Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Influencing Attitudes Towards the Use of CRM’s Analytical Tools in Organizations

Abstract Background and Purpose: Information solutions for analytical customer relationship management CRM (aCRM IS) that include the use of analytical tools are becoming increasingly important, due organizations’ need for knowledge of their customers and the ability to manage big data. The objective of the research is, therefore, to determine how the organizations’ orientations (process, innovation, and technology) as critical organizational factors affect the attitude towards the use of the analytical tools of aCRM IS. Design/Methodology/Approach: To measure the orientation of the organization (process, innovation, and technology), we redesigned the existing scale, which was validated using exploratory factor analysis. In the next phase, we created a model by which we examined the impact of the organization’s stance in relation to the use of the analytical tools of aCRM IS, where we used multiple regression analysis. The model was verified on a sample of Slovenian Organizations (n=105), which use the analytical tools of aCRM IS for analyzing the data they have on their customers and business partners. Results: In the study we found that all critical factors of the organization, specifically process, technology, and innovation orientation, have a positive impact on the attitudes towards using the analytical tools of aCRM IS. Innovation orientation is particularly important and has the strongest influence on the attitude towards using the analytical tools of aCRM IS. We found that innovation orientation on new ideas, methods, and approaches has the strongest effect, followed by the impact of innovation orientation on acceptance of novelty. Conclusion: The more innovation-, technology-, and process-oriented organizations are, the more positive their attitude towards using the analytical tools of aCRM IS. The study is particularly important for organizations that are introducing an aCRM IS into their business system.
Performance Analysis of CRC Codes for Systematic and Nonsystematic Polar Codes with List Decoding

Successive cancellation list (SCL) decoding of polar codes is an effective approach that can significantly outperform the original successive cancellation (SC) decoding, provided that proper cyclic redundancy-check (CRC) codes are employed at the stage of candidate selection. Previous studies on CRC-assisted polar codes mostly focus on improvement of the decoding algorithms as well as their implementation, and little attention has been paid to the CRC code structure itself. For the CRC-concatenated polar codes with CRC code as their outer code, the use of longer CRC code leads to reduction of information rate, whereas the use of shorter CRC code may reduce the error detection probability, thus degrading the frame error rate (FER) performance. Therefore, CRC codes of proper length should be employed in order to optimize the FER performance for a given signal-to-noise ratio (SNR) per information bit. In this paper, we investigate the effect of CRC codes on the FER performance of polar codes with list decoding in terms of the CRC code length as well as its generator polynomials. Both the original nonsystematic and systematic polar codes are considered, and we also demonstrate that different behaviors of CRC codes should be observed depending on whether the inner polar code is systematic or not.
Technical Note: Interleaved bipolar acquisition and low‐rank reconstruction for water–fat separation in MRI

Purpose To acquire interleaved bipolar data and reconstruct the full data using low‐rank property for water–fat separation. Methods Bipolar acquisition suffers from issues related to gradient switching, the opposite gradient polarities, and other system imperfections, which prevent accurate water–fat separation. In this study, an interleaved bipolar acquisition scheme and a low‐rank reconstruction method were proposed to reduce issues from the bipolar gradients while achieving a short imaging time. The proposed interleaved bipolar acquisition scheme collects echo‐time signals from both gradient polarities; however, the sequence increases the imaging time. To reduce the imaging time, the signals were subsampled at every dimension of k‐space. The low‐rank property of the bipolar acquisition was defined and exploited to estimate the full data from the acquired subsampled data. To eliminate the bipolar issues, in the proposed method, the water–fat separation was performed separately for each gradient polarity, and the results for the positive and negative gradient polarities were combined after the water–fat separation. Results A phantom study and in vivo experiments were conducted on a 3T Siemens Verio system. The results for the proposed method were compared with the results of the fully sampled interleaved bipolar acquisition and the Soliman's method, which was the previous water–fat separation approach for reducing the issues of bipolar gradients and accelerating the interleaved bipolar acquisition. The proposed method provided accurate water and fat images without the issues of bipolar gradients and demonstrated a better performance compared with the results of the previous methods. Conclusions The water–fat separation using the bipolar acquisition has several benefits including a short echo‐spacing time. However, it suffers from bipolar‐gradient issues such as strong gradient switching, system imperfection, and eddy current effects. This study demonstrated that accurate water–fat separated images can be obtained using the proposed interleaved bipolar acquisition and low‐rank reconstruction by using the benefits of the bipolar acquisition while reducing the bipolar‐gradient issues with a short imaging time.
Cortical Mechanisms of Prioritizing Selection for Rejection in Visual Search

In visual search, the more one knows about a target, the faster one can find it. Surprisingly, target identification is also faster with knowledge about distractor-features. The latter is paradoxical, as it implies that to avoid the selection of an item, the item must somehow be selected to some degree. This conundrum has been termed the “ignoring paradox”, and, to date, little is known about how the brain resolves it. Here, in data from four experiments using neuromagnetic brain recordings in male and female humans, we provide evidence that this paradox is resolved by giving distracting information priority in cortical processing. This attentional priority to distractors manifests as an enhanced early neuromagnetic index, which occurs before target-related processing, and regardless of distractor predictability. It is most pronounced on trials for which a response rapidly occurred, and is followed by a suppression of the distracting information. These observations together suggest that in visual search items cannot be ignored without first being selected. SIGNIFICANCE STATEMENT How can we ignore distracting stimuli in our environment? To do this successfully, a logical hypothesis is that as few neural resources as possible should be devoted to distractor processing. Yet, to avoid devoting resources to a distractor, the brain must somehow mark what to avoid; this is a philosophical problem, which has been termed the “ignoring paradox” or “white bear phenomenon”. Here, we use MEG recordings to determine how the human brain resolves this paradox. Our data show that distractors are not only processed, they are given temporal priority, with the brain building a robust representation of the to-be-ignored items. Thus, successful suppression of distractors can only be achieved if distractors are first strongly neurally represented.
Inhibition of Human Immunodeficiency Virus Type 1 Entry by a Keggin Polyoxometalate

Here, we report the anti-human immunodeficiency virus (HIV) potency and underlying mechanisms of a Keggin polyoxometalate (PT-1, K6HPTi2W10O40). Our findings showed that PT-1 exhibited highly potent effects against a diverse group of HIV type 1 (HIV-1) strains and displayed low cytotoxicity and genotoxicity. The time-addition assay revealed that PT-1 acted at an early stage of infection, and these findings were supported by the observation that PT-1 had more potency against Env-pseudotyped virus than vesicular stomatitis virus glycoprotein (VSVG) pseudotyped virus. Surface plasmon resonance binding assays and flow cytometry analysis showed that PT-1 blocked the gp120 binding site in the CD4 receptor. Moreover, PT-1 bound directly to gp41 NHR (N36 peptide), thereby interrupting the core bundle formation of gp41. In conclusion, our data suggested that PT-1 may be developed as a new anti-HIV-1 agent through its effects on entry inhibition.
Firm Orientations

Abstract Firm strategic orientations (product, production, selling, marketing, and societal marketing) are routinely discussed in the introductory chapters of marketing management texts. However, to the best of our knowledge, only one empirical paper has been reported to date (Shoham 1999) and this paper was in the context of domestic operations of Israeli firms. Neither the existence of these orientations nor their performance implications have been examined empirically in an exporting context. This research examines orientations of Israeli firms in their export operations. The data suggest that the five orientations have different effects on export performance. The results highlight the need for future research on the relationships between firm orientations, environmental conditions, and performance.
Large Scale Data Shared by Peer to Peer Based System in Shared Network

Recently, the amount of delicate data produced by many executives is out treading their storage ability. The management of such large amount of data is quite exclusive due to the requirements of high storage capacity and qualified recruits. Storage-as-aService (SaaS) offered by cloud service providers (CSPs) is a paid facility that enables organizations to outsource their data to be stored on remote servers. Thus, SaaS decreases the maintenance cost and diminishes the burden of large local data storage at the organization’s end. A data owner pays for a desired level of security and must get some benefit in case of any difficulties dedicated by the CSP. On the other hand, the CSP needs a protection from any false accusation that may be claimed by the owner to get illegal damages. This paper, proposes a scheme that is used cloud storage system which has efficiency to store large amount of data by the CSP and create trust among them.
A comparison of FFD-based nonrigid registration and AAMs applied to myocardial perfusion MRI

Little work has been done on comparing the performance of statistical model-based approaches and nonrigid registration algorithms. This paper deals with the qualitative and quantitative comparison of active appearance models (AAMs) and a nonrigid registration algorithm based on free-form deformations (FFDs). AAMs are known to be much faster than nonrigid registration algorithms. On the other hand nonrigid registration algorithms are independent of a training set as required to build an AAM. To obtain a further comparison of the two methods, they are both applied to automatically register multi-slice myocardial perfusion images. The images are acquired by magnetic resonance imaging, from infarct patients. A registration of these sequences is crucial for clinical practice, which currently is subjected to manual labor. In the paper, the pros and cons of the two registration approaches are discussed and qualitative and quantitative comparisons are provided. The quantitative comparison is obtained by an analysis of variance of landmark errors, i.e. point to point and point to curve errors. Even though the FFD-based approach does not include a training phase it gave similar accuracy as the AAMs in terms of point to point errors. For the point to curve errors the AAMs provided higher accuracy. In both cases AAMs gave higher precision due to the training procedure.
Reverse-engineering ecological theory from data

Ecologists have long sought to understand the dynamics of populations and communities by deriving mathematical theory from first principles. Theoretical models often take the form of dynamical equations that comprise the ecological processes (e.g. competition, predation) believed to govern system dynamics. The inverse of this approach—inferring which processes and ecological interactions drive observed dynamics—remains an open problem in ecology. Here, we propose a way to attack this problem using a machine learning method known as symbolic regression, which seeks to discover relationships in time-series data and to express those relationships using dynamical equations. We found that this method could rapidly discover models that explained most of the variance in three classic demographic time series. More importantly, it reverse-engineered the models previously proposed by theoretical ecologists to describe these time series, capturing the core ecological processes these models describe and their functional forms. Our findings suggest a potentially powerful new way to merge theory development and data analysis.
Perceptual stereoscopic image quality assessment method with tensor decomposition and manifold learning

Perceptual quality assessment of stereoscopic images is a challenge in three-dimensional video systems. Existing studies suggest that simply averaging the quality of left and right views can effectively predict the quality of symmetrically distorted stereoscopic images, but prediction deviation occurs in the case of asymmetrically distorted stereoscopic images. Most previous stereoscopic image quality assessment (SIQA) methods have been based only on the luminance component of the images; in addition, the basis of human visual perception is critical to image quality assessment and lies on the low-dimensional manifold. Inspired by this, a new perceptual SIQA method is proposed, which includes two stages: training stage and quality prediction stage. In the training stage, the authors apply Tucker decomposition to RGB images to reduce dimensions along colour channels to produce training sets, and the projection matrix is obtained through manifold learning. In the quality prediction stage, considering the binocular visual characteristics of visual perception, the overall stereoscopic estimate depends on the monocular image quality via a local energy ratio based pooling strategy and cyclopean based binocular quality. Extensive experiments on three available benchmark databases demonstrate that the proposed metric has better performance and achieves highly consistent alignment with subjective assessment compared with state-of-the-art SIQA metrics.
The Odorant Binding Protein 6 Expressed in Sensilla Chaetica Displays Preferential Binding Affinity to Host Plants Volatiles in Ectropis obliqua

The monophagous tea geometrid Ectropis obliqua selectively feed on tea plants, requiring the specialized chemosensory system to forage for certain host. A deep insight into the molecular basis would accelerate the design of insect-behavior-modifying stimuli. In the present study, we focused on the odorant-binding protein 6 (EoblOBP6) with the high abundance in legs transcriptome of E. obliqua moths. qRT-PCR coupled with western blot analyses revealed the dual expression pattern of EoblOBP6 in antennae and legs. Cellular immunolocalization indicated that EoblOBP6 was predominantly labeled in the outer sensillum lymph of uniporous sensilla chaetica, which is not innervated by sensory neurons. No specific staining was observed in other sensillum types. The fluorescence competition assay showed a relatively narrow binding spectrum of recombinant EoblOBP6. EoblOBP6 could not only bind with intact tea plant volatiles benzaldehyde but also display high binding ability to nerolidol and α-farnesene which are tea plant volatiles dramatically induced by herbivore infestation. Besides, EoblOBP6 tightly bound to the aversive bitter alkaloid berberine. Taken together, EoblOBP6 displayed an unusual expression in sensilla chaetica, exhibited the potential involvement in olfaction and gustation, and may play a functional role in host location of female E. obliqua moths.
Defoiling Foiled Image Captions

We address the task of detecting foiled image captions, i.e. identifying whether a caption contains a word that has been deliberately replaced by a semantically similar word, thus rendering it inaccurate with respect to the image being described. Solving this problem should in principle require a fine-grained understanding of images to detect subtle perturbations in captions. In such contexts, encoding sufficiently descriptive image information becomes a key challenge. In this paper, we demonstrate that it is possible to solve this task using simple, interpretable yet powerful representations based on explicit object information over multilayer perceptron models. Our models achieve state-of-the-art performance on a recently published dataset, with scores exceeding those achieved by humans on the task. We also measure the upper-bound performance of our models using gold standard annotations. Our study and analysis reveals that the simpler model performs well even without image information, suggesting that the dataset contains strong linguistic bias.
BOMBAY PSYCHIATRIC SOCIETY SILVER JUBILEE AWARD

Religion is a form of coping that helps individuals to deal with a wide variety of difficult life situations. But most of the research in this field has been in acute patients of schizophrenia. Also, most of the research on religion and schizophrenia has focused on religion and spirituality as coping mechanisms, and research evaluating the relationship between spirituality/religiousness and repertoire of other coping skills is sparse. Our objective was to evaluate the association between spirituality, religiousness and coping skills in patients with schizophrenia in remission. Hence, a total of 48 consecutive patients with schizophrenia were assessed on Positive and Negative Syndrome Scale (PANSS), Personal and Social Performance Scale (PSP), WHO Quality of Life-Spirituality, Religiousness and Personal Belief scale (WHOQOL-SRPB) and Ways of Coping Checklist - Revised (WCC). Findings were described as patients who used more religiosity and spirituality as measured with WHO-SRPB domain score were better in their managing their stress as they used all the adaptive strategies like planful problem solving, positive reappraisal, distancing, self-controlling, seeking social support rather than maladaptive skills like confrontive coping and escape avoidance. A sound spiritual, religious, or personal belief system positively affects active and adaptive coping skills in patients with schizophrenia during remission, thus helping the individual to cope with illness related stressors.
Vertical Graphene Nanoribbon Interconnects at the End of the Roadmap

To solve electrical contact problem of horizontal multilayer graphene nanoribbon (GNR), a vertical GNR (VGNR) interconnect scheme is proposed. Performance of the VGNR interconnect is theoretically evaluated and compared with those of conventional interconnect technologies. It is shown that the performance of VGNR is comparable (and even superior) to that of the horizontal GNR (HGNR). Moreover, VGNRs may provide a promising solution to the thermal challenges faced by HGNRs in nanoscale ICs.
Particle Swarm Optimization as Applied to Electromagnetic Design Problems

Particle﻿swarm﻿optimization﻿(PSO)﻿is﻿a﻿swarm﻿intelligence﻿algorithm﻿inspired﻿by﻿the﻿social﻿behavior﻿ of﻿birds﻿flocking﻿and﻿fish﻿schooling. ﻿Numerous﻿PSO﻿variants﻿have﻿been﻿proposed﻿in﻿the﻿literature﻿ for﻿addressing﻿different﻿problem﻿types. ﻿In﻿this﻿article,﻿the﻿authors﻿apply﻿different﻿PSO﻿variants﻿to﻿ common﻿design﻿problems﻿in﻿electromagnetics. ﻿They﻿apply﻿the﻿Inertia﻿Weight﻿PSO﻿(IWPSO),﻿the﻿ Constriction﻿Factor﻿PSO﻿(CFPSO),﻿and﻿the﻿Comprehensive﻿Learning﻿Particle﻿Swarm﻿Optimization﻿ (CLPSO)﻿ algorithms﻿ to﻿ real-valued﻿ optimization﻿ problems,﻿ i.e.﻿ microwave﻿ absorber﻿ design,﻿ and﻿ linear﻿array﻿synthesis. ﻿Moreover,﻿the﻿authors﻿use﻿discrete﻿PSO﻿optimizers﻿such﻿as﻿the﻿binary﻿PSO﻿ (binPSO)﻿and﻿the﻿Boolean﻿PSO﻿with﻿a﻿velocity﻿mutation﻿(BPSO-vm)﻿in﻿order﻿to﻿solve﻿discrete-valued﻿ optimization﻿problems,﻿i.e.﻿patch﻿antenna﻿design. ﻿Additionally,﻿the﻿authors﻿apply﻿and﻿compare﻿binPSO﻿ with﻿different﻿transfer﻿functions﻿to﻿thinning﻿array﻿design﻿problems. ﻿In﻿the﻿case﻿of﻿a﻿multi-objective﻿ optimization﻿problem,﻿they﻿apply﻿two﻿multi-objective﻿PSO﻿variants﻿to﻿dual-band﻿base﻿station﻿antenna﻿ optimization﻿for﻿mobile﻿communications. ﻿Namely,﻿these﻿are﻿the﻿Multi-Objective﻿PSO﻿(MOPSO)﻿and﻿ the﻿Multi-Objective﻿PSO﻿with﻿Fitness﻿Sharing﻿(MOPSO-fs)﻿algorithms. ﻿Finally,﻿the﻿authors﻿conclude﻿ the﻿paper﻿by﻿providing﻿a﻿discussion﻿on﻿future﻿trends﻿and﻿the﻿conclusion. KEywORDS Electromagnetics, Inertia Weight PSO, Particle Swarm Optimization, Social Behavior
Empirical Studies in the Economics of Health Insurance, Health, and Fertility

This thesis is a collection of essays in the economics of health insurance, health, and fertility. The three essays each explore distinct and unconnected research questions. The first study asks whether differences in health risk can explain the systematically different health plan choices made by younger and older US consumers. Finding the answer to be no, the essay then explores the implications of these differential selection patterns by age. The second study asks how much of the glaring disparities in life expectancy between blacks and whites in the US can be accounted for by group differences in socioeconomic factors. The third study asks whether the often-observed negative correlation between educational attainment and fertility reflects a causal relationship. The first two essays are single-authored, with the second published in the journal Demography. The third essay is co-authored with Damon Clark and Heather Royer. These three essays share an emphasis on empirical rather than theoretical contributions, and in all cases they benefit from access to unique or restricted datasets. Nonetheless, the essays differ in the ways they characterize the data used, and the extent to which the quantities of interest are non-parametrically identified. The empirical evidence in the health insurance essay relies most heavily on economic theory for identification. In part, this first essay attempts to identify deep parameters associated with expected utility theory. The fertility essay, in contrast, relies on a natural experiment to identify its parameters of interest, which are the behavioral responses to an educational reform, rather than primitives of a utility function. Finally, the essay on racial disparities in mortality pushes aside the issue of identification, and instead provides a novel and careful accounting of partial correlations between race, socioeconomic status, and mortality. These correlations are important because they have not been previously reported, despite much interest in the research question. The first essay, in more detail, examines how health plan choice varies by age and health risk, and asks whether current pricing restrictions in employer-sponsored health insurance are optimal. US employers cannot charge different insurance premiums on the basis of