Miracle-dz/UniFAR-FTUs huggingface dataset:
A Provisional Labels-Reduced, Real-Time Connected Component Labeling Algorithm for Edge Hardware

Connected component labeling (CCL) is an important operation in computer vision tasks, widely used for real-time image processing on edge hardware. The existing connected component labeling algorithms always generate plenty of provisional labels. Solving the equivalence of provisional labels needs much memory access and processing time. The greater difficulty is that the processing time varies with the number and shape of the connected components. To solve the problems, this brief proposes a new two-scan CCL algorithm. It consists of novel provisional label predicting and provisional label assignment methods based on predicting table, linked lists, and equivalent table. The provisional label predicting method reduces the number of provisional labels effectively. The provisional label assignment method can implement quickly the assignment operation of CCL by combination of the first scan and the second scan with fixed processing time. We have implemented the proposed algorithm on Field Programmable Gate Arrays (FPGA) for raster scan images. The results show that its processing speed can achieve 726fps@225MHz for $640\times 480$ image resolution, and its resource utilization is less than 15% of compared implementation. It is suitable for real-time edge applications. Compared with other algorithms, the proposed algorithm reduces provisional labels efficiently and completes the CCL operation with a fixed number of iterations. Therefore, it shortens processing time and makes the processing time constant.
Returns to schooling in European emerging markets: a meta-analysis

ABSTRACT This paper conducts a meta-analysis of 1599 estimates extracted from 69 previous studies to identify time-series changes in returns to schooling in 20 European emerging markets. We examine possible difference in returns to schooling across the region. A meta-synthesis suggests a decreasing trend over time in returns to schooling in European emerging markets. Synthesis results also indicate that the western part of the region tends to have higher returns to schooling than the eastern part. Both the meta-regression analysis of literature heterogeneity and the test for publication selection bias produced findings that are highly consistent with the meta-synthesis results.
Power allocation strategies with per-antenna for secure directional modulation

In directional modulation (DM) networks, conventional power allocation strategy is actually an equal-power allocation method. However, in practice, each antenna is equipped with its own power amplifier and is restricted. This paper considers a more practical situation that the power of each antenna sent to the receiver is different. Here, we study the optimal power allocation (OPA) strategy with multiple-input single-output (MISO) in DM communication system. Explicitly, we first formulate a secrecy rate (SR) maximization problem subject to the total power constraint, with designing the useful information power vector and artificial noise covariance matrix. For the non-convex problem, we propose the maximizing secrecy rate based on successive convex approximation (Max-SR-SCA) method to solve it. Subsequently, in order to reduce the computational complexity, we propose the maximizing product of signal-to-leakage-plus-noise-ratio (SLNR) and artificial-noise-to-leakage-plus-noise-ratio (ANLNR) (Max-SLNR-ANLNR) method to obtain a suboptimal solution. Simulation results show that the proposed two methods have better SR performance than the conventional PA factor scheme. In addition, the proposed Max-SLNR-ANLNR method forms a single energy main peak at Eve position, which indicates it realizes precise jamming.
EaD: ECC-Assisted Deduplication With High Performance and Low Memory Overhead for Ultra-Low Latency Flash Storage

Data deduplication has become a commodity feature in flash storage products to effectively reduce redundant write data and improve space efficiency. However, it also introduces computing and memory overhead to generate and store the cryptographic hash (fingerprint) in face of the moderate data redundancy in primary storage. With the advent of 3D XPoint and Z-NAND technologies, and the stronger cryptographic hash functions in use, such as SHA-256, both the computing and memory overheads are increasingly serious performance bottlenecks for inline data deduplication in these ultra-low latency flash storage. To address these problems, we propose an ECC-assisted Deduplication approach, called EaD, which exploits the ECC property and the asymmetric read-write performance characteristics of modern flash storage. EaD first identifies data similarity by leveraging the device-generated ECC values of data chunks as their fingerprints, significantly reducing the costly MD5/SHA-based cryptographic hash computing and alleviating the memory space overhead. Based on the identification results, similar data chunks and their ECCs are read from the flash to perform a byte-by-byte comparison in memory to definitively identify and remove redundant data chunks. Our experiments show that the EaD approach significantly increases I/O performance by up to 4.2<inline-formula><tex-math notation="LaTeX">${\times }$</tex-math><alternatives><mml:math><mml:mo>×</mml:mo></mml:math><inline-graphic xlink:href="wu-ieq1-3152665.gif"/></alternatives></inline-formula>, with an average of 2.5<inline-formula><tex-math notation="LaTeX">${\times }$</tex-math><alternatives><mml:math><mml:mo>×</mml:mo></mml:math><inline-graphic xlink:href="wu-ieq2-3152665.gif"/></alternatives></inline-formula>, compared with the existing MD5/SHA- and sampling-based deduplication approaches.
Evaluation of adding sodium stearoyl-2-Lactylate to energy-reduced diets on broilers’ development, nutritional digestibility, bacterial count in the excreta, and serum lipid profiles

Abstract The purpose of this study was to evaluate the outcome of sodium stearoyl-2-lactylate (SSL) supplementation to energy reduced diets on broilers’ growth performance, apparent nutrient digestibility, excreta bacterial counts, and blood lipid profile. A total of 700 one-day-old male (feather sexed) Ross 308 broiler chickens having an average body weight of 43 ± 1.2 g were randomly allotted to five (5) dietary treatments (7 pens/treatment). The treatments consisted of: (1) positive control (PC) (basal diet with metabolisable energy, ME = 3000 kcal/kg starter; 3100 kcal/kg grower; 3200 kcal/kg finisher), (2) negative control (NC) (PC − 50 kcal/kg), (3) SSL1, NC + 0.03% SSL, (4) SSL2, NC + 0.04% SSL, (5) SSL3, NC + 0.05% SSL. The PC group showed higher BWG (body weight gain) and lower FCR (feed conversion ration) than the NC group during days 1 to 7, and 7 to 21. SSL supplemented groups showed higher BWG and better FCR than the NC group, along with a linear increase in BWG and linear decrease in FCR during days 1 to 7 and 7 to 21. Furthermore, a linear increase in overall BWG was observed with SSL doses. Excreta microbial counts were not influenced by energy levels or SSL doses. In blood serum parameters, LDL (low density lipoprotein) cholesterol was reduced with a linear tendency by increasing levels of SSL supplementation. In conclusion, sodium stearoyl-2-lactylate supplementation showed better growth and nutrient digestibility in broilers’ at an early age. Highlights Emulsifiers can help broilers to utilise dietary energy more efficiently Sodium Stearoyl-2- Lactylate helped to increase energy and fat digestibility in broilers As a result, growth performance was improved through Sodium Stearoyl-2-Lactylate supplementation in broilers
A generative adversarial network for ultrasound signal enhancement by transforming low-voltage beamformed radio frequency data to high-voltage data

Ultrasound image quality is strongly dependent on penetration depth and attenuation. The transmit voltage in ultrasonic systems can be increased to increase output power and improve the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in deeper regions. However, the utility of using high transmit voltages and thus high output power is limited due to associated thermal and mechanical bioeffects. Additionally, the ability to increase the output power is limited in portable and low-cost ultrasound devices which have lower power. We propose a software-based approach, using a conditional generative adversarial network (cGAN) to amplify signals in deeper regions and enhance image quality without increasing the transmit voltage. The cGAN was customized and trained with beamformed radio frequency phantom data pairs (n=288) acquired with a Verasonics Vantage System; with input data taken at a low output voltage (20V) and corresponding output data taken at a high output voltage (70V). We trained and tested the performance of different loss functions and cGAN architectures. Our proposed model, tested on a hold-out phantom data set (n=73) was able to improve the average penetration depth by roughly 16% (1 cm gain in penetration depth) when compared to the low-voltage images. We found an average increase in CNR of 160.45%±117.64, increase in Peak SNR of 5675%±1.89dB, and increase in SNR of 32.68%±4.84 dB, relative to the low voltage images, for selected hyper and hypoechoic regions of interest. This work has potential applications in fetal imaging, where safety guidelines limit transmit voltage significantly, and portable devices.
Clinical Features and Immunophenotypes of Double-Hit Diffuse Large B-Cell Lymphoma

Double-hit (DH) genetics induces a reduction in the complete remission (CR) and, consequently, in poor overall survival (OS) in diffuse large B-cell lymphoma (DLBCL) patients. Unfortunately, DH identification is time-consuming. Here, we retrospectively reviewed 92 newly diagnosed DLBCL patients, stratified them into the DH (n = 14) and non-DH groups (n = 78), and compared their clinical features and outcomes. The results revealed that the DH group had a higher percentage of bulky disease than the non-DH group (64.3% vs. 28.2%; p = 0.013). More patients in the DH group tested positive for double expresser (DE) (50.0% vs. 21.8%; p = 0.044). The three-year OS rates of patients with and without DH were 33.3% and 52.2%, respectively (p = 0.016). Importantly, advance stage and multiple comorbidities were correlated with a high mortality rate in multivariate analysis. Furthermore, by combining DE and the bulky disease, a specificity of 89.7% for DH prediction was achieved. In summary, DH genetics, not DE immunopositivity, could be a factor for an inferior OS in DLBCL. A combination of bulky disease and a positive DE immunophenotype could facilitate DH genetics prediction in newly diagnosed DLBCL patients.
Entrepreneurship Intentions Analysis of Mexican University Students Using an Artificial Neural Network to Promote Sustainable Businesses: An Interdisciplinary Perspective

This paper shows an analysis of the entrepreneurship intentions patterns in the short, medium, and long term of Mexican university students. The entrepreneurship patterns analysis was carried out using a customized artificial neural network considering as inputs the self-assessment of multiple intelligences from an interdisciplinary perspective. Thus, many important findings reveal that not all multiple intelligences have a direct and proportional impact on entrepreneurship intention. In fact, Linguistic–Verbal Intelligence, Intrapersonal Intelligence, and Interpersonal intelligence are the types of intelligence that have the greatest influence on entrepreneurial intentions. In addition, the performance metrics of the ANN for classifying the entrepreneurship intentions are higher than the ones reported in the literature (i.e., accuracy ≈ 99.29%, precision ≈ 98.89%, sensitivity ≈ 99.53%, and specificity ≈ 99.01%). The paper contributes to the literature on the deep understanding of entrepreneurs’ behavior concerning the strengths and weaknesses of their multiple intelligences. Besides, this interdisciplinary empirical work contributes to improving the design of methods and techniques to strengthen entrepreneurship from the earliest stages of students’ lives and promote sustainable businesses. The most surprising finding was the minimal relationship of Naturalistic Intelligence to undertake sustainable and robust projects, which demands more detailed and in-depth analysis. Finally, some proposals are presented to improve the teaching process of entrepreneurship and sustainability, considering the artificiality, sustainability, and entrepreneurship involved in academic programs at universities.
Design of foundation multi-aperture imaging system validation experiment

On the basis of the demands of high resolution in imaging technologies of developing engineering practices,the imaging principles of an optical synthetic aperture and the advantages in improving the resolution of image was discussed in this paper.The domestic and foreign research results and the exciting technical difficulties in the relevant research fields also were demonstrated.In the current conditions of processing and testing alignment,the imaging experiment of two sub-aperture telescope was designed.From theory of geometrical optics,using Fizeau-type multi-aperture telescope,the experimental possibility of Fizeau-type synthetic aperture was investigated.The adjustment accuracy of the key components in the synthetic imaging system was researched,which ensures that the system can make an image completely.In the experiments,the fine tuning mechanism with a designed resolution less than ±0.03 mm ensures that the system can obtain a clear image,and the precision piezoelectric linear drive system with a resolution 0.05 μm guarantees the synchronization of two beams′ phases.The results show that the foundation of the designed experiment is feasible,and the system can offer the exact resolution values.This research makes a useful basis for the synthetic aperture imaging system,and has important potential in practices.
Yttrium Trifluoride as a Marker of Infiltration Rate of Decalcified Root Cementum: An In Vitro Study

Research related to the development of a dental infiltrant for minimally invasive treatment of initial caries of hard dental tissues is presented. The formulation of the developed infiltrant material includes typical methacrylate monomers used in dentistry, an author’s adhesion monomer containing metronidazole, a photoinitiating system and yttrium trifluoride (YF3). The main objective of the study was to evaluate penetration into decalcified root cementum using scanning electron microscope of an experimental preparation with the characteristics of a dental infiltrant compared to a commercial preparation with the addition of YF3 as a contrast agent. Microscopic observations showed that YF3 particles virtually did not penetrate deep into the root cementum—this was mainly due to the particle size of YF3. Observations of cementum and root dentin tissue infiltration: resin tissue infiltration was visible to a depth of about 80 to 120 μm without the use of a tracer, which, due to agglomeration and particle size, remained on the cementum surface or in the resin used for inlaying. There were no differences between the degree of penetration of an experimental preparation with the characteristics of a dental infiltrant, as compared to a commercial preparation.
Transient loss analysis based on interleaved parallel system of GaN full bridge LLC resonant converter

In order to improve the efficiency of full bridge LLC resonant converter interleaved parallel (FBLLC-SP) system, and make its theoretical loss closer to the actual operation loss, In this paper, the parasitic parameters of cascode GaN HEMT are introduced into the loss model , to set up an accurate loss model of FBLLC-SP system, which is suitable for single phase shift (SPS) open-loop control and three phase shift (TPS) double closed-loop control; In this paper, the optimal dead time calculation method is given, and the theoretical loss of FBLLC-SP system under single phase-shifting (SPS) open-loop control is analyzed, and the accurate calculation methods of transient loss of GaN HEMT with different modes are proposed; The experimental system is built. The experimental results show that the loss value of the loss model in this paper is about 0.6% higher than the actual operation loss of the system, that is to say, the refined loss model established in this paper can be used to analyze the actual operation loss of the system.
Gaze-assisted remote control for quad-rotor UAV

With the development of quad-rotor UAVs, UAVs have been widely used in civilian fields such as aerial photography, agricultural production, surveillance and rescue. Controlling drones is a complex and difficult task for human operators. Therefore, it is of great significance to reduce the burden of human operation and improve the efficiency of drones when performing tasks. With the development of some novel human-computer interaction technologies and the continuous improvement of drone autonomy, manipulating drones can become easier and more interesting. In this work, we designed a method that uses operator gaze to assist drone control and target following. We conducted verification experiments on the Tello UAV, and the experimental results show that eye tracking interaction makes the human operation process more natural, and the combination of eye movement behavior and semi-autonomous drone control further reduces the burden on operators and improves the reliability of drone missions.
Aligning Dynamic Social Networks: An Optimization Over Dynamic Graph Autoencoder

Social network alignment, aligning different social networks on their common users, is receiving increasing attention from both academic and industry. Most of the existing studies consider the social network to be static and neglect its inherent dynamics. In fact, the dynamics of social networks contain the discriminative pattern of an individual, which can be leveraged to facilitate social network alignment. Hence, we for the first time propose to study the problem of aligning dynamic social networks. Towards this end, we propose a novel Dynamic Graph autoencoder based dynamic social network Alignment approach, referred to as DGA, unfolding the fruitful dynamics of social networks for user alignment. However, it faces challenges in both modeling and optimization: (1) To model the intra-network dynamics, we design a novel dynamic graph autoencoder to learn user embeddings with complex network dynamics. (2) To model the inter-network alignment, we design a unified optimization framework over proposed dynamic graph autoencoders, constructing a common subspace for user alignment across different networks. (3) To address this optimization problem, we design an effective alternating algorithm with solid theoretical guarantees. We conduct extensive experiments on real-world datasets and show that the proposed approach substantially outperforms the state-of-the-art methods.
Influence of abscisic acid, Ascophyllum nodosum and Aloe vera on the phenolic composition and color of grape berry and wine of 'Cabernet Sauvignon' variety

In viticulture, various techniques can be used to improve productivity, tolerance to biotic or abiotic stress, the quality of grapes and wines such as the use of plant regulators and biostimulants. Thus, the objective of this work was to evaluate the effect of application of abscisic acid (S-ABA), Ascophyllum nodosum (A. nodosum) seaweed extract and Aloe vera (A. vera) gel on phenolic composition and chromatic characteristics of grapes from the 'Cabernet Sauvignon' variety. The experiment was conducted in a commercial vineyard in Campo Largo - Paraná, in two consecutive seasons, 2017/18 and 2018/19, involving the following treatments: 1) control; 2) (S-ABA) 400 mg/L; 3) S- ABA 600 mg/L; 4) A. vera gel 200 mL/L; 5) A. vera gel 400 mL/L; 6) seaweed extract 0.2 mL/L; 7) seaweed extract 0.4 mL/L. Two applications were performed with the seaweed extract and A. gel when the bunches were at veraison stage (50 and 75% of grape berries with coloration). Total anthocyanins content, total polyphenols content and activity of phenylalanine ammonia-lyase (PAL), polyphenoloxidase and peroxidase enzymes were assessed in the berries skin. Total anthocyanins, individual anthocyanins and total polyphenol contents as well as lightness, chroma and hue angle were analyzed in the corresponding wines. S-ABA increased the content of anthocyanins and total polyphenols, as well as the activity of PAL in the first season. A. nodosum (AN) seaweed extract increased the total polyphenol content, total anthocyanins content and PAL in the berry skin of 'Cabernet Sauvignon' variety. S-ABA increased the total polyphenol content and anthocyanins in wine, as well as the A. nodosum, in at least one of the evaluated seasons.
Discovery of European frogbit (Hydrocharis morus-ranae L.) in Oconto County, Wisconsin: A summary of physical and plant community changes at a Lake Michigan coastal marsh

Located in Oconto County, Wisconsin, Oconto Marsh #2 is a Great Lakes Coastal Wetland Monitoring Program (CWMP) study site that borders the shoreline of Lake Michigan. Plant communities were characterized at Oconto Marsh #2 along three fixed transects in 2011, 2016, 2017 and 2021, a period when Lake Michigan water levels increased by two meters. Transects were placed to intersect with three vegetation zones: submergent, emergent, and wet meadow. Here, we highlight physical landscape changes and the vegetation composition changes that occurred from 2011 to 2021. From satellite imagery, we estimate the vegetated wetland area decreased by 50 percent. High energy wave action and ice scour penetrating farther inland are likely most responsible for causing these changes. Using multivariate ordination and PERMANOVA, we show plant composition in 2011 and 2021 was different from years 2016 and 2017. While invasive Phragmites australis was treated with herbicide in 2014 (herbicide treatment completed by non-CWMP groups), disturbance from progressively increasing water levels has facilitated considerable species turnover since monitoring began. Despite successful treatment of P. australis, the establishment of additional non-native species has caused site-wide mean coefficient of conservatism scores to decline from a calculated score of 4.2 in 2011 to 3.3 in 2021. Of critical importance, we discovered the highly invasive species European frogbit (EFB) (Hydrocharis morus-ranae L) near the research transects in 2021. This is the first documented occurrence of EFB in Wisconsin. The newly discovered EFB range spans 31 km along the general shoreline from Marinette to Oconto, WI.