Bio-Membrane Internalization Mechanisms of Arginine-Rich Cell-Penetrating Peptides in Various Species

Recently, membrane-active peptides or proteins that include antimicrobial peptides (AMPs), cytolytic proteins, and cell-penetrating peptides (CPPs) have attracted attention due to their potential applications in the biomedical field. Among them, CPPs have been regarded as a potent drug/molecules delivery system. Various cargoes, such as DNAs, RNAs, bioactive proteins/peptides, nanoparticles and drugs, can be carried by CPPs and delivered into cells in either covalent or noncovalent manners. Here, we focused on four arginine-rich CPPs and reviewed the mechanisms that these CPPs used for intracellular uptake across cellular plasma membranes. The varying transduction efficiencies of them alone or with cargoes were discussed, and the membrane permeability was also expounded for CPP/cargoes delivery in various species. Direct membrane translocation (penetration) and endocytosis are two principal mechanisms for arginine-rich CPPs mediated cargo delivery. Furthermore, the amino acid sequence is the primary key factor that determines the cellular internalization mechanism. Importantly, the non-cytotoxic nature and the wide applicability make CPPs a trending tool for cellular delivery.

Computational Thinking: Students’ Abstraction on the Concepts of Kinematics

Abstraction is the primary key in computational thinking. This study aims to analyze students’ computational thinking skills of abstraction on the concept of kinematics. The data were collected through students’ project documents and interviews. The data is examined using a content analysis approach that emphasizes writing, verbal, or visual communication. The results revealed that students’ abstraction skills were evident in collecting data and analyzing, and recognizing patterns but were less visible in building models or simulations. Abstraction skills can be used as a foundation and framework for viewing a concept in physics not only in mathematics or formulas views but as a data iterative relationship. This research is expected to provide an overview for physics instructors to integrate computational thinking in their learning classroom

Pelatihan pemanfaatan teknologi sebagai media pendukung pembelajaran untuk guru di Kecamatan Sembalun

The involvement of lecturers, students, and teaching staff is an integral form of the Tri Dharma of higher education. Education has a crucial role and is the primary key to producing quality human resources. In the current practice of teaching and learning activities, many teachers have not used media or technology in teaching. Therefore, it is necessary to increase teacher competence through Community Service Activities to adapt to the industrial era 4.0, which is more likely to use technology in various fields of life, one of which is the world of education. PKM activities were carried out for six villages in Sembalun District to equalize the competence of teachers in the village so that they were equal to teachers in the city in presenting technology-based learning media. This interactive learning media creation training produced enjoyable visual and graphic-based learning to become more exciting and not dull. With the implementation of this activity, teachers have more competence in using technology and have succeeded in building their learning media. Apart from that, the creativity of the teacher increases with this activity.

DETECTION OF THE DSSS SIGNAL WITH VARIABLE PN CODES USING THE ANN

- Direct sequence spread spectrum systems appeared and are used to protect the transmitted data DSSS Systems might be one of the solutions for reliable and secured communications. Also, it is one of the approaches used by signals for transmitting bandwidth larger compared to the satisfied frequency related to the original information. The communication systems of SS were vital to suppress interference, complicating the detection and processing of secure communications, the technology of spread spectrum (DSSS) has been initially created for military applications. In a traditional DSSS system, the PN code is the primary key to make the receiver recover the transmitted data. In this paper, by using the MATLAB R2020a is used to simulate the proposed system, it is considered that the transmitter sends data bits and wants to protect the sent data by making each bit send with a PN code consisting of 127 bits randomly without informing the receiver of that. here the artificial neural network (ANN) was used as a tool to find the PN code for each initial value of 7 flip-flops. so, the receiver could detect the transmitted data with BER =0.

An Assessment of Convective Initiation Nowcasting Algorithm within 0-60 Minutes using Himawari-8 Satellite

Convective cloud monitoring since its growth stage primarily related to location and time of the first convective cloud initiated, called convective initiation (CI), could be the primary key in providing an earlier heavy rainfall event prediction. This study aimed to assess the accuracy and lead time of CI nowcasting using Satellite Convection Analysis and Tracking (SATCAST) algorithm in predicting the CI event within 0-60 minutes over Surabaya and surrounding area using Himawari-8 satellite during June-July-August (JJA) period in 2018. Three main processes used in this study were cloud masking, cloud object tracking, and CI nowcasting. Twelve interest fields were utilized as predictors based on six bands of Himawari-8 satellite, which represented cloud physics attributes such as cloud-top height, glaciation, or cooling rate. The verification was conducted by comparing CI prediction to CI location and time based on Surabaya weather radar within the next 0-60 minutes. The algorithm resulted that the prediction could achieve 87.3% of accuracy from the 3449 cloud objects. The prediction had POD, FAR, and CSI scores of 57.1%, 52.2%, and 35.2%, respectively. The 32.3 minutes of averaged lead time prediction indicated that CI nowcasting could detect growing cumulus about 30 minutes prior to the CI event.

Highly efficient UV/H2O2 technology for the removal of nifedipine antibiotics: Kinetics, co-existing anions and degradation pathways

This study investigates the degradation of nifedipine (NIF) by using a novel and highly efficient ultraviolet light combined with hydrogen peroxide (UV/H2O2). The degradation rate and degradation kinetics of NIF first increased and then remained constant as the H2O2 dose increased, and the quasi-percolation threshold was an H2O2 dose of 0.378 mmol/L. An increase in the initial pH and divalent anions (SO42- and CO32-) resulted in a linear decrease of NIF (the R2 of the initial pH, SO42- and CO32- was 0.6884, 0.9939 and 0.8589, respectively). The effect of monovalent anions was complex; Cl- and NO3- had opposite effects: low Cl- or high NO3- promoted degradation, and high Cl- or low NO3- inhibited the degradation of NIF. The degradation rate and kinetics constant of NIF via UV/H2O2 were 99.94% and 1.45569 min-1, respectively, and the NIF concentration = 5 mg/L, pH = 7, the H2O2 dose = 0.52 mmol/L, T = 20 ℃ and the reaction time = 5 min. The ·OH was the primary key reactive oxygen species (ROS) and ·O2- was the secondary key ROS. There were 11 intermediate products (P345, P329, P329-2, P315, P301, P274, P271, P241, P200, P181 and P158) and 2 degradation pathways (dehydrogenation of NIF → P345 → P274 and dehydration of NIF → P329 → P315).

PEMBANGKIT ENTITY RELATIONSHIP DIAGRAM DARI SPESIFIKASI KEBUTUHAN MENGGUNAKAN NATURAL LANGUAGE PROCESSING UNTUK BAHASA INDONESIA

Memodelkan Entity Relationship Diagram (ERD) dapat dilakukan secara manual, namun umumnya memperoleh pemodelan ERD secara manual membutuhkan waktu yang lama. Maka, dibutuhkan pembangkit ERD dari spesifikasi kebutuhan untuk mempermudah dalam melakukan pemodelan ERD. Penelitian ini bertujuan untuk mengembangkan sebuah sistem pembangkit ERD dari spesifikasi kebutuhan dalam Bahasa Indonesia dengan menerapkan beberapa tahapan-tahapan dari Natural Language Processing (NLP) sesuai kebutuhan penelitian. Spesifikasi kebutuhan yang digunakan tim peneliti menggunakan teknik document analysis. Untuk tahapan-tahapan dari NLP yang digunakan oleh peneliti yaitu: case folding, sentence segmentation, tokenization, POS tagging, chunking dan parsing. Kemudian peneliti melakukan identifikasi terhadap kata-kata dari teks yang sudah diproses pada tahapan-tahapan dari NLP dengan metode rule-based untuk menemukan daftar kata-kata yang memenuhi dalam komponen ERD seperti: entitas, atribut, primary key dan relasi. ERD kemudian digambarkan menggunakan Graphviz berdasarkan komponen ERD yang telah diperoleh Evaluasi hasil ERD yang berhasil dibangkitkan kemudian di evaluasi menggunakan metode evaluasi expert judgement. Dari hasil evaluasi berdasarkan beberapa studi kasus diperoleh hasil rata-rata precision, recall, F1 score berturut-turut dari tiap ahli yaitu: pada ahli 1 diperoleh 91%, 90%, 90%; pada ahli 2 diperoleh 90%, 90%, 90%; pada ahli 3 diperoleh 98%, 94%, 96%; pada ahli 4 diperoleh 93%, 93%, 93%; dan pada ahli 5 diperoleh 98%, 83%, 90%.

AI INFLUENCE IN COVID-19 DETECTION

This paper is on analyzing the feasibility of AI studies and the involvement of AI in COVID interrelated treatments. In all, several procedures were reviewed and studied. It was on point. The best-analyzing methods on the studies were Susceptible Infected Recovered and Susceptible Exposed Infected Removed respectively. Whereas the implementation of AI is mostly done in X-rays and CT- Scans with the help of a Convolutional Neural Network. To accomplish the paper several data sets are used. They include medical and case reports, medical strategies, and persons respectively. Approaches are being done through shared statistical analysis based on these reports. Considerably the acceptance COVID is being shared and it is also reachable. Furthermore, much regulation is needed for handling this pandemic since it is a threat to global society. And many more discoveries shall be made in the medical field that uses AI as a primary key source.

“Like an overly large fantasy”

Audiences at Iganz Schuppanzigh’s 1820s quartet concerts in Vienna would have expected a string quartet to be a weighty, four-movement work with an emphasis on a sonata form, thematische Arbeit (motivic working) between parts, and an overall tonal plan based on one or two primary key areas. Beethoven no doubt had such connoisseur listeners in mind with this work, but was pushing far beyond that traditional idea of the string quartet. Op. 131 is full of all sorts of different kinds of writing. The chapter explores the quartet in terms of fantasia, a word found frequently in connection with Op. 131, starting with a discussion of the free fantasia as a work exhibiting apparently chaotic musings over a highly logical ground plan. As Carl Philipp Emmanuel Bach pointed out in his influential discussion of the subject, there is method in the seeming madness of the free fantasia, especially as regards harmonic links. The chapter considers the entire work as a fantasia, exploring the clever linkage of seemingly disparate ideas within and between movements. The fantasia form might seem the opposite of the formalized string quartet genre as it was starting to be understood by Beethoven’s time, but in one important respect it was not. The free fantasia was a work for the connoisseur: as Carl Friedrich Michaelis noted in his article on music and humor of 1807, the free fantasia, in particular, reveals to the connoisseur listener the soul (or inventive repository) of the composer.

Prediction of E-Commerce Product Ratings Based on Similar Users

Together with the fast advancement of continuous expansion and the Internet of E-commerce scope, product quantity, as well as assortment, boost fast. Merchants offer many goods via going shopping customers and websites generally consider a huge amount of moment to discover the products of theirs.Within e-commerce sites, the item rating is among the primary key ingredients of an excellent pc user expertise. Many methods are working with whose users to consider the goods they wish. A comparable item suggestion is among the favorite modes working with whose customers look for items in line with the item scores. In general, the suggestions aren't personalized to a particular pc user. Exploring a great deal of solutions tends to make customers runoff as a result of the info clog but not offering proper reviews for solutions.Traditional algorithms has data sparsity and cold start issues. To overcome these problems we use cosine similarity method to identify the similarity between those vectors. The nearest similar vector ratings will be used during the estimation of the unknown ratings.The proposed methodology records ratings of each product from users and those are represented by a vector, and the cosine similarity is used a measure to identify the similarity between those vectors. The nearest similar vector ratings will be used during the estimation of the unknown ratings.Hence, By using the above approach it can overcome the above problems and also it can achieve high efficiency and accuracy in a simple manner.