Purposes of Using Information by Iranian and Indian Social Science Faculty Members: A Comparative Study

The present study aims at comparing purposes of using information by Iranian and Indian Social Science Faculty Members. Totally, 487 respondents (232 from Iran and 255 from India) were randomly selected from both countries. A questionnaire measuring extent of usage for various purposes—to prepare for teaching, to carry out research, to write research proposal, to design and develop research tools, to write articles/books, to deliver special lectures, to plan program /activity, to evolve innovative techniques, to crystallize broad and vague assertions, to maintain professional competence and self- improvement—was prepared by the investigator and administered to the sample selected.  Contingency coefficient analysis was employed to verify the hypothesis. Results revealed that teaching and research as purposes of using information were higher for Iranian faculty members than Indian faculty members. In development of research tools, writing articles/books and delivering special lectures, again Iranian faculty members used much more information.  To get clarity also Iranian faculty members used more information than Indian faculty members.  It is suggested that in India more facilities should be provided to increase the information usage for various purposes

Discrepancy of target sites between clinician and cytopathological reports in head neck fine needle aspiration: Did I miss the target or did the clinician mistake the organ site?

The diagnostic accuracy of fine needle aspiration cytology (FNAC) of head and neck lesions is relatively high, but cytologic interpretation might be confusing if the sample is lacking typical cytologic features according to labeled site by physician. These errors may have an impact on pathology search engines, healthcare costs or even adverse outcomes. The cytology archive database of multiple institutions in southern Iran and Australia covering the period 2001–2011, were searched using keywords: salivary gland, head, neck, FNAC, and cytology. All the extracted reports were reviewed. The reports which showed discordance between the clinician’s impression of the organ involved and subsequent fine needle biopsy request, and the eventual cytological diagnosis were selected. The cytological diagnosis was confirmed by histology or cell block, with assistance from imaging, clinical outcome, physical examination, molecular studies, or microbiological culture. The total number of 10,200 head and neck superficial FNAC were included in the study, from which 48 cases showed discordance between the clinicians request and the actual site of pathology. Apart from the histopathology, the imaging, clinical history, physical examination, immunohistochemical study, microbiologic culture and molecular testing helped to finalize the target organ of pathology in 23, 6, 7, 8, 2, and 1 cases respectively. The commonest discrepancies were for FNAC of “salivary gland” [total: 20 with actual final pathology in: bone (7), soft tissue (5), lymph node (3), odontogenic (3) and skin (2)], “lymph node” [total: 12 with final pathology in: soft tissue (3), skin (3), bone (1) and brain (1)], “soft tissue” [total: 11 with final pathology in: bone (5), skin (2), salivary gland (1), and ocular region (1)] and “skin” [total: 5 with final pathology in: lymph node (2), bone (1), soft tissue (1) and salivary gland (1)]. The primary physician requesting FNAC of head and neck lesions are incorrect in their clinical impression of the actual site in nearly 0.5 percent of cases, due to the overlapping clinical and imaging findings or possibly due to inadequate history taking or physical examination

Robust Matrix Completion

This paper considers the problem of recovery of a low-rank matrix in the situation when most of its entries are not observed and a fraction of observed entries are corrupted. The observations are noisy realizations of the sum of a low rank matrix, which we wish to recover, with a second matrix having a complementary sparse structure such as element-wise or column-wise sparsity. We analyze a class of estimators obtained by solving a constrained convex optimization problem that combines the nuclear norm and a convex relaxation for a sparse constraint. Our results are obtained for the simultaneous presence of random and deterministic patterns in the sampling scheme. We provide guarantees for recovery of low-rank and sparse components from partial and corrupted observations in the presence of noise and show that the obtained rates of convergence are minimax optimal

One-Pass Ranking Models for Low-Latency Product Recommendations

Purchase logs collected in e-commerce platforms provide rich information about customer preferences. These logs can be leveraged to improve the quality of product recommenda-tions by feeding them to machine-learned ranking models. However, a variety of deployment constraints limit the näıve applicability of machine learning to this problem. First, the amount and the dimensionality of the data make in-memory learning simply not possible. Second, the drift of customers’ preference over time require to retrain the ranking model regularly with freshly collected data. This limits the time that is available for training to prohibitively short intervals. Third, ranking in real-time is necessary whenever the query complexity prevents us from caching the predictions. This constraint requires to minimize prediction time (or equiva

Low Complexity Regularization of Linear Inverse Problems

Inverse problems and regularization theory is a central theme in contemporary signal processing, where the goal is to reconstruct an unknown signal from partial indirect, and possibly noisy, measurements of it. A now standard method for recovering the unknown signal is to solve a convex optimization problem that enforces some prior knowledge about its structure. This has proved efficient in many problems routinely encountered in imaging sciences, statistics and machine learning. This chapter delivers a review of recent advances in the field where the regularization prior promotes solutions conforming to some notion of simplicity/low-complexity. These priors encompass as popular examples sparsity and group sparsity (to capture the compressibility of natural signals and images), total variation and analysis sparsity (to promote piecewise regularity), and low-rank (as natural extension of sparsity to matrix-valued data). Our aim is to provide a unified treatment of all these regularizations under a single umbrella, namely the theory of partial smoothness. This framework is very general and accommodates all low-complexity regularizers just mentioned, as well as many others. Partial smoothness turns out to be the canonical way to encode low-dimensional models that can be linear spaces or more general smooth manifolds. This review is intended to serve as a one stop shop toward the understanding of the theoretical properties of the so-regularized solutions. It covers a large spectrum including: (i) recovery guarantees and stability to noise, both in terms of $\ell^2$-stability and model (manifold) identification; (ii) sensitivity analysis to perturbations of the parameters involved (in particular the observations), with applications to unbiased risk estimation ; (iii) convergence properties of the forward-backward proximal splitting scheme, that is particularly well suited to solve the corresponding large-scale regularized optimization problem

Determinants of consumers’ intentions to share knowledge and intentions to purchase on s-commerce sites: incorporating attitudes toward persuasion attempts into a social exchange model

This research explores s-commerce users’ intentions to purchase and to share knowledge by incorporating ‘attitudes toward persuasion attempts,’ ‘ease of use,’ and ‘perceived usefulness’ into a social exchange theory model. A survey using an on-site purposive sampling technique was used to recruit the respondents, and an interception technique was used to approach the consumers. A total of 471 Korean consumers participated in this research. Based on 471 Korean social-commerce users, our results reveal that social exchange belief factors and a site’s usability affect user satisfaction, which subsequently affects users’ intentions to purchase and to share knowledge. In addition, attitudes toward persuasion attempts moderate the effect of satisfaction on users’ purchase intentions. Keywords: social exchange theory, attitudes toward persuasion attempts, intention to share knowledge, social exchange belief

Cross-education does not accelerate the rehabilitation of neuromuscular functions after ACL reconstruction: a randomized controlled clinical trial

Purpose: Cross-education reduces quadriceps weakness 8 weeks after anterior cruciate ligament (ACL) surgery, but the long-term effects are unknown. We investigated whether cross-education, as an adjuvant to the standard rehabilitation, would accelerate recovery of quadriceps strength and neuromuscular function up to 26 weeks post-surgery. Methods: Group allocation was randomized. The experimental (n = 22) and control (n = 21) group received standard rehabilitation. In addition, the experimental group strength trained the quadriceps of the non-injured leg in weeks 1–12 post-surgery (i.e., cross-education). Primary and secondary outcomes were measured in both legs 29 ± 23 days prior to surgery and at 5, 12, and 26 weeks post-surgery. Results: The primary outcome showed time and cross-education effects. Maximal quadriceps strength in the reconstructed leg decreased 35% and 12% at, respectively, 5 and 12 weeks post-surgery and improved 11% at 26 weeks post-surgery, where strength of the non-injured leg showed a gradual increase post-surgery up to 14% (all p ≤ 0.015). Limb symmetry deteriorated 9–10% more for the experimental than control group at 5 and 12 weeks post-surgery (both p ≤ 0.030). One of 34 secondary outcomes revealed a cross-education effect: Voluntary quadriceps activation of the reconstructed leg was 6% reduced for the experimental vs. control group at 12 weeks post-surgery (p = 0.023). Both legs improved force control (22–34%) and dynamic balance (6–7%) at 26 weeks post-surgery (all p ≤ 0.043). Knee joint proprioception and static balance remained unchanged. Conclusion: Standard rehabilitation improved maximal quadriceps strength, force control, and dynamic balance in both legs relative to pre-surgery but adding cross-education did not accelerate recovery following ACL reconstruction

Manufacturing and Supply Chain Flexibility: Building an Integrative Conceptual Model Through Systematic Literature Review and Bibliometric Analysis

The purpose of this study is twofold: first, to establish the current themes on the topic of manufacturing and supply chain flexibility (MSCF), assess their level of maturity in relation to each other, identify the emerging ones and reflect on how they can inform each other, and second, to develop a conceptual model of MSCF that links different themes connect and highlight future research opportunities. The study builds on a sample of 222 articles published from 1996 to 2018 in international, peer-reviewed journals. The analysis of the sample involves two complementary approaches: the co-word technique to identify the thematic clusters as well as their relative standing and a critical reflection on the papers to explain the intellectual content of these thematic clusters. The results of the co-word analysis show that MSCF is a dynamic topic with a rich and complex structure that comprises five thematic clusters. The value chain, capability and volatility clusters showed research topics that were taking a central role in the discussion on MSCF but were not mature yet. The SC purchasing practices and SC planning clusters involved work that was more focused and could be considered more mature. These clusters were then integrated in a framework that built on the competence–capability perspective and identified the major structural and infrastructural elements of MSCF as well as its antecedents and consequences. This paper proposes an integrative framework helping managers keep track the various decisions they need to make to increase flexibility from the viewpoint of the entire value chain