Modeling of mPGES-1 Three-Dimensional Structures: Applications in Drug Design and Discovery

This invention relates to representations of prostaglandin synthase three-dimensional structures. Such representations are suitable for designing agents that modulate the activity of the enzyme by binding to the substrate binding domain

SISTEM INFORMASI GEOGRAFIS PEMETAAN LOKASI TEMPAT PEMBUANGAN SAMPAH SEMENTARA (TPSS) MENGGUNAKAN METODE PROMETHE DI KOTA KUPANG

The dynamics of urban population growth is not only caused by the increase in the birth rate, but is more dominantly influenced by the flow of urbanization, whose presence also influences the city's economy. The increasing population and professional variations will lead to intense competition so that changes in lifestyle will tend to be competitive between individuals and urban social groups. The characteristics of the society tend to be individualistic, materialist and consumptive, resulting in social disparities between groups of people which have an impact on horizontal conflicts. Per capita income tends to increase because the dynamics of the economy move more aggressively so that if combined with changes in consumptive patterns, urban communities will waste more than rural communities. This research aims to; [1] Analyzing the accuracy of the distribution of waste based on the distribution pattern of the source of the landfill, [2] Analyzing the suitability of the location of the TPSS bins in accordance with the distribution pattern of the source of the landfill and the ease of access for transportation by the waste fleet, and [3] Determining the strategic location of the placement of TPSS bins for convenience. access to waste transfer in Kelapa Lima District, Kupang City. The research is focused in Kelapa Lima sub-district with a mixed method analysis approach, supported by primary and secondary data. Nearest neighbor analysis or better known as nearest neighbor analysis requires data about the distance between one settlement and the closest settlement, namely the nearest neighboring settlement. This analysis, introduced by Clark and Evans, is a method of geographic quantitative analysis used to determine the pattern of settlement distribution. Good waste management is indicated by the lack of even leaving residual waste from the waste management process at the previous stage. This matter is conceptualized in the 3R (Reduce-Reuse-Recycle) strategy, which starts by regulating [holding] consumption patterns then maximizing the value of the object's function to the highest point of use before it no longer has value and finally if it can no longer be used the object [prospective trash] is recycled. repeat until you get a new benefit value. Such a strategy must continue to be campaigned on a massive scale to the point where it is possible that waste will be generated by every human being as the main source of waste and requires producers to be responsible for ensuring the quality of their products which are more adaptive to environmental conditions

A Sensitive Triple-Band Rectifier for Energy Harvesting Applications

(c) 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.[EN] This paper presents a novel sensitive triple-band power rectifier for RF energy harvesting systems. The proposed rectifier can simultaneously harvest RF energy from GSM-900, GSM-1800, and Wi-Fi-2450 bands at relatively low and medium ambient power densities. Previously, a few multi-band rectennas have been reached a stable conversion efficiency overall frequency bands of interest because of the nonlinearity and the distinct input impedance of the rectifying circuit at these frequencies. The originality of this paper is on the improved impedance matching technique that enhances the efficiency and performance of the rectifier. The proposed high-efficiency triple-band rectifier consists of three parallel branches. Each branch comprises an input matching circuit designed to provide maximum RF power transferred to rectifying diodes, a single voltage doubler using Schottky diode HSMS-2852, and a DC-pass filter to smooth the DC output voltage. A prototype of the proposed rectifier circuit is fabricated and tested to verify its performance against the simulation results. With an optimum load resistance of 3.8 k at -10 dBm input power level, the measured RF to DC conversion efficiency achieves 33.7%, 21.8%, and 20% at 0.9, 1.8 and 2.45 GHz respectively. The efficiency is above 46.5 % overall bands of interest under 0 dBm input powerThis work was supported in part by the EMMAG Program, 2014, funded by the European Commission.Tafekirt, H.; Pelegri-Sebastia, J.; Bouajaj, A.; Reda, BM. (2020). A Sensitive Triple-Band Rectifier for Energy Harvesting Applications. IEEE Access. 8:73659-73664. https://doi.org/10.1109/ACCESS.2020.2986797S7365973664

CNC Machining Path Planning Optimization for Circular Hole Patterns via a Hybrid Ant Colony Optimization Approach

Abstract This paper presents a path-planning optimization study for a Computer Numerical Control (CNC) machining center tasked with machining jobs involving a large number of holes to drill that are mostly arranged in concentric circular patterns. Benefits of this research may contribute to shortening the machining time in certain components used in heat exchangers, boilers, condensers, trammel screens and food separators. Optimization of tool travel distance and machining cost are typically overlooked aspects when generating tool paths and CNC codes from commercially available CAD software packages. Tool path travel distance minimization can be modelled Travelling Salesman Problem (TSP). Optimization algorithms have been heavily applied in the literature to the TSP with varying levels of success. Ant Colony Optimization (ACO) is one of the most prominent approaches that mimics the natural behavior of ant colonies. The research in this paper proposes a hybrid ACO that has a biasing mechanic designed to take advantage of the geometric hole-pattern arrangement, as well as a local search. Simulation examples show the proposed approach exhibiting superior performance compared to the classic ACO approach, a genetic algorithm (GA) approach, as well as the simple spiral path generated via commercial CAD software. The proposed approach is then applied to the drilling path planning of a two-thousand-hole food-industry separator plate

A Simple and Efficient eight node Finite Element for Multilayer Sandwich Composite Plates Bending Behavior Analysis

In this paper, a C0 simple and efficient isoparametric eight-node displacement-model based on higher order shear deformation theory is proposed for the bending behavior study of multilayer composites sandwich plates. Difficult C1-continuity requirement is overcome by extracting the seven degrees of freedom from strain relations for each element node: two displacements for in-plane behavior and five bending unknowns namely: a transverse displacement, two rotations and two shear angles, which results in a kinematic approximation formulation having only first order derivative requirement. The governing equations of the element (constitutive, virtual work and equilibrium equations) are implemented for the prediction of approximate solutions of deflections and stresses of sandwich plates linear elastic problems. Thereby, the formulation element is able to present a cubic in-plane displacement along both core and faces sandwich thickness, as well as, the shear stresses are found to vary as quadratic field without requiring shear correction factors and independent from any transverse shear locking problems. The accuracy and validity of the proposed formulation is verified through the numerical evaluation of displacements and stresses and their comparison with the available analytical 3D elasticity solutions and other published finite element results

PELATIHAN TANGGUH BENCANA SEROJA UNTUK MENINGKATKAN KESIAPSIAGAAN WARGA SEKOLAH DASAR

Abstrak: Bencana cuaca ekstrem yang dipicu siklon tropis Seroja telah berdampak luar biasa kepada masyarakat Nusa Tenggara Timur (NTT). Pada awal April 2021 lalu BMKG merilis adanya dua bibit siklon tropis yang dapat berdampak pada cuaca ekstrem. Salah satunya siklon tropis 99S yang kemudian dikenal luas sebagai Siklon Seroja. Upaya mitigasi bencana perlu di sampaikan kepada masyarakat terutama pada siswa sekolah dasar. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk memberikan wawasan umum terkait sadar bencana dan pemahaman mengenai pentingnya literasi kebencanaan dan spesifikasi cara pencegahan (pra bencana), menanggulangi (pasca bencana) serta evakuasi mandiri (tanggap darurat) yang dapat dilakukan oleh siswa sekolah dasar. Metode yang digunakan adalah metode kontekstual berbantuan media booklet. Untuk mengetahui peningkatan belajar siswa, siswa diarahkan untuk mengerjakan soal pre-test dan post-test. Hasil kegiatan menunjukkan bahwa tingkat literasi terkait mitigasi bencana bagi siswa SD Inpres Kuanheum masih kurang. Hal ini ditunjukkan dengan adanya hasil evaluasi kegiatan yang menunjukkan siswa belum terbekali dengan edukasi mitigasi yang cukup. Penggunaan media berupa booklet ringkas inovatif sesuai untuk diterapkan bagi siswa sekolah dasar SD Inpres Kuanheum untuk menggugah ketertarikan dalam membaca dan belajar. Edukasi literasi mitigasi bencana harus diimbangi dengan integrasi dalam materi pelajaran formal di sekolah dan pembiasaan secara berkelanjutan. Abstract:  The extreme weather disaster triggered by tropical cyclone Seroja has had a tremendous impact on the people of East Nusa Tenggara (NTT). In early April 2021, BMKG released two tropical cyclones that could have an impact on extreme weather. One of them was tropical cyclone 99S which became widely known as Cyclone Seroja. Disaster mitigation efforts need to be conveyed to the community, especially to elementary school students. This community service activity aims to provide general insights related to disaster awareness and understanding of the importance of disaster literacy and specifications on how to prevent (pre-disaster), overcome (post-disaster) and self-evacuation (emergency response) that can be carried o ut by elementary school students. The method used is a contextual method assisted by the media booklet. To find out the improvement of student learning, students are directed to do pre-test and post-test questions. The results of the activity showed that the level of literacy related to disaster mitigation for students of SD Inpres Kuanheum was still lacking. This is shown by the results of the evaluation of activities that show that students have not been equipped with sufficient mitigation education. The use of media in the form of innovative concise booklets is suitable to be applied to elementary school students of SD Inpres Kuanheum to arouse interest in reading and learning. Disaster mitigation literacy education must be balanced with integration in formal subject matter in schools and ongoing habituation

HPLC-DAD analysis, antimicrobial and antioxidant properties of aromatic Herb Melissa officinalis L., aerial parts extracts

Treating specific tissues without affecting other regions is a difficult task. It is desirable to target the particular tissue where the chemical has its biological effect. To study this phenomenon computationally, in this work we numerically study a mathematical model which is written as a nonlinear system composed by three parabolic partial differential equations. The variables involved in the model are the concentration of the chemical, the concentration of the binding protein and the concentration of the chemical bound to the protein. Our aim is to propose a fully discrete approximation of this problem, using the Finite Element Method and a semi-implicit Euler scheme, in order to solve it numerically. This discrete problem is analysed, obtaining a discrete stability property and some a priori error estimates that show the algorithm converges linearly if the continuous solution is regular enough. Also, some representative examples are shown, as well as the numerical verification of the convergence.Universidade de Vig

Wavelet Neural Networks for Speed Control of BLDC Motor

In the recent years, researchers have sophisticated the synthesis of neural networks depending on the wavelet functions to build the wavelet neural networks (WNNs), where the wavelet function is utilized in the hidden layer as a sigmoid function instead of conventional sigmoid function that is utilized in artificial neural network. The WNN inherits the features of the wavelet function and the neural network (NN), such as self-learning, self-adapting, time-frequency location, robustness, and nonlinearity. Besides, the wavelet function theory guarantees that the WNN can simulate the nonlinear system precisely and rapidly. In this chapter, the WNN is used with PID controller to make a developed controller named WNN-PID controller. This controller will be utilized to control the speed of Brushless DC (BLDC) motor to get preferable performance than the traditional controller techniques. Besides, the particle swarm optimization (PSO) algorithm is utilized to optimize the parameters of the WNN-PID controller. The modification for this method of the WNN such as the recurrent wavelet neural network (RWNN) was included in this chapter. Simulation results for all the above methods are given and compared

Peptide Inhibitors Targeting the \u3cem\u3eNeisseria gonorrhoeae\u3c/em\u3e Pivotal Anaerobic Respiration Factor AniA

Neisseria gonorrhoeae causes the sexually transmitted infection gonorrhea, which is highly prevalent worldwide and has a major impact on reproductive and neonatal health. The superbug status of N. gonorrhoeae necessitates the development of drugs with different mechanisms of action. Here, we focused on targeting the nitrite reductase AniA, which is a pivotal component of N. gonorrhoeae anaerobic respiration and biofilm formation. Our studies showed that gonococci expressing AniA containing the altered catalytic residues D137A and H280A failed to grow under anaerobic conditions, demonstrating that the nitrite reductase function is essential. To facilitate the pharmacological targeting of AniA, new crystal structures of AniA were refined to 1.90-Å and 2.35-Å resolutions, and a phage display approach with libraries expressing randomized linear dodecameric peptides or heptameric peptides flanked by a pair of cysteine residues was utilized. Biopanning experiments led to the identification of 29 unique peptides, with 1 of them, C7-3, being identified multiple times. Evaluation of their ability to interact with AniA using enzyme-linked immunosorbent assay and computational docking studies revealed that C7-3 was the most promising inhibitor, binding near the type 2 copper site of the enzyme, which is responsible for interaction with nitrite. Subsequent enzymatic assays and biolayer interferometry with a synthetic C7-3 and its derivatives, C7-3m1 and C7-3m2, demonstrated potent inhibition of AniA. Finally, the MIC50 value of C7-3 and C7-3m2 against anaerobically grown N. gonorrhoeae was 0.6 mM. We present the first peptide inhibitors of AniA, an enzyme that should be further exploited for antigonococcal drug development

The prediction of sleep quality using wearable-assisted smart health monitoring systems based on statistical data

The technology, which plays a significant role in our lives, has made it possible for many of the appliances and gadgets we use on a daily basis to be monitored and controlled remotely. Health and fitness data is collected by wearable devices attached to patients' bodies. A number of parties could benefit from this technology, including doctors, insurers, and health providers. This technology, including smartwatches, smart ring, smart cloth wristbands, and GPS shoes, is frequently used for fitness and wellness since it allows users to track their day-to-day health. Devices that compute the sleep characteristics by storing sleep movements fall within the category of wearables worn on the wrist. In order to lead a healthy lifestyle, sleep is crucial. Inadequate sleep can harm one's physical, mental, and emotional well-being and increase the risk of developing a number of ailments, including stress, heart disease, high blood pressure, insulin resistance, and other conditions. Deep learning (DL) models have recently been used to forecast sleep-quality based on wearables information from the awake hours. Deep learning has been demonstrated to be capable of predicting sleep efficiency based on wearable data obtained during awake periods. In this regard, this study creates a novel deep learning model for wearables-enabled smart health monitoring system (DLM-WESHMS) for the prediction of sleep quality. The wearables are initially able to collect data linked to sleep-activity using the described DLM-WESHMS approach. The data is then put through pre-processing to create a standard format. Using the DLM-WESHMS, sleep quality is predicted using the deep belief network (DBN) model. The DBN model uses the auto-encoders algorithm (AEA) to predict popularity, which improves the accuracy of its predictions of sleep quality. The experimental outcomes of the DLM-WESHMS approach are investigated using several metrics. The DLM-WESHMS model performs significantly better than other models, according to a thorough comparison analysis