Miracle-dz/UniFAR-FTUs huggingface dataset:
New hybrid scaffolds based on ASA/genistein: Synthesis, cytotoxic effect, molecular docking, drug-likeness, and in silico ADME/Tox modeling

Eight hybrids based on genistein and aspirin were designed, synthesized, and elucidated by spectroscopic analysis. Chemopreventive potential of these compounds was evaluated against SW480 human colon adenocarcinoma cells, its metastatic derivative SW620 and normal cells (CHO-K1). According to the results, hybrids 4a and 4c displayed significant activity over SW480 cells causing a reduction of cell viability of 40.49% and 40.39%, respectively, when treated with 300 μM for 48 hours, being timeand concentration-dependent. None of the compounds exhibited activity at 24 hours; besides, these types of molecules were not active on human metastatic SW620 cells (data not shown). On the other hand, compounds 4d, 4e, 4f, and 4h did not display any activity on the cells at the conditions evaluated. Multitarget docking studies performed against six tumor-associated proteins targets in colorectal cancer, would reveal that hybrids 4a and 4c may inhibit function of Polo-like kinase 1 as primary mode of action with a binding affinity about −10 kcal/ mol. However, docking action would suggest these compounds may induce synergistic cytotoxic effects by regulation of B-cell lymphoma 2 (Bcl-2)/Bcl-2-associated X protein system and cyclooxygenase-2 in SW480 colorectal cancer cells with Vina scores in the range −10.1 to −9.3 kcal/mol. Additionally, in silico drug-likeness studies suggest that active hybrids 4a and 4c display favorable pharmacokinetics indices, good Absorption, Distribution, Metabolism and Excretion (ADME)/Tox profile, and a remarkable metabolic stability within recommended therapeutic ranges, making these compounds useful as promising medicinal scaffolds in the designing of novel orally active anticancer candidates.
Estudo das diferentes lógicas de Planejamento e Controle - uma contribuição ao gerenciamento estratégico de operações

As organizacoes estao, hoje, inclusas em ambientes complexos e variaveis que sao definidos pelo mercado que esta cada dia mais competitivo. Para sobreviver a esse desafio, as organizacoes precisam planejar com responsabilidade, definindo suas estrategia, mantendo controle adequado delas, visando a conquista dos objetivos tracados. O processo de planejamento e controle pode ser uma tarefa ardua ja que a literatura nos apresenta uma diversidade de abordagens que podem ser implementadas, porem, essas abordagens, se forem bem aplicadas, tornam-se aliados da gestao. Partindo deste fator motivacional, valendo-se da revisao teorico conceitual, este artigo apresenta uma compilacao das diferentes abordagens utilizadas para planejamento e controle, apresentando uma proposta de classificacao dessas abordagens em grupos de logicas semelhantes, que, segundo a analise detalhada do metodo que cada empresa utiliza para planejamento e controle, levou a classificacao em tres classes dominantes aqui chamadas de Integracao, Desdobramento e Qualidade, que interagem, mas cada uma com uma logica propria. De maneira geral, podese afirmar, de forma sintetica, que a Integracao tem como principal objeto a utilizacao de softwares. O Desdobramento apresenta uma divisao de metas a serem atingidas, enquanto a Qualidade utiliza-se de conceitos de gerenciamento da qualidade para o controle. Agora, com seu desenvolvimento completo, apresenta-se o framework, que e uma importante contribuicao para a Teoria de Engenharia de Producao e Gestao de Operacoes, pois o mapeamento de grupos logicos de planejamento e controle proporciona uma coerente aplicacao na gestao de manufatura e servicos, pois as organizacoes sempre buscam por uma estrategia competitiva, porem, e necessaria uma implantacao bem sucedida para obter os resultados esperados.
Radiolysis Studies of Oxidation and Nitration of Tyrosine and Some Other Biological Targets by Peroxynitrite-Derived Radicals

The widespread interest in free radicals in biology extends far beyond the effects of ionizing radiation, with recent attention largely focusing on reactions of free radicals derived from peroxynitrite (i.e., hydroxyl, nitrogen dioxide, and carbonate radicals). These radicals can easily be generated individually by reactions of radiolytically-produced radicals in aqueous solutions and their reactions can be monitored either in real time or by analysis of products. This review first describes the general principles of selective radical generation by radiolysis, the yields of individual species, the advantages and limitations of either pulsed or continuous radiolysis, and the quantitation of oxidizing power of radicals by electrode potentials. Some key reactions of peroxynitrite-derived radicals with potential biological targets are then discussed, including the characterization of reactions of tyrosine with a model alkoxyl radical, reactions of tyrosyl radicals with nitric oxide, and routes to nitrotyrosine formation. This is followed by a brief outline of studies involving the reactions of peroxynitrite-derived radicals with lipoic acid/dihydrolipoic acid, hydrogen sulphide, and the metal chelator desferrioxamine. For biological diagnostic probes such as ‘spin traps’ to be used with confidence, their reactivities with radical species have to be characterized, and the application of radiolysis methods in this context is also illustrated.
Molecular Aspects of Seed Development Controlled by Gibberellins and Abscisic Acids

Plants have evolved seeds to permit the survival and dispersion of their lineages by providing nutrition for embryo growth and resistance to unfavorable environmental conditions. Seed formation is a complicated process that can be roughly divided into embryogenesis and the maturation phase, characterized by accumulation of storage compound, acquisition of desiccation tolerance, arrest of growth, and acquisition of dormancy. Concerted regulation of several signaling pathways, including hormonal and metabolic signals and gene networks, is required to accomplish seed formation. Recent studies have identified the major network of genes and hormonal signals in seed development, mainly in maturation. Gibberellin (GA) and abscisic acids (ABA) are recognized as the main hormones that antagonistically regulate seed development and germination. Especially, knowledge of the molecular mechanism of ABA regulation of seed maturation, including regulation of dormancy, accumulation of storage compounds, and desiccation tolerance, has been accumulated. However, the function of ABA and GA during embryogenesis still remains elusive. In this review, we summarize the current understanding of the sophisticated molecular networks of genes and signaling of GA and ABA in the regulation of seed development from embryogenesis to maturation.
Analog Circuit Yield Optimization via Freeze–Thaw Bayesian Optimization Technique

While the VLSI community cares about designs with high yields under process variations, expensive computational costs make conventional yield optimization methods for analog circuits inefficient for industrial applications. In this article, an efficient yield optimization method via the freeze–thaw Bayesian optimization technique is proposed for analog circuits. The yield analysis is integrated into the exploration process of the Bayesian optimization. With a specified Gaussian process regression method, the flexible freeze–thaw Bayesian optimization technique is utilized to automatically guide the search in the design space and control the accuracy of yield analysis in the process space. A performance optimization problem is formulated and solved to mine prior knowledge, and a further speed up is achieved. Experimental results show that the proposed method can gain a <inline-formula> <tex-math notation="LaTeX">$2.47\times $ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$5.73\times $ </tex-math></inline-formula> speedup compared with the state-of-the-art methods, without loss of accuracy.
When and How Should Firms Differentiate? Quality and Advertising Decisions in a Duopoly

A prominent hallmark of competitive interaction is the desire to differentiate from rivals. In this article, the authors examine under what conditions firms will differentiate through product quality versus advertising intensity. Firms select quality in a first stage, advertising in a second stage, and price in the last stage. The probability that a consumer is informed of a firm’s offering depends on its advertising expenditure. The authors find that when advertising is not cost effective, both firms choose a light ad spending. This allows them to minimally differentiate in quality without concern of intense price competition, as each firm has a segment of “captive” consumers. When advertising is moderately cost effective, one firm spends heavily on advertising. The rival advertises lightly, while choosing the same maximal quality level. This strategy softens price competition by inducing the heavy advertiser to price high more often to capitalize on its large captive segment. When advertising is very cost effective, both firms advertise heavily and differentiate in quality. Three extensions are examined: upfront fixed quality costs, continuous advertising levels, and simultaneous advertising and pricing decisions. This research reveals that letting market awareness be determined endogenously suggests less product differentiation than previously suspected and regions of advertising differentiation.
Factors Affecting the Occurrence of Coronary Heart Disease in the General Hospital of Waikabubak, Indonesia

Coronary heart disease (CHD) causes many deaths. It is a disease of the heart that occurs due to decreased blood supply to the heart muscle. Risk factors that can trigger CHD can be grouped into two categories, namely those that cannot be modified and those that can. The risk factors that cannot be modified include heredity, age and gender, while the modifiable risk factors include smoking, hypertension, increased serum cholesterol levels, obesity and diabetes. Basic Health Research data show that in 2018, 1.5% or 15 out of 1000 Indonesians suffered from CHD. The aim of this study was to investigate the factors that influence the incidence of CHD at the RSUD Waikabubak. This was a quantitative analytical survey which used a cross-sectional approach. According to the results, CHD was significantly associated with gender (OR = 3.5, p = 0.011), smoking (OR = 3.9, p = 0.006) and hypertension (OR = 4.8, p = 0.001). Of the factors studied, hypertension had the strongest influence on the incidence of CHD. Keywords: coronary heart disease, the factors that influence
GANAN: GAN-based for Anomaly Detection on Attributed Networks

Anomaly detection on attributed networks is crucial for many applications such as social networks security and fraud detection. Existing models utilize deep autoencoder to reconstruct structure and attribute and measure reconstruction errors to obtain anomaly nodes. However, there are problems such as over-smoothing and node’s representation learning. In order to solve these problems, in this paper, we propose a GAN-based for Anomaly Detection on Attributed Networks (GANAN). The fake graph network is generated by autoencoder. We use two encoders map both fake and real graph to latent space. The structure and attribute are used as the input of the discriminator. The game method can alleviate the over-smoothing and help encoder learn node representation. With the decoder output, the measurement considers the reconstruction error of nodes from both structure and attribute perspectives. Extensive experiments on real-world datasets demonstrate that our proposed model has better performance than various existing mothed.
Adaptive Motion Cueing Algorithm Using Optimized Fuzzy Control System for Motion Simulators

The Motion Cueing Algorithm (MCA) is the main unit of motion simulators responsible for transforming the vehicle motions to generate driving motion sensation for the simulator users within the motion simulator's physical workspace through washout filters. In this study, we design and provide a new framework by developing a set of novel washout filters using optimized fuzzy control systems to solve the drawbacks associated with the existing optimal MCAs of the motion simulators. These drawbacks include constant washout filter parameters, inefficient simulator movement in the workspace, lack of considering the simulator's physical constraints and driver sensation-related factors, and sub-optimal settings which causes false motion cues and subsequently simulator sickness. As a pioneering framework, the fuzzy logic controllers generate restitution signals for the optimal washout filters based on the motion sensation error between the real vehicle and simulator divers as well as the platform's position in the workspace aiming to correct the filtered signals, reduce error, generate realistic motions, and increase motion fidelity online. The GA is applied to optimize the fuzzy logic membership functions and control rules. The optimization procedure takes into account a number of important factors that are normally ignored in the current MCAs including the sensed motion error between the drivers of simulator and real car; the platform physical constraints; the motion threshold limiter effects; and signal shape following. The new adaptive MCA is designed, implemented and tested using the MATLAB/Simulink. The simulation results confirm the effectiveness of the developed MCA in maximizing motion fidelity and the reference sensation shape following, and enhancing the workspace usage of the simulator.
PENGARUH EKSTRAK ETANOL KULIT JERUK NIPIS (Citrus aurantifolia (Christm.) Swingle) TERHADAP PENYEMBUHAN ULKUS TRAUMATIK PADA Rattus norvegicus STRAIN WISTAR

Ulkus traumatik merupakan inflamasi pada mukosa mulut yang disebabkan oleh perlukaan traumatik seperti perlukaan termal, kimiawi, radiasi, mekanik dan elektrik. Salah satu alternatif pengobatannya adalah dengan ekstrak etanol kulit jeruk nipis. Ekstrak etanol kulit jeruk nipis merupakan hasil maserasi kulit jeruk nipis yang memiliki zat anti-inflamasi dan membantu proses penyembuhan luka. Tujuan penelitian ini adalah untuk mengetahui pengaruh serta konsentrasi efektif ekstrak kulit jeruk nipis terhadap penyembuhan ulkus traumatik pada Rattus norvegicus strain Wistar. Eksperimental laboratorik murni dengan posttest only control group design digunakan dalam penelitian ini. Dua puluh empat ekor tikus Wistar diberi 1 tetes perhidrol pada mukosa bibir bawah untuk membentuk lesi ulserasi. Dua tetes ekstrak etanol kulit jeruk nipis konsentrasi 6,25%; 12,5%, 25% dan 50%, akuades sebagai kontrol negatif dan Aloclair sebagai kontrol positif diaplikasikan pada area yang sama sebanyak 2 kali sehari. Diameter akhir ulkus diukur menggunakan jangka sorong pada hari kelima. Hasil menyatakan ekstrak etanol kulit jeruk nipis telah meningkatan penyembuhan ulkus traumatik dengan p = 0.001. Konsentrasi ekstrak etanol kulit jeruk nipis yang paling efektif ada pada konsentrasi 25-50%. Sehingga disimpulkan ekstrak etanol kulit jeruk nipis ( Citrus aurantifolia (Christm.) Swingle) berpengaruh terhadap penyembuhan ulkus traumatik pada Rattus norvegicus strain Wistar.
The Importance of a Natural Social Contract and Co-Evolutionary Governance for Sustainability Transitions

The corona (COVID-19) pandemic is not a 'game changer' as such, but it is a crisis that offers opportunities for dealing with three interrelated crises: the ecological crisis (climate change, loss of biodiversity), the rise of populistic leaders, and the inequality crisis (the widening of the gap between rich and poor). Our argument is that sustainability transitions will not succeed without a different economy and another social contract: a different alliance between citizen, society, economy and government, with the associated rights and duties of care (for the environment and the well-being of others, including future generations). A different social contract is not only desirable from the point of view of sustainability and fairness, justice and equality, but is also necessary to restore citizens' trust in politics, government, companies and each other. Drawing on evolutionary governance theory, which says that governance is poly-centric and path-dependent, and insights from innovation/transition studies about systemic change, we discuss mechanisms towards a Natural Social Contract and offer recommendations for how sustainability transitions may be co-optimised with societal transitions.
Academic Librarians and Their Role in Disseminating Accurate Knowledge and Information about the Gray Zone in Predatory Publishing

Abstract “Predatory” publishing is a non-binary academic phenomenon, but personal and professional biases may influence the criteria used to create associated blacklists and whitelists. Academic librarians, as scholarly communicators, play an essential role in transmitting accurate information about “predatory” publishing to students, staff, funders, university management and the public. In this paper, lessons are drawn from the published literature to offer advice to academic librarians about the grey zone in predatory publishing to avoid select misinformation pitfalls. Academic librarians need to recognise the flaws and weaknesses of blacklists and of the criteria used to establish them. By offering accurate insight and advice, academic librarians can establish an effective online warning system to users about “predatory” publishing, allowing them to be more effective scholarly communicators, and not vessels of miscommunication. Academic librarians are essential in aiding the academic community to find solutions to this threat to the literature’s integrity.
Equivalent-Input-Disturbance-Based Dynamic Tracking Control for Soft Robots via Reduced-Order Finite-Element Models

This article develops a systematic framework for dynamic tracking control of soft robots. To this end, we propose a new projector for the proper orthogonal decomposition algorithm to significantly reduce the large-scale robot models, obtained from finite-element methods (FEM), while preserving their structure and stability properties. Such a property preservation enables an effective equivalent-input-disturbance-based scheme for dynamic tracking control of elastic soft robots with various geometries and materials. The proposed control scheme is composed of three key components, i.e., feedforward control, disturbance-estimator control, and feedback control. To account for the trajectory reference, the feedforward action is designed from the dynamic FEM reduced-order robot model. The disturbance-estimator control action is obtained from an unknown input observer, which also provides the estimates of the reduced states for the feedback control design. The feedback gains of the observer-based controller are computed from an optimization problem under linear matrix inequality constraints. The closed-loop tracking properties are guaranteed using the Lyapunov stability theory. The effectiveness of the proposed dynamic control framework has been demonstrated via both high-fidelity SOFA simulations and experimental validations, performed on two soft robots with different natures. In particular, comparative studies with state-of-the-art control methods have been also carried out to highlight the interests of the new soft robot control results. This article is complemented with a video: https://bit.ly/2VVwtLn.
Performance Analysis for AOA-Based Localization Under Millimeter-Wave Wireless Networks

Millimeter-Wave (mmWave) communication is a promising solution for achieving high data rate and low latency in 5G wireless networks. Since directional beamforming and antenna arrays are exploited in the mmWave networks, accurate angle-of-arrival (AOA) measurements can be obtained and utilized for localization purposes. In this work, we consider the AOA-based positioning for the mmWave networks using stochastic geometry and analyze how the Cramér-Rao lower bound (CRLB) is affected by the spatial distribution of nodes, including the target and participating anchors. In order to apply the CRLB on a network setting with random node locations, we propose an accurate approximation of the CRLB using the <inline-formula> <tex-math notation="LaTeX">$\lceil L/4 \rceil $ </tex-math></inline-formula>-th value of the ordered distances where <inline-formula> <tex-math notation="LaTeX">$L$ </tex-math></inline-formula> is the number of participating anchors. These findings provide us deep insight into optimum network design that meets specified localization requirements.
An efficient privacy-preserving user authentication scheme using image processing and blockchain technologies

Abstract User authentication is a measurement challenge for handheld devices and online accounts such as bank accounts, social media accounts etc. because illegal access results in money loss and user privacy. Individual devices, online financial services, and intelligent spaces are three significant areas of concern for customer authentication procedures. Three ways have been identified for authentication factors: i) knowledge-factor, ii) Inherence factor, and iii) possession-factor. This study investigates two-way user authentication through image processing. CNN, RCNN, and Deepface are deep learning algorithms used for image recognition. We used imagechain for image storage and Blockchain for personal information storage (mobile number) to secure the database. The database is stored on an Ethereum-based blockchain. After determining whether the image is fake or real, match the webcam image with the imagechain; if both images match, the one-time password is given to the user’s cellphone number for login access. For image processing, Opencv is employed, and the Python library is used to execute machine and deep learning algorithms for user authentication. Test the proposed model on the 10 to 100 users for authentication. Accuracy of this experiment is 75.35, 76.33, 98.18 and cosine similarities of images are much better between images, but in case of fake image identification it achieved 97.35 % accuracy.