Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultrasound-assisted extraction of starch from frozen jicama (P. erosus) roots: Effect on yield, structural characteristics and thermal properties

ABSTRACT Jicama roots have been studied as an alternative starch source. However, reports about the extraction yield are scarce, as well as publications about the use of pretreatment techniques for this material. Hence, the aim of this study was to analyze the effect of sonication on the starch yield as well as on the granule structure. Ultrasound was observed to have a positive effect on the starch yield, with the largest value obtained at a sonication time of 10 min (24.76 ± 2.4%). This represents a 46.9% increase over a non-treated sample (16.86 ± 0.9%), and the starch granule structure was unaffected, as confirmed by microscopy and an X-ray diffraction analysis The imperviousness of the starch granule to the sonication process is attributed to the protective effect of soluble fiber and a change in viscosity caused by the material released from parenchyma cells. More studies are required in this area.
Leakage-Resilient and Proactive Authenticated Key Exchange (LRP-AKE), Reconsidered

SUMMARY In [31], Shin et al. proposed a Leakage-Resilient and Proactive Authenticated Key Exchange ( LRP-AKE ) protocol for credential services which provides not only a higher level of security against leakage of stored secrets but also secrecy of private key with respect to the involving server. In this paper, we discuss a problem in the security proof of the LRP-AKE protocol, and then propose a modiﬁed LRP-AKE protocol that has a simple and e ﬀ ective measure to the problem. Also, we formally prove its AKE security and mutual authentication for the entire modiﬁed LRP-AKE protocol. In addition, we describe several extensions of the (modiﬁed) LRP-AKE protocol including 1) synchronization issue between the client and server’s stored secrets; 2) randomized ID for the provision of client’s privacy; and 3) a solution to preventing server compromise-impersonation attacks. Finally, we evaluate the performance overhead of the LRP-AKE protocol and show its test vectors. From the performance evaluation, we can conﬁrm that the LRP-AKE protocol has almost the same e ﬃ ciency as the (plain) Di ﬃ e-Hellman protocol that does not provide authentication at all.
A fast satellite selection algorithm for multi-GNSS marine positioning based on improved particle swarm optimisation

This paper introduces an improved particle swarm optimisation algorithm (IPSO), to select satellites rapidly in multi-GNSS marine positioning. The traditional particle swarm optimisation (PSO) may be trapped into local optimisation. To avoid the disadvantage, the proposed algorithm uses linear inertia weight factor and two functions of the immune system, i.e. the memory function and the self-regulatory function. Several experiments are carried out by adopting real survey data collected by the SiNan receiver that is installed on the Snow Dragon scientific research ship during the 9th China Arctic expedition. Compared with the minimum Geometric dilution of precision (GDOP) method, PSO and IPSO significantly reduce the computing time (96.25% and 95.61%). The variance of IPSO is 0.063, which is much lower than that of PSO (0.087). As for the positioning accuracy, the IPSO can reach the centimetre level in the kinematics condition.
Biorefinery approach for lignocellulosic biomass valorisation with an acidic ionic liquid

The commercialisation of the biorefinery approach involving the integration of the multi-step valorisation of low value biomass feedstock into a variety of chemicals, fuels and bioproducts is still very limited. In this context, the present work proposes an advanced methodology that comprises a cascaded approach towards wheat straw valorisation. The studied concept lies in the employment of an aqueous solution of the acidic 1-ethyl-3-methylimidazolium hydrogen sulfate ionic liquid in a selective and efficient hydrolysis of the hemicellulose fraction of wheat straw into pentoses, namely xylose and arabinose. An experimental design was utilised to search for the optimisation parameters, resulting in a maximum 80.5 wt% pentose yield in the liquor. Furthermore, the remaining solid, which contained practically all of the initial cellulose and lignin, was processed by considering two scenarios: (i) a direct enzymatic hydrolysis of the reaction solid, which yielded 75.8 mol% glucose; or (ii) a preceding extraction of lignin followed by enzymatic saccharification of the cellulose pulp, which yielded 91.3 mol% glucose. For both scenarios, lignin-rich solid fractions were obtained with distinct purities and yields. Additionally, the second scenario allowed producing a stream of value-added aromatic (phenolic) compounds. This work also overcame the challenges in IL recycling and reuse, with a simultaneous recovery of the pentoses from the reaction liquor as high as 88.6 mol%.
Online Matching in Advertisement Auctions ∗

Advertising has become a large source of revenue for many internet services, and at the same time internet technologies have completely transformed advertising. At the time of writing, worldwide digital advertising spend is estimated to be close to half a trillion dollars per year, and accounts for a majority of all media ad spending. It is the ad revenue that allows internet services companies to offer for free invaluable services such as search, social media, news, video, email, maps, operating systems, and all kinds of apps. Among the different channels in internet advertising, search advertising deserves special mention. When a user issues a search query with the intent to look for certain goods or services, the platform matches them to firms selling those goods or services, by displaying the relevant ads. Thus, firms are more certain to have their advertising budget spent on opportunities which are likely to result in a good return. Indeed, payment from an advertiser to a search engine is usually per-click, which is already a strong indication that the user has found the ad useful. Even display and video advertising have moved to a world of real-time bidding, which allows sophisticated algorithms to differentially evaluate every single ad opportunity. Whenever user activity generates an ad-slot, ads compete in a fully automated auction to win that slot. Given the size of the ad market and its importance to online commerce, deeper understanding and optimization of the underlying mechanisms has an out-sized impact. In this chapter, we will describe an important aspect of this market design, namely that of online matching in the auction context.
Noise Reduction Method Focusing on Spectral Envelopment and Fine Structure of Speech

We propose a method to enhance noise reduction performance by separating a speech spectrum into spectral envelopes and ﬁne structures using cepstrum analysis and linear predictive coding (LPC) analysis, and removing noise using an autoencoder (AE). A technique for removing noise from the spectrum of noise-containing speech is to use AE to reconstruct the spectrum of speech through the latent variables of the speech. We focused on spectral envelopes and ﬁne structures that constitute speech, and improved the independence between latent variables in AE to reconstruct the speech spectrum by separating them in advance. In this way, we conﬁrmed that the performance of noise reduction was improved in exchange for a slight decrease in the reproducibility of speech spectra when cepstrum analysis was used. It was also conﬁrmed that cepstrum analysis was superior to LPC analysis in noise reduction.
Analysis of Grade 10 English Textbook with Reference to Curriculum and Examination

This paper entitled “Analysis of Grade 10 English textbook with reference to curriculum and examination” was an attempt to explore the relationship among curriculum, text book and examination system. It aims to explore the contents in the textbook which were assumed by curriculum and evaluation procedures specified in the examination system. The contents and exposure sufficiency to develop intended language competency in learners were attempted to analyze. Another important concern of this paper was to explore the opinions of school level English teachers, who are the keys to materialize the textbook in relation to curriculum and examination system. Phenomenological research design was used in the study and the data was collected through interview, group discussion and interaction. The collected data were critically analyzed by developing themes. The findings of the study depict that there is insufficiency of the contents in the prescribed textbook for grade 10 in the experience of teachers and students. Similarly, they also noted that the contents are not suffice to achieve the objectives of the curriculum.
Factors Affecting Weight Gain in Nelore Calves from Birth to Weaning in the Bolivian Tropic

Retrospective data corresponding to the period between 2002 and 2018 were used, belonging to the Cooperativa Agropecuaria Integral San Juan de Yapacaní, Santa Cruz, Bolivia. Data corresponding to 663 male and female calves born to primiparous and multiparous cows were used. The calves had 13 individual weight controls. The calves had 13 individual weight controls. Variables used: Date of birth, Calf live weight at birth in kg, Calf live weight at weaning in kg, Average daily gain in kg, Live weight of cow in kg, Number of calving of cows. The mean values and standard deviations of the weights at birth were 35.1 ± 4.6 kg for males and 32.3 ± 4.7 kg for females, at 240 days (weaning) the weight of the males was 229 ± 35.8 kg and for females 206 ± 31.5 kg. The mean values and standard deviations of the weight increases were 0.807 ± 0.14 kg for males and 1.0 ± 0.13 kg for females. The selected model with the regressor variables: Year, Sex of the calf, Number of calving and Live Weight at Birth, all significant (p ≤0.001). No interaction was significant to be considered in the model (p≥0.05). The live weight at birth, the sex, the years and the number of deliveries of the mothers showed in this work and for the animals analyzed to be the factors affecting the increase in live weight in the rearing stage (from birth to weaning) in Nelore calves in the Bolivian tropics.
Camera Colour Correction using Neural Networks

We demonstrate that a deep neural network can achieve near-perfect colour correction for the RGB signals from the sensors in a camera under a wide range of daylight illumination spectra. The network employs a fourth input signal representing the correlated colour temperature of the illumination. The network was trained entirely on synthetic spectra and applied to a set of RGB images derived from a hyperspectral image dataset under a range of daylight illumination with CCT from 2500K to 12500K. It produced an invariant output image as XYZ referenced to D65, with a mean colour error of approximately 1.0 ΔE*ab.
Wavelet Analysis-Based Texture Analysis of Ceramic Surface Images

This paper is conducted to explore a new characterization method as a supplement to the traditional roughness characterization. The main research includes the extraction and evaluation of damage features of ceramic surface morphology by applying wavelet methods, the extraction of damage features in surface contours by using wavelet analysis, and the quantitative evaluation of damage degree by using damage rate and damage mean spacing. By comparing various fractal dimension calculation methods, a fractal dimension method suitable for calculating the ceramic surface was selected, and the fractal method was used to describe the ceramic surface topography as a whole. By comparing different methods of calculating the fractal dimension and further verifying them with the measured three-dimensional morphology, it is found that the vibrational method is more suitable for calculating the fractal dimension of ceramic surface, and its calculation accuracy is investigated, and the results show that the method is a reliable one. Based on the fractal theory, a mathematical model of surface wear and surface sealing was established. Further study of the model shows that the surface with a large fractal dimension has a good sealing effect; the surface corresponding to the best fractal dimension is the most resistant to wear. The fractal method can characterize the complexity of the surface profile as a whole. The wavelet method can describe the ceramic surface profile from a local perspective, and the combination of the two methods can characterize the ceramic surface well. Finally, the experimental device of the ceramic surface defect detection system is constructed, and the joint debugging of hardware and software is completed. Under different light source intensities, ceramic image samples are collected, and the accuracy detection experiments of sample defective edges are conducted, and the results show that the light source has a small impact on the accuracy of ceramic defective edge detection. The results show that the light source has more influence on the accuracy of scratch detection. The results show that the system constructed in this thesis has good applicability for different ceramic sample detection.
Effects of Plyometric Exercises versus Flatfoot Corrective Exercises on Postural Control and Foot Posture in Obese Children with a Flexible Flatfoot

Background Obesity contributes to the acquired flatfoot deformity which in turn impairs balance. Aim The purpose of the current study was to compare the effect of plyometric exercises with flatfoot corrective exercises on balance, foot posture, and functional mobility in obese children with a flexible flatfoot. Methods Forty-seven children participated in the study. Their age ranged from 7 to 11 years. Participants were randomly divided into 3 groups: experimental group I (EGI), experimental group II (EGII), and the control group (CG). The EGI received plyometric exercises and the EGII received corrective exercises, 2 sessions weekly for 10 weeks. The control group did not perform any planned physical activities. The Prokin system was used to assess balance, the timed up and go test (TUG) was used to assess functional mobility, and the navicular drop test (NDT) was used to assess foot posture. Results EGI showed significant improvement in all balance parameters, foot posture, and TUG. EGII showed improvement in the ellipse area and perimeter in addition to foot posture and TUG. Conclusion Plyometric exercises and foot correction exercises had a positive effect on foot posture, balance, and functional mobility in obese children with flatfeet.
Object Detection on Point Cloud data

With the abundance of Light Detection And Ranging(LIDAR) sensor data and the expanding self driving car industry carrying out accurate object detection is central to improve the performance and safety of autonomous vehicles. However point cloud data is highly sparse and this sparsity varies from one LIDAR to another and there is a need to study how adaptable object detection algorithms to data from different sensors. Due to the expensive nature of high end LIDAR this work aims to explore if a a network trained using a standard dataset like KITTI could be used for inference with a point cloud data from a 2D LIDAR that is modiﬁed to work as a 3D LIDAR. Additionally we also aim to explore if the average precision varies when the input fed to the network changes. We make use of Complex YOLO architecture which is a state of the art real-time 3D object detection network to train the KITTI dataset.
Challenges of integrating economics into epidemiological analysis of emerging infectious diseases

COVID-19 has shown that the consequences of a pandemic are more widereaching than cases and deaths. Morbidity and mortality are important direct costs, but infectious diseases both generate other direct and indirect benefits and costs and produce changes in behaviour that modify and relocate these benefits and costs. These additional effects can, in turn, feedback on health outcomes to create a complicated interdependent system of health and non-health outcomes. As a result, interventions primarily intended to reduce burden of disease can have wider societal and economic effects and more complicated, and possibly unexpected system level influences on the epidemiological dynamics themselves. To capture these effects requires a systems approach that encompasses more the direct health outcomes. Towards this end, we discuss in this article the importance of integrating epidemiology and economic models and we set out the key challenges which merging epidemiology and economics presents. We conclude that understanding behaviour is key to developing a more complete and integrated economic-epidemiological approach to help society understand how best to respond to future pandemics.
Sentiment Analysis on Social Media Data Using Intelligent Techniques

Social media gives a simple method of communication technology for people to share their opinion, attraction and feeling. The aim of the paper is to extract various sentiment behaviour and will be used to make a strategic decision and also aids to categorize sentiment and affections of people as clear, contradictory or neutral. The data was preprocessed with the help of noise removal for removing the noise. The research work applied various techniques. After the noise removal, the popular classification methods were applied to extract the sentiment. The data were classified with the help of Multi-layer Perceptron (MLP), Convolutional Neural Networks (CNN). These two classification results were checked against the others classified such as Support Vector Machine (SVM), Random Forest, Decision tree, Naïve Bayes, etc., based on the sentiment classification from twitter data and consumer affairs website. The proposed work found that Multi-layer Perceptron and Convolutional Neural Networks performs better than another Machine Learning Classifier.
Approximate Error Estimation based Incremental Word Representation Learning

In recent years, neural network based language representation learning model and word embedding technology have been successfully applied in variants of natural language mining tasks. In this paper, we present an incremental hierarchical probabilistic neural language learning algorithm to train evolving word vectors based on hierarchical softmax approximation. We split the incremental word representation learning objective function to reserved term and updated term separately, and factorize the incremental ob-jective function into the hierarchical softmax function. A novel stochastic gradient based approximately incremental method is proposed to update all the inherited word vectors and inherited parameter vectors, to reduce vector errors of inheritance. Theoretical analysis of the bound and convergence is also provided for the approximate incremental objective function. Extensive experiments show that the proposed approximately incremental word embedding method can save a lot of time, and even the maximum acceleration ratio is 30 times. Both word similarity/relatedness tasks, medical domain entity and relation extraction tasks, and temporal word evolution are evaluated as benchmarks for the word correctness and eﬃciency of the incremental learning word vectors.
Bandwidth Enhancement of Array Microstrip Antenna Using Spiral Stub For 5G Communication System

This paper proposes a new design of a 2x2 microstrip array antenna with spiral stub for a 5G communication system at the resonant frequency of 3.5 GHz. Spiral stub is useful for increasing the bandwidth value of the proposed antenna. The spiral stub is designed using a microstrip line with an impedance of 70.7 ohms. This study proposes three antenna models by adjusting the number and dimensions of the spiral stubs. From the simulation results using EM Simulation, the optimal bandwidth is obtained when the number of spiral stubs (n) = 3 with dimensions of spiral stub Wstub =18.5 mm and Ls = 8 mm . The bandwidth of the proposed antenna is 0.8 GHz or an increase until 88.88% compared with array 2x2 without spiral stubs. Furthermore, the gain of the proposed antenna is 10.67 dB at the resonant frequency of 3.5 GHz. This research is very useful for increasing bandwidth for the purposes of 5G communication systems. Streszczenie. W artykule zaproponowano nowy projekt anteny mikropaskowej 2x2 ze spiralnym odgałęzieniem dla systemu komunikacji 5G na częstotliwości rezonansowej 3,5 GHz. Spiralny odcinek jest przydatny do zwiększania wartości szerokości pasma proponowanej anteny. Spiralny króciec został zaprojektowany z wykorzystaniem linii mikropaskowej o impedancji 70,7 omów. W niniejszym opracowaniu zaproponowano trzy modele anten, dostosowując liczbę i wymiary końcówek spiralnych. Z wyników symulacji z wykorzystaniem symulacji EM optymalną szerokość pasma uzyskuje się, gdy liczba króćców spiralnych (n) = 3 o wymiarach króćca spiralnego Wstub =18,5 mm i Ls = 8 mm . Przepustowość proponowanej anteny wynosi 0,8 GHz lub jest wyższa o 88,88% w porównaniu z macierzą 2x2 bez spiralnych odgałęzień. Ponadto zysk proponowanej anteny wynosi 10,67 dB przy częstotliwości rezonansowej 3,5 GHz. Badania te są bardzo przydatne do zwiększania przepustowości na potrzeby systemów komunikacji 5G. (Poprawa przepustowości anteny mikropaskowej za pomocą spiralnego złącza dla systemu) komunikacji 5G)
The UK COVID-19 furlough scheme and associations with smoking, alcohol consumption and vaping: evidence from 8 UK longitudinal population surveys.

Background: Disruptions to employment status can impact smoking and alcohol consumption. During the COVID-19 pandemic, the UK implemented a furlough scheme to prevent job loss. We examine how furlough was associated with participants smoking, vaping and alcohol consumption behaviours in the early stages of the pandemic. Methods: Data were from 27,841 participants in eight UK adult longitudinal surveys. Participants self-reported employment status and current smoking, current vaping and drinking alcohol (>4 days/week or 5+ drinks per typical occasion) both before and during the pandemic (April-July 2020). Risk ratios were estimated within each study using modified Poisson regression, adjusting for a range of potential confounders, including pre-pandemic behaviour. Findings were synthesised using random effects meta-analysis. Sub-group analyses were used to identify whether associations differed by gender, age or education. Results: Compared to stable employment, neither furlough, no longer being employed, nor stable unemployment were associated with smoking, vaping or drinking, following adjustment for pre-pandemic characteristics. However, some sex differences in these associations were observed, with stable unemployment associated with smoking for women (ARR=1.35; 95% CI: 1.00-1.82; I2: 47%) but not men (0.84; 95% CI: 0.67-1.05; I2: 0%). No longer being employed was associated with vaping among women (ARR=2.74; 95% CI: 1.59-4.72; I2: 0%) but not men (ARR=1.25; 95% CI: 0.83-1.87; I2: 0%). There was little indication of associations with drinking differing by age, gender or education. Conclusions: We found no clear evidence of furlough or unemployment having adverse impacts on smoking, vaping or drinking behaviours during the early stages of the COVID-19 pandemic in the UK, with differences in risk compared to those who remained employed largely explained by pre-pandemic characteristics.