Vitamin d and metabolic syndrome risk factors: evidence and mechanisms

The metabolic syndrome develops in an individual with any three of the following risk factors: obesity, diabetes, inflammation, hypertension, dyslipidemia, and thrombosis. Recent evidence suggests that vitamin D may play a role in the development of some of these risk factors. The metabolic syndrome is more common in western societies than the underdeveloped countries. Individuals in western societies usually consume a high calorie diet that lacks essential nutrients and, by virtue of being located in the northern hemisphere, they have limited sun exposures which restrict their vitamin D synthesis. Moreover, the lifestyle of these societies is considered sedentary. These dietary and environmental factors coupled with the sedentary lifestyle predispose them to metabolic syndrome risk factors. Active research revealed the role of vitamin D in the development of obesity, diabetes, inflammation, and hypertension. On the other hand, limited research has been done on the role of vitamin D in other risk factors such as dyslipidemia and thrombosis. The scientific community proposes to increase the current vitamin D fortification level in foods to reduce the risk factors of the metabolic syndrome.     

Novel round-robin tabu search algorithm for prostate cancer classification and diagnosis using multispectral imagery.

Quantitative cell imagery in cancer pathology has progressed greatly in the last 25 years. The application areas are mainly those in which the diagnosis is still critically reliant upon the analysis of biopsy samples, which remains the only conclusive method for making an accurate diagnosis of the disease. Biopsies are usually analyzed by a trained pathologist who, by analyzing the biopsies under a microscope, assesses the normality or malignancy of the samples submitted. Different grades of malignancy correspond to different structural patterns as well as to apparent textures. In the case of prostate cancer, four major groups have to be recognized: stroma, benign prostatic hyperplasia, prostatic intraepithelial neoplasia, and prostatic carcinoma. Recently, multispectral imagery has been used to solve this multiclass problem. Unlike conventional RGB color space, multispectral images allow the acquisition of a large number of spectral bands within the visible spectrum, resulting in a large feature vector size. For such a high dimensionality, pattern recognition techniques suffer from the well-known "curse-of-dimensionality" problem. This paper proposes a novel round-robin tabu search (RR-TS) algorithm to address the curse-of-dimensionality for this multiclass problem. The experiments have been carried out on a number of prostate cancer textured multispectral images, and the results obtained have been assessed and compared with previously reported works. The system achieved 98%-100% classification accuracy when testing on two datasets. It outperformed principal component/linear discriminant classifier (PCA-LDA), tabu search/nearest neighbor classifier (TS-1NN), and bagging/boosting with decision tree (C4.5) classifier.     

The Peril of Evaluating Location Management Proposals through Simulations

The challenge of supporting rapidly growing numbers of mobile users, while constrained by limited radio spectrum, is being faced by cellular network operators worldwide. Several location management schemes have been proposed to improve the performance of such networks, but a fair assessment and comparison of their performance is difficult without an accurate mobility model. The performance of location management schemes depends considerably on subscriber mobility patterns. Some of the recent methods proposed in the literature are reviewed and selected that concentrate on the location updating and paging overhead. To analyze the performance of the selected proposals, two mobility models, namely activity-based mobility model and random mobility model, were used. From the results it is clear that the mobility model has a significant impact and the results described in various proposals using a random mobility model may not reflect the relative performance when deploying schemes in actual systems.     

Offshore Software Maintenance Outsourcing Process Model Validation: A Case Study Approach

The successful execution and management of Offshore Software Maintenance Outsourcing (OSMO) can be very beneficial for OSMO vendors and the OSMO client. Although a lot of research on software outsourcing is going on, most of the existing literature on offshore outsourcing deals with the outsourcing of software development only. Several frameworks have been developed focusing on guiding software system managers concerning offshore software outsourcing. However, none of these studies delivered comprehensive guidelines for managing the whole process of OSMO. There is a considerable lack of research working on managing OSMO from a vendor’s perspective. Therefore, to find the best practices for managing an OSMO process, it is necessary to further investigate such complex and multifaceted phenomena from the vendor’s perspective. This study validated the preliminary OSMO process model via a case study research approach. The results showed that the OSMO process model is applicable in an industrial setting with few changes. The industrial data collected during the case study enabled this paper to extend the preliminary OSMO process model. The refined version of the OSMO process model has four major phases including (i) Project Assessment, (ii) SLA (iii) Execution, and (iv) Risk.     

In Operando Optical Tracking of Oxygen Vacancy Migration and Phase Change in few Nanometers Ferroelectric HZO Memories

Ferroelectric materials offer a low-energy, high-speed alternative to conventional logic and memory circuitry. Hafnia-based films have achieved single-digit nm ferroelectricity, enabling further device miniaturization. However, they can exhibit nonideal behavior, specifically wake-up and fatigue effects, leading to unpredictable performance variation over consecutive electronic switching cycles, preventing large-scale commercialization. The origins are still under debate. Using plasmon-enhanced spectroscopy, a non-destructive technique sensitive to <1% oxygen vacancy variation, phase changes, and single switching cycle resolution, the first real-time in operando nanoscale direct tracking of oxygen vacancy migration in 5 nm hafnium zirconium oxide during a pre-wake-up stage is provided. It is shown that the pre-wake-up leads to a structural phase change from monoclinic to orthorhombic phase, which further determines the device wake-up. Further migration of oxygen ions in the phase changed material is then observed, producing device fatigue. These results provide a comprehensive explanation for the wake-up and fatigue with Raman, photoluminescence and darkfield spectroscopy, combined with density functional theory and finite-difference time-domain simulations.     

De-Noising Brain MRI Images by Mixing Concatenation and Residual Learning (MCR)

Brain magnetic resonance images (MRI) are used to diagnose the different diseases of the brain, such as swelling and tumor detection. The quality of the brain MR images is degraded by different noises, usually salt & pepper and Gaussian noises, which are added to the MR images during the acquisition process. In the presence of these noises, medical experts are facing problems in diagnosing diseases from noisy brain MR images. Therefore, we have proposed a de-noising method by mixing concatenation, and residual deep learning techniques called the MCR de-noising method. Our proposed MCR method is to eliminate salt & pepper and gaussian noises as much as possible from the brain MRI images. The MCR method has been trained and tested on the noise quantity levels 2% to 20% for both salt & pepper and gaussian noise. The experiments have been done on publically available brain MRI image datasets, which can easily be accessible in the experiments and result section. The Structure Similarity Index Measure (SSIM) and Peak Signal-to-Noise Ratio (PSNR) calculate the similarity score between the denoised images by the proposed MCR method and the original clean images. Also, the Mean Squared Error (MSE) measures the error or difference between generated denoised and the original images. The proposed MCR de-noising method has a 0.9763 SSIM score, 84.3182 PSNR, and 0.0004 MSE for salt & pepper noise; similarly, 0.7402 SSIM score, 72.7601 PSNR, and 0.0041 MSE for Gaussian noise at the highest level of 20% noise. In the end, we have compared the MCR method with the state-of-the-art de-noising filters such as median and wiener de-noising filters.     

Physical,Mechanical, and Thermal Characteristics of B2O3 - SiO2- Li2O -Fe2O3 Glasses

Silicon - Glasses of compositions 50.4B2O3 - 30SiO2- $$(19.6-x)$$ Li2O - $$x$$ Fe2O3, $$x$$ = (0 ≤ $$x$$ ≤ 2) were fabricated with molar fraction utilizing the conventional process....     

Versatile Magnetic Mesoporous Carbon Derived Nano-Adsorbent for Synchronized Toxic Metal Removal and Bacterial Disinfection from Water Matrices

Contamination of water resources by toxic metals and opportunistic pathogens remains a serious challenge. The development of nano-adsorbents with desired features to tackle this problem is a continuously evolving field. Here, magnetic mesoporous carbon nanospheres grafted by antimicrobial polyhexamethylene biguanidine (PHMB) are reported. Detailed mechanistic investigations reveal that the electrostatic stabilizer modified magnetic nanocore interfaced mesoporous shell can be programmatically regulated to tune the size and related morphological properties. The core–shell nano-adsorbent shows tailorable shell thickness (≈20–55 nm), high surface area (363.47 m² g⁻¹), pore volume (0.426 cm³ g⁻¹), radially gradient pores (11.26 nm), and abundant biguanidine functionality. Importantly, the nano-adsorbent has high adsorption capacity for toxic thallium (Tl(I) ions (≈559 mg g⁻¹), excellent disinfection against Staphylococcus aureus and Escherichia coli (>99.99% at 2 and 2.5 µg mL⁻¹), ultrafast disinfection kinetics rate (>99.99% within ≈4 min), and remarkable regeneration capability when exposed to polluted water matrices. The Tl(I) removal is attributed to surface complexation and physical adsorption owing to open ended mesopores, while disinfection relies on contact of terminal biguanidines with phospholipid head groups of membrane. The significance of this work lies in bringing up effective synchronic water purification technology to combat pathogenic microorganisms and toxic metal.