bluuebunny/crossref_metadata_2025_split huggingface dataset:
No interface energy barrier and increased surface pinning in low temperature baked niobium
Authors: Turner Daniel Andrew , Burt Graeme , Junginger Tobias 
Published: April 2022

AbstractSuperconducting Radio-Frequency cavities are currently made out of niobium. Niobium cavities are limited by the magnetic field on the cavity walls due to the entry of vortices at the field of first vortex penetration, H$$_{vp}$$

vp

. Low temperature baking in vacuum or low pressure gas atmosphere removes the strong decrease of the quality factor with accelerating gradient (high field Q-slope). Some cavities reach surface magnetic field above the lower critical field H$$_{c1}$$

c
1

. One hypothesis for this performance increase is that the outer layer affected by the treatments acts as a barrier for vortex penetration (effective bilayer). Using a vibrating sample magnetometer the field of first flux penetration (H$$_{vp}$$

vp

) was measured for Nb ellipsoids with various low temperature treatments. All H$$_{vp}$$

vp

values were found to be consistent with the lower critical field, H$$_{c1}$$

c
1

, as predicted for clean niobium. This led to the conclusion that a metastable flux free state above H$$_{c1}$$

c
1

cannot be observed in DC magnetometry for low temperature baked niobium unlike for bilayers consisting of two superconductors as previously published. The effect of flux pinning differed significantly between treatments, suggesting that the high field Q-slope mitigation might be related to vortex pinning in the surface of the cavities.
Modelling shifts in social opinion through an application of classical physics
Authors: Zachary Daniel S. 
Published: March 2022

AbstractThis paper explores the abstraction of classical physics and applies several metrics that explore the evolution of social opinion. These metrics include an abstraction of Newtonian kinematics: mass, position, speed, acceleration, and Newtonian dynamics, an abstraction of force. Poll data is fit to a 2nd-order polynomial and a logistic function. These fits are used to understand the acceleration of opinion shift, and we explore recent social, cultural, and environmental trends, such as views on global climate change. We compare our results with the evolution of communication technologies and time spent on devices over the past 120 years. We show that the model connects the evolution in opinion with an abstraction of a Galilean concept: acceleration is independent of mass. Finally, we discuss the model of social polarization and the non-linear effect of media such as echo chambers.
Search strategy analysis of Tg4-42 Alzheimer Mice in the Morris Water Maze reveals early spatial navigation deficits
Authors: Curdt Nadine , Schmitt Franziska W. , Bouter Caroline , Iseni Trendelina , Weile Hanna C. , Altunok Berfin , Beindorff Nicola , Bayer Thomas A. , Cooke Matthew B. , Bouter Yvonne 
Published: March 2022

AbstractSpatial disorientation is one of the earliest symptoms in Alzheimer’s disease and allocentric deficits can already be detected in the asymptomatic preclinical stages of the disease. The Morris Water Maze (MWM) is used to study spatial learning in rodent models. Here we investigated the spatial memory of female 3, 7 and 12 month-old Alzheimer Tg4-42 mice in comparison to wild-type control animals. Conventional behavior analysis of escape latencies and quadrant preference revealed spatial memory and reference memory deficits in female 7 and 12 month-old Tg4-42 mice. In contrast, conventional analysis of the MWM indicated an intact spatial memory in 3 month-old Tg4-42 mice. However, a detailed analysis of the swimming strategies demonstrated allocentric-specific memory deficits in 3 month-old Tg4-42 mice before the onset of severe memory deficits. Furthermore, we could show that the spatial reference memory deficits in aged Tg4-42 animals are caused by the lack of allocentric and spatial strategies. Analyzing search strategies in the MWM allows to differentiate between hippocampus-dependent allocentric and hippocampus-independent egocentric search strategies. The spatial navigation impairments in young Tg4-42 mice are well in line with the hypometabolism and synaptic deficits in the hippocampus. Therefore, analyzing search strategies in the Tg4-42 model can be a powerful tool for preclinical drug testing and identifying early therapeutic successes.
Strain-resolved analysis in a randomized trial of antibiotic pretreatment and maintenance dose delivery mode with fecal microbiota transplant for ulcerative colitis
Authors: Smith Byron J. , Piceno Yvette , Zydek Martin , Zhang Bing , Syriani Lara Aboud , Terdiman Jonathan P. , Kassam Zain , Ma Averil , Lynch Susan V. , Pollard Katherine S. , El-Nachef Najwa 
Published: April 2022

AbstractFecal microbiota transplant is a promising therapy for ulcerative colitis. Parameters maximizing effectiveness and tolerability are not yet clear, and it is not known how import the transmission of donor microbes to patients is. Here (clinicaltrails.gov: NCT03006809) we have tested the effects of antibiotic pretreatment and compared two modes of maintenance dose delivery, capsules versus enema, in a randomized, pilot, open-label, 2 × 2 factorial design with 22 patients analyzed with mild to moderate UC. Clinically, the treatment was well-tolerated with favorable safety profile. Of patients who received antibiotic pretreatment, 6 of 11 experienced remission after 6 weeks of treatment, versus 2 of 11 non-pretreated patients (log odds ratio: 1.69, 95% confidence interval: −0.25 to 3.62). No significant differences were found between maintenance dosing via capsules versus enema. In exploratory analyses, microbiome turnover at both the species and strain levels was extensive and significantly more pronounced in the pretreated patients. Associations were also revealed between taxonomic turnover and changes in the composition of primary and secondary bile acids. Together these findings suggest that antibiotic pretreatment contributes to microbiome engraftment and possibly clinical effectiveness, and validate longitudinal strain tracking as a powerful way to monitor the dynamics and impact of microbiota transfer.
Lattice Boltzmann-based numerical analysis of nanofluid natural convection in an inclined cavity subject to multiphysics fields
Authors: Ibrahim Muhammad , Berrouk Abdallah S. , Saeed Tareq , Algehyne Ebrahem A. , Ali Vakkar 
Published: April 2022

AbstractThis research conducts a study of natural convection heat transfer (NCHT) in a nanofluid under a magnetic field (MF). The nanofluid is in a cavity inclined at an angle of 45°. The MF can take different angles between 0° and 90°. Radiative heat transfer is present in the cavity in volumetric form. There are two hot semicircles, similar to two half-pipes, on the bottom wall. The top wall is kept cold. The side walls and parts of the bottom wall, except the pipes, have been insulated. The lattice Boltzmann method has been used for the simulation. The studied parameters are the Rayleigh number (in the range 103–106), magnetic field angle, radiation parameter (in the range 0–2), and nanoparticle volume fraction (in the range 0–5%). The generated entropy has been studied as the NCHT. The results indicate that adding nanoparticles improves heat transfer rate (HTR). Moreover, the addition of volumetric radiation to the cavity enhances the Nusselt number by 54% and the generated entropy by 12.5%. With an augmentation in the MF angle from 0° to 90°, HTR decreases and this decrease is observed mostly at higher Rayleigh numbers. An augmentation in the Ra increases NCHT and entropy generation. Indeed, a rise in the Ra from 103 to 106 increases HTR by almost sixfold.
Tumor-suppressive role of Smad ubiquitination regulatory factor 2 in patients with colorectal cancer
Authors: Sato Nami , Sakai Nozomu , Furukawa Katsunori , Takayashiki Tsukasa , Kuboki Satoshi , Takano Shigetsugu , Ohira Gaku , Miyauchi Hideaki , Matsubara Hisahiro , Ohtsuka Masayuki 
Published: March 2022

AbstractSmad ubiquitination regulatory factor 2 (Smurf2) plays various roles in cancer progression. However, the correlation between Smurf2 and clinical outcomes has not been determined in patients diagnosed with colorectal cancer and colorectal liver metastases. We analyzed 66 patients with colorectal cancer who developed liver metastases. Smurf2 expression was assessed using immunohistochemical analysis of primary and metastatic liver tumors. High Smurf2 expression in both primary and metastatic tumors was significantly associated with longer overall survival time and time to surgical failure. Multivariate analyses revealed that low Smurf2 expression in primary tumors was an independent predictor of poor prognosis. In vitro experiments using colon cancer cell lines demonstrated that short interfering RNA knockdown of Smurf2 increased cell migration and tumor sphere formation. Western blot analyses revealed that Smurf2 knockdown increased the protein expression of epithelial cell adhesion molecule (EpCAM). Thus, in summary, high Smurf2 expression in cancer cells was found to be an independent predictor of better prognosis in patients with primary colorectal cancer and consequent liver metastases. The tumor-suppressive role of Smurf2 was found to be associated with cell migration and EpCAM expression; hence, Smurf2 can be considered a positive biomarker of cancer stem cell-like properties.
SARS-CoV-2 spike protein induces cognitive deficit and anxiety-like behavior in mouse via non-cell autonomous hippocampal neuronal death
Authors: Oh Junyoung , Cho Woo-Hyun , Barcelon Ellane , Kim Kwang Hwan , Hong Jinpyo , Lee Sung Joong 
Published: March 2022

AbstractSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is accompanied by chronic neurological sequelae such as cognitive decline and mood disorder, but the underlying mechanisms have not yet been elucidated. We explored the possibility that the brain-infiltrating SARS-CoV-2 spike protein contributes to the development of neurological symptoms observed in COVID-19 patients in this study. Our behavioral study showed that administration of SARS-CoV-2 spike protein S1 subunit (S1 protein) to mouse hippocampus induced cognitive deficit and anxiety-like behavior in vivo. These neurological symptoms were accompanied by neuronal cell death in the dorsal and ventral hippocampus as well as glial cell activation. Interestingly, the S1 protein did not directly induce hippocampal cell death in vitro. Rather, it exerted neurotoxicity via glial cell activation, partially through interleukin-1β induction. In conclusion, our data suggest a novel pathogenic mechanism for the COVID-19-associated neurological symptoms that involves glia activation and non-cell autonomous hippocampal neuronal death by the brain-infiltrating S1 protein.
Listening to bluetooth beacons for epidemic risk mitigation
Authors: Barthe Gilles , Viti Roberta De , Druschel Peter , Garg Deepak , Gomez-Rodriguez Manuel , Ingo Pierfrancesco , Kremer Heiner , Lentz Matthew , Lorch Lars , Mehta Aastha , Schölkopf Bernhard 
Published: April 2022

AbstractThe ongoing COVID-19 pandemic let to efforts to develop and deploy digital contact tracing systems to expedite contact tracing and risk notification. Unfortunately, the success of these systems has been limited, partly owing to poor interoperability with manual contact tracing, low adoption rates, and a societally sensitive trade-off between utility and privacy. In this work, we introduce a new privacy-preserving and inclusive system for epidemic risk assessment and notification that aims to address these limitations. Rather than capturing pairwise encounters between user devices as done by existing systems, our system captures encounters between user devices and beacons placed in strategic locations where infection clusters may originate. Epidemiological simulations using an agent-based model demonstrate that, by utilizing location and environmental information and interoperating with manual contact tracing, our system can increase the accuracy of contact tracing actions and may help reduce epidemic spread already at low adoption.
Prediction of dengue fever outbreaks using climate variability and Markov chain Monte Carlo techniques in a stochastic susceptible-infected-removed model
Authors: Martheswaran Tarun Kumar , Hamdi Hamida , Al-Barty Amal , Zaid Abeer Abu , Das Biswadeep 
Published: March 2022

AbstractThe recent increase in the global incidence of dengue fever resulted in over 2.7 million cases in Latin America and many cases in Southeast Asia and has warranted the development and application of early warning systems (EWS) for futuristic outbreak prediction. EWS pertaining to dengue outbreaks is imperative; given the fact that dengue is linked to environmental factors owing to its dominance in the tropics. Prediction is an integral part of EWS, which is dependent on several factors, in particular, climate, geography, and environmental factors. In this study, we explore the role of increased susceptibility to a DENV serotype and climate variability in developing novel predictive models by analyzing RT-PCR and DENV-IgM confirmed cases in Singapore and Honduras, which reported high dengue incidence in 2019 and 2020, respectively. A random-sampling-based susceptible-infected-removed (SIR) model was used to obtain estimates of the susceptible fraction for modeling the dengue epidemic, in addition to the Bayesian Markov Chain Monte Carlo (MCMC) technique that was used to fit the model to Singapore and Honduras case report data from 2012 to 2020. Regression techniques were used to implement climate variability in two methods: a climate-based model, based on individual climate variables, and a seasonal model, based on trigonometrically varying transmission rates. The seasonal model accounted for 98.5% and 92.8% of the variance in case count in the 2020 Singapore and 2019 Honduras outbreaks, respectively. The climate model accounted for 75.3% and 68.3% of the variance in Singapore and Honduras outbreaks respectively, besides accounting for 75.4% of the variance in the major 2013 Singapore outbreak, 71.5% of the variance in the 2019 Singapore outbreak, and over 70% of the variance in 2015 and 2016 Honduras outbreaks. The seasonal model accounted for 14.2% and 83.1% of the variance in the 2013 and 2019 Singapore outbreaks, respectively, in addition to 91% and 59.5% of the variance in the 2015 and 2016 Honduras outbreaks, respectively. Autocorrelation lag tests showed that the climate model exhibited better prediction dynamics for Singapore outbreaks during the dry season from May to August and in the rainy season from June to October in Honduras. After incorporation of susceptible fractions, the seasonal model exhibited higher accuracy in predicting outbreaks of higher case magnitude, including those of the 2019–2020 dengue epidemic, in comparison to the climate model, which was more accurate in outbreaks of smaller magnitude. Such modeling studies could be further performed in various outbreaks, such as the ongoing COVID-19 pandemic to understand the outbreak dynamics and predict the occurrence of future outbreaks.
K-clique percolation in free association networks and the possible mechanism behind the $$7 \pm 2$$ law
Authors: Valba Olga , Gorsky Alexander 
Published: April 2022

AbstractIt is important to reveal the mechanisms of propagation in different cognitive networks. In this study, we discuss the k-clique percolation phenomenon as related to the free association networks including the English Small World of Words project (SWOW-EN). We compared different semantic networks and networks of free associations for various languages. Surprisingly, k-clique percolation for all $$k<k_c=$$

k
<

k
c

=

6–7 is possible on free association networks of different languages. Our analysis suggests new universality patterns for a community organization of free association networks. We conjecture that our result can provide a qualitative explanation of Miller’s $$7\pm 2$$

7
±
2

rule for the capacity limit of working memory. A new model of network evolution extending the preferential attachment is suggested, providing the observed value of $$k_c$$

k
c

.
Comparative genomic analysis of vertebrate mitochondrial reveals a differential of rearrangements rate between taxonomic class
Authors: Montaña-Lozano Paula , Moreno-Carmona Manuela , Ochoa-Capera Mauricio , Medina Natalia S. , Boore Jeffrey L. , Prada Carlos F. 
Published: March 2022

AbstractVertebrate mitochondrial genomes have been extensively studied for genetic and evolutionary purposes, these are normally believed to be extremely conserved, however, different cases of gene rearrangements have been reported. To verify the level of rearrangement and the mitogenome evolution, we performed a comparative genomic analysis of the 2831 vertebrate mitochondrial genomes representing 12 classes available in the NCBI database. Using a combination of bioinformatics methods, we determined there is a high number of errors in the annotation of mitochondrial genes, especially in tRNAs. We determined there is a large variation in the proportion of rearrangements per gene and per taxonomic class, with higher values observed in Actinopteri, Amphibia and Reptilia. We highlight that these are results for currently available vertebrate sequences, so an increase in sequence representativeness in some groups may alter the rearrangement rates, so in a few years it would be interesting to see if these rates are maintained or altered with the new mitogenome sequences. In addition, within each vertebrate class, different patterns in rearrangement proportion with distinct hotspots in the mitochondrial genome were found. We also determined that there are eleven convergence events in gene rearrangement, nine of which are new reports to the scientific community.
Hybrid leader based optimization: a new stochastic optimization algorithm for solving optimization applications
Authors: Dehghani Mohammad , Trojovský Pavel 
Published: April 2022

AbstractIn this paper, a new optimization algorithm called hybrid leader-based optimization (HLBO) is introduced that is applicable in optimization challenges. The main idea of HLBO is to guide the algorithm population under the guidance of a hybrid leader. The stages of HLBO are modeled mathematically in two phases of exploration and exploitation. The efficiency of HLBO in optimization is tested by finding solutions to twenty-three standard benchmark functions of different types of unimodal and multimodal. The optimization results of unimodal functions indicate the high exploitation ability of HLBO in local search for better convergence to global optimal, while the optimization results of multimodal functions show the high exploration ability of HLBO in global search to accurately scan different areas of search space. In addition, the performance of HLBO on solving IEEE CEC 2017 benchmark functions including thirty objective functions is evaluated. The optimization results show the efficiency of HLBO in handling complex objective functions. The quality of the results obtained from HLBO is compared with the results of ten well-known algorithms. The simulation results show the superiority of HLBO in convergence to the global solution as well as the passage of optimally localized areas of the search space compared to ten competing algorithms. In addition, the implementation of HLBO on four engineering design issues demonstrates the applicability of HLBO in real-world problem solving.
MRI assessment of glutamine uptake correlates with the distribution of glutamine transporters and cancer stem cell markers
Authors: Seo Yoojeong , Kang Joyeon , Kim Tae Il , Joo Chan Gyu 
Published: April 2022

AbstractGlutamine provides carbon and nitrogen for macromolecular synthesis and participates in adenosine triphosphate (ATP) generation, anabolic metabolism, redox homeostasis, cell signaling, and cancer stem cell (CSC) metabolism. New treatment strategies targeting glutamine metabolism in cancer have emerged recently. We previously reported the magnetic resonance imaging (MRI) assessment of glutamine uptake by tumors and activated glutamine metabolism in CSC. In the present study, using MRI, we determined the correlation between glutamine uptake and the distribution of glutamine transporters, namely ASCT2 and SLC38A2 (SNAT2), glutaminase (GLS), and CSC markers, such as CD44 and CD166, in a mouse xenograft model of HT29 human colorectal cancer cells. MRI data revealed an obvious change in intensity following glutamine administration. Immunohistochemistry (IHC) results indicated that ASCT2 staining was stronger in regions that exhibited high glutamine uptake (p = 0.0079). Significant differences were found in the IHC staining intensities of SNAT2, GLS, and CSC markers in the areas of high and low glutamine uptake (p = 0.0079, p = 0.0159 and p = 0.0079, respectively). We also investigated the effect of an ASCT2 inhibitor on the uptake of glutamine using MRI. A statistically significant difference in the initial glutamine uptake was found after ASCT2 inhibitor administration. To conclude, glutamine uptake is positively correlated with the distribution of ASCT2 and certain CSC markers.
Extending conventional surface roughness ISO parameters using topological data analysis for shot peened surfaces
Authors: Senge Jan F. , Astaraee Asghar Heydari , Dłotko Pawel , Bagherifard Sara , Bosbach Wolfram A. 
Published: April 2022

AbstractThe roughness of material surfaces is of greatest relevance for applications. These include wear, friction, fatigue, cytocompatibility, or corrosion resistance. Today’s descriptors of the International Organization for Standardization show varying performance in discriminating surface roughness patterns. We introduce here a set of surface parameters which are extracted from the appropriate persistence diagram with enhanced discrimination power. Using the finite element method implemented in Abaqus Explicit 2019, we modelled American Rolling Mill Company pure iron specimens (volume 1.5 × 1.5 × 1.0 mm3) exposed to a shot peening procedure. Surface roughness evaluation after each shot impact and single indents were controlled numerically. Conventional and persistence-based evaluation is implemented in Python code and available as open access supplement. Topological techniques prove helpful in the comparison of different shot peened surface samples. Conventional surface area roughness parameters might struggle in distinguishing different shot peening surface topographies, in particular for coverage values > 69%. Above that range, the calculation of conventional parameters leads to overlapping descriptor values. In contrast, lifetime entropy of persistence diagrams and Betti curves provide novel, discriminative one-dimensional descriptors at all coverage ranges. We compare how conventional parameters and persistence parameters describe surface roughness. Conventional parameters are outperformed. These results highlight how topological techniques might be a promising extension of surface roughness methods.
Pattern synthesis of linear and ring arrays with minimum number of elements using FFT and Bessel transformation
Authors: Boozari Mahdi , Khalaj-Amirhosseini Mohammad 
Published: March 2022

AbstractIn antenna engineering, to reduce the final cost of array design, it is often necessary to design an array with the minimum number of elements. So, proper selection of the number of array elements and the location of the elements are two important factors in array design. In this work, a novel analytical approach for designing an array with optimal parameters is described. The Nyquist–Shannon sampling theorem is used to determine the number of array elements and the distance between them. The array's excitation coefficients are then determined using the recursive least square approach and the Bessel transform of the array factor. It is also demonstrated that the introduced procedure can be extended to include the concentric ring arrays. Several practical arrays are evaluated to verify the performance of the suggested approach. The results show that the introduced approach is a good candidate for designing practical arrays with acceptable accuracy.