Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative analysis of discriminant wavelet packet features and raw image features for classification of meningioma subtypes

The idea of multiresolution analysis has been around for over two decades now. In this paper, we explore a multiresolution analysis based technique for histopathological image classification and compare it with raw image analysis. The principle idea for the former is to derive an optimal wavelet representation, called Adaptive Discriminant Wavelet Packet Transform (ADWPT), of the images in order to achieve the largest discrimination power. Our results show that the textural features combined with ADWPT yield a significant improvement in classification accuracy.
Recharge and Nitrate Transport Through the Deep Vadose Zone of the Loess Plateau: A Regional‐Scale Model Investigation

The Loess Plateau of China (LPC) is suffering from the impacts of overexploitation of groundwater, leading to a decline in the regional water table. This is compounded by relatively recent large‐scale transformation of land use, which may impact groundwater recharge and threaten future water quality from intensive nitrogen fertilizer application. Understanding the regional unsaturated water flow and nitrate travel time in the deep vadose zone is crucial for the sustainable management of the LPC groundwater system. We develop here a regional‐scale model that exploits an extensive database of soil properties derived from recent intensive soil profile sampling over the LPC, together with climate, vadose zone thickness, and land use data. The model solves the Richards equation and a conservative solute transport model using a multiple 1D column approach. A comparison between model simulations and observations at five sites reveals good model performance. Application over the LPC indicates that areas with dense irrigated agricultural land use contribute significantly to groundwater recharge. By using land use cover information from 1975 to 2008, simulations reveal that the transition from agriculture to forest and grassland accounts for a small reduction of the total annual recharge (6.1%). Modeled nitrate travel times through the deep unsaturated zone range between decades and centuries; however, recent loading of anthropogenic nitrate is expected to reach the aquifer in the near future under irrigated areas or where the vadose zone is relatively thin. The model simulations provide valuable information for assessing future vulnerability of groundwater resources over a regional scale.
A Prosodic Analysis of Discourse Segments in Direction-Giving Monologues

This paper reports on corpus-based research into the relationship between intonational variation and discourse structure. We examine the effects of speaking style (read versus spontaneous) and of discourse segmentation method (text-alone versus text-and-speech) on the nature of this relationship. We also compare the acoustic-prosodic features of initial, medial, and final utterances in a discourse segment.
Plasma Apelin and ADMA Levels in Patients with Essential Hypertension

Both apelin and asymetric dymethyl arginine (ADMA) regulate blood pressures. Low apelin and high ADMA levels have been reported in several cardiometabolic disorders. However, there is no data about ADMA and apelin levels in essential hypertension and any relationship between them. We investigated a group of newly diagnosed and untreated 30 young hypertensive men and 30 healthy controls. Apelin levels were significantly lower and the ADMA levels were significantly higher in the patients (p = 0.04 for both). Both ADMA and apelin were related to the systolic blood pressures (SBP) (beta = −0.393, p = 0.003; beta = 0.285, p = 0.03, respectively). Future studies are necessary in order to clearly define the role of ADMA and apelin in the pathogenesis of essential hypertension.
Testing the Accuracy of Redshift-Space Group-finding Algorithms

Using simulated redshift surveys generated from a high resolution N-body cosmological structure simulation, we study algorithms used to identify groups of galaxies in redshift space. Two algorithms are investigated; both are friends-of-friends schemes with variable linking lengths in the radial and transverse dimensions. The chief difference between the algorithms is in the redshift linking length. The algorithm proposed by Huchra \& Geller (1982) uses a generous linking length designed to find ``fingers of god'' while that of Nolthenius \& White (1987) uses a smaller linking length to minimize contamination by projection. We find that neither of the algorithms studied is intrinsically superior to the other; rather, the ideal algorithm as well as the ideal algorithm parameters depend on the purpose for which groups are to be studied. The Huchra/Geller algorithm misses few real groups, at the cost of including some spurious groups and members, while the Nolthenius/White algorithm misses high velocity dispersion groups and members but is less likely to include interlopers in its group assignments. In a companion paper we investigate the accuracy of virial mass estimates and clustering properties of groups identified using these algorithms.
Developing a sustainable nation brand: a study of Sri Lanka

This study examines the degree to which the Earth Lung Project, a carbon mitigation initiative in Sri Lanka has developed a coherent nation brand. Findings indicate that a shared sense of national identity amongst all stakeholder groups is critical in the development of a national brand. However, whilst concern for the environment was found to be an embedded aspect of national identity within Sri Lanka, conflicting stakeholder perspectives reveal a lack of belief amongst private sector stakeholders in the ELP. Thus there are doubts over the degree to which the ELP is currently capable of generating a sustainable national brand.
Maximum power point tracking of PMSG based grid connected WECS using quadrature axis current

This article proposes the ways to track the maximum power points (MPP) using the torque component (quadrature axis current component) of field oriented controlled (FOC) permanent magnet synchronous generator (PMSG) based grid connected wind energy conversion system (WECS). These methods reduce the time delay to track the exact optimum points using the power versus speed characteristics of WECS and are useful to track the optimum points during rapidly varying wind conditions. This research analyses the position of operating points using power signal feedback (PSF) and optimum torque (OT) MPPT methods and emphasizes that the position of MPP using these methods will not be the exact optimum point due to non unique nature of optimum constant. This article also finds relation between the quadrature axis current component of PMSG, DC-link power and speed and proposes two ways of tracking optimum point that results in fast tracking due to faster settling of quadrature axis current. The back-to-back converter is used in this research and are controlled by sinusoidal pulse width modulation (SPWM). The efficiency of the proposed methods have been verified by simulation and experimentation.
Virtual machine warmup blows hot and cold

Virtual Machines (VMs) with Just-In-Time (JIT) compilers are traditionally thought to execute programs in two phases: the initial warmup phase determines which parts of a program would most benefit from dynamic compilation, before JIT compiling those parts into machine code; subsequently the program is said to be at a steady state of peak performance. Measurement methodologies almost always discard data collected during the warmup phase such that reported measurements focus entirely on peak performance. We introduce a fully automated statistical approach, based on changepoint analysis, which allows us to determine if a program has reached a steady state and, if so, whether that represents peak performance or not. Using this, we show that even when run in the most controlled of circumstances, small, deterministic, widely studied microbenchmarks often fail to reach a steady state of peak performance on a variety of common VMs. Repeating our experiment on 3 different machines, we found that at most 43.5% of pairs consistently reach a steady state of peak performance.
Major food crops production and yield forecast in Pakistan.

This study focuses on forecasting the production and yield of food crops in Pakistan. Utilizing the “Autoregressive Integrated Moving Average” (ARIMA) model and data from 1948 to 2011. The data was obtained from Ministry of Food and Agriculture, Islamabad and various Economic Surveys of Pakistan. The result predicts that wheat (production and yield) forecast for 2029-30 to be -1 about 37188 thousand tons and 3454 kg ha , respectively. The rice (production -1 and yield) forecast for 2029-30 will be about 7176 thousand tons and 2630 kg ha , respectively. The maize (production and yield) forecast for 2029-30 will be about -1 5784 thousand tons and 6088 kg ha , respectively. In short, the production growth rate of wheat, rice and maize was higher in 2012.
A Bio-Inspired Stereo Vision System for Guidance of Autonomous Aircraft

Unmanned aerial vehicles (UAVs) are increasingly replacing manned systems in situations that are either too dangerous, too remote, or too difficult formanned aircraft to access. Modern UAVs are capable of accurately controlling their position and orientation in space using systems such as the Global Positioning System (GPS) and the Attitude and Heading Reference System (AHRS). However, they are unable to perform crucial guidance tasks such as obstacle avoidance, low-altitude terrain or gorge following, or landing in an uncontrolled environment using these systems only. For such tasks, the aircraft must be able to continuously monitor its surroundings. Active sensors, such as laser range finders or radar can be bulky, low-bandwidth, and stealth-compromising. Therefore, there is considerable benefit to be gained by designing guidance systems for UAVs that utilise passive sensing, such as vision. Over the last two decades, a significant amount of research has shown that biological visual systems can inspire novel, vision-based solutions to some of the challenges facing autonomous aircraft guidance. A recent trend in biologically inspired vision systems has been to exploit optical flow information for collision avoidance, terrain and gorge following, and landing. However, systems that rely on optical flow for extracting range information need to discount the components of optical flow that are induced by rotations of the aircraft. Furthermore, altitude cannot be controlled in a precise manner using measurements of optical flow only, as optical flow also depends upon the aircraft’s velocity. Stereo vision, on the other hand, allows the aircraft’s altitude to be directly computed and controlled, irrespective of the attitude or ground speed of the aircraft, and independently of its rotations about the roll, pitch, and yaw axes. Additionally, we will show that a stereo vision system can also allow the computation and control of the orientation of the aircraft with respect to the ground. Stereo vision therefore provides an attractive approach to solving some of the problems of providing guidance for autonomous aircraft operating in low-altitude or cluttered environments. In this chapter, we will explore how stereo vision may be applied to facilitate the guidance of an autonomous aircraft. In particular, we will discuss a wide-angle stereo vision system that has been tailored for the specific needs of aircraft guidance, such as terrain following, obstacle avoidance, and landing. Finally, results from closed-loop flight tests conducted using this system will be presented to demonstrate how stereo vision can be successfully utilised to provide guidance for an autonomous aircraft performing real-world tasks. 16
Streaming for Aibohphobes: Longest Palindrome with Mismatches

A palindrome is a string that reads the same as its reverse, such as "aibohphobia" (fear of palindromes). Given an integer $d>0$, a $d$-near-palindrome is a string of Hamming distance at most $d$ from its reverse. We study the natural problem of identifying a longest $d$-near-palindrome in data streams. The problem is relevant to the analysis of DNA databases, and to the task of repairing recursive structures in documents such as XML and JSON. We present an algorithm that returns a $d$-near-palindrome whose length is within a multiplicative $(1+\epsilon)$-factor of the longest $d$-near-palindrome. Our algorithm also returns the set of mismatched indices of the $d$-near-palindrome, using $\mathcal{O}\left(\frac{d\log^7 n}{\epsilon\log(1+\epsilon)}\right)$ bits of space, and $\mathcal{O}\left(\frac{d\log^6 n}{\epsilon\log(1+\epsilon)}\right)$ update time per arriving symbol. We show that $\Omega(d\log n)$ space is necessary for estimating the length of longest $d$-near-palindromes with high probability. We further obtain an additive-error approximation algorithm and a comparable lower bound, as well as an exact two-pass algorithm that solves the longest $d$-near-palindrome problem using $\mathcal{O}\left(d^2\sqrt{n}\log^6 n\right)$ bits of space.
A new mutual authentication and key exchange protocol with balanced computational power for wireless settings

Mutual authentication and key exchange protocols (MAKEP) provide two parties in communication with guarantee of true identity. And then the two parties end up sharing a common session key for privacy and data integrity during the session. In MAKEP, public-key-based schemes and symmetric-key-based schemes are often used. However, the former requires high computation complexity and hence, it is not suitable for applications in wireless settings. The latter has to maintain many distinct keys for different parties. Wong et al. proposed the Linear MAKEP to solve these problems. But in term of storage space, it is not optimal. In this paper, we propose a scheme that uses the geometric properties of line to achieve mutual authentication and key exchange. Compared with Wong et al.'s scheme, our scheme is efficient and requires less storage space. It can withstand the replay attack and the unknown key-share attack, and the server does not bear much more computation cost than the client in each session, hence we call it a protocal with balanced computational power. Copyright © 2004 AEI
Performance Analysis of Timing Attack on Elliptic Curve Cryptosystem Mr

1. Abstract Cryptosystems often take slightly different amounts of running time depending on the input and the used key. This timing information, extracted from the decryption process, can be used to derive information about the secret key. This new class of attacks on implementations of cryptosystems is named Timing Attacks. Timing attacks attempt to exploit the variations in computational time for private key operations to guess the private key. This type of attack is primitive in the sense that no specialized equipment is needed. An attacker can break a key by simply measuring the computational time required by the user inputs and recording those user inputs. This paper is aimed to analyse the performance of Timing Attack on Elliptic Curve Cryptosystem. The main advantage of Elliptic Curve Cryptography is smaller key size, it is mostly used for public key infrastructure
Exact Simulation of Integrate-and-Fire Models with Synaptic Conductances

Computational neuroscience relies heavily on the simulation of large networks of neuron models. There are essentially two simulation strategies: (1) using an approximation method (e.g., Runge-Kutta) with spike times binned to the time step and (2) calculating spike times exactly in an event-driven fashion. In large networks, the computation time of the best algorithm for either strategy scales linearly with the number of synapses, but each strategy has its own assets and constraints: approximation methods can be applied to any model but are inexact; exact simulation avoids numerical artifacts but is limited to simple models. Previous work has focused on improving the accuracy of approximation methods. In this article, we extend the range of models that can be simulated exactly to a more realistic model: an integrate-and-fire model with exponential synaptic conductances.
Updated clinical diagnostic criteria for sporadic Creutzfeldt-Jakob disease

Several molecular subtypes of sporadic Creutzfeldt–Jakob disease have been identified and electroencephalogram and cerebrospinal fluid biomarkers have been reported to support clinical diagnosis but with variable utility according to subtype. In recent years, a series of publications have demonstrated a potentially important role for magnetic resonance imaging in the pre-mortem diagnosis of sporadic Creutzfeldt–Jakob disease. Magnetic resonance imaging signal alterations correlate with distinct sporadic Creutzfeldt–Jakob disease molecular subtypes and thus might contribute to the earlier identification of the whole spectrum of sporadic Creutzfeldt–Jakob disease cases. This multi-centre international study aimed to provide a rationale for the amendment of the clinical diagnostic criteria for sporadic Creutzfeldt–Jakob disease. Patients with sporadic Creutzfeldt–Jakob disease and fluid attenuated inversion recovery or diffusion-weight imaging were recruited from 12 countries. Patients referred as ‘suspected sporadic Creutzfeldt–Jakob disease’ but with an alternative diagnosis after thorough follow up, were analysed as controls. All magnetic resonance imaging scans were assessed for signal changes according to a standard protocol encompassing seven cortical regions, basal ganglia, thalamus and cerebellum. Magnetic resonance imaging scans were evaluated in 436 sporadic Creutzfeldt–Jakob disease patients and 141 controls. The pattern of high signal intensity with the best sensitivity and specificity in the differential diagnosis of sporadic Creutzfeldt–Jakob disease was identified. The optimum diagnostic accuracy in the differential diagnosis of rapid progressive dementia was obtained when either at least two cortical regions (temporal, parietal or occipital) or both caudate nucleus and putamen displayed a high signal in fluid attenuated inversion recovery or diffusion-weight imaging magnetic resonance imaging. Based on our analyses, magnetic resonance imaging was positive in 83% of cases. In all definite cases, the amended criteria would cover the vast majority of suspected cases, being positive in 98%. Cerebral cortical signal increase and high signal in caudate nucleus and putamen on fluid attenuated inversion recovery or diffusion-weight imaging magnetic resonance imaging are useful in the diagnosis of sporadic Creutzfeldt–Jakob disease. We propose an amendment to the clinical diagnostic criteria for sporadic Creutzfeldt–Jakob disease to include findings from magnetic resonance imaging scans.
Hazardous gas detection for FTIR-based hyperspectral imaging system using DNN and CNN

Recently, a hyperspectral imaging system (HIS) with a Fourier Transform InfraRed (FTIR) spectrometer has been widely used due to its strengths in detecting gaseous fumes. Even though numerous algorithms for detecting gaseous fumes have already been studied, it is still difficult to detect target gases properly because of atmospheric interference substances and unclear characteristics of low concentration gases. In this paper, we propose detection algorithms for classifying hazardous gases using a deep neural network (DNN) and a convolutional neural network (CNN). In both the DNN and CNN, spectral signal preprocessing, e.g., offset, noise, and baseline removal, are carried out. In the DNN algorithm, the preprocessed spectral signals are used as feature maps of the DNN with five layers, and it is trained by a stochastic gradient descent (SGD) algorithm (50 batch size) and dropout regularization (0.7 ratio). In the CNN algorithm, preprocessed spectral signals are trained with 1 × 3 convolution layers and 1 × 2 max-pooling layers. As a result, the proposed algorithms improve the classification accuracy rate by 1.5% over the existing support vector machine (SVM) algorithm for detecting and classifying hazardous gases.
Study of a New Gliadin Capture Agent and Development of a ProteinMicroarray as a New Approach for Gliadin Detection

Celiac disease is an immune-mediated enteropathy precipitated by the ingestion of gluten-containing foods in genetically predisposed children and adults. After a positive diagnosis for celiac disease, the only available treatment is to adopt a gluten-free diet, and evaluation of the absence of gluten in foods is crucial for the health of celiac patients. In the present study, a recombinant glutamine-binding protein (GlnBP) from Escherichia coli showed its ability to recognize peptides deriving from digested wheat flour. GlnBP and the commercially available 4F3 monoclonal antibody, raised against a region of the α-gliadin peptide 33-mer from wheat, demonstrated the ability to detect gliadin extracted from wheat flour. Recombinant GlnBP and 4F3 monoclonal antibody were used as new capture agents for the development of a protein chip able to detect gluten in foods. The protein microarray system has proven to detect the presence of gliadin in a range of concentrations between 500 and 5 ppm.
Strengthened Indonesian Throughflow Drives Decadal Warming in the Southern Indian Ocean

Remarkable warming of the Southern Indian Ocean during the recent two decades is assessed using a heat budget analysis based on the Estimating the Circulation and Climate of the Ocean version 4 release 3 model results. The annual mean temperature averaged in the upper‐700 m Southern Indian Ocean during 1998–2015 has experienced significant warming at a rate of 1.03 × 10−2 °C/year. A heat budget analysis indicates that the increase is mostly driven by decreased cooling from net air‐sea heat flux and increased warming from heat advection. Increased Indonesian Throughflow advection is the largest contributor to warming the upper 700 m of the Southern Indian Ocean, while the reduction of surface turbulent heat flux is of secondary importance. These results expand our understanding of the decadal heat balance in the Indian Ocean and of Indo‐Pacific decadal climate variability.
No association of CSF biomarkers with APOEε4, plaque and tangle burden in definite Alzheimer's disease

The CSF biomarkers b-amyloid peptide (Ab1^42), total tau protein (T-tau) and tau phosphorylated at threonine 181 (P-tau181P) were determined in autopsy-confirmed Alzheimer’s disease patients in order to study possible associations with the e4 allele of APOE and density and spread of plaques (SP) and tangles (NFT). CSF levels of Ab1^42, T-tau and P-tau181P were determined in 50 Alzheimer’s disease patients using commercially available single parameter ELISA kits (INNOTEST ). Genomic DNA was extracted from whole blood and the APOE genotype was determined using standard methods. Tangle burden was assessed by means of Braak’s NFT stages (I^VI), whereas the plaque burden was assessed by means of Braak’s SP stages (A^C). CSF biomarker levels were not different when comparing e4 carriers (n^21) and non-carriers (n^29) (P`0.05 for all comparisons). No significant correlations between the number of e 4a lleles (0, 1 or 2) and CSF levels of Ab1^42 (Spearman Rank Order: r^20.057, P^0.695), T-tau (r^0.104, P^0.472) and P-tau181P (r^0.062, P^0.668) were found. Braak’s SP (Ab1^42: r^20.155, P ¼ 0.280; T-tau: r^20.044, P ¼ 0.763; P-tau181P: r^20.010, P^0.947) and NFT (Ab1^42: r^20.145, P^0.315; T-tau: r^0.117, P^0.415; P-tau181P: r^0.150, P^0.296) stages were not significantly correlated with CSF biomarker levels. In conclusion, CSF levels of Ab1^42 ,T -tau and P-tau 181P were not associated with e4, tangle or plaque burden in 50 autopsy-confirmed Alzheimer’s disease patients. In the light of future biomarker applications like monitoring of disease progression and as allocortical neuropathological changes significantly contribute to clinical symptoms, the concept of in vivo surrogate biomarkers should be further explored.