Miracle-dz/UniFAR-FTUs huggingface dataset:
Gratitude to God: A Unique Construct Adding to Our Understanding of Religiousness and Gratitude

In two national samples in the United States, we aimed to determine the extent to which GTG is distinct from both general gratitude and general religiousness, using statistical methods to determine (1) if GTG shows patterns of association with other variables distinct from general gratitude and religiousness, and (2) whether GTG predicts wellbeing above and beyond both general gratitude and religiousness. Online studies were conducted with 267 (Study 1) and 184 (Study 2) adults. Results across the two studies were consistent in demonstrating that GTG shows associations with relevant constructs that are distinct from both general religiousness and general gratitude. Further, GTG independently predicted aspects of psychological wellbeing, although findings were not consistent across all aspects. These findings indicate GTG is a unique construct warranting future research.
Adaptive Distributed CRC-aided SCL Decoder with Flip Operations for Polar Codes

Polar codes are used for image transmission due to unequal error protection. Meanwhile, a low-complexity polar code decoder helps to reduce the energy loss during polar code decoding. Therefore, this paper proposes a new decoder with low complexity, called adaptive distributed cyclic-redundancy-checkaided successive cancellation list decoder with flip operations (ADD-SCLF). By combining the adaptive scheme and the distributed cyclic redundancy check (CRC) bit scheme, the decoder can find the correct path with lower average computational complexity and end the failed decoding process earlier simultaneously. Simulation results show that our ADD-SCLF decoder can reduce the computational complexity by up to 17.16% compared to the current adaptive ordered shifted-pruning list (ADOSPL) decoder.
Poly(methyl methacrylate)–palladium clusters nanocomposite formation by supersonic cluster beam deposition: a method for microstructured metallization of polymer surfaces

Nanocomposite films were fabricated by supersonic cluster beam deposition (SCBD) of palladium clusters on poly(methyl methacrylate) (PMMA) surfaces. The evolution of the electrical conductance with cluster coverage and microscopy analysis show that Pd clusters are implanted in the polymer and form a continuous layer extending for several tens of nanometres beneath the polymer surface. This allows the deposition, using stencil masks, of cluster-assembled Pd microstructures on PMMA showing a remarkably high adhesion compared with metallic films obtained by thermal evaporation. These results suggest that SCBD is a promising tool for the fabrication of metallic microstructures on flexible polymeric substrates.
Topological types of Pfaffian manifolds

Abstract Let Ω = (ω1,…,ω n-k ) be differential 1-forms with polynomial coefficients in R n . A Pfaffian manifold of Ω is by definition a maximal integral k-manifold of Ω. It is shown that the number of homeomorphism classes of all Pfaffian manifolds of Rolle Type of Ω is finite and, moreover, bounded by a computable function in variables n, k and the degree of ω 1,…, ω n-k . Finiteness is proved also in any o-minimal structure. We give also an example of a semi-algebraic C 1 differential form on a semi-algebraic C2 3-manifold whose Pfaffian manifolds have homeomorphism classes of the cardinality of continuum. Hence the cardinality of all manifolds is the continuum (not countable).
Robust Nonnegative Matrix Factorization Based Background Reconstruction for Hyperspectral Image Anomaly Detection

In the anomaly detection of hyperspectral images (HSIs), aiming at the difficulty of distinguishing the abnormal target from the background and the low accuracy of background prediction, a new HSI anomaly detection approach based on robust nonnegative matrix factorization(NMF) background reconstruction is proposed. In this approach, a more robust new form objective function is introduced into the NMF process to improve the adaptability to noise and outliers, and a new background reconstruction objective function can be obtained. However, the new objective function is non-convex. The global optimal solution of one variable can be obtained when the other is fixed. Thus, we propose an efficient multiplicative updating algorithm with the theory of the iterative reweighted least squares. Finally, when iterative convergences, we can obtain the extracted endmembers and estimated abundances to reconstruct the background. Then, the reconstructed background image was subtracted from the origin image to obtain the residual image. Finally, the anomaly detection is achieved by using the local anomaly detector to traverse the residual image. Furthermore, the effectiveness of the HSI anomaly detection algorithm proposed based on robust NMF background reconstruction is illustrated in a series of real-world data experiments.
Objectively Measured Physical Activity Is Lower in Individuals with Normal Weight Obesity in the United States

The role of physical activity in normal weight obesity (NWO), which is associated with increased cardiometabolic risk, is not clear. This study aimed to determine body composition phenotype-specific differences in objectively measured physical activity and sedentary time in adults in the United States. A total of 2055 adults with a body mass index (BMI) ≥ 18.5 m2 were studied using 2003–2006 National Health and Nutrition Examination Surveys. Physical activity and percent body fat (BF%) were measured using accelerometer and dual-energy X-ray absorptiometry, respectively. A BF% > 23.1% and >33.3% for men and women, respectively, was considered excess. A BMI of 18.5–24.9 kg/m2 with excess BF% was defined as NWO, while those with normal BF%, as normal weight lean (NWL). A BMI of ≥25 kg/m2 with excess BF% was considered overweight/obesity (OB). Compared to NWL, moderate to vigorous physical activity was significantly lower by 8.3 min (95% confidence interval/CI = −15.20, −1.40) and 10.18 min (95% CI = −14.83, −5.54) per day in NWO and OB, respectively. Low-intensity physical activity was also significantly lower by 17.71 min (95% CI = −30.61, −4.81) per day in NWO compared to NWL. However, sedentary time was not different. Objectively measured physical activity is significantly lower in NWO compared to NWL, while sedentary time is not.
Communication Optimization of Body Sensor Network Based on Evolutionary Multi-objective Cooperative Game

To address the conflict problem between data volume, bandwidth consumption and energy consumption in the cloud computing based body sensor networks, a scheme using evolutionary multi-objective cooperative game is proposed. First, a game model of data volume, bandwidth consumption and energy consumption is built. Then, the payoff function is constructed to carry out the coalition cooperative game so as to reach equilibrium of all objects. Furthermore, the elite retention mechanism is adopted to increase convergence speed, and the Levy flight is introduced to avoid trapping into local optimal. Experiments showed that the proposed algorithm could effectively reach equilibrium of the three targets. Moreover, compared with Multi-objective Evolutionary Algorithm and Non-cooperative Game Algorithm, it had better performance in convergence speed, distribution and diversity of solutions.
Getting the privacy calculus right: Analyzing the relations between privacy concerns, expected benefits, and self-disclosure using response surface analysis

Rational models of privacy self-management such as privacy calculus assume that sharing personal information online can be explained by individuals’ perceptions of risks and benefits. Previous research tested this assumption by conducting conventional multivariate procedures, including path analysis or structural equation modeling. However, these analytical approaches cannot account for the potential conjoint effects of risk and benefit perceptions. In this paper, we use a novel analytical approach called polynomial regressions with response surface analysis (RSA) to investigate potential non-linear and conjoint effects based on three data sets (N1 = 344, N2 = 561, N3 = 1.131). In all three datasets, we find that people self-disclose more when gratifications exceed concerns. In two datasets, we also find that self-disclosure increases when both risk and benefit perceptions are on higher rather than lower levels, suggesting that gratifications play an important role in determining whether and how risk considerations will factor into the decision to disclose information.
CryptoSolve: Towards a Tool for the Symbolic Analysis of Cryptographic Algorithms

Recently, interest has been emerging in the application of symbolic techniques to the specification and analysis of cryptosystems. These techniques, when accompanied by suitable proofs of soundness/completeness, can be used both to identify insecure cryptosystems and prove sound ones secure. But although a number of such symbolic algorithms have been developed and implemented, they remain scattered throughout the literature. In this paper, we present a tool, CryptoSolve, which provides a common basis for specification and implementation of these algorithms, CryptoSolve includes libraries that provide the term algebras used to express symbolic cryptographic systems, as well as implementations of useful algorithms, such as unification and variant generation. In its current initial iteration, it features several algorithms for the generation and analysis of cryptographic modes of operation, which allow one to use block ciphers to encrypt messages more than one block long. The goal of our work is to continue expanding the tool in order to consider additional cryptosystems and security questions, as well as extend the symbolic libraries to increase their applicability.
A Proposed Model for Card Fraud Detection Based on CatBoost and Deep Neural Network

The rapid development of technology has digitized customer payment behavior towards a cashless society. To a certain extent, this has created a feast for miscreants to commit fraud. According to Nilson (2020), global fraud loss is projected to reach over $\$ $ 35 billion by 2025. Consequently, the need for a novel method to prevent this menace is undisputed. This research was conducted on the IEEE-CIS Fraud Detection Dataset provided by Vesta Corporation. Based on the logic of labeling for converting the entire account to “Fraud=1” once the credit card has fraud, we navigate the research process towards predicting fraudulent credit cards rather than fraudulent transactions. The key idea behind the proposed model is user separation, in which we divide users into old and new people before applying CatBoost and Deep Neural Network to each category, respectively. In addition, a variety of techniques to improve detection accuracy, namely handling heavily imbalanced datasets, feature transformation, and feature engineering, are also presented in detail in this paper. The experimental results showed that our model performed well, as we obtained AUC scores of 0.97 (CatBoost) and 0.84 (Deep Neural Network).
Sensor Fusion for Occupancy Estimation: A Study Using Multiple Lecture Rooms in a Complex Building

This paper uses various machine learning methods which explore the combination of multiple sensors for quality improvement. It is known that a reliable occupancy estimation can help in many different cases and applications. For the containment of the SARS-CoV-2 virus, in particular, room occupancy is a major factor. The estimation can benefit visitor management systems in real time, but can also be predictive of room reservation strategies. By using different terminal and non-terminal sensors in different premises of varying sizes, this paper aims to estimate room occupancy. In the process, the proposed models are trained with different combinations of rooms in training and testing datasets to examine distinctions in the infrastructure of the considered building. The results indicate that the estimation benefits from a combination of different sensors. Additionally, it is found that a model should be trained with data from every room in a building and cannot be transferred to other rooms.
Six Characters in Search of a Security Problem: Pirandellian Masks for Security Ceremonies

For the Italian play-writer and 1934 Nobel-Prize winner Luigi Pirandello, a fictional mask is either self-imposed or, in most cases, forced on by society, being what makes life possible. Drawing from that, we believe that due to the non-deterministic nature of the human being, the only way to specify and verify human-tailored security protocols (known as security ceremonies) is by the specification of masks that users wear in order to interact with ceremonies. In the current paper, we review further this literary inspiration and propose six possible masks: the Attentive, the Naive, the Careless, the Fearful, the Busy, and the Elder. We then discuss an example of how we can reason about security involving human beings, and present what still needs to be done.
Ensinando desenvolvimento de sistemas de informação baseado na web: um relato de experiência

O objetivo deste trabalho é relatar uma experiência de ensino na qual alunos de graduação participaram de um treinamento sobre o desenvolvimento de um sistema de informação web. O treinamento consistiu de videoaulas e reuniões regulares por um mês. Os resultados foram coletados por meio de questionário e entrevista narrativa episódica, visando analisar qualitativamente a experiência. Como resultado, percebeu-se a importância de um treinamento mais longo, especialmente consolidando conhecimentos teóricos para fundamentar uma abordagem educacional com viés mais prático, para efetivamente alcançar proficiência técnica para desenvolvimento de sistemas web.
An Enhanced Indoor Positioning Solution Using Dynamic Radio Fingerprinting Spatial Context Recognition

Radio fingerprinting positioning is widely used for smartphone location-based services and Internet of Things applications given its high availability and low cost. Radio fingerprinting-based algorithms, however, are subject to the forced matching problem and often yield estimated positions even when a user is actually located outside of the fingerprint region. A positioning solution in multistory buildings should be able to locate positions accurately on the current floor; but these methods may generate unreasonable positioning trajectories, such as irrationally passing through a wall, when fingerprinting positioning is fused the with inertial measurement unit to further improve the accuracy. A radio map must be surveyed dynamically on-the-move, as a dynamic fingerprint, to reduce the time costs and on-site workload. Unlike static fingerprint-based methods, dynamic fingerprinting samples are sparse. Thus, we propose an enhanced indoor positioning solution using spatial context knowledge, extracted from the sparse dynamic fingerprints. In the offline stage of radio map calculation, we extract the dynamic fingerprint features and store them in a spatial features database to reduce the computational time and storage space complexity. The proposed floor detection, region recognition, and path correction algorithms identify the online spatial contexts from the stored spatial features to improve positioning performance. This solution was applied on smartphones combining WiFi and Bluetooth low-energy radio signals in two typical scenarios. The experimental results show that the floor detection accuracy reached 99% while region recognition accuracy reached 90.75%. The positioning path correction method enhances the accuracy of smartphone indoor positioning from 3.27 to 2.56 m.
Plasma Kallikrein-Activated TGF-β Is Prognostic for Poor Overall Survival in Patients with Pancreatic Ductal Adenocarcinoma and Associates with Increased Fibrogenesis

Pancreatic ductal adenocarcinoma (PDAC) is a hard-to-treat cancer due to the collagen-rich (fibrotic) and immune-suppressed microenvironment. A major driver of this phenomenon is transforming growth factor beta (TGF-β). TGF-β is produced in an inactive complex with a latency-associated protein (LAP) that can be cleaved by plasma kallikrein (PLK), hereby releasing active TGF-β. The aim of this study was to evaluate LAP cleaved by PLK as a non-invasive biomarker for PDAC and tumor fibrosis. An ELISA was developed for the quantification of PLK-cleaved LAP-TGF-β in the serum of 34 patients with PDAC (stage 1–4) and 20 healthy individuals. Biomarker levels were correlated with overall survival (OS) and compared to serum type III collagen (PRO-C3) and type VI collagen (PRO-C6) pro-peptides. PLK-cleaved LAP-TGF-β was higher in patients with PDAC compared to healthy individuals (p < 0.0001). High levels (>median) of PLK-cleaved LAP-TGF-β were associated with poor OS in patients with PDAC independent of age and stage (HR 2.57, 95% CI: 1.22–5.44, p = 0.0135). High levels of PLK-cleaved LAP-TGF-β were associated with high PRO-C3 and PRO-C6, indicating a relationship between the PLK-cleaved LAP-TGF-β fragment, TGF-β activity, and tumor fibrosis. If these preliminary results are validated, circulating PLK-cleaved LAP-TGF-β may be a biomarker for future clinical trials.
Evaluation of Physiological State of Pen Shell Pinna nobilis (Linnaeus, 1758) by a Non-Invasive Heart Rate Recording under Short-Term Hyposalinity Test

A non-invasive laser fiber-optic method based on infrared sensors for heart rate (Hr) recording was applied to assess the physiological condition of Pinna nobilis. During 2017, the specimens of P. nobilis were sampled at three sites within the Boka Kotorska Bay, Montenegro and used for ex situ experiments with short-term reduction/restoration of ambient salinity to evaluate their physiological adaptive capacity based on heart rate recovery time (Trec). Mean Trec for specimens from Sv. Nedjelja (reference site), Dobrota and Sv. Stasije were 72 ± 3, 91 ± 7 and 117 ± 15 min, while the coefficients of variation (CV) were 0.12, 0.13 and 0.17, respectively. Resting heart rate (Hrrest) and Trec showed statistically significant differences between the groups of mussels from Dobrota and Sv. Stasije in comparison to the reference site. Statistically significant correlations were observed between Trec and shell length/width, which was not the case in comparison between Hrrest and shell length/width. The lower adaptive capacity within the P. nobilis specimens from Dobrota and Sv. Stasije in comparison to the reference site could occur due to stress induced by deterioration of environmental conditions, which could have led to impairment of the physiological state of the mussels evaluated by Hr. All the specimens of P. nobilis survived the experimental treatments; afterwards, they were successfully transplanted at the Dobrota site. The experimental unit with sensor technology applied in this study can provide Hr recording in real time and could have an application in monitoring the physiological/health state of P. nobilis individuals maintained in aquaria.
The Structure of Bipartite Quantum States - Insights from Group Theory and Cryptography

This thesis presents a study of the structure of bipartite quantum states. In the first part, the representation theory of the unitary and symmetric groups is used to analyse the spectra of quantum states. In particular, it is shown how to derive a one-to-one relation between the spectra of a bipartite quantum state and its reduced states, and the Kronecker coefficients of the symmetric group. In the second part, the focus lies on the entanglement of bipartite quantum states. Drawing on an analogy between entanglement distillation and secret-key agreement in classical cryptography, a new entanglement measure, `squashed entanglement', is introduced.
SLUG: A new way to Stochastically Light Up Galaxies

We present SLUG, a new code to "Stochastically Light Up Galaxies". SLUG populates star clusters by randomly drawing stars from an initial mass function (IMF) and then following their time evolution with stellar models and an observationally-motivated prescription for cluster disruption. For a choice of star formation history, metallicity, and IMF, SLUG outputs synthetic photometry for clusters and field stars with a proper treatment of stochastic star formation. SLUG generates realistic distributions of star clusters, demonstrating the range of properties that result from finite sampling of an IMF and a random distribution of ages. The simulated data sets provide a quantitative means to address open problems in studies of star formation in galaxies and clusters, such as a test for IMF variations that are suggested by the systematic deficiency in the H-alpha/UV ratio in outer disks or in dwarf galaxies. SLUG will be made publicly available through the website this http URL
Dietary Effects of Introducing Salt-Reduced Bread with and without Dietary Counselling—A Cluster Randomized Controlled Trial

Successful strategies for policy makers and the food industry are required to reduce population salt intake. A 4-month cluster randomized controlled trial was conducted to evaluate whether the provision of salt-reduced bread with or without dietary counselling affected the dietary intake of selected food groups, energy, macronutrients, sodium, and potassium. Eighty-nine families (n = 309) consisting of minimum one parent and one child were assigned to receive bread gradually reduced in salt content alone (Intervention A), combined with dietary counselling (Intervention B), or bread with regular salt content (control). Food intake was recorded for seven consecutive days at baseline and follow-up. Salt intake was reduced in both Intervention A (−1.0 g salt/10 MJ, p = 0.027) and Intervention B (−1.0 g salt/10 MJ, p = 0.026) compared to the control. Consumption of bread and both total and salt-rich bread fillings remained similar between groups, while ‘cheese and cheese products’ were reduced in Intervention A (−38%, p = 0.011). Energy intake and macronutrient distribution were not affected in Intervention A, but Intervention B resulted in a higher energy intake (512 kJ, p = 0.019) and a lower energy % (E%) from saturated fat (−1.0 E%, p = 0.031) compared to the control. In conclusion, provision of salt-reduced bread both with and without dietary counselling successfully reduced dietary salt intake without adversely affecting the dietary nutritional quality.