Search Results (1,785)

In this paper, we propose a new method for three-dimensional (3D) visualization that proportionally estimates the number of photons in the background and the object under photon-starved conditions. Photon-counting integral imaging is one of the techniques for 3D image visualization under photon-starved conditions. However, conventional photon-counting integral imaging has the problem that a random noise is generated in the background of the image by estimating the same number of photons in entire areas of images. On the other hand, our proposed method reduces the random noise by estimating the proportional number of photons in the background and the object. In addition, the spatial overlaps have been applied to the space where photons overlap to obtain the enhanced 3D images. To demonstrate the feasibility of our proposed method, we conducted optical experiments and calculated the performance metrics such as normalized cross-correlation, peak signal-to-noise ratio (PSNR), and structural similarity index measure (SSIM). For SSIM of 3D visualization results by our proposed method and conventional method, our proposed method achieves about 3.42 times higher SSIM than conventional method. Therefore, our proposed method can obtain better 3D visualization of objects than conventional photon-counting integral imaging methods under photon-starved conditions. Full article

Traditional entropy source evaluation methods rely on statistical analysis and are hard to deploy on-chip or online. However, online detection of entropy source quality is necessary in some applications with high encryption levels. To address these issues, our experimental results demonstrate a significant negative correlation between minimum entropy values and prediction accuracy, with a Pearson correlation coefficient of −0.925 (p-value = 1.07 × 10⁻⁷). This finding offers a novel approach for assessing entropy source quality, achieving an accurate rate in predicting the next bit of a random sequence using neural networks. To further improve prediction capabilities, we also propose a novel deep learning architecture, Fast Fourier Transform-Attention Mechanism-Long Short-Term Memory Network (FFT-ATT-LSTM), that integrates a simplified soft attention mechanism with Fast Fourier Transform (FFT), enabling effective fusion of time-domain and frequency-domain features. The FFT-ATT-LSTM improves prediction accuracy by 4.46% and 8% over baseline networks when predicting random numbers. Additionally, FFT-ATT-LSTM maintains a compact parameter size of 33.90 KB, significantly smaller than Temporal Convolutional Networks (TCN) at 41.51 KB and Transformers at 61.51 KB, while retaining comparable prediction performance. This optimal balance between accuracy and resource efficiency makes FFT-ATT-LSTM suitable for online deployment, demonstrating considerable application potential. Full article

The Internet of Things produces vast amounts of data that require specialized algorithms in order to secure them. Lightweight cryptography requires ciphers designed to work on resource-constrained devices like sensors and smart things. A new encryption scheme is introduced based on a blend of the best-performing algorithms, SIMECK and TEA. A selection of software-oriented Addition–Rotation–XOR (ARX) block ciphers are augmented with a dynamic substitution security layer. The performance is compared against other lightweight approaches. The US National Institute of Standards and Technology (NIST) SP800-22 Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications and the German AIS.31 of the Federal Office for Information Security (BSI) are used to validate the output of the proposed encryption scheme. The law of iterated logarithm (LIL) for randomness is verified in all three forms. The total variance (TV), the Hellinger Distance (HD), and the root-mean-square deviation (RMSD) show values smaller than the required limit for 10.000 sequences of ciphertext. The performance evaluation is analyzed on a Raspberry PICO 2040. Several security metrics are compared against other ciphers, like χ2 and encryption quality (EQ). The results show that SIMECK-T is a powerful and fast, software-oriented, lightweight cryptography solution. Full article

Introduction: Obesity is an important risk factor for atrial fibrillation (AF) development. Data on cryoballoon ablation (CBA) outcomes in obese patients have so far been scarce. We reviewed the existing literature to compare the efficacy and safety of CBA in obese versus non-obese AF patients. Methods: A systematic literature search was conducted for studies comparing clinical outcomes (arrhythmia recurrence and/or procedural data and/or safety outcomes) between obese and non-obese patients undergoing CBA for AF. Statistical pooling was performed according to a random-effects model with generic inverse-variance weighting of relative risks (RRs) and standardised mean differences (SMDs) computing risk estimates with 95% confidence intervals (CIs). Results: Obese and non-obese patients had comparable arrhythmia recurrence rates (normal versus overweight, RR = 0.95, 95% CI: 0.82–1.11, p = 0.55, I²% = 91%; normal versus class I obesity, RR = 0.97, 95% CI: 0.82–1.13, p = 0.68, I²% = 87%; normal versus class II obesity, RR = 0.98, 95% CI: 0.91–1.07, p = 0.29, I²% = 65%). Procedure time was marginally increased in obese patients compared to non-obese counterparts (normal versus overweight, SMD = 0.05, 95% CI: −0.15–0.26, p = 0.62, I²% = 74%; normal versus class I obesity, SMD = 0.10, 95% CI: −0.00–0.19, p = 0.06, I²% = 2%; overweight versus class I obesity, SMD = 0.11, 95% CI: 0.01–0.21, p = 0.048, I²% = 25%). Regarding radiation exposure, fluoroscopy time was increased in patients with class I obesity compared to normal-weight or overweight patients and dose area product was also increased in obese patients compared to non-obese patients. Lastly, the risk of complications did not differ between obese and non-obese patients. Statistical heterogeneity and the small number of patients included are the main limitations of this study. Conclusion: CBA seems to be effective for obese patients suffering from AF, featuring also similar safety outcomes with non-obese individuals. Radiation exposure was increased in obese patients. Full article

Montbeliarde dairy cattle were introduced in Ecuador with the aim of ameliorating the production performance of other cattle breeds. The aim was to analyze the reproductive performance, demographic structure, inbreeding, and genetic diversity of Montbeliarde cattle obtained by absorption crossing. Official pedigree records from the Ecuadorian Montbeliarde Association were used. The total population was divided into seven populations: (i) historical (all individuals), (ii) 1999–2003, (iii) 2004–2008, (iv) 2009–2013, (v) 2014–2018, (vi) 2019–2023 (current), and (vii) reference (individuals with known parents). Demographic structure variables analyzed: pedigree completeness index (PCI), number of equivalents (GEqu), complete (GCom) and maximum (GMax) generations, and generation interval (GI). Inbreeding-derived variables analyzed: inbreeding (F), inbreeding increment (ΔF), average relatedness (AR), co-ancestry (C), non-random mating (α), effective population size (Ne), and genetic conservation index (GCI). Gene origin probability/genetic diversity variables analyzed: number of founders (f), effective number of founders (fe) and ancestors (fa), number of equivalent genomes (fg), fe/fa and fg/fa ratio, and DG losses. The databases were analyzed by ENDOG, POPREP, and CPC software. PCI in the historical population compared to the current population decreased from 72.95 to 65.87% (sire/dam pathway), while the GI decreased from 7.17 to 3.08 years when the historical and current populations were compared. Dam reproductive efficiency increased over time. Moreover, F = ~1%, AR = 2.06%, ΔF = 0.22%, C = 1.03%, α = −0.0077, GCI = 3.12, and Ne = 58 values were obtained. Gene origin probability in the reference population was f = 439, fa = 37, fe = 71.64, fg = 23.43, and fg/fe = 0.33, showing a GD loss due to unequal contribution of founders (0.55%) and bottleneck and genetic drift (4.25%). In conclusion, the Ecuadorian Montbeliarde cattle population displayed a relatively low diversity and high genetic relationship. Inbreeding levels increased while Ne values decreased over time. The introduction of new purebred bloodlines could be important to minimize the inbreeding levels ensuring the long-term conservation of this breed and minimizing GD loss. Full article

The super-sized pore-throat network model can reflect both microscopic pore characteristics and macroscopic heterogeneity and is excellent in describing cross-scale flow fields. At present, there is no algorithm that can generate a micro pore-throat network model at a macro reservoir scale. This study examines algorithms for super-sized pore-throat network reconstruction using actual core sample data. It conducts a random simulation of mineral growth and dissolution under the constraints of four microscopic pore structure parameters: porosity, coordination number, pore radius, and throat radius. This approach achieves high-precision, super-sized, and regional pore-throat network modeling. Comparative analysis shows that these four parameters effectively guide the random growth process of super-sized pore-throat networks. The overall similarity between the generated pore-throat network model and real core samples is 88.7% on average. In addition, the algorithm can partition and control the generation of pore-throat networks according to sedimentary facies. The 100-megapixel model with 85,000 pores was generated in 455.9 s. This method can generate cross-scale models and provides a basis for cross-scale modeling in physical simulation experiments and numerical simulations. Full article

The .NET framework is widely used for software development, making it a target for a significant number of malware attacks by developing malicious executables. Previous studies on malware detection often relied on developing generic detection methods for Windows malware that were not tailored to the unique characteristics of .NET executables. As a result, there remains a significant knowledge gap regarding the development of effective detection methods tailored to .NET malware. This work introduces a novel framework for detecting malicious .NET executables using statically extracted method names. To address the lack of datasets focused exclusively on .NET malware, a new dataset consisting of both malicious and benign .NET executable features was created. Our approach involves decompiling .NET executables, parsing the resulting code, and extracting standard .NET method names. Subsequently, feature selection techniques were applied to filter out less relevant method names. The performance of six machine learning models—XGBoost, random forest, K-nearest neighbor (KNN), support vector machine (SVM), logistic regression, and naïve Bayes—was compared. The results indicate that XGBoost outperforms the other models, achieving an accuracy of 96.16% and an F1-score of 96.15%. The experimental results show that standard .NET method names are reliable features for detecting .NET malware. Full article

Next- generation wireless communications are projected to integrate reconfigurable intelligent surfaces (RISs) to perpetrate enhanced spectral and energy efficiencies. To quantify the performance of RIS-aided wireless networks, the statistics of a single random variable plus the sum of double random variables becomes a core approach to reflect how communication links from RISs improve wireless-based systems versus direct ones. With this in mind, the work applies the statistics of a single random variable plus the sum of double random variables in the secure performance of RIS-based non-orthogonal multi-access (NOMA) systems with the presence of untrusted users. We propose a new communication strategy by jointly considering NOMA encoding and RIS’s phase shift design to enhance the communication of legitimate nodes while degrading the channel capacity of untrusted elements but with sufficient power resources for signal recovery. Following that, we analyze and derive the closed-form expressions of the secrecy effective capacity (SEC) and secrecy outage probability (SOP). All analyses are supported by extensive Monte Carlo simulation outcomes, which facilitate an understanding of system communication behavior, such as the transmit signal-to-noise ratio, the number of RIS elements, the power allocation coefficients, the target data rate of the communication channels, and secure data rate. Finally, the results demonstrate that our proposed communication can be improved significantly with an increase in the number of RIS elements, irrespective of the presence of untrusted proximate or distant users. Full article

Numerous studies on the number pi ($\pi$) explore its properties, including normality and applicability. This research, grounded in two hypotheses, proposes and proves a theorem that employs a Bernoulli experiment to demonstrate the high probability of encountering any finite bit string within a sequence of consecutive bits in the decimal part of $\pi$. This aligns with findings related to its normality. To support the hypotheses, we present experimental evidence about the equiprobable and independent properties of bits of $\pi$, analyzing their distribution, and measuring correlations between bit strings. Additionally, from a cryptographic perspective, we evaluate the chaotic properties of two images generated using bits of $\pi$. These properties are evaluated similarly to those of encrypted images, using measures of correlation and entropy, along with two hypothesis tests to confirm the uniform distribution of bits and the absence of periodic patterns. Unlike previous works that solely examine the presence of sequences, this study provides, as a corollary, a formula to calculate an upper bound N. This bound represents the length of the sequence from $\pi$ required to ensure the location of any n-bit string at least once, with an adjustable probability p that can be set arbitrarily close to one. To validate the formula, we identify sequences of up to $n=$ 40 consecutive zeros and ones within the first N bits of $\pi$. This work has potential applications in Cryptography that use the number $\pi$ for random sequence generation, offering insights into the number of bits of $\pi$ required to ensure good randomness properties. Full article

Background/Objectives: Diet composition is important for health, especially during critical periods such as pre-gestation (P), gestation (G), or lactation (S), due to its potential impact not only on the mother but on the offspring. The Mediterranean diet includes many healthy foods rich in fiber and/or polyphenols, such as whole grains, fruits, vegetables, beans, and nuts. The present preclinical study assesses the impact of a diet rich in fiber and polyphenols (HFP diet) during one of those three periods (P, G, or S, three weeks each) on the rat gene expression of the small intestine obtained at the end of the lactation period. Methods: This analysis was performed by the mRNA two step PCR amplification by random primers and poly-T, followed by library generation and HiSeq X-Ten Illumina sequencing (Seqplexing), and further confirmed by Real time PCR and ELISA. Results: The results showed a broad number of genes significantly modulated after the HFP diet compared to the reference diet, with a higher number of genes modulated when the supplementing period was closer to the analysis day (S > G > P). Notably, genes involved in immune signaling, intestinal absorption, and cell growth were among those more significantly affected by the HFP dietary intervention. The HFP diet influenced the expression of key genes such as ferritin, fatty acid synthase, apelin, and complement proteins, among others. There was a unique gene modified in all the intervention periods (Family with Sequence Similarity 117 Member A, Fam117A, which codifies a protein with unknown function), indicating that this molecule may participate critically in the effects induced by fiber and polyphenols during these periods. Conclusions: Overall, in rats, the influence of diet for a three-week period around birth is able to modulate the intestinal gene expression, and consequently, maternal health, which can eventually have an indirect impact on the offspring. Full article

High-speed rail (HSR) environments present unique challenges due to their high mobility and dense passenger traffic, resulting in dynamic and unpredictable task generation patterns. Mobile Edge Computing (MEC) has emerged as a transformative paradigm to address these challenges by deploying computation resources closer to end-users. However, the limited resources of MEC servers necessitate efficient task partitioning, wherein a single task is divided into multiple sub-tasks for parallel processing across MEC servers. In the context of HSR environments, the task partitioning ratio is pivotal in ensuring quality of service (QoS) and optimizing resource utilization, particularly under dynamic and high-demand conditions. This paper proposes a deep reinforcement learning (DRL)-based task partitioning mechanism using Twin Delayed Deep Deterministic Policy Gradient (TD3) for HSR environments with MEC servers (MECSs). The proposed method dynamically adjusts task partitioning ratios by leveraging real-time information about task characteristics and server load conditions. The experimental results show that when the task arrival rate is 20, the delay is improved by about 5% compared to random and about 13% compared to no_partition. When it is 50, there is no significant difference from random and about 2% improvement compared to no_partition. The task throughput is almost the same when it is 20. However, when it is 50, random is much better. We also looked at the performance change according to the number of serving MECSs. In this process, we can also note the research direction of finding an appropriate number of serving MECSs K. The results highlight the efficacy of DRL-based approaches in dynamically adapting to the unique characteristics of HSR environments, achieving optimal resource allocation and maintaining high QoS. This paper contributes to advancing task partitioning strategies for HSR systems and lays the groundwork for future research in MEC-based HSR systems. Full article

With the increasing importance of securing images during network transmission, this paper introduces a novel image encryption algorithm that integrates a 3D chaotic system with V-shaped scrambling techniques. The proposed method begins by constructing a unique 3D chaotic system to generate chaotic sequences for encryption. These sequences determine a random starting point for V-shaped scrambling, which facilitates the transformation of image pixels into quaternary numbers. Subsequently, four innovative bit-level scrambling strategies are employed to enhance encryption strength. To further improve randomness, DNA encoding is applied to both the image and chaotic sequences, with chaotic sequences directing crossover and DNA operations. Ciphertext feedback is then utilized to propagate changes across the image, ensuring increased complexity and security. Extensive simulation experiments validate the algorithm’s robust encryption performance for grayscale images, yielding uniformly distributed histograms, near-zero correlation values, and an information entropy value of 7.9975, approaching the ideal threshold. The algorithm also features a large key space, providing robust protection against brute force attacks while effectively resisting statistical, differential, noise, and cropping attacks. These results affirm the algorithm’s reliability and security for image communication and transmission. Full article

We consider two specific families of binomial trees and forests: simply generated binomial d-ary trees and forests versus their increasing phylogenetic version, with tree nodes in increasing order from the root to any of its leaves. The analysis (both pre-asymptotic and asymptotic) consists of some of the main statistical features of their total progenies. We take advantage of the fact that the random distribution of those trees are obtained while weighting the counts of the underlying combinatorial trees. We finally briefly stress a rich alternative randomization of combinatorial trees and forests, based on the ratio of favorable count outcomes to the total number of possible ones. Full article

Intelligent precision agriculture incorporates a number of Internet of Things (IoT) devices and drones to supervise agricultural activities and surroundings. The collected data are then forwarded to processing centers to facilitate crucial decisions. This can potentially help optimize the usage of agricultural resources and thwart disasters, enhancing productivity and profitability. To facilitate monitoring and decision, the smart devices in precision agriculture must exchange massive amounts of data across the open wireless communication channels. This inadvertently introduces a number of vulnerabilities, exposing the collected data to numerous security and privacy threats. To address these issues, massive security solutions have been introduced to secure the communication process in precision agriculture. However, most of the current security solutions either fail to offer perfect protection or are inefficient. In this paper, a scheme deploying efficient cryptographic primitives such as hashing, exclusive OR and random number generators is presented. We utilize the Burrows–Abadi–Needham (BAN) logic to demonstrate the verifiable security of the negotiated session keys. In addition, we execute an extensive semantic analysis which reveals the robustness of our scheme against a myriad of threats. Moreover, comparative performance evaluations demonstrate its computation overheads and energy consumption efficiency. Full article

Background/Objective: Throat packs are widely used during orofacial surgery to reduce the frequency of postoperative nausea and vomiting (PONV). However, evidence supporting their use is mixed, with associated risks such as postoperative sore throat and the possibility of being forgotten in situ. Methods: The aim of this study is to evaluate the effectiveness of throat packs in preventing PONV and postoperative sore throat during dental treatments under general anesthesia in children with special healthcare needs (SHCNs). Eighty children with SHCNs were randomized into two groups: throat packing (Group TP, n = 41) and no throat packing (Group n-TP, n = 39). A throat pack was used in Group TP, and PONV and sore throat were evaluated at 1, 2, and 4 h postoperatively. Statistical Package for Social Sciences (SPSS) version 23.0 was used for data analysis. The registration number at ClinicalTrials.gov is NCT06169306, registered on 28 December 2023. Results: Patients in Group n-TP showed significantly higher PONV values at 1 and 2 h postoperatively (p < 0.001, p = 0.019, respectively). Visual Analog Scale (VAS) values were also significantly higher in Group TP at 1 and 2 h postoperatively (p < 0.001, p = 0.002, respectively). Conclusions: Using throat packs in dental treatments under general anesthesia for children with SHCNs reduced the incidence of PONV but increased the incidence of postoperative sore throat. Full article