Cuculus canorus that defend against cuckoo parasitism mainly by ejecting the parasitic egg from the nest. This species is unique, as its first breeding attempt of the year takes place before the arrival of cuckoos, excluding the possibility for direct interactions. We simulated the ambient presence of cuckoos or hoopoes Upupa epops (control) in sub-populations of redstarts during their first egg-laying period by presenting taxidermic models and playing back vocalizations. Redstarts in cuckoo-treated plots showed significantly higher egg-ejection rates than individuals in control plots, even though females in both groups were equally likely to recognize the parasitic egg. Among females that did recognize the parasitic egg, those exposed to the cuckoo treatment were more likely to eject it than those exposed to the control treatment. Our results demonstrate unequivocally that the mere presence of cuckoos in the environment is sufficient to provoke egg-ejection behavior.
Predicting colorectal cancer tumor mutational burden from histopathological images and clinical information using multi-modal deep learning
Authors: Huang Kaimei , Lin Binghu , Liu Jinyang , Liu Yankun , Li Jingwu , Tian Geng , Yang Jialiang 
Published: September 2022

Abstract

Motivation
Tumor mutational burden (TMB) is an indicator of the efficacy and prognosis of immune checkpoint therapy in colorectal cancer (CRC). In general, patients with higher TMB values are more likely to benefit from immunotherapy. Though whole-exome sequencing is considered the gold standard for determining TMB, it is difficult to be applied in clinical practice due to its high cost. There are also a few DNA panel-based methods to estimate TMB; however, their detection cost is also high, and the associated wet-lab experiments usually take days, which emphasize the need for faster and cheaper alternatives.

Results
In this study, we propose a multi-modal deep learning model based on a residual network (ResNet) and multi-modal compact bilinear pooling to predict TMB status (i.e. TMB high (TMB_H) or TMB low(TMB_L)) directly from histopathological images and clinical data. We applied the model to CRC data from The Cancer Genome Atlas and compared it with four other popular methods, namely, ResNet18, ResNet50, VGG19 and AlexNet. We tested different TMB thresholds, namely, percentiles of 10%, 14.3%, 15%, 16.3%, 20%, 30% and 50%, to differentiate TMB_H and TMB_L.
For the percentile of 14.3% (i.e. TMB value 20) and ResNet18, our model achieved an area under the receiver operating characteristic curve of 0.817 after 5-fold cross-validation, which was better than that of other compared models. In addition, we also found that TMB values were significantly associated with the tumor stage and N and M stages. Our study shows that deep learning models can predict TMB status from histopathological images and clinical information only, which is worth clinical application.
Resisting Dogmatism in Social Work Knowledge Generation: Theorising, Social Justice and Implications for Social Work Doctoral Education
Authors: Lee Eunjung 
Published: September 2022

AbstractSocial work doctoral education is charged with the task of generating and critically evaluating knowledge to inform and transform professional practice. To promote the foundational values of social justice and diversity in social work, scholars highlight the importance of multiple ways of knowing and multiple ontological perspectives in social work knowledge generation. Yet, critical scholars have raised concerns about a reviving dogmatism in the philosophical and theoretical orientations (e.g. positivism and empiricism) of social work knowledge. Recent studies also show a significant gap between research and social justice in the social work doctoral curriculum. Critically reflecting and problematising this ‘social’ phenomenon, I argue that it is essential to engage in ongoing theorising to resist dominant discourses, represent marginalised voices in social work knowledge and furthermore, to teach students how to theorise in doctoral education. Drawing from Foucauldian theories on knowledge and power, this article first contextualises the dangers of dogmatism in knowledge generation in social work. Then, I provide a brief review of the historical development of theorising, introducing Richard Swedberg’s work on the topic, particularly his four steps in the ‘process of theorising’. How this noble sociological ‘theory of theorising’ can be incorporated into social work is discussed.
N-acetylcysteine treatment mitigates loss of cortical parvalbumin-positive interneuron and perineuronal net integrity resulting from persistent oxidative stress in a rat TBI model
Authors: Hameed Mustafa Q , Hodgson Nathaniel , Lee Henry H C , Pascual-Leone Andres , MacMullin Paul C , Jannati Ali , Dhamne Sameer C , Hensch Takao K , Rotenberg Alexander 
Published: September 2022

AbstractTraumatic brain injury (TBI) increases cerebral reactive oxygen species production, which leads to continuing secondary neuronal injury after the initial insult. Cortical parvalbumin-positive interneurons (PVIs; neurons responsible for maintaining cortical inhibitory tone) are particularly vulnerable to oxidative stress and are thus disproportionately affected by TBI. Systemic N-acetylcysteine (NAC) treatment may restore cerebral glutathione equilibrium, thus preventing post-traumatic cortical PVI loss. We therefore tested whether weeks-long post-traumatic NAC treatment mitigates cortical oxidative stress, and whether such treatment preserves PVI counts and related markers of PVI integrity and prevents pathologic electroencephalographic (EEG) changes, 3 and 6 weeks after fluid percussion injury in rats. We find that moderate TBI results in persistent oxidative stress for at least 6 weeks after injury and leads to the loss of PVIs and the perineuronal net (PNN) that surrounds them as well as of per-cell parvalbumin expression. Prolonged post-TBI NAC treatment normalizes the cortical redox state, mitigates PVI and PNN loss, and - in surviving PVIs - increases per-cell parvalbumin expression. NAC treatment also preserves normal spectral EEG measures after TBI. We cautiously conclude that weeks-long NAC treatment after TBI may be a practical and well-tolerated treatment strategy to preserve cortical inhibitory tone post-TBI.
Precision fMRI reveals that the language-selective network supports both phrase-structure building and lexical access during language production
Authors: Hu Jennifer , Small Hannah , Kean Hope , Takahashi Atsushi , Zekelman Leo , Kleinman Daniel , Ryan Elizabeth , Nieto-Castañón Alfonso , Ferreira Victor , Fedorenko Evelina 
Published: September 2022

AbstractA fronto-temporal brain network has long been implicated in language comprehension. However, this network’s role in language production remains debated. In particular, it remains unclear whether all or only some language regions contribute to production, and which aspects of production these regions support. Across 3 functional magnetic resonance imaging experiments that rely on robust individual-subject analyses, we characterize the language network’s response to high-level production demands. We report 3 novel results. First, sentence production, spoken or typed, elicits a strong response throughout the language network. Second, the language network responds to both phrase-structure building and lexical access demands, although the response to phrase-structure building is stronger and more spatially extensive, present in every language region. Finally, contra some proposals, we find no evidence of brain regions—within or outside the language network—that selectively support phrase-structure building in production relative to comprehension. Instead, all language regions respond more strongly during production than comprehension, suggesting that production incurs a greater cost for the language network. Together, these results align with the idea that language comprehension and production draw on the same knowledge representations, which are stored in a distributed manner within the language-selective network and are used to both interpret and generate linguistic utterances.
Predictive coding across the left fronto-temporal hierarchy during language comprehension
Authors: Wang Lin , Schoot Lotte , Brothers Trevor , Alexander Edward , Warnke Lena , Kim Minjae , Khan Sheraz , Hämäläinen Matti , Kuperberg Gina R 
Published: September 2022

AbstractWe used magnetoencephalography (MEG) and event-related potentials (ERPs) to track the time-course and localization of evoked activity produced by expected, unexpected plausible, and implausible words during incremental language comprehension. We suggest that the full pattern of results can be explained within a hierarchical predictive coding framework in which increased evoked activity reflects the activation of residual information that was not already represented at a given level of the fronto-temporal hierarchy (“error” activity). Between 300 and 500 ms, the three conditions produced progressively larger responses within left temporal cortex (lexico-semantic prediction error), whereas implausible inputs produced a selectively enhanced response within inferior frontal cortex (prediction error at the level of the event model). Between 600 and 1,000 ms, unexpected plausible words activated left inferior frontal and middle temporal cortices (feedback activity that produced top-down error), whereas highly implausible inputs activated left inferior frontal cortex, posterior fusiform (unsuppressed orthographic prediction error/reprocessing), and medial temporal cortex (possibly supporting new learning). Therefore, predictive coding may provide a unifying theory that links language comprehension to other domains of cognition.
A middle ground where executive control meets semantics: the neural substrates of semantic control are topographically sandwiched between the multiple-demand and default-mode systems
Authors: Chiou Rocco , Jefferies Elizabeth , Duncan John , Humphreys Gina F , Lambon Ralph Matthew A 
Published: September 2022

AbstractSemantic control is the capability to operate on meaningful representations, selectively focusing on certain aspects of meaning while purposefully ignoring other aspects based on one’s behavioral aim. This ability is especially vital for comprehending figurative/ambiguous language. It remains unclear why and how regions involved in semantic control seem reliably juxtaposed alongside other functionally specialized regions in the association cortex, prompting speculation about the relationship between topography and function. We investigated this issue by characterizing how semantic control regions topographically relate to the default-mode network (associated with memory and abstract cognition) and multiple-demand network (associated with executive control). Topographically, we established that semantic control areas were sandwiched by the default-mode and multi-demand networks, forming an orderly arrangement observed both at the individual and group level. Functionally, semantic control regions exhibited “hybrid” responses, fusing generic preferences for cognitively demanding operation (multiple-demand) and for meaningful representations (default-mode) into a domain-specific preference for difficult operation on meaningful representations. When projected onto the principal gradient of human connectome, the neural activity of semantic control showed a robustly dissociable trajectory from visuospatial control, implying different roles in the functional transition from sensation to cognition. We discuss why the hybrid functional profile of semantic control regions might result from their intermediate topographical positions on the cortex.