Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Implementation of a Web-Based Sms-Notification Clearance System: A Case Study of Federal Polytechnic, Ile – Oluji, Ondo State.

--------------------------------------------------------------------------------------------------------------------------------------- ABSTRACT Each year, tertiary institutions churn out graduating students who are mandated to get cleared by different unit of the institutions which is usually done using the manual process. The manual tends to be extremely time consuming and difficult as students have to move from one building to another to know where they have problem. It has also been found to be vulnerable to fraud and other vices. The existing automated system available do not provide SMS-notification functionalities and other services such as non-user-friendly interface, lack of adequate information to user, non-prioritization of processes and so on. This study proposes a system that addresses the issues with the existing manual processing while improving on the identified automated ones. The study adopts a case study approach of a complete manual system for a leading tertiary institution of learning in Southwest Nigeria, with a view to evolving a working prototype. First a thorough understanding of the existing procedure is carried out. A new system that is web-based is built using Hypertext Markup Language (HTML) along with PHP for business logic layer, CSS for proper rendering of display pages of the front end and MySQL for the data layer. The new system will reduce the amount of time and efforts wasted on students’ clearance as well as reduce cost incurred on paper by the institution. Another advantage is that students can also initiate and monitor their clearance status from any location they are thereby eliminating the need to travel or be physically present.
Quantifying partition-based Kolmogorov-Sinai Entropy on Heart Rate Variability: a young vs. elderly study

In the last decades, a considerable effort has been devoted to quantify complexity in physiological time series, with a particular focus on heart rate variability (HRV). To this end, exemplary quantifiers including Approximate Entropy and Sample Entropy have successfully been applied by leveraging on statistical approximation and further parametrization through the definition of tolerance and embedding dimension, among others. In this study, we investigate the use of the Algorithmic Information Content, which is estimated through an effective compression algorithm, to quantify partition-based Kolmogorov-Sinai (K-S) entropy on HRV series. We test such a K-S estimate on real data gathered from the Fantasia database, aiming to discern young vs. elderly complex dynamics. Experimental results show that elderly people are associated with a lower HRV complexity and a more predictable behavior, with significantly lower partition-based K-S entropy than the young adults. We conclude that partition-based K-S entropy may effectively be used to investigate pathological conditions in the cardiovascular system, complementing state-of-the-art methods for complexity assessment.
ISOLATION, SCREENING, AND PARTIAL CHARACTERIZATION OF OXALATE OXIDASE ENZYME FROM PSEUDOMONAS STRAIN UNDER INDUCED OXALATE STRESS CONDITION

Oxalate oxidase (OxO), a manganese dependent enzyme, is involved in the catalysis of oxalate oxidation to carbon dioxide with the formation of hydrogen peroxide. OxO is present in the cell wall of plants. It increases the resistivity against diseases and external stress. Oxalate is found as waste metabolites in mammals, excess accumulation of oxalate results in hyperoxaluria and urolithiasis in humans. These disorders can be diagnosed by the help of OxO in many analytical methods. The present study is aimed on isolation of OxO enzyme from Pseudomonas strain under high salt stress. The OxO enzyme was produced in bulk under selected salt stress. It was partially purified by ammonium sulphate precipitation method, dialysis and ion-exchange chromatography. The OxO enzyme on enzymatic analysis showed potent activity concerning oxalic acid substrate. The microtiter plate analysis confirmed the ability of OxO enzyme purified from Pseudomonas strain in the diagnosis of oxalate-related disorders and in the future could be used to prepare the diagnostic biosensors.
Identification of Bacillus HN-2 and Analysis of Its Antifungal Properties

The strain HN-2 was isolated from soil. Through morphological, physiological and biochemical characteristics identification, phylogenet tree analysis of 16S rDNA sequence and specific PCR detection, the strain was identified to be Bacillus velezensis. The n-butanol extract, ammonium sulfate precipitation extract and acidification extract of B. velezensis HN-2 demonstrated strong antifungal activity against C. gloeosporioides, with the diameters of inhibition zone of 20.93±0.3 mm, 12.82±0.3mm and 13.57±0.3 mm, respectively. The EC50 value of n-butanol extract was 70.62 μg/mL. Mass spectrum analysis showed that lipopeptide was the main active substance of the strain HN-2, consisting of surfactin, fengycin and iturin. The mycelia of C. gloeosporioides treated with n-butanol extract were distorted, swollen and deformed. Application of n-butanol can reduce the development of C. gloeosporioides on the punctured epidermis of mango. It could be concluded that B. velezensis HN-2 had strong antifungal activity and the main antifungal substance was lipopeptide.
Efficient Point-Process Modeling of Spiking Neurons for Neuroprosthesis

Neuroprosthesis refers to implantable medical devices which can replace injured biological functions in the brain. One of the core problems in neuroprosthesis study is to construct a neural signal transformation model from one cortical area to another. Since the brain encodes and transmits information in spike trains, spiking neural network (SNN) can be an ideal choice for neuroprosthesis modeling. This paper proposes a spiking neuron point-process model (SNPM), which receives spike times as input, and is capable of modeling nonlinear interactions between cortical areas. The proposed SNPM can be implemented on neuromorphic chips for low-energy computing, thus has potential for clinical applications. Experiments show that SNPM can accurately reconstruct functional relationships from PMd (dorsal premotor cortex) to M1 (primary motor cortex) areas.
Modeling Corporate Credit Risk with Multiple Debt Issues

In the last several decades, there has been a tremendous wave of interest in the construction of credit risk models to estimate the default probability of borrowers. Following in the footsteps of Altman (1968), who adopted multiple discriminant analysis, Ohlso (1980) conducted a logistic regression analysis of bankrubtcy prediction and Zmijewski (1984) implemented probit regression analysis of financial distress prediction. The main theme of these studies is to utilize corporate historic financial variables as explanatory variables and use corporate defaults in the next one or more years as explained variables to establish the discriminant function of default prediction or predict corporate default through Logit and Probit regression models. This analytical framework is called the accounting-based credit risk model in the literature. A potential drawback of these accounting-based models is the use of backward-looking accounting information. Hillegeist et al. (2004) argued that the accounting-based models do not take into account the volatility of corporate assets. As a result, these models estimate that firms with similar financial ratios have similar default possibility will have similar default risks. On the other hand, the market-based structural models use the standard European call options of the option-pricing models and follow the Black-Scholes-Merton (Black and Scholes 1973; Merton 1974; hereinafter BSM) model, which assumes that a firm issues a single zero-coupon bond. The BSM structural model views the equity value of a firm as a European call option on the corporate asset value, and uses the market value of corporate equity to estimate the corporate default risk. Since the market price reflects
Towards a Self-Powered ECG and PPG Sensing Wearable Device

This paper presents a multifunctional sensor interface system-on-chip (SoC) for developing self-powered Electrocardiography (ECG) and Photoplethysmography (PPG) sensing wearable devices. The proposed SoC design consists of switch-capacitor-based LED driver and analog front-end (AFE) for PPG sensing, ECG sensing AFE, and power management unit for energy harvesting from Thermoelectric Generator (TEG), all integrated on a 2×2.5 mm2 chip fabricated in 0. 18μm standard CMOS process. We have performed post-layout simulation to verify the functionality and performance of the SoC. The LED driver employs the switch-capacitor-based architecture, which charges a storage capacitor up to 2.1 V and discharges accumulated charge to pass instantaneous current up to 40 mA through a selected LED. The PPG AFE converts the resulting photodiode (PD) current to voltage output with adjustable gain of 114–120 dBΩ and input-referred noise of 119 pARMS within 0.4 Hz–10 kHz. The ECG AFE provides adjustable mid-band gain of 47-63 dB, low-cut frequency of 1.5–6.3 Hz, and input-referred noise of 7.83 µVRMS within 1.5 Hz– 1.2 kHz to amplify/filter the recorded ECG signals. The power management unit is able to perform sufficient energy harvesting with the TEG output voltage as low as 350 mV.
POS-1 and germ cell specification

Hiroaki Tabara 1,*, Russell J. Hill 2,*, Craig C. Mello 3, James R. Priess 2,4,‡ and Yuji Kohara 1 1Department of Genetics, Graduate University of Advanced Studies and Gene Network Lab, National Institute of Genetics, Core Research for Evolutional Science and Technology, Japan Science and Technology Corporation, Mishima 411, Japan 2Fred Hutchinson Cancer Research Center, Howard Hughes Medical Institute, Seattle, WA 98109, USA 3University of Massachusetts Cancer Center, Worcester, MA 01605, USA 4Zoology Department, University of Washington, Seattle WA 98195, USA
Transcutaneous Energy Transmission System for a Totally Implantable Artificial Heart Using a Two-Wire Archimedean Spiral Coil

This paper describes the application of a proposed spiral coil to the transformer of a transcutaneous energy transfer system for a totally implantable artificial heart. To reduce the number of rectifier components in the power receiving circuit, the shape of the power receiving transformer was reviewed. The results indicated that the power transmission efficiency between the transformers was almost the same as that of the receiving transformer with the same shape. In addition, the calculations indicated that the power transmission efficiency including that of the power receiving circuit was increased, and the number of components in the power receiving circuit was reduced.
Supplementary Material for MBA-VO: Motion Blur Aware Visual Odometry

For the ease of illustration, we define following notations. We denote scalar with lower case letter (e.g. λ); we denote vector with bold lower case letter (e.g. x); we denote matrix with bold upper case letter (e.g. T); we denote a point p in coordinate frame Fa with p; the transformation matrix Ta ∈ SE(3) transforms a 3D point p in coordinate frame Fa to coordinate frame Fb; we further decompose Ta with R b a ∈ SO(3) and ta ∈ R, such that
Position accuracy evaluation of the modernized Polish DGPS

Position accuracy evaluation of the modernized Polish DGPS Polish Maritime DGPS system has been modernized to meet the requirements set out in IMO resolution for a future GNSS, but also to preserve backward signal compatibility of user equipment. Having finalized installation of the new technology L1, L2 reference equipment performance tests were performed. This paper presents results of the long-term signal measuring campaign of the DGPS reference station Rozewie, which was performed in July 2009. Final results allowed to verify repeatable and absolute accuracy of the system after the modernization. Obtained statistics were compared to past measurements performed in 2005 when previous system infrastructure was in operation.
Parametric fMRI analysis of videos of variable arousal levels reveals different dorsal vs ventral activation preferences between autism and controls

Atypical sensory processing is now considered a ubiquitous feature of autism spectrum disorder (ASD) and is responsible for the atypical sensory-based behaviours seen in these individuals. Specifically, emotional arousal is a critical ASD target since it comprises emotion regulation and sensory processing, two core aspects of autism. So, in this project, we used task-based fMRI and a well-catalogued dataset of videos with variable arousal levels to characterize the sensory processing of emotional arousal content in ASD and typically developed controls. Our analysis revealed a difference in the secondary attention network where ASD individuals showed a clear yet lateralized preference to the dorsal attention network, whereas the neurotypical individuals preferred the ventral attention network.
U-Net based frames partitioning and volumetric analysis for kidney detection in tomographic images

This work presents an automatic system for generating kidney boundaries in computed tomography (CT) images. This paper presents the main points of medical image processing, which are the parts of the developed system. The U-Net network was used for image segmentation, which is now widely used as a standard solution for many medical image processing tasks. An innovative solution for framing the input data has been implemented to improve the quality of the learning data as well as to reduce the size of the data. Precision-recall analysis was performed to calculate the optimal image threshold value. To eliminate false-positive errors, which are a common issue in segmentation based on neural networks, the volumetric analysis of coherent areas was applied. The developed system facilitates a fully automatic generation of kidney boundaries as well as the generation of a three-dimensional kidney model. The system can be helpful for people who deal with the analysis of medical images, medical specialists in medical centers, especially for those who perform the descriptions of CT examination. The system works fully automatically and can help to increase the accuracy of the performed medical diagnosis and reduce the time of preparing medical descriptions.
Utilization of Edible Mushroom for Nanomaterial-based Bioactive Material Development

Gold nanoparticles (AuNP) were synthesized using edible mushroom Russula delica (RD) in this study. Possibilities to evaluate these synthesized nanoparticles (RD-AuNPs) as bioactive substances were investigated. Characterization of synthesized RD-AuNPs were characterized via UV-vis, XRD, FTIR, EDX. In a spherical view, RD-AuNPs with a crystal size of 34.76 nm were synthesized. As a result, fungal systems used for nanomaterial biosynthesis as an effective alternative to chemical synthesis can be used in different biotechnological and medical applications. RD-AuNPs produced by green synthesis can be evaluated in this context.
Effect of Shock Vector Orientation in Modulating and Terminating Rotors – a Simulation Study

The main treatment option for Ventricular Fibrillation (VF), especially in out-of-hospital cardiac arrests (OHCA) is defibrillation. Typically, the survival-to-discharge rates are very poor for OHCA. Existing studies have shown that rotors may be the sources of arrhythmia and ablating them could modulate or terminate VF. However, tracking rotors and ablating them is not a feasible solution in a OHCA scenario. Hence, if the sources (or rotors) can be regionally localized non-invasively and this information can be used to direct the orientation of the shock vectors, it may aid the termination of rotors and defibrillation success. In this work, using computational modeling, we present our initial results on testing the effect of shock vector orientation on modulating (or) terminating rotors. A combination of Sovilj’s and Aliev Panfilov’s monodomain cardiac models were used in inducing rotors and testing the effect of shock vector magnitude and direction. Based on our simulation results on an average with four experimental trials, a shock vector directed in the perpendicular direction along the axis of the rotor terminated the rotor with 16% lesser magnitude than parallel direction and 38% lesser magnitude than in oblique direction.Clinical Relevance— A rotor localization dependent defibrillation strategy may aid the defibrillation protocol procedures to improve the survival rates. Based on the four experimental trials, the results indicate shock vectors oriented perpendicular to the axis of the rotors were efficient in modulating or terminating rotors with lower magnitude than other directions.
A Wearable Patch for Prolonged Sweat Lactate Harvesting and Sensing

Operating at low sweat rates, such as those experienced by humans at rest, is still an unmet need for state-of-the-art wearable sweat harvesting and testing devices for lactate. Here, we report the on-skin performance of a non-invasive wearable sweat sampling patch that can harvest sweat at rest, during exercise, and post-exercise. The patch simultaneously uses osmosis and evaporation for long-term (several hours) sampling of sweat. Osmotic sweat withdrawal is achieved by skin-interfacing a hydrogel containing a concentrated solute. The gel interfaces with a paper strip that transports the fluid via wicking and evaporation. Proof of concept results show that the patch was able to sample sweat during resting and post-exercise conditions, where the lactate concentration was successfully quantified. The patch detected the increase in sweat lactate levels during medium level exercise. Blood lactate remained invariant with exercise as expected. We also developed a continuous sensing version of the patch by including enzymatic electrochemical sensors. Such a battery-free, passive, wearable sweat sampling patch can potentially provide useful information about the human metabolic activity.
Breast Cancer Prediction Through DHBCA Algorithm in Horizontal Partitioned Database

According to the world health organization (WHO) cancer will became leading cause of woman death of the world wide. Breast cancer has become the most hazardous type of cancer among woman in the world. Early detection of breast cancer is essential in reducing life losses. In this paper mining rules to mine the attributes relationship. The support and confidence value are used to estimated from all item set. Minimum support and confidence value are used to predict rule from the list datasets. Our proposed work is applicable where the numbers of sites are greater than two and each site want to calculate the global rule and global confidence from the database without disclosing their private information to other sites presents in the global environments. Our proposed algorithm Double Hash Based Cryptography Algorithm (DHBCA) to provide the highest privacy in the breast cancer database and also zero percent of data leakage.
A Hotness-aware Write Buffer Management Scheme for the Lifetime Extension of Flash-based Solid State Drives

 Abstract —Flash-based solid state disks(SSDs) provide high I/O performance, low energy, and shock resistance. However, random writes limit its application in the update intensive applications such as Web services. Existing buffer management schemes usually employ a hot page detection mechanism to reduce random writes. Since the mechanisms usually take reuse distance or frequency as a parameter to identify frequently updated page/block, which become inefficient in handling fast changing workloads. In this paper, an efficient buffer management scheme, named HWB, is proposed, which reduces random writes by identifying frequently updated page/block. To improve both buffer hit rate and data sequentiality, HWB divides write buffer space into a hot region, a warm region, and a cold region. Frequently updated date is stored in the hot and warm region at page granularity, meanwhile infrequently updated date is kept in the cold region at block granularity. A replacement and flush policy, which combined with a temperature predictor, is designed to improve buffer hit ratio and reduce random write. HWB is evaluated using extensive trace-driven simulations. Its evaluated results show that HWB significantly reduces random write and extends SSD lifetime compared to existing buffer management schemes.
A modified lucky electron model for impact ionization rate in NMOSFET's at 77 K

The nonstationary effects of electrons at 77 K, in the high field saturation region of the MOSFET, are modeled by incorporating an appropriate electron temperature decrease (-/spl Delta/T/sub e/) to the carrier energy, within the framework of a modified lucky electron model. For a thin oxide MOSFET (T/sub cx/=5 nm, L/sub 0/=0.5 /spl mu/m), /spl Delta/T/sub c/ is a function of the electric field in the saturation region, and increases rapidly with drain bias. However, for a thick oxide MOSFET (T/sub cx/=12.5 nm, L/sub g/=5 /spl mu/m), /spl Delta/T/sub e/=280 K is found to adequately describe the impact ionization rate. Our model also explains the crossover of the ionization rates in the thick oxide MOSFET at 77 K and 300 K.
Monetary Policy Communication during the 2016 Economic Recession in Nigeria: Insights from a Text Mining Analysis

This paper analyses the monetary policy communication of the Central Bank of Nigeria (CBN) during the 2016 economic recession. Particularly, we apply text mining techniques to derive useful insights from the monetary policy communiques published between 2015 and 2017. First, we nd evidence of greater monetary policy transparency during the recession as evidenced by increased communication about the CBN's objectives and prevailing economic conditions. Second, the computed readability scores of the published communiques declined at the outset of the recession, implying increased complexity of the documents. Third, our results show that the communiques expressed negative policy sentiments over the sample period, reecting the economic uncertainties that trailed the oil price slump of 2014. Interestingly, the negative sentiments reached its trough in July 2016 and recorded an inexion, reecting the optimism of the Monetary Policy Committee (MPC) about future economic conditions. Fourth, results from our estimated topic model show that issues relating to oil price shocks, external reserves, and ination were of concern to the MPC in 2015 while exchange rate management was prioritised in 2016. The topic proportion for prices and macroeconomic policies is found to be consistently sizeable across the sample period, reecting the MPC's commitment to the CBN's primary mandate of price stability.
Cash on the Table? Imperfect Take-up of Tax Incentives and Firm Investment Behavior

We investigate whether tax incentives are effective in stimulating private investment in less developed countries, by exploiting the introduction of accelerated depreciation for fixed assets investment in China as a natural experiment. In contrast to the large positive impact of similar tax incentives in the U.S. and U.K. found in recent studies, accelerated depreciation appeared ineffective in stimulating Chinese firms’ investment. Using confidential corporate tax returns from a large province, we find that firms fail to claim the tax benefits on over 80 percent of eligible investments. Firms’ take-up of the tax incentive is significantly influenced by their taxable positions and tax sophistication. Information transmission and resources of local tax authorities also play a significant role. Our study contributes to the understanding of conditions under which tax-based investment incentives can be effective.