Miracle-dz/UniFAR-FTUs huggingface dataset:
Renormalization of fluctuations for a generalized Harper equation for periodic continued fractions

A renormalization analysis is presented for a generalized Harper equation For values of the parameter ω having periodic continued fraction expansion, we construct the periodic orbits of the renormalization strange sets in function space that govern the fluctuations of the solutions of the generalized Harper equation in the strong-coupling limit λ → ∞. In so doing, we give a detailed analysis of the structure of the sets and the renormalization dynamics, including an analysis of the symmetry structure of the renormalization strange sets in terms of D3, the dihedral group of order 6.
Far-infrared measurements of the phonon density of states of superconducting lead

Far-infrared measurements of the derivative of the reflectivity of lead and lead alloys in the superconducting state are presented. The derivative of the reflectivity contains detailed information about the phonon spectrum including peaks not observed by tunneling spectroscopy. The peaks are, in general, in good agreement with neutron measurements and include evidence of phonon lifetime effects at a phonon frequency of $2\ensuremath{\Delta}$
SecLoRa: A Secure LoRa Based Communication System for Residential Smart-grids

With technological advancements in urban and suburban areas, the need for a smart management system for electricity consumption increases. A smart-grid system offers a solution to manage the shift to more sustainable technologies such as microgrids. A smart-grid connects the electrical grids with a communication system that enables a two-way flow of information, building a widely distributed intelligent and automated energy delivery system. One of the key functions of smart-grid, and smart metering to enable the substation automation system (SAS) to get meter readings remotely and on time. In such systems, secure communication and data privacy questions have been prudent issues since large-scale communication networks will connect numerous geographically distributed devices. Thus, a robust, low-power, and secure communication system become necessary. In this paper, we evaluate the applicability of LoRa technology for building a communication system in a smart grid. We implement and test a LoRa-based peer-to-peer, encrypted, and long-range communication system to enable two-way communication and present numerical estimations for a mesh network that extends the communication range through multi-hop communication. The experimental results reflect the suitability of the proposed system for implementing a secure residential smart-grid.
Arithmetische Theorie der Korrespondenzen algebraischer Funktionenkörper. I.*)

Einleitung. 1. In einer Reihe von Arbeiten über abstrakte elliptische Funktionenkörper) hat H. Hasse gezeigt, daß die algebraischen Eigenschaften eines algebraischen Funktionenkörpers vom Geschlecht l, die sich aus seiner Darstellung als Körper von doppeltperiodischen Funktionen einer komplexen Variablen ergeben, nicht auf diesen klassischen Fall beschränkt sind, sondern auch bei abstrakten Funktionenkörpern vom Geschlecht l über irgendeinem algebraisch abgeschlossenen Konstantenkörper zu finden sind. Es ist wünschenswert, die entsprechenden algebraischen Eigenschaften der Körper höheren Geschlechts aufzufinden. Es ist bekannt, daß die komplexen Multiplikationen in sich der Periodenmatrix der Integrale erster Gattung eines algebraischen Funktionenkörpers einer komplexen Variablen mit den Korrespondenzen einer zu diesem Körper gehörigen irreduziblen algebraischen Kurve zusammenhängen. Wir kommen auf diesen Zusammenhang am Schluß der Arbeit ausführlich zu sprechen. Die angestrebte Verallgemeinerung der Hasseschen Resultate muß hiernach in der algebraischen Theorie dieser Korrespondenzen zu suchen sein. Für diese Theorie sei auf F. Severi, Trattato di geometria algebrica, vol. I, parte I, Bologna 1927, insbesondere Gap. 6 verwiesen. Die hier entwickelte Theorie ist davon unabhängig entstanden. Erst nachträglich wurde ihre Übereinstimmung mit der dort entwickelten Theorie erkannt. Es erscheint mir aber dennoch gerechtfertigt, meine neuen Beweise, die der arithmetischen Auffassung der algebraischen Funktionen entsprungen sind, hier zu veröffentlichen, weil sie, wie ich glaube, der Natur der in Rede stehenden Probleme besonders angepaßt sind. 2. Wir erklären eine Korrespondenz eines algebraischen Funktionenkörpers K der Unbestimmten zu einem algebraischen Funktionenkörper K der Unbestimmten über dem gleichen algebraisch abgeschlossenen Konstantenkörper k auf die folgende
Speaker Recognition using Multiple X-Vector Speaker Representations with Two-Stage Clustering and Outlier Detection Refinement*

This paper presents a novel Variational Bayes x-vector Voice Print Extraction (VBxVPE) system, capable of capturing vocal variations using multiple x-vector representations with two-stage clustering and outlier detection for robust speaker recognition and verification. The presented approach demonstrates beyond the state-of-the-art results when evaluated against the ‘core-core’ and ‘core-multi’ evaluation conditions of the Speakers In the Wild dataset, achieving an Equal Error Rate of 1.06%, Cost of Detection score of 0.052, minimum Cost of Detection score of 0.010, Speaker Identification Accuracy of 95.84% with Precision, Recall and F1 score values of 0.964, 0.958 and 0.961, respectively on the ‘core-core’ evaluation condition and Equal Error Rate of 1.07%, Cost of Detection score of 0.066, minimum Cost of Detection score of 0.010 with Precision, Recall and F1 score values of 0.967, 0.963 and 0.965, respectively on the ‘core-multi’ evaluation condition.
An Electron‐Microscope Study of Shock‐Synthesized Diamond

The microstructure of diamonds formed from the graphite in cast iron by an explosive shock process was investigated by means of transmission electron microscopy electron, diffraction, and selected beam microscopy. Morphologically, the material consists of a mixture of two different forms: compact aggregates of of usually acicular crystallites with a strong preferred orientation, and single crystals. The latter partly consist of hexagonal diamond, the recently discovered modification of carbon, and contain many stacking faults. Hexagonal diamond is also randomly distributed in the polycrystalline fraction.
InGaAs/InP single photon avalanche diodes for quantum communication and sensing

We present a planar InGaAs/InP single photon avalanche diode with an active diameter of 25 μm. The photon detection efficiency for 4 V excess bias is 23% with 1.2 Mcps dark count rate at room temperature or 257 kcps at 275 K and 18% with 10 kcps at 225 K
The Impact of Live Streaming Shopping on Customers' Purchase Intention in Social Commerce and E-commerce

The development of the Internet that moves quickly makes the trend of online shopping in e-commerce and social commerce emerge. Currently, both e-commerce and social commerce come with a live streaming shopping feature that allows interaction between sellers and buyers even from a distance. However, the effectiveness of this strategy needs further validation. This study aims to find out the impact of live streaming shopping on customers' purchase intentions. The study was conducted using causal research and SmartPLS as a tool for data analysis. Data for this study was obtained by distributing questionnaires via Google Form with 300 respondents from all over Indonesia. This study reveals that immersion has an influence on purchase intention through customer trust (indicated by p-values of less than 0.05), while social presence and telepresence have no influence on purchase intention (indicated by p-values of greater than 0.05). It is hoped that this study could contribute to the advancement of social commerce and e-commerce research and practice, where it is advised that sellers across platforms make the best of live streaming shopping to increase their sales performance.
A Climate Adaptation Device-Free Sensing Approach for Target Recognition in Foliage Environments

Accurate and efficient foliage penetration (FOPEN) target recognition plays a vital role in many mission-critical applications, ranging from civilian to surveillance and military. Recently, device-free sensing (DFS), as an emerging technique, has gained great popularity because it requires no dedicated equipment other than wireless transceivers. Although some DFS-based approaches have been successfully applied in foliage environments, they are vulnerable to climate dynamics and heavily rely on relabeling large amounts of new data when the weather is altered. To address this issue, a convolutional neural network (CNN)-based weather adaptive target recognition network (WATRNet) is proposed in this article. Specifically, a lightweight weather conditional normalization (WCN) module is embedded atop each convolutional block to encode inputs under different weather conditions into a shared latent feature space. Under an end-to-end learning manner, the proposed WATRNet first learns knowledge from sufficient labeled data under a certain weather condition to achieve a precise classifier. When applying this model under another weather condition, only the WCN module needs to be retrained using limited new labeled samples to learn weather-invariant features, while the rest convolutional parameters in WATRNet are frozen. Consequently, the domain discrepancy caused by climate variations can be adaptively mitigated with as few relabeled data as possible. Comprehensive evaluations are carried out on a real FOPEN dataset collected under four different weather conditions. Experimental results verify that the presented method can achieve over 90% accuracy, even when it implements from a normal weather condition to another severe weather condition with only small amounts of training samples.
Damage detection using thermal experiments and wavelet transformation

Damage detection using the discrete wavelet transformation (DWT) of temperature field recorded on the surface of a plate structure is discussed. Defects in the form of voids and inclusions of various magnitude are considered. Computer-simulated experiments including the ones accounting for white noise and real thermal experiments are applied. Transient heat transfer problems are analysed. The efficiency of DWT in damage detection is studied by way of a number of examples. Haar, Daubechies 4, 6 and 8 wavelets in 1D and 2D DWT are used. The usefulness of the Lipschitz exponent evaluated with the use of DWT is discussed. The issue of denoising the thermal response signals using the soft threshold shrinkage procedure is also taken up.
AlGaInAs/InP EML with Sidewall Grating Distributed Feedback Laser and Quantum Well Intermixing Technology

An electro-absorption modulated laser comprising a sidewall grating DFB laser and quantum well intermixed electroabsorption modulator with 10 nm blueshift is modelled. An extinction ratio of 40 dB and −3-dB bandwidth of 17 GHz are derived at −2.5 V and −1.6 V EAM bias, respectively.
Development of a hybrid vehicle identification system based on video recognition and RFID

The article presents an architecture and experimental implementation of a hybrid vehicle identification system that uses data from a photo-video automatic license plate recognition and an RFID reader. Such a system will significantly increase the likelihood of identifying vehicles that violate traffic rules. In particular, this hybrid system will be capable of recognizing vehicles when license plates are covered with dirt or deliberately hidden. The article presents the system architecture, describes its main components, algorithms for their interaction, and an algorithm for matching data received from the optical recognition system and identifiers received from the RFID reader. We describe an experimental implementation of a hybrid system based on the “Cordon” photo and video recording complex, an experimental RFID reader “P1210” and license plates with tags produced by JSC “Mikron”. In particular, experiments show proper work of the matching algorithm and successful license plate recognition when some characters were changed.
A Power-Efficient 1–2-MHz Hysteretic Buck Converter With High DVS Rate Enabled by Isosceles-Triangular Shunt Current Push–Pull Technique

This letter presents a dc–dc buck converter featuring rapid dynamic voltage scaling (DVS) speed without sacrificing efficiency. The proposed isosceles-triangular shunt current (ITSC) push–pull technique allows an arithmetically-simplified turning point voltage for optimal DVS to be independent of passive components while supplying a sufficient current of 35 A/<inline-formula> <tex-math notation="LaTeX">$\mu \text{s}$ </tex-math></inline-formula>. Current-tailing handover (CTH), also presented in this letter, can realize no voltage droop after DVS even under resistive loads. Combining ITSC and CTH aids in enhancing load-transient response. The chip fabricated in a 180-nm CMOS operates at the slow switching frequency of 1–2 MHz, offering a peak efficiency of 97.6%. A high DVS rate of 7 V/<inline-formula> <tex-math notation="LaTeX">$\mu \text{s}$ </tex-math></inline-formula>, enabled by the proposed ITSC, is measured.
Invariant metrics, contractions and nonlinear matrix equations

In this paper we consider the semigroup generated by the self-maps on the open convex cone of positive definite matrices of translations, congruence transformations and matrix inversion that includes symplectic Hamiltonians and show that every member of the semigroup contracts any invariant metric distance inherited from a symmetric gauge function. This extends the results of Bougerol for the Riemannian metric and of Liverani–Wojtkowski for the Thompson part metric. A uniform upper bound of the Lipschitz contraction constant for a member of the semigroup is given in terms of the minimum eigenvalues of its determining matrices. We apply this result to a variety of nonlinear equations including Stein and Riccati equations for uniqueness and existence of positive definite solutions and find a new convergence analysis of iterative algorithms for the positive definite solution depending only on the least contraction coefficient for the invariant metric from the spectral norm.
Factors Influencing Behavioral Intentions to Use Sharia Mobile Banking: Extended Theory of Planned Behavior

This study applied the extended Theory of Planned Behavior (TPB). This study examined the influence of subjective norms, perceived behavioral control, attitude, Islamic financial literacy, and religiosity on the intention to use Sharia mobile banking. In this quantitative study, residents of Jakarta and the surrounding area (JABODETABEK) were chosen using purposive sampling. The questionnaire passed its validity and reliability. Using path analysis, data were analyzed. This work employs the Structural Equation Modeling with Partial Least Squares (SEM-PLS) technique. This result showed that the intention to use Sharia mobile banking is influenced by subjective norms, perceived behavioral control, attitude, Islamic financial literacy, and religiosity. Meanwhile, the effect of religiosity on intention to use mobile banking services from sharia banks is the largest compared to the influence of other variables.
2022 WUOF/SIU International Consultation on Urological Diseases: Imaging of Renal Cell Carcinoma

Imaging plays a central role in the contemporary multidisciplinary management of renal cell carcinoma. This article provides an overview of the current imaging modalities, including ultrasound, computed tomography, multiparametric magnetic resonance imaging, and molecular imaging, used in the evaluation of renal cell carcinoma. A summary of the imaging strategies for renal cell carcinoma staging and restaging post-treatment is provided.
Impact of the Mobile Game FightHPV on Cervical Cancer Screening Attendance: Retrospective Cohort Study

Background The wide availability of mobile phones has made it easy to disseminate health-related information and make it accessible. With gamification, mobile apps can nudge people to make informed health choices, including attending cervical cancer screening. Objective This matched retrospective cohort study examined the association between exposure to the FightHPV mobile app gamified educational content and having a cervical exam in the following year. Methods Women aged 20 to 69 years who signed an electronic consent form after downloading the FightHPV app in 2017 (intervention group) were matched 1:6 with women of the same age and with the same screening history (reference group) in 2015. To estimate the impact of exposure to the FightHPV app, we estimated cumulative incidence and hazard ratios (HRs) with 95% CIs. We used data from the Norwegian Cervical Cancer Screening Program database and Statistics Norway to determine screening participation and outcomes, respectively. Results We matched 3860 women in the control group to 658 women in the intervention group; 6 months after enrollment, 29.6% (195/658) of the women in the intervention group and 15.21% (587/3860) of those in the reference group underwent a cervical exam (P<.01). Women exposed to the FightHPV app were 2 times more likely to attend screening (adjusted HR 2.3, 95% CI 2.0-2.7), during which they were 13 times more likely to be diagnosed with high-grade abnormality (adjusted HR 12.7, 95% CI 5.0-32.5) than the women in the reference group. Conclusions Exposure to the FightHPV app significantly increased cervical cancer screening attendance across the various analyses and improved detection of women with high risk for cervical cancer. For the first time, we demonstrated the effectiveness of gamification combined with mobile technology in cancer prevention by empowering women to make active health-related decisions. Gamification can significantly improve the understanding of complicated scientific concepts behind interventions and increase the acceptance of proposed cancer control measures.
Prediction of Churning behavior in Telecom using Machine Learning

For any industry to flourish, the key role is played by their customers. Growth of industry is directly proportional to customer-database. It is always said and believed throughout that the process of retention of customers is easier than finding new customers especially in the case of the Telecom industry. Thus, the process of detecting or predicting those customers who might leave the organization in the near future is called churn behavior prediction of customers and this process is most important in today’s technological world. To get this most wanted information, we have incorporated a model that detects customer churn behavior. This model is constructed by the help of two supervised machine learning models, Random Forest and Artificial Neural Network. The pre-stored data is preprocessed using one hot encoding technique, normalization techniques and analyzed using k-means clustering. This data is applied on Random Forest in order to obtain important features. Top twelve important features are retained and thus refined dataset is fed into ANN model to obtain 83.8% accuracy. These important features have a feature importance score that tells where the organization is going wrong in retaining its customers.
A point source of heat in a stable salinity gradient

When a salinity gradient is heated at a single point, a hot plume is formed with a series of layers around and above it in a ‘Christmas-tree’ flow pattern. Qualitative visual observations of the development of this system are reported. Three kinds of layers are observed: the first kind is formed above the basic plume from a hierarchy of secondary plumes on top of the basic one, the second develops around the upper part of the basic plume, and is driven by the same mechanism as the layers in sidewall-heating experiments, and the third, forming around the lower part of the basic plume, is of the same nature as the second type but also has something in common with double-diffusive intrusions. A characteristic feature for all the three kinds of layers is the existence of systematic shearing motions and vortices. Quantitative estimates for the plume height and the thickness of the layers are obtained.
Sensor and Feature Selection for Lightweight Emotion Recognition on Resource-Constrained Smartwatches

Emotion recognition (ER) systems are generally based on cumbersome sensors specifically suited for laboratory settings, which limits their portability. To mitigate this shortcoming, efforts are being made to achieve lightweight ER systems to make them available on person’s daily-life devices. Such devices are required to have the capabilities to collect measurements and to handle machine learning (ML) methodologies. In this regard, smartwatches represent a viable solution for gathering such measurements in a simpler and unobtrusive manner. However, smartwatches, and specifically low-cost ones, are generally equipped with few sensors and, due to their limited computational and memory resources, they can only execute lightweight ML models (e.g., described by a low number of features). In this work, we aim at designing a lightweight ML-based ER systems for resource-constrained devices such as smartwatches. We consider an ER problem of detecting person’s happiness or sadness state. We model the problem as a binary classification problem and train lightweight ML models such as, e.g., Random Forest and Extreme Gradient Boosting, to tackle it. Considering public data sets, we investigate the impact of sensor selection and feature selection on classification accuracy and computational and memory requirements. Experimental results show that sub-sets of sensors can be enough to guarantee same performance as when considering all sensors. Similarly, results show that feature selection can significantly reduce number of features to be used by ER systems while maintaining performance levels. In terms of memory requirements, selecting subset of sensors and features permits up to 46% reduction.
Real-World Experiences Adopting Workflows at Exascale on the ExaAM Project

The purpose of this study is to discuss the experiential lessons associated with adopting scientific workflows in the Exascale Additive Manufacturing project (ExaAM) through the lens of Perceived Characteristic of Innovation (PCI). Besides the implementation, the factors we considered critical to the adoption of the workflow are provenance, sustainable automation, implementation challenges, and integration/compatibility challenges. Through conversations and interviews among the program managers, project leads, and software engineers, we have developed critical insight and strategies to overcome the obstacles and augment the successful adoption and long-term use of these workflows in ExaAM and beyond. We hope our work will pave the way for others in the research community to develop and use workflows in their respective science domains.
Autoencoder-Based Four Dimensional Constellation for Phase Noise Channels

A four-dimensional constellation tolerant to AWGN and phase noise (PN) is designed with 8 bits/symbol using autoencoder based end-to-end learning system. Compared with dual polarized square 16QAM, our method obtained up to 1.9 and 1.8 dB gain in SER and BER performances, respectively.