bluuebunny/crossref_metadata_2025 huggingface dataset:
The North American Cordillera during the Mesozoic to Paleogene: Selected questions and controversies
Authors: Busby C.J. , Pavlis T.L. , Roeske S.M. , Tikoff B.
Published: November 2022

The North American Cordillera experienced significant and varied tectonism during the Triassic to Paleogene time interval. Herein, we highlight selected questions and controversies that remain at this time. First, we describe two tectonic processes that have hindered interpretations of the evolution of the orogen: (1) strike-slip systems with poorly resolved displacement; and (2) the closing of ocean basins of uncertain size, origin, and mechanism of closure. Next, we divide the orogen into southern, central, and northern segments to discuss selected controversies relevant to each area. Controversies/questions from the southern segment include: What is the origin of cryptic transform faults (Mojave-Sonora megashear vs. California Coahuila transform fault)? Is the Nazas an arc or a continental rift province? What is the Arperos basin (Guerrero terrane), and did its closure produce the Mexican fold-and-thrust belt? How may inherited basement control patterns of deformation during subduction? Controversies/questions from the central segment include: Can steeply dipping mantle anomalies be reconciled with geology? What caused high-flux events in the Sierra Nevada batholith? What is the origin of the North American Cordilleran anatectic belt? How does the Idaho segment of the orogen connect to the north and south? Controversies/questions from the northern segment include: How do we solve the Baja–British Columbia problem? How big and what kind of basin was the Early Cretaceous lost ocean basin? What connections can be found between Arctic geology and Cordilleran geology in Alaska? How do the Cretaceous tectonic events in the Arctic and northern Alaska connect with the Cordilleran Cretaceous events? What caused the Eocene tectonic transitions seen throughout the northern Cordillera? By addressing these questions along the length of the Cordillera, we hope to highlight common problems and facilitate productive discussion on the development of these features.
Climatic influence on the expression of strike-slip faulting
Authors: Reitman Nadine G. , Klinger Yann , Briggs Richard W. , Gold Ryan D.
Published: November 2022

Earthquakes on strike-slip faults are preserved in the geomorphic record by offset land-forms that span a range of displacements, from small offsets created in the most recent earthquake (MRE) to large offsets that record cumulative slip from multiple prior events. An exponential decay in the number of large cumulative offsets has been observed on many faults, and a leading hypothesis is that climate controls the rate of decay. We present offset measurements compiled from 31 studies of strike-slip faults with evidence of multiple paleoearthquakes and corresponding climatic and tectonic information to test this hypothesis. Both the global compilation and numerical landscape evolution modeling reveal that the decay rate in large offsets is negatively correlated with mean annual precipitation. Faults in dry regions with high drainage density more commonly preserve small MRE offsets, and faults in wet regions with lower drainage density more commonly preserve a mix of small MRE and large cumulative offsets. Geomorphology of faults in different climates supports this result and illustrates precipitation's effect on the development and preservation of off-set channels. Our findings imply that current and past climate affect how displacement on strike-slip faults is recorded and interpreted to inform earthquake history.
Spindle cell sarcomatoid tumour of the trachea: a rare primary malignant tumour
Authors: Moore Emily , Khosla Shivun , Jogai Sanjay , Derbyshire Stephen
Published: November 2022

Spindle cell carcinoma is a subtype of sarcomatoid carcinoma, which has previously been described in various anatomical locations, though rarely in the trachea.

We present the case of a woman in her 70s who presented with a sore throat and stridor. Fibreoptic nasendoscopy demonstrated a tracheal mass occupying 80% of the airway from the cricoid cartilage to the third tracheal ring, infiltrating the thyroid gland. Subsequent CT demonstrated pulmonary emboli and vertebral metastasis. Biopsy of the infiltrated thyroid confirmed the diagnosis of spindle cell carcinoma. The length of the tumour and metastasis at presentation made this surgically unresectable, and she was referred for a palliative stent but died after an acute deterioration.

This pathology has been reported only five times previously in the literature, with management strategies varying greatly between patients. Primary tracheal tumours are difficult to manage as, due to their rarity, there are no clear guidelines.
Hilar tuberculosis versus Klatskin tumour: a diagnostic challenge
Authors: Biswas Jyotirmoy , Rathna Roger B , Dhali Arkadeep , Ray Sukanta
Published: November 2022

Hepatobiliary tuberculosis is a rare condition causing obstructive jaundice either by enlarged lymph nodes around the bile ducts or involvement of biliary epithelium by the tuberculous process. Since a tissue diagnosis is not mandatory to proceed with the resection or initiation of a liver transplant protocol, benign lesions are occasionally misdiagnosed as hilar cholangiocarcinoma. Here, we present a case of hepatobiliary tuberculosis which presented as obstructive jaundice due to hilar obstruction. The mass causing the obstruction was then later found to be a pseudotumour, typical of tuberculosis. This diagnosis meant that extensive surgical resection as a protocol for cholangiocarcinoma was avoided. The patient recovered completely after a course of antitubercular therapy.
Protecting the stars of tomorrow: do international cardiovascular preparticipation screening policies account for the paediatric athlete? A systematic review and quality appraisal
Authors: Riding Nathan R , Dorobantu Dan-Mihai , Williams Craig A , Stuart Graham , Fritsch Peter , Wilson Mathew G , Mossialos Elias , Pieles Guido
Published: November 2022

Objective

(1) Identify and review current policies for the cardiovascular screening of athletes to assess their applicability to the paediatric population and (2) evaluate the quality of these policy documents using the Appraisal of Guidelines for Research & Evaluation II (AGREE II) tool.

Design

Systematic review and quality appraisal of policy documents.

Data sources

A systematic search of PubMed, MEDLINE, Scopus, Web of Science, SportDiscus and CINAHL.

Eligibility criteria for selecting studies

An article was included if it was a policy/position statement/guideline/consensus or recommendation paper relating to athletes and cardiovascular preparticipation screening.

Results and summary

Of the 1630 articles screened, 13 met the inclusion criteria. Relevance to paediatric athletes was found to be high in 3 (23%), moderate in 6 (46%) and low in 4 (31%), and only 2 provide tailored guidance for the athlete aged 12–18 years. A median 5 related citations per policy investigated solely paediatric athletes, with study designs most commonly being retrospective (72%). AGREEII overall quality scores ranged from 25% to 92%, with a median of 75%. The lowest scoring domains were rigour of development; (median 32%) stakeholder involvement (median 47%) and Applicability (median 52%).

Conclusion

Cardiac screening policies for athletes predominantly focus on adults, with few providing specific recommendations for paediatric athletes. The overall quality of the policies was moderate, with more recent documents scoring higher. Future research is needed in paediatric athletes to inform and develop cardiac screening guidelines, to improve the cardiac care of youth athletes.
Phase III, randomised, double-blind, placebo-controlled trial of Neuroaspis plp10 as an adjuvant treatment for relapsing multiple sclerosis: the MINERAL Study
Authors: Pantzaris Marios C , Bakirtzis Christos , Grigoriadis Nikolaos , Hadjigeorgiou Georgios , Dardiotis Efthimos , Loucaides George , Ntzani Evangelia , Markozannes Georgios , Omorfos Savvas , Valsasina Paola , Messina Roberta , Preziosa Paolo , Rocca Maria A , Patrikios Ioannis
Published: November 2022

Objectives

To assess the effectiveness of Neuroaspis plp10 nutritional supplement when added to interferon (IFN)-β treatment in patients with relapsing-remitting multiple sclerosis (RRMS).

Design

A 30-month phase III multicentre, randomised, double-blind, placebo-controlled trial. Randomisation stratified by centre using a computer-generated procedure with Neuroaspis plp10 versus placebo in 1:1 ratio. The first 6 months were used as both the pre-entry and normalisation period.

Setting

3 teaching hospitals in Greece and 1 Neurology Institute in Cyprus.

Participants

61 patients with RRMS on IFN-β were randomly assigned to receive Neuroaspis plp10 (n=32) or placebo (n=29), 20 mL, orally, once daily, for 30 months.

Intervention

Neuroaspis plp10, a cocktail mixture, containing specific PUFA (12 150 mg) and γ-tocopherol (760 mg) versus virgin olive oil (placebo).

Main outcome measure

The primary end point was the annual relapse rate (ARR) whereas the secondary ones were the rate of sustained progression of disability, as measured by the Expanded Disability Status Scale (EDSS) and the brain T2 and gadolinium-enhancing lesions, at 2 years.

Results

For the intention-to-treat analyses Neuroaspis plp10 significantly reduced the ARR by 80%, (RRR, 0.20; 95% CI: 0.09 to 0.45; p=0.0001) and the risk of sustained progression of disability by 73% (HR, 0.27; 95% CI: 0.09 to 0.83; p=0.022) versus placebo, at 2 years. The number of T1 gadolinium-enhancing lesions and the number of new/enlarged T2-hyperintense lesions were significantly reduced (p=0.01 and p<0.0001, respectively). Both T1-enhancing and new/enlarging T2-hyperintense lesions were significantly reduced (p=0.05 and p<0.0001, respectively). No significant adverse events were reported.

Conclusions

Neuroaspis plp10 added to IFN-β was significantly more effective than IFN-β alone in patients with RRMS.

Trial registration number

ISRCTN06166891.
Mer-tyrosine kinase: a novel susceptibility gene for SLE related end-stage renal disease
Authors: Yavuz Sule , Pucholt Pascal , Sandling Johanna K , Bianchi Matteo , Leonard Dag , Bolin Karin , Imgenberg-Kreuz Juliana , Eloranta Maija-Leena , Kozyrev Sergey V , Lanata Cristina M , Jönsen Andreas , Bengtsson Anders A , Sjöwall Christopher , Svenungsson Elisabet , Gunnarsson Iva , Rantapää-Dahlqvist Solbritt ,   ImmunoArray Development Consortium,   DISSECT Consortium, Nititham Joanne , Criswell Lindsey A , Lindblad-Toh Kerstin , Rönnblom Lars
Published: November 2022

Objective

Lupus nephritis (LN) is a common and severe manifestation of SLE. The genetic risk for nephritis and progression to end-stage renal disease (ESRD) in patients with LN remains unclear. Herein, we aimed to identify novel genetic associations with LN, focusing on subphenotypes and ESRD.

Methods

We analysed genomic data on 958 patients with SLE (discovery cohort: LN=338) with targeted sequencing data from 1832 immunological pathway genes. We used an independent multiethnic cohort comprising 1226 patients with SLE (LN=603) as a replication dataset. Detailed functional annotation and functional epigenomic enrichment analyses were applied to predict functional effects of the candidate variants.

Results

A genetic variant (rs56097910) within theMERTKgene was associated with ESRD in both cohorts, meta-analysis OR=5.4 (2.8 to 10.6); p=1.0×10-6. We observed decreased methylation levels in peripheral blood cells from SLE patients with ESRD, compared with patients without renal SLE (p=2.7×10-4), at one CpG site (cg16333401) in close vicinity to the transcription start site ofMERTKand located in a DNAse hypersensitivity region in T and B cells. Rs56097910 is linked to alteredMERTKexpression in kidney tissue in public eQTL databases. Two loci were replicated for association with proliferative LN:PRDM1(rs6924535, pmeta=1.6×10-5, OR=0.58) andAPOA1BP(NAXE) (rs942960, pmeta=1.2×10-5, OR=2.64).

Conclusion

We identified a novel genetic risk locus,MERTK, associated with SLE-ESRD using the data from two large SLE cohorts. Through DNA methylation analysis and functional annotation, we showed that the risk could be mediated through regulation of gene expression. Our results suggest that variants in theMERTKgene are important for the risk of developing SLE-ESRD and suggest a role forPRDM1andAPOA1BPin proliferative LN.
Developing a contemporary community clinic for patients with heart failure with preserved ejection fraction within the current National Health Service model
Authors: Tran Patrick , Long Thomas , Smith Jessica , Kuehl Michael , Mahdy Tarek , Banerjee Prithwish
Published: November 2022

Introduction

The diagnostic and therapeutic arsenal for heart failure with preserved ejection (HFpEF) has expanded. With novel therapies (eg, sodium-glucose co-transporter 2 inhibitors) and firmer recommendations to optimise non-cardiac comorbidities, it is unclear if outpatient HFpEF models can adequately deliver this. We; therefore, evaluated the efficacy of an existing dedicated HFpEF clinic to find innovative ways to design a more comprehensive model tailored to the modern era of HFpEF.

Methods

A single-centre retrospective analysis of 202 HFpEF outpatients was performed over 12 months before the COVID-19 pandemic. Baseline characteristics, clinic activities (eg, medication changes, lifestyle modifications, management of comorbidities) and follow-up arrangements were compared between a HFpEF and general cardiology clinic to assess their impact on mortality and morbidity at 6 and 12 months.

Results

Between the two clinic groups, the sample population was evenly matched with a typical HFpEF profile (mean age 79±9.6 years, 55% female and a high prevalence of cardiometabolic comorbidities). While follow-up practices were similar, the HFpEF clinic delivered significantly more interventions on lifestyle changes, blood pressure and heart rate control (p<0.0001) compared with the general clinic. Despite this, no significant differences in all-cause hospitalisation and mortality were observed. This may be attributed to the fact that clinic activities were primarily cardiology-focused. Importantly, non-cardiovascular admissions accounted for >60% of hospitalisation, including causes of recurrent admissions.

Conclusion

This study suggests that existing general and emerging dedicated HFpEF clinics may not be adequate in addressing the multifaceted aspects of HFpEF as clinic activities concentrated primarily on cardiological measures. Although the small cohort and short follow-up period are important limitations, this study reminds clinicians that HFpEF patients are more at risk of non-cardiac than HF-related events. We have therefore proposed a pragmatic framework that can comprehensively deliver the modern guideline-directed recommendations and management of non-cardiac comorbidities through a multidisciplinary approach.
Development of algorithms for determining heart failure with reduced and preserved ejection fraction using nationwide electronic healthcare records in the UK
Authors: Sundaram Varun , Zakeri Rosita , Witte Klaus K , Quint Jennifer kathleen
Published: November 2022

Background

Determining heart failure (HF) phenotypes in routine electronic health records (EHR) is challenging. We aimed to develop and validate EHR algorithms for identification of specific HF phenotypes, using Read codes in combination with selected patient characteristics.

Methods

We used The Healthcare Improvement Network (THIN). The study population included a random sample of individuals with HF diagnostic codes (HF with reduced ejection fraction (HFrEF), HF with preserved ejection fraction (HFpEF) and non-specific HF) selected from all participants registered in the THIN database between 1 January 2015 and 30 September 2017. Confirmed diagnoses were determined in a randomly selected subgroup of 500 patients via GP questionnaires including a review of all available cardiovascular investigations. Confirmed diagnoses of HFrEF and HFpEF were based on four criteria. Based on these data, we calculated a positive predictive value (PPV) of predefined algorithms which consisted of a combination of Read codes and additional information such as echocardiogram results and HF medication records.

Results

The final cohort from which we drew the 500 patient random sample consisted of 10 275 patients. Response rate to the questionnaire was 77.2%. A small proportion (18%) of the overall HF patient population were coded with specific HF phenotype Read codes. For HFrEF, algorithms achieving over 80% PPV included definite, possible or non-specific HF HFrEF codes when combined with at least two of the drugs used to treat HFrEF. Only in non-specific HF coding did the use of three drugs (rather than two) contribute to an improvement of the PPV for HFrEF. HFpEF was only accurately defined with specific codes. In the absence of specific coding for HFpEF, the PPV was consistently below 50%.

Conclusions

Prescription for HF medication can reliably be used to find HFrEF patients in the UK, even in the absence of a specific Read code for HFrEF. Algorithms using non-specific coding could not reliably find HFpEF patients.
Revisiting survival at sea from a nutrition and food perspective: rationalizing the rations
Authors: Bordenave Nicolas , Brown Robert , Basset Fabien , Power Jonathan , Godin Nathalie , Haman François
Published: November 2022

This study examines the design of food rations for survival at sea required by the International Maritime Organization through the Life Saving Appliances (LSA) Code, as implemented by Transport Canada. Energy demand and body fat reserves were estimated for the Canadian population based on demographic and anthropometric data. It was determined that caloric content of food rations could be drastically decreased without potential harm to survivors of a marine abandonment. Coupled with ration reformulation, such decrease could be an opportunity to extend safe survival conditions to up to 5 days versus 2 days as currently provisioned by the LSA Code.
Comparative ecology of chasmogamous and cleistogamous reproduction inDanthonia compressa: effects of floral type and maternal environment
Authors: Cheplick Gregory P.
Published: November 2022

The significance of maternal and progeny environment to chasmogamy (CH) and cleistogamy (CL) in perennial plants is not well known. The perennial grass Danthonia compressa produces CH spikelets capable of outcrossing on terminal panicles in summer followed by selfing axillary CL spikelets in autumn. This study compared CH and CL seed mass, germination, seedling size, tillering, and reproduction in a sunny woodland edge and shaded interior habitat in the Catskill Mountains of New York State. CL seeds were significantly heavier than CH seeds. Numbers and mass of both seed types were greater in the edge. CL seeds showed much greater germination than CH seeds in both environments during spring, 2018; CL seedlings were larger than CH seedlings in the sunnier habitat. Survival was much greater in the edge than interior and higher for CL seedlings. After 27 months, maternal effects were mostly not detected and there was no significant effect of plant type (CH vs CL) on tiller production, final biomass, or reproduction via CH and CL. For this native grass, non-dispersed CL seeds may be more critical to seedling establishment and population persistence due to greater mass and germinability, and better plant survival, relative to smaller, dispersible CH seeds.
Quantum operations on conformal nets
Authors: Bischoff Marcel , Del Vecchio Simone , Giorgetti Luca
Published: November 2022

On a conformal net [Formula: see text], one can consider collections of unital completely positive maps on each local algebra [Formula: see text], subject to natural compatibility, vacuum preserving and conformal covariance conditions. We call quantum operations on [Formula: see text] the subset of extreme such maps. The usual automorphisms of [Formula: see text] (the vacuum preserving invertible unital *-algebra morphisms) are examples of quantum operations, and we show that the fixed point subnet of [Formula: see text] under all quantum operations is the Virasoro net generated by the stress-energy tensor of [Formula: see text]. Furthermore, we show that every irreducible conformal subnet [Formula: see text] is the fixed points under a subset of quantum operations.

When [Formula: see text] is discrete (or with finite Jones index), we show that the set of quantum operations on [Formula: see text] that leave [Formula: see text] elementwise fixed has naturally the structure of a compact (or finite) hypergroup, thus extending some results of [M. Bischoff, Generalized orbifold construction for conformal nets, Rev. Math. Phys. 29 (2017) 1750002]. Under the same assumptions, we provide a Galois correspondence between intermediate conformal nets and closed subhypergroups. In particular, we show that intermediate conformal nets are in one-to-one correspondence with intermediate subfactors, extending a result of Longo in the finite index/completely rational conformal net setting [R. Longo, Conformal subnets and intermediate subfactors, Comm. Math. Phys. 237 (2003) 7–30].
A Prediction Model for Normal Variation of Somatosensory Evoked Potential During Scoliosis Surgery
Authors: Fei Ningbo , Li Rong , Cui Hongyan , Hu Yong
Published: November 2022

Somatosensory evoked potential (SEP) has been commonly used as intraoperative monitoring to detect the presence of neurological deficits during scoliosis surgery. However, SEP usually presents an enormous variation in response to patient-specific factors such as physiological parameters leading to the false warning. This study proposes a prediction model to quantify SEP amplitude variation due to noninjury-related physiological changes of the patient undergoing scoliosis surgery. Based on a hybrid network of attention-based long-short-term memory (LSTM) and convolutional neural networks (CNNs), we develop a deep learning-based framework for predicting the SEP value in response to variation of physiological variables. The training and selection of model parameters were based on a 5-fold cross-validation scheme using mean square error (MSE) as evaluation metrics. The proposed model obtained MSE of 0.027[Formula: see text][Formula: see text] on left cortical SEP, MSE of 0.024[Formula: see text][Formula: see text] on left subcortical SEP, MSE of 0.031[Formula: see text][Formula: see text] on right cortical SEP, and MSE of 0.025[Formula: see text][Formula: see text] on right subcortical SEP based on the test set. The proposed model could quantify the affection from physiological parameters to the SEP amplitude in response to normal variation of physiology during scoliosis surgery. The prediction of SEP amplitude provides a potential varying reference for intraoperative SEP monitoring.
Impulsivity Classification Using EEG Power and Explainable Machine Learning
Authors: Hüpen Philippa , Kumar Himanshu , Shymanskaya Aliaksandra , Swaminathan Ramakrishnan , Habel Ute
Published: November 2022

Impulsivity is a multidimensional construct often associated with unfavorable outcomes. Previous studies have implicated several electroencephalography (EEG) indices to impulsiveness, but results are heterogeneous and inconsistent. Using a data-driven approach, we identified EEG power features for the prediction of self-reported impulsiveness. To this end, EEG signals of 56 individuals (18 low impulsive, 20 intermediate impulsive, 18 high impulsive) were recorded during a risk-taking task. Extracted EEG power features from 62 electrodes were fed into various machine learning classifiers to identify the most relevant band. Robustness of the classifier was varied by stratified [Formula: see text]-fold cross validation. Alpha and beta band power showed best performance in the classification of impulsiveness (accuracy = 95.18% and 95.11%, respectively) using a random forest classifier. Subsequently, a sequential bidirectional feature selection algorithm was used to estimate the most relevant electrode sites. Results show that as little as 10 electrodes are sufficient to reliably classify impulsiveness using alpha band power ([Formula: see text]-measure = 94.50%). Finally, the Shapley Additive exPlanations (SHAP) analysis approach was employed to reveal the individual EEG features that contributed most to the model’s output. Results indicate that frontal as well as posterior midline alpha power seems to be of most importance for the classification of impulsiveness.
Viscoelastic Cahn–Hilliard models for tumor growth
Authors: Garcke Harald , Kovács Balázs , Trautwein Dennis
Published: November 2022

We introduce a new phase field model for tumor growth where viscoelastic effects are taken into account. The model is derived from basic thermodynamical principles and consists of a convected Cahn–Hilliard equation with source terms for the tumor cells and a convected reaction–diffusion equation with boundary supply for the nutrient. Chemotactic terms, which are essential for the invasive behavior of tumors, are taken into account. The model is completed by a viscoelastic system consisting of the Navier–Stokes equation for the hydrodynamic quantities, and a general constitutive equation with stress relaxation for the left Cauchy–Green tensor associated with the elastic part of the total mechanical response of the viscoelastic material. For a specific choice of the elastic energy density and with an additional dissipative term accounting for stress diffusion, we prove existence of global-in-time weak solutions of the viscoelastic model for tumor growth in two space dimensions [Formula: see text] by the passage to the limit in a fully-discrete finite element scheme where a CFL condition, i.e. [Formula: see text], is required.

Moreover, in arbitrary dimensions [Formula: see text], we show stability and existence of solutions for the fully-discrete finite element scheme, where positive definiteness of the discrete Cauchy–Green tensor is proved with a regularization technique that was first introduced by Barrett and Boyaval [Existence and approximation of a (regularized) Oldroyd-B model, Math. Models Methods Appl. Sci. 21 (2011) 1783–1837]. After that, we improve the regularity results in arbitrary dimensions [Formula: see text] and in two dimensions [Formula: see text], where a CFL condition is required. Then, in two dimensions [Formula: see text], we pass to the limit in the discretization parameters and show that subsequences of discrete solutions converge to a global-in-time weak solution. Finally, we present numerical results in two dimensions [Formula: see text].
Destroying Kaluza–Klein black holes
Authors: Siahaan Haryanto M. , Tjiang Paulus C.
Published: November 2022

We investigate the destroying of charged and rotating black holes in Einstein–Maxwell-(dilaton) theory. We show that a test particle with some appropriate properties in the black hole background can turn the black hole into a naked singularity. In this work, we neglect the self-force, self-energy and radiative effects as considered by some others in literature. As the result, we are able to show that the Kaluza–Klein black holes can be destroyed by the test particle. Furthermore, we consider the overspinning of the black hole by a neutral test scalar field.
MICROSTRUCTURE, MECHANICAL PROPERTIES AND WEAR BEHAVIOR OF NI-COATED CONTINUOUS CARBON FIBER-REINFORCED A356 ALUMINUM MATRIX COMPOSITES FABRICATED BY SQUEEZE CASTING
Authors: ALIZADEH ALI , KAZEMI-FARD SOBHAN , HAJIZAMANI MOHSEN
Published: November 2022

In this research, aluminum matrix composites reinforced with continuous carbon fibers (CFs) were fabricated using A356 aluminum alloy and PAN-based CFs by squeeze casting. For this purpose, CFs were first coated with a nickel layer using the electroless method and then the microstructure of the nickel–phosphorus (Ni–P) electroless coating was investigated. In the next step, composite samples reinforced with volume fractions of 5, 10, and 15 vol.% CFs coated with Ni–P coating were fabricated by squeeze casting at 60 MPa, and then microstructure and mechanical properties were examined. The results of the bending test on the composite samples indicated that the nickel coating had a significant effect on the flexural strength of the composite and increased the flexural strength by up to 30%. In addition, with the increase in the volume percentage of the fibers, the hardness of the samples increased while both the wear rate and the coefficient of friction decreased. Moreover, the best wear resistance was observed in the sample containing 15 vol.% as-coated carbon fibers. The Ni coating led to the formation of a mechanically mixed layer (MML) containing a fine mixture of metallic oxides and carbon thus enhancing the wear resistance.
EFFECT OF AUSTEMPERED TEMPERATURE ON THE MICROSTRUCTURE AND PROPERTIES OF B-BEARING CADI
Authors: SUN YUFAN , FU HANGUANG , GUO XINGYE , XING ZHENGUO , YIN WENHANG , LIN JIAN
Published: November 2022

Carbidic austempered ductile iron (CADI) is a new type of wear-resistant material with high performance developed in recent years. The effect of austempered temperature on the microstructure and properties of high B-bearing CADI was investigated. Boron is an element that significantly interferes with the spheroidization process. When the boron content in CADI is high, the crystallization of spheroidal graphite in the as-cast microstructure is hindered, and its roundness, spheroidization rate, and volume fraction are significantly reduced. The results of its heat treatment process show that with the increase of austempered temperature, the volume fraction of residual austenite in the matrix increased, the size of acicular ferrite becomes coarser, and the ferrite also increases significantly, and the macroscopic hardness and wear resistance of the specimens gradually decreased.
Effective image splicing detection using deep neural network
Authors: Priyadharsini S. , Devi K. Kamala
Published: November 2022

Digital forgery is increasing day by day due to the increase in the usage of digital media files and the ease of editing media files. But digital media editing is a serious issue, as digital media are the primary source of evidence for criminal cases in the courtrooms. Consequently, there is an urge to detect and localize forgeries in digital media to aid digital forensics. The main aim of the proposed work is to detect forgeries in digital images. Image splicing forgery involves copying an image region from one image and pasting it into another image. A deep learning-based technique is proposed to detect image splicing forgery. A pre-trained deep Convolution Neural Network is transferred for the proposed application. The network is trained using spliced and original images to adapt it to the image splicing detection problem. The layers in the network are modified and fine-tuned to make it perform well for the new unseen dataset. This re-designed convolution network discriminates spliced and original images accurately. Also, the proposed work locates the spliced image regions if both the source and spliced images are provided as input image pairs. The proposed work is tested on CASIA and Columbia splicing image datasets and achieved good results.
Existence and regularity of shock-effected solitons for nonlinear problems in electro-cardiac-physiology
Authors: Iqbal Muhammad Sajid , Inc Mustafa , Ghazanfar Sidra , Ahmed Nauman
Published: November 2022

In this paper, mainly the exact traveling waves fitting the mathematical model in electro-cardio-physiology have been investigated. The source functions of noise-type are used in the proposed coupled system of nonlinear partial differential equations. The Ricatti–Bernoulli Sub-ODE method together with the Bäcklund extension is applied. The interesting plots for the obtained traveling waves and solitons are shown. The proposed model provides new applications for the considerations under the electric pulses or shocks. The application of current method and the modification of classical existence theory are first time applied to the stochastic nonlinear problems in electro-cardiac-physiology.
Correlations dynamics of two-spin XYZ Heisenberg model via negativity and skew information
Authors: Khedr Ahmad N. , Tammam Mahmoud , Abdel-Aty Mahmoud
Published: November 2022

We introduce a new framework for quantum two-spin correlations based on a quantum skew information quantity and long-negativity. The quantum correlations for an anisotropic two-qubit Heisenberg [Formula: see text] model are affected by physical parameters such as intrinsic decoherence, Werner states and time-dependent magnetic fields. In particular, the joint effects of Werner states, magnetic fields and anisotropic parameters on quantum correlation robustness are investigated in the presence of intrinsic decoherence. For an initially uncorrelated state, robust entanglement is generated while skew information between the two quantum bits no longer exists. It is shown that the magnetic field makes the system strongly correlated with incredibly significant steady-state values in uncorrelated states. The phenomenon of sudden death and sudden birth appear during the evolution process of initial conditions. Finally, if the system starts from a mixed state or a Werner state, the magnetic field does not play a significant role in the monotonically decreasing correlations. By leveraging our framework, one can create a kind of stability between the uncertainty-induced quantum nonlocality and the local quantum uncertainty correlations.
On L-Fuzzy Topological Spaces Determined by Implicators
Authors: Tripathi Abha , Tiwari S. P.
Published: November 2022

This paper is towards the study of [Formula: see text]-fuzzy topological spaces, [Formula: see text]-fuzzy pretopological spaces and their corresponding operators determined by general implicators. We show that the results regarding one-to-one correspondence between [Formula: see text]-fuzzy reflexive approximation spaces and [Formula: see text]-fuzzy pretopological spaces as well as [Formula: see text]-fuzzy preorder approximation spaces and [Formula: see text]-fuzzy topological spaces heavily depend on implicators. Finally, we establish a relationship between category of [Formula: see text]-fuzzy pretopological spaces and category of [Formula: see text]-fuzzy topological spaces by using category of [Formula: see text]-fuzzy approximation spaces.
PERSONAL FINANCIAL MANAGEMENT BEHAVIOR USING DIGITAL PLATFORMS AND ITS DOMAINS
Authors: CHHILLAR NEETU , ARORA SWARANJEET
Published: November 2022

Personal Finance Management (PFM) is crucial to control money to ensure that people have a comfortable present as well as secure future. It’s important for every individual to manage his finance digitally in the digital age. This study aims to identify the main dimensions of PFM from literature review and empirically test the impact of its each domain on the overall Digitalized Financial Management Behavior (DFMB). Also, the study verified the psychometric properties of the tool used to measure Personal Financial Management Behavior (PFMB) using digital platforms. The questionnaire was online administrated using Google forms among 388 young adults in the National Capital Territory (NCT) of India. The Kaiser–Meyer–Olkin (KMO) test of sampling adequacy and Bartlett’s test, linearity assessment, data screening were done in International Business Machines Statistical Package for Social Sciences (IBM SPSS). Factor analysis was done for unidimensionality assessment, bootstrapping (5000 resamples), and reliability and validity statistics in SmartPLS. The study identified six key dimensions of PFM from the existing significant literature and empirically verified the psychometric properties of the instrument in digital context. The resultant instrument includes 25 items under the six constructs. The study found that spending, credit management, saving behavior, personal cash management, investment and insurance are theoretically and empirically important determinants of PFM practices using digital platform therefore more attention need to be paid to these determinants for promoting sound DFMB.
Role of Artificial Intelligence in Quality Assurance in ART: A Review
Authors: Khan Haroon Latif , Khan Shezae , Bhatti Shahzad , Abbas Sana
Published: November 2022

During the last few decades, assisted reproductive technologies (ARTs) have flourished rapidly and accompanied a set of advanced procedures such as intracytoplasmic sperm injection (ICSI), electronic witnessing, digital monitoring through embryoscope time-lapse systems, consistent decision-making algorithms with advanced statistics modes and preimplantation genetic testing (PGT). In usual practice, manual procedures were routinely used in IVF (in vitro fertilization) laboratories worldwide, but automation and artificial intelligence (AI) systems are promising techniques for quality assurance, which reduced the burden on the working staff in the embryology laboratory. In addition, these systems are equipped with powerful mathematical tools that minimize technician variability in the IVF lab and efficiently generate data for impaired gametes and embryos. The principal challenge of single-sperm selection out of 108 gametes can be sorted out by incorporating machine learning algorithms coupled with advanced data processing capabilities. In the same line, the emergence of closed embryo culture systems (CECSs) in human embryology has enabled the accurate morphokinetic evaluation of the more rapid cell division and the identification of normal and abnormal hallmarks of embryo viability. In particular, these CECSs are guided by the latest time-lapse microscopy (TLM) facility to continuously monitor embryo development kinetics without removing them from controlled and stable incubator conditions. In conclusion, AI-driven models can reduce technical variability in sample handling and remove the burden of the most subjective, tedious and/or monotonous aspects of the IVF lab. Furthermore, these systems also highlight environmental stressors that could hamper embryo development competence. In a broader sense, AI-based approaches are more accurate, precise and rapid in predicting embryo quality noninvasively.
Differential geometric formulation of hanging membranes: Shell membrane theory and variational principle
Authors: Jikumaru Yoshiki , Yokosuka Yohei
Published: November 2022

In this paper, we present differential geometric formulation of hanging membrane forms based on the equilibrium equations in the shell membrane theory and the geometric variational problems. We also present the equations of hanging membranes in isothermic coordinates which will be an effective representation for numerical analysis in our forthcoming paper.
Roadside Unit-based Unknown Object Detection in Adverse Weather Conditions for Smart Internet of Vehicles
Authors: Chen Yu-Chia , Jhong Sin-Ye , Hsia Chih-Hsien
Published: November 2022

For Internet of Vehicles applications, reliable autonomous driving systems usually perform the majority of their computations on the cloud due to the limited computing power of edge devices. The communication delay between cloud platforms and edge devices, however, can cause dangerous consequences, particularly for latency-sensitive object detection tasks. Object detection tasks are also vulnerable to significantly degraded model performance caused by unknown objects, which creates unsafe driving conditions. To address these problems, this study develops an orchestrated system that allows real-time object detection and incrementally learns unknown objects in a complex and dynamic environment. A you-only-look-once–based object detection model in edge computing mode uses thermal images to detect objects accurately in poor lighting conditions. In addition, an attention mechanism improves the system’s performance without significantly increasing model complexity. An unknown object detector automatically classifies and labels unknown objects without direct supervision on edge devices, while a roadside unit (RSU)-based mechanism is developed to update classes and ensure a secure driving experience for autonomous vehicles. Moreover, the interactions between edge devices, RSU servers, and the cloud are designed to allow efficient collaboration. The experimental results indicate that the proposed system learns uncategorized objects dynamically and detects instances accurately.
Deep Appearance Prefiltering
Authors: Bako Steve , Sen Pradeep , Kaplanyan Anton
Published: November 2022

Physically based rendering of complex scenes can be prohibitively costly with a potentially unbounded and uneven distribution of complexity across the rendered image. The goal of an ideal level of detail (LoD) method is to make rendering costs
independent
of the 3D scene complexity, while preserving the appearance of the scene. However, current prefiltering LoD methods are limited in the appearances they can support due to their reliance of approximate models and other heuristics. We propose the first comprehensive multi-scale LoD framework for prefiltering 3D environments with complex geometry and materials (e.g., the Disney BRDF), while maintaining the appearance with respect to the ray-traced reference. Using a multi-scale hierarchy of the scene, we perform a data-driven prefiltering step to obtain an appearance phase function and directional coverage mask at each scale. At the heart of our approach is a novel neural representation that encodes this information into a compact latent form that is easy to decode inside a physically based renderer. Once a scene is baked out, our method requires no original geometry, materials, or textures at render time. We demonstrate that our approach compares favorably to state-of-the-art prefiltering methods and achieves considerable savings in memory for complex scenes.
Cytomegalovirus Therapy: Role of Letermovir in Prophylaxis and Treatment in Transplant Recipients
Authors: Saullo Jennifer L. , Miller Rachel A.
Published: November 2022

Cytomegalovirus (CMV) is a common viral pathogen in the transplant population and is associated with significant morbidity and mortality. CMV prevention is paramount; however, selecting the best preventive strategy depends on many factors including donor–recipient CMV serostatus, transplant-specific risks, antiviral toxicities and cost. Novel CMV therapeutics such as letermovir (LTV) are desperately needed to optimize CMV management. Uniquely among CMV antiviral therapies, LTV inhibits the viral terminase complex in the CMV DNA synthesis pathway and disrupts viral genome packaging. Further, it lacks side effects frequently associated with other CMV antiviral therapies and evades common mechanisms of resistance. LTV is approved by the US Food and Drug Administration for CMV prevention in adult CMV-seropositive hematopoietic cell transplant recipients but is increasingly applied off-label for prophylaxis and treatment. This review summarizes important concepts of CMV management in transplantation, with a specific focus on LTV pharmacology and clinical experience to date alongside future prospects for its application.
Core-Shell Enhanced Single Particle Model for Lithium Iron Phosphate Batteries: Model Formulation and Analysis of Numerical Solutions
Authors: Pozzato Gabriele , Takahashi Aki , Li Xueyan , Lee Donghoon , Ko Johan , Onori Simona
Published: November 2022

In this paper, a core-shell enhanced single particle model for iron-phosphate battery cells is formulated, implemented, and verified. Starting from the description of the positive and negative electrodes charge and mass transport dynamics, the positive electrode intercalation and deintercalation phenomena and associated phase transitions are described with the core-shell modeling paradigm. Assuming two phases are formed in the positive electrode, one rich and one poor in lithium, a core-shrinking problem is formulated and the phase transition is modeled through a shell phase that covers the core one. A careful discretization of the coupled partial differential equations is proposed and used to convert the model into a system of ordinary differential equations. To ensure robust and accurate numerical solutions of the governing equations, a sensitivity analysis of numerical solutions is performed and the best setting, in terms of solver tolerances, solid phase concentration discretization points, and input current sampling time, is determined in a newly developed probabilistic framework. Finally, unknown model parameters are identified at different C-rate scenarios and the model is verified against experimental data.
New insights into mechanisms of endothelial insulin resistance in type 2 diabetes
Authors: Padilla Jaume , Manrique-Acevedo Camila , Martinez-Lemus Luis A.
Published: November 2022

Insulin resistance in the vasculature is a hallmark of type 2 diabetes (T2D), and blunting of insulin-induced vasodilation is its primary consequence. Individuals with T2D exhibit a marked impairment in insulin-induced dilation in resistance arteries across vascular beds. Importantly, reduced insulin-stimulated vasodilation and blood flow to skeletal muscle limits glucose uptake and contributes to impaired glucose control in T2D. The study of mechanisms responsible for the suppressed vasodilatory effects of insulin has been a growing topic of interest for not only its association with glucose control and extension to T2D but also its relationship with cardiovascular disease development and progression. In this mini-review, we integrate findings from recent studies by our group with the existing literature focused on the mechanisms underlying endothelial insulin resistance in T2D.
Study on the Damage Diagnosis of Ancient Wood Structure in Tianshui under Traffic Excitation
Authors: Wang Xin , Meng Zhaobo , Zhang Xicheng
Published: November 2022

Three‐dimensional finite element model of the wood structure‐foundation of the North House’s main hall in Tianshui under ground traffic excitation was established, and the damage of the first‐floor longitudinal beam of the wood structure was simulated by the finite element method. The node acceleration response signals on beams were decomposed with a wavelet packet. The wavelet packet energy curvature difference index was proposed to determine the structural damage location. The results show that the wavelet packet energy curvature difference can decide the damage location of the middle part of the first‐floor longitudinal beam, and the index value increases with the increase of damage degree. If SNR is 40 db or larger, the damage index can accurately identify the damage of ancient wooden structures. When SNR increases, the damage index will have an increasingly higher sensitivity and certain ability to resist the effect of noise. The function relation between the damage index and the damage degree is obtained to determine the structural damage degree. The study results provide a theoretical basis for the damage diagnosis of the wood structure of ancient buildings along the traffic line.
MoSeFi: Duration Estimation Robust Human Motion Sensing via Commodity WiFi Device
Authors: Wang Xu , Zhang Linghua , Cheng Qin , Shu Feng
Published: November 2022

Accurate motion interval segmentation is the basic and crucial step in the advanced human perception based on WiFi signals. However, previous works have rarely considered motion duration, which is one of the important parameters for complete description of human motion. On this basis, we deeply investigate the properties of the CSI ratio from the perspective of Mobius transformation and construct a novel motion indicator using its complementary real and imaginary parts. The new indicator can attenuate the impact of motion fragmentation under short-window conditions and significantly reduce the duration error while ensuring detection accuracy. Moreover, we propose a universal subcarrier screening method based on response sensitivity and shape similarity, which provides more accurate information for perception. Furthermore, we present MoSeFi—a duration estimation robust human motion detection system using an existing commercial WiFi device. Detailed experimental results demonstrate that MoSeFi is lightweight yet effective compared to state-of-the-art systems.