Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality Assessment for Retargeted Images: A Review

Transmission, saving and many processing methods cause different damage in images. Image Quality Assessment (IQA) is necessary to benchmark processing algorithms, to optimize them, and to monitor the quality of images in quality control systems. Traditional quality metrics have low correlations with subjective perception. The key problem is to evaluate the distorted images as human do. Subjective quality assessment is more reliable but is cumbersome and time-consuming, so it is impossible to embed it in online applications. Therefore, many objective perceptual IQA models have been developed until now. Content-aware retargeting methods aim to adapt source images to target display devices with different sizes and aspect ratios so that salient areas will be less distorted. The size mismatch and the completely different distortions caused by retargeting have made common IQA methods useless in this area. Therefore, retargeted Image Quality Assessment (RIQA) methods are designed for this purpose. The quality of retargeted images is different depending to image content and retargeting algorithm. This paper provides a literature review and a new categorization of the current subjective and objective retargeted image quality measures. Also, we intend to compare and analyze the performance of these measures. It is demonstrated that the performance of RIQA methods can be further improved by using high-level descriptors in addition to low-level ones.
Effect of Processing Variants on the Nutritive Value of Cottonseed Meal for Chicks

Abstract THE nutritional value of cottonseed meals for non-ruminants varies greatly. In processing cottonseed meal, both preservation of protein quality and detoxification must be achieved. The present processes of extraction of the oil from cottonseed involve two major phases, cooking and pressing. The cottonseed meals must be cooked to increase the yield and quality of the oil (Olcott, 1941). Reports generally credit moist cooking at high temperature with inactivation of the gossypol, which compound has been shown by Lillie and Bird (1950) and Heywang, Bird and Altschul (1950) to account for the toxicity of cottonseed meal for poultry. Among others, Gallup (1927) and Lyman, Holland and Hale (1944) reported destruction or inactivation of gossypol under these conditions. The evidence of the effect of cooking on the nutritive value of cottonseed meal is more contradictory. Olcott and Fontaine (1941) found that steam autoclaving at high temperatures markedly reduced nutritive value of the .
CINNAMATE 4-HYDROXYLASE DOWNREGULATION IN TRANSGENIC TOBACCO ALTERS TRANSCRIPT LEVEL OF OTHER PHENYLPROPANOID PATHWAY GENES

Cinnamate 4-hydroxylase ( C4H ) is the second gene of phenylpropanoid pathway res ponsible for the production of a variety of compounds including lignin. Transgenic t obacco plants were raised using antisense construct harbouring partial C4H gene from Leucaena leucocephala . C4H down-regulation in transgenic tobacco had pro found effect on the transcript level of C4H and other lignin biosynthesis pathway genes invest igated. Transgenics had reduced C4H transcript level, as low as about 5% of the level i n control plants in one of the transgenics. It was interesting to see higher reduction in the transcript level of phenyla lanine ammonia lyase ( PAL ), the enzyme preceding C4H in the pathway, than C4H itself. Reduction in the transcript level of 4-Cou marate: CoA Ligase ( 4CL ), the enzyme that follows C4H in the pathway, was comparable to that of C4H . Transcript levels of two other phenylpropanoid pathway genes, Caffeoyl coenzyme A 3-O- methyltransferase ( CCoAOMT ) and cinnamyl alcohol dehydrogenase (CAD ) were also found reduced compared to control. In t he transgenic line AS9, a small reduction of about 11% in the transcript level of C4H resulted in about 88% reduction in the transcript level of PAL and 19-29% reduction in the transcript level of 4CL , CCoAOMT and CAD . In our knowledge, this is the first quantitative report of concomitant decrease in the transcript level of fiv e phenylpropanoid pathway genes as a result of down-regulation of one of the pathway genes.
Directed Search Pattern of a Leafminer Parasitoid Among Mines of Host Larvae

Abstract Parasitoids have developed a variety of searching strategies to maximize their searching efficiency. To increase the efficiency, leafminer parasitoids first search for host mines, which are linear and visually conspicuous, and then search for host larvae situated at the end of the mines by tracking the mines. We hypothesized that the leafminer parasitoids have the ability of directional orientation toward larvae as opposed to orienting randomly and tested this hypothesis by using the leafminer Liriomyza trifolii (Burgess) (Diptera; Agromyzidae) and its parasitoid Hemiptarsenus varicornis (Girault) (Hymenoptera: Eulophidae). Direct observations of parasitoid behavior revealed that female parasitoids mostly selected the correct direction immediately after mine encounter. However, they did not select correctly when the host had been parasitized, or when the point of the mine encounter was far from the host larva, suggesting the possibility of sound-based search. Curiously, the success of encounter rates was not influenced by the directions that the female had selected. This was because the female turned to the correct direction during her search even after selecting the wrong direction. Thus, female H. varicornis can recognize which end of the mine the target larva lays upon mine encounter or during the foraging bout. The importance of the ability of recognizing the correct direction by the parasitoid and the possible mechanism involved in this ability is discussed.
Phylogenetic relationships within the cahirinus-dimidiatus group of the genus Acomys (Rodentia: Muridae): new mitochondrial lineages from Sahara, Iran and the Arabian Peninsula

Spiny mice belonging to the cahirinus-dimidiatus group of the genus Acomys have become a widely used model in physiology and behaviour. To improve current knowledge concerning the phylogeny of this taxon, we analysed 24 samples from Libya, Chad, Egypt, Jordan, Cyprus, Crete, Turkey, Yemen and Iran. We sequenced the whole mitochondrial control region and part of the flanking tRNA genes for a total length of 986 to 996 bp and described 22 haplotypes. Our results confirmed that the Afro-Mediterranean and Asian clades are clearly distinct (p-distance = 6-8.1%). The former clade corresponds to A. cahirinus sensu lato (i.e. including also the Cretan A. minous, Cypriot A. nesiotes and Turkish A. cilicicus). Haplotypes of A. cahirinus from the E Sahara (S Egypt, SW Libya, N Chad) grouped with those of A. cilicicus and A. minous (p-distance ≤ 2.2%), while haplotypes of A. nesiotes grouped with one haplotype representing the commensal A. cahirinus from Cairo (p-distance = 1.2%). Close similarity among haplotypes from mainland Africa and NE Mediterranean (clade A. cahirinus sensu stricto) support the hypothesis that ancestors of A. nesiotes, A. cilicicus and A. minous dispersed most probably as commensal populations, thus questioning their status of valid species. The most surprising finding was the considerable genetic variation in Asia. In addition to a haplogroup from Sinai and Jordan (corresponding to A. dimidiatus sensu stricto), we detected two previously unknown haplogroups, from Yemen and Iran + United Arab Emirates. These clades are fairly distinct and separate species/subspecies status of these animals might be further considered.
High Frequency Monolithic Inductor with Air-Gaps

In this paper, we evaluate the possible implementation of air-gaps for extending the operating range of an RF on-chip inductor, without affecting the inductance. To determine where air-gaps should be placed, the dominant parasitic capacitance component of an inductor is first identified, using an equivalent circuit model to extract their values from numerical simulation data. An air-gap fabrication in the back-end of line technology is given to illustrate for the feasibility of the integration. Based on the fabricated array of air-gaps at a 2:1 void-to-dielectric interval, we show that the capacitance is reduced by 40%, which translates to an increase in the inductor self-resonance frequency by 20% to 27 GHz, while having a large value inductance at 1.5 nH range.
Detritus processing, ecosystem engineering and benthic diversity: a test of predator–omnivore interference

Summary 1 Interference between species from different functional groups may influence ecosystem functioning and biological diversity. This study tested whether interactions between predacious cutthroat trout and an omnivorous signal crayfish modified the crayfish's trophic and engineering effects within a detrital-based, stream benthic community. 2 We show in a trough experiment that omnivorous crayfish through their trophic and engineering roles enhance detritus decomposition, reduce particulate organic matter (POM) accumulation, and diminish diversity in leaf packs. 3 In crayfish troughs by day 30, leaf dry weight loss was 1·8-fold greater, whereas POM trapped in leaf packs was 80% less, than of those in controls, and the abundance, biomass and taxon richness of benthos in leaf packs were lower than those in controls. Predatory cutthroat trout did not affect those variables and did not interfere with the crayfish. 4 Crayfish and cutthroat trout both decreased fine material sedimentation in the troughs. 5 Thus, with no interference from cutthroat trout, the signal crayfish acted as ecosystem processors and engineers, and strongly influenced detrital processing, benthic diversity, and the accumulation of POM and fine sediments.
LowSHeP: Low-overhead forwarding and update Solution in ndn with Hexadecimal Patricia trie

Named Data Networking (NDN) is designed to cope with today's internet usage by making data as the first class entity irrespective of its source. But, NDN suffers from certain overheads such as storage, data forwarding and update overheads. We address such issues primarily by proposing to keep the entire database in some of the selective special nodes only and partial database in rest of the nodes. This results in reduction of both update overheads in terms of number of message exchange and storage overheads. We also propose tokenized hexadecimal patricia trie structure to store the database to be stored in the nodes resulting in significant reduction of database look-up time. Accordingly we propose forwarding and update algorithms for NDN. Performance of our low-overhead solution for NDN is evaluated in terms of data forwarding, update and storage overheads both theoretically and through simulation. Finally, the scheme is compared with one existing patricia trie based scheme and the results confirm our scheme's supremacy over the competitor scheme.
Myuchelys gen. nov. a new genus for Elseya latisternum and related forms of Australian freshwater turtle (Testudines: Pleurodira: Chelidae)

Myuchelys, a new genus, is erected for a well supported clade of Australasian freshwater turtles; its establishment resolves an unacceptable paraphyly in relationships among species of the genus Elseya. Molecular and morphological evidence indicates that the closest relationship of the new genus is with Emydura, not the redefined Elseya.
Study on Curved Surface Fitting of Countersink Based on Point Cloud

According to high precision of point cloud, countersink quality detection based on point cloud is an effective way to detect defect of countersink. One of the major processes in countersink quality detection is curved surface fitting. In this study, we eliminate point cloud interference considering curved surface which is not absolutely smooth and propose a curved surface fitting algorithm for building cone model by using circular curves and conical surfaces. The fitting algorithm is designed to establish model precisely considering diameter of edge, depth, and nest angel of countersink. In addition, to validate the performance of the algorithm, a computer vision approach which is developed in literature is presented and its results are compared with those obtained by using the fitting algorithm based on point cloud. Experimental results show that the fitting algorithm can be regard as an effective and precise algorithm for curved surface fitting under external interference in terms of experimental results. Furthermore, this study reveals that the proposed algorithm is more precision and has better anti-noise performance compared with computer vision detection approach.
Design and Characterization of a Miniature Hydraulic Power Supply for High-Bandwidth Control of Soft Robotics

Soft robotics holds enormous promise for a wide class of applications. However, system controllability, bandwidth, portability, and energy efficiency of soft robot power supplies are often inadequate. Soft robotics desperately needs improved solutions to drive soft actuators either pneumatically or hydraulically. This research paper offers a contribution to bridge this gap. It deals with small-scale power supplies for hydraulically-driven soft robots based on fluidic elastomer actuators in the power range 5-400 W. A design procedure for such power supplies is developed with an emphasis on high-bandwidth control. The performance requirements are established based on a literature survey, and design alternatives are discussed. Then, a prototype consisting of a $0.102 c^{3}$/rev positive-displacement, external gear pump directly driven by a 70 W brushless dc motor is built and experimentally characterized. Control of the targeted soft robots results possible because the proposed power supply has high-bandwidth varying between about 12 and 30 Hz (i.e., well above the actuators’ mechanical frequency). The power supply’s energy efficiency is also measured, and areas for its improvement are identified. The proposed solution is feasible, applicable to autonomous soft robots, scalable to the power levels of interest, and possibly useful for both tethered soft robots and rigid/semi-rigid robots.
OrthrusPE: Runtime Reconfigurable Processing Elements for Binary Neural Networks

Recent advancements in Binary Neural Networks (BNNs) have yielded promising results, bringing them a step closer to their full-precision counterparts in terms of prediction accuracy. These advancements were brought about by additional arithmetic and binary operations, in the form of scale and shift operations (fixed-point) and convolutions with multiple weight and activation bases (binary). In this paper, we propose OrthrusPE, a runtime reconfigurable processing element (PE) which is capable of executing all the operations required by modern BNNs while improving resource utilization and power efficiency. More precisely, we exploit DSP48 blocks on off-the-shelf FPGAs to compute binary Hadamard products (for binary convolutions) and fixed-point arithmetic (for scaling, shifting, batch norm, and non-binary layers), thereby utilizing the same hardware resource for two distinct, critical modes of operation. Our experiments show that common PE implementations increase dynamic power consumption by 67%, while requiring 39% more lookup tables, when compared to an OrthrusPE implementation.
Biological Microscopy with Undetected Photons

Novel imaging techniques utilizing nondegenerate, correlated photon pairs sparked intense interest during the last couple of years among scientists of the quantum optics community and beyond. It is a key property of such “ghost imaging” or “quantum interference” methods that they use those photons of the correlated pairs for imaging that never interacted with the sample, allowing detection in a spectral range different from that of the illumination of the object. Extensive applications of these techniques in spectroscopy and microscopy are envisioned, however, their limited spatial resolution to date has not yet supported real-life microscopic investigations of tiny biological objects. Here we report a modification of the method based on quantum interference by using a seeding laser and confocal scanning, that allows the improvement of the resolution of imaging with undetected photons by more than an order of magnitude, and we also present examples of application in the microscopy of biological samples.
Image Classification and Detection of Cigarette Combustion Cone Based on Inception Resnet V2

In order to guide the production of cigarette products and improve the quality of cigarette products, this paper proposes a classification method for cigarette combustion cones based on deep convolutional neural network model. The method is optimized based on the Inception Resnet V2 model and is innovatively used in the detection of cigarette burning cones. The classification accuracy of combustion cone fallout is characterized by the overall classification accuracy (OA) and the Kappa coefficient (Kappa). The experimental results show that the overall classification accuracy is 97.22%, and the Kappa coefficient is 0.9583. The deep convolutional neural network has better classification effect. Based on the classification method of deep convolutional neural network, the cigarette burning cone can be accurately identified.
Comparison of Predictive Statistical Learning Accuracy with Computational Intelligence Methods

Forecasting of high-frequency economic time series data is a complex problem, which has benefited from recent advancements and research in machine learning. To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models. The Computational Intelligence (CI) models are based on neural networks (NN) and Support Vector Machines (SVM). The main work of this study is to compare the predictive accuracy level of the statistical methodological approach with NN and SVM on the large data set. We evaluate statistical ML (Maximum Likelihood) learning method, Back- Propagation (BP) and genetic algorithms (GA) for half-hourly 1-step-ahead electricity demand prediction using Australian electricity data. We showed that all ARIMA, NN, SVM models as prediction methods are reasonable and acceptable for use in forecasting systems that routinely predict values of variables in competitive energy markets.
Problem Analysis for Creating an Algorithm for Detecting Episodes of Epileptic Seizures

This paper deals with the problems that may arise while objectifying the onset of an epileptic seizure. The electroencephalography (EEG) is the most commonly used method to search for epileptiform activity, but it does not always provide accurate determination of the onset of an epileptic seizure, because each physician's assessment is subjective and based on his or her knowledge and experience. Therefore, in order to avoid disputes, it is proposed to use the information on cardiac activity and cardiovascular system activity during attacks, in particular the use of electrocardiography (ECG), to analyze complex cases. The algorithm for identifying an epileptic seizure was developed, which is based on these principles. It is a combination of some methods, such as amplitude detection and HRV analysis. Their mathematical simplicity provides that software, which can be developed on this algorithm’s basis, may have advantages like quick signal processing and low PC’s resources consumption.
A 92%-Efficiency Hybrid Envelope Tracking Modulator Based on 3-Level Hysteresis-Controlled Buck Converter with Capacitor Current Integration Sensor

This paper presents a 20 MHz bandwidth, 92%-efficiency, hybrid envelope tracking modulator with a 3-level hysteresis-controlled buck converter in parallel with a Class-AB linear amplifier for LTE application. Compared with the 3-level PWM control, this control method has fast loop response with the improvement of efficiency. The 3-level hysteresis controller controls LA output current and flying capacitor voltage of switching stage concurrently without synchronization clocks. And capacitor current integration sensor is embedded in the hysteresis-control loop to solve the current sensor problem. The designed Class-AB linear amplifier with rail-to-rail input stage and maximum current selection achieves a small signal -3 dB bandwidth of 238 MHz. With an optimized design in 65 nm CMOS technology, the modulator can deliver 0.92 W output power to a 4Ω load, achieving a maximum efficiency of 92% for LTE-20MHz application.
De-Authentication Attack Detection using Discrete Event Systems in 802.11 Wi-Fi Networks

There is a lot of growth in Wi-Fi technology, that has given rise to Internet access without the need of wires. In IEEE 802.11 protocol, many vulnerabilities are present at the MAC layer which give rise to a lot of Denial of Service (DoS) attacks. In this manuscript we mainly concentrate on de-authentication DoS attack in Wi-Fi Networks. The victim station get disconnects from the network due to the de-authentication DoS attack. Minimum resources are required to launch the de-authentication attack. However, the schemes for detecting the de-authentication DoS attack suffer from major drawbacks namely, require protocol modification, require firmware upgradation, no proof of correctness etc. To acknowledge these issues, a Discrete Event System (DES) based Intrusion Detection System (IDS) for detection of de-authentication attack is proposed.
Effect of dietary supplementation with Anacardium occidentale on growth performance and immune and visceral organ weights in replacement laying pullets

This study was conducted to determine the effect of Anacardium occidentale powder as a dietary supplement on growth performance, immune and visceral organ weights of replacement laying pullets. A total of 320-day-old White Leghorn (Hybrid L 33 ) replacement laying pullets were placed for 35 days for trial 1. Birds were assigned to four dietary treatments, with four replicates per treatment and 20 birds per replicate. Two hundred and forty pullets from trial 1 and maintained on their respective treatments were used trial 2 which lasted three weeks (up to 56 days old). Each treatment was assigned to four replicates of 15 birds according to a completely randomized design. Dietary treatments consisted of a control diet fed without or with 0.5, 1.5 and 2.5% supplemental A. occidentale powder. Supplementation of 0.5% of Anacardium occidentale powder increased the BW and the bursa of Fabricius and cecum relative weights at 35 days. However, productive indicators were reduced (P<0.05) with supplementation of 1.5 and 2.5% of A. occidentale powder. Also, variations were observed in the thymus, proventriculus and gizzard relative weights at 56 days. Supplementing A. occidentale powder did not affect the viscera relative weights at 35 days. However, at 56 days the pancreas relative weight was higher in the treatment without powder and the kidney relative weight and intestinal pH (P<0.05) increased with supplementation of 1.5 and 2.5% of A. occidentale powder. These findings indicate a beneficial effect of dietary supplementation of A. occidentale powder at 0.5% on growth performance, immune and visceral organs in the replacement laying pullets.
A Gain-improved Broadband Twin-Whip Antenna for High Frequency

In this paper, a new type of 10-meters single-loaded broadband twin-whip antenna is designed. The influence of antenna spacing on the performance of twin-whip antenna is analyzed by moment method. The loading position, the parameters of loading and broadband matching network of antenna is optimized and calculated by using algorithm. A 10:1 scaled model antenna has been fabricated, whose VSWR, gain, pattern and non-circularity are simulated and calculated. The measured VSWR is in agreement with the simulation results, which of all frequency points is less than 3 with an average value of 2.15. The maximum gain is greater than -3dB, the maximum is 5.29dB with an average of 3.39dB. The minimum non-circularity of gain is 0.03dB (at30MHz), and the maximum is 2.74dB (at230MHz). The efficiency is higher than 16.5%, the maximum was 68.7% with an average of 57.75%.