Miracle-dz/UniFAR-FTUs huggingface dataset:
Physicochemical properties of sorghum (Sorghum Bicolor L. Moench) starch as affected by drying temperature

N. A. Aviara 1 , J. C. Igbeka 2 , L. M. Nwokocha 3 ( 1 . Department of Agricultural and Environmental Resources Engineering , University of Maiduguri , Maiduguri , Nigeria ; 2 . Department of Agricultural and Environmental Engineering , University of Ibadan , Ibadan , Nigeria ; 3 . Department of Chemistry , University of Ibadan , Ibadan , Nigeria ) Abstract: Starch was isolated from sorghum (white) grains and its proximate composition determined. Scanning electron micrograph and x-ray diffraction pattern of the starch were obtained using scanning electron microscope and x-ray diffractometer, respectively. The effect of drying temperature in a tray dryer on starch physicochemical and pasting properties was investigated. The open air dried starch had a composition of 10.73% moisture, 0.30% ash, 1.06% protein and 1.07% fat. Amylose content was 21.08% and it had an average granule size and pH of 18.59 μm and 5.45, respectively. The starch exhibited the A-type crystalline diffraction pattern, which was not altered by drying in a tray dryer at the temperature range of 40 to 60 ℃ . Water binding capacity and swelling power of the open air dried starch were not significantly different from those of starch dried at 40 ℃ ( p <0.05). Water binding capacity increased from 79.63 to 88.5%, while swelling power, solubility and percentage syneresis decreased from 12.01 to 8.96 g/g, 7.08 to 2.85% and 14.00 to 10.80%, respectively as the drying temperature increased from 40 to 60 o C. Paste clarity was low (22.50 % –26.20%) but increased with an increase in drying temperature up to 50 ℃ and decreased with a further increase in temperature. Pasting properties of open air dried starch differed significantly from those of starch dried at different temperatures. Peak viscosity decreased from 398.75 to 325.25 RVU as the drying temperature increased from 40 to 60 ℃ . Setback viscosity increased with an increase in drying temperature up to a point and decreased with a further increase in temperature. Final and breakdown viscosities as well as pasting temperature and peak time had polynomial relationships of the third order with drying temperature. Regression equations that could be used to adequately express the relationships existing between the physicochemical and pasting properties of sorghum starch and drying temperature were established. These models could be used to select the drying temperature that would yield starch of desired physicochemical properties for a functional application. Keywords: s orghum starch, degree of crystallinity, physicochemical properties, pasting properties, drying temperature, tray dryer Citation: Aviara N. A, J. C. Igbeka , and L. M. Nwokocha. Physicochemical properties of sorghum ( sorghum bicolor l. Moench) starch as affected by drying temperature . Agric Eng Int : CIGR Journal , 20 1 0 , 12 ( 2 ): 85 - 94 .
Automated MOS Transistor Gamma Degradation Measurements Based on LabVIEW Environment

In recent years, the study of the effects of ionizing radiation in thin gate oxides has received increasing attention. This is due not only to the appearance of new lithography tools for ultra low scale integration (ULSI) technologies, that use Xrays or e-beams, but also for the interest of space, medical, military or high-energy applications, where the complementary metal-oxide-semiconductor (CMOS) read-out circuitry will be subjected to a very hostile radiation environment. A major concern in the reliability of metal-oxide-semiconductor field effect transistor (MOSFET) devices is the formation of interface traps and near-interface oxide traps; called also border traps; under hot carrier injection, irradiation and processing. Traps at or near the semiconductor/gate dielectric interface can cause degraded transconductance (Doyle et al., 1990), the shifting of threshold voltage (Tsuchiya et al., 1987) and may lead to dielectric breakdown (Chen et al., 1985). In order to improve the resistance of MOSFET devices to these effects, it is necessary to have a reliable method of determining the densities of both interface traps and oxide traps (Djezzar et al., 2004). The reliable test procedure to predict radiation response of integrated circuits (IC’s) from standard test laboratory, for example in space, is very important and requires a development of simple and rapid electrical characterization techniques easily mountable in production line. Therefore, intensive works have been carried out on the electrical characterization techniques for MOS gate oxide and Si/SiO2 interface degradation caused by radiation (Schwank et al., 1993). The charge pumping (CP) technique (Groeseneken et al., 1984) is a valuable tool for all kind of traps characterization. In this article, we present an automatic measurement bench programmable by the IEEE-488 bus that permits to characterize MOSFET device degradation induced by gamma radiation at low doses. This characterization permits to extract threshold voltage and flatband voltage for virgin and irradiated samples. Moreover, the determination of the breakpoint frequency that represents the limit between interface and border trap contributions to the charge trap is automatically extracted. The measurement bench is managed by a program, written by a graphical language LabVIEW. LabVIEW is a powerful, platform-independent, graphical programming development system which is ideally suited for data acquisition, storage, analysis, and presentation.
In vitro antioxidant and cytotoxicity studies of Curcuma amada Roxb. (Mango ginger)

Curcuma amada Roxb, of Zingiberaceae is an important active spice used in traditional system of medicine. They also used in the manufacture of pickles, chutney, salad and jam. Phosphomolybdenam method was used to measure the total antioxidant capacity (TAC) of C. amada ethanolic rhizome extract (CAEREt). The free radical scavenging capacity of CAEREt was also carried out by ABTS and DPPH methods. The cytotoxicity effect of CAEREt was determined by Trypan blue dye exclusion method and MTT assay using two different cell lines such as Dalton Lyphoma Ascites (DLA) and Human Cervical Cancer Cell Line (HeLa). The results showed that the rhizome extract of C. amada rich in phytocompounds and have exhibited better antioxidant and cytotoxicity properties.
FAST-TRACK Project Project No . : SB 080007 Final Report 1

Orthogonal Frequency Division Multiplexing (OFDM) combines the advantages of high achievable rates and relatively easy implementation. However, for proper recovery of the input, the OFDM receiver needs accurate channel information. In this project, we show how the cyclic prefix can be used to enhance the performance of an OFDM receiver. In the first part of the project, we consider blind data detection for OFDM transmission over block fading channels. Specifically, we show how an OFDM symbol can be blindly detected using the output symbol and associated cyclic prefix. Our approach relies on decomposing the OFDM channel into two subchannels (circular and linear) that share the same input and are characterized by the same channel parameters. This fact enables us to estimate the channel parameters from one subchannel and substitute the estimate into the other, thus obtaining a nonlinear relationship involving the input and output data only that can be searched for the maximum likelihood estimate of the input. This shows that OFDM systems are completely identifiable using output data only, irrespective of the channel zeros, as long as the channel delay spread is less than the length of the cyclic prefix. In the second part, we propose six iterative methods to reduce the computational complexity involved in the maximum likelihood search of input. In the last part of the project, we show how the cyclic prefix can be used to enhance the operation of the channel equalizer when the channel is known at the receiver (perfectly or through training).
Design of a 40 MHz 128 Element CMUT PhasedArray for Ophthalmic Anterior Segment Imaging

High-resolution ultrasonic imaging of delicate small tissues in eyes requires high frequency (>20MHz) ultrasonic transducers as higher frequency provides superior axial and lateral resolutions suitable for better diagnosis of small tissues. However, ultrasound waves at higher frequencies suffer higher attenuation that limits the penetration depth. As all the clinically important tissues in the anterior segment are located within a few millimeters from the surface of the eye, this imaging problem is an ideal candidate for high-frequency ultrasound to obtain high resolution images for better diagnosis [1-3]. In the early 1970s, several groups developed relatively simple reliable systems for ultrasound based routine clinical imaging of ophthalmic anterior segments. An ultrasound based manual B-scan method was developed and commercialized by Sonometrics Systems in New York for a broad variety of ocular and orbital diseases [4]. An instrument called ultrasonic bio microscope was reported in [4] where a 50-MHz polyvinylidene difluoride transducer and a sector scanner were used to achieve excellent definition of the anterior segment of an eye for diagnosis of glaucoma [4]. The Artemis system [4] uses 50MHz transducers in an arc scan mode that maintains approximately normal angles of incidence over the entire surface of the specular cornea. This permits very high definition imaging over the entire anterior segment. In conjunction with digital signal processing, arc scans have provided highly detailed maps of the thicknesses and local radii of curvature of the 50-μm corneal epithelium and 500μm corneal stroma. Such maps have helped to plan and evaluate corneal sculpting procedures such as LASIK [4].
Methods and Algorithms for Inference Problems in Population Genetics

Inference of population history is a central problem of population genetics. The advent of large genetic data brings us not only opportunities on developing more accurate methods for inference problems, but also computational challenges. Thus, we aim at developing accurate method and fast algorithm for problems in population genetics. Inference of admixture proportions is a classical statistical problem. We particularly focus on the problem of ancestry inference for ancestors. Standard methods implicitly assume that both parents of an individual have the same admixture fraction. However, this is rarely the case in real data. We develop a Hidden Markov Model (HMM) framework for estimating the admixture proportions of the immediate ancestors of an individual, i.e. a type of appropriation of an individual’s admixture proportions into further subsets of ancestral proportions in the ancestors. Based on a genealogical model for admixture tracts, we develop an efficient algorithm for computing the sampling probability of the genome from a single individual, as a function of the admixture proportions of the ancestors of this individual. We show that the distribution and lengths of admixture tracts in a genome contain information about the admixture proportions of the ancestors of an individual. This allows us to perform probabilistic inference of admixture proportions of ancestors only using the genome of an extant individual. To better understand population, we further study the species delimitation problem. It is a problem of determining the boundary between population and species. We propose a classificationbased method to assign a set of populations to a number of species. Our new method uses summary Jingwen Pei – University of Connecticut, 2018 statistics generated from genetic data to classify pairwise populations as either ‘same species’ or ‘different species’. We show that machine learning can be used for species delimitation and scaled for large genomic data. It can also outperform Bayesian approaches, especially when gene flow involves in the evolutionary process. Methods and Algorithms for Inference Problems in Population Genetics Jingwen Pei B.S., Xi’an Jiaotong University, 2012 A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy at the University of Connecticut
The Influence of Background Music of Video Games on Immersion

The background music has been proved to be an indispensable part in every successful video game. At the same time, all the video game designers and players hope video games could be as immersive as possible. Present research aimed to make an investigation about the role of video games background music in the influence of players’ subjective immersion. Eighty participants were employed according to their game experience to join the experiment. All of them were assigned in pairs to finish a same video game synchronously with local area network. One was with earphone while the other not. After 20 minutes’ gameplay, they needed to complete three missions (questionnaire, task after game and time distortion) with the purpose of detecting their immersion during video game. The results showed that the participants with background music got significant higher scores from questionnaire, performed worse in after-game task and expressed more serious time distortion than those participants without hearing background music. But these changes just happened to low gamers in the questionnaire and time distortion. Besides, correlations were made to find that only the questionnaire scores and time distortion were significantly related. These results of present research showed that background music did increase participants’ immersion. But this improvement was likely just happened in low gamers.
INVESTIGATION OF JOINT VISIBILITY BETWEEN SAR AND OPTICAL IMAGES OF URBAN ENVIRONMENTS

In this paper, we present a work-flow to investigate the joint visibility between very-high-resolution SAR and optical images of urban scenes. For this task, we extend the simulation framework SimGeoI to enable a simulation of individual pixels rather than complete images. Using the extended SimGeoI simulator, we carry out a case study using a TerraSAR-X staring spotlight image and a Worldview2 panchromatic image acquired over the city of Munich, Germany. The results of this study indicate that about 55% of the scene are visible in both images and are thus suitable for matching and data fusion endeavours, while about 25% of the scene are affected by either radar shadow or optical occlusion. Taking the image acquisition parameters into account, our findings can provide support regarding the definition of upper bounds for image fusion tasks, as well as help to improve acquisition planning with respect to different application goals.
Modeling anomalous diffusion by a subordinated fractional Lévy-stable process

Two phenomena that can be discovered in systems with anomalous diffusion are long-range dependence and trapping events. The first effect concerns events that are arbitrarily distant but still influence each other exceptionally strongly, which is characteristic for anomalous regimes. The second corresponds to the presence of constant values of the underlying process. Motivated by the relatively poor class of models that can cover these two phenomena, we introduce subordinated fractional Lévy-stable motion with tempered stable waiting times. We present in detail its main properties, propose a simulation scheme and give an estimation procedure for its parameters. The last part of the paper is a presentation, via the Monte Carlo approach, of the effectiveness of the estimation of the parameters.
Spatial and temporal scales of pre-Columbian disturbance associated with western Amazonian lakes

The history of landscape alteration in Amazonia by humans prior to the arrival of Europeans remains poorly understood. Estimates of human population size at the time of European contact vary by several million, and the trajectories of cultural and agricultural development are equally uncertain. The extent to which human populations altered Amazonian ecosystems is a function of population size, land management style, radius of influence of each subpopulation, and the temporal development of settlements. Here we report evidence that relates to the temporal and spatial scales of human disturbance in western Amazonia. Three lake sediment records and 94 terrestrial soil cores located 0–12 km from the adjacent lake were used to examine scales of pre-Columbian human impacts at two sites in western Amazonian forests. Lake sediment and soil charcoal records indicate discontinuous and localized burning around the study areas. Terrestrial soil phytolith and nutrient analyses reveal a range in disturbance intensity between the two sites but contain no evidence of large-scale forest clearing or anthropogenic soil enrichment. Our data suggest that while all of the settings examined were occupied or used, the halo of influence around each was limited. It should not be assumed that intensive landscape transformations by prehistoric human populations occurred throughout Amazonia or that Amazonian forests were resilient in the face of heavy historical disturbance.
Using Author Embeddings to Improve Tweet Stance Classification

Many social media classification tasks analyze the content of a message, but do not consider the context of the message. For example, in tweet stance classification – where a tweet is categorized according to a viewpoint it espouses – the expressed viewpoint depends on latent beliefs held by the user. In this paper we investigate whether incorporating knowledge about the author can improve tweet stance classification. Furthermore, since author information and embeddings are often unavailable for labeled training examples, we propose a semi-supervised pretraining method to predict user embeddings. Although the neural stance classifiers we learn are often outperformed by a baseline SVM, author embedding pre-training yields improvements over a non-pre-trained neural network on four out of five domains in the SemEval 2016 6A tweet stance classification task. In a tweet gun control stance classification dataset, improvements from pre-training are only apparent when training data is limited.
Comparison of the Detection Performance of Three Nonlinear Crystals for the Electro-optic Sampling of a FEL-THz Source

The detector of a FEL-THz source at HUST is now in the physical design stage. The electro-optic (EO) sampling method will be employed for the coherent detection. The performances of three widely used EO crystals will be evaluated and compared numerically in the time domain detection: zinc telluride (ZnTe), gallium arsenide (GaAs) and gallium phosphide (GaP). The phase matching properties are analyzed to find the appropriate probe wavelength. The EO detection response is calculated to select the suitable crystal thickness and to discuss the detection ability of each crystal.
Analysis of EEG Signals for Detection of Seizure Abnormalities

The human brain is like command center of human body . EEG is non-invasive technique of recording electrical patterns in your brain due to firing of neurons. The changes in pattern of EEG can be used to detect if any kind of disorders in human body like seizures, level of anesthesia injected during operations, awakefulness of a person, pattern of migraine etc. These disorders can be easily detected by doctors by observing the EEG patterns of the patients. The analysis of EEG signal for the detection of brain abnormalities is in itself difficult process. So a PC based automatic system is needed for the detection of brain abnormalities. Proposed work can be used as a useful tool in studying normal and abnormal seizure patients and the accuracy of the system with the different routine waves i.e. beta alpha theta delta can be checked for correct detection of seizure abnormality using a PC based system reducing the efforts of the doctors for diagnosing the disorder
Physics of singularities in pressure-impulse theory

The classical solution in the pressure-impulse theory for the inviscid, incompressible, and zero-surface-tension water impact of a flat plate at zero dead-rise angle exhibits both singular-in-time initial fluid acceleration, ∂v/∂t |t=0 ∼ δ(t), and a near-plate-edge spatial singularity in the velocity distribution, v ∼ r−1/2, where r is the distance from the plate edge. The latter velocity divergence also leads to the interface being stretched infinitely right after the impact, which is another nonphysical artifact. From the point of view of matched asymptotic analysis, this classical solution is a singular limit when three physical quantities achieve limiting values: sound speed c0 → ∞, fluid kinematic viscosity ν → 0, and surface tension σ → 0. This leaves open a question on how to resolve these singularities mathematically by including the neglected physical effects—compressibility, viscosity, and surface tension—first one by one and then culminating in the local compressible viscous solution valid for t → 0 and r → 0, demonstrating a nontrivial flow structure that changes with the degree of the bulk compressibility. In the course of this study, by starting with the general physically relevant formulation of compressible viscous flow, we clarify the parameter range(s) of validity of the key analytical solutions including classical ones (inviscid incompressible and compressible, etc.) and understand the solution structure, its intermediate asymptotics nature, characteristics influencing physical processes, and the role of potential and rotational flow components. In particular, it is pointed out that sufficiently close to the plate edge surface tension must be taken into account. Overall, the idea is to highlight the interesting physics behind the singularities in the pressure-impulse theory.
LSH Softmax: Sub-Linear Learning and Inference of the Softmax Layer in Deep Architectures

Log-linear models models are widely used in machine learning, and in particular are ubiquitous in deep learning architectures in the form of the softmax. While exact inference and learning of these requires linear time, it can be done approximately in sub-linear time with strong concentrations guarantees. In this work, we present LSH Softmax, a method to perform sub-linear learning and inference of the softmax layer in the deep learning setting. Our method relies on the popular Locality-Sensitive Hashing to build a well-concentrated gradient estimator, using nearest neighbors and uniform samples. We also present an inference scheme in sub-linear time for LSH Softmax using the Gumbel distribution. On language modeling, we show that Recurrent Neural Networks trained with LSH Softmax perform on-par with computing the exact softmax while requiring sub-linear computations.