Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of Inhibition Activity of Dihydrofolate Reductase Inhibitors With Multivariate Adaptive Regression Splines

Dihydrofolate reductase (DHFR) enzyme is a crucial component of cell growth and proliferation in the human body, making it an important target for treating cancer diseases. This study aims to predict the inhibitory activity (pXC50) of dihydrofolate reductase inhibitors in terms of the quantitative structure-activity relationship (QSAR) model. Interpretation of the QSAR model is vital for understanding the physicochemical processes and to assist structural optimisation. Multivariate adaptive regression splines (MARS), a non-parametric technique, is proposed to model the non-linear relationship between the predictor variables and the response variable of a high-dimensional dataset. The dataset used in this research consists of pXC50 activity of 778 DHFR inhibitors. For our study, the data is divided into 80% training set for model building and 20% testing set for model validation. In comparison, the baseline methods deep neural network (DNN) and partial least squares (PLS) are also applied to QSAR modeling. The testing results show that MARS has the best prediction accuracy according to different measures, where RMSE, MAE, MAPE, and RMSPE are 0.96, 0.69, 0.11, and 0.15 respectively. The efficiency of MARS is apparent in its robust interaction of variables, prediction accuracy, and ability to overcome the neural network’s black box system. Thus, MARS technique can be considered an excellent tool for modeling QSAR high-dimensional datasets while exploring the non-linear patterns of data.
Euler B-spline for Curve Interpolation and Data Fitting ⋆

Euler spirals are a kind of fair curves that have linear curvatures in terms of arc length. However, Euler spirals cannot be represented by polynomials exactly. In this paper, we propose an algorithm for approximating a segment of Euler spiral which interpolates two specified points and two tangents at the points by a B-spline curve. The approximating B-spline curve is obtained as the solution to a differential equation which satisfies the boundary conditions. Similar to the exact interpolating Euler spiral, the interpolating B-spline curve is also fair and has approximate linear curvature. Furthermore, an algorithm for fitting data points by a sequence of smoothly connected fair B-spline curves is also developed.
Development of a Micromegas Time Projection Chamber in Xe-based Penning Mixtures for Rare Event Searches

The performance of a microbulk Micromegas High Pressure Time Projection Chamber (HP TPC) filled with Xe-based Penning mixtures towards Rare Event Searches, like the observation of the neutrinoless double beta decay or the direct detection of dark matter particles, was studied. Two Xe-based Penning mixtures were analyzed in a small TPC prototype (2.4 l of volume): a xenon+trimethylamine (Xe+TMA) mixture and a xenon+neon (Xe+Ne) mixture. From X-rays measurements, it was found that a mixture of Xe (which should be enriched in 136Xe) with TMA concentration between 1-2% is very attractive for neutrinoless double decay searches. The most important advantage of this mixture is the improvement in energy resolution, reaching values that fulfill the requirements of an experiment looking for this process. In particular, values of energy resolution of 9.6% FWHM at 10 bar for 22.1 keV were attained, which extrapolate into 0.9% FWHM at the transition energy value. Gains up to a factor 100 higher and required amplification fields at least 40% lower than in pure Xe were achieved. On the other hand, the drift velocity in Xe+TMA mixtures is higher than in pure Xe in the range 50-400 V/cm/bar, reaching values up to an order of magnitude superior; for instance, for a reduced drift field (Ed/P) of 300 V/cm/bar the drift velocity in a Xe+2.2%TMA mixture is 1.3 cm/us and for pure Xe 0.14 cm/us. A reduction of the longitudinal diffusion coefficient by a factor about 3 respect to pure Xe was also observed. On the other hand, columnar recombination was observed for alpha-particles in Xe+TMA mixtures. These results represent a first step towards the evaluation of the idea to use this mixture as medium gas for directional dark matter searches on virtue of the columnar recombination effect. The direction of the nuclear recoil of each event could be deduced thanks to the dependence of charge collection on the track angle, which would be an identifying signature of dark matter interactions. Furthermore, the study of the Xe+Ne mixtures indicated that a microbulk Micromegas High Pressure TPC with Ne concentration between 20 and 30% may be optimum for application at low energy as for axions and dark matter searches, where the presence of a lighter noble gas is of interest.
Efficient algorithms for drawing planar graphs

This thesis presents efficient algorithms for drawing planar graphs. Graph drawing addresses the problem of constructing geometric representation of information and finds applications in almost every branch of science and technology. In this thesis we study rectangular drawings, orthogonal drawings, convex drawings and our newly defined box-rectangular drawings. Rectangular drawings and box-rectangular drawings have practical applications in VLSI floorplanning and in architectural floorplanning, whereas orthogonal drawings have applications in circuit schematics, data-flow diagrams etc. We give a linear-time algorithm for finding a rectangular drawing of a plane graph if it exists, and obtain the best possible upper bound on grid size for a rectangular drawing. Minimizing the number of bends in an orthogonal drawing is a challenging problem. We give a linear-time algorithm for finding an orthogonal drawing of a triconnected cubic plane graph with the minimum number of bends. We introduce a new drawing style called box-rectangular drawing and obtain a necessary and sufficient condition for a plane graph to have a box-rectangular drawing. We also present the corresponding linear-time algorithm. We newly define 4-canonical decomposition and give a linear-time algorithm for finding a 4-canonical decomposition of a 4-connected planar graph. Our 4-canonical decomposition has applications in finding a convex drawing of a 4-connected planar graph.
Procrastination Predicts Future Internet Use Disorders in Adolescents but Not Vice Versa: Results from a 12-Month Longitudinal Study

Background: Use of Internet applications is often associated with postponing real-life obligations. Previous cross-sectional studies have reported a positive association between procrastination and Internet use disorders (IUDs). Further, procrastination is included in theoretical models explaining the development of IUDs. However, little is known about the temporal relationship; thus, longitudinal studies identifying the specific predictive direction are required. Methods: Using a cross-lagged panel design, a total of 240 students who were at high risk for IUDs, aged between 12 and 18 years (M = 15.17, SD = 1.66) were assessed at baseline (t1) and reassessed one year later (t2) with standardized measures for IUDs and procrastination. Results: Our results showed that IUD symptom severity at t2 was significantly predicted both by IUD symptom severity at t1 and procrastination at t1. However, procrastination at t2 was predicted only by procrastination at t1 but not by IUD symptom severity at t1. Conclusions: We could not find a reciprocal relationship between procrastination and IUD symptom severity. Procrastination appears to be a causal risk factor for IUDs, but not a consequence. As a modifiable risk factor, procrastination is a promising starting point for preventive and therapeutic interventions for IUDs.
Delta Path Tracing for Real-Time Global Illumination in Mixed Reality

Visual coherence between real and virtual objects is important in mixed reality (MR), and illumination consistency is one of the key aspects to achieve coherence. Apart from matching the illumination of the virtual objects with the real environments, the change of illumination on the real scenes produced by the inserted virtual objects should also be considered but is difficult to compute in real-time due to the heavy computation demands of global illumination. In this work, we propose delta path tracing (DPT), which only computes the radiance blocked by the virtual objects from the light sources at the primary hit points of Monte Carlo path tracing, then combines the blocked radiance and multi-bounce indirect illumination with the image of the real scene. Multiple importance sampling (MIS) between BRDF and environment map is performed to handle all-frequency environment maps captured by a panorama camera. Compared to conventional differential rendering methods, our method can remarkably reduce the number of times required to access the environment map and avoid rendering scenes twice. Therefore, the performance can be significantly improved. We implement our method using hardware-accelerated ray tracing on modern GPUs, and the results demonstrate that our method can render global illumination at real-time frame rates and produce plausible visual coherence between real and virtual objects in MR environments.
Transactive Energy Model – The approach used for Two–Sided Electricity Market

In energy sector, transformation occurs due to penetration of increased renewable energy sources together with distributed energy resources and thus leads to the development of existing electricity market reformation. The electricity market reformations have an active customers and prosumers. The prosumers can produce as well as consume energy. The consumers consume energy from grid network. The active customers and prosumers leads to the development of two sided market with different approaches such as demand response, virtual power plant, transactive energy frame work and peer -2- peer energy trading. This paper discuss about the challenges and opportunities related to two sided electricity market with transactive framework. The transactive energy control is considered to be a new method but widely studied in recent years. The important key point is, it deals with the control and profitable system technology to have a generation and load equilibrium in electrical energy market infrastructure.
Perturbed Unicycle Mobile Robots: A Second-Order Sliding-Mode Trajectory Tracking Control

This article contributes to the design of a second-order sliding-mode controller for the trajectory tracking problem in perturbed unicycle mobile robots. The proposed strategy takes into account the design of two particular sliding variables, which ensure the convergence of the tracking error to the origin in a finite time despite the effect of some external perturbations. The straightforward structure of the controller is simple to tune and implement. The global, uniform, and finite-time stability of the closed-loop tracking error dynamics is demonstrated by means of Lyapunov functions. Furthermore, the performance of the proposed approach is validated through some experiments using a QBot2 unicycle mobile robot.
Design and Investigation of graphene based 2 × 2 CPW feed Vivaldi MIMO Antenna for THz Applications

In this paper, 2 × 2 CPW feed Vivaldi multiple-input-multiple-outputs (MIMO) antenna is projected for different Terahertz (THz) applications. Graphene material is utilized over the radiating copper patch of Vivaldi’s arm to enhance the conductivity and achieve the frequency reconfigurability of the proposed design. The projected antenna is configured by placing all four elements at the orthogonal position to each other. Also, all the elements are structured on the SiO2 substrate having a dielectric permittivity of 3.75. Reconfigurable characteristics are observed by changing the chemical potential with bias voltage of graphene sheets. This Vivaldi-structured MIMO antenna shows good isolation (>25 dB), maximum Gain of 10 dB, and maximum radiation efficiency of around 92.5% in the operating frequency band from 0.65 THz to 1.3 THz. The Envelop-Correlation-Coefficient (ECC) and Diversity-Gain (DG) are also studied to verify the MIMO performance.
On the Theory and Application of Distributed Asynchronous Optimization over Weakly Coupled Renewal Systems

This paper considers optimization over multiple renewal systems coupled by time average constraints. These systems act asynchronously over variable length frames. For each system, at the beginning of each renewal frame, it chooses an action which affects the duration of its own frame, the penalty, and the resource expenditure throughout the frame. The goal is to minimize the overall time average penalty subject to several overall time average resource constraints which couple these systems. This problem has applications to task processing networks, coupled Markov decision processes(MDPs) and so on. We propose a distributed algorithm so that each system can make its own decision after observing a global multiplier which is updated slot-wise. We show that this algorithm satisfies the desired constraints and achieves $\mathcal{O}(\varepsilon)$ near optimality with $\mathcal{O}(1/\varepsilon^2)$ convergence time.
A Bivariant Chern Character, II

In [Con2] Connes introduced cyclic cohomology HC*(A) for an associative algebra A. When A is a complex algebra he constructed a Chern character for p-summable Fredholm modules over A taking values in HC*(A). As a very special case, when X is a closed C ∞-manifold and A = C ∞ (X), this construction recovers the usual Chern character, which is a rational isomorphism from the K-homology K 0(X) to , the even dimensional deRham homology of X.
The Genomic Landscape of Melanoma and Its Therapeutic Implications

Melanoma is one of the most aggressive malignancies of the skin. The genetic composition of melanoma is complex and varies among different subtypes. With the aid of recent technologies such as next generation sequencing and single-cell sequencing, our understanding of the genomic landscape of melanoma and its tumor microenvironment has become increasingly clear. These advances may provide explanation to the heterogenic treatment outcomes of melanoma patients under current therapeutic guidelines and provide further insights to the development of potential new therapeutic targets. Here, we provide a comprehensive review on the genetics related to melanoma tumorigenesis, metastasis, and prognosis. We also review the genetics affecting the melanoma tumor microenvironment and its relation to tumor progression and treatment.
Advantages of Total Bilirubin for Predicting Malignant Obstructive Jaundice, A Combination of the Pandemic Era and Limited Resources Settings

BACKGROUND: Hepatopancreatobiliary (HPB) cancer incidence and mortality are increasing worldwide. An initial diagnostic predictor is needed for recommending further diagnostic modalities, referral, and curative or palliative decisions. There were no studies conducted in area with limited accessibility setting of the COVID-19 pandemic, coupled with limited human resources and facilities. AIM: We aimed to investigate the advantages of total bilirubin for predicting malignant obstructive jaundice, a combination of the pandemic era and limited resources settings. METHODS: Data from all cholestasis jaundice patients at M. Djamil Hospital in Pandemic COVID-19 period from July 2020 to May 2022 were retrospectively collected. The data included demographics, bilirubin fraction results, and final diagnosis. Bivariate analysis for obtain demographic risk factor, and Receiver Operating Characteristics (ROC) analysis for getting bilirubin value. RESULTS: Of a total 132 patients included, 35.6% were malignant obstructive jaundice, and Pancreatic adeno ca was the most malignant etiology (34.4%). Bivariate analysis showed a significant correlation between age and malignant etiology (p = 0,024). Direct and total Bilirubin reach the same level of Area Under Curve (AUC). Total bilirubin at the cutoff point level of 10.7 mg/dl had the most optimal results on all elements of ROC output, AUC 0.88, sensitivity 76.6%, specificity 90.1%, +LR 8.14, and -LR 0.26. CONCLUSION: The bilirubin fraction is a good initial indicator for differentiating benign and malignant etiology (AUC 0.8–0.9) in pandemic era and resource-limited areas to improve diagnostic effectiveness and reduce referral duration.
Geometry and topology extraction and visualization from scalar and vector fields

T h is d o c to ra l w o rk c o n tr ib u te s in s e v e ra l m a jo r a s p e c ts : (1 ) E x tr a c ti o n o f g e o m e tr ic a l a n d t o p o lo g ic a l in fo rm a ti o n o f 1 a n d 2 -m a n if o ld s p re s e n t in s ta ti c a n d v id e o i m a g in g . T h is e n d e a v o r in c lu d e s s e v e ra l v a ri a n ts o f M a rc h in g C u b e s a lg o ri th m , in c lu d in g e n h a n c e d p re c is io n is o -s u rf a c e s fo r n o n -n e g a ti v e s c a la r fi e ld s . (2 ) H y b ri d v is u a li z a ti o n o f s c a la r a n d v e c to r fi e ld s , a lo n g w it h s im p le x g e o m e tr y a n d t o p o lo g y , u n d e rl y in g i n m e d ic a l, g e o -s c ie n c e s a n d e n te rt a in m e n t d a ta . (3 ) O p ti m iz a ti o n o f p a ra ll e l v is u a li z a ti o n a lg o ri th m s a n d u s a g e o f te x tu re o p ti m iz e d h a rd w a re a s a m e a n s o f e ff ic ie n t s c ie n ti fi c c o m p u ta ti o n a n d v is u a li z a ti o n . (4 ) D e fi n it io n o f W E B IS O s ta n d a rd s fo r in te ra c ti v e h o m o g e n e o u s v is u a li z a ti o n o f s im p le x , s c a la r a n d v e c to r fi e ld d a ta i n m o b il e d e v ic e s ( s m a rt c e ll p h o n e s , p a d s , ta b le ts , e tc .) . (5 ) A n o v e l te c h n iq u e fo r v o lu m e re n d e ri n g in lo w -l e v e l m o b il e d e v ic e s , a lo n g w it h p ra c ti c a l, fe a s ib le s o lu ti o n s fo r o v e rc o m in g c u rr e n t a rc h it e c tu re li m it a ti o n s . T h is d o c to ra l w o rk h a s b e e n th o ro u g h ly s c re e n e d b y t h e i n te rn a ti o n a l a c a d e m ic c o m m u n it y in t h e s c e n a ri o o f a v ig o ro u s p u b li c a ti o n a c ti v it y o f th e d o c to ra l te a m , s c ru ti n iz e d b y w o rl d t o p e x p e rt s i n t h e r e le v a n t fi e ld s .
A Novel SVPWM Strategy for Multilevel Converters Based on Sector Triangle Numbering

In order to simplify the location of the reference vector, avoid calculating a large number of redundant switching states and selecting the optimal switching state, and apply the space vector modulation to any level converters, a novel space vector pulse width modulation (SVPWM) strategy based on sector triangle numbering for multilevel converters is proposed in this article. First, the reference vector located in the large sector <inline-formula><tex-math notation="LaTeX">$N$</tex-math></inline-formula> is rotated clockwise to Sector I, and the numbers <inline-formula><tex-math notation="LaTeX">$T_{n}$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$K$</tex-math></inline-formula>, and <inline-formula><tex-math notation="LaTeX">$q$</tex-math></inline-formula> of the small sector triangle where the rotated vector is located are calculated. Then, the three vertex vectors of the small sector triangle where the reference vector is located are directly calculated using <inline-formula><tex-math notation="LaTeX">$N$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$T_{n}$</tex-math></inline-formula>, <inline-formula><tex-math notation="LaTeX">$K$</tex-math></inline-formula>, and <inline-formula><tex-math notation="LaTeX">$q$</tex-math></inline-formula> to realize the reference vector location, which is a very simple reference vector location method. Next, the switching state corresponding to the space vector is calculated using the minimum common-mode voltage constraint, which does not need to calculate the redundant switching states and select the optimal switching state. The proposed SVPWM strategy is applicable to any level converters without increasing the calculation workload and has strong engineering applicability. Simulations and experiments verified the correctness and feasibility of the proposed SVPWM strategy.
High Performance Adaptive Mppt Technique For Photovoltaic Power System

MPPT’s or maximum power point trackers, have a crucial function, solar system’s (PV) generators play a crucial role in generating electricity since they produce the most electricity(MPP) and are accessible despite swings in temperature and irradiance. The photovoltaic (PV) system is the major challenging one to take energy efficient. Maximum power point tracker (MPPT)has a vital role in this technique. PSO and P&O algorithm is implemented for tracking of maximum power in this system. As a result, MPPT’s effectiveness is in forefront of global PV system is increased by boost converter various MPPT algorithm control them. We focus on trackers because they are easy to use inside programmable electric circuits, one of which is perturb and observe approach. In order to explore a PV panel’s output, which is controlled by its behavior, this project incorporates a large number of environmental parameters in model. MPPT tracking tools is the suggested system’s components and their roles are carried out.
Lagrange multiplier rules for approximate solutions in vector optimization

In Asplund space, Lagrange multiplier rules for approximate solutions of nonsmooth vector optimization problems are studied. The relationships between the vector and the scalar optimization problems are established. And the optimality conditions of approximate solutions for vector optimization are obtained. Moreover, the vector variational inequalities are considered by applying the partial results given in this paper.
Targeted DNA Demethylation: Vectors, Effectors and Perspectives

Aberrant DNA hypermethylation at regulatory cis-elements of particular genes is seen in a plethora of pathological conditions including cardiovascular, neurological, immunological, gastrointestinal and renal diseases, as well as in cancer, diabetes and others. Thus, approaches for experimental and therapeutic DNA demethylation have a great potential to demonstrate mechanistic importance, and even causality of epigenetic alterations, and may open novel avenues to epigenetic cures. However, existing methods based on DNA methyltransferase inhibitors that elicit genome-wide demethylation are not suitable for treatment of diseases with specific epimutations and provide a limited experimental value. Therefore, gene-specific epigenetic editing is a critical approach for epigenetic re-activation of silenced genes. Site-specific demethylation can be achieved by utilizing sequence-dependent DNA-binding molecules such as zinc finger protein array (ZFA), transcription activator-like effector (TALE) and clustered regularly interspaced short palindromic repeat-associated dead Cas9 (CRISPR/dCas9). Synthetic proteins, where these DNA-binding domains are fused with the DNA demethylases such as ten-eleven translocation (Tet) and thymine DNA glycosylase (TDG) enzymes, successfully induced or enhanced transcriptional responsiveness at targeted loci. However, a number of challenges, including the dependence on transgenesis for delivery of the fusion constructs, remain issues to be solved. In this review, we detail current and potential approaches to gene-specific DNA demethylation as a novel epigenetic editing-based therapeutic strategy.