Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Elliptic Curve Multiplications Resistant against Side Channel Attacks

This paper proposes fast elliptic curve multiplication algorithms resistant against side channel attacks, based on the Montgomery-type scalar multiplication. The proposed scalar multiplications can be applied to all curves over prime fields, e.g., any standardized curves over finite fields with characteristic larger than 3. The method utilizes the addition formulas xECDBL and xECADD assembled by only x-coordinates of points, and is applicable for any types of curves over finite fields. Then, we encapsulate two addition formulas into one formula xECADDDBL, which accomplishes a faster computation because several auxiliary variables of two formulas can be shared. We also develop a novel addition chain for the new formula, with which we can compute scalar multiplications. The improvement of our scalar multiplications over previous Coron's dummy operation method is about 18% for a 160-bit scalar multiplication. Our method requires no table-up of precomputed points and it is suitable for the implementation on memory constraint computing architectures, e.g., smart cards. Moreover, we optimize the proposed algorithms for parallelized implementations with SIMD operations. Compared with the similar scheme proposed by Fischer et al., our scheme is about 16% faster.
A completely autonomous system that learns anomalous movements in advanced videosurveillance applications

This paper describes an automatic real-time video surveillance system, capable of autonomously learning and signaling anomalous activities of moving objects. To obtain these capabilities, an improved version of the altruistic vector quantization algorithm (AVQ) is proposed. The modified AVQ automatically evaluates the number of trajectory prototypes, and improves the representativeness of the prototypes themselves, so the visual events can be easily and accurately classified. Anomalous behaviors are detected if visual trajectories deviate from the self-learned representations of "typical" behaviors. The system has been implemented by means of standard PCs and TV cameras, and has been tested in many real outdoor contexts in different conditions (night and day). Currently it is used to monitor the storage areas of British Airways at the airport of Peretola (Florence, Italy), and some access gates of Autostrade per FItalia S.p.A. (the main Italian highways company). If the camera field-of-view is changed, the system automatically re-learns new "typical" behaviors and accurately detects anomalous events.
Water Supply and Wastewater Treatment and Reuse in Future Cities: A Systematic Literature Review

Due to climate emergencies, water stress, and fast-growing populations, many cities around the world are adopting wastewater reclamation and reuse to improve the water supply for their residents. The purpose of the paper was to investigate the effectiveness of expanding wastewater reclamation and reuse as a solution to water supply challenges for future cities. It used a systematic review of the literature to evaluate and synthesize the available evidence in support of wastewater reclamation and reuse for future cities. A model known as PRISMA was used to identify the most appropriate articles for inclusion in the study. Out of the 105 studies, a total of 46 articles were selected for analysis based on their relevance, content validity, and strength of evidence. The findings indicate that wastewater reclamation and reuse create additional sources of water for both domestic and industrial use, reducing the overall pressure on the natural water sources. Wastewater reclamation and reuse effectively increase water supply for future cities while minimizing pressure on natural resources and promoting environmental sustainability.
TUTORING EFFICACY, HOUSEHOLD SUBSTITUTION, AND STUDENT ACHIEVEMENT: EXPERIMENTAL EVIDENCE FROM AN AFTER‐SCHOOL TUTORING PROGRAM IN RURAL CHINA

Public after‐school tutoring has risen globally despite limited evidence of effectiveness. We implement a randomized after‐school tutoring program in rural China where many children are left‐behind by parents in care of grandparents. Compared to tutees cared for by parents, those in care of grandparents reported much smaller home‐tutoring reductions but larger test‐score gains. We interpret our data analysis with a model with tutoring efficacy and substitution between private and public inputs both differing by family background: increased public tutoring generates larger test‐score gains for children who experience greater tutoring efficacy and lesser substitution with household inputs, consistent with our estimates.This article is protected by copyright. All rights reserved
Conservation Implications When the NestPredators Are Known

Conservation and management of passerines has largely focused on habitat manipulation or restoration because the natural communities on which these birds depend have been destroyed and fragmented. However, productivity is another important aspect of avian conservation, and nest predation can be a large source of nesting mortality for passerines. Recent studies using video surveillance to identify nest predators allow researchers to start evaluating what methods could be used to mitigate nest predation to help passerines of conservation concern. From recent studies, we identified latitudinal and habitat-related patterns in the importance of predator groups that depredate passerine nests. We then reviewed how knowledge of specific nest predators can benefit conservation of bird species of concern. Mammals were the dominant predator group in northern grasslands. Snakes were the dominant predator group in southern habitats. Fire ants were only a nest predator in southern latitudes. Differences in the importance of predator species or groups were likely the result of both their geographic patterns of distribution and habitat preferences. Some direct and indirect predator control measures developed for waterfowl management potentially could be used to benefit passerine productivity. We reviewed three examples—cowbirds, snakes in shrublands, and ground squirrels in grasslands—to illustrate how different predator control strategies may be needed in different situations. Mitigation of passerine nest predation will need to be based on knowledge of predator communities to be effective. This requires large samples of predation events with identified predators; video technology is essential for this task.
Funkcje podatków w gospodarce

DOI: 10.19251/ne/2017.25(14) Podatki stanowią podstawowe źrodlo dochodow budzetu panstwa i jednostek samorządu terytorialnego, a problematyka podatkowa ma szczegolne znaczenie dla gospodarki kazdego kraju, jego obywateli i podmiotow gospodarczych funkcjonujących na rynku danego kraju. W związku z objeciem swoim zasiegiem niemal wszystkich osob fizycznych oraz osob prawnych dzialających na rynku, podatki są podstawowym instrumentem wplywania przez panstwo na gospodarke. Podatki odgrywają znaczącą role w zyciu codziennym i powinny byc brane pod uwage przez kazdego przy planowaniu kazdej aktywności gospodarczej. Najstarszą funkcją podatkow jest funkcja fiskalna, zgodnie z ktorą, ze podatki mają dostarczac panstwu i samorządom lokalnym odpowiednie dochody na pokrycie wydatkow publicznych. Podatki stanowią prawie 90% wszystkich dochodow budzetowych, a funkcja fiskalna podatkow w ostatnich latach wzrasta wraz z rozwojem gospodarczym kraju. Slowa kluczowe: podatki, funkcje, budzet panstwa, znaczenie
RuNi/MMO Catalysts Derived from a NiAl-NO3-LDH Precursor for CO Selective Methanation in H2-Rich Gases

CO selective methanation (CO-SMET) is a promising method for deep CO removal from H2-rich gases. In this study, a series of RuNi/MMO catalysts are prepared using the support MMO-N derived from NiAl-NO3-LDHs, which was prepared from NiAl-CO3-LDHs via an acid–alcohol ion-exchange reaction. The prepared catalysts were characterized by XRD, SEM, TEM, XPS, H2-TPR, CO-TPD, CO2-TPD, NH3-TPD, and TG. The RuNi/MMO-N catalyst demonstrated excellent CO-SMET performance, successfully reducing the CO to less than 10 ppm with a selectivity greater than 50% in a reaction temperature window ranging from 180 °C to 260 °C. Compared with similar catalysts derived from NiAl-CO3-LDHs, the exceptional CO-SMET capability of the RuNi/MMO-N catalyst is suggested to be associated with a more effective hydrogen spillover, a larger number of electron-rich Ni sites, and a higher density of acid sites on the surface of RuNi/MMO-N, which are conducive to CO adsorption and the inhibition of CO2 methanation.
Quick Notification of Block Generation Using Bloom Filter in a Blockchain

Forks in a blockchain sacrifice security. In this paper, we propose a protocol for quickly propagating block generation notifications in the blockchain network quickly to reduce the fork rate. Block generation notifications contain a Bloom filter that represents transactions in the generated block. Thus, when nodes receive a block generation notification, they can start mining the next block. In experiments in which a simulator is used, we compared the propagation time of a block generation notification with that of a block in the existing protocol. As a result, the propagation time of the 50 %ile is 41.1 % of an existing protocol, the 90 %ile is 39.2 % of the existing protocol, and the fork rate calculated from the average propagation time is 40.8 % of the existing protocol.
Marginal Ulcer and Dumping Syndrome in Patients after Duodenal Switch: A Multi-Centered Study

Background: The current design of biliopancreatic diversion with duodenal switch (BPD/DS) and single anastomosis duodenal–ileal bypass with sleeve (SADI-S) emphasizes the importance of the pylorus’ preservation to reduce the incidence of marginal ulcer (MU) and dumping. However, no institutional studies have yet reported data on their prevalence. We aimed to assess the incidence of MU and dumping after duodenal switch (DS) and identify the associative factors. Methods: A multi-center review of patients who underwent BPD/DS or SADI-S between 2008 and 2022. Baseline demographics, symptoms, and management of both complications were collected. Fisher’s exact test was used for categorical variables and the independent t-test for continuous variables. Results: A total of 919 patients were included (74.6% female; age 42.5 years; BMI 54.6 kg/m2) with mean follow-up of 31.5 months. Eight patients (0.9%) developed MU and seven (0.8%) had dumping. Patients who developed MU were more likely to be using non-steroidal anti-inflammatory drugs (NSAID) (p = 0.006) and have a longer operation time (p = 0.047). Primary versus revisional surgery, and BDP/DS versus SADI-S were not associated with MU or dumping. Conclusions: The incidences of MU and dumping after DS were low. NSAID use and a longer operation time were associated with an increased risk of MU, whereas dumping was attributed to poor dietary habits.
Prevalence and Prognostic Implications of PSA Flares during Radium-223 Treatment among Men with Metastatic Castration Resistant Prostate Cancer

Radium-223 (Ra233) prolongs the survival of men with symptomatic bone-predominant metastatic castration-resistant prostate cancer (mCRPC). However, prostate-specific antigen (PSA) response patterns are not closely associated with Ra223 therapy outcomes. Herein, we sought to analyze the impact of Ra223-induced PSA flares on patient outcome. Using a retrospective cohort study of Ra223 treatment in four Ontario/Canada cancer centres, we identified 134 patients grouped into sub-cohorts according to distinct PSA response patterns: (i) initial PSA flare followed by eventual PSA decline; (ii) PSA response (≥30% PSA decrease within 12 weeks of treatment); and (iii) PSA non-response. We analyzed patient characteristics and outcome measures, including overall survival (OS), using the Kaplan-Meier method and log-rank testing. PSA flares were observed in 27 (20.2%), PSA responses in 11 (8.2%), and PSA non-responses in 96 (71.6%) patients. Amongst PSA flare patients, 12 presented with post-flare PSA decreases below baseline and 15 with PSA decreases below the flare peak but above baseline. Although only six flare patients achieved ≥30% PSA decreases below baseline, the median OS of all flare patients (16.8 months, 95% CI 14.9–18.7) was comparable to that of PSA responders and non-responders (p = 0.349). In summary, around 20% of mCRPC patients experience Ra223-induced PSA flares, whose outcome is similar to that of men with or without PSA responses. Further studies are needed regarding suitable biochemical surrogate markers of response to Ra223.
il-27 inhibits non-small-cell lung cancer cell metastasis by mir-935 in vitro

with miR-935, and the cell proliferation was assayed by Cell Counting Kit-8 (CCK-8) and colony formation. Cell metastasis was analyzed by Transwell chamber system and wound healing assay. IL-27 protein in the medium was analyzed by ELISA. IL-27 mRNA expression was measured by quantitative reverse transcriptase-PCR. Results: We found that IL-27 played an inhibiting role in NSCLC cell proliferation and metastasis. The molecular mechanism of the suppressing role of IL-27 in NSCLC was regulated by miR-935. IL-27 expression was negatively associated with miR-935 in the clinical NSCLC samples. Conclusion: The study revealed that IL-27 decreased lung cancer cell proliferation and metastasis via miR-935.
Quantum Cryptography in 5G Networks: A Comprehensive Overview

Every attempt to access to the Internet through a Web browser, email sent, VPN connection, VoIP call, instant message or other use of telecommunications systems involves cryptographic techniques. The most commonly applied technique is asymmetric cryptography, which is generally executed in the background without the user even being aware. It establishes a cryptographic code based on the computational complexity of mathematical problems. However, this type of cryptography, which is widely used in today’s telecommunications systems, is under threat as electronics and computing rapidly develop. The development of fifth-generation cellular networks (5G) is gaining momentum, and given its wide field of application, security requires special attention. This is especially true faced with the development of quantum computers. One solution to this security challenge is to use more advanced techniques to establish cryptographic keys that are not susceptible to attack. An essential part of quantum cryptography, Quantum Key Distribution (QKD) uses the principles of quantum physics to establish and distribute symmetric cryptographic keys between two geographically distant users. QKD establishes information-theoretically secure cryptographic keys that are resistant to eavesdropping when they are created. In this paper, we survey the security challenges and approaches in 5G networks concerning network protocols, interfaces and management organizations. We begin by examining the fundamentals of QKD and discuss the creation of QKD networks and their applications. We then outline QKD network architecture and its components and standards, following with a summary of QKD and post-quantum key distribution techniques and approaches for its integration into existing security frameworks such as VPNs (IPsec and MACsec). We also discuss the requirements, architecture and methods for implementing the FPGA-based encryptors needed to execute cryptographic algorithms with security keys. We discuss the performance and technologies of post-quantum cryptography, and finally, examine reported 5G demonstrations which have used quantum technologies, highlighting future research directions.
Information Quality Improvement With Task Selection Algorithm For IoT Energy Harvesting Devices

The purpose of study is to propose a task selection algorithm that both keeps information quality and saves power consumption in IoT energy harvesting devices. The proposed algorithm not only keeps stable information quality but saves power loss also. The sensor node operation is divided into four tasks depending on the input data including battery capacity, solar panel charging current, and input sensor data variation. The task selector based on a neural network consists of an input layer, a hidden layer of 20 neurons, and an output layer. The proposed algorithm is different from the predefined task algorithm, which mainly focused on deep sleep mode or scheduled tasks. Our proposed algorithm helps the sensor node to be more adaptive to the environment based on real-time execution at each node. The collected information amount varies according to the input data variation. The experiment results show that the proposed algorithm collects higher quality information at large input data variation. The battery lifetime is also improved by up to 22%.
Gauss-Seidel Progressive Iterative Approximation (GS-PIA) for Loop Surface Interpolation

We propose a Gauss-Seidel progressive iterative approximation (GS-PIA) method for Loop subdivision surface interpolation by combining classical Gauss-Seidel iterative method for linear system and progressive iterative approximation (PIA) for data interpolation. We prove that GS-PIA is convergent by applying matrix theory. GS-PIA algorithm retains the good features of the classical PIA method, such as the resemblance with the given mesh and the advantages of both a local method and a global method. Compared with some existed interpolation methods of subdivision surfaces, GS-PIA algorithm has advantages in three aspects. First, it has a faster convergence rate compared with the PIA and WPIA algorithms. Second, compared with WPIA algorithm, GS-PIA algorithm need not to choose weights. Third, GS-PIA need not to modify the mesh topology compared with other methods with fairness measures. Numerical examples for Loop subdivision surfaces interpolation illustrated in this paper show the efficiency and effectiveness of GS-PIA algorithm.
Enhancing Cloud Security with a Fuzzy Rule-Based Classifier for Intrusion Detection and Classification

Cloud computing (CC) is a model of distributed computing that makes it possible to access data, applications, and computer infrastructure through the Internet whenever and wherever it is needed. CC is a method of providing online consumers with access to virtualized, dynamically scaled resources. The importance of safety in this on-demand CC cannot be overstated. That's why the authors of this study are presenting a new method of cloud intrusion detection using fuzzy rules. The IDFRC method can monitor the distributed CC platform for intrusions and protect it from any dangers. Each client has their own unique IDS instance installed, with its own dedicated controller. In order to better detect and categorize intrusions, the authors of this piece provide the improved intrusion detection using Fuzzy Rule-based Classifier (IDFRC) model for use in the cloud. The proposed ID-FRC paradigm seeks to distinguish between malicious and benign cloud-based data flows. The improved results of the suggested method are analyzed by a comprehensive simulation study. A hybrid intelligent fruit fly optimization algorithm (HFOA) is used to fine-tune the FRC model's parameters. The FRC is a powerful paradigm in pattern recognition that provides useful results by the incorporation of language labels into the rules' antecedents. The KDD99 and NSL-KDD dataset is utilized to evaluate the suggested approach. Improvements of the current method over recent state-of-the-art methods were guaranteed by a simulation study of the IDFRC model. Maximum detection performance was reported by the model, with an F-score of 98.5 and a reliability of 100%.
Male hypogonadism: an extended classification based on a developmental, endocrine physiology‐based approach

Normal testicular physiology results from the integrated function of the tubular and interstitial compartments. Serum markers of interstitial tissue function are testosterone and insulin‐like factor 3 (INSL3), whereas tubular function can be assessed by sperm count, morphology and motility, and serum anti‐Müllerian hormone (AMH) and inhibin B. The classical definition of male hypogonadism refers to testicular failure associated with androgen deficiency, without considering potential deficiencies in germ and Sertoli cells. Furthermore, the classical definition does not consider the fact that low basal serum testosterone cannot be equated to hypogonadism in childhood, because Leydig cells are normally quiescent. A broader clinical definition of hypogonadism that could be applied to male patients in different periods of life requires a comprehensive consideration of the physiology of the hypothalamic‐pituitary‐testicular axis and its disturbances along development. Here we propose an extended classification of male hypogonadism based on the pathophysiology of the hypothalamic‐pituitary‐testicular axis in different periods of life. The clinical and biochemical features of male hypogonadism vary according to the following: (i) the level of the hypothalamic‐pituitary‐testicular axis primarily affected: central, primary or combined; (ii) the testicular cell population initially impaired: whole testis dysfunction or dissociated testicular dysfunction, and: (iii) the period of life when the gonadal function begins to fail: foetal‐onset or postnatal‐onset. The evaluation of basal testicular function in infancy and childhood relies mainly on the assessment of Sertoli cell markers (AMH and inhibin B). Hypergonadotropism should not be considered a sine qua non condition for the diagnosis of primary hypogonadism in childhood. Finally, the lack of elevation of gonadotropins in adolescents or adults with primary gonadal failure is indicative of a combined hypogonadism involving the gonads and the hypothalamic‐pituitary axis.
A Framework for Few-Shot Network Threats Based on Generative Adversarial Networks

A small amount of malicious logs is confusing and unbalanced for a large number of normal logs. We proposed a framework of network threats sample based on Generative Adversarial Networks(GAN). This paper solves the imbalance problem of multidimensional sample data such as logs, traffic, programs, and feature spaces in the field of cyberspace security by generating confrontation networks. We carried out a large-scale confrontation generation experiment of security event logs based on SeqGAN and generated corresponding log text for data enhancement, which effectively solve the problem of few-shot. The results in this section show that the use of the AC-GAN augmentation dataset is enhanced compared to the original non-equilibrium dataset using the artificial synthesis of the SMOTE dataset Network traffic data set to improve the performance of supervised learning classification. It has inestimable effects on threat detection, various types of offensive to defensive, and cryptography algorithms.
DifferentialTrendsinWeight-RelatedHealthBehaviors AmongAmericanYoungAdultsbyGender,Race/Ethnicity, andSocioeconomicStatus:1984-2006

Objectives. We investigated temporal patterns from 1984 to 2006 in 6 weightrelated health behaviors by using longitudinal data for multiple cohorts of young adults (aged 19–26 years) from the nationally representative Monitoring the Future Study. Methods. We used growth curve models to examine historical trends in 6 health behaviors: frequency of eating breakfast, eating green vegetables, eating fruit, exercising, watching television, and sleeping 7 hours each night. Variations across gender, race/ethnicity, and socioeconomic status were investigated. Results. Frequency of exercising was consistently lower among young adult women than young adult men over this 23-year period. Compared with White women, Hispanic women, and women from other race/ethnic groups, Black women showed declines in the frequency of exercise since 1984. In general, young adult women showed a marked increase in the frequency of eating breakfast over this period, although Black women did not show any net gains. Conclusions. Social disparities in body weight may increase because Black women, Hispanic women, and men with lower socioeconomic status show declining trends in positive weight-related health behaviors compared with White young adults with higher socioeconomic status. (Am J Public Health.