Miracle-dz/UniFAR-FTUs huggingface dataset:
PCAT: Functionality and Data Stealing from Split Learning by Pseudo-Client Attack

Split learning (SL) is a popular framework to protect a client’s training data by splitting up a model among the client and the server. Previous efforts have shown that a semi-honest server can conduct a model inversion attack to recover the client’s inputs and model parameters to some extent, as well as to infer the labels. However, those attacks require the knowledge of the client network structure and the performance deteriorates dramatically as the client network gets deeper ( ≥ 2 layers). In this work, we explore the attack on SL in a more general and challenging situation where the client model is unknown to the server and gets more complex and deeper. Different from the conventional model inversion, we investigate the inherent privacy leakage through the server model in SL and reveal that clients’ functionality and private data can be easily stolen by the server model, and a series of intermediate server models during SL can even cause more leakage. Based on the insights, we propose a new attack on SL: P seudo-C lient AT tack (PCAT). To the best of our knowledge, this is the first attack for a semi-honest server to steal clients’ functionality, reconstruct private inputs and infer private labels without any knowledge about the clients’ model. The only requirement for the server is a tiny dataset (about 0.1% - 5% of the private training set) for the same learning task. What’s more, the attack is transparent to clients, so a server can obtain clients’ privacy without taking any risk of being detected by the client. We implement PCAT on various benchmark datasets and models. Extensive experiments testify that our attack significantly outperforms the state-of-the-art attack in various conditions, including more complex models and learning tasks, even in non-i.i. d. conditions. Moreover, our functionality stealing attack is resilient to the existing defensive mechanism.
Análisis de la estabilidad fisicoquímica de una bebida de cacahuate con jengibre

Las bebidas vegetales son una opción saludable, amigable con el planeta y se ajustan al estilo de vida de consumidores que buscan bebidas funcionales de origen no animal, pero con características organolépticas similares a la leche de vaca. El presente trabajo tuvo como objetivo elaborar una bebida vegetal a base de cacahuate (Arachis hypogaea) adicionada con jengibre (Zingiber officinale). Se elaboraron 13 bebidas con diferentes formulaciones, variando contenido de cacahuate (C), lecitina de soya (L) y goma gelana (G), pero manteniendo fija la cantidad de jengibre. Se analizó el potencial zeta y tamaño de partícula (diámetro de Sauter y diámetro de Brouckere) en un inicio y después de dos meses de almacenamiento a 4°C. Después de dos meses, el potencial zeta varió entre -18 y -32 mV; el diámetro de Sauter entre 11.46 y 27.33 mm; y el diámetro de Broukere entre 49.17 y 99.38 mm. De acuerdo al diseño de superficie de respuesta, la formulación óptima fue 5.64 % C, 1.50% L y 0.30% G. Los resultados sugieren que la combinación de lecitina de soya y goma gelana tiene un efecto positivo en la estabilidad coloidal.
Affine sl(N)conformal blocks from [FORMULA] SU(N) gauge theories

Recently Alday and Tachikawa [1] proposed a relation between conformal blocks in a two-dimensional theory with affine sl(2) symmetry and instanton partition functions in four-dimensional conformal [FORMULA] SU(2) quiver gauge theories in the presence of a certain surface operator. In this paper we extend this proposal to a relation between conformal blocks in theories with affine sl(N) symmetry and instanton partition functions in conformal [FORMULA] SU(N) quiver gauge theories in the presence of a surface operator. We also discuss the extension to non-conformal [FORMULA] SU(N) theories.
A Sequential Cross-Sectional Analysis Producing Robust Weekly COVID-19 Rates for South East Asian Countries

The COVID-19 pandemic has expanded fast over the world, affecting millions of people and generating serious health, social, and economic consequences. All South East Asian countries have experienced the pandemic, with various degrees of intensity and response. As the pandemic progresses, it is important to track and analyse disease trends and patterns to guide public health policy and treatments. In this paper, we carry out a sequential cross-sectional study to produce reliable weekly COVID-19 death (out of cases) rates for South East Asian countries for the calendar years 2020, 2021, and 2022. The main objectives of this study are to characterise the trends and patterns of COVID-19 death rates in South East Asian countries through time, as well as compare COVID-19 rates among countries and regions in South East Asia. Our raw data are (daily) case and death counts acquired from “Our World in Data”, which, however, for some countries and time periods, suffer from sparsity (zero or small counts), and therefore require a modelling approach where information is adaptively borrowed from the overall dataset where required. Therefore, a sequential cross-sectional design will be utilised, that will involve examining the data week by week, across all countries. Methodologically, this is achieved through a two-stage random effect shrinkage approach, with estimation facilitated by nonparametric maximum likelihood.
A Variational Bayes Approach to Clustered Latent Preference Models for Directed Network Data

Variational Bayes (VB) refers to a framework used to make fast deterministic approximations to the posterior density for Bayesian statistical inference. Traditionally, it has competed with Markov Chain Monte Carlo (MCMC) methods, a stochastic method which is asymptotically correct but computationally expensive. We derive the VB approximation to the Directed Clustered Latent Preference Network Model, which is inspired by ideas from Hoff et al. (2002); Handcock et al. (2007); Ward and Hoff (2007); Salter-Townshend and Murphy (2013); Krivitsky and Handcock (2008). The model handles binary-valued or continuous directed network data, and incorporates Gaussian mixture models over the separate latent sending and receiving preference spaces of each actor. We apply the model to simulated and real datasets to evaluate its performance against existing MCMC methods such as the Gibbs sampler. We discover new insights in the well-studied Sampson’s Monks dataset (Sampson, 1968), as well as confirm existing results with the Correlates of War International Trade dataset (Barbieri and Keshk, 2012). We conclude by discussing unresolved issues, potential solutions, and areas of future work. v
k-Anonymity Based on Tuple Migration in Sharing Data

—Nowadays, the development of big data, cloud computing, and the internet of things has led to an increase in sharing data. Through the data mining process, some valuable information can be discovered from such shared data. However, most shared data contain personal sensitive information such as users’ location information or disease status and attackers, by analysing such data, may also extract some private (sensitive) information of the user and this can result in threats against the user's privacy. Therefore, before sharing data or making it open we must apply privacy techniques to protect the sensitive information in the data. In this paper, we propose a new approach as well as a technique to guarantee k-anonymity, the most popular privacy protection technique, in the data. The main idea is to design an algorithm to organize tuples/records in the data into groups and then migrate tuples between the groups such that all the groups satisfy k-anonymity. Specifically, the proposed algorithm also maintains the significant association rules in the k-anonymity data so that the data mining process, based on association rule mining, can preserve valuable information as in original data. We perform experiments to evaluate the performance and data utility of our proposed technique in comparison with state-of-the-art anonymization techniques. The experimental results show that our technique outperforms such state-of-the-art ones.
Sklopitev med stimulacijo in sekrecijo in medcelične interakcije celic alfa v zdravju in pri sladkorni bolezni tipa 2 Alpha Cell Stimulus–Secretion Coupling and Intercellular Interactions in Health and Type 2 Diabetes

Beta cell dysfunction has long been thought to be at the root of type 2 diabetes pathogenesis; however, a bi-hormonal model of the disease appears to be more realistic. Alpha cells play a significant role in glucose homeostasis due to their communication with other cells within the islets of Langerhans and tissues through glucagon action. Despite the lack of a concise model for their physiology, new approaches provide more insight into the pathways of glucagon secretion and processes that regulate it. This increased understanding of alpha cell function in healthy and diseased states has potential implications for managing type 2 diabetes.
Implementation and Evaluation of a Smart Uplink Jamming Attack in a Public 5G Network

In this paper, we present a hardware implementation and an evaluation of the effectiveness and feasibility of a smart jamming attack that targets specific uplink physical channels to destabilize 5G communication systems. Using software defined radio (SDR), we examine the susceptibility of the 5G Physical Uplink Shared Channel (PUSCH) to a smart jamming attack as well as the impact of such an attack on user equipment (UE) throughput. The smart jamming attack is designed to exploit the radio access procedure by: 1) identifying the user’s cell radio network temporary identifier (C-RNTI); 2) decoding the physical downlink control channel (PDCCH) information containing the specific UE resources; and 3) generating a quadrature phase shift keying (QPSK) modulated Orthogonal Frequency-Division Multiplexing (OFDM) waveform to effectively deny uplink access. A detailed description of the implementation of the overall testbed used to evaluate and quantify the effectiveness of the custom implementation of a smart jamming attack is presented in this paper. The evaluation results show that the smart jamming attack successfully denied uplink access by reducing the throughput of a specific UE by 100%.
Stationary distributions of the R[X]/R/1 cross-correlated queue

ABSTRACT We consider an infinite buffer single server queue wherein batch interarrival and service times are correlated having a bivariate mixture of rational (R) distributions, where R denotes the class of distributions with rational Laplace–Stieltjes transform (LST), i.e., ratio of a polynomial of degree at most n to a polynomial of degree n. The LST of actual waiting time distribution has been obtained using Wiener–Hopf factorization of the characteristic equation. The virtual waiting time, idle period (actual and virtual) distributions, as well as inter-departure time distribution between two successive customers have been presented. We derive an approximate stationary queue-length distribution at different time epochs using the Markovian assumption of the service time distribution. We also derive the exact steady-state queue-length distribution at an arbitrary epoch using distributional form of Little’s law. Finally, some numerical results have been presented in the form of tables and figures.
Exploring the Latency Sensitivity of Cache Replacement Policies

With DRAM latencies increasing relative to CPU speeds, the performance of caches has become more important. This has led to increasingly sophisticated replacement policies that require complex calculations to update their replacement metadata, which often require multiple cycles. To minimize the negative impact of these metadata updates, architects have focused on policies that incur as little update latency as possible through a combination of reducing the policies’ precision and using parallel hardware. In this work we investigate whether these tradeoffs to reduce cache metadata update latency are needed. Specifically, we look at the performance and energy impact of increasing the latency of cache replacement policy updates. We find that even dramatic increases in replacement policy update latency have very limited effect. This indicates that designers have far more freedom to increase policy complexity and latency than previously assumed.
Precise measurement of the beta-asymmetry in the decay of magneto-optically trapped, spin-polarized 37K

Precise low-energy measurements in nuclear β-decay provide constraints on possible physics beyond the standard model complementary to high-energy collider experiments. This thesis describes the most precise measurement of the positron asymmetry from a polarized nucleus to date. At the Triumf Neutral Atom Trap, atoms of the positron emitter K are confined in an alternating-current magneto-optical trap and spin-polarized to 99.13(9)% via optical pumping. The use of atom-trapping techniques allows for an exceptionally open geometry with the decay products escaping the trapping region unperturbed by the trapping potential. The emitted positrons are detected in a pair of symmetric detectors placed along the polarization axis to measure the asymmetry. The analysis was performed blind and considers β-scattering and other systematic effects. The result, Aβ (0) = −0.5707 ± 0.0018, places limits on the mass of a hypothetical W boson coupling to right-handed neutrinos to be > 300GeV/c at zero-mixing as well as contributes to an independent determination of the Vud element of the CKM matrix.
The Effects of Polyaniline Nanofibers and Graphene Flakes on the Electrical Properties and Mechanical Properties of ABS-like Resin Composites Obtained by DLP 3D Printing

Three-dimensional printing is regarded as a future-oriented additive manufacturing technology that is making significant contributions to the field of polymer processing. Among the 3D printing methods, the DLP (digital light processing) technique has attracted great interest because it requires a short printing time and enables high-quality printing through selective light curing of polymeric materials. In this study, we report a fabrication method for ABS-like resin composites containing polyaniline (PANI) nanofibers and graphene flakes suitable for DLP 3D printing. As-prepared ABS-like resin composite inks employing PANI nanofibers and graphene flakes as co-fillers were successfully printed, obtaining highly conductive and mechanically robust products with the desired shapes and different sizes through DLP 3D printing. The sheet resistance of the 3D-printed composites was reduced from 2.50 × 1015 ohm/sq (sheet resistance of pristine ABS-like resin) to 1.61 × 106 ohm/sq by adding 3.0 wt. % of PANI nanofibers and 1.5 wt. % of graphene flakes. Furthermore, the AP3.0G1.5 sample (the 3D-printed composite containing 3.0 wt.% of PANI nanofibers and 1.5 wt.% of graphene flakes) exhibited 2.63 times (22.23 MPa) higher tensile strength, 1.47 times (553.8 MPa) higher Young’s modulus, and 5.07 times (25.83%) higher elongation at break values compared to the pristine ABS-like resin with a tensile strength of 8.46 MPa, a Young’s modulus of 376.6 MPa, and an elongation at break of 5.09%. Our work suggests the potential use of highly conductive and mechanically robust ABS-like resin composites in the 3D printing industry. This article not only provides optimized DLP 3D printing conditions for the ABS-like resin, which has both the advantages of the ABS resin and the advantages of a thermoplastic elastomer (TPE), but also presents the effective manufacturing process of ABS-like resin composites with significantly improved conductivity and mechanical properties.
Is a typical bi-Perron algebraic unit a pseudo-Anosov dilatation?

In this note, we deduce a partial answer to the question in the title. In particular, we show that asymptotically almost all bi-Perron algebraic units whose characteristic polynomial has degree at most $2n$ do not correspond to dilatations of pseudo-Anosov maps on a closed orientable surface of genus $n$ for $n\geq 10$ . As an application of the argument, we also obtain a statement on the number of closed geodesics of the same length in the moduli space of area-one abelian differentials for low-genus cases.
On the chromatic number of (P_{5},windmill)-free graphs

In this paper we study the chromatic number of \((P_5, windmill)\)-free graphs. For integers \(r,p\geq 2\) the windmill graph \(W_{r+1}^p=K_1 \vee pK_r\) is the graph obtained by joining a single vertex (the center) to the vertices of \(p\) disjoint copies of a complete graph \(K_r\). Our main result is that every \((P_5, windmill)\)-free graph \(G\) admits a polynomial \(\chi\)-binding function. Moreover, we will present polynomial \(\chi\)-binding functions for several other subclasses of \(P_5\)-free graphs.
Benefits of Gd for High Energy Neutrinos in SuperK-Gd

The SuperK-Gd project is the approved upgrade of the Super-Kamiokande (SK) detector in order to enable it to efficiently (> 80%) detect thermal neutrons by dissolving 0.2% of gadolinium sulphate (Gd2(SO4)3) into its water. This ability has also significant advantages in the analysis of high energy (> 102 MeV) neutrinos in SK, namely atmospheric and long baseline neutrinos from T2K. Here we present the improvements due to the use of the tagged final state neutrons in the separation of the interacting neutrinos and antineutrinos, the distinction between Neutral Current and Charged Current neutrino interactions, and the neutrino energy reconstruction. We study the impact of those features on both, atmospheric and long baseline neutrino oscillation analyses.
Yeasts Inoculation Effect on Bacterial Development in Carbonic Maceration Wines Elaboration

Carbonic maceration (CM) vinification is a very traditional method that allows saving energy without great equipment investment, obtaining high-quality wines. However, due to its particularities, CM winemaking implies a higher risk of microbial alteration. This work studies the evolution of bacterial population along carbonic maceration wines elaboration with and without yeast inoculation. In the same way, two strategies of yeast inoculation were studied: “pied de cuve” and Active Dry Yeasts (ADY) seed. For this purpose, three conditions were assayed: spontaneous fermentation (without inoculation), “pied de cuve” technology, and ADY inoculation. For each condition, two winemaking methods were compared: carbonic maceration and the standard method of destemming and crushing (DC). The bacterial evolution (lactic acid and acetic acid bacteria) was followed in different fermentation stages. Finally, the wines obtained were analysed (pH and volatile acidity). In the non-inoculated wines produced by CM, high development of the bacterial population was observed (counts of acetic acid bacteria around 4.3 log cfu/mL), and finished wines presented high values of volatile acidity (>1.5 g/L), which did not occur in the inoculated vinifications (counts of acetic acid bacteria around 1.5 log cfu/mL and 0.5 g/l of volatile acidity). Thus, the control of yeast population, as a “pied de cuve” as ADY seed, seems to be an effective tool to avoid bacterial alterations in CM vinifications.
As temáticas da regulação do jornalismo português: análise às deliberações da AACS e ERC

Com base numa sistematizacao de pareceres alargada a todos os organismos de regulacao do jornalismo portugues, este artigo compreende uma analise aprofundada das tematicas, atores e resolucoes que participam nas diferentes deliberacoes dos dois principais organismos da historia da heterorregulacao da comunicacao social portuguesa: Alta Autoridade para a Comunicacao Social (AACS) e Entidade Reguladora para a Comunicacao Social (ERC). O estudo baseia-se numa analise de 1738 processos da AACS e 1126 da ERC. Paralelamente, a presente investigacao procura fundamentar empiricamente o desfecho de um atribulado e complexo processo de relacao entre mecanismos, sustentado no receio das consequencias de uma juridificacao da deontologia e da captura estatal dos poderes da autorregulacao do jornalismo. Sustentado numa analise de conteudo, este artigo pretende ainda propor uma ferramenta metodologica apta a apoiar a investigacao empirica sobre os organismos de regulacao do jornalismo.
Performance Analysis of SPSK with Dual Polarized Transmit Antennas over Rayleigh Fading Channel

In this paper, the Space Polarization Shift Keying (SPSK) system, which is an extended version of Space Shift Keying (SSK) and includes both space and polarization dimensions with dual polarized antennas, is studied. The capacity and error probability analysis of SPSK for different polarization configurations are dealt with over the Rayleigh fading channel with a rich scattering environment. The analysis conducted shows that the SPSK with a dual polarized antenna (DP) offers better results than SPSK with a single orthogonal polarized antenna SPSK(SP), under non-LOS conditions. SPSK(DP) outperforms SSK by 4.2 dB over the correlated Rayleigh fading channel at 3 bits/s/Hz. Keywords—ABER, dual polarized antenna, Rayleigh fading, spatial modulation, SPSK, SSK.
The Impediment Factors of Customers Intentions to Borrow in Peer to Peer Lending Apps

In the last decade, Indonesia's fintech trend are supported by the growth of Internet users. A recent report by OJK in 2021 shows that online loan services continue to increase by the millennial generation's dominance. It's because online loan services are easier to gain rather than conventional loan services. Unfortunately, its service provides several potential threats to its users. Moreover, religious values play a critical role in shaping consumers' attitudes and behavior towards products or services. The purpose of this study is to analyze the role of perceived risk: security risks and privacy risks, and religiosity in predicting customers' intention to borrow in P2P Lending apps. The research approach is quantitative, with a random sampling technique, and the research sample is 86 respondents. The data were analyzed by using multiple linear regression with IBM SPSS 23. Based on the study results, it can be concluded that security risk has a negative and significant effect in predicting the intention to borrow in P2P Lending apps, but no relationship between privacy risk and religiosity on the intention to borrow. As a managerial implication, our findings can help the company to focus on providing highly secure apps and promoting and campaigning the confidentiality of users' personal information.