Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection of Precancerous Cells and Incidence of Human Papillomavirus among Women of Reproductive Age Attending Selected Hospitals in Katsina

Infection with oncogenic or high risk human papillomavirus (hrHPV) types significantly triggers the development of cervical cancer. Cervical cancer is the most common female cancer in northern Nigeria, yet the pattern of infection with human papillomavirus, the principal aetiologic agent is unknown; besides, prevalence data that governs research and policy is often inadequate or nonexistent. This study aims to detect precancerous cells and elucidate the incidence of HPV in cervical cancer among women attending selected hospitals in Katsina State. This was a preliminary study conducted in two hospitals in order to establish base-line data on the incidence and risk factors for the infection in Katsina State, Nigeria. The employed study design was Hospital based and cross sectional, involving the use of structured questionnaires to obtain socio-demographic and clinical data. Sixty (60) randomly selected women aged 18 years and above were recruited from gynaecology clinics in General Hospital, Katsina and Turai Umar Yar'adua Maternal and Children Hospital (TUYMCH). Relevant sexual and socio-demographic information were obtained from each subject using a questionnaire. Sixty (60) cervical scraping samples were screened for both HPV and squamous intraepithelial llesion (SIL) using enzyme linked immunosorbent assay and conventional Papsmear, respectively. Data is presented in tables, and analyzed using the Graphpad Prism statistical software, version 69, at 0.05 level of significance and 95% confidence interval. The incidence rate of HPV infection obtained from ELISA test was 35% [(21/60)] and also 33.2% [(20/60)] with abnormal cytology results. Risk factors of the infection include low literacy levela; living in rural settlements; low parity; early menarche (< 15 years of age); early onset of first sexual intercourse (≤ 16 years of age) and multiple sexual partners with 48%. There was however, no statistically significant association between oral contraceptive usage and acquisition of the infections. The findings from this study have shown that there is a high possibility of detecting the DNA of hrHPV in women that are infected with HPV and those that have cervical dysplasia, which points out the possibility of these women developing cervical cancer. Further studies should be done using molecular screening techniques such as the linear Array, HPV Genotyping, and molecular characterization of HPV.
Influence of Salts on the Adsorption of Lysozyme on a Mixed-Mode Resin

Mixed-mode chromatography (MMC), which combines features of ion exchange chromatography (IEC) and hydrophobic interaction chromatography (HIC), is an interesting method for protein separation and purification. The design of MMC processes is challenging as adsorption equilibria are influenced by many parameters, including ionic strength and the presence of different salts in solution. Systematic studies on the influence of those parameters in MMC are rare. Therefore, in the present work, the influence of four salts, namely, sodium chloride, sodium sulfate, ammonium chloride, and ammonium sulfate, on the adsorption of lysozyme on the mixed-mode resin Toyopearl MX-Trp-650M at pH 7.0 and 25°C was studied systematically in equilibrium adsorption experiments for ionic strengths between 0 mM and 3000 mM. For all salts, a noticeable adsorption strength was observed over the entire range of studied ionic strengths. An exponential decay of the loading of the resin with increasing ionic strength was found until approx. 1000 mM. For higher ionic strengths, the loading was found to be practically independent of the ionic strength. At constant ionic strength, the highest lysozyme loadings were observed for ammonium sulfate, the lowest for sodium chloride. A mathematical model was developed that correctly describes the influence of the ionic strength as well as the influence of the studied salts. The model is the first that enables the prediction of adsorption isotherms of proteins on mixed-mode resins in a wide range of technically interesting conditions, accounting for the influence of the ionic strength and four salts of practical relevance.
Non-peer reviewed preprint submitted to EarthArXiv

Strain transfer analysis is an important means of correcting the measurement error of embedded or surface-bonded distributed fiber-optic sensors, but the effect of host strain patterns has not been well elucidated. Here, a theoretical model for strain transfer analysis of surface-bonded multi-layered fiber-optic sensor subjected to a linear gradient strain was established. Closed-form solutions were obtained for both singleand bi-linear strain distributions, and, in particular, a simple method was described for determining the strain transfer coefficient at the turning point of a bi-linear type strain. The presented model was validated through laboratory testing with high-spatial resolution strain profiles acquired by optical frequency-domain reflectometry. Furthermore, parametric analyses were performed to investigate the influences of mechanical and geometrical properties of protective and adhesive layers on the strain transfer performance, shading light on the design, installation, and measurement error correction of fiber-optic sensors after accounting for the effect of host strain distribution.
Carbon Dynamics in Humic Fractions of Soil Organic Matter Under Different Vegetation Cover in Southern Tocantins

Soil organic matter has great importance in chemical, physical and biological processes in soil-plant system. This study aimed to evaluate changes in carbon humic fractions of soil organic matter under different vegetation coverings in Cerrado in Tocantins, Brazil. The work was developed in Eucalyptus sp. , Pasture, Agriculture and Cerrado sensu stricto areas. Soil samples were collected in dry period, October, 2018, in trenches 70 x 70 cm at depths 0-10, 10-20, 20-30, 30-40 and 40-50 cm, with six replications. The vegetation cover in Eucalyptus sp. area showed higher levels of total carbon in soil humic fraction. Respectively fulvic acid, humic acid and humin in Eucalyptus sp. area had stocks of 22.09; 2.71 and 20.01% higher than native forest, 32.04; 2.57 and 35.59% higher than pasture and 10.59; 19.19 and 7.61% higher than the agriculture area. Among the different areas evaluated, the soil of Eucalyptus sp. has great potential to increase carbon storage in soil humic fractions.
Transport of continental air to the subantarctic Indian Ocean

The occurrence of high levels of atmospheric 222 Rn (radonic storms) at 3 subantarctic islands in the Indian Ocean is simulated with a 3-d chemical tracer model (CTM) based on the meteorology of the GISS general circulation model (GCM). Radon-222 (half-life 3.8 days) is a sensitive tracer of continental air over the oceans. The CTM simulates well the observed intensities of the radonic storms at the islands, their seasonal frequency (highest in winter), and their periodicity (25–28 days). The storms are due to fast boundary layer advection of air from South Africa, made possible by the conjunction of a subtropical high SE of Madagascar (Mascarene High) and a mid-latitudes low off the southern tip of the African continent. Transit times of air from South Africa to the islands range from 1 to 5 days. The Mascarene high is a semi-permanent feature of the circulation from May to October, and is responsible for the seasonal frequency of the radonic storms. The low is transient but exhibits an oscillation of period 23–28 days which appears to be responsible for the observed periodicity of the storms. Transport to the subantarctic Indian Ocean is the principal mechanism for ventilation of South Africa in the CTM, but most of this transport takes place in the free troposphere following deep convection over the continent. The boundary layer advection mechanism associated with radonic storms accounts for only a small fraction of the total continental air exported to the subantarctic Indian Ocean. DOI: 10.1034/j.1600-0889.1990. 00008.x
Decentralized Online Voting using Blockchain and Secret Contracts

Voting is a complex process with a lot depending on it. Building an e-voting system that can guarantee anonymity, verifiability, and transparency together is a challenging task. Continuous efforts are being made to improve the voting system to achieve these properties. Recently, blockchain has hit the technology space with many promises, especially to make verifiable and transparent decentralized systems. However, a major challenge faced with blockchain-based e-voting systems is to achieve the users’ anonymity while ensuring only authorized voters should be able to vote, and that too only once. To address these issues, this paper proposes a blockchain-based e-voting system with secret contracts. We have used Enigma (a secure multiparty computation platform) to design secret contracts. The proposed system meets most of the features required to conduct free and fair voting electronically.
A Multilevel Feature and Structure Prior Information-Based Positioning Approach for Catenary Support Components

The work state of catenary support components (CSCs) is essential for trains’ powering safety under high-speed operation. However, because of the difficulty of positioning the CSCs whose sizes are much different, some detection methods based on classical deep learning technologies only position one specific component, and the others that can position all categories CSCs have poor performance. A new position method for 12 categories of CSCs called CSC structure inference net (CSCSIN) is proposed in this article. This method is composed of three sections, including the feature extraction with a multilevel feature, feature inference with structure prior information, regression, and classification. In the feature extraction section, to extract small-scale CSCs’ features, a modified VGG16, which is used to generate a legible feature map based on the fusion of low and high layers’ features, is proposed, and multiscales anchors for RoIs prediction are applied to suit multiscale CSCs. In the feature inference section, considering application scenarios and fixed position relationship between CSCs, the scene visual feature and position information between targets are used to iteratively update each target state in structure inference net, and the final state of each target is used for its classification in regression and classification section. Based on the modification in the feature extraction section and the combination of relevant information of CSCs, CSCSIN is efficient and sensitive to all 12 CSCs whose scales are much different. The experimental results demonstrate that the position precision of CSCSIN is superior to other classical models and relevant methods.
Smart Locker System Acceptance for Rural Last-Mile Delivery

This study is a typical Information and Communications Technologies for Development (ICT4D) initiative that aims to bridge digital divides i.e. the gap between technological ‘haves' and ‘have nots' based on geographic locations. This study proposes the use of smart locker systems that are opened by pin codes, mobile applications, mobile USSDs, or RFID tags. These lockers will be placed at secure centres in rural areas e.g. hospitals or police stations and be used for the collection of parcels. Currently, most rural areas are under-serviced by logistics service providers as they do not have good roads and address systems. Anchoring on the Unified Theory of Acceptance and Use of Technology (UTAUT), this paper analyses attributes that affect a customer's intention to accept and use smart locker systems as a last-mile delivery method. The study has 56 voluntary participants from Gqala village (Eastern Cape, South Africa) who were divided into focus groups for interviews to be conducted. The data collected was coded and themes were identified, of the themes identified the strongest six are presented in this paper as propositions. These results highlighted some critical determinants of technology acceptance and use that are not reflected in the UTAUT. This study then also presents a modification of the UTAUT which the enhanced unified theory of acceptance and use of technology (EUTAUT) is coined from. The research work presented in this paper is transdisciplinary, hence, enriches the literature on information and communication technology (ICT), logistics, retail, e-commerce as well as psychology (human behaviour towards new technology)
Eigenvalue Decomposition of a Parahermitian Matrix: Extraction of Analytic Eigenvalues

An analytic parahermitian matrix admits an eigenvalue decomposition (EVD) with analytic eigenvalues and eigenvectors except in the case of multiplexed data. In this paper, we propose an iterative algorithm for the estimation of the analytic eigenvalues. Since these are generally transcendental, we find a polynomial approximation with a defined error. Our approach operates in the discrete Fourier transform (DFT) domain and for every DFT length generates a maximally smooth association through EVDs evaluated in DFT bins; an outer loop iteratively grows the DFT order and is shown, in general, to converge to the analytic eigenvalues. In simulations, we compare our results to existing approaches.
Automatic determination of the morphotropic phase boundary in lead magnesium niobate titanate Pb(Mg1/3Nb2/3)(1−x)TixO3 within a single crystal using birefringence imaging

A detailed phase diagram of Pb(Mg 1/3 Nb 2/3 ) (1-x) Ti x O 3 , conventionally abbreviated to PMN-PT, has been constructed around the morphotropic phase boundary from measurements taken from one single crystal possessing a composition gradient. Optical birefringence imaging was employed as a function of temperature to plot retardation and orientation information as a function of temperature and position within the crystal. Electron-probe microanalysis measured the composition across the crystal and this enabled the phase boundaries to be plotted to high precision. Cubic (C), rhomhohedral (R), tetragonal (T) and monoclinic (M) phases were observed, with the a C-R-T critical point at a composition x = 0.275 (4) at 394.7 (5)K on heating and at the same composition at 386.5 (5)K on cooling, in close agreement with phase diagrams suggested by published dielectric and diffraction experiments.
Alternative Solutions for Reducing the Undesired Coupling Effect in Stub Loaded Microstrip Filters for Ka-band Applications

This work characterizes the undesired coupling effect that appears in stub loaded microstrip Ka-band filters due to the propagation of surface waves. This effect limits the achievable isolation level in the stopband of this type of filters. To overcome this limitation, we propose two solutions: alternate the direction of the resonator stubs and implement the filter following a bent configuration. To validate these solutions in practical microstrip devices, four stopband filters in Ka-band are designed, manufactured and measured. The measurements demonstrate that these two strategies allow to improve the selectivity in the stopband, therefore improving the isolation level in stub loaded microstrip filters.
Diagnosis of Scan Chain Faults Based-on Machine-Learning

In order to improve yield of nanometer-scale chips, scan-based test and diagnosis are important. However, the scan chain can be subject to defects due to large hardware incurred by itself, which accounts for considerable portion of total chip area. Hence, scan chain test and diagnosis has played a critical role in recent years. In this paper, an efficient scan chain diagnosis method based on two-stage neural networks is proposed for not only stuck-at fault but also transition fault. Experimental results on benchmark circuits show that the proposed method is 10% more accurate than a previous work and CPU time for training the neural networks is also reduced dramatically.
A Dual-Mode Ground-Referenced Signaling Transceiver with a 3-Tap Feed-Forward Equalizer for Memory Interfaces

This paper describes a ground-referenced signaling (GRS) transceiver with a 3-tap feed-forward equalizer and low frequency mode. In the prototype transceiver, four DQ data lanes share one DQS clock-forwarding lane. To accommodate dynamic voltage and frequency scaling, the proposed transmitter operates in two modes depending on the frequency. The feed-forward equalizer's tap coefficients can be tuned by the pre-charged voltage levels and the number of activated segments. Fabricated in a 28-nm CMOS process, a single DQ block of the proposed GRS transceiver occupies 0.018 mm2. The voltage margin and timing margin were 29.7 mV and 51.6 ps when the equalizer is turned on, but the eye diagram with the equalizer turned off was almost closed with a 13.6-dB channel at at 10 Gb/s. The transceiver achieves BER < 10−13 while dissipating 12.9 mW per lane from a 0.85-V core power supply and 1-V I/O power supply.
The formation of efficient and inefficient social convention driven by conformity bias

Social conventions governs our social behavior in many ways, ranging from left- and right-hand traffic to a way of greeting. We sometimes find inefficient social conventions like bullying in a class are formed, where almost of the people in the group are at a disadvantage. Although such conventions can be disadvantageous for all the people in the group, why are those conventions formed and continue to be maintained? A conformity bias, behavioral tendency with which people take an action that a majority of the group take, can be one of key ingredients of this phenomena. In this study, we investigated the impact of the conformity bias to the formation of social convention with a multi-agent simulations. Analysing stationary states of the dynamics of the model, we found that the conformity bias can drive the formation of both of efficient and inefficient social convention depending on an extent of the bias.
Forced-Sleep SVR SRAM for High Frequency Applications

The present world with its fast-paced processing and data manipulation requires equally fast accessible data to match up to its performance and output. From temporary to permanent storage of data for the processors and devices, Static-Random-Access Memory (SRAM) has been one of the primary choices for industrialists, that it constitutes as memory in about 60% of the devices worldwide. Nevertheless, memories have proven to be one of the primary factors for power and delay issues in a handheld system, which demands the need for power optimization in memory devices at all times. This paper aims at designing and modifying the power dissipation in a single bit-cell of conventional 6T-SRAM to deduce a stable low power dissipating structure and verifies its stability by computing the performance parameter Power-Delay-Product (PDP) at various operating frequencies. The project made use of Tanner-EDA v16.01 to simulate the proposed structure and analyze the factors that contribute to power dissipation for optimizations. The proposed structure is observed to attain a power reduction of 62.273% compared to conventional 6T at an operating frequency of 2GHz. Furthermore, a 66.6033% decrease in PDP is also observed. Thus, a stable low power dissipating SRAM cell that is suitable for high frequency application is designed.
Reconfigurable PETPG for External Testing of Digital Circuits

In this paper, the application of the board-level external testing using the pseudo-exhaustive testing (PET) was explored. The new design approach to reconFigure the hardware of the pseudo-exhaustive test pattern generator (PETPG), based on the permutated convolved linear feedback shift register/shift register (LFSR/SR), is developed. The permutated convolved LFSR/SR is considered a superset of all previously published output-specific PETPGs in the PET with low test application time (TAT). The PET segments digital circuit-under-test (CUT) into several output cones. The proposed test system can stimulate all combinational hard faults in each output cone using the reconfigured PETPG without the need of the fault simulator, and to compact test responses of digital circuits for signature generation. The simulation results using some digital circuits, compared to previously published works, illustrate the effectiveness of the presented test approach to detect target faults with reduction of TAT.
An Exploration of Machine Learning Models to Forecast the Unemployment Rate of South Africa: A Univariate Approach

The South African unemployment rate is 29.1%, this is the highest unemployment rate that the country has recorded since the 1970s. The country is in the top ten countries with the highest unemployment rates in the world. COVID-19 threatens to increase the unemployment rate above the 50% mark. A public policy intervention is the most suitable instrument for the country in order to address this problem, however, policy is reliant on accurate and reliable forecasting. This paper explores univariate machine learning techniques to forecast the South African unemployment rate. Six traditional statistical models are compared with seven machine learning models. The multi-layer perceptron achieves the lowest error rate, whilst the ridge regression model achieved the highest R - squared. These are closely followed by ARIMA, LASSO, and the elastic net, showing that machine learning models can forecast the South African unemployment rate with higher accuracy than traditional statistical methods.
Morphologic and Surface Characterization of Different Types of Activated Carbon Fibres

This study provides a comparison of different types of commercially available activated carbon fibres (ACFs). Thus, ACFs in cloth (ACFC) and felt forms (ACFF) with three different surface areas were each analyzed for their pore volumes, pore sizes and pore-size distributions. The fibre morphology and organization was visualized using scanning electron microscopy (SEM). The microporosity of the ACF materials based on nitrogen isotherms, the percentage of micropores by area and volume, the average pore size and the pore-size distribution were also determined. An increase in the surface areas of the ACFC types led to an increase in the total pore volume, micropore volume, micropore area and pore width, but led to a decrease in the percentage of micropores by area and volume. The nitrogen isotherms demonstrated that the surface area dictated the amount of adsorption onto the ACF regardless of the form of the latter. The difference in the volume of smaller micropores between the ACFC and ACFF types may be attributed to the difference in the adsorbent density and the accessibility of the fibre surface to the activating gas during the activation process. An understanding of the pore structure of ACFs by form and surface area is crucial in determining the appropriate specific applications of such adsorbents.