Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Of Full-Duplex One-Way And Two-Way Cooperative Relaying Networks

The wireless research requires concurrent transmission and reception in a single time/frequency channel with good spectral efficiency. The Full duplex system is the alternate for the conventional half duplex systems. An investigation on the need for a full duplex two way (FD-TWR) and one way relaying (FD-OWR) to improve the performance of outage probability and average rate employing amplify-and-forward (AF) and decode-and-forward (DF) protocol is considered. Further the relaying systems performance under the network coding schemes is taken into consideration. The outage probability and average rate of FD-TWR and FD-OWR using a physical layer network coding was performed. In contrast to “straightforward” network coding which performs arithmetic function on digital bit streams after information have been received. The result shows the DF protocol achieves better outage probability and average rate, when compared to the AF protocol. And comparing the full duplex schemes like FD-TWR and FD-OWR, it is found that the FD-TWR achieves better outage probability and average rate, when compared to the FD-OWR. The performance was extended with different loop interference among the relay antennas. The performance show that FD-TWR performs well even in spite of loop interference.
Hierarchical Multi‐Step Folding of Polymer Bilayers

A highly complex multi‐step folding of isotropic stimuli‐responsive polymer bilayers resulting in a variety of 2D and 3D structures is reported. Experimental observations allow determination of empirical rules, which can be used to direct the folding of polymer films in a predictable manner. In particular, it is demonstrated that these rules can be used for the design of a 3D pyramid. The understanding and know‐how attained in this study allow the very simple design of highly complex, self‐folding 3D objects and open new horizons for 3D patterning, important for the design of microfluidic devices, biomaterials, and soft electronics.
Implementation Oriented Phase based IRIS Recognition

Phase based image matching is one of the technique which is used for iris recognition. In this technique phase component present in Two dimensional (2D) Discrete Fourier Transform (DFT) of given images are used to determine similarity between two images. This technique can be used for developing applications such as access control system. But here problem is size of iris database. As number of individuals using such application will go on increasing, size of iris database will also go on increasing. This paper discusses the method which is used to address this problem. In this paper 2D Fourier phase code (2D FPC) is used to represent iris information. Instead of storing whole iris image, only 2D FPC is stored in the database which reduces size of required database significantly. This method is evaluated with CASIA iris image database (version 1.0).
Sensing Shear Strains with Electrostriction Effect in Solid Electrorheological Composites

Solid electrorheological (ER) composites are created by applying an electric field to a liquid suspension of isotropic, homogeneously distributed inclusions and cross-linking the obtained transverse isotropic structure. Electrostriction phenomenon in ER composites can be defined as change in dielectric properties with deformation. Solid dielectric material, which consists of inclusions arranged in a chain-like structure and embedded in a matrix phase, demonstrates strong electrostriction response to normal and shear deformations. Such high sensitivity of ER composites to shear electrostriction can be utilized for sensing shear stresses and strains in active damping of vibrations. In this article, we model an electrostriction response and measure electromechanical properties of solid ER composites.
Construction of a support system for learning character balance in transcription for beginners

Learning character balance is important in calligraphy. Transcription is the practice method for learning characters, however it has some problems, for example, it is hard to judge intuitively whether character balance is correct, because the sheet of white paper and the sample image are separate. Therefore, the goal of our study is the construction of a support system for learning character balance in transcription, for beginners. The proposed system uses a tablet-type device. Learners practice transcription in Indian ink on a sheet of white paper laid on top of the tablet-type device which is displaying a sample character. Learners can see the contents displayed by the tablet-type device because a sheet of white paper is thin. Moreover, the tablet-type device can recognize the touch of a Japanese brush wrapped in conductive tape. The system offers a function that changes the sample characters based on the learner's skill level to withdraw from the system support. We have developed a prototype system, and evaluated its effectiveness through actual use of the system.
Recent advances in short-wavelength AR coatings for thinned CCDs

This paper discusses the development of two materials as AR coatings for thinned backilluminated charge-coupled devices. The first material is the heavy metal oxide Ta205 deposited as a spin on layer using sol-gel technology. The second material is Si3N4. Both these films have the high index of refraction and low absorption coefficients needed to produce good AR coatings in the near UV down to 300 nm. The goal of the program was to produce a coating which would yield devices with quantum efficiencies of greater than 50 at 300 nm. Both these materials satisfy this goal. Data on test devices will be reported. 1.
Bayesian Optimization Using Monotonicity Information and Its Application in Machine Learning Hyperparameter

We propose an algorithm for a family of optimization problems where the objective can be decomposed as a sum of functions with monotonicity properties. The motivating problem is optimization of hyperparameters of machine learning algorithms, where we argue that the objective, validation error, can be decomposed as monotonic functions of the hyperparameters. Our proposed algorithm adapts Bayesian optimization methods to incorporate the monotonicity constraints. We illustrate the advantages of exploiting monotonicity using illustrative examples and demonstrate the improvements in optimization efficiency for some machine learning hyperparameter tuning applications.
A Modified Reading the Mind in the Eyes Test Predicts Behavioral Variant Frontotemporal Dementia Better Than Executive Function Tests

Behavioral variant frontotemporal dementia (bvFTD) is characterized by deep alterations in behavior and personality. Although revised diagnostic criteria agree for executive dysfunction as most characteristic, impairments in social cognition are also suggested. The study aimed at identifying those neuropsychological and behavioral parameters best discriminating between bvFTD and healthy controls. Eighty six patients were diagnosed with possible or probable bvFTD according to Rascovsky et al. (2011) and compared with 43 healthy age-matched controls. Neuropsychological performance was assessed with a modified Reading the Mind in the Eyes Test (RMET), Stroop task, Trail Making Test (TMT), Hamasch-Five-Point Test (H5PT), and semantic and phonemic verbal fluency tasks. Behavior was assessed with the Apathy Evaluation Scale, Frontal Systems Behavioral Scale, and Bayer Activities of Daily Living Scale. Each test’s discriminatory power was investigated by Receiver Operating Characteristic curves calculating the area under the curve (AUC). bvFTD patients performed significantly worse than healthy controls in all neuropsychological tests. Discriminatory power (AUC) was highest in behavioral questionnaires, high in verbal fluency tasks and the RMET, and lower in executive function tests such as the Stroop task, TMT and H5PT. As fluency tasks depend on several cognitive functions, not only executive functions, results suggest that the RMET discriminated better between bvFTD and control subjects than other executive tests. Social cognition should be incorporated into diagnostic criteria for bvFTD in the future, such as in the International Classification of Diseases (ICD)-11, as already suggested in the Diagnostic and Statistical Manual for Mental Disorders (DSM)-5.
The Somatostatin 2A Receptor Is Enriched in Migrating Neurons during Rat and Human Brain Development and Stimulates Migration and Axonal Outgrowth

The neuropeptide somatostatin has been suggested to play an important role during neuronal development in addition to its established modulatory impact on neuroendocrine, motor and cognitive functions in adults. Although six somatostatin G protein-coupled receptors have been discovered, little is known about their distribution and function in the developing mammalian brain. In this study, we have first characterized the developmental expression of the somatostatin receptor sst2A, the subtype found most prominently in the adult rat and human nervous system. In the rat, the sst2A receptor expression appears as early as E12 and is restricted to post-mitotic neuronal populations leaving the ventricular zone. From E12 on, migrating neuronal populations immunopositive for the receptor were observed in numerous developing regions including the cerebral cortex, hippocampus and ganglionic eminences. Intense but transient immunoreactive signals were detected in the deep part of the external granular layer of the cerebellum, the rostral migratory stream and in tyrosine hydroxylase- and serotonin- positive neurons and axons. Activation of the sst2A receptor in vitro in rat cerebellar microexplants and primary hippocampal neurons revealed stimulatory effects on neuronal migration and axonal growth, respectively. In the human cortex, receptor immunoreactivity was located in the preplate at early development stages (8 gestational weeks) and was enriched to the outer part of the germinal zone at later stages. In the cerebellum, the deep part of the external granular layer was strongly immunoreactive at 19 gestational weeks, similar to the finding in rodents. In addition, migrating granule cells in the internal granular layer were also receptor-positive. Together, theses results strongly suggest that the somatostatin sst2A receptor participates in the development and maturation of specific neuronal populations during rat and human brain ontogenesis.
Single-case cognitive neuropsychology in the age of big data

ABSTRACT Historically, single-case studies of brain-damaged individuals have contributed substantially to our understanding of cognitive processes. However, the role of single-case cognitive neuropsychology has diminished with the proliferation of techniques that measure neural activity in humans. Instead, large-scale informatics approaches in which data are gathered from hundreds of neuroimaging studies have become popular. It has been claimed that utilizing these informatics approaches can address problems found in single imaging studies. We first discuss reasons for why cognitive neuropsychology is thought to be in decline. Next, we note how these informatics approaches, while having benefits, are not particularly suited for understanding functional architectures. We propose that the single-case cognitive neuropsychological approach, which is focused on developing models of cognitive processing, addresses several of the weaknesses inherent in informatics approaches. Furthermore, we discuss how using neural data from brain-damaged individuals provides data that can inform both cognitive and neural models of cognitive processing.
Multiple-Input Single-Output Wireless Power Transmission System for Coal Mine

In Wireless Power Transmission (WPT) systems, the proportion of energy received by the load is critical and the efficiency is the more significant parameter. The magnetic multiple input algorithms as well as many multiple overlapping coils structures in the transmitter side are proposed for the coal mine Internet of the Things (IOT) nodes. Different phase shifts cases for the input signal were considered to study their effect on the efficiency. Simulation results showed that the axial component of magnetic induction resulted from the multiple overlapping coils structure has preferable homogeneous distribution over the traditional single input coil. The proposed system achieved an efficiency value of 60 % for a receiver placed 40 cm away from a 4 coils transmitter comparing to an efficiency value of 50% for the same distance using a single coil transmitter. Simulation results shows that the proposed model is well adapted for the movable charging mode for the IOT nodes in coal mine. DOI : http://dx.doi. org/10.11591/telkomnika.v12i6. 5439 Full Text: PDF
A Novel System for Correction of Relative Angular Displacement between Airborne Platform and UAV in Target Localization

This paper provides a system and method for correction of relative angular displacements between an Unmanned Aerial Vehicle (UAV) and its onboard strap-down photoelectric platform to improve localization accuracy. Because the angular displacements have an influence on the final accuracy, by attaching a measuring system to the platform, the texture image of platform base bulkhead can be collected in a real-time manner. Through the image registration, the displacement vector of the platform relative to its bulkhead can be calculated to further determine angular displacements. After being decomposed and superposed on the three attitude angles of the UAV, the angular displacements can reduce the coordinate transformation errors and thus improve the localization accuracy. Even a simple kind of method can improve the localization accuracy by 14.3%.
Improving Retrieval Modeling Using Cross Convolution Networks And Multi Frequency Word Embedding

To build a satisfying chatbot that has the ability of managing a goal-oriented multi-turn dialogue, accurate modeling of human conversation is crucial. In this paper we concentrate on the task of response selection for multi-turn human-computer conversation with a given context. Previous approaches show weakness in capturing information of rare keywords that appear in either or both context and correct response, and struggle with long input sequences. We propose Cross Convolution Network (CCN) and Multi Frequency word embedding to address both problems. We train several models using the Ubuntu Dialogue dataset which is the largest freely available multi-turn based dialogue corpus. We further build an ensemble model by averaging predictions of multiple models. We achieve a new state-of-the-art on this dataset with considerable improvements compared to previous best results.
Holomorphic k-differentials and holomorphic approximation on open Riemann surfaces

This thesis consists of two parts: In the first part (Chapters 1 and 2) we study some spaces of holomorphic k−differentials on open Riemann surfaces, and make some observations about these spaces, then we obtain two main theorems about the kernel of Poincaré series map. In the second part (Chapters 3 and 4), we study holomorphic and meromorphic approximation on closed subsets of non-compact Riemann surfaces. We add a condition to the Extension Theorem and correct its proof. The Extension Theorem was first stated and proved by G. Schmieder, but there are a few examples where the theorem as stated by Schmieder fails. That added condition is slightly affecting the definition of a class of closed sets (which is called “weakly of infinite genus”) where approximation is possible.
Complete genome sequence and analysis of the industrial Saccharomyces cerevisiae strain N85 used in Chinese rice wine production

Abstract Chinese rice wine is a popular traditional alcoholic beverage in China, while its brewing processes have rarely been explored. We herein report the first gapless, near-finished genome sequence of the yeast strain Saccharomyces cerevisiae N85 for Chinese rice wine production. Several assembly methods were used to integrate Pacific Bioscience (PacBio) and Illumina sequencing data to achieve high-quality genome sequencing of the strain. The genome encodes more than 6,000 predicted proteins, and 238 long non-coding RNAs, which are validated by RNA-sequencing data. Moreover, our annotation predicts 171 novel genes that are not present in the reference S288c genome. We also identified 65,902 single nucleotide polymorphisms and small indels, many of which are located within genic regions. Dozens of larger copy-number variations and translocations were detected, mainly enriched in the subtelomeres, suggesting these regions may be related to genomic evolution. This study will serve as a milestone in studying of Chinese rice wine and related beverages in China and in other countries. It will help to develop more scientific and modern fermentation processes of Chinese rice wine, and explore metabolism pathways of desired and harmful components in Chinese rice wine to improve its taste and nutritional value.
A Study on Optimal Strategy in Relative Radiometric Calibration for Optical Sensors

Based on the analysis of three main factors involved in the relative radiometric calibration for optical sensors, namely: the number of radiance level; the number of measurements at each level; and the radiance level grouping method, an optimal strategy is presented in this paper for relative radiometric calibration. First, the maximization to the possible extent of either the number of the radiance level or the number of measurements at each level can improve the precision of the calibration results, where the recommended number of measurements is no less than 20. Second, when the number of the radiance level is divisible by four, dividing all the levels evenly into four groups by intensity gradient order and conducting averages for each group could achieve calibration results with the highest precision, which is higher than the result of no grouping or any other grouping method with the mean square error being 22Mn/IT (where Mn is the mean square error of noise in the calibration data, I is the number of the radiance level, and T is the number of measurements for each level. In this case, the first two factors had an equivalent effect and showed their strongest effect on the precision. Third, when the calibration data were not evenly divided, the number of measurements demonstrated a stronger effect than the number of the radiance level. These cognitions are helping to achieve more precise relative radiometric calibration of optical sensors.
PRODIGY: an integrated architecture for planning and learning

Artificial intelligence has progressed to the point where multiple cognitive capabilities are being integrated into computational architectures, such as SOAR, PRODIGY, THEO, and ICARUS. This paper reports on the PRODIGY architecture, describing its planning and problem solving capabilities and touching upon its multiple learning methods. Learning in PRODIGY occurs at all decision points and integration in PRODIGY is at the knowledge level; the learning and reasoning modules produce mutually interpretable knowledge structures. Issues in architectural design are discussed, providing a context to examine the underlying tenets of the PRODIGY architecture.
β-Elemene Reverses Chemoresistance of Breast Cancer via Regulating MDR-Related MicroRNA Expression

Background: Multidrug resistance (MDR) directly contributes to the clinical failure of chemotherapy in breast cancer (BCA). β-elemene is a natural antitumor drug from plants. We previously confirmed that MDR could be reversed by β-elemene. In this study, we intended to investigate the reversal effect of β-elemene on MDR in human BCA adriacin (Adr) -resistant MCF-7 cells (MCF-7/Adr) and docetaxel (Doc) - resistant MCF-7 cells (MCF-7/Doc) through the gene regulatory network. Methods: MTT-cytotoxic, miRNA microarray, Real-time quantitative PCR, Dual Luciferase Activity Assay, Western blot analysis were performed to investigate the impact of β-elemene on chemo-resistant BCA cell suvival, and its impact on the expression of chemo-resistance specific miRNA and the downstream target genes PTEN and Pgp. Results: Compared with the miRNAs expression profiles of MCF-7/Adr and MCF-7/Doc cell lines from our previous studies, there were 322 differentially expressed miRNAs in MCF-7/Adr and MCF-7/Doc breast cancer cells with β-elemene intervention (50μM/L) for 30h, and 6 miRNAs were significantly up-regulated and 12 miRNAs were significantly down-regulated in both MCF-7/Adr and MCF-7/Doc. We have testified that 5 miRNA is related to MDR before, in this study, the expression of miR-34a, miR-222, miR-452 and miR-29a can lead to changes of the characteristics of chemo-resistant MCF-7/Adr and MCF-7/Doc. The PTEN expression under intervention of β-elemene was significantly increased and Pgp expression under β-elemene intervention was significantly decreased in both cell lines. Conclusions: β-elemene could influence MDR related miRNA expression and subsequently regulate the expression of the target genes PTEN and Pgp, which may lead to reduction of the viability of the chemo-resistant breast cancer cells.
65.3: Phase‐Modulation LCoS Display System with Off‐Axis LED Reconstruction Light

A near eye holographic display using light‐emitted diode (LED) instead of laser diode as the reconstruction light source has been proposed. An off‐axis illumination architecture on a phase modulation only liquid crystal on silicon(LCoS) panel is used for investigating the influence of LED source property on the reconstruction image quality.
From Actor Event-Loop to Agent Control-Loop: Impact on Programming

Event-loops and control-loops are the main control architectures adopted in actors and in agents, respectively. These architectures have a strong impact on the principles and discipline that can be adopted to design and program actors and agents. In this paper we develop this point, considering some main models/languages/technologies - ActorFoundry, Akka Actors, SALSA, AmbientTalk on the actor side and Jason and ALOO on the agent side - discussing and comparing them.
Feasibility, architecture and cost considerations of using TVWS for rural Internet access in 5G

The cellular technology is mostly an urban technology that has been unable to serve rural areas well. This is because the traditional cellular models are not economical for areas with low user density and lesser revenues. In 5G cellular networks, the coverage dilemma is likely to remain the same, thus widening the rural-urban digital divide further. It is about time to identify the root cause that has hindered the rural technology growth and analyse the possible options in 5G architecture to address this issue. We advocate that it can only be accomplished in two phases by sequentially addressing economic viability followed by performance progression. We deliberate how various works in literature focus on the later stage of this ‘two-phase’ problem and are not feasible to implement in the first place. We propose the concept of TV band white space (TVWS) dovetailed with 5G infrastructure for rural coverage and show that it can yield cost-effectiveness from a service provider's perspective.