bluuebunny/crossref_metadata_2025 huggingface dataset:
Environmental hazard assessment of metals in marine sediments of Sabah and Sarawak, Malaysia
Authors: Ahmed Amel. Y. , Abdullah Md Pauzi , Siddeeg Saifeldin M.
Published: September 2022

The fractionation of 10 metals (As, Co, Cr, Cu, Mn, Ni, Pb, Se, V, and Zn) within labile fractions in shallow marine sediments collected from the coasts of Sabah and Sarawak, Malaysia, was evaluated. Spatial distribution revealed that coastal sediments from Sabah were approximately 10% higher in metal content than sediments from Sarawak. Risk assessment code, enrichment factor, and pollution accumulation index calculations were used to investigate the environmental hazards of elements. For the risk assessment code, the modified Tessier sequential extraction procedure was applied. The risk assessment code values showed that metal V recorded the lowest environment risk (~ 10%) while As, Co, Cr, Cu, Mn, and Zn exhibited medium risk (Risk assessment code range of 11%–30%). The element Ni displayed no risk (0.67%) to the environment, whereas Se and Pb recorded the highest risk with values of 47% and 52%, respectively. For the enrichment factor calculation, the continental crust data presented by Taylor (Taylor, Geochim Cosmochim Acta 28:1273–1285, 1964) were used as background, with metal Al used as a reference element. Results illustrated that most of the metals show enrichment (enrichment factor > 1). However, Se was considered extremely severe to the environment (enrichment factor > 50). While the pollution accumulation index calculation demonstrated that all metals under study can be considered as non-contaminant elements except for Ni, V, and Co. These findings indicated that marine sediments in Sabah are more polluted with metal contaminants than the sediments in Sarawak, despite both states having numerous active oil- and gas-related production facilities.
Application of physics-informed neural network in the analysis of hydrodynamic lubrication
Authors: Zhao Yang , Guo Liang , Wong Patrick Pat Lam
Published: September 2022

The last decade has witnessed a surge of interest in artificial neural network in many different areas of scientific research. Despite the rapid expansion in the application of neural networks, few efforts have been carried out to introduce such a powerful tool into lubrication studies. Thus, this work aims to apply the physics-informed neural network (PINN) to the hydrodynamic lubrication analysis. The 2D Reynolds equation is solved. The PINN is a meshless method and does not require big data for network training compared with classical methods. Our results are consistent with those obtained by experiments and the finite element method. Hence, we envision that the PINN method will have great application potential in lubrication and bearing research.
Stitching Womanhood in theZongo: Seamstress Apprenticeship in Accra
Authors: Cassiman Ann
Published: September 2022

Focusing upon the daily lives of young female Muslim apprentices in the sewing shops of Accra’szongocommunities, Cassiman argues that the sewing workshop may be understood as a playground in which young women may experiment with the normative chronologies shaping women’s lives, and with ideals of female respectability, self-making, and autonomy. Opening up the possibility to subvert the chrononormativity of apprenticeship and marriage, young seamstress apprentices carve out a platform from which they can exert specific forms of agency, by suspending marriage or hastening it, while trying out various possible futures.
A categorical approach to dynamical quantum groups
Authors: Kalmykov Artem , Safronov Pavel
Published: September 2022

We present a categorical point of view on dynamical quantum groups in terms of categories of Harish-Chandra bimodules. We prove Tannaka duality theorems for forgetful functors into the monoidal category of Harish-Chandra bimodules in terms of a slight modification of the notion of a bialgebroid. Moreover, we show that the standard dynamical quantum groups

$F(G)$

and

$F_q(G)$

are related to parabolic restriction functors for classical and quantum Harish-Chandra bimodules. Finally, we exhibit a natural Weyl symmetry of the parabolic restriction functor using Zhelobenko operators and show that it gives rise to the action of the dynamical Weyl group.
Energy transfer mechanisms in adverse pressure gradient turbulent boundary layers: production and inter-component redistribution
Authors: Gungor Taygun R. , Maciel Yvan , Gungor Ayse G.
Published: September 2022

Production and inter-component redistribution of turbulence in adverse pressure gradient (APG) turbulent boundary layers (TBLs) with small and large velocity defects are investigated, along with the structures playing a role in these energy transfer mechanisms. We examine the wall-normal and spectral distributions of energy, production and pressure-strain in APG TBLs, and compare these distributions with those in canonical flows. It is found that the spectral distributions of production and pressure-strain are not affected profoundly by an increase of the velocity defect, although the energy spectra change drastically in the inner layer of the large-defect APG TBL. In the latter, the signature of the inner-layer streaks is absent from the energy spectra. In the outer layer, energetic, production and pressure-strain structures appear to change from wall-attached to wall-detached structures with increasing velocity defect. Despite this, the two-dimensional spectral distributions have similar shapes and wavelength aspect ratios of the peaks in all these flows. Therefore, the conclusion is that the mechanisms responsible for turbulence production and inter-component energy transfer may remain the same within each layer in all these flows. It is the intensity of these mechanisms within one layer that changes with velocity defect, because of the local mean shear variation.
Fast mixing of a randomized shift-register Markov chain
Authors: Levin David A. , Tankala Chandan
Published: September 2022

We present a Markov chain on the n-dimensional hypercube
$\{0,1\}^n$
which satisfies
$t_{{\rm mix}}^{(n)}(\varepsilon) = n[1 + o(1)]$
. This Markov chain alternates between random and deterministic moves, and we prove that the chain has a cutoff with a window of size at most
$O(n^{0.5+\delta})$
, where
$\delta>0$
. The deterministic moves correspond to a linear shift register.
Effects of parasitic freshwater mussels on their host fishes: a review
Authors: Rock Sebastian L. , Watz Johan , Nilsson P. Anders , Österling Martin
Published: September 2022

Freshwater mussels in the order Unionida are highly adapted to parasitize fish for the primary purpose of dispersal. The parasitic larval stage affixes itself to the gills or fins of the host where it becomes encysted in the tissue, eventually excysting to develop into a free-living adult. Research on the parasitic interactions between unionids and their host fishes has garnered attention recently due to the increase in worldwide preservation efforts surrounding this highly endangered and ecologically significant order. With the exception of heavy infestation events, these mussels cause minor effects to their hosts, typically only observable effect in combination with other stressors. Moreover, the range of effect intensities on the host varies greatly with the species involved in the interaction, an effect that may arise from different evolutionary strategies between long- and short-infesting mussels; a distinction not typically made in conservation practices. Lower growth and reduced osmotic potential in infested hosts are commonly observed and correlated with infestation load. These effects are typically also associated with increases in metabolic rate and behaviour indicative of stress. Host fish seem to compensate for this through a combination of rapid wound healing in the parasitized areas and higher ventilation rates. The findings are heavily biased towardsMargaritifera margaritifera, a unique mussel not well suited for cross-species generalizations. Furthermore, the small body of molecular and genetic studies should be expanded as many conclusions are drawn from studies on the ultimate effects of glochidiosis rather than proximate studies on the underlying mechanisms.
An infrastructural account of scientific objectivity for legal contexts and bloodstain pattern analysis
Authors: Koolage W. John , Williams Lauren M. , Barroso Morgen L.
Published: September 2022

Argument

In the United States, scientific knowledge is brought before the courts by way of testimony – the testimony of scientific experts. We argue that this expertise is best understoodfirstas related to the quality of the underlying scienceand thenin terms of who delivers it. Bloodstain pattern analysis (BPA), a contemporary forensic science, serves as the vaulting point for our exploration of objectivity as a metric for the quality of a science in judicial contexts. We argue that BPA fails to meet the minimal standard set by Helen Longino’s social-procedural account of objectivity (1990, 2002). In light of some pressing issues for social-procedural accounts, we offer an infrastructural account of objectivity. This account offers what amounts to a friendly amendment to Longino’s account and adds to the ways in which we might analyze social-procedural objectivity. Finally, we address an issue that is pressing in the legal context: given that scientific knowledge is delivered by individuals, not communities, at least in U.S. courts, we (may) need a way to evaluate individual scientific and epistemic agents. We suggest a means for making this evaluation that is derived from our infrastructural account of objectivity.
Animism and natural teleology from Avicenna to Boyle
Authors: Kochan Jeff
Published: September 2022

Argument

Historians have claimed that the two closely related concepts of animism and natural teleology were both decisively rejected in the Scientific Revolution. They tout Robert Boyle as an early modern warden against pre-modern animism. Discussing Avicenna, Aquinas, and Buridan, as well as Renaissance psychology, I instead suggest that teleology went through a slow and uneven process of rationalization. As Neoplatonic theology gained influence over Aristotelian natural philosophy, the meaning of animism likewise grew obscure. Boyle, as some historians have shown, exemplifies this uneven process. There is an unresolved tension between his religious convictions and the implicit animism of his empirical practice.
Using one’s talents in honor of God: Lambert ten Kate (1674-1731) and Isaac Newton’s natural philosophy
Authors: Ducheyne Steffen
Published: September 2022

Argument

Lambert ten Kate (1674-1731), the scholar of language, religious writer, art theoretician and collector, and natural philosophy enthusiast, was part of an informal network of Amsterdam-based mathematics and natural philosophy enthusiasts who played a pivotal role in the early diffusion of Newton’s natural philosophical ideas in the Dutch Republic. Because Ten Kate contributed to several areas of research, it is worth asking whether connections can be found between his different scholarly activities and, more specifically, whether his oeuvre as a whole was shaped by his religious views, as has been suggested. In this essay, I shall argue that his oeuvre was indeed shaped by his religious beliefs, which reflect elements typical of Dutchdoperdom, but also reflect a more general Christian orientation that transcends confessional divides. More particularly, I aim to show that, if we want to understand why Ten Kate was drawn to the natural philosophy of his day, and especially to Isaac Newton’s (1642-1727), and why he sought to promote it, we also need to pay attention to this broader Christian orientation in his thought. Along the way, I shall add nuance to earlier characterizations of how ten Kate mobilized Isaac Newton’s natural philosophy according to his own agenda.
Establishing the Domains of a Hospital Disaster Preparedness Evaluation Tool: A Systematic Review
Authors: Munasinghe Nimali Lakmini , O’Reilly Gerard , Cameron Peter
Published: September 2022

Introduction:

Recent disasters emphasize the need for disaster risk mitigation in the health sector. A lack of standardized tools to assess hospital disaster preparedness hinders the improvement of emergency/disaster preparedness in hospitals. There is very limited research on evaluation of hospital disaster preparedness tools.

Objective:

This study aimed to determine the presence and availability of hospital preparedness tools across the world, and to identify the important components of those study instruments.

Method:

A systematic review was performed using three databases, namely Ovid Medline, Embase, and CINAHL, as well as available grey literature sourced by Google, relevant websites, and also from the reference lists of selected articles. The studies published on hospital disaster preparedness across the world from 2011-2020, written in English language, were selected by two independent reviewers. The global distribution of studies was analyzed according to the World Health Organization’s (WHO) six geographical regions, and also according to the four categories of the United Nations Human Development Index (UNHDI). The preparedness themes were identified and categorized according to the 4S conceptual framework: space, stuff, staff, and systems.

Result:

From a total of 1,568 articles, 53 met inclusion criteria and were selected for data extraction and synthesis. Few published studies had used a study instrument to assess hospital disaster preparedness. The Eastern Mediterranean region recorded the highest number of such publications. The countries with a low UNHDI were found to have a smaller number of publications. Developing countries had more focus on preparedness for natural disasters and less focus on chemical, biological, radiological, and nuclear (CBRN) preparedness. Infrastructure, logistics, capacity building, and communication were the priority themes under the space, stuff, staff, and system domains of the 4S framework, respectively. The majority of studies had neglected some crucial aspects of hospital disaster preparedness, such as transport, back-up power, morgue facilities and dead body handling, vaccination, rewards/incentive, and volunteers.

Conclusion:

Important preparedness themes were identified under each domain of the 4S framework. The neglected aspects should be properly addressed in order to ensure adequate preparedness of hospitals. The results of this review can be used for planning a comprehensive disaster preparedness tool.
New Landslide Reporting Tool Uses Social Media and AI
Authors: Padmanaban Deepa
Published: September 2022

The tool extracts landslide information in real time, which could advance landslide research as well as disaster response.
Distinct Microbial Communities in the Soils, Waters, and Speleothems of a Hyperalkaline Cave System
Authors: Shen Jianxun , Smith Andrew C. , Barnett Megan J. , Morgan Alistair , Wynn Peter M.
Published: September 2022

Caves are complex ecosystems with various microbial habitats. Understanding the individual community structures in the key source environments (soils, waters) and those in the sinks (speleothems, cave muds) can help elucidate the extent to which in‐cave communities are a function of their source communities, or if they can successfully adapt and diversify locally. Here, we assess the network of microbial communities existing within a unique British cave system. Poole's Cavern is characterized by alkalinity or even hyperalkalinity (pH > 9) in its drip waters, creating a series of challenging ecological niches for microbes to survive. Samples of soil, drip water, speleothem, and cave sediment were collected for chemical characterization, cell culture assays and DNA sequencing analysis. We show that microbial abundance and diversity were highest in the soils proximal to the cave, and the microbiotas of the hyperalkaline cave chamber were less abundant and less diverse than the cave chamber with lower pH. Proteobacteria and Planctomycetota were the most prevalent bacterial phyla throughout the cave system irrespective of pH, indicating their members are comparatively more metabolically versatile. Predicted essential metabolic pathways were still dominant within all sampling sites, and microorganisms were shown to be capable of utilizing various inorganic or simple organic compounds to survive. Interestingly, co‐occurrence between Poole's samples was limited, never demonstrating more than 50% similarity. This work highlights the diversity of microbial communities within this extreme environment and the development of microbial niches which reflects the adaptation strategy of microorganisms under alkaline‐hyperalkaline conditions.
Non‐Local Parameterization of Atmospheric Subgrid Processes With Neural Networks
Authors: Wang Peidong , Yuval Janni , O’Gorman Paul A.
Published: September 2022

Subgrid processes in global climate models are represented by parameterizations which are a major source of uncertainties in simulations of climate. In recent years, it has been suggested that machine‐learning (ML) parameterizations based on high‐resolution model output data could be superior to traditional parameterizations. Currently, both traditional and ML parameterizations of subgrid processes in the atmosphere are based on a single‐column approach, which only use information from single atmospheric columns. However, single‐column parameterizations might not be ideal since certain atmospheric phenomena, such as organized convective systems, can cross multiple grid boxes and involve slantwise circulations that are not purely vertical. Here we train neural networks (NNs) using non‐local inputs spanning over 3 × 3 columns of inputs. We find that including the non‐local inputs improves the offline prediction of a range of subgrid processes. The improvement is especially notable for subgrid momentum transport and for atmospheric conditions associated with mid‐latitude fronts and convective instability. Using an interpretability method, we find that the NN improvements partly rely on using the horizontal wind divergence, and we further show that including the divergence or vertical velocity as a separate input substantially improves offline performance. However, non‐local winds continue to be useful inputs for parameterizating subgrid momentum transport even when the vertical velocity is included as an input. Overall, our results imply that the use of non‐local variables and the vertical velocity as inputs could improve the performance of ML parameterizations, and the use of these inputs should be tested in online simulations in future work.
Correcting a 200 km Resolution Climate Model in Multiple Climates by Machine Learning From 25 km Resolution Simulations
Authors: Clark Spencer K. , Brenowitz Noah D. , Henn Brian , Kwa Anna , McGibbon Jeremy , Perkins W. Andre , Watt‐Meyer Oliver , Bretherton Christopher S. , Harris Lucas M.
Published: September 2022

Bretherton et al. (2022, https://doi.org/10.1029/2021MS002794) demonstrated a successful approach for using machine learning (ML) to help a coarse‐resolution global atmosphere model with real geography (a ∼200 km version of NOAA's FV3GFS) evolve more like a fine‐resolution model, at the scales resolved by both. This study extends that work for application in multiple climates and multi‐year ML‐corrected simulations. Here four fine‐resolution (∼25 km) 2 year reference simulations are run using FV3GFS with climatological sea surface temperatures perturbed uniformly by −4, 0, +4, and +8 K. A data set of state‐dependent corrective tendencies is then derived through nudging the ∼200 km model to the coarsened state of the fine‐resolution simulations in each climate. Along with the surface radiative fluxes, the corrective tendencies of temperature and specific humidity are machine‐learned as functions of the column state. ML predictions for the fluxes and corrective tendencies are applied in 5.25 years ∼200 km resolution simulations in each climate, and improve the spatial pattern errors of land precipitation by 8%–28% and land surface temperature by 19%–25% across the four climates. The ML has a neutral impact on the pattern error of oceanic precipitation.
Integrative multi-omics landscape of fluoxetine action across 27 brain regions reveals global increase in energy metabolism and region-specific chromatin remodelling
Authors: Rayan Nirmala Arul , Kumar Vibhor , Aow Jonathan , Rastegar Naghmeh , Lim Michelle Gek Liang , O’Toole Nicholas , Aliwarga Edita , Arcego Danusa Mar , Yeo Hui Ting Grace , Wong Jen Yi , Lee May Yin , Schmidt Florian , Haja Hajira Shreen , Tam Wai Leong , Zhang Tie-Yuan , Diorio Josie , Anacker Christoph , Hen Rene , Parent Carine , Meaney Michael J , Prabhakar Shyam
Published: September 2022

Depression and anxiety are major global health burdens. Although SSRIs targeting the serotonergic system are prescribed over 200 million times annually, they have variable therapeutic efficacy and side effects, and mechanisms of action remain incompletely understood. Here, we comprehensively characterise the molecular landscape of gene regulatory changes associated with fluoxetine, a widely-used SSRI. We performed multimodal analysis of SSRI response in 27 mammalian brain regions using 310 bulk RNA-seq and H3K27ac ChIP-seq datasets, followed by in-depth characterisation of two hippocampal regions using single-cell RNA-seq (20 datasets). Remarkably, fluoxetine induced profound region-specific shifts in gene expression and chromatin state, including in the nucleus accumbens shell, locus coeruleus and septal areas, as well as in more well-studied regions such as the raphe and hippocampal dentate gyrus. Expression changes were strongly enriched at GWAS loci for depression and antidepressant drug response, stressing the relevance to human phenotypes. We observed differential expression at dozens of signalling receptors and pathways, many of which are previously unknown. Single-cell analysis revealed stark differences in fluoxetine response between the dorsal and ventral hippocampal dentate gyri, particularly in oligodendrocytes, mossy cells and inhibitory neurons. Across diverse brain regions, integrative omics analysis consistently suggested increased energy metabolism via oxidative phosphorylation and mitochondrial changes, which we corroborated in vitro; this may thus constitute a shared mechanism of action of fluoxetine. Similarly, we observed pervasive chromatin remodelling signatures across the brain. Our study reveals unexpected regional and cell type-specific heterogeneity in SSRI action, highlights under-studied brain regions that may play a major role in antidepressant response, and provides a rich resource of candidate cell types, genes, gene regulatory elements and pathways for mechanistic analysis and identifying new therapeutic targets for depression and anxiety.
Lithium produces bi-directionally regulation of mood disturbance, acts synergistically with anti-depressive/-manic agents, and did not deteriorate the cognitive impairment in murine model of bipolar disorder
Authors: Zhuo Chuanjun , Zhou Chunhua , Tian Hongjun , Li Qianchen , Chen Jiayue , Yang Lei , Zhang Qiuyu , Li Ranli , Ma Xiaoyan , Cai Ziyao , Chen Guangdong , Xu Yong , Song Xueqin
Published: September 2022

Lithium (Li) is a well-established mood disorder treatment and may be neuroprotective. Bi-directional regulation (i.e. affecting manic symptoms and depressive symptoms) by Li has not been demonstrated. This study explored: (1) bidirectional regulation by Li in murine models of depression, mania, and bipolar disorder (BP); and (2) potential Li synergism with antidepressant/anti-mania agents. The chronic unpredictable mild stress (CUMS) and ketamine-induced mania (KM) models were used. These methods were used in series to produce a BP model. In vivo two-photon imaging was used to visualize Ca2+ activity in the dorsolateral prefrontal cortex. Depressiveness, mania, and cognitive function were assessed with the forced swim task (FST), open field activity (OFA) task, and novel object recognition task, respectively. In CUMS mice, Ca2+ activity was increased strongly by Li and weakly by lamotrigine (LTG) or valproate (VPA), and LTG co-administration reduced Li and VPA monotherapy effects; depressive immobility in the FST was attenuated by Li or LTG, and attenuated more strongly by LTG-VPA or LTG-Li; novel object exploration was increased strongly by Li and weakly by LTG-Li, and reduced by LTG, VPA, or LTG-VPA. In KM mice, Li or VPA attenuated OFA mania symptoms and normalized Ca2+ activity partially; Li improved cognitive function while VPA exacerbated the KM alteration. These patterns were replicated in the respective BP model phases. Lithium had bi-directional, albeit weak, mood regulation effects and a cognitive supporting effect. Li co-administration with antidepressant/-manic agents enhanced mood-regulatory efficacy while attenuating their cognitive-impairing effects.
A bitter pill to swallow? Impact of affective temperaments on treatment adherence: a systematic review and meta-analysis
Authors: Szabo Georgina , Fornaro Michele , Dome Peter , Varbiro Szabolcs , Gonda Xenia
Published: September 2022

Background

Predominant affective temperament may affect adherence to prescribed pharmacotherapeutic interventions, warranting systematic review and meta-analysis.

Methods

The Scopus, Web of Science, PubMed, and OVID MedLine databases were inquired since inception up to 31st of March 2022 for records of any study design documenting quantitative evidence about affective temperaments as measured by the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego (TEMPS-A) questionnaire and treatment adherence measured by the means of major rating scales on the matter. People with low vs. high levels of treatment adherence, matched for otherwise clinically relevant variables, were deemed as cases and controls, respectively, using standardized mean differences (SMDs) in pertinent scores under random-effects meta-analysis.

Results

Nine studies encompassing 1138 subjects pointed towards significantly higher cyclothymic (SMD = −0.872; CI: [−1.51 to −0.24]; p = 0.007), irritable (SMD = −0.773; CI: [−1.17 to −0.37]; p < 0.001) and depressive (SMD = −0.758; CI: [−1.38 to −0.14]; p = 0.017) TEMPS-A scores both for psychiatric and nonpsychiatric samples with poorer adherence.

Limitations

Intrinsic limitations of the present report include the heterogeneity of the operational definitions documented across different primary studies, which nonetheless reported on the sole medication-treatment adherence, thus limiting the generalizability of the present findings based on a handful of comparisons.

Conclusions

Though further primary studies need to systematically account for different clinical and psychosocial moderators across different clinical populations and operational definitions, cyclothymic, depressive, and irritable temperament scores may nonetheless predict treatment adherence and, thus, overall treatment outcomes.
Dimension learning based chimp optimizer for energy efficient wireless sensor networks
Authors: Preeti  , Kaur Ranjit , Singh Damanpreet
Published: September 2022

Wireless sensors are the basic requisite of today’s smart infrastructure based on internet of things (IoTs), 5G and wireless sensor networks (WSNs). WSNs are widely used in industrial applications, precision agriculture and animal tracking systems, environment monitoring, smart grids, energy control systems, smart buildings and entertainment industry etc. The distributed and dynamic scheme of WSNs establishes very unique demands in developing clustering and routing protocols. In order to meet the demand of efficient WSNs, most important requirement is energy management and extension of network lifetime. So energy constraints issue is one of the most emerging area for research to reduce the complexity of network functioning. Due to the complexity of this task we need more robustness optimizer algorithms which can tackle these types of tasks. In this article we are trying to develop one improved version of chimp optimizer for energy constraint issues. In this modification have been integrated the chimp optimizer with dimension learning based hunting (DLH) search technique, known as Improved Chimp Optimizer Algorithm (IChoA). Here the DLH search strategy helps in maintaining diversity and improves the balance between exploitation and exploration. To compute the robustness in solving the optimizer issues, IChoA has been tested on 29-CEC-2017 test suites and energy constraint issues. Experimental solutions obtained by proposed methods are verified with recent methods. All simulation shows that the IChoA method can be most effective in solving the standard complex suites and energy constraint issues.
Genome scanning of behavioral selection in a canine olfactory detection breeding cohort
Authors: Eyre Alexander W. , Zapata Isain , Hare Elizabeth , Lee Katharine M. N. , Bellis Claire , Essler Jennifer L. , Otto Cynthia M. , Serpell James A. , Alvarez Carlos E.
Published: September 2022

Research on working dogs is growing rapidly due to increasing global demand. Here we report genome scanning of the risk of puppies being eliminated for behavioral reasons prior to entering the training phase of the US Transportation Security Administration’s (TSA) canine olfactory detection breeding and training program through 2013. Elimination of dogs for behavioral rather than medical reasons was based on evaluations at three, six, nine and twelve months after birth. Throughout that period, the fostered dogs underwent standardized behavioral tests at TSA facilities, and, for a subset of tests, dogs were tested in four different environments. Using methods developed for family studies, we performed a case-control genome wide association study (GWAS) of elimination due to behavioral observation and testing results in a cohort of 528 Labrador Retrievers (2002–2013). We accounted for relatedness by including the pedigree as a covariate and maximized power by including individuals with phenotype, but not genotype, data (approximately half of this cohort). We determined genome wide significance based on Bonferroni adjustment of two quasi-likelihood score tests optimized for either small or nearly-fully penetrant effect sizes. Six loci were significant and five suggestive, with approximately equal numbers of loci for the two tests and frequencies of loci with single versus multiple mapped markers. Several loci implicate a single gene, includingCHD2,NRG3andPDE1Awhich have strong relevance to behavior in humans and other species. We briefly discuss how expanded studies of canine breeding programs could advance understanding of learning and performance in the mammalian life course. Although human interactions and other environmental conditions will remain critical, our findings suggest genomic breeding selection could help improve working dog populations.
Leukocyte glucose index as a novel biomarker for COVID-19 severity
Authors: Ramos-Hernández Wendy Marilú , Soto Luis F. , Del Rosario-Trinidad Marcos , Farfan-Morales Carlos Noe , De Jesús-González Luis Adrián , Martínez-Mier Gustavo , Osuna-Ramos Juan Fidel , Bastida-González Fernando , Bernal-Dolores Víctor , del Ángel Rosa María , Reyes-Ruiz José Manuel
Published: September 2022

The severity of coronavirus disease 2019 (COVID-19) quickly progresses with unfavorable outcomes due to the host immune response and metabolism alteration. Hence, we hypothesized that leukocyte glucose index (LGI) is a biomarker for severe COVID-19. This study involved 109 patients and the usefulness of LGI was evaluated and compared with other risk factors to predict COVID 19 severity. LGI was identified as an independent risk factor (odds ratio [OR] = 1.727, 95% confidence interval [CI]: 1.026–3.048,P = 0.041), with an area under the curve (AUC) of 0.749 (95% CI: 0.642–0.857,P < 0.0001). Interestingly, LGI was a potential risk factor (OR = 2.694, 95% CI: 1.575–5.283,Pcorrected < 0.05) for severe COVID-19 in female but not in male patients. In addition, LGI proved to be a strong predictor of the severity in patients with diabetes (AUC = 0.915 (95% CI: 0.830–1), sensitivity = 0.833, and specificity = 0.931). The AUC of LGI, together with the respiratory rate (LGI + RR), showed a considerable improvement (AUC = 0.894, 95% CI: 0.835–0.954) compared to the other biochemical and respiratory parameters analyzed. Together, these findings indicate that LGI could potentially be used as a biomarker of severity in COVID-19 patients.
Aerodynamics and three-dimensional effect of a translating bristled wing at low Reynolds numbers
Authors: Liu Wenjie , Sun Mao
Published: September 2022

The smallest insects fly with bristled wings at very low Reynolds numbers (Re) and use the drag of the wings to provide the weight-supporting force and thrust. Previous studies used two-dimensional (2-D) models to study the aerodynamic force and the detailed flow field of the bristled wings, neglecting the three-dimensional (3-D) effect caused by the finite span. At high Re, the 3-D effect is known to decrease the aerodynamic force on a body, compared with the 2-D case. However, the bristled wing operates at very low Re, for which the 3-D effect is unknown. Here, a 3-D model of the bristled wing is constructed to numerically investigate the detailed flow field and the aerodynamic force of the wing. Our findings are as follows: The 3-D effect at low Re increases the drag of the bristled wing compared with that of the corresponding 2-D wing, which is contrary to that of the high-Re case. The drag increase is limited to the tip region of the bristles and could be explained by the increase of the flow velocity around the tip region. The spanwise length of the drag-increasing region (measuring from the wing tip) is about 0.23 chord length and does not vary as the wing aspect ratio increases. The amount of the drag increment in the tip region does not vary as the wing aspect ratio increases either, leading to the decrease of the drag coefficient with increasing aspect ratio.
Natraemia variations induced by acute dialysis in critically ill patients: a database study
Authors: Troché Gilles , Laurent Virginie , Ferré Alexis , Jacq Gwenaelle , Paul Marine , Merceron Sybille , Legriel Stephane
Published: September 2022

Natraemia is often abnormal in critically ill patients and may change rapidly during renal replacement therapy (RRT). This database study in a single intensive care unit (ICU) evaluated natraemia before and after the first RRT session for acute kidney injury. Of 252 patients who required RRT in 2018–2020, 215 were included. Prevalences were 53.9% for hyponatraemia (≤ 135 mmol/L) and 3.7% for hypernatraemia (> 145 mmol/L). Dialysate sodium was ≥ 145 mmol/L in 83% of patients. Median dialysis sodium gradient was 12 mmol/L, with a value above 16 mmol/L in 25% of patients. Median natraemia increased from 135 before to 140 mmol/L after RRT, the median hourly increase being faster than recommended, at 1.0 mmol/L [0.2–1.7]. By multivariate analysis, the only variable significantly associated with the RRT-induced natraemia change was the dialysis sodium gradient [odds ratio, 1.66; 95% confidence interval 1.39–2.10]. Pearson’s correlation coefficient between the gradient and the natraemia change was 0.57. When performing RRT in ICU patients, in addition to the haemodynamic considerations put forward in recommendations, the dialysis sodium gradient deserves careful attention in order to control natraemia variations. Studies to devise a formula for predicting natraemia variations might prove helpful to confirm our results.
Thermal annealing effects on tunnel oxide passivated hole contacts for high-efficiency crystalline silicon solar cells
Authors: Kim Yong-Jin , Kweon I Se , Min Kwan Hong , Lee Sang Hee , Choi Sungjin , Jeong Kyung Taek , Park Sungeun , Song Hee-eun , Kang Min Gu , Kim Ka-Hyun
Published: September 2022

Tunnel oxide passivated contacts (TOPCon) embedding a thin oxide layer between polysilicon and base crystalline silicon have shown great potential in the development of solar cells with high conversion efficiency. In this study, we investigate the formation mechanism of hole-carrier selective contacts with TOPCon structure on n-type crystalline silicon wafers. We explore the thermal annealing effects on the passivation properties in terms of the stability of the thermally-formed silicon oxide layer and the deposition conditions of boron-doped polysilicon. To understand the underlying principle of the passivation properties, the active dopant in-diffusion profiles following the thermal annealing are investigated, combined with an analysis of the microscopic structure. Based on PC1D simulation, we find that shallow in-diffusion of boron across a robust tunnel oxide forms a p–n junction and improves the passivation properties. Our findings can provide a pathway to understanding and designing high-quality hole-selective contacts based on the TOPCon structure for the development of highly efficient crystalline silicon solar cells.
Potential risk of SARS-CoV-2 infection among people handling linens used by COVID-19 patients before and after washing
Authors: Fujita Retsu , Kurosu Hitomi , Norizuki Masataro , Ohishi Takayuki , Zamoto-Niikura Aya , Iwaki Masaaki , Mochida Keiko , Takagi Hirotaka , Harada Toshihiko , Tsushima Kenji , Matsumoto Tetsuya , Hanaki Ken-Ichi , Sugai Motoyuki , Yamagishi Takuya
Published: September 2022

The risk of SARS-CoV-2 infection when people handle linens is uncertain. We examined the presence of SARS-CoV-2 on linens, in the air, and on personal protective equipment (PPE) to assess potential infection risk among individuals who handle linens used by SARS-CoV-2-infected people. Patients in a hospital and an accommodation facility who tested positive for SARS-CoV-2 participated in this study in 2020. Linen samples before washing or disinfection, rinse water after washing or disinfection, air in the workplace at the hospital and an accommodation facility, and the PPE worn by linen-handling people were tested for SARS-CoV-2 RNA and viable viruses. Among 700 samples from 13 SARS-CoV-2-infected participants and their surrounding environment, SARS-CoV-2 RNA was detected from 14% (52/362) of the linens used by COVID-19 patients (cycle threshold [Ct] value: 33–40). SARS-CoV-2 RNA was detected from 8% (2/26) of rinse water after washing or disinfection, from 15% (16/104) of air samples in the workspace, and from 10% (5/52) of gowns worn by linen-handling people, all with high Ct values (> 36). No SARS-CoV-2 was isolated from any samples. The potential risk of SARS-CoV-2 infection from handling linens used by SARS-CoV-2-infected people exists but appears to below.
Adult fibroblasts use aggresomes only in distinct cell-states
Authors: Morrow Christopher S. , Arndt Zachary P. , Klosa Payton C. , Peng Bo , Zewdie Eden Y. , Benayoun Bérénice A. , Moore Darcie L.
Published: September 2022

The aggresome is a protein turnover system in which proteins are trafficked along microtubules to the centrosome for degradation. Despite extensive focus on aggresomes in immortalized cell lines, it remains unclear if the aggresome is conserved in all primary cells and all cell-states. Here we examined the aggresome in primary adult mouse dermal fibroblasts shifted into four distinct cell-states. We found that in response to proteasome inhibition, quiescent and immortalized fibroblasts formed aggresomes, whereas proliferating and senescent fibroblasts did not. Using this model, we generated a resource to provide a characterization of the proteostasis networks in which the aggresome is used and transcriptomic features associated with the presence or absence of aggresome formation. Using this resource, we validate a previously reported role for p38 MAPK signaling in aggresome formation and identify TAK1 as a novel driver of aggresome formation upstream of p38 MAPKs. Together, our data demonstrate that the aggresome is a non-universal protein degradation system which can be used cell-state specifically and provide a resource for studying aggresome formation and function.
Online knowledge distillation network for single image dehazing
Authors: Lan Yunwei , Cui Zhigao , Su Yanzhao , Wang Nian , Li Aihua , Zhang Wei , Li Qinghui , Zhong Xiao
Published: September 2022

Single image dehazing, as a key prerequisite of high-level computer vision tasks, catches more and more attentions. Traditional model-based methods recover haze-free images via atmospheric scattering model, which achieve favorable dehazing effect but endure artifacts, halos, and color distortion. By contrast, recent learning-based methods dehaze images by a model-free way, which achieve better color fidelity but tend to acquire under-dehazed results due to lacking of knowledge guiding. To combine these merits, we propose a novel online knowledge distillation network for single image dehazing named OKDNet. Specifically, the proposed OKDNet firstly preprocesses hazy images and acquires abundant shared features by a multiscale network constructed with attention guided residual dense blocks. After that, these features are sent to different branches to generate two preliminary dehazed images via supervision training: one branch acquires dehazed images via the atmospheric scattering model; another branch directly establishes the mapping relationship between hazy images and clear images, which dehazes images by a model-free way. To effectively fuse useful information from these two branches and acquire a better dehazed results, we propose an efficient feature aggregation block consisted of multiple parallel convolutions with different receptive. Moreover, we adopt a one-stage knowledge distillation strategy named online knowledge distillation to joint optimization of our OKDNet. The proposed OKDNet achieves superior performance compared with state-of-the-art methods on both synthetic and real-world images with fewer model parameters. Project website: https://github.com/lanyunwei/OKDNet.
Mechanosensitive expression of the mesenchymal subtype marker connective tissue growth factor in glioblastoma
Authors: Grundy Thomas James , Orcheston-Findlay Louise , de Silva Eshana , Jegathees Thuvarahan , Prior Victoria , Sarker Farhana Amy , O’Neill Geraldine Margaret
Published: September 2022

Mechanical forces created by the extracellular environment regulate biochemical signals that modulate the inter-related cellular phenotypes of morphology, proliferation, and migration. A stiff microenvironment induces glioblastoma (GBM) cells to develop prominent actin stress fibres, take on a spread morphology and adopt trapezoid shapes, when cultured in 2D, which are phenotypes characteristic of a mesenchymal cell program. The mesenchymal subtype is the most aggressive among the molecular GBM subtypes. Recurrent GBM have been reported to transition to mesenchymal. We therefore sought to test the hypothesis that stiffer microenvironments—such as those found in different brain anatomical structures and induced following treatment—contribute to the expression of markers characterising the mesenchymal subtype. We cultured primary patient-derived cell lines that reflect the three common GBM subtypes (mesenchymal, proneural and classical) on polyacrylamide (PA) hydrogels with controlled stiffnesses spanning the healthy and pathological tissue range. We then assessed the canonical mesenchymal markers Connective Tissue Growth Factor (CTGF) and yes-associated protein (YAP)/transcriptional co-activator with PDZ-binding motif (TAZ) expression, via immunofluorescence. Replating techniques and drug-mediated manipulation of the actin cytoskeleton were utilised to ascertain the response of the cells to differing mechanical environments. We demonstrate that CTGF is induced rapidly following adhesion to a rigid substrate and is independent of actin filament formation. Collectively, our data suggest that microenvironmental rigidity can stimulate expression of mesenchymal-associated molecules in GBM.
Reactivity disturbance suppression method for small modular reactors based on core coolant flow control
Authors: Xie Hongyun , Duan Qizhi , Ping Jialin , Lu Chao , Zhang Liming , Li Shuqiang
Published: September 2022

Small modular reactors (SMR) have an exceptionally wide range of applications due to their flexibility. But the reactivity of SMR is more susceptible to disturbance than that of large commercial reactors, which may cause the core power to deviate from the set value, and the limited internal space makes it difficult for SMR to compensate or adjust for reactivity disturbance by setting a sufficient number of control rods as in large commercial reactors. Therefore, in order to improve the operational stability of SMR, a method is proposed to indirectly change the nuclear fuel temperature by adjusting the coolant flow rate and thus compensate the reactivity disturbance by the Doppler effect of nuclear fuel resonance absorption. Simulation experiments show that the method can effectively eliminate reactive disturbances that cannot be completely eliminated by control rods under the conditions of restricted SMR space and limited number of control rod sets, thus providing operational stability of SMR.
Current sensorless position-tracking control with angular acceleration error observers for hybrid-type stepping motors
Authors: Kim Seok-Kyoon , Kim Kwan Soo , Lee Dong Kyu , Ahn Choon Ki
Published: September 2022

This paper exhibits an advanced observer-based position-tracking controller for hybrid-type stepping motors with consideration of parameter and load uncertainties. As the main contribution, a current sensorless observer-based pole-zero cancellation speed controller is devised for the outer loop position-tracking controller including the convergence rate boosting mechanism. The features of this study are summarized as follows; first, the pole-zero cancellation angular acceleration error observer for the inner loop speed controller, second, the pole-zero cancellation speed control forcing the order of the controlled speed error dynamics to be 1, and, third, the outer loop position control incorporating the first-order target tracking system with its convergence rate booster. The resultant effectiveness is verified on a 10-W stepping motor control system.
Searching for the ground state of complex spin-ice systems using deep learning techniques
Authors: Kwon H. Y. , Yoon H. G. , Park S. M. , Lee D. B. , Shi D. , Wu Y. Z. , Choi J. W. , Won C.
Published: September 2022

Searching for the ground state of a given system is one of the most fundamental and classical questions in scientific research fields. However, when the system is complex and large, it often becomes an intractable problem; there is essentially no possibility of finding a global energy minimum state with reasonable computational resources. Recently, a novel method based on deep learning techniques was devised as an innovative optimization method to estimate the ground state. We apply this method to one of the most complicated spin-ice systems, aperiodic Penrose P3 patterns. From the results, we discover new configurations of topologically induced emergent frustrated spins, different from those previously known. Additionally, a candidate of the ground state for a still unexplored type of Penrose P3 spin-ice system is first proposed through this study. We anticipate that the capabilities of the deep learning techniques will not only improve our understanding on the physical properties of artificial spin-ice systems, but also bring about significant advances in a wide range of scientific research fields requiring computational approaches for optimization.