A Path Analysis of Factors Affecting Social Control of Cybercultural Transgressions

Social control of cyberspace is a necessity to restrict online transgressions (non-normative behaviors), and reduce their disruptive effects. The current study aimed at examining the factors affecting social control of cybercultural transgressions. A questionnaire was administered to Iranian social media users, and 989 participants have filled it out. A path analysis model was constructed testing the effects of Low Self-Control, Depression, Negative Interpersonal Relationships, Computer/ Internet Self-Efficacy, Netiquette, and Normative Beliefs on Transgressive Behaviors, and Transgressive Content Consumption. The results showed that Low Self-Control increased both criterion variables, and fully or partially mediated the effects of other variables on them, except for Negative Interpersonal Relationships. The important contribution of the current study was the recognition of the role of self-control as a mediator among examined variables. The findings of this study can be employed to devise new policies and initiatives to socially control the cybercultural transgressions, without applying coercion

Serum-based metabolic alterations in patients with papillary thyroid carcinoma unveiled by non-targeted 1H-NMR metabolomics approach

Objective(s): As the most prevalent endocrine system malignancy, papillary thyroid carcinoma had a very fast rising incidence in recent years for unknown reasons besides the fact that the current methods in thyroid cancer diagnosis still hold some limitations. Therefore, the aim of this study was to improve the potential molecular markers for diagnosis of benign and malignant thyroid nodules to prevent unnecessary surgeries for benign tumors. Materials and Methods: In this study, 1H-NMR metabolomics platform was used to seek the discriminating serum metabolites in malignant papillary thyroid carcinoma (PTC) compared to benign multinodular goiter (MNG) and healthy subjects and also to better understand the disease mechanisms using bioinformatics analysis. Multivariate statistical analysis showed that PTC and MNG samples could be successfully discriminated in PCA and OPLS-DA score plots. Results: Significant metabolites that differentiated malignant and benign thyroid lesions included citrate, acetylcarnitine, glutamine, homoserine, glutathione, kynurenine, nicotinic acid, hippurate, tyrosine, tryptophan, β-alanine, and xanthine. The significant metabolites in the PTC group compared to healthy subjects also included scyllo- and myo-inositol, tryptophan, propionate, lactate, homocysteine, 3-methyl glutaric acid, asparagine, aspartate, choline, and acetamide. The metabolite sets enrichment analysis demonstrated that aspartate metabolism and urea cycle were the most important pathways in papillary thyroid cancer progression. Conclusion: The study results demonstrated that serum metabolic fingerprinting could serve as a viable method for differentiating various thyroid lesions and for proposing novel potential markers for thyroid cancers. Obviously, further studies are needed for the validation of the results

Predicting sex as a soft-biometrics from device interaction swipe gestures

Touch and multi-touch gestures are becoming the most common way to interact with technology such as smart phones, tablets and other mobile devices. The latest touch-screen input capacities have tremendously increased the quantity and quality of available gesture data, which has led to the exploration of its use in multiple disciplines from psychology to biometrics. Following research studies undertaken in similar modalities such as keystroke and mouse usage biometrics, the present work proposes the use of swipe gesture data for the prediction of soft-biometrics, specifically the user's sex. This paper details the software and protocol used for the data collection, the feature set extracted and subsequent machine learning analysis. Within this analysis, the BestFirst feature selection technique and classification algorithms (naïve Bayes, logistic regression, support vector machine and decision tree) have been tested. The results of this exploratory analysis have confirmed the possibility of sex prediction from the swipe gesture data, obtaining an encouraging 78% accuracy rate using swipe gesture data from two different directions. These results will hopefully encourage further research in this area, where the prediction of soft-biometrics traits from swipe gesture data can play an important role in enhancing the authentication processes based on touch-screen devices

The impact of privacy protection filters on gender recognition

Deep learning-based algorithms have become increasingly efficient in recognition and detection tasks, especially when they are trained on large-scale datasets. Such recent success has led to a speculation that deep learning methods are comparable to or even outperform human visual system in its ability to detect and recognize objects and their features. In this paper, we focus on the specific task of gender recognition in images when they have been processed by privacy protection filters (e.g., blurring, masking, and pixelization) applied at different strengths. Assuming a privacy protection scenario, we compare the performance of state of the art deep learning algorithms with a subjective evaluation obtained via crowdsourcing to understand how privacy protection filters affect both machine and human vision

Design of a high-performance optical tweezer for nanoparticle trapping

Integrated optical nanotweezers offer a novel paradigm for optical trapping, as their ability to confine light at the nanoscale leads to extremely high gradient forces. To date, nanotweezers have been realized either as photonic crystal or as plasmonic nanocavities. Here, we propose a nanotweezer device based on a hybrid photonic/plasmonic cavity with the goal of achieving a very high quality factor-to-mode volume (Q/V) ratio. The structure includes a 1D photonic crystal dielectric cavity vertically coupled to a bowtie nanoantenna. A very high Q/V ~ 107 (λ/n)−3 with a resonance transmission T = 29 % at λR = 1381.1 nm has been calculated by 3D finite element method, affording strong light–matter interaction and making the hybrid cavity suitable for optical trapping. A maximum optical force F = −4.4 pN, high values of stability S = 30 and optical stiffness k = 90 pN/nm W have been obtained with an input power Pin = 1 mW, for a polystyrene nanoparticle with a diameter of 40 nm. This performance confirms the high efficiency of the optical nanotweezer and its potential for trapping living matter at the nanoscale, such as viruses, proteins and small bacteria

Carcinoid Tumor of the Common Bile Duct Misdiagnosed as Cholangiocarcinoma

Carcinoid tumors of the bile duct are rare. Despite cholangiocarcinoma, they grow more slowly and generally occur in younger patients and females. These tumors have a better prognosis and more disease-free survival. We present the case of a 25-year-old male with common bile duct (CBD) carcinoid tumor misdiagnosed ascholangiocarcinoma

Spermatic cord metastasis as early manifestation of small bowel adenocarcinoma

Malignant tumors of the spermatic cord are rare. There are a few case reports on spermatic cord metastasis from colonic, gastric, pancreas, and prostatic cancer. Here, we report a 36-year-old man with brucellosis presenting with spermatic cord metastasis as early manifestation of small bowel adenocarcinoma