Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Identity Verification Based on Infrared Face Images

Face recognition using visible-image (RGB) has been found to be largely affected by variation of illuminations and face expressions. Relatively, the infrared-image (IR) shows certain robustness with respect to the above external factors. In this work, we focus on identity verification using IR face images and study its robustness in response to variation of above environmental factors and expression. The well-known principal component analysis (PCA) technique and another dimension reduction method, random projection (RP) are adopted to extract necessary IR face features for identity matching. To boost the verification performance, several fusion techniques are proposed and investigated. Our empirical experiments show reasonable effectiveness using IR and its contour images as well as using fusion method for identity verification under several varying conditions.
Generalized Binary Search Trees and Clock Trees Revisited

In this paper, we study two diverse problems from a random matrix perspective. The first one is the problem of binary testing (or object/entity identification) that arises in applications such as active learning, fault diagnosis and computer vision, and the second is the problem of zero or bounded skew clock tree construction which arises in applications such as VLSI circuit design and network multicasting. Though both these problems involve construction of binary trees, the objectives and the greedy algorithms used for binary tree construction are very different. In the problem of binary testing, the goal is to identify an unknown object while minimizing the number of binary questions posed about that object. A binary decision tree is a solution to this problem, where often the goal is to minimize the average depth of the binary tree. Generalized binary search (GBS) is a greedy algorithm that is popularly used in the literature to construct near optimal binary decision trees. Here, we study the depth distribution of trees constructed using GBS and show that it converges to a strange distribution known as the Airy distribution under certain random matrix models. Refer Section 3 for more details. Next, we study the zero or bounded skew clock tree problem. The skew of an edge-weighted rooted tree is defined to be the maximum difference between any two root-to-leaf path weights. Zero or boundedskew trees are needed for achieving synchronization in applications such as network multicasting and VLSI clock routing, where the edge weights correspond to propagation delays. In these applications, the signal generated at the root should be received by multiple recipients located at the leaves (almost) simultaneously. The goal in these problems is to find a zero or bounded-skew tree of minimum total weight, since the weight of the tree corresponds to the amount of resources that must be allocated. Here, we study the skew distribution in clock trees and show that once again, this distribution converges to an Airy distribution as the size of the clock tree increases (refer Section 4). These observations are both surprising and unexpected. Further, they raise several interesting questions regarding the connection of these problems to that of Catalan trees studied in the literature. Also, Airy distribution has been observed to arise as a limit in several other problems involving binary trees in the literature. Hence, these findings pave way for future investigations into these problems by exploiting their relation to previously studied problems.
Non-random distribution of individual genetic diversity along an environmental gradient

Improving our knowledge of the links between ecology and evolution is especially critical in the actual context of global rapid environmental changes. A critical step in that direction is to quantify how variation in ecological factors linked to habitat modifications might shape observed levels of genetic variability in wild populations. Still, little is known on the factors affecting levels and distribution of genetic diversity at the individual level, despite its vital underlying role in evolutionary processes. In this study, we assessed the effects of habitat quality on population structure and individual genetic diversity of tree swallows (Tachycineta bicolor) breeding along a gradient of agricultural intensification in southern Québec, Canada. Using a landscape genetics approach, we found that individual genetic diversity was greater in poorer quality habitats. This counter-intuitive result was partly explained by the settlement patterns of tree swallows across the landscape. Individuals of higher genetic diversity arrived earlier on their breeding grounds and settled in the first available habitats, which correspond to intensive cultures. Our results highlight the importance of investigating the effects of environmental variability on individual genetic diversity, and of integrating information on landscape structure when conducting such studies.
Implementation for Multiplying IEEE 754-2008 Binary 32 Bit Number Using Verilog

The main aim of this paper is to design a parameterized 32 bit floating point multiplier which is based on IEEE 754-2008 binary interchange format. The proposed work is capable of checking overflow and underflow using corresponding flags by flagger circuit. In this design rounding modes are also considered based on the two bit control signal provided as input such as round to nearest even, round to zero, round to positive infinity and round to negative infinity for better accuracy of output result. The delay summary report generated presents a chart of some of the delay list in implementing the design, the numbers of signals are completely routed in this design. The total gate delay is 22.94ns. The xpower analyzer tool is used to calculate power of this implemented design which comes out to be 34mw. The proposed design of floating point multiplier format is implemented on Xilinx virtex-6, Xp6gls240t family, 40 nm technology, which is having top level source as HDL, the synthesis tool used is XST (Verilog/Vhdl), and the preferred language is Verilog. The core is verified against Xilinx floating point multiplier and simulation has been done on unified ISE simulator.
Students’ Conceptions of and Feelings About Land Use: Building a Conceptual Framework for Teaching and Learning About Land Use

Abstract The purpose of this study was to investigate students’ conceptions of and feelings about land use. Specifically: (1) What are students’ conceptions of and feelings about land use? And (2) in what ways might students’ conceptions and feelings vary by community setting and grade level? This study was qualitative and descriptive in nature and reflected a cross-age design involving the collection of qualitative data from 863 students, grades 4 through 12, from the Midwestern United States. These qualitative data were analyzed for their content in an inductive manner. Five categories of land use and three categories of feelings about land use emerged from the data. Based on these findings, a land use framework is recommended that builds on the students’ conceptions, the scientific perspective, and the NRC (2012) science education framework.
An ensemble of morphology based Pattern Spectrum and Height functions for shape representation and classification

In this paper, we propose a combined classifier model based on Pattern Spectrum (PS) and Height functions (HF) to classify shapes accurately. The PS captures the intrinsic details of shape, the HF is insensitive to geometric transformations and nonlinear deformations, and hence combined to represent/classify shapes accurately. The Earth Movers Distance (EMD) metric in case of PS and Dynamic Programming (DP) in case of HF were respectively employed to obtain similarity values and fused to classify a given query shape based on minimum similarity value. The experiments are conducted on publicly available shape datasets namely MPEG-7, Kimia-99, Kimia-216, Myth and Tools-2D and the results are presented by means of Bull's eye score. The comparative study is also provided with the well known approaches to exhibit the retrieval accuracy of the proposed approach. The proposed approach shows better results compared to other algorithms.
Femtosecond Laser Processing of Nitinol

The effects of femtosecond laser machining on surface characteristics and subsurface microstructure of a Nitinol alloy were studied. The femtosecond laser machining produced an average surface roughness of 0.2 μm. A re-deposited layer of 7 μm and a hardened layer of 70 μm were also resulted from the machining.
Formal Description of OCL Specification Patterns for Behavioral Specification of Software Components

The Object Constraint Language (OCL) is often used for behavioral specification of software components. One current problem in specifying behavioral aspects comes from the fact that editing OCL constraints manually is time consuming and error-prone. To simplify constraint definition we propose to use specification patterns for which OCL constraints can be generated automatically. In this paper we outline this solution proposal and develop a way how to formally describe such specification patterns on which a library of reusable OCL specifications is based.
House Finch Populations Differ in Early Inflammatory Signaling and Pathogen Tolerance at the Peak of Mycoplasma gallisepticum Infection

Host individuals and populations often vary in their responses to infection, with direct consequences for pathogen spread and evolution. While considerable work has focused on the mechanisms underlying differences in resistance—the ability to kill pathogens—we know little about the mechanisms underlying tolerance—the ability to minimize fitness losses per unit pathogen. Here, we examine patterns and mechanisms of tolerance between two populations of house finches (Haemorhous [formerly Carpodacus] mexicanus) with different histories with the bacterial pathogen Mycoplasma gallisepticum (MG). After infection in a common environment, we assessed two metrics of pathology, mass loss and eye lesion severity, as proxies for fitness. We calculated tolerance using two methods, one based on pathology and pathogen load at the peak of infection (point tolerance) and the other based on the integrals of these metrics over time (range tolerance). Alabama birds, which have a significantly longer history of exposure to MG, showed more pronounced point tolerance than Arizona birds, while range tolerance did not differ between populations. Alabama birds also displayed lower inflammatory cytokine signaling and lower fever early in infection. These results suggest that differences in inflammatory processes, which can significantly damage host tissues, may contribute to variation in tolerance among house finch individuals and populations. Such variation can affect pathogen spread and evolution in ways not predictable by resistance alone and sheds light on the costs and benefits of inflammation in wild animals.
IL-10 and ET-1 as biomarkers of rheumatic valve disease

Objective To evaluate the immunological profile and gene expression of endothelin-1 (ET-1) in mitral valves of patients with rheumatic fever originated from a reference service in cardiovascular surgery. Methods This was a quantitative, observational and cross-sectional study. Thirty-five subjects (divided into four groups) participated in the study, 25 patients with chronic rheumatic heart disease and ten control subjects. The mean age of the sample studied was 34.5 years. Seventeen of them (48.58%) were male and 18 (51.42%) were female. Inflammatory cytokines (TNF-α, IL-4 and IL-10) were measured and ten mitral valves of patients who underwent first valve replacement were collected for determination of gene expression of endothelin-1 by real time PCR. Results Among the groups studied (patients vs. controls), there was a statistically significant difference in IL-10 levels (P=0.002), and no differences in other cytokines. Expression of endothelin-1 was observed in 70% of samples. Quantitatively, average of ET-1 expression was 62.85±25.63%. Conclusion Inflammatory cytokine IL-10 participates in the maintenance of chronicity of rheumatic fever in patients who underwent valve replacement and those who are undergoing medical treatment. The expression of endothelin-1 in heart valve lesions in patients undergoing mitral valve replacement confirms its association with inflammatory activity in rheumatic fever.
Quantification of RNA integrity and its use for measurement of transcript number

RNA degradation can distort or prevent measurement of RNA transcripts. A mathematical model for degradation was constructed, based on random RNA damage and exponential polymerase chain reaction (PCR) amplification. Degradation, measured as the number of lesions/base, can be quantified by amplifying several sequences of a reference gene, calculating the regression of Ct on amplicon length and determining the slope. Reverse transcriptase–quantitative PCR (RT–qPCR) data can then be corrected for degradation using lesions/base, amplicon length(s) and the relevant equation obtained from the model. Several predictions of the model were confirmed experimentally; degradation in a sample quantified using the model correlated with degradation quantified using an additional control sample and the ΔΔCt method and application of the model corrected erroneous results for relative quantification resulting from degradation and differences in amplicon length. Compared with RIN, the method was quantitative, simpler, more sensitive and spanned a wider range of RNA damage. The method can use either random or specifically primed complementary DNA and it enables relative and absolute quantification of RNA to be corrected for degradation. The model and method should be applicable to many situations in which RNA is quantified, including quantification of RNA by methods other than nucleic acid amplification.
Common Subspace for Model and Similarity: Phrase Learning for Caption Generation from Images

Generating captions to describe images is a fundamental problem that combines computer vision and natural language processing. Recent works focus on descriptive phrases, such as "a white dog" to explain the visual composites of an input image. The phrases can not only express objects, attributes, events, and their relations but can also reduce visual complexity. A caption for an input image can be generated by connecting estimated phrases using a grammar model. However, because phrases are combinations of various words, the number of phrases is much larger than the number of single words. Consequently, the accuracy of phrase estimation suffers from too few training samples per phrase. In this paper, we propose a novel phrase-learning method: Common Subspace for Model and Similarity (CoSMoS). In order to overcome the shortage of training samples, CoSMoS obtains a subspace in which (a) all feature vectors associated with the same phrase are mapped as mutually close, (b) classifiers for each phrase are learned, and (c) training samples are shared among co-occurring phrases. Experimental results demonstrate that our system is more accurate than those in earlier work and that the accuracy increases when the dataset from the web increases.
Power spectrum analysis of three-dimensional redshift surveys

We develop a general method for power spectrum analysis of three dimensional redshift surveys. We present rigorous analytical estimates for the statistical uncertainty in the power and we are able to derive a rigorous optimal weighting scheme under the reasonable (and largely empirically verified) assumption that the long wavelength Fourier components are Gaussian distributed. We apply the formalism to the updated 1-in-6 QDOT IRAS redshift survey, and compare our results to data from other probes: APM angular correlations; the CfA and the Berkeley 1.2Jy IRAS redshift surveys. Our results bear out and further quantify the impression from e.g.\ counts-in-cells analysis that there is extra power on large scales as compared to the standard CDM model with $\Omega h\simeq 0.5$. We apply likelihood analysis using the CDM spectrum with $\Omega h$ as a free parameter as a phenomenological family of models; we find the best fitting parameters in redshift space and transform the results to real space. Finally, we calculate the distribution of the estimated long wavelength power. This agrees remarkably well with the exponential distribution expected for Gaussian fluctuations, even out to powers of ten times the mean. Our results thus reveal no trace of periodicity or other non-Gaussian behavior.
Formation of mRNA 3′ Ends in Eukaryotes: Mechanism, Regulation, and Interrelationships with Other Steps in mRNA Synthesis

SUMMARY Formation of mRNA 3′ ends in eukaryotes requires the interaction of transacting factors with cis-acting signal elements on the RNA precursor by two distinct mechanisms, one for the cleavage of most replication-dependent histone transcripts and the other for cleavage and polyadenylation of the majority of eukaryotic mRNAs. Most of the basic factors have now been identified, as well as some of the key protein-protein and RNA-protein interactions. This processing can be regulated by changing the levels or activity of basic factors or by using activators and repressors, many of which are components of the splicing machinery. These regulatory mechanisms act during differentiation, progression through the cell cycle, or viral infections. Recent findings suggest that the association of cleavage/polyadenylation factors with the transcriptional complex via the carboxyl-terminal domain of the RNA polymerase II (Pol II) large subunit is the means by which the cell restricts polyadenylation to Pol II transcripts. The processing of 3′ ends is also important for transcription termination downstream of cleavage sites and for assembly of an export-competent mRNA. The progress of the last few years points to a remarkable coordination and cooperativity in the steps leading to the appearance of translatable mRNA in the cytoplasm.
Collaborative Design of a New Dual-Bandpass 180$^{\circ}$ Hybrid Coupler

A new dual-bandpass 180° hybrid coupler, based on four properly designed shorted-stub loaded stepped-impedance resonators, is proposed in this paper. In order to construct the collaboratively designed coupler/filter, the resonators are coupled magnetically and electrically with each other through three shorted stubs and an open coupled line, respectively. According to the approach of filter synthesis and the derived design equations, the characteristic admittances and electrical lengths of the resonators and coupling sections are determined to achieve the desired resonant frequencies, external Q factors, and internal coupling coefficients for dual passbands. A design procedure is provided. The design flexibilities for ratios of central frequencies and achievable bandwidths are explored. The component shows both filtering and power dividing functions within two specific passbands, whose good performances are demonstrated by the simulated and measured results. The two second-order passbands of a fabricated prototype are located at 2.42 and 5.84 GHz, with 4.6% and 5.2% bandwidths, respectively. The insertion losses are 1.0 and 1.4 dB over 3-dB power division. The isolations are better than 23.5 and 32.8 dB. In both the in-phase and out-of-phase responses, the in-band amplitude and phase imbalances are always within -1.6-0.6 dB and -6.5°-9.5°, respectively.
Dependence of entrainment in shallow cumulus convection on vertical velocity and distance to cloud edge

The dependence of entrainment rate on environmental conditions and cloud characteristics is investigated using large eddy simulations (LES) of the response of shallow cumulus convection to a small‐amplitude temperature perturbation that is horizontally uniform and localized in height. The simulated cumulus fields are analyzed in the framework of an ensemble of entraining plumes by tracking a large number of Lagrangian parcels embedded in the LES and grouping them into different plumes based on their detrainment heights. The results show that fractional entrainment rate per unit height of a plume is inversely proportional to the plume's vertical velocity and its distance to the cloud edge, while changes in environmental stratification and relative humidity, the plume's buoyancy, or the vertical gradient of its buoyancy due to the temperature perturbation have little effect on the plume's entrainment rate.
Strategic Agility in MNEs: Managing Tensions to Capture Opportunities across Emerging and Established Markets

Traditional sources of sustainable competitive advantages are very rare in today's heterogeneous and hyper-competitive global business environment. This article identifies and illustrates three dynamic capabilities—sensing local opportunities, enacting global complementarities, and appropriating local value—by which MNEs are able to operate successfully across emerging and established markets. For MNEs in these markets, strategic agility is a meta-capability that enables them to create and deploy these three capabilities in a dynamic balance over time. Doing so demands embracing the tensions between these capabilities effectively.
Using Machine Learning and Natural Language Processing Algorithms to Automate the Evaluation of Clinical Decision Support in Electronic Medical Record Systems

Introduction: As the number of clinical decision support systems (CDSSs) incorporated into electronic medical records (EMRs) increases, so does the need to evaluate their effectiveness. The use of medical record review and similar manual methods for evaluating decision rules is laborious and inefficient. The authors use machine learning and Natural Language Processing (NLP) algorithms to accurately evaluate a clinical decision support rule through an EMR system, and they compare it against manual evaluation. Methods: Modeled after the EMR system EPIC at Maine Medical Center, we developed a dummy data set containing physician notes in free text for 3,621 artificial patients records undergoing a head computed tomography (CT) scan for mild traumatic brain injury after the incorporation of an electronic best practice approach. We validated the accuracy of the Best Practice Advisories (BPA) using three machine learning algorithms—C-Support Vector Classification (SVC), Decision Tree Classifier (DecisionTreeClassifier), k-nearest neighbors classifier (KNeighborsClassifier)—by comparing their accuracy for adjudicating the occurrence of a mild traumatic brain injury against manual review. We then used the best of the three algorithms to evaluate the effectiveness of the BPA, and we compared the algorithm’s evaluation of the BPA to that of manual review. Results: The electronic best practice approach was found to have a sensitivity of 98.8 percent (96.83–100.0), specificity of 10.3 percent, PPV = 7.3 percent, and NPV = 99.2 percent when reviewed manually by abstractors. Though all the machine learning algorithms were observed to have a high level of prediction, the SVC displayed the highest with a sensitivity 93.33 percent (92.49–98.84), specificity of 97.62 percent (96.53–98.38), PPV = 50.00, NPV = 99.83. The SVC algorithm was observed to have a sensitivity of 97.9 percent (94.7–99.86), specificity 10.30 percent, PPV 7.25 percent, and NPV 99.2 percent for evaluating the best practice approach, after accounting for 17 cases (0.66 percent) where the patient records had to be reviewed manually due to the NPL systems inability to capture the proper diagnosis. Discussion: CDSSs incorporated into EMRs can be evaluated in an automatic fashion by using NLP and machine learning techniques.