Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Feature Transformer-Based Learning for Continuous Human Motion Recognition with High Similarity Using mmWave FMCW Radar

Doppler-radar-based continuous human motion recognition recently has attracted extensive attention, which is a favorable choice for privacy and personal security. Existing results of continuous human motion recognition (CHMR) using mmWave FMCW Radar are not considered the continuous human motion with the high similarity problem. In this paper, we proposed a new CHMR algorithm with the consideration of the high similarity (HS) problem, called as CHMR-HS, by using the modified Transformer-based learning model. As far as we know, this is the first result in the literature to investigate the continuous HMR with the high similarity. To obtain the clear FMCW radar images, the background and target signals of the detected human are separated through the background denoising and the target extraction algorithms. To investigate the effects of the spectral-temporal multi-features with different dimensions, Doppler, range, and angle signatures are extracted as the 2D features and range-Doppler-time and range-angle-time signatures are extracted as the 3D features. The 2D/3D features are trained into the adjusted Transformer-encoder model to distinguish the difference of the high-similarity human motions. The conventional Transformer-decoder model is also re-designed to be Transformer-sequential-decoder model such that Transformer-sequential-decoder model can successfully recognize the continuous human motions with the high similarity. The experimental results show that the accuracy of our proposed CHMR-HS scheme are 95.2% and 94.5% if using 3D and 2D features, the simulation results also illustrates that our CHMR-HS scheme has advantages over existing CHMR schemes.
Implementation with Missing Data ∗

We analyze implementation in environments where planners observe societies’ incomplete choice data and are partially informed about how to associate individuals’ preferences with states of the economy, on which desired collective goals depend. We identify necessary conditions and show that they are su ﬃ cient in economic environments. Further, we establish that more information enriches implementation opportunities. To demonstrate practicality, we examine the implementability of an e ﬃ ciency notion suited to this setting.
A Printed Arabic Optical Character Recognition System using Deep Learning

: Recognizing Arabic script is challenging for many reasons: The Arabic language is cursive and morphologically rich. There is a high similarity between Arabic letters. Moreover, Arabic has many diacritics and dots, and they change the letter's phonetic transcription. This study proposes a Printed Arabic Optical Character Recognition approach (PAOCR) based on the state-of-the-art You Only Look Once (YOLO) object detector. Four techniques were proposed and implemented to design an end-to-end Arabic OCR system. First, the YOLO4 object detector is customized and trained on deep Convolutional Neural Networks (CNNs) to recognize Arabic characters. Second, the overlapped bounding boxes are processed to keep the most accurate box for each character. Third, the Hunspell library checks the word spelling and corrects the wrong ones. Fourth, edit distance is used to compare OCR misspelled words with Hunspell's suggestions and choose the closest correct word. The experimental results in the Arabic Printed Text Image (APTI) dataset showed that the Word Recognition Rate (WRR) of customized YOLO4 Arabic OCR is 66.7%, whereas applying the three proposed techniques with YOLO4 achieved 82.4%. A comparison with two existing OCR systems Tesseract and ABBYY showed that the proposed approach achieved a 95.7% Character Recognition Rate (CRR), whereas Tesseract and ABBYY achieved 92.3 and 84.8%, respectively.
Structured inhibitory activity dynamics in new virtual environments

Inhibition plays a powerful role in regulating network excitation and plasticity; however, the activity of defined interneuron types during spatial exploration remain poorly understood. Using two-photon calcium imaging, we recorded hippocampal CA1 somatostatin- and parvalbumin-expressing interneurons as mice performed a goal-directed spatial navigation task in new visual virtual reality (VR) contexts. Activity in both interneuron classes was strongly suppressed but recovered as animals learned to adapt the previously learned task to the new spatial context. Surprisingly, although there was a range of activity suppression across the population, individual somatostatin-expressing interneurons showed consistent levels of activity modulation across exposure to multiple novel environments, suggesting context-independent, stable network roles during spatial exploration. This work reveals population-level temporally dynamic interneuron activity in new environments, within which each interneuron shows stable and consistent activity modulation.
Simulating phase transition phenomena of the unitary cell model

Lattice process models are used to explain phase transitions in statistical mechanics, a branch of physics. The Ising model, a specific form of lattice process model, was proposed by Ising in 1925. Since then, variants of the Ising model such as the Potts model and the unitary cell model have been proposed. Like the Ising model, it is believed that the more general models exhibit phase transitions on the critical surface, which is based on the mathematical equation. In statistical sense, phase transitions can be simulated through Markov Chain Monte Carlo (MCMC). We applied Swendsen-Wang algorithm, a block Gibbs algorithm, to a general lattice process models and we simulate phase transition phenomena of the unitary cell model.
Representation and computation in working memory

The ability to sustain internal representations of the sensory environment beyond immediate perception is a fundamental requirement of cognitive processing. In recent years, debates regarding the capacity and fidelity of the working memory (WM) system have driven significant advances in our understanding of the nature of these representations. In particular, there is growing recognition that WM representations are not merely imperfect copies of a perceived object or event, as new experimental tools have revealed that observers possess richer information about the uncertainty in their memories, and take advantage of environmental regularities to use limited memory resources optimally. Meanwhile, computational models of visual WM formulated at different levels of implementation have converged on common principles relating capacity to variability and uncertainty. Here we review recent research in human visual WM from a computational perspective and the latest developments in identifying neural mechanisms that support it.
Gaussian Multiuser Wiretap Channels in the Presence of a Jammer-Aided Eavesdropper

This paper considers secure communication in the presence of an eavesdropper and a malicious jammer. The jammer is assumed to be oblivious of the communication signals emitted by the legitimate transmitter(s) but can employ any jamming strategy subject to a given power constraint and shares her jamming signal with the eavesdropper. Four such models are considered: (i) the Gaussian point-to-point wiretap channel; (ii) the Gaussian multiple-access wiretap channel; (iii) the Gaussian broadcast wiretap channel; and (iv) the Gaussian symmetric interference wiretap channel. The use of pre-shared randomness between the legitimate users is not allowed in our models. Inner and outer bounds are derived for these four models. For (i), the secrecy capacity is obtained. For (ii) and (iv) under a degraded setup, the optimal secrecy sum-rate is characterized. Finally, for (iii), ranges of model parameter values for which the inner and outer bounds coincide are identified.
Reactive Programming on the Bare Metal: A Formal Model for a Low-Level Reactive Virtual Machine

Reactive programming has many applications for embedded devices in IoT and other application domains. For these constrained devices it is crucial to bound the overhead of the execution of non-functional concerns such as glitch freedom. Reactive programming languages with static dependency graphs can implement glitch freedom by topologically sorting the dependency graph ahead of time. However, for more traditional reactive programming languages that support a dependency graph that can dynamically change, glitch freedom is typically implemented using a priority queue in which signals are enqueued according to their location in the graph. This is undesirable for embedded devices, as dynamically updating this priority queue has an undesirable, and sometimes unbounded, overhead. In this paper, we present a small-step operational semantics of a virtual machine specialised for running reactive programs that combines static ahead-of-time compilation of reactive programs into topologically sorted dependancy graphs while maintaining support for dynamic modifications to those dependency graphs.
Deft Particle Swarm Optimization-Based Routing Protocol (DPSORP) for Energy Consumption Minimization in Mobile Ad-Hoc Network

– Rapid technological development in the wireless communication sector has improved mobile ad hoc networks (MANETs) to serve a variety of domains, such as military activities, emergency operations, civilian settings, and disaster management. Self-organizing mobile nodes in MANET work together to create a dynamic network architecture to make connections. Before reaching its destination node in a MANET, data must pass through several intermediate nodes. For the creation and maintenance of routes, local link connection is crucial. This paper proposes the Deft Particle Swarm Optimization-based Routing Protocol (DPSORP) to reduce delay, which minimizes energy consumption. DPSORP gives precedence for local and global optimal routes. Before using a route for data transmission, DPSORP assesses its quality using two distinct kinds of rules. DPSORP uses a multi-path for data transmission rather than relying on a single path. Using the NS3 simulator and common network performance metrics and parameters, DPSORP is evaluated. The findings demonstrate unequivocally that the proposed routing protocol, DPSORP, outperforms existing routing protocols in terms of reducing delay and energy consumption .
Complete Bell-state analysis for superconducting-quantum-interference-device qubits with a transitionless tracking algorithm

In this paper, we propose a protocol for complete Bell-state analysis for two superconducting-quantum-interference-device qubits. The Bell-state analysis could be completed by using a sequence of microwave pulses designed by the transition- less tracking algorithm, which is an useful method in the technique of shortcut to adiabaticity. After the whole process, the information for distinguishing four Bell states will be encoded on two auxiliary qubits, while the Bell states keep unchanged. One can read out the information by detecting the auxiliary qubits. Thus the Bell-state analysis is nondestructive. The numerical simulations show that the protocol possesses high success probability of distinguishing each Bell state with current experimental technology even when decoherence is taken into account. Thus, the protocol may have potential applications for the information readout in quantum communications and quantum computations in superconducting quantum networks.
Stability Analysis of Disease Free Equilibrium (DFE) State of a Mathematical Model of Yellow Fever Incorporating Secondary Host

In this paper we formulate a mathematical model of yellow fever incorporating secondary host. We obtained the Disease Free Equilibrium (DFE) Points and compute the basic reproduction number. The local and global stability of the DFE was analyzed using Jacobian Matrix stability techniques and Lyapunov function respectively. The local and global stability was asymptotically stable if 1 0  R and 1 0  R , respectively. The basic reproduction number and control parameters of the model were presented graphically.
Lender-Aﬃliated Analysts and Syndicated Loans

We examine whether coverage by analysts aﬃliated with lenders aﬀects loan contracting. We ﬁnd that loans to borrowers covered by aﬃliated analysts have lower spreads but more ﬁnancial covenants. Further analyses suggest that the results are driven mostly by aﬃliated analysts sharing information with, but not demanding information from, the lending side. Exploiting plausibly exogenous variation in aﬃliated analysts generated by changes in brokerage house aﬃliation, we ﬁnd that the result is likely to be causal. The results suggest that analysts could transfer private information to their aﬃliated lenders.
Analisis Permintaan Pakaian Pada Marketplace Shopee di Generasi Milenial

Kemajuan internet saat ini berkembang dengan pesat, orang-orang masa ini tidak terlepas dengan internet. Kemajuan internet menyebabkan dunia perdagangan berkembang, saat ini konsumen banyak berbelanja online dimana mereka tidak harus datang ke toko untuk membeli barang yang diinginkannya, konsumen toko online juga didominasi oleh generasi milenial. Marketplace Shopee berada diurutan pertama ranking download aplikasi di appstore dan playstore. Shopee juga unggul dari segi produk terlaris ditoko online yaitu produk pakaian atau fashion. Permintaan pakaian di Shopee sebesar 59 persen lebih banyak dibandingkan dengan marketplace lainnya. Tujuan penelitian ini yaitu untuk mengetahui pengaruh harga, pendapatan, selera, dan diskon terhadap permintaan pakaian di marketplace Shopee. Metode yang digunakan dalam penelitian ini adalah Ordinary Least Square (OLS) dengan analisis regresi berganda yang dibantu program aplikasi statistik yaitu Eviews 9. Responden penelitian ini merupakan generasi milenial yang lahir tahun 1980 hingga 2000 yang belanja pakaian di marketplace Shopee di kawasan Universitas Nahdlatul Ulama Sumatera Barat. Untuk membatasi dan menentukan jumlah sampel digunakan metode Slovin. Hasil penelitian yaitu variabel harga berpengaruh signifikan dan negatif terhadap permintaan pakaian di marketplace Shopee, variabel pendapatan berpengaruh signifikan dan positif terhadap permintaan pakaian di marketplace Shopee, variabel selera berpengaruh signifikan dan positif terhadap permintaan pakaian di marketplace Shopee, dan variabel diskon berpengaruh signifikan dan positif terhadap permintaan pakaian di marketplace Shopee.
Minor Changes for a Major Impact: A Review of Epigenetic Modifications in Cell-Based Therapies for Stroke

Epigenetic changes in stroke may revolutionize cell-based therapies aimed at reducing ischemic stroke risk and damage. Epigenetic changes are a novel therapeutic target due to their specificity and potential for reversal. Possible targets for epigenetic modification include DNA methylation and demethylation, post-translational histone modification, and the actions of non-coding RNAs such as microRNAs. Many of these epigenetic modifications have been reported to modulate atherosclerosis development and progression, ultimately contributing to stroke pathogenesis. Furthermore, epigenetics may play a major role in inflammatory responses following stroke. Stem cells for stroke have demonstrated safety in clinical trials for stroke and show therapeutic benefit in pre-clinical studies. The efficacy of these cell-based interventions may be amplified with adjunctive epigenetic modifications. This review advances the role of epigenetics in atherosclerosis and inflammation in the context of stroke, followed by a discussion on current stem cell studies modulating epigenetics to ameliorate stroke damage.
Influence Analysis of Lubricant Recesses on the Working Capacity of the Bridge Span Spherical Bearing

The load on transport and logistics systems is increasing every year. This is due to car park growth around the world. Thus, increasing bridge structure durability is an urgent task for bridge-building companies. This study analyses the contact deformation of spherical bearing elements through an anti-friction polymer layer with different geometrical configurations of recesses for the lubricant, i.e., annular grooves and spherical holes. The material of the anti-friction layer (a modified polytetrafluoroethylene (PTFE)) is modelled within the framework of the deformation theory of plasticity. The procedure of automating the numerical model construction depends on the input parameters, including the thickness of the layer, the basic geometrical parameters of the recesses for the lubricant, and the distance between the rows of recesses, etc. The influence of the arrangement of filling sliding anti-friction layers on recesses for lubricants in the form of spherical holes on the contact deformation behaviour of bridge bearings has been considered. The reduction of lubricant volume in the sliding anti-friction layer with the geometry of recesses in the form of spherical holes ranges from 26 to 48.4%, depending on the filling scheme, has been found. In this case, structures with lubrication recesses in the form of spherical holes have several advantages, including a more uniform distribution of contact parameters in the interface areas of the steel plates with the anti-friction layer, reduction of the maximum level of the plastic deformation intensity, displacements along the normal relative to the free end of the sliding layer, and the settlement of the bearing.
Lamp1 Deficiency Enhances Sensitivity to α-Synuclein and Oxidative Stress in Drosophila Models of Parkinson Disease

Parkinson disease (PD) is a common neurodegenerative condition affecting people predominantly at old age that is characterized by a progressive loss of midbrain dopaminergic neurons and by the accumulation of α-synuclein-containing intraneuronal inclusions known as Lewy bodies. Defects in cellular degradation processes such as the autophagy-lysosomal pathway are suspected to be involved in PD progression. The mammalian Lysosomal-associated membrane proteins LAMP1 and LAMP2 are transmembrane glycoproteins localized in lysosomes and late endosomes that are involved in autophagosome/lysosome maturation and function. Here, we show that the lack of Drosophila Lamp1, the homolog of LAMP1 and LAMP2, severely increased fly susceptibility to paraquat, a pro-oxidant compound known as a potential PD inducer in humans. Moreover, the loss of Lamp1 also exacerbated the progressive locomotor defects induced by the expression of PD-associated mutant α-synuclein A30P (α-synA30P) in dopaminergic neurons. Remarkably, the ubiquitous re-expression of Lamp1 in a mutant context fully suppressed all these defects and conferred significant resistance towards both PD factors above that of wild-type flies. Immunostaining analysis showed that the brain levels of α-synA30P were unexpectedly decreased in young adult Lamp1-deficient flies expressing this protein in comparison to non-mutant controls. This suggests that Lamp1 could neutralize α-synuclein toxicity by promoting the formation of non-pathogenic aggregates in neurons. Overall, our findings reveal a novel role for Drosophila Lamp1 in protecting against oxidative stress and α-synuclein neurotoxicity in PD models, thus furthering our understanding of the function of its mammalian homologs.
On $p$-adic analytic families of Galois representations

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Spherically symmetric solutions of gravitation equations on the background with spatial sections of constant curvature

We investigate the vacuum and charged spherically symmetric static solutions of the Einstein equations on cosmological background. The background metric is not ﬂat, but curved, with constant - curvature spatial sections. Both vacuum and charged cases contain two branches. The ﬁrst branches transform into the Schwarzschild and Reissner-Nordstr¨om solutions if the background metric goes to the Minkovski one. The second branches describe wormholes and have no Einstein limit.
Time-Delay Systems: Lyapunov Functionals and Matrices

Preface. - Notations and Symbols. - Part I: Delay Type Systems. - 1 General Theory. 2 Single Delay Case. - 3 Multiple Delay Case. - 4 Systems with Distributed Delay. - Part II: Neutral Type Systems. - 5 General Theory. - 6 Linear Systems. - 7 Distributed Delay Case. - References. - Subject Index.
Druggable Metabolic Vulnerabilities Are Exposed and Masked during Progression to Castration Resistant Prostate Cancer

There is an urgent need for exploring new actionable targets other than androgen receptor to improve outcome from lethal castration-resistant prostate cancer. Tumor metabolism has reemerged as a hallmark of cancer that drives and supports oncogenesis. In this regard, it is important to understand the relationship between distinctive metabolic features, androgen receptor signaling, genetic drivers in prostate cancer, and the tumor microenvironment (symbiotic and competitive metabolic interactions) to identify metabolic vulnerabilities. We explore the links between metabolism and gene regulation, and thus the unique metabolic signatures that define the malignant phenotypes at given stages of prostate tumor progression. We also provide an overview of current metabolism-based pharmacological strategies to be developed or repurposed for metabolism-based therapeutics for castration-resistant prostate cancer.
On solutions of the 2D Navier-Stokes equations with constant energy and enstrophy

It is not yet known if the global attractor of the space periodic 2D Navier-Stokes equations contains nonstationary solutions $u(x,t)$ such that their energy and enstrophy per unit mass are constant for every $t \in (-\infty, \infty)$. The study of the properties of such solutions was initiated in \cite{CMM13}, where, due to the hypothetical existence of such solutions, they were called "ghost solutions". In this work, we introduce and study geometric structures shared by all ghost solutions. This study led us to consider a subclass of ghost solutions for which those geometric structures have a supplementary stability property. In particular, we show that the wave vectors of the active modes of this subclass of ghost solutions must satisfy certain supplementary constraints. We also found a computational way to check for the existence of these ghost solutions.
Finite volume effects in a quenched lattice-QCD quark propagator

We investigate finite volume effects in the pattern of chiral symmetry breaking. To this end we employ a formulation of the Schwinger-Dyson equations on a torus which reproduces results from the corresponding lattice simulations of staggered quarks and from the overlap action. Studying the volume dependence of the quark propagator we find quantitative differences with the infinite volume result at small momenta and small quark masses. We estimate the minimal box length L below which chiral perturbation theory cannot be applied to be L{approx_equal}1.6 fm. In the infinite volume limit we find a chiral condensate of | |{sub MS}{sup 2{sup G}}{sup eV}=(253{+-}5 MeV){sup 3}, an up/down quark mass of m{sub MS}{sup 2{sup G}}{sup eV}=4.1{+-}0.3 MeV and a pion decay constant which is only 10% smaller than the experimental value.