bluuebunny/crossref_metadata_2025 huggingface dataset:
An associative knowledge network model for interpretable semantic representation of noun context
Authors: Li Yulin , Xie Zhenping , Wang Fanyu
Published: May 2022

Uninterpretability has become the biggest obstacle to the wider application of deep neural network, especially in most human–machine interaction scenes. Inspired by the powerful associative computing ability of human brain neural system, a novel interpretable semantic representation model of noun context, associative knowledge network model, is proposed. The proposed network structure is composed of only pure associative relationships without relation label and is dynamically generated by analysing neighbour relationships between noun words in text, in which incremental updating and reduction reconstruction strategies can be naturally introduced. Furthermore, a novel interpretable method is designed for the practical problem of checking the semantic coherence of noun context. In proposed method, the associative knowledge network learned from the text corpus is first regarded as a background knowledge network, and then the multilevel contextual associative coupling degree features of noun words in given detection document are computed. Finally, contextual coherence detection and the location of those inconsistent noun words can be realized by using an interpretable classification method such as decision tree. Our sufficient experimental results show that above proposed method can obtain excellent performance and completely reach or even partially exceed the performance obtained by the latest deep neural network methods especially in F1 score metric. In addition, the natural interpretability and incremental learning ability of our proposed method should be extremely valuable than deep neural network methods. So, this study provides a very enlightening idea for developing interpretable machine learning methods, especially for the tasks of text semantic representation and writing error detection.
Helping novice developers harness security issues in cloud-IoT systems
Authors: Corno Fulvio , De Russis Luigi , Mannella Luca
Published: May 2022

The development of cloud-connected Internet of Things (IoT) systems is becoming more and more affordable, even to novice programmers, thanks to dedicated cloud platforms that already integrate the core functionality needed by an IoT system. In this context, a growing number of IoT systems are being developed and deployed on open networks, often without integrating adequate security in the process. Novice IoT programmers, in particular, tend to overlook security issues, as confirmed by a small user study. Starting from this risk, the paper analyzes the security features available in two major cloud-IoT platforms (Amazon Web Services and Microsoft Azure) and highlights those settings, tools, and practices designed to ensure more secure implementations. We observed that these platforms would reasonably address many security problems detected in the study, if only the correct features were identified and used. The paper finally contributes a set of guidelines to support novice IoT developers in avoiding the main and recurrent security issues in their projects and better exploiting cloud-IoT platforms’ inherent security features.
Learning from the Dirt: Initiating university food gardens as a cross-disciplinary tertiary teaching tool
Authors: Sherry Cathy
Published: May 2022

Food gardens are an underdeveloped resource for teaching and research in Australian universities. While some campuses have food or botanical gardens, outside the biological or physical sciences food growing is not routinely incorporated into mainstream curricula. This article investigates why and how we might change this. It examines universities’ traditional reliance on classroom-based, non-experiential learning, which preferences reading and writing over doing, particularly doing anything outdoors. Questions are raised about the implications of this approach for environmental education and graduate environmental literacy. The article then explores the example that United States campus food gardens provide other universities, as well as the process of creating food gardens for teaching and research at a high-density campus in Sydney, Australia. The article ends by postulating lessons students and staff might learn about food systems, sustainability and green cities, when food growing is incorporated into teaching and research. The article aims to inspire academic staff, particularly outside the biological sciences, to instigate campus food gardens to increase graduate environmental literacy.
A numerical analysis of the instability in the Taylor Vortex flow by using the visualization of attractors
Authors: Toya Yorinobu , Watanabe Takashi
Published: May 2022

This study clarifies the critical values of bifurcations from a steady Taylor flow into a wavy Taylor flow by a numerical analysis applying chaos theory. In our previous numerical research, we adopt the amplitude fluctuation of the kinetic energy of the axial velocity component as a standard criterion to identify the critical Reynolds number. However, the amplitude fluctuation of the kinetic energy is very small near the critical value, which affects the judgment of Taylor flow or wavy Taylor flow. In this study, in order to improve this problem, we introduce a new method that visualizes attractors in the three-dimensional embedded space composed from the axial velocity component. The targets are the normal 2-vortex, 4-vortex and 6-vortex modes, which stably present in the range of the aspect ratio from 1.0 to 7.2 in a system with stationary end walls of two cylinders with the radius ratio 0.667. The critical values at which the Taylor flow bifurcates into the wavy Taylor flow are determined based on the converged orbit shapes of the attractors. The analytical result shows that, in each flow mode, the critical Reynolds number for the onset of the wavy flow has its peak and presents a quantitative agreement with the experimental result in the lower range than the peak Reynolds number. This study shows that the instability of the Taylor flow is revealed by determining the structure of the attractor applied by the Hopf bifurcation. In addition, it is represented that this numerical approach using attractors can obtain more accurate results than those obtained by a numerical evaluation method using the amplitude of the kinetic energy of the Taylor flow.
Modeling, simulation and experimental exploration of metal magnetic memory under weak magnetic excitation
Authors: Liu Bo , Zhang Juwei , Zhang Zengguang
Published: May 2022

This study proposes to use the improved Jiles–Atherton (J–A) magneto-mechanical effect model combined with simulation analysis to detect the damage of wire rope. By establishing the theoretical basis of the J–A model under weak magnetic excitation, the simulation analysis is carried out by using ANSYS software, and finally the correctness of the simulation and theoretical results is verified by experiments. The results show that the weak magnetic excitation magnetic field has a strengthening effect on the magnetic memory signal under the action of the force-magnetic coupling. By processing the extracted magnetic memory signal, it is verified that the weak magnetic excitation magnetic field alone has a certain inhibitory effect on the environmental interference of the geomagnetic field. Compared with the geomagnetic field environment, the weak magnetic excitation magnetic field can better identify the different defect types of simulated 60 steel damage and wire rope defects. Studies have shown that weak magnetic excitation plays an important role in the damage detection of ferromagnetic materials.
Elevated Vulnerability of Chronic Leukemia Patients to COVID-19 Infection: A Systems Biology Approach
Authors: Alsalman Abdulkhaliq J. , Al Mohaini Mohammed , Malik Md. Zubbair , Imran Mohd. , Alomar Fadhel A. , Al Awwad Nasir
Published: May 2022

Background

Emerging evidence has shown that SARS-CoV-2 may affect the circulatory system in addition to the human respiratory system. However, no study has indicated whether patients with leukemia have a greater likelihood of SARS-CoV-2 infection or have poor treatment outcomes.

Objective

The study aimed to demonstrate the relationship between essential blood proteins and the major SARS-CoV-2 proteins by network pharmacology bioinformatics analysis.

Methods

Bioinformatics analysis was used to establish eight differentially expressed gene hubs in leukemia through differential gene screening, protein–protein interaction network analysis, and gene enrichment analysis. Molecular docking analysis was also conducted to dock the two up-regulated proteins with the spike glycoprotein in leukemia and the critical protease enzyme (Mpro) of SARS-CoV-2.

Results

We identified two up-regulated genes (PTPRC and BCL6) among the eight differentially expressed genes. The PTPRC and BCL6 also docked perfectly with the main SARS-CoV-2 structural proteins.

Conclusion and Recommendation

This study indicates that SARS-CoV-2 is likely to affect with the blood in patients with chronic leukemia. Therefore, patients with chronic leukemia require greater medical attention and precautions during the COVID-19 pandemic.
The control of particles in the Stokes limit
Authors: Walker B.J. , Ishimoto K. , Gaffney E.A. , Moreau C.
Published: May 2022

There are numerous ways to control objects in the Stokes regime, with microscale examples ranging from the use of optical tweezers to the application of external magnetic fields. In contrast, there are relatively few explorations of theoretical controllability, which investigate whether or not refined and precise control is indeed possible in a given system. In this work, seeking to highlight the utility and broad applicability of such rigorous analysis, we recount and illustrate key concepts of geometric control theory in the context of multiple particles in Stokesian fluids interacting with each other, such that they may be readily and widely applied in this largely unexplored fluid-dynamical setting. Motivated both by experimental and abstract questions of control, we exemplify these techniques by explicit and detailed application to multiple problems concerning the control of two particles, such as the motion of tracers in flow and the guidance of one sphere by another. Further, we showcase how this analysis of controllability can directly lead to the construction of schemes for control, in addition to facilitating explorations of mechanical efficiency and contributing to our overall understanding of non-local hydrodynamic interactions in the Stokes limit.
Interpreted machine learning in fluid dynamics: explaining relaminarisation events in wall-bounded shear flows
Authors: Lellep Martin , Prexl Jonathan , Eckhardt Bruno , Linkmann Moritz
Published: May 2022

Machine Learning (ML) is becoming increasingly popular in fluid dynamics. Powerful ML algorithms such as neural networks or ensemble methods are notoriously difficult to interpret. Here, we introduce the novel Shapley additive explanations (SHAP) algorithm (Lundberg & Lee, Advances in Neural Information Processing Systems, 2017, pp. 4765–4774), a game-theoretic approach that explains the output of a given ML model in the fluid dynamics context. We give a proof of concept concerning SHAP as an explainable artificial intelligence method providing useful and human-interpretable insight for fluid dynamics. To show that the feature importance ranking provided by SHAP can be interpreted physically, we first consider data from an established low-dimensional model based on the self-sustaining process (SSP) in wall-bounded shear flows, where each data feature has a clear physical and dynamical interpretation in terms of known representative features of the near-wall dynamics, i.e. streamwise vortices, streaks and linear streak instabilities. SHAP determines consistently that only the laminar profile, the streamwise vortex and a specific streak instability play a major role in the prediction. We demonstrate that the method can be applied to larger fluid dynamics datasets by a SHAP evaluation on plane Couette flow in a minimal flow unit focussing on the relevance of streaks and their instabilities for the prediction of relaminarisation events. Here, we find that the prediction is based on proxies for streak modulations corresponding to linear streak instabilities within the SSP. That is, the SHAP analysis suggests that the break-up of the self-sustaining cycle is connected with a suppression of streak instabilities.
Fluid-mediated sources of granular temperature at finite Reynolds numbers
Authors: Lattanzi Aaron M. , Tavanashad Vahid , Subramaniam Shankar , Capecelatro Jesse
Published: May 2022

We derive analytical solutions for hydrodynamic sources and sinks to granular temperature in moderately dense suspensions of elastic particles at finite Reynolds numbers. Modelling the neighbour-induced drag disturbances with a Langevin equation allows an exact solution for the joint fluctuating acceleration–velocity distribution function

$P(v^{\prime },a^{\prime };t)$

. Quadrant-conditioned covariance integrals of

$P(v^{\prime },a^{\prime };t)$

yield the hydrodynamic source and sink that dictate the evolution of granular temperature that can be used in Eulerian two-fluid models. Analytical predictions agree with benchmark data from particle-resolved direct numerical simulations and show promise as a general theory from gas–solid to bubbly flows.
Community Response to Rebordering Politics: The Case of Two Twin Towns in Central Europe
Authors: Kajta Justyna , Opiłowska Elżbieta
Published: May 2022

The coronavirus disease 2019 (COVID-19) pandemic has once again brought borders to the center of attention, as journalists, authorities, and scholars have grappled with the pandemic. The coronavirus outbreak, which began in late 2019 and early 2020 has caused tremendous personal, economic, and social upheaval. As many states decided to pursue the national interests and to close their borders to prevent the spread of the virus, this decision had major consequences for residents in border regions, for whom border crossing is an everyday practice. The article aims at exploring the discourse on the rebordering experience as constructed by local authorities and residents of two twin towns, one on the Polish-Czech (Cieszyn-Český Těšín) and one on the Polish-German (Słubice-Frankfurt/Oder) border. By applying a Discursive Historical Approach, we identified four main discursive strands which deployed diverse imaginaries.
Undisciplined Constituency Campaign Behaviour in Canadian Federal Elections
Authors: Robbins-Kanter Jacob
Published: May 2022

Scholarly research suggests that Canadian election campaigns are centralized affairs, with party headquarters managing a disciplined campaign organization across 338 federal constituencies. At the same time, local realities can incentivize constituency campaigns to deviate from their parties. This article examines the extent of local campaign discipline, given these tensions between parties’ centralizing compulsions and countervailing forces that militate against party cohesion. The article relies on original data to identify and explain the extent of local campaign behaviour that defies central party preferences and directives. It draws from interviews with 87 former candidates and eight party strategists, as well as observational data gathered from 10 constituency campaigns during the 2019 federal election. The findings indicate a relatively high level of undisciplined constituency campaign behaviour during the 2015 and 2019 elections. The article contends that this behaviour stems from insubordination, innovation and incompetence within constituency campaigns.
‘Males are Undeserving; Females are Ideal Victims’: Gender Bias Hides Demand in Human-Smuggling Networks
Authors: Izcara Palacios Simón Pedro
Published: May 2022

The objective of this paper, based on interviews with 95 human smugglers (coyotes) involved in agriculture and 51 in prostitution, is to provide a comparative analysis of the networks transporting (mostly) male migrants intending to work in US agriculture and those recruiting women/girls for the US sex industry. Networks carrying females for sex work are bigger and use more fraudulent recruitment strategies. However, migrant smuggling for agriculture is not totally different from sex trafficking; similarities between the types of networks analysed dwarf their differences. Smugglers frequently use some form of deception to convince their would-be clients/victims to undertake risky journeys. I conclude that both networks are demand-driven. Smugglers serve the interests of US agribusinesses and sex business owners rather than those of the males and females they recruit.
Experiments make a good breakfast, but a poor supper
Authors: Jetten Jolanda , Selvanathan Hema Preya , Crimston Charlie R. , Bentley Sarah V. , Haslam S. Alexander
Published: May 2022

Cesario's analysis has three key flaws. First, the focus on whether an effect is “real” (an “effects flaw”) overlooks the importance of theory testing. Second, obsession with effects (a “fetishization flaw”) sidelines theoretically informed questions about when and why an effect may arise. Third, failure to take stock of cultural and historical context (a “decontextualization flaw”) strips findings of meaning.
Surely not all experimental studies of bias need abandoning?
Authors: White Fiona A.
Published: May 2022

Cesario misrepresents experimental social psychology. The discipline encompasses significantly more than implicit bias research, including controlled decision making and real-world behavioral observations. Paradoxically, while critiquing popular implicit bias tasks, Cesario also describes task refinements that have significantly advanced their external validity and our contextual understanding of bias. Thus rather than abandonment, a call for “continued improvement” is a far more sensible proposition.
Social bias insights concern judgments rather than real-world decisions
Authors: Białek Michał , Grossmann Igor
Published: May 2022

Judgments differ from decisions. Judgments are more abstract, decontextualized, and bear fewer consequences for the agent. In pursuit of experimental control, psychological experiments on bias create a simplified, bare-bone representation of social behavior. These experiments resemble conditions in which people judge others, but not how they make real-world decisions.
The logic of challenging research into bias and social disparity
Authors: Rini Regina
Published: May 2022

There are two problems with the logic of Cesario's argument for abandoning existing research on social bias. First, laboratory findings of decisional bias have social significance even if Cesario is right that the research strips away real-world context. Second, the argument makes overly skeptical demands of a research program seeking complex causal linkages between micro- and macro-scale phenomena.
The diameter of the uniform spanning tree of dense graphs
Authors: Alon Noga , Nachmias Asaf , Shalev Matan
Published: May 2022

We show that the diameter of a uniformly drawn spanning tree of a simple connected graph on n vertices with minimal degree linear in n is typically of order
$\sqrt{n}$
. A byproduct of our proof, which is of independent interest, is that on such graphs the Cheeger constant and the spectral gap are comparable.
Al2O3 Grain Boundary Segregation in a Thermal Barrier Coating on a Ni-Based Superalloy
Authors: Chen Yimeng , Rice Katherine P , Prosa Ty J , Reed Roger C , Marquis Emmanuelle A
Published: May 2022

The segregation of reactive elements (REs) along thermally grown oxide (TGO) grain boundaries has been associated to slower oxide growth kinetics and improved creep properties. However, the incorporation and diffusion of these elements into the TGO during oxidation of Ni alloys remains an open question. In this work, electron backscatter diffraction in transmission mode (t-EBSD) was used to investigate the microstructure of TGO within the thermal barrier coating on a Ni-based superalloy, and atom probe tomography (APT) was used to quantify the segregation behavior of REs to α-Al2O3 grain boundaries. Integrating the two techniques enables a higher level of site-specific analysis compared to the routine focused ion beam lift-out sample preparation method without t-EBSD. Needle-shaped APT specimens readily meet the thickness criterion for electron diffraction analysis. Transmission EBSD provides an immediate feedback on grain orientation and grain boundary location within the APT specimens to help target grain boundaries in the TGO. Segregation behavior of REs is discussed in terms of the grain boundary character and relative location in TGO.
Impact of split X-jaw technique on target volume coverage and organ at risk sparing in prostate cancer: a comparative dosimetric study
Authors: Sarma Gautam , Nath Jyotiman , Goswami Shachindra , Goswami Pranjal , Sharma Shashi Bhushan , Kalita Apurba Kumar
Published: May 2022

Introduction:

The Varian Trilogy linear accelerator’s multi-leaf collimator moves on a carriage with a maximum leaf span of 15 cm. The traditional open and limited X-jaw technique of volumetric-modulated arc radiotherapy (VMAT) yields a relatively compromised dose distribution within the planning target volume (PTV) region. This study aimed to determine whether the split X-jaw planning technique for VMAT improves plan quality regarding target dose coverage and organs at risk (OAR) sparing for PTVs that require a field size of more than 15 cm in the X-jaw direction in prostate cancer patients.

Method:

Computed tomography data sets from 15 patients with prostate cancer were enrolled in the study. Only the PTVs requiring a field size larger than 18 cm in the X-jaw position were considered, and a dose of 4500 cGy in 25 fractions was prescribed. For each case, three separate treatment plans were generated: open, limited and split X-jaw planning techniques with similar planning objectives

Results:

The split X-jaw technique resulted in statistically significant superior coverage of PTV when compared with the open (P < 0·0001) and limited methods (P < 0·001). The split technique delivered a lower dose to the OARs, although statistical significance could not be achieved. D2% (cGy) was lowest for the PTV in the split technique (4684·8 ± 18·16) and highest for the open technique (4710 ± 18·75), P < 0·001.

Conclusion:

The x-split jaw technique can replace the traditional open X-jaw practice of VMAT for PTVs requiring an X-jaw width of more than 15 cm in the Varian linear accelerator.
Equatorial Origin of the Observed Tropical Pacific Quasi‐Decadal Variability From ENSO Nonlinearity
Authors: Liu Chao , Zhang Wenjun , Jin Fei‐Fei , Stuecker Malte F. , Geng Licheng
Published: May 2022

Quasi‐decadal (QD) climate variability is detected in the tropical Pacific based on the recent 70 years of observations. This QD variability is identified in equatorial sea surface temperatures (SSTs), the pattern of which resembles the Central Pacific (CP) El Niño‐Southern Oscillation (ENSO) but extends further meridionally to the northeastern subtropical Pacific. Whereas equatorial upper‐ocean heat content and SSTs are in quadrature for ENSO, these two quantities are almost in phase on the QD timescale. Further analysis shows that nonlinear dynamical heating, primarily originating from strong El Niño events, tends to lead QD SSTs by a quarter of its dominant period (approximately 30 months) and shapes the dominant QD periodicity in observations. Our results suggest that the observed QD variability largely originates from ENSO nonlinearity and thus is fundamentally different from ENSO's oscillatory nature.
Icequake‐Magnitude Scaling Relationship Along a Rift Within the Ross Ice Shelf, Antarctica
Authors: Huang Mong‐Han , Udell Lopez Kathrine , Olsen Kira G.
Published: May 2022

Fractures within ice shelves are zones of weakness, which can deform on timescales from seconds to decades. Icequakes produced during the fracturing process show a higher b‐value in the Gutenberg‐Richter scaling relationship than continental earthquakes. We investigate icequakes on the east side of rift WR4 in the Ross Ice Shelf, Antarctica. Our model suggests a maximum icequake slip depth that is ∼7.8 m below the rift mélange, where the slip area can only grow laterally along the fracture planes. We propose ductile deformation below this depth, potentially due to the saturation of unfrozen water. We use remote sensing and geodetic tools to quantify surface movement on different timescales and find that the majority of icequakes occur during falling tides. The total seismic moment is <1% of the estimated geodetic moment during a tidal cycle. This study demonstrates the feasibility of using seismology and geodesy to investigate ice rift zone rheology.
The relationship of life-course patterns of adiposity with type 2 diabetes, depression, and their comorbidity in the Northern Finland Birth Cohort 1966
Authors: Choudhary Priyanka , Ronkainen Justiina , Nedelec Rozenn , Tolvanen Mimmi , Lowry Estelle , Miettunen Jouko , Jarvelin Marjo-Riitta , Sebert Sylvain
Published: May 2022

Objectives

Type 2 diabetes (T2D) and comorbid depression challenges clinical management particularly in individuals with overweight. We aim to explore the shared etiology, via lifecourse adiposity, between T2D and depression.

Methods

We used data from birth until 46years from Northern Finland Birth Cohort 1966 (n = 6,372; 53.8% females). We conducted multivariate analyses on three outcomes: T2D (4.2%), depression (19.2%) and as comorbidity (1.8%). We conducted (i) Path analysis to clarify time-dependent body mass index (BMI) related pathways, including BMI polygenic risk scores (PRS); and (ii) Cox regression models to assess whether reduction of overweight between 7years and 31years influence T2D, depression and/or comorbidity. The models were tested for covariation with sex, education, smoking, physical activity, and diet score.

Results

The odd ratios (OR) of T2D in individuals with depression was 1.68 [95% confidence interval (CI): 1.34–2.11], and no change in estimate was observed when adjusted for covariates. T2D and comorbidity showed similar patterns of relationships in the path analyses (P < 0.001). The genetic risk for obesity (PRS BMI) did not show direct effect on T2D or comorbidity in adulthood but indirectly through measures of adiposity in early childhood and mid-adulthood in the path analysis (P < 0.001). Having early-onset of overweight at 7years and 31years showed highest risk of T2D (OR 3.8, 95%CI 2.4–6.1) and comorbidity (OR 5.0, 95%CI 2.7–9.5), with mild-to-moderate attenuation with adjustments. Depression showed no significant associations.

Conclusions

We found evidence for overweight since childhood as a risk factor for T2D and co-morbidity between T2D and depression, influenced moderately by lifestyle factors in later life. However, no shared early life adiposity related risk factors were observed between T2D and depression when assessed independently in this Finnish setting.
Gefitinib and fostamatinib target EGFR and SYK to attenuate silicosis: a multi-omics study with drug exploration
Authors: Wang Mingyao , Zhang Zhe , Liu Jiangfeng , Song Meiyue , Zhang Tiantian , Chen Yiling , Hu Huiyuan , Yang Peiran , Li Bolun , Song Xiaomin , Pang Junling , Xing Yanjiang , Cao Zhujie , Guo Wenjun , Yang Hao , Wang Jing , Yang Juntao , Wang Chen
Published: May 2022

Silicosis is the most prevalent and fatal occupational disease with no effective therapeutics, and currently used drugs cannot reverse the disease progress. Worse still, there are still challenges to be addressed to fully decipher the intricated pathogenesis. Thus, specifying the essential mechanisms and targets in silicosis progression then exploring anti-silicosis pharmacuticals are desperately needed. In this work, multi-omics atlas was constructed to depict the pivotal abnormalities of silicosis and develop targeted agents. By utilizing an unbiased and time-resolved analysis of the transcriptome, proteome and phosphoproteome of a silicosis mouse model, we have verified the significant differences in transcript, protein, kinase activity and signaling pathway level during silicosis progression, in which the importance of essential biological processes such as macrophage activation, chemotaxis, immune cell recruitment and chronic inflammation were emphasized. Notably, the phosphorylation of EGFR (p-EGFR) and SYK (p-SYK) were identified as potential therapeutic targets in the progression of silicosis. To inhibit and validate these targets, we tested fostamatinib (targeting SYK) and Gefitinib (targeting EGFR), and both drugs effectively ameliorated pulmonary dysfunction and inhibited the progression of inflammation and fibrosis. Overall, our drug discovery with multi-omics approach provides novel and viable therapeutic strategies for the treatment of silicosis.
Altered amygdala shape trajectories and emotion recognition in youth at familial high risk of schizophrenia who develop psychosis
Authors: Guimond Synthia , Mothi Suraj S. , Makowski Carolina , Chakravarty M. Mallar , Keshavan Matcheri S.
Published: May 2022

Relatives of individuals with schizophrenia have a higher risk of developing the illness compared to the general population. Thus, youth at familial high risk (FHR) offer a unique opportunity to identify neuroimaging-based endophenotypes of psychosis. Previous studies have identified lower amygdalo-hippocampal volume in FHR, as well as lower verbal memory and emotion recognition. However, whether these phenotypes increase the risk of transition to psychosis remains unclear. To determine if individuals who develop psychosis have abnormal neurodevelopmental trajectories of the amygdala and hippocampus, we investigated longitudinal changes of these structures in a unique cohort of 82 youth FHR and 56 healthy controls during a 3-year period. Ten individuals from the FHR group converted to psychosis. Longitudinal changes were compared using linear mixed-effects models. Group differences in verbal memory and emotion recognition performance at baseline were also analyzed. Surface-based morphometry measures revealed variation in amygdalar shape (concave shape of the right dorsomedial region) in those who converted to psychosis. Significantly lower emotion recognition performance at baseline was observed in converters. Percent trial-to-trial transfer on the verbal learning task was also significantly impaired in FHR, independently of the conversion status. Our results identify abnormal shape development trajectories in the dorsomedial amygdala and lower emotion recognition abilities as phenotypes of transition to psychosis. Our findings illustrate potential markers for early identification of psychosis, aiding prevention efforts in youth at risk of schizophrenia.
Resin-based composite materials: elution and pollution
Authors: Mulligan Steven , Hatton Paul V. , Martin Nicolas
Published: May 2022

Pollution arises from all human activity and the provision of oral healthcare using resin-based composite restorative materials (RBCs) should be considered. This paper aims to provide a comprehensive review of the potential pollutant risk to the environment from the chemical compounds found in resin-based restorative materials, by including: 1) the principal pollutant compounds present in the resin matrix; 2) the degradation process of RBCs and its consequences; 3) the methods used for the detection and quantification of monomer elution and RBC microparticles; and 4) a review of the release mechanisms of eluates and RBC microparticles into the environment.

RBCs are pollutants by virtue of the compounds created during the degradation processes. These are in the form of the constituent eluted monomers and microparticles. Their impact on the environment and biodiversity is unknown. These materials are currently one of the main direct-placement restorative materials and their success is unquestionable when used and maintained correctly. Mitigation strategies for reducing the impact of pollution on the environment should be considered and implemented by all stakeholders and processes in the supply chain, from manufacturing, clinical use and waste management.
Relevance of sleep and associated structural changes in GBA1 mouse to human rapid eye movement behavior disorder
Authors: Gelegen Cigdem , Cash Diana , Ilic Katarina , Sander Millie , Kim Eugene , Simmons Camilla , Bernanos Michel , Lama Joana , Randall Karen , Brown Jonathan T. , Kalanj-Bognar Svjetlana , Cooke Samuel , Ray Chaudhuri K. , Ballard Clive , Francis Paul , Rosenzweig Ivana
Published: May 2022

Rapid eye movement (REM) sleep behaviour disorder (RBD) is a REM parasomnia that often predicts the later occurrence of alpha-synucleinopathies. Variants in the gene encoding for the lysosomal enzyme glucocerebrosidase, GBA, strongly increase the risk of RBD. In a GBA1-mouse model recently shown to mimic prodromal stages of α-synucleinopathy, we now demonstrate striking REM and NREM electroencephalographic sleep abnormalities accompanied by distinct structural changes in the more widespread sleep neurocircuitry.
Quantum cyber-physical systems
Authors: Villalba-Diez Javier , González-Marcos Ana , Ordieres-Meré Joaquín
Published: May 2022

This paper aims to promote a quantum framework that analyzes Industry 4.0 cyber-physical systems more efficiently than traditional simulations used to represent integrated systems. The paper proposes a novel configuration of distributed quantum circuits in multilayered complex networks that enable the evaluation of industrial value creation chains. In particular, two different mechanisms for the integration of information between circuits operating at different layers are proposed, where their behavior is analyzed and compared with the classical conditional probability tables linked to the Bayesian networks. With the proposed method, both linear and nonlinear behaviors become possible while the complexity remains bounded. Applications in the case of Industry 4.0 are discussed when a component’s health is under consideration, where the effect of integration between different quantum cyber-physical digital twin models appears as a relevant implication.
Shrimp thrombospondin (TSP): presence of O-β1,4 N-acetylglucosamine polymers and its function in TSP chain association in egg extracellular matrix
Authors: Magerd Sirilug , Senarai Thanyaporn , Thongsum Orawan , Chawiwithaya Chidchanok , Sato Chihiro , Kitajima Ken , Weerachatyanukul Wattana , Asuvapongpatana Somluk , Surinlert Piyaporn
Published: May 2022

We characterized the existence of O-β(1,4)-GlcNAc polymers (β1,4GNP) that were anchored on the O-linked glycosylation sites of shrimp thrombospondin (pmTSP-II). There were five putative β1,4GNP linkages on the epithelial growth factor-like domain of pmTSP-II. Antibody against O-β-GlcNAc (CTD110.6) was used to prove the existence of linear and complex β1,4GNP. The antibody well reacted with linear chito-triose, -tetraose and -pentaose conjugated with phosphatidylethanolamine lipid. The immunoreactivity could also be detected with a complex β1,4GNP within pmTSP-II (at MW > 250 kDa). Upon denaturing the protein with SDS-PAGE buffer, the size of pmTSP-II was shifted to be 250 kDa, approximately 2.5 folds larger than the deduced molecular mass of pmTSP-II (110 kDa), suggesting additional association of pmTSP-II apart from its known disulfide bridging. This was confirmed by chitinase digestion on pmTSP-II protein leading to the subsequent smaller protein bands at 110–170 kDa in time- and concentration-dependent manners. These bands well reacted with CTD110.6 antibody and disappeared after extensive chitinase hydrolysis. Together, we believe that β1,4GNP on pmTSP-II serve the function in an inter-chain association to provide structural architecture of egg extracellular matrix, a novel function of pmTSP-II in reproductive biology.
Megasphaera elsdenii and Saccharomyces Cerevisiae as direct fed microbials during an in vitro acute ruminal acidosis challenge
Authors: Monteiro Hugo F. , Agustinho Bruna C. , Vinyard James R. , Harden Takoha , Bennett Sarah L. , Arce-Cordero Jose A. , Sarmikasoglou Efstathios , Ravelo Anay D. , Bahman Aneesa , So Sarong , Vieira Elis R. , Faciola Antonio P.
Published: May 2022

This study aimed to evaluate the effects of Saccharomyces cerevisiae and Megasphaera elsdenii as direct fed microbials (DFM) in beef cattle finishing diets to alleviate acute ruminal lactic acidosis in vitro. A dual-flow continuous culture system was used. Treatments were a Control, no DFM; YM1, S. cerevisiae and M. elsdenii strain 1; YM2, S. cerevisiae and M. elsdenii strain 2; and YMM, S. cerevisiae and half of the doses of M. elsdenii strain 1 and strain 2. Each DFM dose had a concentration of 1 × 108 CFU/mL. Four experimental periods lasted 11 days each. For the non-acidotic days (day 1–8), diet contained 50:50 forage to concentrate ratio. For the challenge days (day 9–11), diet contained 10:90 forage to concentrate ratio. Acute ruminal acidosis was successfully established. No differences in pH, d-, l-, or total lactate were observed among treatments. Propionic acid increased in treatments containing DFM. For N metabolism, the YMM treatment decreased protein degradation and microbial protein synthesis. No treatment effects were observed on NH3–N concentration; however, efficiency of N utilization by ruminal bacteria was greater than 80% during the challenge period and NH3–N concentration was reduced to approximately 2 mg/dL as the challenge progressed.
Near-infrared spectroscopy combined with pattern recognition algorithms to quickly classify raisins
Authors: Guo Jiawei , Chen Cheng , Chen Chen , Zuo Enguang , Dong Bingyu , Lv Xiaoyi , Yang Wenzhong
Published: May 2022

With the development of commodity economy, the emergence of fake and shoddy raisin has seriously harmed the interests of consumers and enterprises. To deal with this problem, a classification method combining near-infrared spectroscopy and pattern recognition algorithms were proposed for adulterated raisins. In this study, the experiment was performed by three kinds of raisins in Xinjiang (Hongxiangfei, Manaiti, Munage). After collecting and normalizing the spectral data, we compared the spectra of three kinds of raisins. Next the principal component analysis (PCA) was preformed to compress the dimension of the spectral data, and then classification models including support vector machine (SVM), multiscale fusion convolutional neural network (MCNN) and improved AlexNet were established to identify raisins. The accuracy of SVM, MCNN, and improved AlexNet is 100%, 92.83%, and 97.78% respectively. This study proves that near-infrared spectroscopy combined with pattern recognition is feasible for the raisin inspection.
A new non-human primate model of desiccating stress-induced dry eye disease
Authors: Gong Li , Guan Yilin , Cho WonKyung , Li Baowen , Pan Lingzhen , Yang Zhenyan , Wu Mingling , Yang Zunyuan , Chauhan Sunil K. , Zeng Wen
Published: May 2022

Dry eye disease (DED), a multifactorial ocular surface disease, is estimated to affect up to 34% of individuals over 50 years old. Although numerous animal models, including rodents and rabbits, have been developed to mimic the pathophysiologic mechanisms involved in dry eye, there is a lack of non-human primate (NHP) models, critical for translational drug studies. Here, we developed a novel desiccating stress-induced dry eye disease model using Rhesus macaque monkeys. The monkeys were housed in a controlled environment room for 21 to 36 days under humidity, temperature, and airflow regulation. Following desiccating stress, NHPs demonstrated clinical symptoms similar to those of humans, as shown by increased corneal fluorescein staining (CFS) and decreased tear-film breakup time (TFBUT). Moreover, corticosteroid treatment significantly reduced CFS scoring, restored TFBUT, and prevented upregulation of tear proinflammatory cytokines as observed in dry eye patients following steroid treatment. The close resemblance of clinical symptoms and treatment responses to those of human DED patients provides great translational value to the NHP model, which could serve as a clinically relevant animal model to study the efficacy of new potential treatments for DED.
A fusion approach to improve accuracy and estimate uncertainty in cuffless blood pressure monitoring
Authors: Landry Cederick , Peterson Sean D. , Arami Arash
Published: May 2022

A substantial barrier to the clinical adoption of cuffless blood pressure (BP) monitoring techniques is the lack of unified error standards and methods of estimating measurement uncertainty. This study proposes a fusion approach to improve accuracy and estimate prediction interval (PI) as a proxy for uncertainty for cuffless blood BP monitoring. BP was estimated during activities of daily living using three model architectures: nonlinear autoregressive models with exogenous inputs, feedforward neural network models, and pulse arrival time models. Multiple one-class support vector machine (OCSVM) models were trained to cluster data in terms of the percentage of outliers. New BP estimates were then assigned to a cluster using the OCSVMs hyperplanes, and the PIs were estimated using the BP error standard deviation associated with different clusters. The OCSVM was used to estimate the PI for the three BP models. The three BP estimations from the models were fused using the covariance intersection fusion algorithm, which improved BP and PI estimates in comparison with individual model precision by up to 24%. The employed model fusion shows promise in estimating BP and PI for potential clinical uses. The PI indicates that about 71%, 64%, and 29% of the data collected from sitting, standing, and walking can result in high-quality BP estimates. Our PI estimator offers an effective uncertainty metric to quantify the quality of BP estimates and can minimize the risk of false diagnosis.
Serial and parallel convolutional neural network schemes for NFDM signals
Authors: Zhang Wen Qi , Chan Terence H. , Vahid Shahraam Afshar
Published: May 2022

Two conceptual convolutional neural network (CNN) schemes are proposed, developed and analysed for directly decoding nonlinear frequency division multiplexing (NFDM) signals with hardware implementation taken into consideration. A serial network scheme with a small network size is designed for small user applications, and a parallel network scheme with high speed is designed for places such as data centres. The work aimed at showing the potential of using CNN for practical NFDM-based fibre optic communication. In the numerical demonstrations, the serial network only occupies 0.5 MB of memory space while the parallel network occupies 128 MB of memory but allows parallel computing. Both network schemes were trained with simulated data and reached more than 99.9% accuracy.
Implications for ozone control by understanding the survivor bias in observed ozone-volatile organic compounds system
Authors: Wang Zhenyu , Shi Zongbo , Wang Feng , Liang Weiqing , Shi Guoliang , Wang Weichao , Chen Da , Liang Danni , Feng Yinchang , Russell Armistead G.
Published: May 2022

Tropospheric ozone (O3) affects Earth’s climate and human health. Volatile organic compounds (VOCs), major contributors to O3 formation, are of particular interest. Generally, the measured concentrations of VOCs (M-VOCs) and O3 show nonlinear or even opposite time serial-trend. We attributed the phenomenon to survivor bias: lack of insight of the photochemically consumed VOCs (C-VOCs) which emitted from sources to ambient and devote to forming O3, while excessive concern on the measured VOCs (M-VOCs) at observation site. Both observational and model results provide evidence that C-VOCs are the key to O3 formation. We proposed an improved model to quantify the source contributions of C-VOCs (biogenic emissions, gasoline evaporation, industry, etc.) and their impacts on the formation of O3, successfully avoiding the misidentification of dominant VOCs sources originated from the survivor bias in observational data. The survivor bias found in this study highlights that focusing of M-VOCs directly is insufficient and demonstrates the necessity of capture the sources of C-VOCs which contribute to O3 formation.
Systems-wide analysis revealed shared and unique responses to moderate and acute high temperatures in the green alga Chlamydomonas reinhardtii
Authors: Zhang Ningning , Mattoon Erin M. , McHargue Will , Venn Benedikt , Zimmer David , Pecani Kresti , Jeong Jooyeon , Anderson Cheyenne M. , Chen Chen , Berry Jeffrey C. , Xia Ming , Tzeng Shin-Cheng , Becker Eric , Pazouki Leila , Evans Bradley , Cross Fred , Cheng Jianlin , Czymmek Kirk J. , Schroda Michael , Mühlhaus Timo , Zhang Ru
Published: May 2022

Different intensities of high temperatures affect the growth of photosynthetic cells in nature. To elucidate the underlying mechanisms, we cultivated the unicellular green algaChlamydomonas reinhardtiiunder highly controlled photobioreactor conditions and revealed systems-wide shared and unique responses to 24-hour moderate (35°C) and acute (40°C) high temperatures and subsequent recovery at 25°C. We identified previously overlooked unique elements in response to moderate high temperature. Heat at 35°C transiently arrested the cell cycle followed by partial synchronization, up-regulated transcripts/proteins involved in gluconeogenesis/glyoxylate-cycle for carbon uptake and promoted growth. But 40°C disrupted cell division and growth. Both high temperatures induced photoprotection, while 40°C distorted thylakoid/pyrenoid ultrastructure, affected the carbon concentrating mechanism, and decreased photosynthetic efficiency. We demonstrated increased transcript/protein correlation during both heat treatments and hypothesize reduced post-transcriptional regulation during heat may help efficiently coordinate thermotolerance mechanisms. During recovery after both heat treatments, especially 40°C, transcripts/proteins related to DNA synthesis increased while those involved in photosynthetic light reactions decreased. We propose down-regulating photosynthetic light reactions during DNA replication benefits cell cycle resumption by reducing ROS production. Our results provide potential targets to increase thermotolerance in algae and crops.
Cargo receptor Surf4 regulates endoplasmic reticulum export of proinsulin in pancreatic β-cells
Authors: Saegusa Keiko , Matsunaga Kohichi , Maeda Miharu , Saito Kota , Izumi Tetsuro , Sato Ken
Published: May 2022

Insulin is an essential peptide hormone that maintains blood glucose levels. Although the mechanisms underlying insulin exocytosis have been investigated, the mechanism of proinsulin export from the endoplasmic reticulum (ER) remains unclear. Here, we demonstrated that Surf4, a cargo receptor homolog, regulates the ER export of proinsulin via its recruitment to ER exit sites (ERES). Under high-glucose conditions, Surf4 expression was upregulated, and Surf4 proteins mainly localized to the ER at a steady state and accumulated in the ERES, along with proinsulin in rat insulinoma INS-1 cells.Surf4-knockdown resulted in proinsulin retention in the ER and decreased the levels of mature insulin in secretory granules, thereby significantly reducing insulin secretion. Surf4 forms an oligomer and can physically interact with proinsulin and Sec12, essential for COPII vesicle formation. Our findings suggest that Surf4 interacts with proinsulin and delivers it into COPII vesicles for ER export in co-operation with Sec12 and COPII.