Miracle-dz/UniFAR-FTUs huggingface dataset:
OVERCONFIDENCE BIAS IN NIFTY 50 SHARIAH: AN EMPIRICAL ANALYSIS

In this paper, we have empirically analyzed the relation between market turnover and market return to find the presence of overconfidence bias in the Nifty 50 shariah index in the Indian equity market. By taking daily data of endogenous variables like market turnover and market returns and exogenous variables return volatility and exchange rate, we find that market return does not impact market turnover while market turnover impact the return. The return volatility and exchange rate has significant impact on both the endogenous variables. The study is conducted in linear VAR environment for the period 1st January 200131st December 2019. Our results suggest that investors are riskaverse as they are less prone to overconfidence bias.
On ‘interface-plane scheme’ and symmetric grain boundaries

Abstract Quantitative analysis of grain boundaries relies on proper boundary parameterizations. One of the approaches to identification of boundaries is the ‘interface-plane scheme’. A rigorous examination reveals that this approach is deficient. It is demonstrated that the ‘interface-plane scheme’ fails to satisfy necessary conditions for a parameterization. Moreover, the difference between boundaries symmetric in the conventional sense and those termed as symmetric in the ‘interface-plane scheme’ is clarified. Also the relationship of these boundaries to twist and tilt boundaries is analyzed. Revealing the unsuitability of the ‘interface-plane scheme’ for boundary parameterization and eliminating the confusion caused by the incompatible definitions of symmetric boundaries is of importance for the progress in analysis of homophase interfaces.
Estimation of load-set behavior of driven concrete piles using artificial neural network and cone penetration test

Pile foundations are among the most common types of deep foundations. Predicting their draft is a fairly standard engineering goal. There are many techniques for this. Many methods for determining the settlement of piles are based on various empirical relationships. In particular, the cone penetration test allows you to determine the settlement and bearing capacity of a pile using the developed empirical dependencies. However, some models must be used to develop such correlations. This study proposes to use a slightly different approach. Instead of using a pile model and a set of empirical dependencies, it is suggested to use machine learning methods. Artificial neural networks are one of the machine learning methods. The article presents a description of the development of a neural network that allows estimating pile settlement using data from the CPT test.
Ensemble clustering-based fault diagnosis method incorporating traditional and deep representation features

The traditional and deep representation features have been successfully employed in the clustering-based fault diagnosis, however, current studies have ignored their heterogeneity and complementarity. Besides, these studies have rarely explored the superiority of ensemble clustering, leading to unstable diagnostic results. To address these issues, a novel ensemble clustering-based fault diagnosis method, namely ECFD, is proposed based on the collaboration of traditional and deep representation features. To the best of our knowledge, this is the first attempt to develop an ensemble clustering method with these types of features for fault diagnosis of rotating machinery. Initially, features are extracted by different approaches, among which the traditional features are obtained by time-domain, frequency-domain, time–frequency-domain approaches, and the deep representation features are extracted by the gated recurrent units-based autoencoders. Then, the heterogeneous and complementary information among these features is explored by the adaptive group regularization method, which is also developed to generate high-quality feature subspaces for constructing the base learners of the ensemble clustering. Finally, the clustering results of each base learner are integrated by a weighted voting method. The effectiveness of the proposed ECFD was verified by the experiments on the real-world bearing vibration dataset. The results indicate that the proposed ECFD can explore the heterogeneity and complementarity among different kinds of features and take advantage of the ensemble clustering, which is superior to other existing benchmark clustering methods in unsupervised fault diagnosis.
Jet grouting technique and strength properties of jet grout columns

Jet grouting is a relatively recent development which is applied for mainly ground improvement purposes and provides effective solutions to many geotechnical and geoenvironmental problems. Jet grouting technique differs substantially from the other grouting techniques in that this technique can be used in treating a wide range of soil types. Therefore the application fields of jet grouting are rapidly increasing. The main emphasize in this paper is given to the strength properties of jet grout columns. The strength properties of jet grout columns is investigated by the example of five case studies. The subsoil conditions and foundation engineering evaluations of the investigation areas are presented in the case studies. The strength properties are investigated by referring to the unconfined compressive strength test results of the core samples obtained from jet grouting columns.
Traffic vehicle cognition in severe weather based on radar and infrared thermal camera fusion

The accuracy and robustness of vehicle cognition in severe weather have always been the focus and difficulty of intelligent vehicle environment perception. This paper proposes a vehicle cognition method based on radar and infrared thermal camera information fusion in severe weather. The fusion of radar and infrared cameras can greatly enrich the completeness of vehicle cognitive information. First, an attention mechanism based on radar guidance information was proposed to extract the vehicle region of interest (ROI). Unlike the traditional ROI extraction method, this method is not disturbed by the environment and does not need complicated calculations, which can quickly and accurately extract ROI for vehicles. Second, based on ROI information, the infrared thermal image is reconstructed and enhanced, which is of great significance to improve the accuracy of vehicle detection for deep learning. Finally, we propose a vehicle depth estimation method based on pixel regression and use multi-scale cognitive information to fuse radar and image targets. The fusion method considering depth information can reduce target confusion and improve fusion robustness and accuracy, especially when vehicles are adjacent to each other. The experimental results show that the vehicle detection accuracy of this method is 95.2% and the vehicle detection speed is 37 fps, which effectively improves the performance of vehicle detection in severe weather.
J un 2 02 1 Repulsive Casimir force in stationary axisymmetric spacetimes

We study the influence of stationary axisymmetric spacetimes on Casimir energy. We consider a massive scalar field and analyze its dependence on the apparatus orientation with respect to the dragging direction associated with such spaces. We show that, for an apparatus orientation not considered before in the literature, the Casimir energy can change its sign, producing a repulsive force. As applications, we analyze two specific metrics: one associated with a linear motion of a cylinder and a circular equatorial motion around a gravitational source described by Kerr geometry.
Assortment Optimization under the Multi-Purchase Multinomial Logit Choice Model

Updating a Classic: Assortment Optimization under the Multi-Purchase MNL Model In the paper “Updating a Classic: Assortment Optimization under the Multi-Purchase MNL Model,” our primary contribution resides in proposing the first multi-purchase choice model that can be fully operationalized. Our main algorithmic results consist of two distinct polynomial time approximation schemes (PTAS); the first, and simpler of the two, caters to a setting where each customer may buy only a constant number of products, whereas the second, more nuanced algorithm applies to our multi-purchase model in its general form. Additionally, we study the revenue potential of making assortment decisions that account for multi-purchase behavior in comparison with those that overlook this phenomenon. In particular, we relate both the structure and revenue performance of the optimal assortment under a traditional single-purchase model to that of the optimal assortment in the multi-purchase setting.
[TDNQ][CoCp*2] and [TDNQ]3[CoCp2]2; Radical Anions of a 1,2,5-Thiadiazolo-naphthoquinone

The first crystal structure of a quinone[1,2,5]thiadiazole radical anion is presented. Reduction of naphtha[2,3-c][1,2,5]thiadiazole-4,9-dione (TDNQ) with outersphere electron transfer agents, decamethylcobaltocene (CoCp*2) and cobaltocene (CoCp2), by slow mixing of solutions, generates two species: [TDNQ][CoCp*2] and [TDNQ]3[CoCp2]2, respectively. The [TDNQ][CoCp*2] is soluble in a wide variety of organic solvents, whereas [TDNQ]3[CoCp2]2 is generally insoluble. The radical anion oxidation state, TDNQ•—, in [TDNQ][CoCp*2] is confirmed by lengthened C–O bond distances in the (solvated) crystal structure, as compared to neutral TDNQ, shifting of the ν(C–O) stretch in the IR absorption spectrum, and the presence of a solution electron paramagnetic resonance (EPR) signal. In the [TDNQ]3[CoCp2]2 species, copacking of single-molecule radical anions, TDNQ•—, and bimolecular radical anion units, (TDNQ)2•—, with cobaltocenium cations is observed. The magnetic measurements highlight the presence of dominating anti.
Linking population‐level and microevolutionary processes to understand speciation dynamics at the macroevolutionary scale

Abstract Although speciation dynamics have been described for several taxonomic groups in distinct geographic regions, most macroevolutionary studies still lack a detailed mechanistic view on how or why speciation rates change. To help partially fill this gap, we suggest that the interaction between the time taken by a species to geographically expand and the time populations take to evolve reproductive isolation should be considered when we are trying to understand macroevolutionary patterns. We introduce a simple conceptual index to guide our discussion on how demographic and microevolutionary processes might produce speciation dynamics at macroevolutionary scales. Our framework is developed under different scenarios: when speciation is mediated by geographical or resource‐partitioning opportunities, and when diversity is limited or not. We also discuss how organismal intrinsic properties and different overall geographical settings can influence the tempo and mode of speciation. We argue that specific conditions observed at the microscale might produce a pulse in speciation rates even without a pulse in either climate or physical barriers. We also propose a hypothesis to reconcile the apparent inconsistency between speciation measured at the microscale and macroscale, and emphasize that diversification rates are better seen as an emergent property. We hope to bring the reader's attention to interesting mechanisms to be further studied, to motivate the development of new theoretical models that connect microevolution and macroevolution, and to inspire new empirical and methodological approaches to more adequately investigate speciation dynamics either using neontological or paleontological data.
SARS-CoV-2 seroprevalence among Vancouver public school staff in British Columbia, Canada

Importance: Contact-tracing studies suggest minimal secondary transmission in schools. However, there are limited school data accounting for asymptomatic cases, particularly late in the 2020/21 school year, and in the context of uninterrupted in-person schooling and widespread community transmission. Objectives: To determine the SARS-CoV-2 seroprevalence in a sample of school staff, compared to the community, and to COVID-19 rates among all students and staff within the same school population. Design: Incident COVID-19 cases among students and school staff using public health data, with an embedded cross-sectional serosurvey among school staff sampled from February 10 to May 15, 2021, comparing to age, sex and geographic location-matched blood donors sampled in January 2021. Setting: Vancouver School District (British Columbia, Canada) from kindergarten to grade 12. Participants: Active school staff enrolled from February 3 to April 23, 2021. Main outcome measures: SARS-CoV-2 antibodies in a sample of school staff using spike (S)-based testing (unvaccinated staff) or N-based serology testing (vaccinated staff). Results: The incidence of COVID-19 cases among students attending in-person was 9.8 per 1,000 students during the 2020/21 school year (N = 47,280 students), and among staff was 13 per 1,000 since the beginning of the pandemic (N = 7,071 active school staff). In total, 1,689 school staff (64% elementary, 28% secondary, 8.3% school board staff or multiple grades) completed the questionnaire, 78.2% had classroom responsibilities, and spent a median of 17.6 hours in class per week [IQR: 5.0 - 25 hours]. Although 21.5% (363/1,686) reported close contact with a COVID-19 case, only 1.4% (24/1688) of the school staff reported having had a positive viral nucleic acid test. Of this group, five believed they acquired the infection at school. The adjusted seroprevalence in staff who gave blood (1,556/1,689, 92.1%) was 2.3% [95%CI: 1.6 - 3.2%] compared to 2.3% [95%CI: 1.7 - 3.0%] in blood donors. Conclusion and relevance: Despite high reported COVID-19 cases among students and staff, and frequent within-school exposures, we found no detectable increase in seroprevalence among school staff above the community seroprevalence. These findings corroborate claims that, with appropriate mitigation strategies, in-person schooling is not associated with significantly increased risk for school staff.
Review of Fuels for Direct Carbon Fuel Cells

In this paper, the current status of direct carbon fuel cell (DCFC) technology has been reviewed. Recent promising advances in the design of fuel cells has resulted in a reprisal of research into the DCFC technology. As a result, more is understood about the roles of species and mechanisms that govern the performance of DCFC systems. Of particular interest to industry and researchers are the direct carbon molten carbonate fuel cell (MCFC) and solid oxide fuel cell (SOFC) arrangements, with the bulk of research articles and large-scale investment focused on these DCFC types. However, the variety of fuels used and trialled within these fuel cells is limited. This is especially true for the SOFC arrangement, with the overwhelming fuel of choice for researchers being carbon black and light gases for industry. The application of more readily available and cheaper fuels in this type of DCFC is unassessed. This review addresses this gap in the literature by reviewing all fuels tested in direct carbon MCFC and SOFC systems, in particular critically evaluating low-rank coals and biomass, among other alternative fuels.
The Anxiety Depression Pathway Among Men Following a Prostate Cancer Diagnosis: Cross-Sectional Interactions Between Anger Responses and Loneliness

Anger has been a largely neglected emotion in prostate cancer research and intervention. This paper highlights the role of anger in the anxiety depression pathway among men with prostate cancer, and whether its impact is dependent on loneliness. Data are presented from a sample of men with prostate cancer (N = 105, M = 69.12 years, prostatectomy = 63.8%) and analysed using conditional process analysis. Dimensions of anger were evaluated as parallel mediators in bi-directional anxiety and depression pathways. Loneliness was evaluated as a conditional moderator of identified significant mediation relationships. Moderate severity depression (16.5%) was endorsed more frequently than moderate severity anxiety (8.6%, p = .008), with 19.1% of the sample reporting past two-week suicide ideation. Consistent with hypotheses, anger-related social interference (but not other dimensions of anger) significantly mediated the anxiety-depression pathway, but not the reverse depression-anxiety pathway. This indirect effect was conditional on men experiencing loneliness. Sensitivity analyses indicated the observed moderated mediation effect occurred for affective, but not somatic symptoms of depression. Findings support anger-related social interference (as opposed to anger frequency, intensity, duration or antagonism) as key to explaining the previously established anxiety-depression pathway. Results underscore the need for enhanced psychosocial supports for men with prostate cancer, with a particular focus on relational aspects. Supporting men with prostate cancer to adaptively process and manage their anger in ways that ameliorate negative social consequences will likely enhance their perceived social support quality, which may in turn better facilitate post-diagnosis recovery and emotional adjustment.
Characteristics of slow light from coupled fiber ring resonators

ABSTRACT This article optimizes the conditions for the formation of slow light produced by coupled fiber ring resonators. Investigated parameters include the number of rings, ring length, splitting ratio of couplers, and ring losses. The optimized parameters included two rings in the resonator, equal length of the rings, and splitting ratios of 90:10 and 50:50 for the couplers. Under these conditions, a slow light delay time of 32.0668 ns was achieved, which corresponds to a group velocity of 3.43 × 107 m/s.
Hypoperfusion Intensity Ratio Correlates with CTA Collateral Status in Large-Vessel Occlusion Acute Ischemic Stroke

BACKGROUND AND PURPOSE: Collateral blood supply is a key determinant of outcome in large-vessel occlusion acute ischemic stroke. Single- and multiphase CTA collateral scoring systems have been described but are subjective and require training. We aimed to test whether the CTP-derived hypoperfusion intensity ratio is associated with CTA collateral status and whether a threshold hypoperfusion intensity ratio exists that predicts poor CTA collaterals. MATERIALS AND METHODS: Imaging and clinical data of consecutive patients with large-vessel occlusion acute ischemic stroke were retrospectively reviewed. Single-phase CTA and multiphase CTA scoring were performed by 2 blinded neuroradiologists using the Tan, Maas, and Calgary/Menon methods. CTP was processed using RApid processing of PerfusIon and Diffusion software (RAPID). Hypoperfusion intensity ratio = ratio of brain volume with time-to-maximum >10 seconds over time-to-maximum >6-second volume. Correlation between the hypoperfusion intensity ratio and CTA collateral scores was calculated using the Pearson correlation. The optimal threshold of the hypoperfusion intensity ratio for predicting poor collaterals was determined using receiver operating characteristic curve analysis. RESULTS: Fifty-two patients with large-vessel occlusion acute ischemic stroke were included. Multiphase CTA collateral scoring showed better interrater agreement (κ = 0.813) than single-phase CTA (Tan, κ = 0.587; Maas, κ = 0.273). The hypoperfusion intensity ratio correlated with CTA collateral scores (multiphase CTA: r = −0.55; 95% CI, −0.67 to −0.40; P ≤ .001). The optimal threshold for predicting poor multiphase CTA collateral status was a hypoperfusion intensity ratio of >0.45 (sensitivity = 78%; specificity = 76%; area under the curve = 0.86). Patients with high hypoperfusion intensity ratio/poor collateral status had lower ASPECTS/larger infarcts, higher NIHSS scores, and larger hypoperfused volumes. CONCLUSIONS: The hypoperfusion intensity ratio is associated with CTA collateral status in patients with large-vessel occlusion acute ischemic stroke. The hypoperfusion intensity ratio is an automated and quantitative alternative to CTA collateral scoring methods for both clinical and future stroke trial settings.
The septin complex links the catenin complex to the actin cytoskeleton for establishing epithelial cell polarity

Abstract Cell polarity is essential for spatially regulating of physiological processes in metazoans by which hormonal stimulation‒secretion coupling is precisely coupled for tissue homeostasis and organ communications. However, the molecular mechanisms underlying epithelial cell polarity establishment remain elusive. Here, we show that septin cytoskeleton interacts with catenin complex to organize a functional domain to separate apical from basal membranes in polarized epithelial cells. Using polarized epithelial cell monolayer as a model system with transepithelial electrical resistance as functional readout, our studies show that septins are essential for epithelial cell polarization. Our proteomic analyses discovered a novel septin‒catenin complex during epithelial cell polarization. The functional relevance of septin‒catenin complex was then examined in three-dimensional (3D) culture in which suppression of septins resulted in deformation of apical lumen in cysts, a hallmark seen in polarity-deficient 3D cultures and animals. Mechanistically, septin cytoskeleton stabilizes the association of adherens catenin complex with actin cytoskeleton, and depletion or disruption of septin cytoskeleton liberates adherens junction and polarity complexes into the cytoplasm. Together, these findings reveal a previously unrecognized role for septin cytoskeleton in the polarization of the apical‒basal axis and lumen formation in polarized epithelial cells.
Recent Advances in Understanding Peripheral Taste Decoding I: 2010 to 2020

Taste sensation is the gatekeeper for direct decisions on feeding behavior and evaluating the quality of food. Nutritious and beneficial substances such as sugars and amino acids are represented by sweet and umami tastes, respectively, whereas noxious substances and toxins by bitter or sour tastes. Essential electrolytes including Na+ and other ions are recognized by the salty taste. Gustatory information is initially generated by taste buds in the oral cavity, projected into the central nervous system, and finally processed to provide input signals for food recognition, regulation of metabolism and physiology, and higher-order brain functions such as learning and memory, emotion, and reward. Therefore, understanding the peripheral taste system is fundamental for the development of technologies to regulate the endocrine system and improve whole-body metabolism. In this review article, we introduce previous widely-accepted views on the physiology and genetics of peripheral taste cells and primary gustatory neurons, and discuss key findings from the past decade that have raised novel questions or solved previously raised questions.