Miracle-dz/UniFAR-FTUs huggingface dataset:
Incorporating Latent Constraints to Enhance Inference of Network Structure

A complex network is a model representation of interactions within technological, social, information, and biological networks. Oftentimes, we are interested in identifying the underlying network structure from limited and noisy observational data, which is a challenging problem. Here, to address this problem, we propose a novel and effective technique that incorporates latent structural constraints into binary compressed sensing. We show high accuracy and robust effectiveness of our proposed method by analyzing artificial small-world and scale-free networks, as well as two empirical networks. Our method requires a relatively small number of observations and it is robust against strong measurement noise. These results suggest that incorporating latent structural constraints into an algorithm for identifying the underlying network structure improves the inference of connections in complex networks.
System Order Determination by Using LDL T Decomposition and Information Criteria

In t . hls paper, we present a new ordeI determin且tionmethod of applying the LDL T decomposi・ tion加 d泊forma十ioncriteria. A statistical test is availal】lefor the syはemorder determination, and is hased on the relation hetween the system order加 dthe rank of the correlation matrix of the Hankel matrix consi抗日 ofinput-output data. We apply LDL T decomposition and Akaike's Information Criterion (AIC) [3] to determine the r加 k, so that we r.an determine the system order hy the minimum AIC estimate (MAICE). AIC requireB the heavy complltation hecause the maximum likelihood estimates should he obtained by solving the nonlinear optimi7.ation problem. Thus we apply a suhspace method, e.g., N4SID (Numeri・ r.al algorithms for Sut】 日paceState Space System IDentification) [4] , to simpliかthecomp川 ation of the log-likelihood functions. But in suhspace method日, stahility of the ohtained model cannot he gu紅 anteed.When the model ohtained is unstable, the maximum likelihood estimates cannot he ohtained. So we apply the method [6] that can guarantee the stability of the obtained model to MAICE.
Higgs Boson Properties

This chapter presents an overview of the measured properties of the Higgs boson discovered in 2012 by the ATLAS and CMS collaborations at the CERN LHC. Searches for deviations from the properties predicted by the standard theory are also summarised. The present status corresponds to the combined analysis of the full Run 1 data sets of collisions collected at centre-of-mass energies of 7 and 8 TeV.
On anisotropy evolution in finite strain plasticity

Motivated by the experimental investigations on cold rolled sheet metal presented in [1], this contribution focuses on a specific modelling approach to capture the evolution of (plastic) material symmetry groups that is induced by finite plastic deformation processes. The ensuing developments are based on the general theoretical framework by Lu and Papadopoulos with regard to evolving material symmetries proposed in [2, 3]. In particular, we elaborate a specific form of the evolution equation for the structural tensor that characterises the respective material symmetry group and show that the simulation results are in good accordance with the experimental findings.
Torsional Alfvén waves in small scale density threads of the solar corona

The density structuring of the solar corona is observed at large scales (loops and funnels), but also at small scales (sub-structures of loops and funnels). Coronal loops consist of thin density threads with sizes down to (and most probably below) the resolution limit. We study properties of torsional Alfven waves propagating in inhomogeneous cylindrical density threads using the two-fluid magnetohydrodynamic equations. The eigenmode solutions supported by such a structure are obtained and analysed. It is shown that the dispersive and dissipative effects become important for the waves localised in thin threads. In this case, the Alfven wave continuum is replaced with a discrete spectrum of Alfven waves. This mathematical model is applied to the waves propagating in coronal structures. In particular, we consider ∼1 Hz Alfven waves propagating along density threads with a relatively smooth radial profile, where a density contrast of about 1.1 is attained at radial distances of about 0.1 km. We found that the dissipation distance of these waves is less than the typical length of hot coronal loops, 50 Mm. Torsional Alfven waves are localised in thin density threads and produce localised heating. Therefore, these waves can be responsible for coronal heating and for maintenance of small-scale coronal structuring.
The Modeling of the Young's Interference Experiment in terms of Single-photon wave function in the coordinate representation

The main principles of photon quantum mechanics describing its one-particle states with the help of the wave function in coordinate representations are given. This wave function (packet) is the superposition of the basic bivectors that are generalized eigenfunctions of energy, momentum, and helicity operators. The quantum-mechanical approach is offered for an explanation of the interference Young's experiment. This explanation is especially important for new interpretation of the non-laser method of obtaining the interference by the amplitude division, as in this case it is traditionally assumed that the radiation of one light train of a single atom interferes with itself. In our explanation, not both “halves” of some real train (“scrap”) of the electromagnetic wave interfere with each other, but the both terms of the photon's wave function do this. Nevertheless, the wave function is not directly measured by experience, and therefore it does not exist as a physical object. The attraction of the wave function to the explanation of single-photon interference obtained “by the division of the wave front” is obviously also necessary. Therefore, the situation for the photons emitted by individual atoms (and also, obviously, by laser), is absolutely similar to the situation with the particles having mass, whose distribution in space is described by wave function in coordinate representation. It is pointed out that in fact the photon is not some “formed” quantum particle, but it is a quasi-particle arising when a certain spin wave propagates in a physical vacuum at Planck distances. Keywords—Schrödinger equation; Maxwell’s equations; wave packet; probability density; bivector; detector; extreme maximon, friedmon, planckeon; Planck’s parameters; wave-particle duality.
Off the grid low-rank matrix recovery

Matrix sensing problems capitalize on the assumption that a data matrix of interest is low-rank or it can be well-approximated by a low-rank matrix. This low dimensional structure sometimes arises because the data matrix is obtained by sampling a âĂĲsmooth" function on a regular (or structured) grid. However, in many practical situations the measurements are taken on an irregular grid (that is accurately known). This results in what we call an "unstructured data matrix" that is a worse ﬁt for the low rank model compared to its regular counterpart and results in degraded reconstruction via rank penalization techniques. In this talk, we propose a modiﬁed low-rank matrix recovery work-ﬂow that admits unstructured observations. Speciﬁcally, we incorporate into the nuclear-norm minimization problem a regularization operator that (suﬃciently accurately) maps structured data to unstructured data. As a result, we are able to compensate for data irregularity. We establish recovery error bounds for our method. Furthermore, we will present numerical experiments, both in the matrix sensing and matrix completion settings, including applications to seismic trace interpolation to demonstrate the potential of the approach. This is joint work with
The Adomian Decomposition Method of Volterra Integral Equation of Second Kind

In this work, we consider linear and nonlinear Volterra integral equations of the second kind. Here, by converting integral equation of the first kind to a linear equation of the second kind and the ordinary differential equation to integral equation we are going to solve the equation easily. The Adomian decomposition method or shortly (ADM) is used to find a solution to these equations. The Adomian decomposition method converts the Volterra integral equations into determination of computable components. The existence and uniqueness of solutions of linear (or nonlinear) Volterra integral equations of the second kind are expressed by theorems. If an exact solution exists for the problem, then the obtained series convergence very rabidly to that solution. A nonlinear term F(u) in nonlinear volterra integral equations is Lipschitz continuous and has polynomial representation. Finally, the sufficient condition that guarantees a unique solution of Volterra (linear and nonlinear) integral equations with the choice of the initial data is obtained, and the solution is found in series form. Theoretical considerations are being discussed. To illustrate the ability and simplicity of the method. A few examples including linear and nonlinear are provided to show validity and applicability of this approach. The results are taken from the works mentioned in the reference.
On the geometry of optimization problems and their structure

Dans de nombreux domaines tels que l’apprentissage statistique, la recherche operationnelle ou encore la conception de circuits, une tâche est modelisee par un jeu de parametres que l’on cherche a optimiser pour prendre la meilleure decision possible. Mathematiquement, le probleme revient a minimiser une fonction de l’objectif recherche par des algorithmes iteratifs. Le developpement de ces derniers depend alors de la geometrie de la fonction ou de la structure du probleme. Dans une premiere partie, cette these etudie comment l’acuite d’une fonction autour de ses minima peut etre exploitee par le redemarrage d’algorithmes classiques. Les schemas optimaux sont presentes pour des problemes convexes generaux. Ils necessitent cependant une description complete de la fonction, ce qui est rarement disponible. Des strategies adaptatives sont donc developpees et prouvees etre quasi-optimales. Une analyse specifique est ensuite conduite pour les problemes parcimonieux qui cherchent des representations compressees des variables du probleme. Leur geometrie conique sous-jacente, qui decrit l’acuite de la fonction de l’objectif, se revele controler a la fois la performance statistique du probleme et l’efficacite des procedures d’optimisation par une seule quantite. Une seconde partie est dediee aux problemes d’apprentissage statistique. Ceux-ci effectuent une analyse predictive de donnees a l’aide d’un large nombre d’exemples. Une approche generique est presentee pour a la fois resoudre le probleme de prediction et le simplifier en groupant soit les variables, les exemples ou les tâches. Des methodes algorithmiques systematiques sont developpees en analysant la geometrie induite par une partition des donnees. Une analyse theorique est finalement conduite lorsque les variables sont groupees par analogie avec les methodes parcimonieuses.
Acoustic damping of an annular tail-pipe under mean flow conditions

A damping device, consisting of an annular tail-pipe, has been developed. It is applicable in situations wherein acoustic damping is required in combination with low flow resistance. The device consists of a central tube surrounded by a narrow slit. The central tube has an acoustic mass which impedance increases with frequency while the slit resistance remains constant. When the frequency has been increased sufficiently, a considerable part of the acoustic flow passes through the slit where it will be damped. In this way, acoustic energy can be dissipated while the flow experiences a low flow resistance. The acoustic properties of the device will be investigated using an electrical equivalent circuit. The impedance will be measured using an impedance measurement duct, from which the slit resistance will be deduced. The resulting slit resistance consists of a linear part depending on the air viscosity, and a non-linear part which is caused by the loss of kinetic energy of the fluidum through the slit. The presence of a laminar mean flow does not effect the acoustic performance of the annular tailpipe, only some minor effects are observed in the low frequency range. Even with a mean turbulent flow, the acoustic damping mechanism still remains intact.
Sampling Error Damping Method for a Cloud-Resolving Model Using a Dual-Scale Neighboring Ensemble Approach

AbstractIn ensemble-based assimilation schemes for cloud-resolving models (CRMs), the precipitation-related variables have serious sampling errors. The purpose of the present study is to examine the sampling error properties and the forecast error characteristics of the operational CRM of the Japan Meteorological Agency (JMANHM) and to develop a sampling error damping method based on the CRM forecast error characteristics.The CRM forecast error was analyzed for meteorological disturbance cases using 100-member ensemble forecasts of the JMANHM. The ensemble forecast perturbation correlation had a significant noise associated with the precipitation-related variables, because of sampling errors. The precipitation-related variables were likely to suffer this sampling error in most precipitating areas. An examination of the forecast error characteristics revealed that the CRM forecast error satisfied the assumption of the spectral localization, while the spatial localization with constant scales, or variable l.
Detection of Consciously Controlled Motor Cortical Activation by Near Infrared Spectroscopy (NIRS)

Custom headgear was developed and fabricated for the purposes of detecting the hemodynamic response in the motor cortex of the human brain by near infrared spectroscopy (NIRS). We present here, results from this NIRS study. Light in the NIR region was incident upon the human motor cortex in anticipation of observing differences in the absorption curves for recordings of periodic motor activation with respect to periods of rest. Frequency domain NIRS was used to obtain the properties of the NIR signal after the light waves had traversed the brain tissue. Analysis of the intensity of the signal reveals that the absorptive properties of the tissue are altered during periods of activation. T en neurologically healthy individuals each performed both a resting and a motor cortical activation task. We examined the shape of the average time domain curve for each of the two tasks and observe distinct differences; therefore, we anticipate that feature differences between these two curves will consistently discriminate between activation task and baseline responses. In particular, we examined the distribution of the peak-to-peak ranges, inter-peak times, the slopes of the average curves, and the magnitude of the extrema with respect to the mean value. These feature differences may be harnessed to discern a binary signal, thereby demonstrating the hemodynamic signal’s potential as an access pathway enabling individuals with severe motor disability.
A Novel Isotope-labeled Small Molecule Probe CC12 for Anti-glioma via Suppressing LYN-mediated Progression and Activating Apoptosis Pathways

Background: Glioblastoma multiforme (GBM) is the most lethal malignancy in brain, which is surrounded by the blood-brain barrier (BBB), which limits the efficacy of standard treatments. Developing an effective drug that can penetrate the blood-brain barrier (BBB) remains a critical challenge in the fight against GBM. CC12 (NSC749232) is an anthraquinone tetraheterocyclic homolog with a lipophilic structure that may facilitate penetration of the brain area. Methods: We used temozolomide sensitive and resistance GBM cells and animal model to identify the CC12 delivery, anti-tumor potential and its underlying mechanism. Results: Importantly, toxicity triggered by CC12 was not associated with the methyl guanine-DNA methyl transferase (MGMT) methylation status which revealed a greater application potential compared to temozolomide. Alexa F488 cadaverine-labelled CC12 successfully infiltrated into the GBM sphere; in addition, 68Ga-labeled CC12 was also found in the orthotopic GBM area. After passing BBB, CC12 initiated both caspase-dependent intrinsic/extrinsic apoptosis pathways and apoptosis-inducing factor, EndoG-related caspase-independent apoptosis signaling in GBM. RNA sequence analysis from The Cancer Genome Atlas indicated that LYN was overexpressed in GBM is associated with poorer overall survival. We proved that targeting of LYN by CC12 may diminish GBM progression and suppress it downstream factors such as signal transduction and activator of extracellular signal-regulated kinases (ERK)/transcription 3 (STAT3)/nuclear factor (NF)-κB. CC12 was also found to participate in suppressing GBM metastasis and dysregulation of the epithelial-mesenchymal transition (EMT) through inactivation of the LYN axis. Conclusion: CC12, a newly developed BBB-penetrating drug, was found to possess an anti-GBM capacity via initiating an apoptotic mechanism and disrupting LYN/ERK/STAT3/NF-κB-regulated GBM progression.
Hamiltonian bifurcations in Schrodinger trimers

HAMILTONIAN BIFURCATIONS IN SCHRÖDINGER TRIMERS by Casayndra H Basarab The phase space of the three-mode discrete NLS in the nonlinear regime with periodic boundary conditions is investigated by reducing the degree of freedom from three down to two. The families of standing waves are enumerated and normal forms are used to describe several families of relative periodic orbits whose topologies change due to Hamiltonian Hopf bifurcations and transcritical bifurcations. The Hamiltonian Hopf bifurcation occurs when eigenvalues on the imaginary axis collide and split and has two types: elliptic and hyperbolic. These two types arise in the DNLS problem, and the families of periodic orbits are discussed as a conserved quantity N is changed. The stability of each standing wave solution is discussed both numerically and analytically to describe how the dynamics change under perturbation of the parameter N . HAMILTONIAN BIFURCATIONS IN SCHRÖDINGER TRIMERS by Casayndra H Basarab A Dissertation Submitted to the Faculty of New Jersey Institute of Technology and Rutgers, The State University of New Jersey – Newark in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy in Mathematical Sciences Department of Mathematical Sciences Department of Mathematics and Computer Science, Rutgers-Newark
A Comparison of the Checklist Scoring Systems, Global Rating Systems, and Borderline Regression Method for an Objective Structured Clinical Examination for a Small Cohort in a Saudi Medical School

Background: This study aims to compare the effectiveness of using the checklist and global rating scores to evaluate the clinical competency of medical students in Objective Structured Clinical Examinations (OSCEs). Additionally, the study assesses the appropriateness of using the borderline regression method to set standards for small-scale OSCE exams and determines if the estimated passing marks differ significantly from the university's prefixed passing score of 70%. The study also examines whether the university should utilize the borderline regression method to determine passing scores for each OSCE exam instead of a set passing score. Methods: The study analyzed medical students' grades in 11 OSCE exams in the 2022-2023 academic year at Alfaisal University, Riyadh, Saudi Arabia. Students received family medicine clerkship rotations, and after each rotation, they took an OSCE exam consisting of three stations that family medicine consultants graded. The exam included a checklist of 30 tasks and a five-level global rank scale. The study collected all the checklist marks and global rank grades and analyzed them using IBM® Statistical Package for Social Sciences (SPSS® Statistics) software. The statistical tests used were descriptive statistics, the T-test, chi-square tests, Fisher's exact test, and Pearson correlation. Results: The study showed that students were more likely to pass when using the global rating system than the checklist scoring system. Additionally, students had a significantly lower passing rate when using the higher cut-off passing score estimated using the borderline regression method compared to the pre-set passing score of 70% established by the university (with a p-value of 0.00). Conclusion: Each scoring system has advantages and disadvantages, but they complement each other. Combining scoring systems can produce a more comprehensive and precise evaluation of a candidate's performance. The study also emphasizes the importance of carefully selecting and validating cut-off points in OSCE exams to ensure fairness and consistency in assessment.
Influence of Light Intensity and Temperature on Cultivation of Microalgae Desmodesmus Communis in Flasks and Laboratory-Scale Stirred Tank Photobioreactor

Abstract Optimization of the microalgae cultivation process and of the bioprocess in general traditionally starts with cultivation experiments in flasks. Then the scale-up follows, when the process from flasks is transferred into a laboratory-scale bioreactor, in which further experiments are performed before developing the process in a pilot-scale reactor. This research was done in order to scale-up the process from a 0.4 1 shake flask to a 4.0 1 laboratory-scale stirred-tank photobioreactor for the cultivation of Desmodesmus (D.) communis microalgae. First, the effect of variation in temperature (21-29 ºC) and in light intensity (200-600 μmol m-2s-1) was studied in the shake-flask experiments. It was shown that the best results (the maximum biomass concentration of 2.72 g 1-1 with a specific growth rate of 0.65 g g-1d-1) can be achieved at the cultivation temperature and light intensity being 25 °C and 300 μmol m2s-1, respectively. At the same time, D. communis cultivation under the same conditions in stirred-tank photobioreactor resulted in average volumetric productivities of biomass due to the light limitation even when the light intensity was increased during the experiment (the maximum biomass productivity 0.25 g 1-1d-1; the maximum biomass concentration 1.78 g 1-1). Kopsavilkums Mikroaļģu kultivēšanas procesa optimizēšana parasti sākas ar kultivēšanas eksperimentiem kolbās. Tālāk seko procesa pārnese uz laboratorijas mēroga fotobioreaktoru, kurā tiek veikti tālāki eksperimenti, pirms tiek izveidots pilota mēroga reaktors. Šis pētījums tika veikts ar mērķi, pārnest Desmodesmus communis kultivēšanas procesu no 0.4 1 kolbas uz 4.0 1 laboratorijas fotobioreaktoru. Vispirms tika pētīta dažādu temperatūru (21-29 ºC) un gaismas intensitātes (200-600 μmol m-2s-1) ietekme uz aļģu biomasu veicot eksperimentus kolbās. Labākie rezultāti (maksimālā biomasas koncentrācija 2.72 g 1-1; īpatnējais augšanas ātrums 0.65 g g-1d-1) sasniegti, kad kultivācijas temperatūra ir 25 °C un gaismas intensitāte - 300 μmol m2 s-1. Savukārt D. communis kultivācija fotobioreaktorā pie tādiem pašiem apstākļiem deva vidējus biomasas produktivitātes rezultātus gaismas limitēšanas dēļ arī tad, kad gaismas intensitāte tika palielināta eksperimenta laikā (maksimālā biomasas produktivitāte - 0.25 g 1-1d-1; maksimālā biomasas koncentrācija - 1.78 g 1-1).