Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of biological activities of onion from Turkey and determination of phytochemical contents

: Allium cepa L. belonging to Amaryllidaceae, is considered to be one of the most cultivated and consumed vegetable in the world. Besides nutritional value, as medicinal usage has also been reported. Onion has been cultivated widely and used as a vegetable mainly, in Turkey. Treatment of wounds, abscess, hemorrhoids, arteriosclerosis, gynecological problems, urinary inflammation, headache, cough by usage of onion and its diuretic and hypoglycemic activities are recorded in Turkish folk medicine. In this study, antimicrobial, antioxidant, anti-inflammatory activities and total phenolic-flavonoid contents of red, white and yellow onion samples from Ankara-Turkey, were investigated. The peels and tissues of onion samples were extracted by sonication with 80% ethanol at room temperature. Phytochemical contents were investigated by High Performance Liquid Chromatography. The highest amount of quercetin was detected in red onion peel (0.3169 mg/100 mg); and protocatechuic acid in yellow onion peel (0.3492 mg/100 mg). Determining the antimicrobial activities against Staphylococcus aureus, Enterococcus faecalis, Escherichia coli, Pseudomonas aeruginosa by using microbroth dilution method, peel extracts exhibited higher activity than tissues. Yellow onion peel displayed the best 2,2’-azino bis (3-ethylbenzothiazoline-6-sulphonic acid) and 2,2-diphenyl-l-picrylhydrazyl scavenging activity (IC 50 =0.0125 and 0.0433 mg/ml, respectively) and also human red blood cell membrane stabilization activity which was used as a marker of anti-inflammatory activity (IC 50 =0.5363 mg/ml). Supporting these biological activities, the highest flavonoid content was determined in yellow onion peel (186.9250 mg QE/g crude extract). Additionally, red onion peel displayed the highest superoxide anion radical scavenging activity (IC 50 =0.0987 mg/ml). All results have revealed that peel extracts possessed higher activity than tissues.
Results of studies on extending the time operation of gin and linter grates

Results of studies on extending the time operation of gin and linter grates by hardening of the working area by high-frequency current are given in article. Mathematical models for calculation of key parameters of the mode of hardening of the working area of gin and linter grates are made. As a result of the executed researches the following conclusions are drawn: change of a gap between grates in a grate lattice leads to change of parameters of process of ginning and finally to deterioration of products. Mathematical models for calculations of parameters of process of hardening of the working area of grates are received. On the received mathematical models key parameters of hardening process current of high frequency which have the following values are calculated: depth of the tempered layer – 2.0 mm, the optimum frequency of current – 60000, specific power – 500 W/cm2, hardening time – 10, studying hardness tempered and not tempered sites of grates by method of Rockwell showed increase in hardness of the tempered site to HRC 55 against HRC 45 at not tempered by the working area.
LoRa-LiSK: A Lightweight Shared Secret Key Generation Scheme for LoRa Networks

Physical-layer security (PLS) schemes use the randomness of the channel parameters, namely, channel state information (CSI) and received signal strength indicator (RSSI) to generate the secret keys. There has been limited work in PLS schemes in long-range (LoRa) wide-area networks (LoRaWANs) which hinder their widespread application. Limitations observed in existing studies include the requirement of high correlation between channel parameter measurements for secret key generation in the proposed schemes and the evaluation of the schemes has only been done in either fully indoor or outdoor environments. The real-world wireless sensor networks (WSNs) and LoRa use cases might not meet both requirements thus making the current PLS schemes inappropriate for these systems. By considering the limitations found in existing PLS schemes, this article proposes LoRA-LiSK, a practical and efficient shared secret key generation scheme for LoRa networks. Our proposed LoRa-LiSK scheme consists of several preprocessing techniques (timestamp matching, two sample Kolmogorov–Smirnov tests, and a Savitzky–Golay filter), multilevel quantization, information reconciliation using Bose–Chaudhuri–Hocquenghem (BCH) codes, and finally, privacy amplification using secure hash algorithm SHA-2. The LoRa-LiSK scheme is extensively evaluated on real WSN/IoT devices in practical application scenarios: 1) indoor to outdoor and 2) LoRa static and mobile outdoor links. It outperforms existing schemes by generating keys with channel parameter measurements of low correlation values (0.2–0.6), while still essentially achieving high key generation rates, and low key disagreement rates (10%–20%). The scheme updates a key in approximately 1 h using an application profile with high transmission rate compared to 3 h reported by existing works while still respecting the duty cycle regulation. It also incurs less communication overhead compared to the existing works.
Design and Modeling of Dual-Band Dual-Mode Coupled Shorted Patch Antennas

This article presents the coupled shorted patch antennas (CSPAs), which exhibit dual-band operation of both broadside and conical radiation patterns and successfully overcome the major disadvantage of the large H-plane cross-polarization radiation of conventional shorted patch antennas (SPAs). The basic concept behind this breakthrough innovation is to create and explore the coupled TM0,1/2 modes. It will be shown that the CSPAs provide the horizontally polarized broadside radiation under the odd coupled TM0,1/2 mode for the low band and vertically polarized conical radiation patterns under the even coupled TM0,1/2 mode for the high band, respectively. The CSPAs have smaller resonant sizes when compared with those of the conventional SPAs for broadside radiation. The sum of the two resonant frequencies for the CSPAs is twice of that for the corresponding conventional SPAs based on a single microstrip. The ratio of two resonant frequencies depends on the odd and even mode impedances of the coupled microstrips. The calculated results are validated with the simulated and measured ones.
In silico investigation of wound healing potential of some compounds in tubers of Asphodelus species with GSK3-β protein

: Wound healing is a process that involves biochemical processes such as inflammation and cell proliferation and is controlled by many proteins. It is known that one of the most effective factors in this process is the inhibition of GSK3-β protein. In current study, in silico wound healing activity of the some compounds found in the tubers of Asphodelus species used as a wound healing in traditional medicine were investigated. For this purpose, the interactions between the compounds and GSK3-β protein were studied in silico. As a result of the study, it has been determined that and stigmasterol, β-sitosterol and emodin molecules are effective.
Discrete Laplace Operator in the Space with a Fuzzy Partition

Differential operators deﬁnitely play an important role in image processing tasks. One of the most frequently used operator for this purpose is the Laplace operator, usually de-ﬁned as the divergence of a gradient of a function. Since images are considered as discrete objects, many applications require discrete version of this operator. But at the same time, these discrete Laplace operators should preserve certain properties known from the continuous case. Based on this fact, we present discrete variant of F-transform-based Laplace operator, satisfying such conditions. Moreover, Laplace operator can be also de-ﬁned axiaomatically, throughout its certain properties. Therefore, we propose a construction of such operator from the other side, just with notion of the inner product of the current space and its desired properties.
Scientific and Technological Resource Sharing Model Based on Few-Shot Relational Learning

SUMMARY Resource sharing is to ensure required resources available for their demanders. However, due to the lack of proper sharing model, the current sharing rate of the scientiﬁc and technological resources is low, impeding technological innovation and value chain development. Here we propose a novel method to share scientiﬁc and technological resources by storing resources as nodes and correlations as links to form a complex network. We present a few-shot relational learning model to solve the cold-start and long-tail problems that are induced by newly added resources. Experimentally, using NELL-One and Wiki-One datasets, our one-shot re-sults outperform the baseline framework - metaR by 40.2% and 4.1% on MRR in Pre-Train setting. We also show two practical applications, a resource graph and a resource map, to demonstrate how the complex network helps resource sharing.
Agricultural Financing and Food Security in Nigeria: An Empirical Assessment 1996-2019

: This paper seeks to examine the effect of agric financing on agric productivity in Nigeria for the period 1996 to 2019 and its implications for national food security. Multiple linear regression model was developed in order to unearth the nature of relationship between the model parameters in the period under review. Agric GDP was used as a proxy for agricultural productivity while agric credit guarantee, government expenditure on agriculture and Commercial banks’ credit to agricultural sector served as proxies for agricultural financing. Results show overwhelming evidence that all the regressors have a positive and highly significant effect on agricultural productivity. Consequent upon on the findings of this study, it was recommended that the government should come up with policies aimed at incentivizing private investors and deposit money banks to advance the much-needed credit for the agric sector since government cannot do it all. All these and more if well implemented, will make our dear country Nigeria to achieve the much need food security. The study is also of the opinion that diligent and painstaking approach should be adopted in the process of implementing such policies so that funds meant for agric sector does not end up in the hands of middlemen who camouflage as the real farmer.
Reinforcement Learning-Based Near-Optimal Load Balancing for Heterogeneous LiFi WiFi Network

Owing to the nonoverlapping spectrum, light fidelity (LiFi) and WiFi technologies can coexist and form a heterogeneous LiFi WiFi network (HLWN). The performance of HLWN significantly depends upon the load balancing strategies. Since load balancing of HLWN is a nonconvex mixed-integer nonlinear programming optimization problem, it is mathematically intractable, and therefore, the conventional optimization methods fail to provide an optimal global solution. Although an optimal solution can be obtained using the exhaustive search method, it would be computationally complex. Therefore, in this article, a reinforcement learning (RL)-based algorithm is explored for solving the load balancing problem for the downlink HLWN at reasonably low complexity and near optimal performance. We have proposed three different reward functions for RL; the first and second reward functions work toward maximizing average network throughput and user satisfaction, respectively. The third reward function is designed to maximize the long-term system throughput and ensure at least 50% user’s satisfaction for all users. In order to study the effects of link aggregation on the system performance, this article considers two different types of receiver schemes, namely, single access point (SAP) and link aggregation (LA) scheme. While the SAP allows the user to receive data only from an SAP, the LA scheme allows the user to receive data simultaneously from both LiFi and WiFi AP. This article also includes effect of random orientation of the receiver device and handover overhead. Furthermore, concepts of domain knowledge have been included in this article to reduce the computational complexity of the algorithm. The proposed system performance is compared with the the following two benchmarks: received signal strength (RSS) and exhaustive search based on the computational complexity, average system throughput, and user satisfaction. It is shown that the proposed RL scheme outperforms the RSS scheme in average system throughput and user satisfaction. The RL scheme with an appropriate reward function provides a matching performance to the exhaustive search at reasonably low complexity.
High temperature associated microRNAs and their potential roles in mediating heat tolerance in the leaf of banana inoculated with Serendipita indica

ABSTRACT Serendipita indica (S. indica) is an endophytic root fungus that sustains the growth and enhances tolerance of plants to biotic and abiotic stresses. However, little is known on the symbiosis mediated high temperature stress (HT) tolerance regulated at microRNAs (miRNAs) level. In this study, we have elucidated the impact of miRNAs in regulating the S. indica-mediated heat tolerance in the leaves of ‘Tianbao’ banana (Musa acuminata cv.). The small RNA (sRNA) sequence analysis of the leaves of ‘Tianbao’ banana inoculated and exposed to HT of 45°C established a set of 278 differentially abundant miRNAs in response to HT stress. These included 185 known miRNAs differentially expressed (DE) and 93 novel miRNAs. GO and KEGG analysis showed that the DE miRNAs were significantly associated with nutrient sources uptake, secondary metabolism, growth regulators, auxin-responsive factor, signal transduction pathways. In summary, our study revealed that miRNA play important regulatory roles during the banana-HT tolerance by regulating the genes involved in heat shock protein, peroxidase, transcription factor, phenylalanine, sucrose synthase, protein kinase, 7-hydroxymethyl chlorophyll. Our result unravelled a framework for future functional analysis of selected miRNAs and their targets in response to HT stress, which may contribute towards the future development of S. indica application to plants.
A Saturated Amorphous Alloy Core-Based Inrush Current Limiter to Eliminate Inrush Currents and Restrain Harmonics during Transformer Energization

In this article, a new saturated amorphous alloy core-based inrush current limiter (ICL) has been designed and built to limit the inrush current of a power transformer. A toroidal core with a middle limb is developed using the Metglas amorphous alloy and the middle limb is excited with a dc current to saturate the amorphous alloy core. Only a very small dc excitation current is required using such a core when compared to that using a similar design with conventional materials. Under normal conditions, the saturated amorphous alloy ICL core steady-state impedance is low and has a negligible effect on the operation of the system. During the energization of a power transformer connected to the ICL, the large inrush current desaturates the amorphous alloy core, resulting in an increase in the ac winding impedance, which limits the peak amplitude of the transformer inrush current and harmonics. To validate the proposed saturated amorphous alloy core-based ICL, a prototype ICL has been built and tested in the laboratory. The experimental results show that the core power loss, core saturation, the fundamentals, and harmonics of the inrush current of the proposed saturated amorphous alloy core-based ICL are significantly better compared with those from the sheet steel core-based ICL. It is expected that the proposed saturated amorphous alloy core will be used in future inrush current limiters that can help to improve the performance of the power transmission and distribution system.
Blockchain-Based Cross-Domain Authentication for Intelligent 5G-Enabled Internet of Drones

While 5G can facilitate high-speed Internet access and make over-the-horizon control a reality for unmanned aerial vehicles (UAVs; also known as drones), there are also potential security and privacy considerations, for example, authentication among drones. Centralized authentication approaches not only suffer from a single point of failure but they are also incapable of cross-domain authentication. This complicates the cooperation of drones from different domains. To address these limitations, a blockchain-based cross-domain authentication scheme for intelligent 5G-enabled Internet of drones is proposed in this article. Our approach employs multiple signatures based on threshold sharing to build an identity federation for collaborative domains. This allows us to support domain joining and exiting. Reliable communication between cross-domain devices is achieved by utilizing smart contract for authentication. The session keys are negotiated to secure subsequent communication between two parties. Our security and performance evaluations show that the proposed scheme is resistant to common attacks targeting Internet of Things (IoT) devices (including drones), as well as demonstrating its effectiveness and efficiency.
Going Deeper into OSNR Estimation with CNN

As optical performance monitoring (OPM) requires accurate and robust solutions to tackle the increasing dynamic and complicated optical network architectures, we experimentally demonstrate an end-to-end optical signal-to-noise (OSNR) estimation method based on the convolutional neural network (CNN), named OptInception. The design principles of the proposed scheme are specified. The idea behind the combination of the Inception module and finite impulse response (FIR) filter is elaborated as well. We experimentally evaluate the mean absolute error (MAE) and root-mean-squared error (RMSE) of the OSNR monitored in PDM-QPSK and PDM-16QAM signals under various symbol rates. The results suggest that the MAE reaches as low as 0.125 dB and RMSE is 0.246 dB in general. OptInception is also proved to be insensitive to the symbol rate, modulation format, and chromatic dispersion. The investigation of kernels in CNN indicates that the proposed scheme helps convolutional layers learn much more than a lowpass filter or bandpass filter. Finally, a comparison in performance and complexity presents the advantages of OptInception.
Image quality in chest tomography employing three different equipment technologies

Computed tomography represents the largest portion of the population´s exposure to ionizing radiation related to medical imaging. This article aims to assess the quality of the images through the analysis of radiologists in routine chest protocols, performed at one hospital and two diagnostic imaging clinics, and employing three equipment with different technologies. A total of 1,088 criteria were analyzed with the three imaging techniques, and the average percentage of the observed structures were 95, 99 and 99% for each service. There was an excellent correlation between observers and even an absolute agreement in some cases for the most modern technologies. The three studied devices provided acceptable dose values and images with a quality close to 100%, reducing the exposure and improving the radiological protection of patients.
Multi-scale and densely arranged target detection in SAR images with a gated feature pyramid network and oriented bounding boxes

Target detection in SAR images plays an important role in remote sensing, but still presents many challenges in the deep learning era. The deep learning-based detector performs well. However, the results also showed that the Faster R-CNN detector is not able to detect ships of different sizes and those that are densely arranged near the shore. In order to solve the two problems above, we propose a detector with a Gated Feature Pyramid Network and oriented bounding boxes. The Gated Feature Pyramid Network can selectively build a feature pyramid with channel-wise and space-wise attention modules. Channel-wise attention can be viewed as the process of selecting semantic attributes to detect ships with different scales. This is helpful for classification. Space-wise attention pays more attention to the semantic-related regions. This is helpful for localization. The oriented bounding boxes can locate ships tightly and thus recognize and locate them with a high level of accuracy, especially for the densely arranged ships. The anchors are also redesigned to best fit ships in SSDD+. Oriented Region-of-Interest aligning is used to generate a fixed-length vector without misalignment on small ships. Angle-related intersection-of-union is used to prepare positive and negative oriented proposals. It can compute the real overlap of two oriented bounding boxes. The multi-task loss function with angle information is used to train the model. The results of SSDD+ show that the proposed detector can adapt to complex situations with multi-scale and densely arranged ships.
Rethinking the education potential of older adults to delay the onset of dementia

This paper demonstrates the effects of education on cognitive functioning which could serve as an alternative preventive method to halt or delay cognitive decline in older adults. The purpose of this proposal is to discuss and illustrate the benefits of improving cognitive ability through continuing education. As such, taking advantage of educational programmes that are already in place would not only provide mental stimulation for older adults, but would be a source for social networking, as well as technology training and physical education activities. To establish a link between cognition and education, this paper provides examples from a number of studies as well as a review of a longitudinal study on educational differences in the prevalence of dementia. The findings of this systematic review revealed a connection between cognitive decline and education after considering regions and economic status. Suggestions from these reviews imply that keeping one’s mind stimulated could be influential in delaying the onset of dementia resulting in possibly extending the time older adults are independent.
Inference of recent admixture using genotype data

The inference of biogeographic ancestry (BGA) has become a focus of forensic genetics. Mis-inference of BGA can have profound unwanted consequences for investigations and society. We show that recent admixture can lead to misclassification and erroneous inference of ancestry proportions, using state of the art analysis tools with (i) simulations, (ii) 1000 genomes project data, and (iii) two individuals analyzed using the ForenSeq DNA Signature Prep Kit. Subsequently, we extend existing tools for estimation of individual ancestry (IA) by allowing for different IA in both parents, leading to estimates of parental individual ancestry (PIA), and a statistical test for recent admixture. Estimation of PIA outperforms IA in most scenarios of recent admixture. Furthermore, additional information about parental ancestry can be acquired with PIA that may guide casework.