Miracle-dz/UniFAR-FTUs huggingface dataset:
CHE: Channel-Wise Homomorphic Encryption for Ciphertext Inference in Convolutional Neural Network

Privacy-preserving deep learning (PPDL), which leverages Homomorphic Encryption (HE), has attracted attention as a promising approach to ensure the privacy of deep learning applications’ data. While recent studies have developed and evaluated the HE-based PPDL algorithms, the achieved performances, such as accuracy and latency, need improvement to make the applications practical. This work aims to improve the performance of the image classification of HE-based PPDL by combining two approaches — Channel-wise Homomorphic Encryption (CHE) and Batch Normalization (BN) with coefficient merging. Although these are commonly used schemes, their detailed algorithms and formulations have not been clearly described. The main contribution of the current study is to provide complete and reproducible descriptions of these schemes. We evaluate our CHE and BN implementation by targeting the Cheon-Kim-Kim-Song scheme as an HE scheme and Convolution Neural Network (CNN) as a machine learning scheme while using the MNIST and CIFAR-10 as the datasets. In addition, we compare the results with the five state-of-the-art neural network architectures. Our experiments demonstrate that the CHE can serve as a tool for empirically achieving shorter latency (the shortest 7.76 seconds) and higher accuracy (the highest 99.32%) compared with the previous studies that aimed to establish the classification of the encrypted MNIST data with CNN. Our approach can aid in designing a more robust and flexible PPDL.
The delay-time distribution of Type Ia supernovae from Sloan II

We derive the delay-time distribution (DTD) of Type Ia supernovae (SNe Ia) using a sample of 132 SNe Ia, discovered by the Sloan Digital Sky Survey II (SDSS2) among 66 000 galaxies with spectral-based star formation histories (SFHs). To recover the best-fitting DTD, the SFH of every individual galaxy is compared, using Poisson statistics, to the number of SNe that it hosted (zero or one), based on the method introduced in Maoz et al. This SN sample differs from the SDSS2 SN Ia sample analysed by Brandt et al., using a related, but different, DTD recovery method. Furthermore, we use a simulation-based SN detection-efficiency function, and we apply a number of important corrections to the galaxy SFHs and SN Ia visibility times. The DTD that we find has 4σ detections in all three of its time bins: prompt (τ 2.4 Gyr), indicating a continuous DTD, and it is among the most accurate and precise among recent DTD reconstructions. The best-fitting power-law form to the recovered DTD is t−1.07 ± 0.07, consistent with generic ∼t−1 predictions of SN Ia progenitor models based on the gravitational-wave-induced mergers of binary white dwarfs. The time-integrated number of SNe Ia per formed stellar mass is NSN/M = 0.00130 ± 0.00015 M⊙−1, or about 4 per cent of the stars formed with initial masses in the 3 - 8 M⊙ range. This is lower than, but largely consistent with, several recent DTD estimates based on SN rates in galaxy clusters and in local-volume galaxies, and is higher than, but consistent with NSN/M estimated by comparing volumetric SN Ia rates to cosmic SFH.
A Retrospective Case Series in Fournier’s Disease: And Its EmergencyManagement etGraftingTechnique forPenisCoverage

Department of Surgical Sciences, “Sapienza” University of Rome, Rome 00161, Italy Multidisciplinary Department of Medical-Surgical and Dental Specialties, University “Luigi Vanvitelli” Naples, Naples, Italy Department of Surgery and Biomedical Sciences, University of Perugia, Perugia, Italy Department of Urology, M.G. Vannini Hospital, Rome, Italy Plastic and Reconstructive Surgery Unit, Centre Hospitalier Universitaire Bichat Claude-Bernard, Paris, France
Does digitalization contribute to lesser income inequality? Evidence from G20 countries

ABSTRACT This study examines both the direct and moderating effects of digitalization on income inequality by using the panel data of Group of Twenty countries for 2002–2018. We find that digitalization alleviated income inequality and the interaction of digitalization with trade openness, and foreign direct investment helped narrow the income gap in the full sample, but the impact is heterogeneous by income level. The impact of digitalization on narrowing income gap has a greater effect on middle-income countries than on high-income countries. The interaction between digitalization and trade openness tends to widen the income inequality in high-income countries but has the opposite effect in middle-income countries. The interaction of digitalization with foreign direct investment has helped narrow income inequality in both high-income and middle-income countries. It implies that digitalization contributes to narrowing income inequality; there is a difference in the intensity of the digitalization effect between high-income and middle-income countries.
Effects of Ca substitution and the pseudogap on the magnetic properties of Y1-xCaxBa2Cu3O7-delta

The effects of planar hole content, p, on the static magnetic susceptibility, χ(T), of Y1-xCaxBa2Cu3O7-δ polycrystalline samples were investigated over a wide range of Ca (x) and oxygen contents. Non-magnetic Ca, in the 3p state, induces a Curie-like contribution to χ(T) that increases systematically and non-linearly with x but is almost independent of p. We argue that this arises from statistical clusters containing two or more nearest neighbor Ca atoms. We have again found that the pseudogap in the quasiparticle spectral weight appears abruptly below a planar hole content p = 0.190 ± 0.005. PACS numbers: 74.72. Bk, 74.25. Ha, 74.25. Dw, 74.62. Dh
The Role of Beta-Adrenergic Receptors in Depression and Resilience

Norepinephrine is a catecholamine neurotransmitter that has been extensively implicated in the neurobiology of major depressive disorder (MDD). An accumulating body of evidence indicates that investigations into the action of norepinephrine at the synaptic/receptor level hold high potential for a better understanding of MDD neuropathology and introduce possibilities for developing novel treatments for depression. In this review article, we discuss recent advances in depression neuropathology and the effects of antidepressant medications based on preclinical and clinical studies related to beta-adrenergic receptor subtypes. We also highlight a beta-3 adrenergic receptor-involved mechanism that promotes stress resilience, through which antidepressant efficacy is achieved in both rodent models for depression and patients with major depression—an alternative therapeutic strategy that is conceptually different from the typical therapeutic approach in which treatment efficacy is achieved by reversing pathological alterations rather than by enhancing a good mechanism such as natural resilience. Altogether, in this review, we systematically describe the role of beta-adrenergic receptors in depression and stress resilience and provide a new avenue for developing a conceptually innovative treatment for depression.
Least Squares Learning? Evidence from the Laboratory

We report on an experiment testing the empirical relevance of least squares (LS) learning, a common way of modelling how individuals learn a rational expectations equilibrium (REE). Subjects are endowed with the correct perceived law of motion (PLM) for a price level variable they are seeking to forecast, but do not know the true parameterization of that PLM. Instead, they must choose and can adjust the parameters of this PLM over 50 periods. Consistent with the E-stability of the REE in the model studied, 93.1% of subjects achieve convergence to the REE in terms of their price level predictions. However, only 20.3% of subjects can be characterized as least squares learners via the adjustments they make to the parameterization of the PLM over time. We also find that subjects’ parameter estimates are more accurate when there is greater variance in the independent variable of the model. We consider several alternatives to least squares learning and find evidence that many subjects employ a simple satisficing approach. JEL Classification: C53, C91, D83, D84
Onychomycosis in Two Populations with Different Socioeconomic Resources in an Urban Nucleus: A Cross-Sectional Study

Onychomycosis is one of the most common foot conditions. Mixed onychomycosis and onychomycosis caused by non-dermatophyte moulds are increasing in incidence, especially in vulnerable populations, hence the importance of this study, which presents the prevalence of onychomycosis in a population of homeless people, comparing the findings with a sample of a well-resourced population. The total sample consisted of 70 participants, divided into two separate groups, a homeless population and a second group in which we included people attending a private clinic. The average age of the sample is [49.19 ± 28.81] with an age range of 18 to 78 years. In the homeless group, the most prevalent infectious agents were non-dermatophyte fungi, with a total of 48%, compared to 28% in the group housed. The most common site of infection in both groups was the nail of the first finger. We, therefore, conclude that there is a difference in the infecting agent in the homeless population and the population with homes.
Teacher’s Challenges and Solutions in Teaching Speaking in Kampung Inggris

Teaching speaking English in not an easy thing to do. There are several challenges faced by teachers, especially in teaching speaking because in speaking there are several aspects that must be mastered, including pronunciation, vocabulary, fluency and grammar. The purposes of this study is to explain the findings of the challenges faced by teachers in teaching speaking in Kampung Inggris, the problems faced by students in learning speaking in Kampung Inggris, and the potential solutions used by the teacher in teaching speaking in Kampung Inggris. In the data collection method, the researcher used semi-structured interviews by taking four participant namely two teachers and two students in Kampung Inggris Kediri, East Java, Indonesia. The data is processed using thematic analysis. The results of the study found that there were four challenges face by teachers in teaching speaking English, namely: 1). Different student backgrounds, 2). Various student abilities, 3). Pressure from the institutions, 4). Students’ anxiety about their abilities. The researcher also found four problems faced by students in learning speaking in Kampung Inggris, namely: 1). Students’ anxiety about their abilities, 2). The relationship between teachers and students is not close, 3). Class selection is not age propriate, 4). Negative influence from the environment. In addition, the researcher identified 4 potential solutions for teachers in teaching English speaking in Kampung Inggris, namely: 1). Build a good relationship between teachers and students, 3). The teacher determines which teaching matrials are mastered by the teacher, 4). The teacher provides motivation to students. From these finding, the researcher suggests improving the wuality of teachers by updating the classroom management system, improving teaching methods, making appropriate teaching materials and evaluating the teaching and learning process. This is expected to be able to make the teaching and learning process more effective and conducive for both teachers and students. Keywords: Teaching English Speaking, Student Problems in Learning Speaking, Challenges and Solutions in Teaching Speaking, Kampung Inggris
Resting-State fMRI Whole Brain Network Function Plasticity Analysis in Attention Deficit Hyperactivity Disorder

Attention deficit hyperactivity disorder (ADHD) is a common mental disorder in children, which is related to inattention and hyperactivity. These symptoms are associated with abnormal interactions of brain networks. We used resting-state functional magnetic resonance imaging (rs-fMRI) based on the graph theory to explore the topology property changes of brain networks between an ADHD group and a normal group. The more refined AAL_1024 atlas was used to construct the functional networks with high nodal resolution, for detecting more subtle changes in brain regions and differences among groups. We compared altered topology properties of brain network between the groups from multilevel, mainly including modularity at mesolevel. Specifically, we analyzed the similarities and differences of module compositions between the two groups. The results found that the ADHD group showed stronger economic small-world network property, while the clustering coefficient was significantly lower than the normal group; the frontal and occipital lobes showed smaller node degree and global efficiency between disease statuses. The modularity results also showed that the module number of the ADHD group decreased, and the ADHD group had short-range overconnectivity within module and long-range underconnectivity between modules. Moreover, modules containing long-range connections between the frontal and occipital lobes disappeared, indicating that there was lack of top-down control information between the executive control region and the visual processing region in the ADHD group. Our results suggested that these abnormal regions were related to executive control and attention deficit of ADHD patients. These findings helped to better understand how brain function correlates with the ADHD symptoms and complement the fewer modularity elaboration of ADHD research.
A two-stage multi-attribute group consensus model based on distributed linguistic assessment information from the perspective of fairness concern

The consensus reaching process (CRP) is a key step in group decision-making (GDM), in which reaching a satisfactory consensus often requires certain costs, such as time, money, and effort. Moreover, benefits from the CRP are often compared among decision-makers, which raises fairness issues. Given these, this paper comprehensively considers these two factors in linguistic GDM modeling. Aiming at the problem of multi-attribute group decision-making (MAGDM) under distributed linguistic assessment (DLA) information, a two-stage group consensus model that considers psychological behaviors with fairness concern is proposed. Subsequently, the feasibility and effectiveness of the proposed model are illustrated by a case of selecting emergency material warehouses related to urban flood disasters. The main innovations and contributions of this paper are as follows. (a) The psychology of individual fairness concern is integrated into the MAGDM process with DLA information. (b) The DLA-based two-stage group consensus model, including the first-stage consensus model with maximum fairness satisfaction degree and the second-stage consensus model with minimum cost, is developed. Compared with the existing consensus models for distributed linguistic MAGDM, the proposed consensus model can not only improve the consensus level on the opinions with minimum cost but also promote the fairness satisfaction degree of decision-makers.
θ13: phenomenology, present status and prospect

The leptonic mixing angle θ13 is currently a high-priority topic in the field of neutrino physics, with five experiments under way, searching for neutrino oscillations induced by this angle. We review the phenomenology of θ13 and discuss the information from the present global oscillation data. A description of the upcoming reactor and accelerator experiments searching for a non-zero value of θ13 is given, and we evaluate the sensitivity reach within the next few years.
Evaluating Low-cost Networked Energy Metering Systems: A University Campus Study

In this paper we focus on analyzing the precision error of electrical parameters as well as the quality of the data transmission of measurements generated by low cost electric meter devices. The study is based on data collected in a large university campus which includes many non-linear electrical loads. Related harmonic distortions are identified as one possible source of measurement error. Also, we evaluate a quality of service proxy for the deployed data network and discuss design changes to robustify data transmission. After evaluating campus measurements using a standardized power quality analyzer we find that many meters presented high measurement errors and while some may be attributed to harmonics and large non-linear loads, other errors can be related to the transducers and the internal code used by the device. The need for open hardware is motivated throughout the study when discussing limitations of the system evaluated.
SCN1A polymorphisms influence the antiepileptic drugs responsiveness in Jordanian epileptic patients

Background The aim of this study was to evaluate whether the voltage-gated sodium channel alpha subunit 1 (SCN1A) gene polymorphisms influence the responsiveness of Jordanian epileptic patients to antiepileptic drugs (AEDs). Methods A total of 72 AEDs-treated epileptics were polymerase chain reaction (PCR)-genotyped for six single nucleotide polymorphisms (SNPs), including SCN1A rs2298771, rs3812718, rs3812719, rs2217199, rs2195144 and rs1972445. Genotype and allele distributions in drug-responsive and drug-resistant patients were compared. The six SNPs haplotypes were examined, and the linkage disequilibrium (LD) was assessed. Results The genotypes of drug-resistant and drug-responsive groups were in Hardy-Weinberg equilibrium. Three genetic polymorphisms of the SCN1A gene seemed to influence the resistance to AEDs, on the level of alleles and genotypes. Data revealed that rs2298771 G allele, rs3812719 C allele, and rs2195144 T allele increased the risk of developing AEDs-resistance (OR=2.9; 95%CI= 1.4-5.9, p=0.003; OR=2.4; 95%CI=1.2-4.7, p=0.01; OR=2.3; 95%CI=1.2-4.7, p=0.01), respectively. Haplo type analysis of SCN1A polymorphisms revealed high-degree LD associated with resistance to AEDs. A synergetic effect appears with highly significant association in GCCATG haplotype of rs2298771, rs3812718, rs3812719, rs2217199, rs2195144, and rs1972445 respectively (OR=2.8; 95%CI=1.5-6.2, p=0.002). Conclusions Data suggests that SCN1A polymorphisms could influence the resistance to AEDs in Jordanian epileptics at three SNPs (rs2298771; rs3812719; rs2195144). Additionally, haplotype analysis indicated a substantial degree of LD between the six SCN1A polymorphisms. Further investigation with larger sample size is needed to confirm the results of the current study.
Risk Factors for Retained Hemothorax after Trauma: A 10-Years Monocentric Experience from First Level Trauma Center in Italy

Thoracic trauma occurs in 20–25% of all trauma patients worldwide and represents the third cause of trauma-related mortality. Retained hemothorax (RH) is defined as a residual hematic pleural effusion larger than 500 mL after 72 h of treatment with a thoracic tube. The aim of this study is to investigate risk factors for the development of RH in thoracic trauma and predictors of surgery. A retrospective, observational, monocentric study was conducted in a Trauma Hub Hospital in Milan, recording thoracic trauma from January 2011 to December 2020. Pre-hospital peripheric oxygen saturation (SpO2) was significantly lower in the RH group (94% vs. 97%, p = 0.018). Multivariable logistic regression analysis identified, as independent predictors of RH, sternum fracture (OR 7.96, 95% CI 1.16–54.79; p = 0.035), pre-admission desaturation (OR 0.96; 95% CI 0.77–0.96; p = 0.009) and the number of thoracic tube maintenance days (OR 1.22; 95% CI 1.09–1.37; p = 0.0005). The number of tubes placed and the 1° rib fracture were both significantly associated with the necessity of surgical treatment of RH (2 vs. 1, p = 0.004; 40% vs. 0%; p = 0.001). The risk of developing an RH in thoracic trauma should not be underestimated. Variables related to RH must be taken into account in order to schedule a proper follow-up after trauma.
Hypervelocity A and B Stars Should Be Slow Rotators

The most commonly accepted explanation for the origin of hypervelocity stars in the halo of the Milky Way is that they are the result of tidal disruption of binaries by the massive black hole at the center of the Galaxy. We show that if this scenario is correct and if the original binary properties are similar to those in the local stellar neighborhood, then the hypervelocity stars should rotate with velocities measureably lower than those for field stars of similar spectral type. This may prove to be a more direct test of the model than trying to predict the position and velocity distributions.
Kynurenine Pathway of Tryptophan Metabolism Is Associated with Hospital Mortality in Patients with Acute Respiratory Distress Syndrome: A Prospective Cohort Study

Acute respiratory distress syndrome (ARDS) involves dysregulated immune-inflammatory responses, characterized by severe oxidative stress and high mortality. Metabolites modulating the inflammatory and immune responses may play a central role in the pathogenesis of ARDS. Most biogenic amines may induce the production of reactive oxygen species, oxidative stress, mitochondrial dysfunction, and programmed cell death. We conducted a prospective study on metabolic profiling specific to the amino acids and biogenic amines of 69 patients with ARDS. Overall, hospital mortality was 52.2%. Between day 1 and day 7 after ARDS onset, plasma kynurenine levels and the kynurenine/tryptophan ratio were significantly higher among non-survivors than in survivors (all p < 0.05). Urine metabolic profiling revealed a significantly higher prevalence of tryptophan degradation and higher concentrations of metabolites downstream of the kynurenine pathway among non-survivors than among survivors upon ARDS onset. Cox regression models revealed that plasma kynurenine levels and the plasma kynurenine/tryptophan ratio on day 1 were independently associated with hospital mortality. The activation of the kynurenine pathway was associated with mortality in patients with ARDS. Metabolic phenotypes and modulating metabolic perturbations of the kynurenine pathway could perhaps serve as prognostic markers or as a target for therapeutic interventions aimed at reducing oxidative stress and mortality in ARDS.
CORRELATING THE INTERSTELLAR MAGNETIC FIELD WITH PROTOSTELLAR JETS AND ITS SOURCES

This paper combines new CCD polarimetric data with previous information about protostellar objects in a search for correlations involving the interstellar magnetic field (ISMF). Specifically, we carried out an optical polarimetric study of a sample of 28 fields of 10′ × 10′ located in the neighborhood of protostellar jets and randomly spread over the Galaxy. The polarimetry of a large number of field stars is used to estimate both the average and dispersion of the ISMF direction in each region. The results of the applied statistical tests are as follows. Concerning the alignment between the jet direction and the ISMF, the whole sample does not show alignment. There is, however, a statistically significant alignment for objects of Classes 0 and I. Regarding the ISMF dispersion, our sample presents values slightly larger for regions containing T Tauri objects than for those harboring younger protostars. Moreover, the ISMF dispersion in regions containing high-mass objects tends to be larger than in those including only low-mass protostars. In our sample, the mean interstellar polarization as a function of the average interstellar extinction in a region reaches a maximum value around 3% for A(V) = 5, after which it decreases. Our data also show a clear correlation of the mean value of the interstellar polarization with the dispersion of the ISMF: the larger the dispersion, the smaller the polarization. Based on a comparison of our and previous results, we suggest that the dispersion in regions forming stars is larger than in quiescent regions.