Statistical optimization of compression coated ketoprofen tablet using amylose/ethyl cellulose mixture for colonic delivery

In the present study the effect of two independent factors (amount of ethyl cellulose in coating layer and coating level) on ketoprofen release from compression coated tablet in order to optimize coated tablet for colonic delivery. 3 2 factorial design was used for designing coated formulation. Amount of ethyl cellulose (X1) and coating level (X2) were selected as independent variables. The studied responses were drug release at 5 hr (Y1) and drug release at 10 hr (Y2). The core tablets were compression coated with different ratio of amylose and ethylcellulose. In vitro drug release study was carried out in pH1.2 for 2 hr, pH 7.4 for 3 hr and goat caecal medium for 5 hr. Drug release revealed that amount of ethyl cellulose and coating level have antagonistic effect on drug release. Multiple regression analysis was used for generation of polynomial equation and optimization of formulation. The optimized formulation consisted of ethyl cellulose (14.33 %) and coating level (318 mg) provided a release profile that is closed to estimated values. The model is found to be accurate and robust for optimization of compression-coated tablet for colonic delivery of ketoprofe

Range-enhanced packet classification to improve computational performance on field programmable gate array

Multi-filed packet classification is a powerful classification engine that classifies input packets into different fields based on predefined rules. As the demand for the internet increases, efficient network routers can support many network features like quality of services (QoS), firewalls, security, multimedia communications, and virtual private networks. However, the traditional packet classification methods do not fulfill today’s network functionality and requirements efficiently. In this article, an efficient range enhanced packet classification (REPC) module is designed using a range bit-vector encoding method, which provides a unique design to store the precomputed values in memory. In addition, the REPC supports range to prefix features to match the packets to the corresponding header fields. The synthesis and implementation results of REPC are analyzed and tabulated in detail. The REPC module utilizes 3% slices on Artix-7 field programmable gate array (FPGA), works at 99.87 Gbps throughput with a latency of 3 clock cycles. The proposed REPC is compared with existing packet classification approaches with better hardware constraints improvements

High performance modified bit-vector based packet classification module on low-cost FPGA

The packet classification plays a significant role in many network systems, which requires the incoming packets to be categorized into different flows and must take specific actions as per functional and application requirements. The network system speed is continuously increasing, so the demand for the packet classifier also increased. Also, the packet classifier's complexity is increased further due to multiple fields should match against a large number of rules. In this manuscript, an efficient and high performance modified bitvector (MBV) based packet classification (PC) is designed and implemented on low-cost Artix-7 FPGA. The proposed MBV based PC employs pipelined architecture, which offers low latency and high throughput for PC. The MBV based PC utilizes <2% slices, operating at 493.102 MHz, and consumes 0.1 W total power on Artix-7 FPGA. The proposed PC considers only 4 clock cycles to classify the incoming packets and provides 74.95 Gbps throughput. The comparative results in terms of hardware utilization and performance efficiency of proposed work with existing similar PC approaches are analyzed with better constraints improvement

Prognóstico de exploração no Chat GPT com ética de inteligência artificial

Natural language processing innovations in the past few decades have made it feasible to synthesis and comprehend coherent text in a variety of ways, turning theoretical techniques into practical implementations. Both report summarizing software and sectors like content writers have been significantly impacted by the extensive Language-model. A huge language model, however, could show evidence of social prejudice, giving moral as well as environmental hazards from negligence, according to observations. Therefore, it is necessary to develop comprehensive guidelines for responsible LLM (Large Language Models). Despite the fact that numerous empirical investigations show that sophisticated large language models has very few ethical difficulties, there isn't a thorough investigation and consumers study of the legality of present large language model use. We use a qualitative study method on OpenAI's ChatGPT3 to solution-focus the real-world ethical risks in current large language models in order to further guide ongoing efforts on responsibly constructing ethical large language models. We carefully review ChatGPT3 from the four perspectives of bias and robustness. According to our stated opinions, we objectively benchmark ChatGPT3 on a number of sample datasets. In this work, it was found that a substantial fraction of principled problems are not solved by the current benchmarks; therefore new case examples were provided to support this. Additionally discussed were the importance of the findings regarding ChatGPT3's AI ethics, potential problems in the future, and helpful design considerations for big language models. This study may provide some guidance for future investigations into and mitigation of the ethical risks offered by technology in large Language Models applications.Las innovaciones en el procesamiento del lenguaje natural en las últimas décadas han hecho posible sintetizar y comprender textos coherentes en una variedad de formas, transformando las técnicas teóricas en implementaciones prácticas. Ambos informan que el software extenso y las industrias como la de los creadores de contenido se han visto significativamente afectadas por el modelo de lenguaje extensivo. Sin embargo, un modelo de lenguaje enorme podría mostrar evidencia de sesgo social, dando riesgos morales y ambientales por negligencia, según las observaciones. Por lo tanto, es necesario desarrollar lineamientos completos para los LLM (Modelos de Lenguaje Grandes) responsables. A pesar de que numerosas investigaciones empíricas muestran que los modelos sofisticados de lenguaje amplio tienen muy pocas dificultades éticas, no existe una investigación exhaustiva y un estudio del consumidor sobre la legalidad del uso actual de modelos de lenguaje amplio. Usamos un método de estudio cualitativo en ChatGPT3 de OpenAI para enfocarnos en resolver los riesgos éticos del mundo real en los modelos actuales de lenguaje amplio para guiar aún más los esfuerzos en curso en la construcción responsable de modelos éticos de lenguaje amplio. Analizamos cuidadosamente ChatGPT3 desde las cuatro perspectivas de sesgo y robustez. De acuerdo con nuestras opiniones expresadas, comparamos ChatGPT3 objetivamente en múltiples conjuntos de datos de muestra. En este trabajo se encontró que una fracción sustancial de los problemas de principios no son resueltos por los marcos actuales; por lo tanto, se han proporcionado nuevos ejemplos de casos para respaldar esto. Además, se discutió la importancia de los hallazgos sobre la ética de la IA de ChatGPT3, los problemas potenciales en el futuro y las consideraciones de diseño útiles para modelos de lenguaje grandes. Este estudio puede proporcionar algunas pautas para futuras investigaciones y mitigación de los riesgos éticos que ofrece la tecnología en grandes aplicaciones de Language Models.As inovações de processamento de linguagem natural nas últimas décadas tornaram possível sintetizar e compreender textos coerentes de várias maneiras, transformando técnicas teóricas em implementações práticas. Ambos relatam que softwares resumidos e setores como criadores de conteúdo foram significativamente afetados pelo extenso modelo de linguagem. Um enorme modelo de linguagem, no entanto, poderia mostrar evidências de preconceito social, dando riscos morais e ambientais por negligência, de acordo com as observações. Portanto, é necessário desenvolver diretrizes abrangentes para LLM (Large Language Models) responsáveis. Apesar do fato de numerosas investigações empíricas mostrarem que modelos sofisticados de linguagem ampla têm muito poucas dificuldades éticas, não há uma investigação completa e estudo de consumidores sobre a legalidade do uso atual de modelos de linguagem ampla. Usamos um método de estudo qualitativo no ChatGPT3 da OpenAI para focar na solução os riscos éticos do mundo real nos atuais modelos de linguagem ampla, a fim de orientar ainda mais os esforços contínuos na construção responsável de modelos éticos de linguagem ampla. Analisamos cuidadosamente o ChatGPT3 a partir das quatro perspectivas de viés e robustez. De acordo com nossas opiniões declaradas, comparamos objetivamente o ChatGPT3 em vários conjuntos de dados de amostra. Neste trabalho, constatou-se que uma fração substancial dos problemas de princípios não é resolvida pelos referenciais atuais; portanto, novos exemplos de casos foram fornecidos para apoiar isso. Além disso, foram discutidas a importância das descobertas sobre a ética de IA do ChatGPT3, possíveis problemas no futuro e considerações de design úteis para grandes modelos de linguagem. Este estudo pode fornecer algumas orientações para futuras investigações e mitigação dos riscos éticos oferecidos pela tecnologia em grandes aplicações de Modelos de Linguagem

A STUDY TO ASSESS THE PREVALENCE OF WHATSAPP ADDICTION AMONG NURSING STUDENTS OF HIMALAYAN SCHOOL OF NURSING KALA-AMB DISTRICT SIRMAUR, HIMACHAL PRADESH.

Objective:To assess the prevalence of whatsapp addiction among nursing students of Himalayan school of nursing Kala-Amb Himachal Pradesh. Methodology:A cross sectional descriptive study was used, a sample size of 60 nursing students were selected by using Purposive sampling technique, Semi structured questionnaire were used to assess the prevalence of whatsapp addiction among nursing students of Himalayan school of nursing Kala-Amb Himachal Pradesh. Result: The study revealed that among 60 Nursing students, Benefits of using whatspp is easy way 57(95%), improve IPR 40(66.6%), building friendship 42(70%), fast and speedily 50(83.3%), and long distance communication 56(93.3%) . The Drawback of using whatspp is unwanted relations 32(53.3%), lack interaction without society 37(61.6%), no face to face interaction 48(80%) ignoring people around use 30(50%), and reduce attachment with parents 32(53.3%).When not using how you do feel are happy 39 (65%), calm 35(58.3), loneliness 27(45%), restlessness 23(38.3%)and stress 15(25%).Whatspp is mainly used for the group 51(85%),friends 60(100%), relatives 59(98.3%),(Education purpose 53(88.3%) and General purpose 46(76.6%)

A mouse protein that localizes to acrosome and sperm tail is regulated by Y-chromosome

BACKGROUND: Acrosomal proteins play crucial roles in the physiology of fertilization. Identification of proteins localizing to the acrosome is fundamental to the understanding of its contribution to fertilization. Novel proteins are still being reported from acrosome. In order to capture yet unreported proteins localizing to acrosome in particular and sperm in general, 2D-PAGE and mass spectrometry analysis of mouse sperm proteins was done. RESULTS: One of the protein spots identified in the above study was reported in the NCBI database as a hypothetical protein from Riken cDNA 1700026L06 that localizes to chromosome number 2. Immunofluorescence studies using the antibody raised in rabbit against the recombinant protein showed that it localized to mouse acrosome and sperm tail. Based on the localization of this protein, it has been named mouse acrosome and sperm tail protein (MAST, [Q7TPM5 (http://www.ncbi.nlm.nih.gov/protein/Q7TPM5)]). This protein shows 96% identity to the rat spermatid specific protein RSB66. Western blotting showed that MAST is expressed testis-specifically. Co-immunoprecipitation studies using the MAST antibody identified two calcium-binding proteins, caldendrin and calreticulin as interacting partners of MAST. Caldendrin and calreticulin genes localize to mouse chromosomes 5 and 8 respectively. In a Yq-deletion mutant mouse, that is subfertile and has a deletion of 2/3rd of the long arm of the Y chromosome, MAST failed to localize to the acrosome. Western blot analysis however, revealed equal expression of MAST in the testes of wild type and mutant mice. The acrosomal calcium-binding proteins present in the MAST IP-complex were upregulated in sperms of Yq-del mice. CONCLUSIONS: We have identified a mouse acrosomal protein, MAST, that is expressed testis specifically. MAST does not contain any known motifs for protein interactions; yet it complexes with calcium-binding proteins localizing to the acrosome. The misexpression of all the proteins identified in a complex in the Yq-del mice invokes the hypothesis of a putative pathway regulated by the Y chromosome. The role of Y chromosome in the regulation of this complex is however not clear from the current study

Overview of the Process of Enzymatic Transformation of Biomass

Cellulase is an enzyme which depolymerizes the cellulose into glucose. Cellulases are produced by a diverse array of microbes including fungi, bacteria, yeast and actinomycetes. Considerable research for understanding the mechanism of cellulases began in early 1950s because of the significant use of these enzymes in various industries. This review provides a general account structure and availability of lignocellulosic biomass, pretreatment strategies for effective digestion, cellulase producing organisms, cellulase activity assay, and enzymology of cellulose degradation. Cellulase production, optimization, purification and characterization studies in addition to the industrial application of cellulase have also been discussed. At last a brief account of present market scenario of cellulases and future prospects of the study are also taken into account

PHARMACOGNOSTIC AND HPTLC BASED COMPARATIVE STUDY ON LEAVES OF MERREMIA EMARGINATA BURM. F. AND CENTELLA ASIATICA (L.) URBAN

Objective: In this study, an attempt was made to generate information based on botanical, physicochemical and HPTLC data needed for proper identification and authentication of M. emarginata and C. asiatica belonging to two different families. Methods: Botanical study comprises of macroscopy, microscopy and powder microscopy of leaves of both crude drugs. The physicochemical parameters such as water-soluble extractive, alcohol soluble extractive and loss on drying at 105℃, total ash, acid insoluble ash, and volatile oil were determined according to standard methods. HPTLC studies of chloroform extracts of leaves of both drugs were conducted at 254 nm, 366 nm and 575 nm after derivatisation using vanillin-sulphuric acid and the results were documented. Results: The present study reveals that microscopy and most of the physicochemical parameters of both the plant materials are different. Anatomy of the leaves showed two main characteristic differences. First plenty of trichome with trichome base and calcium oxalate crystal is common in M. emarginata, which is not observed in C. asiatica. Both plants have different venation patterns and leaf constants. The total ash content and the solubility in alcohol and water for leaves of C. asiatica are higher than that of M. emarginata. The HPTLC fingerprinting pattern obtained for both drugs are different. Conclusion: All the results obtained from this study help in determining differences and similarities of leaves of M. emarginata and C. asiatica and thereby preventing adulteration and substitution and emphasizing the importance of standardization

Podophyllum hexandrum-Mediated Survival Protection and Restoration of Other Cellular Injuries in Lethally Irradiated Mice

This study aims at the development of a safe and effective formulation to counter the effects of lethal irradiation. The sub-fraction (G-001M), prepared from Podophyllum hexandrum has rendered high degree of survival (>90%) at a dose of 6 mg kg−1 body weight (intramuscular) in lethally irradiated mice. Therapeutic dose of G-001M, at about 20 times lower concentration than its LD100, has revealed a DRF of 1.62. Comet assay studies in peripheral blood leukocytes have reflected that, treatment of G-001M before irradiation has significantly reduced DNA tail length (P < .001) and DNA damage score (P < .001), as compared to radiation-only group. Spleen cell counts in irradiated animals had declined drastically at the very first day of exposure, and the fall continued till the 5th day (P < .001). In the treated irradiated groups, there was a steep reduction in the counts initially, but this phase did not prolong. More than 60% decline in thymocytes of irradiated group animals was registered at 5 h of irradiation when compared with controls, and the fall progressed further downwards with the similar pace till 5th day of exposure (P < .001). At later intervals, thymus was found fully regressed. In G-001M pre-treated irradiated groups also, thymocytes decreased till the 5th day but thereafter rejuvenated and within 30 days of treatment the values were close to normal. Current studies have explicitly indicated that, G-001M in very small doses has not only rendered high survivability in lethally irradiated mice, but also protected their cellular DNA, besides supporting fast replenishment of the immune system