Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of Locally-Clocked Asynchronous Finite State Machines with no Memory Elements

Synchronous Finite State Machine (FSM) controllers are extensively employed in the design of control units for complex digital systems. These systems can be realized on Field Programmable Gate Arrays (FPGAs), but they often face challenges associated with the global clock signal, such as clock skew and increased power consumption. In this context, the asynchronous paradigm offers intriguing characteristics that can serve as an alternative for design. However, Asynchronous FSMs implemented on the FPGA platform are highly susceptible to essential hazards arising from significant delays between logical blocks. One effective solution to mitigate hazards is the insertion of delay elements into the feedback of Asynchronous FSMs, which can be a challenging task on the FPGA platform. This article presents a novel architecture and approach for the synthesis of locally-clock Asynchronous FSMs that are free from essential hazards. The proposed locally-clock Asynchronous FSMs are described using the Extended BurstMode (XBM) specification. Unlike existing local clock architectures in the literature that employ latches or flip-flops to store states, our architecture is based on Huffman’s architecture, utilizing feedback combinational functions. Through a comparative analysis with existing locally-clock Asynchronous FSMs in the literature, our approach demonstrates the potential for achieving superior cycle time and latency performance.
The Influence of the Input Array on the Learning Error of a Multilayer Neural Network

For a multilayer neural network (MLNN) with three hidden layers, the influence of the input array size on the learning process was studied when recognizing printed digits. A study was conducted both with and without the use of optimization training methods such as AMSGrad, and AdaDelta. The learning error of this neural network was analyzed using the Fourier spectra of the error function and constructing branching diagrams when analyzing the logistic function that describes the doubling of existing local minima. The Fourier spectra were found to indicate a more significant number of harmonics in the training process for arrays with smaller dimensions. Increasing the input array size for representing the digits $(\mathbf{3}\times \mathbf{5},\ \mathbf{4}\times \mathbf{7},\ \mathbf{28}\times \mathbf{28}$ pixels) leads to more homogeneous learning process. It is demonstrated that the existence of error function harmonics throughout the range of learning parameter variations, given a fixed learning rate, is associated with the heterogeneity of the input array. In other words, the heterogeneity of the input array provokes the emergence of local minima and, consequently, the more complex behavior of the error function for the learning parameters. Therefore, the heterogeneity of the input array, under the condition of a fixed learning rate, acts as a catalyst for the neural network retraining process.
Nutritional, Productive, and Qualitative Characteristics of European Quails Fed with Diets Containing Lipid Sources of Plant and Animal Origin

Simple Summary This study focused on evaluating the impact of different alternative lipid sources in the diet of meat quails. The researchers investigated nutrient metabolism, performance, carcass characteristics, and meat quality. Two experiments were conducted, the first of which analyzed the energy values and metabolizability of various lipid sources. Surprisingly, no significant differences were observed in energy values and metabolizability among the different lipid sources. However, variations were found in the metabolizability of crude protein and ether extract. Based on these findings, the second experiment assessed performance, carcass characteristics, and meat quality. Notably, the inclusion of distilled corn oil had positive effects on carcass yield and skin/meat color parameters. This study demonstrates the successful incorporation of alternative lipid sources into the diet of meat quails, with no compromise to performance and carcass characteristics. These findings provide valuable insights into improving nutrition and meat quality, benefiting both the quail industry and society as a whole. Abstract The objective of this study was to investigate the impact of alternative lipid sources on nutrient metabolism, performance, carcass characteristics, and meat quality in European quails. Trial 1 determined the energy values and nutrient metabolizability of non-conventional lipid sources. Six treatments (control, soybean oil, conventional corn oil, distilled corn oil, poultry fat, and beef tallow) were randomly assigned with 10 replicates per treatment. Trial 2 evaluated animal performance, carcass characteristics, and meat quality using a randomized design with five treatments and 10 replicates each. Statistical analysis showed no significant difference in apparent metabolizable energy corrected by nitrogen (AMEn) and coefficients of metabolizability (CM%) among the lipid sources. The AMEn values found were 8554 for soybean oil, 7701 for corn, 7937 for distilled corn oil, 7906 for poultry fat, and 7776 for beef tallow (kcal/kg). The CM values were 88.01% for soybean oil, 79.01% for corn oil, 84.10% for distilled corn oil, 81.43% for poultry fat, and 79.28% for beef tallow. The inclusion of lipid sources of plant and animal origin in the diet of 7–35-day old meat quails did not influence performance or carcass and cut characteristics. The inclusion of distilled corn oil increased carcass yield and influenced skin and meat color parameters. AMEn values varied for each lipid source. The inclusion of distilled corn oil positively influenced skin and meat color as well as carcass yield in quails.
The Effects of ICT-Based Interventions on Physical Mobility of Older Adults: A Systematic Literature Review and Meta-Analysis

Systematic literature review and meta-analysis were conducted to integrate and analyze intervention studies dealing with the effects of information and communications technology- (ICT-) based interventions on the physical mobility of older adults in the community. The PubMed/MEDLINE, Embase, CINAHL, and Cochrane CENTRAL databases were searched for studies published from January 2000 to December 2022. We used the Risk of Bias 2 (RoB 2) tool to evaluate the quality of the randomized controlled studies in the systematic review. The meta-analysis was performed using a random-effects model. The model was used to calculate the standardized mean difference (SMD) and 95% confidence interval (CI) for both effect measures. I2 tests were used to measure the presence of heterogeneity. Thirty-seven randomized controlled trials were included (2,419 intervention participants), of which 23 were included in the meta-analysis. ICT interventions significantly improved Timed Up and Go (TUG) as a marker of physical mobility variable in older adults (SMD = −0.33, 95% CI: −0.57 to −0.10, p=0.005, I2 = 74.7%). A sensitivity analysis was performed on subgroups, and interventions were found to be effective in improving TUG in the exergame group (SMD = −0.40, 95% CI: −0.72 to −0.08, p < 0.001, I2 = 75.0%) and in the exergame with virtual reality (VR) group (SMD = −0.33, 95% CI: −1.01 to 0.35, p < 0.001, I2 = 91.0%) but both groups showed high heterogeneity. A meta-analysis was also performed on Short Physical Performance Battery (SPPB) but statistically significant results were not found (SMD = −0.19, 95% CI: −0.61 to 0.23, p=0.375, I2 = 87.7%). For the Berg Balance Scale (BBS), the post-intervention scores were significantly better than baseline (SMD = 1.52, 95% CI: 0.48 to 2.57, p=0.004, I2 = 93.5%). However, the number of studies included in the meta-analysis was small and heterogeneity was high, so follow-up studies are needed. This study confirmed that exergames, telecommunication, e-health, information applications, and robots were used as effective ICT-based interventions for improving the physical mobility of older adults. It is necessary to develop and apply more diverse ICT-based interventions that will prevent impairments of mobility and encourage older adults to live more independently, with a higher quality of life, based on extensive research on ICT-based interventions.
Studies on the mathematical model for function deployment of Jiaozhou Bay and its adjacent coastline

A dynamic model of multiple criteria decision analysis for function deployment of Jiaozhou Bay and its adjacent coastline was established based on the theories and methods of systems engineering integrating with locational theory, macro economic analysis methods and computer techniques. The optimal results were derived by solving the model, which will exert a great influence upon the exploiting and protecting, and the sustainable development and prosperous of Qingdao City.
Defense Method against Adversarial Attacks Using JPEG Compression and One-Pixel Attack for Improved Dataset Security

Machine Learning has gained widespread applications, especially in the domain of image recognition due to the high performance of algorithms and models. Nonetheless, the potential threat posed by adversarial samples has impeded their widespread adoption, especially in safety-critical applications. In such cases, the model's final performance is significantly compromised due to the presence of adversarial perturbations that are invisible to human perception. This paper introduces a novel pre-processing solution for protecting image datasets against adversarial attacks such as the Fast Sign Gradient Method or other similar attacks. The proposed method involves utilizing high JPEG compression for removing the adversarial perturbations of the dataset and applying a Targeted One Pixel Attack with the aim of recovering the true class of the images after the compression process. The proposed approach results in a highly secured and clean dataset maintaining a high classification accuracy. The approach was tested on CIFAR10 dataset. The results have shown that the misclassification rate after the FGSM attack was significantly reduced from 89.3% to 12.5% using this method for the compression quality of 20 on a subset of 1000 images.
The Diurnal Cycle of Rainfall and Deep Convective Clouds Around Sumatra and the Associated MJO‐Induced Variability During Austral Summer in Himawari‐8

The effects of the diurnal cycle and large‐scale atmospheric disturbances dominate rainfall and cloud variability in the Maritime Continent. This study examines the modulation of the Austral Summer diurnal cycle by the Madden–Julian Oscillation (MJO) using cloud populations through precipitation and deep convective cloud derived from satellite measurements. Using Rainfall Potential Areas from Himawari‐8 Advanced Himawari Imager as a proxy for deep convection, our analysis shows that convective clouds are present ∼55% of the time over land in Sumatra during the afternoon and night. Cloud signatures reveal semi‐diurnal structures of deep convective clouds off the West Coast of Sumatra. In contrast, the East Coast exhibits explicit sea‐ward propagation patterns of deep convective controlled by the coastal effects around the Strait of Malacca and Java Sea, together with the influence of synchronized diurnal forcing between islands. We show that the MJO drives the enhanced convective phases, changing the cloud top type distribution, moisture convergence, and moisture transport over the equatorial Indian Ocean. The cold cloud area also increases during the MJO active phases, which is linked to frequent deep convective cloud development near the mountain ranges of Sumatra and the adjacent ocean. The analyses of cloud variations based on the rainfall potential areas and cloud top type provide evidence of the effects of convective processes on the diurnal cycle of ice and water vapor distribution in the troposphere.
The Norwegian Foreign Visitor Survey

This border survey has been arranged since 1995 on an all-year-round basis. The survey covers in principle all inbound tourism including air, sea, road, bus and railway connections. It includes both business and leisure travel, but not travel to and from work. The visitor survey is based on existing statistics and reports from the travel companies, observations of vehicles and interviews with the travellers when they leave the country. Border surveys of this type entail special methodological problems. Because the population is in fact unknown, it is not possible to draw a probability sample. In this survey the population is stratified into 27 strata, and the sample selection is improved as the knowledge about the structure of the traffic increases. Some other relevant methodological and practical issues will also be discussed. Preliminary main results from the survey in the summer season 2004 will be presented, with special emphasis on some key trends in the foreign holiday traffic.
In vitro anticancer effect of azithromycin targeting hypoxic lung cancer cells via the inhibition of mitophagy

Solid tumors are predisposed to hypoxia, which induces tumor progression, and causes resistance to treatment. Hypoxic tumor cells exploit auto- and mitophagy to facilitate metabolism and mitochondrial renewal. Azithromycin (AZM), a widely used macrolide, inhibits autophagy in cancer cells. The aim of the present study was to determine whether AZM targeted hypoxic cancer cells by inhibiting mitophagy. Lung cancer cell lines (A549, H1299 and NCI-H441) were cultured for up to 72 h under normoxic (20% O2) or hypoxic (0.3% O2) conditions in the presence or absence of AZM (≤25 µM), and the cell survival, autophagy flux and mitophagy flux were evaluated. AZM treatment reduced cell survival under hypoxic conditions, caused mitolysosome dysfunction with raised lysosomal pH and impaired the efficient removal of hypoxia-damaged mitochondria, eventually inducing apoptosis in the cancer cells. The cytotoxic effect of AZM under hypoxic conditions was abolished in mitochondria-deficient A549 cells (ρ° cells). The present study demonstrated that AZM reduced lung cancer cell survival under hypoxic conditions by interfering with the efficient removal of damaged mitochondria through mitophagy inhibition. Thus, AZM may be considered as a promising anticancer drug that targets the mitochondrial vulnerability of hypoxic lung cancer cells.
Spatio-Temporal Patterns of Biodiversity and their Drivers - Method Development and Application

To resolve the confusion surrounding the concept of ‘beta-diversity’, a more consistent terminology is proposed. Almost 50 years ago, Whittaker (1960) suggested a concept for biodiversity measurement. He formulated the terms ‘alpha-’, ‘beta-’ and ‘gammadiversity’, which have been widely applied since. However, there is no agreement between ecologists on the definition of the terms especially regarding ‘beta-diversity’. A multitude of different definitions hamper application and scientific progress. As the importance of variability of species composition in space and time becomes more and more evident, a concise terminology is urgently needed. On basis of a review of the existing concepts we propose a less ambiguous, clear terminology: ‘inventory diversity’ for describing within sample diversity, ‘differentiation diversity’ for compositional similarity between samples and ‘proportional diversity’ for the comparison of inventory diversity across spatial and temporal scales.
Study of urban intersection lane structure based on floating car tracking data

For road intersection,the turning information of lanes changes quickly and it is difficult to be gathered,therefore,the method of extracting lane structure and turning information using the floating car data was proposed in the paper.Firstly,the trajectory points set were selected by the selection rule and processed by optimized rules;secondly,Gaussian mixture density model was used for lane structure modeling of intersection and greedy EM algorithm was used for calculating the parameters to get the lane number and the lane structure;thirdly,the strategy of calculating the lane turning was given by the relation between the trajectory and the lanes.Finally,agroup of real intersection data were selected for experiment,and the results demonstrated the effectiveness of this method,which could not only serve the lane information update,but also be applied in finer navigation system for the improvement of the navigation experience.
An Analysis of Diffusion of Teacher-curated Resources on Pinterest

Teachers increasingly rely on online social media platforms to supplement their educational resources, greatly influencing PK-12 education through the swift and extensive diffusion of teacher-curated resources. Understanding this diffusion process is crucial, but current educational studies primarily report resource diffusion through small-scale analyses, such as teacher interviews or anecdotal accounts. To bridge this gap, we conduct a pioneering, large-scale, quantitative, and data-driven analysis of the diffusion of teacher-curated resources on Pinterest, a platform widely embraced by educators. Our study begins by defining a resource’s diffusion tree, which encapsulates the cascade of resource sharing across the social network. Based on this diffusion tree, we identify three measures to characterize a resource’s diffusion process: volume, virality, and velocity. Equipped with these three measures, we conduct an in-depth analysis of the diffusion of over one million resources curated by thousands of teachers on Pinterest. Our investigation concludes by examining the correlation between a resource’s attributes and its curator’s attributes and the diffusion of the resource.
Computational modelling of micro-structured burners with improved combustion stability by ﬂuid recirculation structures

While burners designed in a backﬂow way enable operation with very low noxious emissions, they frequently operate very close to the extinction limit of the ﬂame. Cavity structures have been designed for the purpose of improving ﬂame stability. However, the precise mechanism by which the cavity method provides increased ﬂame stability remains unclear. Computational ﬂuid dynamics simulations are conducted to gain insights into burner performance such as reaction rates, species concentrations, temperatures, and ﬂames. Factors aﬀecting combustion characteristics and ﬂame stability are determined. The results indicate that burner dimensions greatly aﬀect ﬂame stability. Burners with large dimensions lead to a delay in ﬂame ignition and may cause blowout. The combustion is stabilized by recirculation of hot combustion products induced by the cavity structure. The inlet velocity of the mixture is a critical factor in assuring ﬂame stability within the cavity-stabilized burner. There is a narrow range of inlet velocities that permit sustained combustion within the cavity-stabilized burner. Design recommendations are provided.
Gooseberry Anthocyanins Alleviates Insulin Resistance by Regulating Ceramide Metabolism in High Fat Diet Mice

In order to explore the effect and mechanism of Gooseberry anthocyanins (GA) on reducing the ceramide content to reduce Insulin Resistance (IR) in mice.Molecular docking, Real-Time PCR and Western Blotting were used to explore the molecular mechanism and the effects of different doses GA in high-fat diet (HFD) mice.The results showed that the binding energy of anthocyanins on CerS6 was in the range of -8.2 to 5.2 kcal/mol, with low energy parameters and good binding positions. GA could effectively inhibit visceral fat, liver index, TC, TG and LDL-C, and improved HDL-C, GSH-Px and SOD.GA decreased the level of Insulin sensitivity index from-5.15 to-4.54 and improved insulin sensitivity and insulin resistance in HFD mice. Real-Time PCR and Western blotting results showed that GA could reducemRNA levels of in�ammatory factors IL-6 and TNF-α , inhibit the expression of CerS6,PKC ζ , PPAR γ , CD36 and enhance the expression of SphK2, Akt, p-Akt/Akt, ISR. This study revealed the molecular mechanism of improving insulin resistance of GA in S1P/Cer signaling pathway, and provided theoretical support for preventive treatment of obesity related diseases by polyphenols.
MIT Open Access Articles Simultaneous Registration of Multiple Images: Similarity Metrics and Efficient Optimization

—We address the alignment of a group of images with simultaneous registration. Therefore, we provide further insights into a recently introduced framework for multivariate similarity measures, referred to as accumulated pair-wise estimates (APE), and derive efﬁcient optimization methods for it. More speciﬁcally, we show a strict mathematical deduction of APE from a maximum-likelihood framework and establish a connection to the congealing framework. This is only possible after an extension of the congealing framework with neighborhood information. Moreover, we address the increased computational complexity of simultaneous registration by deriving efﬁcient gradient-based optimization strategies for APE: Gauss-Newton and the efﬁcient second-order minimization (ESM). We present next to SSD the usage of intrinsically non-squared similarity measures in this least-squares optimization framework. The fundamental assumption of ESM, the approximation of the perfectly aligned moving image through the ﬁxed image, limits its application to mono-modal registration. We therefore incorporate recently proposed structural representations of images, which allow us to perform multi-modal registration with ESM. Finally, we evaluate the performance of the optimization strategies with respect to the similarity measures, leading to very good results for ESM. The extension to multi-modal registration is in this context very interesting because it offers further possibilities for evaluations, due to publicly available data sets with ground-truth alignment.
On the Feasibility of Compressing Certifiably Robust Neural Networks

Knowledge distillation is a popular approach to compress high-performance neural networks for use in resource-constrained environments. However, the threat of adversarial machine learning poses the question: Is it possible to compress adversarially robust networks and achieve similar or better adversarial robustness as the original network? In this paper, we explore this question with respect to certifiable robustness defenses , in which the defense establishes a formal robustness guarantee irrespective of the adversarial attack methodology. We present our preliminary findings answering two main questions: 1) Is the traditional knowledge distillation sufficient to compress certifiably robust neural networks? and 2) What aspects of the transfer process can we modify to improve the compression effectiveness? Our work represents the first study of the interaction between machine learning model compression and certifiable robustness.
IN CHIPMUNKS: RESPONSES TO EXPERIMENTAL MANIPULATION OF POPULATION DENSITY AND DISTRIBUTION

An experimental perturbation study was performed on a natural population of eastern chipmunks, Tamias striatus , inhabiting a peninsula supporting a fairly mature deciduous forest. Animals were marked and recaptured during a 4-week preperturbation period and their home ranges and centers of activity were determined. During the second 4-week phase of the study, 49 of the 69 resident chipmunks were removed from the study area; the remaining 20 animals had well-established home ranges and centers of activity on the upper half of the study area, allowing one-half of the study area to remain free of chipmunks. Shifts in home range and center of activity were noted for the period during which this artificial reduction in population density was maintained; although home range and center of activity shifts were observed for some animals, size of home range did not increase in response to the reduced density. There was, however, a statistically significant movement of animals onto the vacated section of the study area.