Miracle-dz/UniFAR-FTUs huggingface dataset:
Advances of the Target-Based and Phenotypic Screenings and Strategies in Drug Discovery

Review Advances of the Target-Based and Phenotypic Screenings and Strategies in Drug Discovery Shoubao Wang 1,*, Zihan Wang1, Lianhua Fang1, Yang Lv2, and Guanhua Du1,* 1 Beijing Key Laboratory of Drug Targets Identification and Drug Screening, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100050, China. 2 Beijing Key Laboratory of Polymorphic Drugs, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100050, China. * Correspondence: shoubaowang@imm.ac. cn (Shoubao Wang); dugh@imm.ac. cn (Guanhua Du). Received: 8 November 2022 Accepted: 15 November 2022 Published: 21 December 2022 Abstract: Drug discovery and development is a complex and expensive process. There are two approaches, phenotypic and target-based approaches, each holding different advantages for screening novel drug candidates when pursuing successful marketing authorization. However, the attrition rates of drug candidates continue to increase. In this review, we discuss recent successes and ongoing advances in phenotypic screening and target-based screening for drug discovery. We also explore how strategic and technological innovations may fuel new approaches in drug discovery. There are two approaches in drug discovery.
Potential Nanotechnology-Based Therapeutics to Prevent Cancer Progression through TME Cell-Driven Populations

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer with a high risk of metastasis and therapeutic resistance. These issues are closely linked to the tumour microenvironment (TME) surrounding the tumour tissue. The association between residing TME components with tumour progression, survival, and metastasis has been well elucidated. Focusing on cancer cells alone is no longer considered a viable approach to therapy; thus, there is a high demand for TME targeting. The benefit of using nanoparticles is their preferential tumour accumulation and their ability to target TME components. Several nano-based platforms have been investigated to mitigate microenvironment-induced angiogenesis, therapeutic resistance, and tumour progression. These have been achieved by targeting mesenchymal originating cells (e.g., cancer-associated fibroblasts, adipocytes, and stem cells), haematological cells (e.g., tumour-associated macrophages, dendritic cells, and myeloid-derived suppressor cells), and the extracellular matrix within the TME that displays functional and architectural support. This review highlights the importance of nanotechnology-based therapeutics as a promising approach to target the TME and improve treatment outcomes for TNBC patients, which can lead to enhanced survival and quality of life. The role of different nanotherapeutics has been explored in the established TME cell-driven populations.
Pharmacotherapy Evolution in Alzheimer’s Disease: Current Framework and Relevant Directions

Alzheimer’s disease (AD), once considered a rare disease, is now the most common form of dementia in the elderly population. Current drugs (cholinesterase inhibitors and glutamate antagonists) are safe but of limited benefit to most patients, offering symptomatic relief without successful cure of the disease. Since the last several decades, there has been a great need for the development of a treatment that might cure the underlying causes of AD and thereby slow its progression in vulnerable individuals. That is why phase I, II, and III studies that act on several fronts, such as cognitive improvement, symptom reduction, and enhancing the basic biology of AD, are imperative to stop the disease. This review discusses current treatment strategies, summarizing the clinical features and pharmacological properties, along with molecular docking analyses of the existing medications.
Optimum solar energy harvesting system using artificial intelligence

Renewable energy is promoted massively to overcome problems that fossil fuel power plants generate. One popular renewable energy type that offers easy installation is a photovoltaic (PV) system. However, the energy harvested through a PV system is not optimal because influenced by exposure to solar irradiance in the PV module, which is constantly changing caused by weather. The maximum power point tracking (MPPT) technique was developed to maximize the energy potential harvested from the PV system. This paper presents the MPPT technique, which is operated on a new high‐gain voltage DC/DC converter that has never been tested before for the MPPT technique in PV systems. Fuzzy logic (FL) was used to operate the MPPT technique on the converter. Conventional and adaptive perturb and observe (P&O) techniques based on variables step size were also used to operate the MPPT. The performance generated by the FL algorithm outperformed conventional and variable step‐size P&O. It is evident that the oscillation caused by the FL algorithm is more petite than variables step‐size and conventional P&O. Furthermore, FL's tracking speed algorithm for tracking MPP is twice as fast as conventional P&O.
The Impact of Liquidity, Solvability, Activity, Profitability, Asset Growth, and Sales Growth to Systematic Risk With Firm Size as Moderating Variable on Consumer Non-Cyclicals Company Listed in Indonesia Stock Exchange 2017-2021

Investors need useful information as a signal to decide on investment because investment activity contains risk of uncertainty that will occur in the future that can not be handled by diversification which is called systematic risk. Systematic risk is calculated by beta stock which the companies have different beta values. Therefore, this research aims to analyze the impact of financial information on the beta stock in sector consumer non-cyclicals listed on Bursa Efek Indonesia (BEI) with the observation period 2017-2021. Respon variables in this research are liquidity, solvability, activity, profitability, asset growth, and sales growth, with firm size as the moderating variable. Population in this research was 103 companies, then got 40 companies after doing the purposive sampling method, so there were 200 units of analysis with five years of analysis. Data analysis method using SEM-PLS analysis with software SmartPLS. The results show that liquidity has a significant negative impact on systematic risk. Solvability, profitability, and sales growth significantly positively affect systematic risk. Activity and asset growth are not relevant to systematic risk. The moderation test result proves that firm size significantly adequates the impact of liquidity, profitability, and sales growth on systematic risk. Firm size does not significantly adequate the impact of solvability, activity, and asset growth on systematic risk.
Obstructive Sleep Apnoea in Children with Down Syndrome: A Multidisciplinary Approach

A comprehensive evaluation of obstructive sleep apnoea (OSA) may allow for the development of more efficient management of Down syndrome (DS). We aimed to evaluate the effect of a multidisciplinary approach to DS with OSA. A total of 48 DS children aged 4–12 years were prospectively investigated with nasal endoscopy, orthodontic examination, and overnight polygraphy (PG); the Italian Child Sleep Habits Questionnaire (CSHQ-IT) was filled out by the mothers. The total CSHQ-IT score was 63 (96% of children reporting sleep problems). The major ear, nose, and throat characteristics were enlarged palatine tonsils (62%), adenoid tonsils (85%), and chronic rhinosinusitis (85%). DS children showed orthognathic profile in 68% of cases, class I relationship in 63%, and cross-bite in 51%. PG revealed OSA in 67% of cases (37% mild, 63% moderate–severe). The oxygen desaturation index (ODI) was higher in the group with OSA (5.2) than with non-OSA (1.3; p < 0.001). The ODI was higher (p = 0.001) and SpO2 lower (p = 0.03) in children with moderate–severe OSA than with mild OSA. The apnoea–hypopnea index (AHI) and percentage time with SpO2 < 90% were higher in DS children with grade III than with grade I or II adenoids (5 vs. 1, p = 0.04, and 1.2 vs. 0.1, p = 0.01, respectively). No significant correlations were found between PG and the total CSHQ-IT score or orthodontic data. However, children showing associated cross-bite, grade III adenoids and size 3 or 4 palatine tonsils showed higher AHI and ODI than those without (p = 0.01 and p = 0.04, respectively). A coordinated multidisciplinary approach with overnight PG is a valuable tool when developing diagnostic protocols for OSA in DS.
A diamond gasket for the laser-heated diamond anvil cell

Advances in laser heating techniques with diamond anvil cells have enabled direct investigations of materials under extreme pressure-temperature conditions. The success of uniform heating to the maximum temperatures at megabar pressures relies critically on maximizing the gasket thickness which in turn depends upon the shear strength of the gasket. We have used diamond powder, the strongest possible material, to formulate a gasket for in situ x-ray diffraction with double-sided laser heating. The increase in gasket thickness allows increases in sample and insulator thickness, thereby improving the quality and pressure-temperature range of the measurement. We did not observe any pressure difference within 40 μm of the center of the sample chamber and the temperature distribution across the sample itself is within ±47 K. These improvements as well as the fact that the diamond gasket can allow the sample to remain in good condition after high P–T processing make it an extremely useful technique in diamond ce.
Annotated Open Corpus Construction and BERT-Based Approach for Automatic Metadata Extraction From Korean Academic Papers

With the accelerating development of science and technology, the academic papers being published in various fields are increasing rapidly. Academic papers specially in science and technology fields are a crucial media for researchers who develop new technologies by identifying knowledge regarding the latest technological trends and conduct derivative studies in science and technology. Therefore, the continual collection of extensive academic papers, structuring of metadata, and construction of databases are significant tasks. However, research on automatic metadata extraction from Korean papers is not being actively conducted currently owing to insufficient Korean training data. We automatically constructed the largest labeled corpus in South Korea to date from 315,320 PDF papers belonging to 503 Korean academic journals and this labeled corpus can be used for training the models of automatic extraction for 12 metadata types from PDF papers. This labeled corpus is available at https://doi.org/10.23057/48. Moreover, we developed inspection process and guidelines for the automatically constructed data and performed a full inspection of the validation and testing data. The reliability of the inspected data was verified through the inter-annotator agreement measurement. Using our corpus, we trained and evaluated the BERT based transfer learning model to verify its reliability. Furthermore, we proposed new training methods that can improve the metadata extraction performance of Korean papers, and through these methods, we developed KorSciBERT-ME-J and KorSciBERT-ME-J+C models. The KorSciBERT-ME-J showed the highest performance with an F1 score of 99.36%, as well as robust performance in automatic metadata extraction from Korean academic papers in various formats.
Structural instabilities of excited phases

The structural stability of various elemental metals (Ti, Sc, Al, Mo, and Nb), ordered compounds (PtTi and PtV), and disordered Ni-Cr alloys along distortion paths linking high-symmetry structures are investigated. A number of high-symmetry nonequilibrium structures are found to be mechanically unstable for these deformation paths, even for structures that occur at high temperature. For Ti, the electronic entropy is found to stabilize of the bcc phase at high temperatures, but without vibrational effects the hcp{leftrightarrow}bcc transition would occur at much higher temperatures than observed. To treat disordered alloys along the Bain distortion path, the cluster expansion method is applied to the body-centered-tetragonal lattice, with particular choices of clusters in order to guarantee that the effective cluster interactions comply with the symmetry conditions of the cubic lattices. For disordered Ni-Cr alloys, the range of composition where the bcc and fcc phases are mechanically stable is determined. {copyright} {ital 1997} {ital The American Physical Society}
On the remarkable nonlinear diffusion equation (∂/∂x)[a (u+b)−2(∂u/∂x)]−(∂u/∂t)=0

We study the invariance properties (in the sense of Lie–Backlund groups) of the nonlinear diffusion equation (∂/∂x)[C (u)(∂u/∂x)]−(∂u/∂t) =0. We show that an infinite number of one‐parameter Lie–Backlund groups are admitted if and only if the conductivity C (u) =a (u+b)−2. In this special case a one‐to‐one transformation maps such an equation into the linear diffusion equation with constant conductivity, (∂2ū/∂x2)−(∂ū/∂t) =0. We show some interesting properties of this mapping for the solution of boundary value problems.
Assignments of laser lines in optically pumped CH3CN

A careful analysis of the rotovibrational spectroscopic data of CH3CN is presented taking into account Fermi and Coriolis interactions. A large majority of the FIR lines obtained by optical pumping is assigned. New values are proposed for some molecular constants and the need of more accurate experimental investigation is pointed out.
A Parallel and Vector Variant of the Cyclic Reduction Algorithm

The Buneman variant of the block cyclic reduction algorithm begins as a highly parallel algorithm, but collapses with each reduction to a very serial one. Using partial fraction expansions of rational matrix functions, it is shown how to regain the parallelism. The resulting algorithm using $n^2 $ processors runs in $O(\log ^2 n)$ time.
Design of Stable Digital V2 Controllers for the Synchronous Noninverting Buck–Boost Converter

The noninverting buck–boost converter is suitable for battery-powered applications as it can operate in buck, buck–boost, and boost modes. Traditional current mode and voltage mode controllers are generally employed to control it in a closed loop. It is well established that a peak V2 controller provides superior load-transient performance compared to conventional current mode and voltage mode controllers. However, a peak V2 controller cannot be applied to the noninverting buck–boost converter during boost and buck–boost modes because of its nonminimum phase behavior. This article proposes a digital peak V2 controller that can work effectively during all modes. The proposed controller samples both the inductor current and output voltage at the rate of the switching frequency. Thus, the digital implementation of this controller does not need high-speed analog-to-digital converters (ADCs). Unlike traditional peak V2 controllers, the proposed controller does not depend on the effective series resistance (ESR) of the output capacitor. An average model-based small-signal model of the proposed controller is presented. Analysis shows that a sufficient current loop gain can make the system behave like a first-order system. This enables the designer to employ a PI controller to achieve superior transient performance in all the modes. Furthermore, fast-scale stability analysis of the controller is carried out using approximate discrete-time models to derive an analytical stability boundary of slope compensation. A noninverting buck–boost converter prototype is fabricated, and the proposed controller is implemented using an FPGA platform. Experimental results show a close correlation with the analysis.
Multi-Agent Deep Reinforcement Learning-Based Interdependent Computing for Mobile Edge Computing-Assisted Robot Teams

A group of robots can be assigned with different roles to collaboratively conduct interdependent tasks. The robots form a multi-robot system (MRS), where one robot's decision or action relies on the others'. This paper addresses the sequential decision problem of user association and resource allocation in a mobile edge computing (MEC)-enabled, wirelessly-connected MRS to maximize the time-averaged completion rate of interdependent computing tasks. The problem is challenging due to the partial observability of the network environment, and the delicate delay requirements of interdependent computing tasks. A new decentralized partially observable Markov decision process (Dec-POMDP) problem is reformulated, where edge servers act as intelligent agents and can make decentralized decisions about user association and resource management with their local information of the network state. By leveraging the multi-agent deep deterministic policy gradient (MADDPG) theory, a new cooperative multi-agent deep reinforcement learning (MADRL) model is developed to enable interdependent computing. Simulations show the merits of our approach in terms of task completion rate compared to existing techniques.
Pursuit-evasion orbital game for satellite interception and collision avoidance

This paper develops and evaluates a pursuit-evasion orbital game approach for satellite interception and collision avoidance. Using a coupled zero-sum differential pursuit-evasion game, the pursuer minimizes the satellite interception time, and the evader tries to maximize interception time for collision avoidance. For the satellite interception problem we design an algorithm for pursuer and one for collision avoidance, where the game solution controls the evader satellite. The interception-avoidance (IA) game approach provides a worst-case solution, which is the robust lower-bound performance case. We divide our IA algorithm into two parts: first, the pursuer will rotate its orbit to the same plane of the evader; and second, the two spacecraft will play a zero-sum pursuit-evasion (PE) game. A two-step setup saves energy during the PE game because rotating a pursuer orbit requires more energy than maneuvering within the orbit plane. For the PE orbital game, an optimum open loop feedback saddle-point equilibrium solution is calculated between the pursuer and evader control structures. Using the open-loop feedback control rule, each player will calculate their distributed control track state. Numerical simulations are calculated to demonstrate the performance.
On separating amplitude from frequency modulations using energy operators

To estimate the amplitude envelope and instantaneous frequency of an AM-FM signal the authors developed a novel approach that uses nonlinear combinations of instantaneous signal outputs from an energy-tracking operator to separate its output energy product into its amplitude modulation and frequency modulation components. This energy separation algorithm is then applied to search for modulations in speech resonances, which the authors model using AM-FM signals. The theoretical and experimental results demonstrate that the energy separation algorithm, due to its low computational complexity and instantaneously adapting nature, is very useful in detecting modulation patterns in speech and other time-varying signals. <<ETX>>
Physico-morphological Characteristics of Semen Ejaculates in Vrindavani Crossbred Bulls

In crossbred cattle bulls, poor seminal quality and freezability are major constraints. The present study was conducted to determine semen quality parameters of Vrindavani crossbred bulls. In this study 130 semen samples were collected from five Vrindavani crossbred bulls. The volume, mass motility, concentration and individual progressive motility, viability and abnormality of spermatozoa were examined. Then ejaculates were categorized into four groups on the basis of spermatozoa concentration and individual progressive motility. The percentage of normozoospermia, asthenozoopsermia, oligozoospermia and oligoasthenozoospermia ejaculates were 44.62%, 29.23%, 11.54% and 14.61%, respectively. The overall mean of volume, mass motility, concentration of spermatozoa, individual progressive motility, viability and sperm abnormality in semen ejaculates of crossbred Vrindavani bulls were 4.64±0.63 mL, 2.48±0.09, 772.20±27.95 million/mL, 65.08±1.47%, 79.94±1.07% and 7.82±0.44%, respectively. Ejaculate mass motility, concentration, progressive motility and abnormality of spermatozoa varied significantly (p<0.05) among the semen ejaculate categories. The mean of the mass motility was significantly higher in normozoospermia as compared to other ejaculates categories. The normozoospermia and asthenozoospermia groups had significantly higher spermatozoa concentration than oligozoospermia and oligoasthenozoospermia groups. The normozoospermia ejaculates had significantly higher progressive motile spermatozoa as compared to other three ejaculates categories. Percent livability of spermatozoa in normozoospermia and oligozoospermia groups were significantly higher than asthenozoospermia and oligoasthenozoospermia groups. Percent abnormal spermatozoa on the other hand, was significantly lower in normozoospermia and oilgozoospermia groups than asthenozoopsermia and aligoasthenozoospermia groups.
Deep Learning-based SNR Estimation for Multistage Spectrum Sensing in Cognitive Radio Networks

 Vacant frequency bands are used in cognitive radio (CR) by incorporating the spectrum sensing (SS) technique. Spectrum sharing plays a central role in ensuring the effectiveness of CR applications. Therefore, a new multi-stage detector for robust signal and spectrum sensing applications is introduced here. Initially, the sampled signal is subjected to SNR estimation by using a convolutional neural network (CNN). Next, the detection strategy is selected in accordance with the predicted SNR levels of the received signal. Energy detector (ED) and singular value-based detector (SVD) are the solutions utilized in the event of high SNR, whilst refined non-negative matrix factorization (MNMF) is employed in the case of low SNR. CNN weights are chosen via the Levy updated sea lion optimization (LU-SLNO) algorithm inspired by the traditional sea lion optimization (SLNO) approach. Finally, the outcomes of the selected detectors are added, offering a precise decision on spectrum tenancy and existence of the signal.
Plasma-Based Flow Control for Delay of Excrescence-Generated Transition

Numerical simulations are carried out to explore flow control that delays transition generated by excrescence on a platelike geometry in subsonic flow. Both forward-facing and rearward-facing steps of small roughness heights are considered in the simulations. These are representative of joints and other surface imperfections on wing sections that disrupt laminar flow, thereby increasing skin friction and drag. Dielectric barrier discharge plasma-based flow control is employed to delay transition and increase the extent of the laminar flow region. Solutions are obtained to the Navier–Stokes equations, which were augmented by source terms used to characterize the body force imparted by a plasma actuator on the fluid. A simple phenomenological model provided these forces resulting from the electric field generated by the plasma. The numerical method is based upon a high-order numerical scheme and an implicit time-marching approach on overset mesh systems used to describe the steps. Very small-amplitude numer.