Detailed and high-throughput measurement of composition dependence of magnetoresistance and spin-transfer torque using a composition-gradient film: application to Cox_{x}Fe1−x_{1-x} (0 ≤\le x\textit{x} ≤\le 1) system

We develop a high-throughput method for measuring the composition dependence of magnetoresistance (MR) and spin-transfer-torque (STT) effects in current-perpendicular-to-plane giant magnetoresistance (CPP-GMR) devices and report its application to the CoFe system. The method is based on the use of composition-gradient films deposited by combinatorial sputtering. This structure allows the fabrication of devices with different compositions on a single substrate, drastically enhancing the throughput in investigating composition dependence. We fabricated CPP-GMR devices on a single GMR film consisting of a Co$_{x}$Fe$_{1-x}$ (0 $\le$ $\textit{x}$ $\le$ 1) composition-gradient layer, a Cu spacer layer, and a NiFe layer. The MR ratio obtained from resistance-field measurements exhibited the maximum in the broad Co concentration range of 0.3 $\le$ $\textit{x}$ $\le$ 0.65. In addition, the STT efficiency was estimated from the current to induce magnetization reversal of the NiFe layer by spin injection from the Co$_{x}$Fe$_{1-x}$ layer. The STT efficiency was also the highest around the same Co concentration range as for the MR ratio, and this correlation was theoretically explained by the change in the spin polarization of the Co$_{x}$Fe$_{1-x}$ layer. The results revealed the Co$_{x}$Fe$_{1-x}$ composition range suitable for spintronic applications, demonstrating the advantages of the developed method.Comment: 19 pages, 5 figure

IMPORTANCE OF HAIR GROWTH IN HISUTISM: DIAGNOSIS AND TREATMENT

The objective of the review is to explain the pathogenesis, causes and various treatment involved in hirsutism. This article discusses the disease’s pathogenesis, causes and diagnosis. This review looks at the main significant type of hairs and clinical studies on the role of several lifestyle therapies in hirsutism development. This review examines the numerous methods that causes hirsutism in order to discover new medicaments. In addition, it covers the various type of hirsutism therapy. Hirsutism, is reported to have the strongest impact on patients’ health-related quality of life, following in descending order by body mass index, irregular menses, and infertility. To assess the types of hairs and pathogenesis, sign and symptoms, as well as causes of hirsutism. Moreover, we studied the management of hirsutism and how to treat this. At least six to nine months of therapy are required to produce improvement in hirsutism. We suggest testing for elevated androgen levels in women with moderate or severe hirsutism or hirsutism of any degree when it is sudden in onset, rapidly progressive, or associated with other abnormalities such as menstrual dysfunction, obesity, or macroclitoris. For women with patient-important hirsutism despite cosmetic measures, we suggest either pharmacological therapy or direct hair removal methods. For pharmacological therapy, we suggest oral contraceptives for the majority of women, adding an Antiandrogens after 6 mo if the response is suboptimal. We recommend against androgen antagonist monotherapy unless adequate contraception is used. We suggest against using insulin-lowering drugs. For women who choose hair removal therapy, we suggest laser/photo epilation

Cellular oxido-reductive proteins of Chlamydomonas reinhardtii control the biosynthesis of silver nanoparticles

<p>Abstract</p> <p>Background</p> <p>Elucidation of molecular mechanism of silver nanoparticles (SNPs) biosynthesis is important to control its size, shape and monodispersity. The evaluation of molecular mechanism of biosynthesis of SNPs is of prime importance for the commercialization and methodology development for controlling the shape and size (uniform distribution) of SNPs. The unicellular algae <it>Chlamydomonas reinhardtii </it>was exploited as a model system to elucidate the role of cellular proteins in SNPs biosynthesis.</p> <p>Results</p> <p>The <it>C. reinhardtii </it>cell free extract (<it>in vitro</it>) and <it>in vivo </it>cells mediated synthesis of silver nanoparticles reveals SNPs of size range 5 ± 1 to 15 ± 2 nm and 5 ± 1 to 35 ± 5 nm respectively. <it>In vivo </it>biosynthesized SNPs were localized in the peripheral cytoplasm and at one side of flagella root, the site of pathway of ATP transport and its synthesis related enzymes. This provides an evidence for the involvement of oxidoreductive proteins in biosynthesis and stabilization of SNPs. Alteration in size distribution and decrease of synthesis rate of SNPs in protein-depleted fractions confirmed the involvement of cellular proteins in SNPs biosynthesis. Spectroscopic and SDS-PAGE analysis indicate the association of various proteins on <it>C. reinhardtii </it>mediated <it>in vivo </it>and <it>in vitro </it>biosynthesized SNPs. We have identified various cellular proteins associated with biosynthesized (<it>in vivo </it>and <it>in vitro) </it>SNPs by using MALDI-MS-MS, like ATP synthase, superoxide dismutase, carbonic anhydrase, ferredoxin-NADP⁺reductase, histone etc. However, these proteins were not associated on the incubation of pre-synthesized silver nanoparticles <it>in vitro</it>.</p> <p>Conclusion</p> <p>Present study provides the indication of involvement of molecular machinery and various cellular proteins in the biosynthesis of silver nanoparticles. In this report, the study is mainly focused towards understanding the role of diverse cellular protein in the synthesis and capping of silver nanoparticles using <it>C. reinhardtii </it>as a model system.</p

Proximally migrated Double J stent in hydronephrotic kidneys: Etiological factors and management

Double J stents have become an essential tool in urologist’s armamentarium but are never without potential complications. Migration of DJ stent is a recognized complication, though its proximal migration into the upper ureter, pelvicalyceal system is reported rarely. This can add to the cost of patients and increases hospital stay if another general/ regional anesthesia session is required for its repositioning/removal. We successfully repositioned or removed proximally migrated DJ stents ureteroscopically under local anesthesia and analgesia in all of our case series patients on a daycare basis. We emphasize the importance of recordkeeping and follow up of stented patients particularly with those with hydronephrotic systems. In the event of proximal migration of the DJ stent, it can be successfully repositioned or removed under local anesthesia and analgesia. Keywords: Double J stent, proximal migration, ESWL-Extracorporeal shockwave lithotrips

Machine Learning-Based Hybrid Recommendation (SVOF-KNN) Model For Breast Cancer Coimbra Dataset Diagnosis

An effective way to identify breast cancer is by creating a prediction algorithm using risk factors. Models for ML have been used to improve the effectiveness of early detection. This article analyses a KNN combined with singular value decomposition and Grey wolf optimization(GWO) method to give a detection of breast cancer(BC) at the early phase depending on risk metrics. The SVD technique was utilized to eliminate the reliable feature vectors, the GW optimizer was used to select the feature vectors, and while KNN model was used to diagnose the BC status. The proposed hybrid recommendation model (SVOF-KNN) for BC prediction's main objective is to give an accurate recommendation for BC prognosis through four different steps such as;BCCD dataset collection, data pre-processing, feature selection, and classification/recommendation. It is implemented to classify the consequence of risk metrics connected withregular blood analysis(BA) in the BCCD database. The aspects of the BC dataset are insulin, glucose, HOMA, Leptin, resistin, etc. The error categories such as RMSE and MAE are used to calculate the exception values for each instance of the BC dataset. It hybrid model has recommended the best score instance having the minimumexception rateas the defined features for BC prediction. It improves significance in automatic BC classification with the optimum solution. The hybrid recommendation model (SVOF-KNN) also recommends the accurateclassification method for BC diagnosis. The results of this work shall enhance the QoS in BC care

CASSIA FISTULA: BOTANY, PHYTOCHEMISTRY AND PHARMACOLOGICAL LEVERAGES-A REVIEW

Cassia fistula Linn. is also called a “golden shower”. It is aboriginal to India, Sri Lanka and diffused in various countries, including Mexico, China, Mauritius, East Africa, South Africa, and West Indies. Plant and its parts, such as bark, fruit, leaves, and seeds, are used traditionally to cure diseases. Traditionally the plant possesses hepatoprotective, antipyretic, anti-inflammatory, leukotriene inhibition, antitussive activity, antioxidant, wound healing, hypo-lipidemia, anticancer, antidiabetic, central nervous system activity, antiulcer, antibacterial, antifertility, larvicidal and ovicidal, antifeedant, laxative, anti-epileptic, antimicrobial, urease inhibition, antifungal, anti-tobacco mosaic virus activities. The review contains botanical information, constituents and pharmacological leverages of the plant. The review draws attention towards the traditional, phytochemical and pharmacological knowledge accessible on Cassia fistula Linn, which would be beneficial for research scholars to develop novel chemical entities. This review article is written after studying most of the journal’s articles, which were published between 1998 to 2019

Medicinally Important Phytoconstituents of Sweet Flag (Acorus Calamus): A Critical Overview

Now a day there has been a notable increase in interest in medicinal plants. The cause of this is growing knowledge of the limitations of synthetic chemotherapeutic drugs. Natural products and herbal remedies are currently highly sought after worldwide. Ayurveda serve as a “goldmine” for novel medicinal products to treat various chronic diseases. This review article provides the detailed description of Acorus calamus (Vacha) one of most important medicinal plant. Acorus calamus (Sweet flag) used in the treatment of various illnesses such as epilepsy, memory loss, dysentery, chronic diarrhea, intermittent fever etc. A broad range of chemical constituents isolated &nbsp;from the rhizomes and leaves part includes A-asarone, b-asarone, c-asarone, calamene, calamenenol, calameone, a-pinene, b-pinene etc. From a long ago Acorus calamus has been used for various purposes and many of its uses has to be scientifically not proven. The present review attempt to explore its traditional uses and pharmacological bioactive compounds present in it.&nbsp

Genetic and Phenotypic Correlations between Production and Reproduction Traits in Frieswal Cattle under Field Progeny Testing Programme

Aim: To estimate the genetic and phenotypic correlations in production and reproduction traits in Frieswal Cattle under FPT. Place and Duration of Study: G B Pant University of Agricultural and Technology, Pantnagar, Uttarakhand, India, Between March, 2023 to March, 2024. Methodology: The present study was conducted on Frieswal cattle, a synthetic breed, using data from 1163 first lactation records, progenies of 67 sires, spread over period of nine years (2013-2021) as part of an ongoing field progeny testing programme at GBPUA&amp;T, Pantnagar, Uttarakhand. The study aimed to estimate genetic and phenotypic correlations among various production and reproduction traits, such as test day peak yield (TDPY), first lactation 305-days milk yield (FL305D-MY), fat percentage (FP), first lactation length (FLL), age at sexual maturity (ASM), age at first calving (AFC), gestation period (GP), first calving interval (FCI), first service period (FSP), and number of services per conception (NSPC).The data were analyzed using WOMBAT software. Results: The study revealed that age at first service (ASM) and age at first calving (AFC) had very high genetic (0.99) and phenotypic (0.99) correlations, suggesting they were influenced by the same genes. A strong genetic correlation (0.71) between ASM and gestation period (GP) indicates a close association, while the negative correlation between ASM and total days to peak yield (TDPY) (-0.76) suggests younger cows reach higher peak yields. ASM’s negative genetic correlation (-0.57) with first lactation 305-days milk yield (FL305D-MY) implied that selecting for earlier maturity could enhance milk production. Positive correlation between ASM and reproductive traits (FCI, FSP, NSPC, and FDP) were observed, while FL305D-MY showed high negative correlation with traits like FLL and FP but positive phenotypic correlation with FLL, FCI, and FSP. Additionally, there were varied genetic correlation among FCI, FSP, NSPC and FDP, highlighting complex inter-trait relationships. Conclusions: The present study highlighted the potential of Frieswal herd for selective breeding to improve both milk production and reproductive efficiency. By focusing on traits like age at sexual maturity (ASM), age at first calving (AFC), and milk yield indicators such as test day peak yield (TDPY) and first lactation 305-days milk yield (FL305D-MY), breeders can target genetically associated traits for enhanced overall productivity. These findings provide a valuable foundation for future genetic improvement strategies in Frieswal cattle

Natural Language Processing and Machine Learning-Based Solution of Cold Start Problem Using Collaborative Filtering Approach

In today’s digital era, the abundance of online services presents users with a daunting array of choices, spanning from streaming platforms to e-commerce websites, leading to decision fatigue. Recommendation algorithms play a pivotal role in aiding users in navigating this plethora of options, among which collaborative filtering (CF) stands out as a prevalent technique. However, CF encounters several challenges, including scalability issues, privacy implications, and the well-known cold start problem. This study endeavors to mitigate the cold start problem by harnessing the capabilities of natural language processing (NLP) applied to user-generated reviews. A unique methodology is introduced, integrating both supervised and unsupervised NLP approaches facilitated by sci-kit learn, utilizing benchmark datasets across diverse domains. This study offers scientific contributions through its novel approach, ensuring rigor, precision, scalability, and real-world relevance. It tackles the cold start problem in recommendation systems by combining natural language processing (NLP) with machine learning and collaborative filtering techniques, addressing data sparsity effectively. This study emphasizes reproducibility and accuracy while proposing an advanced solution that improves personalization in recommendation models. The proposed NLP-based strategy enhances the quality of user-generated content, consequently refining the accuracy of Collaborative Filtering-Based Recommender Systems (CFBRSs). The authors conducted experiments to test the performance of the proposed approach on benchmark datasets like MovieLens, Jester, Book-Crossing, Last.fm, Amazon Product Reviews, Yelp, Netflix Prize, Goodreads, IMDb (Internet movie Database) Data, CiteULike, Epinions, and Etsy to measure global accuracy, global loss, F-1 Score, and AUC (area under curve) values. Assessment through various techniques such as random forest, Naïve Bayes, and Logistic Regression on heterogeneous benchmark datasets indicates that random forest is the most effective method, achieving an accuracy rate exceeding 90%. Further, the proposed approach received a global accuracy above 95%, a global loss of 1.50%, an F-1 Score of 0.78, and an AUC value of 92%. Furthermore, the experiments conducted on distributed and global differential privacy (GDP) further optimize the system’s efficacy.publishedVersio

Quality of life among lung cancer patients undergoing treatment at a tertiary cancer institute in North India

Background: Lung cancer patients mostly present with advanced disease. Its treatment has shown limited progress in recent decades, so we studied their quality of life (QOL) and how it is affected during treatment.Methods: Patients ≥18 years of age, diagnosed/registered at our institute from 1st September 2012 through August 2013 were included in the study. QOL was assessed by means of the EORTC QLQ-C30 and QLQ-LC13. Data was analyzed using descriptive and inferential statisticsResults: Out of 91 patients included in the study, 73 (80.2%) were males and 18 (19.8%) were females. Mean age of the study population was 59.24±10.53 years and median age was 60 years. A better QOL for nausea and vomiting (P=0.011), sleep disturbance (p=0.021), and coughing (p=0.016) was observed in female patients. There was significant worsening in symptom scales of fatigue (p=0.000), nausea and vomiting (p=0.000), sleep (0.006), appetite (p=0.000) and constipation (p=0.000). Though the mean scores of pain, dyspnoea and financial difficulties decreased, but they were not significant. According to the LC13 module, significant improvement was seen in the symptom scales of cough (p=0.000), haemoptysis (p=0.000) and pain chest (p=0.040).Conclusions: Lung cancer patients undergoing treatment suffer many limitations due to an array of symptoms and disruptions in various areas of QOL, arising from both the disease process and its treatment. It should be studied at every visit for each individual patient