Miracle-dz/UniFAR-FTUs huggingface dataset:
Linking Seasonal‐to‐Interannual Variability of Intermediate Currents in the Southwest Tropical Pacific to Wind Forcing and ENSO

Seasonal‐to‐interannual variability of intermediate circulations in the southwest tropical Pacific is key to interhemisphere and interbasin water mass exchange and is shown to be interconnected with wind forcing and the El Niño–Southern Oscillation (ENSO) based on numerical model results validated by mooring observations. The Lower Equatorial Intermediate Current and the intermediate part of the New Guinea Coastal Undercurrent show clear seasonal variability and a significant interannual response to ENSO at a 7–12‐month lag, both of which are induced by Rossby waves. Baroclinic modes 1 and 2 of the direct wind‐forced Rossby waves contribute mainly to the seasonal variability. In contrast, the Rossby waves from baroclinic modes 2 and 4 and the reflection of Kelvin waves are the main contributors to the variability on ENSO time scales. The presence of the southwest tropical Pacific coastline enhances the intermediate seasonal variance and the interannual relationship between intermediate currents and ENSO.
Fusion of multi representation and multi descriptors for facial expression recognition

Facial Expression Recognition has become vital for efficient Human Computer Interaction. In this paper, we propose effective facial expression recognition approachfor recognizing six basic facial expressions. Our approach consists of three main phases which are: (1) face detection and pre-processing, (2) features extraction and (3) facial expression classification. The face pre-processing phase is performed using the facial landmarks. After the face is aligned and cropped, facial regions of interest (eyes, nose and mouth) are detected. In the features extraction phase, we used Histogram of oriented gradients (HOG), Local Binary Pattern (LBP) and the fusion of the two features. For the last step, Support Vector Machine (SVM) is used to recognize the facial expression. To evaluate the performance of our approach, we used three popular datasets which are The Extended Cohn-Kanade (CK+), The Japanese Female Facial Expression (JAFFE) and Oulu-CASIA NIR-VIS dataset (CASIA), In addition, 10 folds cross-validation scheme is used to evaluate the performance of our approach. Our proposed fusion of multi representations and multi descriptors achieves better or competitive performance compared with the state-of-the-art methods. The accuracies of our approach are 99.18%, 95.77% and 99.09% for CK+, JAFFE and CASIA, respectively. The results prove the efficiency of our approach although the challenging conditions from one dataset to another.
HARVEST: High-Resolution Haptic Vest and Fingertip Sensing Glove That Transfers Tactile Sensation of Fingers to the Back

Human fingertips are densely populated with tactile receptors and are hence incredibly sensitive. However, wearing gloves on the fingers drastically reduces the tactile information available to the fingertips, such as the texture and shape of the object, and makes it difficult to perform dexterous work. As a solution, in this study, we developed a high-resolution haptic vest that transfers the tactile sensation of the fingertips to the back. The haptic vest contains 80 voice-coil type vibrators which are located at each of the two discrimination thresholds on the back and can be driven independently. The tactile sensation of the fingertips is transferred to the back using the developed haptic vest in combination with a sensing glove that can detect the pressure distribution on the finger skin at up to 100 points. Different experiments were conducted to validate the performance of the proposed haptic vest and sensing gloves. The use of the haptic vest and the sensing glove enabled the user to perceive the shape of a planar object more accurately when compared to the case where the user wore only the glove.
Trusted Security Immune Model of Power Monitoring System

Power monitoring system is an important national infrastructure; its security has a vital position. In recent years, malicious attacks against power information systems emerge in an endless stream, which makes power systems worldwide suffer a major blow. Aiming at the hierarchical structure of the power monitoring system and the security threats it faces, this paper proposes a security immune model based on trusted computing technology. The security analysis shows that the model can guarantee the credibility of the power monitoring system.
Diel at‐sea activity of two species of great albatrosses: the ontogeny of foraging and movement behaviour

2 2 : e02597 The first year of life is a period of high mortality in animals. Reduced foraging capacities of naive individuals might be the primary cause of their mortality. These capacities are supposed to be progressively acquired during the first months of life. In this study, we investigate the ontogeny of flight capacities, by day and night, of first-year individuals, and compare it with adults from two closely related species of great albatrosses: Amsterdam Diomedea amsterdamensis and wandering Diomedea exulans albatrosses which forage in different environmental conditions. We used 71 tracks of 71 juvenile birds and 141 of 116 incubating adults to compare both age categories. In order to explore the effect of moon light on night activity, we elaborated a new formula which improves the precision of the proxy of moon illumination. By day, we found that juveniles of both species reach some adult foraging capacities in less than two months. By night, albatrosses have reduced activity increasing during the first weeks at sea for juveniles and changing in accordance with moon illumination for both juveniles and adults. A peak of flight activity at dawn and dusk was apparent for both species. Interspecific comparison underlined that Amsterdam albatrosses were more active than wandering albatrosses, suggesting a difference in food and foraging strategy. Overall, we highlighted how life history traits, environmental conditions and time of the day affect the foraging activity of two related species of seabirds.
Blockchain-based Academic Journals

We propose a decentralized journal platform based on blockchain, in which referees are individually incentivized. We construct a model in which the journal publishes qualified papers under two types of information asymmetry: paper quality and type of referees. We investigate under what conditions equilibrium in decentralization exists or fails and it leads to a better outcome. The results from the model can be widely applied to information-production processes in intermediary funding decisions, loan inspection, and credit ratings. Our research helps to understand how to design the incentive structure for information providers (specialists) in terms of social welfare.
Removal of Thiophene from Mixtures with n-Heptane by Selective Extraction Using Deep Eutectic Solvents

This work investigates the use of deep eutectic solvents (DESs) to extract sulfur-based compounds from n-heptane as model diesel compounds. Four DESs were prepared by combining tetrabutylammonium bromide or methyltriphenylphosphonium bromide with ethylene glycol, triethylene glycol, or sulfolane. All DESs showed good ability to extract thiophene with the best extraction efficiency (35%) being observed for the sulfolane-based DES. The extraction efficiency can be further enhanced to reach 98% when five extraction cycles are performed. Moreover, the DESs were easily regenerated using rotary evaporation. In addition,1H NMR analysis is used to elucidate the extraction mechanism. Finally, the COSMO-RS model was used to predict the ternary tie lines for the studied systems and the NRTL model allowed, correlating the experimental data with an average root-mean-square deviation of <2% for all DESs. These models can be utilized for further simulation analysis of the extraction process.
Particulate carbon in artic ice : Ice archives in Antarctica and Greenland

Combustion causes the emission of fine carbonaceous particles which may become trapped in polar ice, far from the original source. These ancient particles may constitute a unique record of fires in the past. Studies on particulate carbon in polar ice are rare, primarily because of problems linked to the large volume of sample required for analysis
Identification of Nucleus Sterility Candidate Genes Using a Resequencing Technique in Sweet Pepper Sterile Line AB91

Background:Breeding hybrids with nuclear malesterile lines is an important method for the cross breeding of sweet peppers. To date, few reports have been published on the nuclear malesterility gene of sweet pepper.Yet, there are approximately 20 pepper nuclear malesterility lines in the world. Results: Using the self-developed testing material, sweet pepper nuclear malesterile dual-purpose line AB91, the genome-wide resequencing technique was applied to firstly find that the mutation site causing the abortion of sweet pepper nuclear malesterility AB91 is on chromosome #5. The mutation gene Capana05g000747 was filtered out and validated by the flight mass spectrometry genotyping and quantitative real-time PCR method and determined to be the gene causing the abortion of sweet pepper nuclear male sterility AB91.The gene Capana05g000747 mutation site is a non-synonymous mutation site located at the 6th exon,the base C mutated into A, and the amino acid changed from alanine to serine. The three-dimensional protein structure of fertile and sterile plant Capana05g000747 was predicted. The results showed that the three-dimensional structure of the two proteins was differed significantly. Sequence alignment analysis showed that the gene Capana05g000747 has a similar function to gene At2g02148. The gene At2g02148 contains a pentatricopeptide repeatprotein which has important physiological functions in the gene expression process of organelles and is closely related to the performance of malesterility genes. Conclusions: This study revealed that Capana05g000747 was selected as an important candidate gene for sweet pepper nuclear male sterile testingmaterial AB91.This gene provides a theoretical and technical foundation for further cloning as well as transformation and utilization of the gene.
A high sensitivity microwave glucose sensor

A simple, sensitive, low-cost microwave sensor capable of conducting glucose concentration measurements has been developed without chemical bindings. The sensing device uses a microstrip transmission line to detect variation of the glucose component of the solutions placed in a cavity under it. The uniform and concentrated electric field distribution results in an accurate and sensitive measurement of the absorption frequency shift in the frequency response of the sensor. The sensor was fabricated on a FR4 substrate for low-cost purpose. The shift in the absorption frequency of the device was measured in the frequency range between 4.8 GHz and 5.7 GHz using solutions with different glucose concentrations in two ranges: (a) high concentration from 1000 mg dl−1 to 8000 mg dl−1 and (b) low concentration from 100 mg dl−1 to 300 mg dl−1. The experimental results showed a high sensitivity of 0.32 MHz (mg dl−1)−1 for the low concentrations in terms of absorption frequency.
Smart paddy field monitoring system using deep learning and IoT

Paddy is an essential nutrient worldwide. Rice gives 21% of worldwide human per capita energy and 15% of per capita protein. Asia represented 60% of the worldwide populace, about 92% of the world’s rice creation, and 90% of worldwide rice utilization. With the increase in population, the demand for rice is increased. So, the productivity of farming is needed to be enhanced by introducing new technology. Deep learning and IoT are hot topics for research in various fields. This paper suggested a setup comprising deep learning and IoT for monitoring of paddy field remotely. The vgg16 pre-trained network is considered for the identification of paddy leaf diseases and nitrogen status estimation. Here, two strategies are carried out to identify images: transfer learning and deep feature extraction. The deep feature extraction approach is combined with a support vector machine (SVM) to classify images. The transfer learning approach of vgg16 for identifying four types of leaf diseases and prediction of nitrogen status results in 79.86% and 84.88% accuracy. Again, the deep features of Vgg16 and SVM results for identifying four types of leaf diseases and prediction of nitrogen status have achieved an accuracy of 97.31% and 99.02%, respectively. Besides, a framework is suggested for monitoring of paddy field remotely based on IoT and deep learning. The suggested prototype’s superiority is that it controls temperature and humidity like the state-of-the-art and can monitor the additional two aspects, such as detecting nitrogen status and diseases.
Polymer nanocomposites based on inorganic and organic nanomaterials

Nanotechnology is the focus of the research world of today. In this respect, nanocellulose is considered to be one of the most important nanomaterials which is found to be suitable for an enormous range of applications. In this chapter, the various intricate isolation techniques of nanocellulose fibers have been discussed, augmented by the wide spectrum of properties and applications which the material displays. The synthesis of nanocellulose fibers covers the different processes of acid hydrolysis, alkaline hydrolysis, electrospinning, mechanical crushing, use of organic and ionic solvents, and application of microwave and gamma radiation, along with production by the use of enzymes. Furthermore, the material displays unique properties which are supported by morphological evidence. The broad range of applications of nanocellulose fibers is revealed in their usage in diverse fields of modern technology-based global scenario of today.
Design and Simulation of a Portable Copper Tubes Induction Brazing Tool for PV System Application

This paper presents the design and simulation of a portable induction heating brazing tool. This tool is intended to be very lite, flexible and low price. It is an application of a singlephase Push-Pull as a DC-AC inverter to achieve the high frequency, high voltage suitable for induction heating applications. Two types of power supplies proposed for the welding tool the first is a portable battery, and the second is a photovoltaic panel. The Finite Element Analysis (FEA) applied to study the induction coil design and the welding process using ANSYS programming package, while MATLAB programming package used for simulating the power supply. The achieved results prove the visibility of this tool.
Assessment of biological and agronomic diversity of seven durum wheat varieties cultivated in the Northeastern region of Algeria

Abstract. Boudersa N, Chaib G, Atoui A, Cherfia R, Bouderbane H, Boudour L. 2021. Assessment of biological and agronomic diversity of seven durum wheat varieties cultivated in the Northeastern region of Algeria. Biodiversitas 22: 1025-1036. The present work was carried out during the 2017/2018 agricultural season, at the experimental station of the ‘Institut Technique des Grandes Cultures’ (ITGC) – El Khroub, Constantine, Algeria. The main objective of this study was the evaluation and the characterization of seven varieties of durum wheat (Triticum durum Desf.) in terms of their behavior and yield. For these reasons, several phenological, morpho-physiological, and biochemical traits, as well as the yield with its components were studied. The obtained results showed a significant variety effect, in particular, for the variables corresponding to the production and to the tolerance. The analysis of the correlation coefficients indicated that the number of spikes per m2, the number of grains spike-1, and the rate of chlorophyll pigments in the leaves were the most related characteristics to grain yield. Indirect selection for breeding productivity through these traits could prove to be effective. Besides, it revealed that tall varieties displayed better resistance to possible hazards; had high relative water content (RWC), accumulated more soluble sugars and proline, as well as, they showed a low level of Malondialdehyde (MDA) compared to other varieties. In addition, this study allowed us to determine many relationships between the studied parameters, that can make a contribution in both the productivity and the adaptation improvement programs of the durum wheat.
A New Robust Adaptive Fusion Method for Double-Modality Medical Image PET/CT

A new robust adaptive fusion method for double-modality medical image PET/CT is proposed according to the Piella framework. The algorithm consists of the following three steps. Firstly, the registered PET and CT images are decomposed using the nonsubsampled contourlet transform (NSCT). Secondly, in order to highlight the lesions of the low-frequency image, low-frequency components are fused by pulse-coupled neural network (PCNN) that has a higher sensitivity to featured area with low intensities. With regard to high-frequency subbands, the Gauss random matrix is used for compression measurements, histogram distance between the every two corresponding subblocks of high coefficient is employed as match measure, and regional energy is used as activity measure. The fusion factor d is then calculated by using the match measure and the activity measure. The high-frequency measurement value is fused according to the fusion factor, and high-frequency fusion image is reconstructed by using the orthogonal matching pursuit algorithm of the high-frequency measurement after fusion. Thirdly, the final image is acquired through the NSCT inverse transformation of the low-frequency fusion image and the reconstructed high-frequency fusion image. To validate the proposed algorithm, four comparative experiments were performed: comparative experiment with other image fusion algorithms, comparison of different activity measures, different match measures, and PET/CT fusion results of lung cancer (20 groups). The experimental results showed that the proposed algorithm could better retain and show the lesion information, and is superior to other fusion algorithms based on both the subjective and objective evaluations.
New large-volume detector at the Baksan Neutrino Observatory: Detector prototype

At the Baksan Neutrino Observatory (Institute for Nuclear Research of the Russian Academy of Sciences, Moscow) deployed in the Caucasus mountains, it is proposed to create, at a depth corresponding to about 4700 mwe (meter water equivalent), a large-volume neutrino detector on the basis of a liquid scintillator with a target mass of 10 kt. This article describes the current state of the first stage of the project, namely a prototype detector with a scintillator mass of 0.5 t. The design of the detector, the equipment and methods used are described.
The behavior to cavitation erosion-corrosion of the CuZn39Pb3 brass structures, obtained by in-depth heat treatments

The paper highlights the behavior at the vibratory cavitation erosion of CuZn39Pb3 brass microstructures, as obtained by in-depth heat treatments. Two heat treatment cycles are analysed (hardening at 800ºC, followed by cooling in water, and hardening at 800ºC, with cooling in water, followed by tempering at 400ºC with cooling in air). The micro-hardness measurements show that the change in the microstructure, relative to the initial status of the material (semi-finished), determines higher values of the micro-hardness. The studies of the cavitation erosion, using the vibrating standard piezoelectric crystal assembly, available in the Cavitation Research Laboratory at the Polytechnic University from Timisoara, presented in the paper, shows significant increases in the surface resistance to the stress determined by the cavitation micro-jets, as compared to the initial state of the material (semi-finished).
A THEORETICAL STUDY OF THE MECHANISM AND REGIOSELECTIVITY OF THE 1,3-DIPOLAR CYCLOADDITION REACTION OF AZIDES WITH ALKYNES

The mechanism and regioselectivities of the [3+2] cycloaddition reactions of the ethynylbenzene 4 and azide compounds 1, 2 and 3, have been theoretically studied using DFT methods at the B3LYP/6-31G(d) computational level. The possible ortho/meta regioselective channels were explored and characterized. The low polar character of these 32CA reactions is the consequence of the high nucleophilic character of both reagents. Analysis of the free energies associated with the different reaction pathways indicates that the 32CA reactions of the ethynyl-benzene 4 and azide compounds 1, 2 and 3 are highly meta regioselective, in agreement with the experimental observations.
Insight into the Impact of COVID-19 on Australian Transportation Sector: An Economic and Community-Based Perspective

The Coronavirus Disease 2019 (COVID-19) is a major virus outbreak of the 21st century. The Australian government and local authorities introduced some drastic strategies and policies to control the outspread of this virus. The policies related to lockdown, quarantine, social distancing, shut down of educational institute, work from home, and international and interstate travel bans significantly affect the lifestyle of citizens and, thus, influence their activity patterns. The transport system is, thus, severely affected due to the COVID-19 related restrictions. This paper analyses how the transport system is impacted because of the policies adopted by the Australian government for the containment of the COVID-19. Three main components of the transport sector are studied. These are air travel, public transport, and freight transport. Various official sources of data such as the official website of the Australian government, Google mobility trends, Apple Mobility trends, and Moovit were consulted along with recently published research articles on COVID-19 and its impacts. The secondary sources of data include databases, web articles, and interviews that were conducted with the stakeholders of transport sectors in Australia to analyse the relationship between COVID-19 prevention measures and the transport system. The results of this study showed reduced demand for transport with the adoption of COVID-19 prevention measures. Declines in revenues in the air, freight, and public transport sectors of the transport industry are also reported. The survey shows that transport sector in Australia is facing a serious financial downfall as the use of public transport has dropped by 80%, a 31.5% drop in revenues earned by International airlines in Australia has been predicted, and a 9.5% reduction in the freight transport by water is expected. The recovery of the transport sector to the pre-pandemic state is only possible with the relaxation of COVID-19 containment policies and financial support by the government.
Real Time Object Detection Using SSD For Bank Security

Object detection in real time applications are more challenging and thus faces more difficulties in designing object detection applications. Object detection is a method of identifying predefined objects from images, videos or from other input sources. It consist of different steps for identifying the object from its surroundings. Earlier detection system uses different techniques for objection detection with computationally demanding networks that requires high GPU and needs more power. Considering the current circumstances in the society, it is better to design real time object detection system for security applications. The newly evolved technique such as Tensorflow(TF) along with OpenCV can be used used for object detection. The CCTV footages can be used as input and the monitoring of it can be done inorder to find any security violations. The proposed real time object detection system for bank security mainly aims in providing security to bank vaults. This system can also be used for other security applications where human entry is restricted. The proposed model can be used for different security related applications effectively.