Miracle-dz/UniFAR-FTUs huggingface dataset:
Structure and complexity in non-convex and non-smooth optimization

Structure and complexity in non-convex and non-smooth optimization Courtney Paquette Chair of the Supervisory Committee: Assistant Professor Dmitriy Drusvyatskiy Mathematics Complexity theory drives much of modern optimization, allowing a fair comparison between competing numerical methods. The subject broadly seeks to both develop efficient algorithms and establish limitations on efficiencies of any algorithm for the problem class. Classical complexity theory based on oracle models targets problems that are both smooth and convex. Without smoothness, methods rely on exploiting the structure of the target function to improve on the worst-case complexity of non-smooth convex optimization. This thesis explores complexity of first-order methods for structured non-smooth and non-convex problems. A central example is the minimization of a composition of a convex function with a smooth map – the so-called convex-composite problem class. Nonlinear least squares formulations in engineering and nonlinear model fitting in statistics fall within this framework. The thesis develops new algorithms for the composite problem class, along with inertial variants that are adaptive to convexity. Acceleration is a widely used term in contemporary optimization. The term is often used to describe methods with efficiency guarantees matching the best possible complexity estimates for a given problem class. This thesis develops methods that interpolate between convex and non-convex settings. In particular, we focus on minimizing large finite sum problems, popular for modeling empirical risk in statistical applications, when the user is unaware of the convexity of the objective function. The scheme we describe has convergence guarantees that adapt to the underlying convexity of the objective function. First-order algorithms for non-smooth problems depend on having access to generalized derivatives of the objective function. We conclude the thesis with a fresh look at variational properties of spectral function. These are the functions on the space of symmetric matrices that depend on the matrix only through its eigenvalues. In particular, our analysis dramatically simplifies currently available derivations of differential formulas of such functions.
A home energy management system

In this study, an offline home energy management system that reduces electricity expense and peak demand without deteriorating residents’ contentment is considered. The main goal is to improve the system in the sense of reducing electricity expense, via interfering with appliances by means of interrupting as well as shifting their operation; and keeping up with the benefits of the newest technology, via plug-in hybrid electrical vehicle integration. The proposed offline home energy management system (OF-HEM) consists of smart electrical appliances, power resources (photovoltaic system, grid, backup battery), main controller, communication network and plug-in hybrid electrical vehicle. The main controller manages the power resources, appliances and plug-in hybrid electrical vehicle based on the solution of a mixed integer linear program with defined smart and energy-efficient operation constraints related to the smart appliances and power sources for data collected at the beginning of the day from the power resources and residents’ preferences. Conducted case studies demonstrate that OF-HEM significantly reduces electricity expenses and high peak demand.
The Performance Evaluation of NOMA for 5G Systems Using Automatic Deployment of Multi Users

— Non-Orthogonal Multiple Access (NOMA) in the fifth generation (5G) system is one of the optimistic technologies for wireless radio access networks. Compared to orthogonal multiple accesses (OMA) reduce the spectral efficiency; NOMA provides the best solution by increasing the data rates. This study evaluates NOMA with a downlink in the automatic deployment of multi-users. The outage performance and ergotic sum-rate gain give the NOMA better performance can be concluded at the final results. NOMA provides the Quality of Service (QoS) to the multi-users by considering the power allocation and data rate factors. Here is considered the outage probability will be 1 when it identifies the different user and allocates the data rate and power.
Global and local structures of oscillatory bifurcation curves with application to inverse bifurcation problem

We consider the bifurcation problem $$ -u''(t) = \lambda (u(t) + g(u(t))), \quad u(t) > 0, \quad t \in I := (-1,1), \quad u(\pm 1) = 0, $$% where $g(u) = g_1(u) := \sin \sqrt{u}$ and $g_2(u) := \sin u^2 (= \sin (u^2))$, and $\lambda > 0$ is a bifurcation parameter. It is known that $\lambda$ is parameterized by the maximum norm $\alpha = \Vert u_\lambda\Vert_\infty$ of the solution $u_\lambda$ associated with $\lambda$ and is written as $\lambda = \lambda(g,\alpha)$. When $g(u) = g_1(u)$, this problem has been proposed in Cheng [4] as an example which has arbitrary many solutions near $\lambda = \pi^2/4$. We show that the bifurcation diagram of $\lambda(g_1,\alpha)$ intersects the line $\lambda = \pi^2/4$ infinitely many times by establishing the precise asymptotic formula for $\lambda(g_1,\alpha)$ as $\alpha \to \infty$. We also establish the precise asymptotic formulas for $\lambda(g_i,\alpha)$ ($i = 1,2$) as $\alpha \to \infty$ and $\alpha \to 0$. We apply these results to the new concept of inverse bifurcation problems.
Least energy solutions for nonlinear Schrödinger equation involving the fractional Laplacian and critical growth

In this paper, we study a class of nonlinear Schrodinger equations involving the fractional Laplacian and the nonlinearity term with critical Sobolev exponent. We assume that the potential of the equations includes a parameter $λ$. Moreover, the potential behaves like a potential well when the parameter λ is large. Using variational methods, combining Nehari methods, we prove that the equation has a least energy solution which, as the parameter λ large, localizes near the bottom of the potential well. Moreover, if the zero set int \begin{document} $V^{-1}(0)$ \end{document} of \begin{document} $V(x)$ \end{document} includes more than one isolated component, then \begin{document} $u_\lambda (x)$ \end{document} will be trapped around all the isolated components. However, in Laplacian case when \begin{document} $s=1$ \end{document} , for \begin{document} $\lambda$ \end{document} large, the corresponding least energy solution will be trapped around only one isolated component and will become arbitrary small in other components of int \begin{document} $V^{-1}(0)$ \end{document} . This is the essential difference with the Laplacian problems since the operator \begin{document} $(-Δ)^{s}$ \end{document} is nonlocal.
Autoregressive Decoder With Extracted Gap Sessions for Sequential/Session-Based Recommendation

Learning the complex relationships between items in a sequential recommendation system (SRS) and session-based recommendation system (SBRS) is critical for obtaining higher prediction scores. In recent studies, to capture item-item information, items have been represented as the nodes of graph neural networks (GNNs) and the relevance of items with self-/soft attention layers has been calculated. GNNs have been used because standalone attention-based methods focus only on the relative significance of items within a single session, neglecting high-order item-item relationships that change through sessions. The relational summarization task is a natural language processing task that extracts the relationship between two tokens from a related corpus; however, its adaptation to SRS and SBRS is unknown. To fill this lacuna, in this study, the relationships between items from related sessions are extracted using the transformer-based abstractive summarization model PEGASUS. To improve session embedding, the proposed model, named “gap-session transformer” utilizes gap-session masking to learn the relationships between items within different sessions. In addition, a group of sessions are divided into multiple corpus sets based on the theme of each corpus, and the autoregressive beam-search decoder is connected to a transformer decoder for the generation of the next session while auxiliary tasks are performed to enhance the recommendation task. Extensive experiments conducted on the MovieLens1M dataset and Yoochoose dataset verify that our model significantly outperforms the state-of-the-art (SOTA) methods, and the results demonstrate the efficacy of the relational summarization task in recommendation systems.
Agile and Dynamic Standing-Up Control for Humanoids Using 3D Divergent Component of Motion in Multi-Contact Scenario

Standing-up is a task that humanoids need to be able to perform in order to be employed in real-world scenarios. This letter proposes a new robust strategy for a humanoid to stand up in challenging scenarios where no completely preplanned motion can accomplish the same task. This strategy exploits the concept of three-dimensional divergent component of motion and passivity-based whole-body control. The latter firstly maximizes the push forces applied to the robot's center of mass to make agile whole-body recovery motion. Then, during the rising phase, it reduces these forces to zero and stabilizes the robot in an upward position. Optimization of centroidal angular momentum is fully integrated into the proposed whole-body standing-up control to create the trajectories of the hip and the upper body joints online. The effectiveness of the proposed method is validated in simulations and experiments on the humanoid TORO.
The Effect of Customer Trust on Repurchase Intention Through User-Generated Content as an Intervening Variable in The Automotive Industry Case Study @Bandarmotor_

Social media is used for brand awareness. Instagram ranks third as a media that is often used in Indonesia. Bandarmotor is a shop that provides spare parts and two-wheeled vehicle service services located in South Banyuwangi. If there is no increase in followers and decrease in turnover, research is carried out to find out whether it is true that customer trust will increase motivation to create user-generated content and the desire to repurchase Bandarmotor. The study population of Instagram followers of @bandarmotor_ account amounted to 1533 people. The study sample using the purposive sampling method was 73 people. Questionnaires using Google forms. The analysis method uses Partial Least Squares-Structural Equation Modeling (PLS-SEM) with SmartPLS software. The results showed that Customer trust had a significant positive effect on user-generated content. Customer trust has a significant positive effect on repurchase intention. User-generated has a significant positive effect on repurchase intention. User-generated content has a significant positive effect on customer trust and repurchase intention.
A Fast Electrothermal Response Analysis Method for Interconnect Circuits With Multiexcitations in Multilayer Packages

The design of package interconnects is increasingly vital as integrated circuits (ICs) continue to shrink in size and increase in density. However, reducing interconnect size may lead to various issues such as increased temperature, resistivity, and decreased reliability. Accurate estimation of the electrothermal response of interconnect structures is crucial in guiding circuit design. In this article, an efficient method for transient thermal analysis has been proposed for interconnect circuits with complex stacking structures and multiexcitations. This method utilizes the tensorial analysis network (TAN) in combination with the Cauer I RC network (i.e., RC-TAN) to analyze the electrothermal sensitivity of package interconnects. Then, the main parameters affecting the electrothermal response and the optimal interconnect layer stacking order can be derived to guide the design of package interconnects. The effectiveness of this method has been verified by comparing the results with those obtained through finite element method (FEM) simulation. It indicates that the proposed method can save up to 99.8% of the computation time compared to FEM. Furthermore, the maximum temperature error is only 1.7% and the steady-state error is below 1%, highlighting the method’s high accuracy.
Energy-preserving affine connections

A Riemannian affine connection on a Riemannian manifold has the property that is preserves the “kinetic energy” associated with the metric. However, there are other affine connections which have this property, and here we characterise them. A class of such energy-preserving affine connections, related to mechanical systems with constraints, is provided.
Production and Purification of Cell Culture–generated Hepatitis B Virus by Transient Transfection and Density Gradient

An efficient cell culture system for hepatitis B virus (HBV) is indispensable for research on viral characteristics and antiviral agents. Currently, for HBV infection assays in cell culture, HBV genome-integrated cell line–derived viruses are commonly used. However, these viruses are not suitable for the evaluation of polymorphism-dependent viral characteristics or resistant mutations against anti-viral agents. To detect the infection of cell culture–generated HBV (HBVcc) by the transient transfection of the HBV molecular clone, a large amount of purified viruses is needed, because such viruses exhibit limited infection efficiencies in cell culture. Here, we describe how to generate and purify HBVcc by the transient transfection of HBV molecular clones. This system provides a powerful tool for studying the infection and propagation of HBV and for developing anti-viral agents against HBV.
Game-Theoretic Vaccination Against Networked SIS Epidemics and Impacts of Human Decision-Making

In this paper, we study decentralized protection strategies against susceptible-infected-susceptible epidemics on networks. We consider a population game framework where nodes choose whether or not to vaccinate themselves, and the epidemic risk is defined as the infection probability at the endemic state of the epidemic under a degree-based mean-field approximation. Motivated by studies in behavioral economics showing that humans perceive probabilities and risks in a nonlinear fashion, we specifically examine the impacts of such misperceptions on the Nash equilibrium protection strategies. We first establish the existence and uniqueness of a threshold equilibrium where nodes with degrees larger than a certain threshold vaccinate. When the vaccination cost is sufficiently high, we show that behavioral biases cause fewer players to vaccinate, and vice versa. We quantify this effect for a class of networks with power-law degree distributions by proving tight bounds on the ratio of equilibrium thresholds under behavioral and true perceptions of probabilities. We further characterize the socially optimal vaccination policy and investigate the inefficiency of Nash equilibrium.
Anticyclonic selection by instability of parallel flows in a frontal regime

Large-scale flows are known to present a predominance of anti cyclonic vortices. A previous study (Perret et al. (2006)) showed a strong cyclone-anticyclone asymmetry in l arge-scale wakes, anticyclones are circular whereas cyclones are deformed. To determine the mechanisms respons ible for the asymmetry, we perform a stability analysis of parallel wake flows associated with experimental vel ocity profiles. It is shown that the most unstable mode, in a frontal regime, is localized in the anticyclonic shear l eading to a strong cyclone-anticyclone asymmetry in the nonlinear evolution of the perturbation. Moreover, the wak e instability changes from the absolute instability in the quasigeostrophic regime to the strongly convective ins tability of the frontal regime. To determine whether the stability property of a parallel flow in a frontal regime coul d be a mechanism of anticyclones selection, we extend this stability analysis to parallel jets and shears. The ant icyclonic shear, in a frontal regime, is much more unstable than the cyclonic one, but the nonlinear evolution of the flow leads, in both cases, to circular vortices.
Notes from the Anatolian underground: two new mole taxa from Eastern Turkey, together with a revised phylogeny of the genus Talpa (Mammalia: Eulipotyphla: Talpidae)

Subterranean life is associated with strong adaptive constraints, leading to the frequent occurrence of morphologically cryptic lineages. This is true of most small mammals, including moles (Eulipotyphla: Talpidae), where a number of species have been recognized recently, particularly following the application of molecular genetics. Here, we use mitochondrial and nuclear DNA sequence data and geometric morphometrics to explore the systematics and evolution of some of the least-known Western Palaearctic moles: the Talpa davidiana group of Eastern Anatolia/Iran. We show that T. davidiana includes four taxa, two of which we describe herein: T. hakkariensis sp. nov., T. davidiana davidiana, T. davidiana tatvanensis ssp. nov., and T. streetorum valid species. For the first time, we apply molecular species delimitation analyses to Talpa, confirming taxonomic hypotheses and suggesting the existence of further morphologically cryptic lineages. These analyses also support the recognition of T. transcaucasica as a valid species distinct from T. levantis. We present a revised phylogeny for Eurasian Talpa and increase the number of known extant taxa to 18, most of which are found in Anatolia, the global hotspot of diversity in this genus. This probably results from the isolation of suitable habitats by a combination of climatic and topographical heterogeneity.
Integrated analysis of plasma proteome and cortex single-cell transcriptome reveals the novel biomarkers during cortical aging

Background With the increase of age, multiple physiological functions of people begin gradually degenerating. Regardless of natural aging or pathological aging, the decline in cognitive function is one of the most obvious features in the process of brain aging. Brain aging is a key factor for several neuropsychiatric disorders and for most neurodegenerative diseases characterized by onset typically occurring late in life and with worsening of symptoms over time. Therefore, the early prevention and intervention of aging progression are particularly important. Since there is no unified conclusion about the plasma diagnostic biomarkers of brain aging, this paper innovatively employed the combined multi-omics analysis to delineate the plasma markers of brain aging. Methods In order to search for specific aging markers in plasma during cerebral cortex aging, we used multi-omics analysis to screen out differential genes/proteins by integrating two prefrontal cortex (PFC) single-nucleus transcriptome sequencing (snRNA-seq) datasets and one plasma proteome sequencing datasets. Then plasma samples were collected from 20 young people and 20 elder people to verify the selected differential genes/proteins with ELISA assay. Results We first integrated snRNA-seq data of the post-mortem human PFC and generated profiles of 65,064 nuclei from 14 subjects across adult (44–58 years), early-aging (69–79 years), and late-aging (85–94 years) stages. Seven major cell types were classified based on established markers, including oligodendrocyte, excitatory neurons, oligodendrocyte progenitor cells, astrocytes, microglia, inhibitory neurons, and endotheliocytes. A total of 93 cell-specific genes were identified to be significantly associated with age. Afterward, plasma proteomics data from 2,925 plasma proteins across 4,263 young adults to nonagenarians (18–95 years old) were combined with the outcomes from snRNA-seq data to obtain 12 differential genes/proteins (GPC5, CA10, DGKB, ST6GALNAC5, DSCAM, IL1RAPL2, TMEM132C, VCAN, APOE, PYH1R, CNTN2, SPOCK3). Finally, we verified the 12 differential genes by ELISA and found that the expression trends of five biomarkers (DSCAM, CNTN2, IL1RAPL2, CA10, GPC5) were correlated with brain aging. Conclusion Five differentially expressed proteins (DSCAM, CNTN2, IL1RAPL2, CA10, GPC5) can be considered as one of the screening indicators of brain aging, and provide a scientific basis for clinical diagnosis and intervention.
Sport-specific balance tests account for youth alpine skiers’ ranking

Objective: Alpine skiing requires complex motor skills and fine adjustments to maintain balance in dynamic and challenging conditions. This study aimed to understand whether the balance ability in unspecific (UST) and sport-specific (SST) tasks could depend on the skiers’ ranking level. The balance performance of the dominant and non-dominant limbs in the SST was also investigated. Methods: Twenty-five skiers (14.96 ± 1.61 yrs; 1.69 ± 0.69 m; 59.9 ± 9.52 kg) were divided into high-ranking (position < 50) and low-ranking (position > 50) groups. Subjects performed three balance conditions: static (ST), dynamic UST, and dynamic SST. Subjects stood on an unstable board over a force platform during UST. During SST, subjects wore ski boots, grasped ski poles, and each foot was clipped to an unstable board over two force plates. From the center-of-pressure (CoP) trajectory the area of the 95th percentile ellipse and the CoP mean velocity were calculated. Angular displacements were recorded by a 12-camera system, to calculate the full balance (FB), fine (FiB), and gross (GB) balance in UST and SST. Results: Balance control was higher (p < 0.01) in high-ranking than low-ranking skiers only in the SST. Kinematic parameters (i.e., FB, FiB, and GB) showed a higher (p < 0.001) balance performance in SST than UST independently from the group. Dominant and non-dominant limbs motion was similar (Pearson correlation, r = 0.97) in SST independently from the skiers’ ranking. Conclusion: High-ranking skiers showed better balance control and performance than low-ranking skiers only when the task was sport-specific. Therefore, we suggest testing balance under sport-specific conditions to discriminate the youth skiers’ abilities.
Influence of the Bowtie Shaped Dimples on the Performance of Sliding Surfaces under Hydrodynamic Lubrication

It covers the tribological behaviour of sliding surfaces, one of which has bowtie-shaped micro-dimples. Against the other fixed, textured wall, one wall is smooth and moving at a constant speed. For the formation of hydrodynamic pressure and tribological behaviour, the effects of bowtie-shaped dimples and orientated bowtie-shaped dimples have been compared with circular-shaped dimples. Additionally, the impact of sliding speed, dimple area density, and dimple depth on tribological behaviour was examined. The findings show that compared to a circular-shaped dimple, an atypical bowtie-shaped and orientated bowtie-shaped dimple generates a higher net hydrodynamic pressure in the fluid domain and offers improved stability between the sliding surfaces. It has been demonstrated that geometrical factors like dimple depth and area density as well as operational factors like sliding speed have a substantial impact on the hydrodynamic average pressure and tribological behaviour of sliding surfaces. The experimental results support the conclusions from the analysis and CFD.