Miracle-dz/UniFAR-FTUs huggingface dataset:
An improved integral model for plane and round turbulent buoyant jets

The integral momentum and tracer equations for the mean motion with the turbulence contribution in momentum and tracer fluxes are integrated on the centreline of either plane or round buoyant jets, using suitable assumptions for the spreading coefficients and a closing function, and unified first- and second-order solutions are derived in the entire buoyancy range for mean axial velocities and mean concentrations. Comparisons to experimental data in the literature validate the model and show that second-order solutions deviate less than first-order solutions. Both types are used in conjunction with the integral continuity and kinetic energy equations for the mean motion to determine the variation of the local Richardson and Froude numbers, dispersion ratio, bulk dilution, dilution ratio, entrainment coefficient and mean velocity, kinetic energy flux and its gradient for the mean motion; and the variations of these quantities are evaluated using reported experimental or theoretical data. Finally, the variation of the product of kinetic energy flux and the local Richardson number is examined and a universal constant for both plane and round buoyant jets is revealed, leading to a unified definition of the local Richardson number, which is independent of the flow and mixing geometry and could be useful. Simple computational programming and good overall agreement make the proposed model a very promising tool for laboratory and field studies, outfall design and validation of numerical models.
Antenna‐plasma and antenna‐spacecraft resistance on the Wind spacecraft

Measurements have been made of the resistance of three different electric field sensing antennas on the Wind spacecraft in the solar wind. The measurements have been separated into base resistance and plasma resistance by assuming that the plasma resistance is inversely proportional to the antenna length. Simple formulas for the resistances, as functions of the plasma electron flux, are given and fitted to the data. The results imply that the division of the signal by the base resistance is important and needs to be taken into account in low-frequency measurements of electric fields when the antennas are shorter than a few tens of meters.
IMPACT OF NEW PRODUCT KNOWLEDGE AND PROMOTIONAL SIGNAGE ON CONSUMERS’ IMPULSE BUYING INTENTION AND BEHAVIOUR: A MEDIATED MODEL

Customer research has paid a lot of attention to consumer impulse buying. The phenomena is intriguing since it is influenced by both external, market-related inputs and a number of internal psychological elements. The research attempts to comprehend the factors affecting impulse buying behaviour of consumers typically when they consider purchasing new products. Furthermore, the effects of different concepts on the impulse buying are discovered, such as impulse buying intention, new product knowledge and promotional signage in the Pakistani context. This study uses a survey method to test a theoretically grounded set of hypotheses. Using a 22 items questionnaire, the data were obtained from 200 respondents and the data were analysed using SPSS. This study findings reveal that new product knowledge and promotional signage has positive and significant influence on consumers’ impulse buying behaviour as well as impulse buying intention, similarly our mediator that is impulse buying intention also has a positive significant influence on consumers’ impulse buying behaviour. There lies a partial mediation between the promotional signage and impulse buying behaviour in the presence of mediator but impulse buying intention has no significant mediating impact between new product knowledge and impulse buying behaviour. The paper supports the importance of new product knowledge and promotional signage as key drivers of consumer’s impulse buying behaviour. It further underlines the importance of consumer’s impulse buying intention with a mediating effect between new product knowledge, promotional signage and consumer’s impulse buying behaviour. Marketers, retailers, executives and managers can have advantage from these findings for future marketing strategies and can acquire new customers by retaining the old ones to achieve long-term performance objectives.
Learning Recourse on Instance Environment to Enhance Prediction Accuracy

Machine Learning models are often susceptible to poor performance on instances sampled from bad environments. For example, an image classifier could provide low accuracy on images captured under low lighting conditions. In high stake ML applications, such as AI-driven medical diagnostics, a better option could be to provide recourse in the form of alternative environment settings in which to recapture the instance for more reliable diagnostics. In this paper, we propose a model called R ECOURSE N ET that learns to apply recourse on the space of environments so that the recoursed instances are amenable to better predictions by the classifier. Learning to output optimal recourse is challenging because we do not assume access to the underlying physical process that generates the recoursed instances. Also, the optimal setting could be instance-dependent — for example the best camera angle for object recognition could be a function of the object’s shape. We propose a novel three-level training method that (a) Learns a classifier that is optimized for high performance under recourse, (b) Learns a recourse predictor when the training data may contain only limited instances under good environment settings, and (c) Triggers recourse selectively only when recourse is likely to improve classifier confidence. We experiment with synthetic and real world datasets to show the efficacy of our proposed approach.
Memory-Efficient Hashed Page Tables

Conventional radix-tree page tables have scalability challenges, as address translation following a TLB miss potentially requires multiple memory accesses in sequence. An alternative is hashed page tables (HPTs) where, conceptually, address translation needs only one memory access. Traditionally, HPTs have been shunned due to high costs of handling conflicts and other limitations. However, recent advances have made HPTs compelling. Still, a major issue in HPT designs is their requirement for substantial contiguous physical memory.This paper addresses this problem. To minimize HPTs’ contiguous memory needs, it introduces the Logical to Physical (L2P) Table and the use of Dynamically-Changing Chunk Sizes. These techniques break down the HPT into discontiguous physical-memory chunks. In addition, the paper also introduces two techniques that minimize HPTs’ total memory needs and, indirectly, reduce the memory contiguity requirements. These techniques are In-place Page Table Resizing and Per-way Resizing. We call our complete design Memory-Efficient HPTs (ME-HPTs). Compared to state-of-the-art HPTs, ME-HPTs: (i) reduce the contiguous memory allocation needs by 92% on average, and (ii) improve the performance by 8.9% on average. For the two most demanding workloads, the contiguous memory requirements decrease from 64MB to 1MB. In addition, compared to state-of-the-art radix-tree page tables, ME-HPTs achieve an average speedup of 1.23× (without huge pages) and 1.28× (with huge pages).
On High dimensional Poisson models with measurement error: hypothesis testing for nonlinear nonconvex optimization

We study estimation and testing in the Poisson regression model with noisy high dimensional covariates, which has wide applications in analyzing noisy big data. Correcting for the estimation bias due to the covariate noise leads to a non-convex target function to minimize. Treating the high dimensional issue further leads us to augment an amenable penalty term to the target function. We propose to estimate the regression parameter through minimizing the penalized target function. We derive the L1 and L2 convergence rates of the estimator and prove the variable selection consistency. We further establish the asymptotic normality of any subset of the parameters, where the subset can have infinitely many components as long as its cardinality grows sufficiently slow. We develop Wald and score tests based on the asymptotic normality of the estimator, which permits testing of linear functions of the members if the subset. We examine the finite sample performance of the proposed tests by extensive simulation. Finally, the proposed method is successfully applied to the Alzheimer's Disease Neuroimaging Initiative study, which motivated this work initially.
Nonparametric estimation of the gap time distributions for serial events with censored data

Summary In many follow-up studies, each subject can potentially experience a series of events, which may be repetitions of essentially the same event or may be events of entirely diVerent natures. This paper provides a simple nonparametric estimator for the multivariate distribution function of the gap times between successive events when the follow-up time is subject to right censoring. The estimator is consistent and, upon proper normalisation, converges weakly to a zero-mean Gaussian process with an easily estimated covariance function. Numerical studies demonstrate that both the distribution function estimator and its covariance function estimator perform well for practical sample sizes. An application to a colon cancer study is presented.
Route Travel Time Estimation on A Road Network Revisited: Heterogeneity, Proximity, Periodicity and Dynamicity

In this paper, we revisit the problem of route travel time estimation on a road network and aim to boost its accuracy by capturing and utilizing spatio-temporal features from four significant aspects: heterogeneity, proximity, periodicity and dynamicity. Spatial-wise, we consider two forms of heterogeneity at link level in a road network: the turning ways between different links are heterogeneous which can make the travel time of the same link various; different links contain heterogeneous attributes and thereby lead to different travel time. In addition, we take into account the proximity: neighboring links have similar traffic patterns and lead to similar travel speeds. To this end, we build a link-connection graph to capture such heterogeneity and proximity. Temporal-wise, the weekly/daily periodicity of temporal background information (e.g., rush hours) and dynamic traffic conditions have significant impact on the travel time, which result in static and dynamic spatio-temporal features respectively. To capture such impacts, we regard the travel time/speed as a combination of static and dynamic parts, and extract many spatio-temporal relevant features for the prediction task. Talking about the methodology, it remains an open problem to build a generic learning model to boost the estimation accuracy. Hence, we design a novel encoder-decoder framework - The encoder uses the sequence attention model to encode dynamic features from the temporal-wise perspective. The decoder first uses the heterogeneous graph attention model to decode the static part of travel speed based on static spatio-temporal features, and then leverages the sequence attention model to decode the estimated travel time from spatial-wise perspective. Extensive experiments on real datasets verify the superiority of our method as well as the importance of the four aspects outlined above.
Near-field visualization of focal depth modulation by step corrugated plasmonic slits

Nanometric plasmonic slits with stepped corrugations have been designed and fabricated to achieve plasmonic focusing and focal depth modulation. A scanning near-field optical microscope is employed to directly visualize the transmitted light from the slits. The near-field and far-field two-dimensional images taken at different planes parallel to the slit surface unambiguously demonstrated the focusing effect of the nanoslits. Furthermore, by forming stepped corrugations with either a concave or a convex profile on both sides of the slits, the phase of the transmitted beam can be effectively manipulated, thus allowing an accurate tuning of the focal depth.
SEXUAL ACTS AND ESCALATION: AN ANALYSIS OF THE FACTORS LEADING TO SEX CRIMES

Sex crime is a worldwide phenomenon, but being an Islamic state, Pakistan's position is very crucial. In Pakistan, the number of sex crimes is uncontrolled and increasing regardless of strong efforts at the government and non-government levels. The focus of the research at hand was to dig out the possible factors leading to sex crimes in Pakistani society. The study is conducted using a qualitative approach, applying interview protocol to such citizens who are professionals and serving in different fields of law; hence, the study is also abreast of the enriched experience and knowledge of learned officials. An in-depth interview for exploring these areas was developed and validated. Data were collected from 11 key informants with prolonged experience in their field of work. The study has important implications for dealing with such an obscene phenomenon for the government, judiciary, law enforcement departments, policymakers, non-governmental organisations linked with fields of law, personnel from grass-roots level administration, parents and teachers, and so on. Keywords: Sexual Acts, Crimes, Sexual Abuse, Sexual Penal provisions, Pakistan.
Examining Relationships Between Transgender Prejudice, Gender Essentialism, and Defining and Categorizing Transgender People

Some definitions and adoptions of the word “transgender” may be rooted in transgender prejudice and result in different conclusions about who is considered transgender. Transnormative definitions, fixed to the gender binary and medical transitions, could lead to categorical exclusions, whereas umbrella definitions, centered on people’s self-identification and often featuring a greater range of gender identities, could lead to broader inclusion. The present work explored whether the relationship between attitudes toward transgender people and transgender target categorization is associated with divergent definitions of the word transgender. We hypothesized that higher prejudice and gender essentialism would predict agreement with transnormative definitions that would then predict lower categorization of transgender targets. We also hypothesized that lower prejudice and gender essentialism would predict agreement with umbrella definitions that would then predict higher transgender categorization. Using a sample of MTurk Workers (N = 497), we tested these hypotheses with a parallel moderated-mediation analysis. Results support that gender essentialism moderated the relationship between prejudice and umbrella definitions, and umbrella definitions mediated the relationship between attitudes and categorization of transgender targets (index of moderated mediation = .46, BCa CI [.20, .76]). Transnormative definition agreement was not predicted by prejudice or gender essentialism, and did not mediate the relationship between these attitudes and categorization (index of moderated mediation = .00, BCa CI [–.06, .05]). These findings provide insight into the role of underlying attitudes on categorization, which has implications on transgender and gender-diverse people’s identity affirmation, social belonging, and healthcare access.
Time-resolved multiphoton imaging of basal cell carcinoma

We investigated human cutaneous basal cell carcinoma ex-vivo samples by combined time resolved two photon intrinsic fluorescence and second harmonic generation microscopy. Morphological and spectroscopic differences were found between malignant skin and corresponding healthy skin tissues. In comparison with normal healthy skin, cancer tissue showed a different morphology and a mean fluorescence lifetime distribution slightly shifted towards higher values. Topical application of delta-aminolevulinic acid to the lesion four hours before excision resulted in an enhancement of the fluorescence signal arising from malignant tissue, due to the accumulation of protoporphyrines inside tumor cells. Contrast enhancement was prevalent at tumor borders by both two photon fluorescence microscopy and fluorescence lifetime imaging. Fluorescence-based images showed a good correlation with conventional histopathological analysis, thereby supporting the diagnostic accuracy of this novel method. Combined morphological and lifetime analysis in the study of ex-vivo skin samples discriminated benign from malignant tissues, thus offering a reliable, non-invasive tool for the in-vivo analysis of inflammatory and neoplastic skin lesions.
CASE STUDY Proximate values and elemental analysis in wheat and soybean using inductively coupled plasma mass spectrometry

BACKGROUND AND OBJECTIVES: Determining food composition and bioactivity is critical to both theoretical and applied research in food science and technology. This is frequently used to determine the nutritional value and overall acceptance of the food by consumers. The current study’s goal is to determine the macronutrient, mineral and antioxidant activity of selected wheat and soybean varieties with the potential to be useful in the food industry to develop value-added products that are safe for consumption. METHODS: The proximate and mineral composition, gluten characterization, total phenolic contents, and antioxidant activity of three wheat cultivars and five soybean cultivars that are indigenous to India were studied. FINDINGS: Wheat varieties were found to be rich in carbohydrates (65.8-68.8 percent) and gluten (27.2-28.6 percent), whereas soybean varieties were found to be the richest source of protein (32.8-33.7 percent), fat (17.1-17.6 percent), fiber (21.7-28.8 percent), polyphenols (2.76-3.59 milligram gallic acid equivalent per gram, and antioxidant activity (97-123 microgram ascorbic acid equivalent per gram). These samples were also found to have significant content of essential minerals. CONCLUSION: The tested samples had a high nutritional value and energy content and could be a good source of nutrition for a large population. A comprehensive report on the proximate and mineral composition, total phenolic content and antioxidant activity of the wheat and soybean varieties collected from the Rewa district, India, was reported.
Electric field induced short range to long range structural ordering and its influence on the Eu+3 photoluminescence in the lead-free ferroelectric Na1/2Bi1/2TiO3

Eu+3 was incorporated into the lattice of a lead-free ferroelectric Na1/2Bi1/2TiO3 (NBT) as per the nominal formula Na0.5Bi0. 5-xEuxTiO3. This system was investigated with regard to the Eu+3 photoluminescence (PL) and structural behaviour as a function of composition and electric field. Electric field was found to irreversibly change the features in the PL spectra and also in the x-ray diffraction patterns below the critical composition x = 0.025. Detailed analysis revealed that below the critical composition, electric field irreversibly suppresses the structural heterogeneity inherent of the host matrix NBT and brings about a long range ferroelectric state with rhombohedral (R3c) distortion. It is shown that the structural disorder on the nano-scale opens a new channel for radiative transition which manifests as a new emission line branching off from the main D-5(0)-> F-7(0) line along with a concomitant change in the relative intensity of the other crystal field induced Stark lines with different J values. The study suggests that Eu+3 luminescence can be used to probe the relative degree of field induced structural ordering in relaxor ferroelectrics and also in high performance piezoelectric alloys where electric field couples very strongly with the lattice and structural degrees of freedom. (C) 2015 AIP Publishing LLC.
Can chaos and intransitivity lead to interannual variability

We suggest that the atmosphere–ocean–earth system is unlikely to be intransitive, i.e. to admit two or more possible climates, any one of which, once established, will persist forever. Our reasoning is that even if the system would be intransitive if the external heating could be held fixed, say as in summer, the new heating patterns that actually accompany the advance of the seasons will break up any established summer circulation, and an alternative circulation may develop during the following summer, particularly if chaos has prevailed during the intervening winter. We introduce a very-low-order geostrophic baroclinic “general circulation” model, which may be run with or without seasonal variations of heating. Under perpetual summer conditions the model is intransitive, admitting either weakly oscillating or strongly oscillating westerly flow, while under perpetual winter conditions it is chaotic. When seasonal variations of heating are introduced, weak oscillations prevail through some summers and strong oscillations prevail through others, thus lending support to our original suggestion. We develop some additional properties of the model as a dynamical system, and we speculate as to whether its behaviour has a counterpart in the real world. DOI: 10.1034/j.1600-0870.1990. t01-2-00005.x
Comment: Distribution of Quadratic Forms in Normal Random Variables—Evaluation by Numerical Integration

Rice’s method [SIAM J. Sci. Stat. Comput. , 1 (1980), pp. 438–448] of calculating the cumulative distribution of a random variable by numerically integrating the inversion integral for the characteristic function, described in the paper named in the title, is modified by a different choice of the saddlepoint through which the path of integration passes, a modification that renders the method efficient for values of the variable not only in the tails of the distribution, as in Rice’s paper, but even in the neighborhood of its mean. It is shown how the method can also be applied to calculating the cumulative distribution of a positive-integer-valued random variable from its probability generating function.
An efﬁcient O ( N ) algorithm for computing O ( N 2 ) acoustic wave interactions in large N -obstacle three dimensional conﬁgurations

We develop and implement a fast and memory efﬁcient scheme for sim-ulating the wave interactions between large numbers of particles. This is crucial for iteratively computing a time harmonic acoustic ﬁeld exterior to a conﬁguration of the particles. The main focus of this article is on efﬁcient computation of the wave interactions between the particles in any iterative multiple scattering approach. We develop our algorithm in four stages and demonstrate the efﬁciency of our interaction evaluation algorithm at each stage for conﬁgurations with several thousand convex and non-convex particles. Using this efﬁcient approach, we simulate the full large particle wave propagation models using a ﬂexible GMRES based inner–outer preconditioned multiple scattering iterative technique on a single compute node.