Miracle-dz/UniFAR-FTUs huggingface dataset:
Corvidae in Pakistan are Represented by Two Distinct Clades Revealed through Maternally Inherited Gene Region

Corvidae is a species rich and morphologically diverse family of the order Passeriformes (Aves), generally well identified by barcodes globally. Species identification and phylogenetic analysis through DNA barcodes using mitochondrial COI gene (cytochrome c oxidase subunit I) was aimed for samples of birds collected from different regions of Pakistan. Mitochondrial DNA was successfully extracted from keel tissue and Folmer region of COI gene comprising ~650 bps was amplified using universal primers and PCR products were confirmed by 1% agarose gel electrophoresis. Sequencing was carried out by Sanger’s method and BLAST analysis identified these samples as five species ( Urocissa flavirostris , Dendrocitta vagabunda, Corvus splendens, Corvus corax and Corvus macrorhynchos) from three genera of family Corvidae. The nucleotide sequences were submitted to the Barcode of Life Data System (BOLD) and the eligible sequences were assigned the Barcode Index Numbers (BINs). The COI gene sequence data of 8 species of family Corvidae were retrieved from GenBank (NCBI) database and phylogenetic relationship was established in these 13 barcodes. K2-parameter distances were calculated on MEGA7 software with overall average distance of 0.141 calculated at 1000 bootstrap repetitions. Phylogenetic tree reconstructed by neighbour joining method discriminated all species into two distinct clades initially and then into subclades based on similarity and variations in their sequences. Species of the same genera were grouped into one clade as genus Corvus . DNA barcoding was proved to be an effective tool for species molecular identification and their phylogenetic analysis during this study which may help in identification and biogeographic studies of birds in future.
Discrete duality finite volume schemes for doubly nonlinear degenerate hyperbolic-parabolic equations

We consider a class of doubly nonlinear degenerate hyperbolic-parabolic equations with homogeneous Dirichlet boundary conditions, for which we first establish the existence and uniqueness of entropy solutions. We then turn to the construction and analysis of discrete duality finite volume schemes (in the spirit of Domelevo and Omnes [43]) for these problems in two and three spatial dimensions. We derive a series of discrete duality formulas and entropy dissipation inequalities for the schemes. We establish the existence of solutions to the discrete problems, and prove that sequences of approximate solutions generated by the discrete duality finite volume schemes converge strongly to the entropy solution of the continuous problem. The proof revolves around basic a priori estimates, the discrete duality features, Minty–Browder type arguments, and "hyperbolic" L∞ weak-⋆ compactness arguments (i.e. propagation of compactness along the lines of Tartar, DiPerna, …). Our results cover the case of non-Lipschitz nonlinearities.
Analysis of invariants for thermophysical models in infrared image understanding

Object recognition requires robust and stable features that are unique in feature space. Stable long-wave infrared features are invariant to transformations that may be a function of viewing aspect, ambient temperature, wind speed, and solar insolation. Uniqueness guarantees a one-to-one correspondence between feature values and the objects to be recognized. Currently, many features are selected based on intuition and heuristics. Since the extracted features are the foundation upon which the entire object recognition system is built, the limitations of a system cannot be determined and robustness cannot be guaranteed. An improved method for defining classifier features is required—a method that involves more science and less art. The following approach is unique in the field since it considers not just surface reflection and surface geometry in the specification of invariant features, but it also takes into account internal object composition and state which affect images sensed in the non-visible spectrum. The approach utilizes a physics-based model that is derived from the principle of the conservation of energy (COE) applied at the surface of the imaged object. Lie group analysis can determine (absolute) invariant functions for classification in object recognition problems. The mathematics of Lie groups is discussed and its application to the thermophysical model is illustrated. Lie group analysis is used to determine the simplest non-trivial function that has a constant value on the set of all roots of a conservation equation (which determines a manifold). The goal is to use this function for classification. Since the form of the conservation equation remains the same, with only the coefficients changing for different objects, the set of roots will differ depending on the object being viewed. An invariant function of the conservation equation (with the coefficients as parameters) yields different values based upon which object is currently observed. Lie group analysis is used to prove that the thermophysical model is the simplest invariant. Quasi-invariants are a generalization of absolute invariants. Non-trivial absolute invariants are generally rare. Because the restrictions required for absolute invariance are relaxed, quasi-invariants are more common. These types of functions could be just as useful as absolute invariants in practice. A constructive algorithm is developed to find a particular type of quasi-invariant called a Dominant-Subspace Invariant (DSI). Experimental results validate the approach.
The accuracy of diagnosing Burkitt lymphoma in serous effusion specimen: A cytological‐histological correlation with ancillary studies

The objective of this study is to evaluate the effectiveness of diagnosing Burkitt lymphoma (BL) in serous effusion (SE) specimen and summarise the characteristics of BL in SE. We also assess the utility of a germinal centre–associated marker, LMO2, in the differential diagnosis of BL in SE specimens.
An Automated Stock Trading Auditing System Using Hybrid Adaptive Neuro-Fuzzy Inference System (ANFIS)

This study presents a hybrid Adaptive Neuro-Fuzzy Inference System (ANFIS) that automates the audit of listed companies in a stock exchange. Software Methodology employed is object oriented and Model Base Engineering. Financial data collected from Nigeria Stock Exchange for 3 years was used as training set and 2016 financial data of listed companies as research test source data. The Model provides a profit or loss decision based on the evaluation of each listed company, testing and checking were used for validity test. The performance of listed companies for the year 2016 was obtained. Companies with minimal testing value 0.5 to 1 are healthy (profit) and companies with minimal testing value 0 to 0.4 are unhealthy (loss) to invest. The result shows that the prediction model is accurate and will enable investors know the right company that makes profit or loss to invest in. Proposed system performed better than TSFNN system with 86.32% accuracy using Root Mean Square Metrics. This technique was implemented in MATLAB.
REVIEW PAPER ON SENTIMENT CLASSIFICATION OF MOVIES REVIEW.

- The process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer's attitude towards a particular topic, product, etc. is positive, negative, or neutral. The papers are basically focussed on encapsulating the movie reviews at characteristic level so that user can find easily that which character of the movie they liked or disliked. The system also performs subjectivity analysis. The subjective analysis is one and most useful tasks that take place in sentiment analysis. Online reviews have mostly consists of objective and subjective sentences. Talking about the objective sentences, it mostly consists of factual information and no opinion or sentiments. On the other hand, subjective sentences broadly cover the greater interpretation based on personal feeling, emotions, aesthetics etc to find summary at the characteristic level. In this paper, two different methods are implemented for finding subjectivity of sentences and then rule based system is used to find feature-opinion pair and finally the orientation of extracted opinion is revealed using two different method. Initially the proposed system uses SentiWordNet approach to find out orientation of extracted opinion and then it uses the method which is based on lexicon consisting list of positive and negative words.
Characterization of a Novel 4.0-kb Y-type HMW-GS from Eremopyrum distans

A novel 4.0-kb Fy was sequenced and bacterially expressed. This gene, the largest y-type HMW-GS currently reported, is 4,032-bp long and encodes a mature protein with 1,321 amino acid (AA) residues. The 4.0-kb Fy shows novel modifications in all domains. In the N-terminal, it contains only 67 AA residues, as three short peptides are absent. In the repetitive domain, the undecapeptide RYYPSVTSPQQ is completely lost and the dodecapeptide GSYYPGQTSPQQ is partially absent. A novel motif unit, PGQQ, is present in addition to the two standard motif units PGQGQQ and GYYPTSPQQ. Besides, an extra cysteine residue also occurs in the middle of this domain. The large molecular mass of the 4.0-kb Fy is mainly due to the presence of an extra-long repetitive domain with 1,279 AA residues. The novel 4.0-kb Fy gene is of interest in HMW-GS gene evolution as well as to wheat quality improvement with regard to its longest repetitive domain length and extra cysteines residues. with smaller repetitive domains. Our future work will focus on evaluating the wheat quality improvement potential of this larger HMW-GS by introduc-ing it into wheat transgenically.
Design of High-Speed Ultralow Power Time-Based Analog-to-Digital Converters in Nanoscale CMOS

Time-based Analog-to-Digital Converters have become more and more popular due to the fact that they allow us to take advantage of technology scaling and achieve greater time resolution by reducing the gate delay as well as the power consumption. This work focuses at the trade-offs of designing an ADC based on a Local Passive Interpolation TDC [13] [10] in the GHz range in terms of speed, accuracy and power consumption. The proposed architecture after converting the initial voltage value to a time interval through a VTC, it obtains the MSB by a phase detector. The time interval is then fed to an LPI TDC that produces a 64-bit thermometer code. The result from the two different parts of the implementation are combined and a 7-bit digital value arises. The trade-offs and requirements of all the building blocks and the whole ADC are analyzed and taken into consideration. The proposed ADC is implemented in 45 nm CMOS technology. The performance of the ADC and its building blocks is verified by Cadence Virtuoso environment and MATLAB. Simulation results at 1V power supply, show a sampling rate of 1GS/s, resolution 3.13ps and inputs varying with a range from 4MHz up the Nyquist input frequency of 500 MHz at 45nm Technology. For the above requirements the simulation results indicate an SNDR of 40.2 dB and an ENOB of 6.38 bit at the Nyquist input frequency with power consumption of 6.4mW.
ENERGY EFFICIENT IMPROVED LEACH PROTOCOL FOR WIRELESS SENSOR NETWORK

- This research work deals to minimize energy spending of nodes and maximize lifetime of sensor network. As original LEACH (Low Energy Adaptive clustering Hierarchy) protocol selects cluster head (CH) on the basis of a random number generation and it does not see residual energy of nodes. In our dissertation, we proposed a modified cluster head selection algorithm and cluster formation algorithm. Proposed cluster formation algorithm executes in less number of iteration than existing K-Mean algorithm. The cluster formation is done on the basis of nearest neighbor distance algorithm which is an improvement over k-mean algorithm of forming clustering structure. Our simulation outcome show that our proposed protocol is improved in terms of dead node occurrence, percentage of the alive nodes, residual energy and throughput of the sensor network. Hence proposed cluster formation selection of cluster head have performed better than the original LEACH protocol.
Kobe University Repository : Kernel タイトル Tit le The IGF-1 / Akt / S 6 pathway and expressions of glycolyt ic myosin heavy chain isoforms are upregulated in chicken skeletal muscle during the first week after hatching 著者

Skeletal muscle mass is an important trait in animal industry. We previously reported an age-dependent downregulation of the IGF-1/Akt/S6 pathway, major protein synthesis pathway, in chicken breast muscle after 1 week of age, despite a continuous increase of breast muscle weight. Myosin heavy chain (HC), a major protein in muscle fiber, has several isoforms depending on chicken skeletal muscle types. HC I (fast-twitch glycolytic type) is known to be expressed in adult chicken breast muscle. However, little is known about the changes in the expression levels of protein synthesis-related factors and HC isoforms in perihatching chicken muscle. In the present study, protein synthesis-related factors, such as IGF-1 mRNA levels, phosphorylation of Akt, and phosphorylated S6 content, increased in an age-dependent manner after post-hatch day (D) 0. The mRNA levels of HC I, III, and V (fast-twitch glycolytic type) dramatically increased after D0. The increase ratio of breast muscle weight was approximately 1,100% from D0 to D7. To our knowledge, these findings provide the first evidence that upregulation of protein synthesis pathway and transcription of fast twitch glycolytic HC isoforms play critical roles in the increase of chicken breast muscle weight during the first week after hatching.
European Journal of Literature, Language and Linguistics Studies-ISSN 2559-7914

This study uses rigorous validation procedures to validate an attitude towards the intercultural learning community (intercultural posture) scale. 180 Arabic learners at the International Islamic University of Malaysia (IIUM) were given a questionnaire with 25 items represented five sub-dimensions. Exploratory factor (EFA) and confirmatory factor (CFA) respectively applied to validate the final measurement model. SPSS and Amos were used for Data analysis. The final findings yielded only four sub-dimensions to support intercultural posture construct as a multidimensional concept represented: Attitude to Intercultural Tendency, Intercultural Friendship Orientation, Intercultural Working Group, and Intercultural Group Cohesiveness. A validated Intercultural posture of 12 measured items remained in the CFA result that confirmed the final valid instrument. The instrument scale would promote the identifications of variables in the sense of study abroad context which stimulus students’ engagement in intercultural communication in learning the English language.
Design and Validation of a Course Control System for a Wave-Propelled Unmanned Surface Vehicle

Unlike common marine vessels, wave-propelled vehicles cannot directly control their speed, but rely instead on the forces exerted by the environment to navigate as intended. The unique navigation capabilities of such vehicles motivate the study of control solutions that adapt the vehicle heading to the prevailing environmental conditions and ensure robust course-keeping performances across different sea states, winds, and currents over extended periods of time. This article presents the design and experimental validation of a path following and course control system for an underactuated, wave-propelled unmanned surface vehicle (USV). The major focus and novelty of this work stands in the analysis of the model nonlinearities that appear when the vehicle propulsion force does not prevail on the wind and sea current forces generated by the environment. In these situations, low maneuverability is experienced depending on the magnitude of counteracting forces and, in some cases, loss of controllability is a risk. Initial investigation of the vehicle’s nonlinear dynamics is followed by derivation of a simplified quasilinear mathematical model that isolates the major source of nonlinearity. This provides a basis for the control design, the theory of which is supported and validated by extensive field experiments. In particular, when the USV’s ground speed is close to zero, the theory shows singularities in the model that lead to instabilities and loss of controllability of the course over ground that is experienced in the field. Our test results verify that an effective solution is to switch to heading control when the ground speed is small.
Depth Completion with Edge Optimization for Depth Maps from Lidar

Depth completion is an important research field in self-driving which complements depths mapped from point cloud of Lidar. This paper shows a depth completion method combining traditional image processing and image optimization. In our method, a depth map is completed through a series of well-designed morphological dilation and filtering methods, and then is optimized referring to a RGB image and a confidence map. The method is simple, data independent and runs only relying on the CPU. It is evaluated on the challenging KITTI depth completion benchmark [20]. The result performs as good as IP-Basic and better than sparse CNN in depth accuracy. Furthermore, it optimizes the edges of objects in the depth maps, which has a greater help for image segmentation, obstacle perception or other tasks in self-driving.
RESOURCE-BASED VIEW THEORY APPLICATION ON THE EDUCATIONAL SERVICE QUALITY

Background and Objectives: The purpose of this study is to review the resource-based view theory on service quality that contribute to and expand internal resources and services of high quality. Several empirical studies have examined how to apply resource-based view theory to exploiting opportunities in higher education. With the help of this resource-based view theory, urban higher education can apply how to obtain and mobilize additional resources or use existing resources more efficiently and effectively to increase the productivity of existing resources to improve the quality of education services. Perhaps providing high-quality service based views are hampered by a lack of resources for urban education institutions and new ventures, and for them to survive, the resource constraints should address effectively. The issue in this paper is how the RBV theory or concept is to be studied in urban higher education so that researchers and organizations can benefit from this perspective. Methodology: The RBV framework was used to delimit the review so that the research method used in this paper is an empirical approach through a study of journals and supporting journals related to the topic under study. This paper evaluated and reviewed several empirical studies in terms of methodology and strategy that used to apply and implement the resourcebased view theory to improve the service based view quality of students' retention. Many articles indicated quantitative methods as the method strategy, but restrictions showed qualitative and mixed methods that should be concerned in future research. Findings: This article's literature search aimed at obtaining a usable sample of recently published papers to provide a sense of the conceptual gaps, knowledge gaps, methodological gaps and problem gaps in several resource-based (RBV) industries, but lesser are using in education. The dynamics and heterogeneity in this field of science encourage university researchers to develop and strengthen RBV theory. With this development, the concepts and theories of management are expected to be useful for academics. Recommendation & Limitation: On the critical reviews above, specific recommendations may in future serve as the key to enriching resource-based views. In this article, mixed and qualitative methods should be used to obtain accurate results. Additional attention should be paid to future research into higher education institutional resources, and integrate tangible and intangible resources into organizational capacity. Conclusion & Contribution: Resource-based view theory appears to have the capability to leverage resources and create more opportunities with fewer funds when applied to urban systems. One of the biggest contributions of this article is the direct strategy of scholars towards empirical studies and finding of resources as an essential antecedent to service quality and end to educational performance.
Postoperative Mortality After Non-Cardiac Surgery Heart Rate Variability and Cardiac Troponin I Are Incremental and Independent Predictors of One-Year All-Cause Mortality After Major Noncardiac Surgery in Patients at Risk of Coronary Artery Disease

OBJECTIVES The aim of this study was to determine whether perioperative measurements of heart rate variability (HRV) and cardiac troponin I (cTnI) add additional prognostic information to established risk scores for first-year mortality in patients at risk of coronary artery disease (CAD) undergoing major noncardiac surgery. BACKGROUND In cardiac-risk patients undergoing major noncardiac surgery, the shortand long-term prognoses are mainly influenced by perioperative cardiac complications. Heart rate variability and cTnI are important prognostic markers in patients with congestive heart failure and myocardial infarction. METHODS In a prospective study, 173 patients with CAD or at high risk of CAD undergoing major noncardiac surgery were followed up for one year. The main outcome measure was all-cause mortality. In addition to clinical parameters and established risk scores, HRV and cTnI were assessed perioperatively. RESULTS Twenty-eight (16%) patients died within one year. Multivariate logistic regression analysis revealed three findings that were independently associated with death within the first year after surgery: the revised cardiac risk index (odds ratio 6.2 [95% confidence interval 1.6 to 25], depressed HRV before induction of anesthesia (16.2 [2.8 to 94]), and elevation of cTnI on postoperative day 1 or 2 (9.8 [3.0 to 32]). CONCLUSION Depressed HRV before induction of anesthesia and elevated cTnI postoperatively are independent and powerful predictors of one-year mortality for patients at risk of CAD undergoing major noncardiac surgery and add incremental prognostic information to established risk scores that only consider preoperative information. (J Am Coll Cardiol 2003;42:1767–76) © 2003 by the American College of Cardiology Foundation
Evaluation of a Soil Moisture Sensor in Different Soil Textures

Real-time irrigation management considering field condition, has an important role on water saving and stability of agricultural and horticultural production. One of the approaches of real time irrigation management is the use of soil moisture sensors that have important effect on improving water productivity. In this study the feasibility of designing and evaluation of Iranian soil moisture accompanying watermark sensor was investigated in different soil textures. For designing and calibrating of Iranian soil moisture sensor, an experiment was conducted in 2018 and 2019 at Soil and Water Department of Yazd Agricultural and Natural Resources Research and Education Center. The designed sensor was evaluated in three different soil textures including sandy clay loam, loamy and silty clay with 4 replications. The designed and watermark sensors were calibrated in three soil textures, compared and validated with the direct method of soil moisture measurement. Results showed that the designed and watermark sensor could estimate soil moisture in loamy and sandy clay loam soil textures with proper precision. While in silty clay soil texture both designed and watermark sensors couldn't estimate the soil water content with acceptable precision. According to the results of this study, for soil water content lower than 50%AW (50% of available water), the designed and watermark sensors could accurately estimate the soil moisture. While for the soil water content upper than field capacity these sensors couldn’t acceptably estimate soil moisture.