Miracle-dz/UniFAR-FTUs huggingface dataset:
Big Data Analytics Adoption for Cyber-security: A Review of Current Solutions, Requirements, Challenges and Trends

: With the continuous advancements of technology, cyber-criminals accordingly develop sophisticated tactics to exploit vulnerabilities in individual systems, organization networks, and nation-states. Enterprises routinely collect huge amount of security-relevant data such as log events of people, networks, and software applications for future forensic analysis. Existing traditional security analysis tools fail to work well with large scales of data and usually produces high false alarms especially when the enterprises moves to cloud architecture and collect more data. Moreover, the detection of recent and more sophisticated attacks, like advanced persistent threats (APTs), requires continuous monitoring and analysis of huge security related data, accurately and rapidly. Big Data analytics has been in active use in several fields such as financial transactions, healthcare and industrial applications among others. Recently, it has attracted the attention of information security audience due to its promised ability in correlating security related data and draw insights efficiently at unprecedented scale. In this paper, we analyze the traditional technology/systems and Security Information and Event Management (SIEM) tools and show their shortcomings in dealing with huge data scales and advanced sophisticated threats. We then explore the requirements for Big Data analytics to be successfully adopted in cyber threat intelligence and cyber-security landscape to deal with high data scales and sophisticated threats. Finally, we highlight the challenges resulted from such adoption, and suggest some recommendations to overcome adoption challenges in future research.
Should Patients with Kearns-Sayre Syndrome and Corneal Endothelial Failure Be Genotyped for a TCF4 Trinucleotide Repeat, Commonly Associated with Fuchs Endothelial Corneal Dystrophy?

The aim of this study was to describe the ocular phenotype in a case with Kearns-Sayre syndrome (KSS) spectrum and to determine if corneal endothelial cell dysfunction could be attributed to other known distinct genetic causes. Herein, genomic DNA was extracted from blood and exome sequencing was performed. Non-coding gene regions implicated in corneal endothelial dystrophies were screened by Sanger sequencing. In addition, a repeat expansion situated within an intron of TCF4 (termed CTG18.1) was genotyped using the short tandem repeat assay. The diagnosis of KSS spectrum was based on the presence of ptosis, chronic progressive external ophthalmoplegia, pigmentary retinopathy, hearing loss, and muscle weakness, which were further supported by the detection of ~6.5 kb mtDNA deletion. At the age of 33 years, the proband’s best corrected visual acuity was reduced to 0.04 in the right eye and 0.2 in the left eye. Rare ocular findings included marked corneal oedema with central corneal thickness of 824 and 844 µm in the right and left eye, respectively. No pathogenic variants in the genes, which are associated with corneal endothelial dystrophies, were identified. Furthermore, the CTG18.1 genotype was 12/33, which exceeds a previously determined critical threshold for toxic RNA foci appearance in corneal endothelial cells.
EXTRACTION OF ROCKS AND BOULDERS ON NATURAL TERRAIN USING SEMANTIC SEGMENTATION

: The geological mapping for the rock outcrop and boulders distribution on countryside is necessary for support hazard and risk management. Different approaches were proposed to detect and identify the rock outcrop and boulders based on remote sensing technology in literature. Given the latest development in technology, using traditional remote sensing methods to detect the rocks and boulders in VHR aerial imagery is still challenging. The complicated background noise prohibits the precision and accuracy of identifying the targets as well as their boundaries detection. Currently, deep neural networks (DNNs) have been demonstrating its outstanding performance on feature extraction which has been widely used in the computer vision. The semantic image segmentation is a pixel-level classification model, which is appropriate to the rock and boulder detection due to the model itself can segment very dense and detailed features over VHR imagery. In this paper, an optimized FCN-DenseNet was proposed to detect the rock outcrops and boulders in Hong Kong. Since the sizes of the rocks and boulders are variated, the neural network should be employed with multi-scale pooling to extract low/high-level features. As the contexts of the rocks and background terrain are similar, the pyramid dense blocks were employed to enhance the capability of self-feature-extraction. Our proposed boulder-net was evaluated over the VHR imagery in Hong Kong. The results show that the rocks and boulders are identified and classified and the boundaries of the rocks are accurately segmented.
Product Proliferation as Price Obfuscation? Evidence from the Mortgage Market

This paper provides a supply-driven explanation behind price dispersion and product proliferation in the mortgage market: given the salient cost dimension, interest rates, firms can issue new products and adjust prices via a secondary cost dimension, fees, to appear cheap to consumers who fail to minimize total cost. Hence non-salient fees may allow lenders to obfuscate prices and make the true cost ranking more difficult to read for consumers. I provide a framework in which I can test for this supply-side mechanism empirically, by studying lenders’ price adjustment and product strategies in response to firm-specific shocks to funding cost. Using novel data on the universe of mortgage products on offer in the UK, I show that lenders maintain competitive interest rates, but raise fees and the number of product alternatives with different fees when their funding costs increase relative to other lenders. In loan-level data, I indeed find lower excess cost dispersion, as a measure of search outcomes, for products without fees compared to products with fees, suggesting that supply-driven motives may help explain suboptimal search in the mortgage market, by exacerbating existing demand-side search frictions. JEL classification: G1, D12, D18
Synergistic Effects of Different Levels of Genomic Data for the Staging of Lung Adenocarcinoma: An Illustrative Study

Lung adenocarcinoma (LUAD) is a common and very lethal cancer. Accurate staging is a prerequisite for its effective diagnosis and treatment. Therefore, improving the accuracy of the stage prediction of LUAD patients is of great clinical relevance. Previous works have mainly focused on single genomic data information or a small number of different omics data types concurrently for generating predictive models. A few of them have considered multi-omics data from genome to proteome. We used a publicly available dataset to illustrate the potential of multi-omics data for stage prediction in LUAD. In particular, we investigated the roles of the specific omics data types in the prediction process. We used a self-developed method, Omics-MKL, for stage prediction that combines an existing feature ranking technique Minimum Redundancy and Maximum Relevance (mRMR), which avoids redundancy among the selected features, and multiple kernel learning (MKL), applying different kernels for different omics data types. Each of the considered omics data types individually provided useful prediction results. Moreover, using multi-omics data delivered notably better results than using single-omics data. Gene expression and methylation information seem to play vital roles in the staging of LUAD. The Omics-MKL method retained 70 features after the selection process. Of these, 21 (30%) were methylation features and 34 (48.57%) were gene expression features. Moreover, 18 (25.71%) of the selected features are known to be related to LUAD, and 29 (41.43%) to lung cancer in general. Using multi-omics data from genome to proteome for predicting the stage of LUAD seems promising because each omics data type may improve the accuracy of the predictions. Here, methylation and gene expression data may play particularly important roles.
Analog modulation properties of oxide confined VCSELs at microwave frequencies

Motivated by the need for affordable, high-performance fiber-optic microwave links in fiber-fed microcellular networks and radar systems, we have performed a comprehensive experimental evaluation of the microwave modulation characteristics of high-speed oxide-confined vertical cavity surface emitting lasers (VCSELs) emitting at 840 nm. VCSELs with different oxide aperture diameters, including both single- and multimode lasers, have been used to track the dependence on modal behavior. The study includes both static and dynamic characteristics, with an emphasis on those of major importance for analog modulation. This includes the small-signal modulation response (S/sub 11/ and S/sub 21/), the relative intensity noise (RIN), and the intermodulation distortion. From this, we determine the spurious free dynamic range, the impedance characteristics, and the speed limitations.
Peer-to-Peer Cooperative Positioning between GNSS Receivers

Global navigation satellite system (GNSS)-like the Global Positioning System (GPS) and the future Chinese Beidou system-can deliver very good position estimates under optimum conditions. However, especially in critical positioning scenarios like urban canyons or indoor environments the performance loss would be very high or GNSS based positioning is even not possible. Based on the concept of Cooperative Positioning in acquiring real-time positioning information of mobile robots, GNSS Peer-to-Peer Cooperative Positioning (P2P-CP) technology is proposed to overcome the shortage of GNSS positioning. Terrestrial ranging and communication modular are equipped with GNSS receivers to construct real-time CP network. The terrestrial ranging and communication modular respectively used for distance measurement and communication between nearby GNSS receivers, distributed algorithms are applied to fuse pseudorange and neighbors nodes distance to calculate the nodes position. Current research results of GNSS CP show that this new positioning strategy gets equal or better precision with less time cost compared with Assisted GNSS (AGNSS).
Measuring the dynamic interaction between electric vehicle shoegear and the third rail

The mechanical interface between vehicle-mounted shoegear and the third rail is critically important to the smooth running of electrically powered railway vehicles. An investigation is being undertaken into the static and dynamic interactions between shoegear and the third rail. This is being done by instrumenting the shoegear of a class 375 railway vehicle in the UK.
The Melon Zym Locus Conferring Resistance to ZYMV: High Resolution Mapping and Candidate Gene Identification

Zucchini yellow mosaic virus (ZYMV; potyviridae) represents a major pathogen of Cucurbitaceae crops. ZYMV resistance in melon PI 414723 is conditioned by a dominant allele at the Zym locus. This resistant accession restricts viral spread and does not develop mosaic symptoms, but necrosis sometimes develops in response to inoculation. In previous studies, Zym has been mapped to linkage group II of the melon genetic map. In the present study, positional cloning of the locus was undertaken, starting from the CM-AG36 SSR marker at approximately 2 cm distance. We utilized five mapping populations that share the same resistant parent, PI 414723, and analyzed a total of 1630 offspring, to construct a high-resolution genetic map of the Zym locus. Two melon BAC libraries were used for chromosome walking and for developing new markers closer to the resistance gene by BAC-end sequencing. A BAC contig was constructed, and we identified a single BAC clone, from the ZYMV susceptible genotype MR-1, that physically encompasses the resistance gene. A second clone was isolated from another susceptible genotype, WMR 29, and the two clones were fully sequenced and annotated. Additional markers derived from the sequenced region delimited the region to 17.6 kb of a sequence that harbors a NAC-like transcription factor and, depending on the genotype, either two or three R-gene homologs with a CC-NBS-LRR structure. Mapping was confirmed by saturating the map with SNP markers using a single mapping population. The same region was amplified and sequenced also in the ZYMV resistant genotype PI 414723. Because numerous polymorphic sites were noted between genotypes, we could not associate resistance with a specific DNA polymorphism; however, this study enables molecular identification of Zym and paves the way to functional studies of this important locus.
Acupuncture versus Lornoxicam in the Treatment of Acute Renal Colic: A Randomized Controlled Trial

Objective To compare the analgesic efficacy and safety of acupuncture and lornoxicam in acute renal colic (ARC). Design, Setting, Participant A randomized, double-blind, parallel-controlled, single-centered trial was conducted at Susong County People’s Hospital from October 2019 to November 2020. Eighty-four patients with ARC were randomly divided into lornoxicam group (Group L) and acupuncture group (Group A). Group A was treated with acupuncture at Sanyinjiao (SP6), Yinlingquan (SP9) and normal saline, and Group L was treated with sham acupuncture at SP6, SP9 and lornoxicam. Main Outcome Measures Visual analogue scale (VAS) scores and adverse reactions such as nausea and dizziness were recorded within 5, 10, 15, 20 and 40 minutes after treatment. The main outcome of this study was the short-term effective (STE) rate, the secondary outcome was the onset time, and the safety index was incidence of adverse reactions. Results A total of 80 patients completed this study, including 41 patients (21 males and 20 females) in Group L and 39 patients (21 males and 18 females) in Group A. Group A exhibited lower scores versus group L after treatment (P < 0.05). The overall STE of group L was 61.00% (25/41), significantly lower than group A [84.62% (33/39)] (P < 0.001). There was no difference in the incidence of adverse reactions between group A [2.6% (1/39)] and group L [7.3% (3/41)] (P = 0.616). The ordered logistic regression analysis showed patients receiving acupuncture therapy are more likely to be cured [OR = 2.887, 95% CI: (1.190, 7.000), P = 0.019]. Conclusion Acupuncture at SP6, SP9 and intramuscular injection of lornoxicam can effectively and safely relieve ARC, but the former has faster and better analgesic effect. Moreover, the incidence of adverse reactions was similar between the two treatments. This acupuncture therapy is recommended as a complementary therapy for ARC.
Sliding Mode Dynamic Torsional Load Control of Double-Fed Wind Turbine Drive-Train

Wind energy is one of the most competitive renewable energies, load has become the problem which has to be taken into consideration with larger capacity and flexibility. Due to drive-train damping was small and torsional load was large by traditional constant torque control (CTC) at above rated wind speed, a dynamic torsional load control (DTLC) was presented based on state feedback and sliding mode control. The method reduced the fluctuation of low speed shaft torque by decreasing equivalent torsional displacement difference. The model and controller were simulated in MATLAB/Simulink, the results demonstrate its effectiveness.
Biometric technologies and the prospect of sustainable democracy in Africa

The paper interrogates the prospect of attaining sustainable democracy in Africa using biometric technology (BT) for elections. Technology has become relevant in virtually every aspect of human endeavour, including election management and democratic development. In Africa, BT has also been deployed to improve the quality of elections and democracy. Using document analysis and review of relevant literature, findings indicate that to a large extent, BT is charting the path for sustainable democracy in Africa. However, the deployment of BT for African elections still faces serious challenges such as its high cost, inability to address some forms of electoral fraud, and lack of technical know-how. The paper concludes that the cultivation of political will to improve the quality of elections is important in order to address the current challenges of using BT in African elections and increase the prospect of attaining sustainable democracy.
Improvements in losses and size of frequency tunable coplanar filter structures using MMIC negative resistance chips for multistandard mobile communication systems

A new band-pass filter design technique is presented that uses coplanar passive interdigitated filters assisted by an MMIC active component which performs a negative resistance with an associated imaginary part in order to compensate for the losses of the passive filter and to reduce significantly the length of the resonators. A tunable version of the filter is also presented.
Effects of Soil Water Salinity on Field Soil Hydraulic Functions

Unsaturated soil hydraulic parameters and functions used in numerical models to simulate water flow and solute transport in the unsaturated zone are generally considered invariant of soil water salinity levels. This study uses 5 years of field soil water salinity levels at three observation sites from the Land Retirement Demonstration Project (LRDP) (2006) located in western Fresno County, California, to test the hypothesis that field unsaturated soil hydraulic properties are also a function of soil water salinity level. The HYDRUS-1D software package for simulating one-dimensional (1D) movement of water, heat, and multiple solutes in variably saturated media, and Parameter Estimation (PEST), a model-independent parameter optimizer, is used to optimize the soil hydraulic parameters and downward bottom flux corresponding to three different average soil salinity levels at each site. The results show that at the same pressure head, soil water content is less with higher soil water salinity as compared with l.
An experimental study revisiting the link between media attention and breast cancer concern: exploring the role of cognitive fusion

ABSTRACT Research examining the link between media attention and breast cancer concern has been frequently conducted with middle/old-age women, even though young women (<40 years old) have been overrepresented media stories about breast cancer. Accordingly, little is known about young women’s emotional reactions to breast cancer media messages and the psychological factors modulating such reactions. This study examined the impact of breast cancer media messages and cognitive fusion on negative affect, fear of breast cancer (FBC), and perceived susceptibility to breast cancer. 207 young women were randomly assigned to watch a low- or high-threat video about breast cancer. A MANCOVA revealed that participants who viewed the high-threat video reported greater negative affect and perceived susceptibility, but not FBC; however, participants in both conditions showed moderate/high FBC. Correlational analyses and a MANOVA showed that participants reporting higher cognitive fusion reported higher negative affect across conditions, as well as higher FBC in the high-threat condition. Taken together, these results suggest that young women may show habituation to alarmist media messages, but may nonetheless construe breast cancer as a significant threat. Moreover, young women showing medium/high cognitive fusion seem more likely to show heightened concern upon exposure to alarmist media messages about breast cancer.
Students’ Perception towards the Usefulness and Satisfaction of Practical Biochemistry Skills in a Public University versus Private University in Khartoum, Sudan (2019)

Practical biochemistry skills (PBS) teaching sessions employ experiential learning techniques to promote medical students’ understanding and recall of essential concepts and basic clinical tests. Biochemistry Practical skill sessions constitute about 45% of the contact teaching hours and between 10% - 20% of the final assessment grades, in addition the students are unacquainted about the method of assessment used. This cross sectional institutional based study aimed to assess medical students’ perception towards the practical biochemistry skills (PBS). Medical students in one public (Al-Neelain) and one private (Al-Moughtarbeen) universities, in Khartoum State were involved. After ethical approval, the questionnaire was approved after using it in a pilot study. Data collected by a questionnaire were analyzed using (SPSS version 22). Private university students have more satisfaction (58% versus 18%, p<0.001), more positive perception with PBS (49.5% versus 15.1%, p<0.001) and are more convinced that it helps to retain knowledge (68.3% versus 12.9%, p<0.001). They are more satisfied with laboratory environment (p<0.001), PBS relation to theory (p<0.001) and more aware of PBS assessment and scores allocation (p≤0.002). Medical student satisfaction and engagement with Practical biochemistry skills is likely to be driven by the students’ awareness of the relevance of these sessions to other aspects of the curriculum, to their end-of-year assessment, and to their future clinical practice rather than the laboratory environment. In conclusion, we recommend updating Practical biochemistry skills contents and assessment methods and raising students’ awareness of its importance.
Domain-general conflict monitoring predicts neural and behavioral indices of linguistic error processing during reading comprehension

The ability to detect and respond to linguistic errors is critical for successful reading comprehension, but these skills can vary considerably across readers. In the current study, healthy adults (age 18-35) read short discourse scenarios for comprehension while monitoring for the presence of semantic anomalies. Using a factor analytic approach, we examined if performance in non-linguistic conflict monitoring tasks (Stroop, AX-CPT) would predict individual differences in neural and behavioral measures of linguistic error processing. Consistent with this hypothesis, domain-general conflict monitoring predicted both readers’ end-of-trial acceptability judgments and the amplitude of a late neural response (the P600) evoked by linguistic anomalies. Interestingly, the influence on the P600 was non-linear, suggesting that online neural responses to linguistic errors are influenced by both the effectiveness and efficiency of domain-general conflict monitoring. These relationships were also highly specific and remained after controlling for variability in working memory capacity and verbal knowledge. Finally, we found that domain-general conflict monitoring also predicted individual variability in measures of reading comprehension, and that this relationship was partially mediated by behavioral measures of linguistic error detection. These findings inform our understanding of the role of domain-general executive functions in reading comprehension, with potential implications for the diagnosis and treatment of language impairments.