Miracle-dz/UniFAR-FTUs huggingface dataset:
Secure Messaging Platform Using Blockchain Technology

This work aims to study the feasibility and advantages of blockchain technology in chat applications and propose a blockchain-based system for the messaging system. The existing Messaging System is based on centralized computing system architecture, but on a broader level replicas of such servers are distributed over several regions or zones. Secondly, the issue with the existing chat system is privacy, confidentiality, and trust. As every chat and related data is processed via centralized systems which are prone to various Cyber attacks like MITM, EFAIL, and others. This work proposed a blockchain-based system to counter and address such issues that exist in messaging systems and to help the user to exchange message and information securely.
Effectiveness and Safety of Shorter-Term Regimen (STR) for Multidrug-Resistant Tuberculosis (MDR-TB) Treatment: A Systematic Review of Cohort Studies

The Multidrug-resistantce tuberculosis (MDR-TB) remains a public health burden in facing global TB treatment. Patients infected with MDR-TB are resistant to isoniazid and rifampicin due to genotypic mutation, thus proven incurable by standard first-line treatment. Patients infected with MDR-TB are resistant to isoniazid and rifampicin, thus proven incurable by standard first-line treatment. The management of MDR-TB using Short-Term Regimen (STR) is a crucial topic to be discussed due to low success rate of conventional therapy and its long duration. This systematic review aims to further examine the effectiveness and safety of STR to manage MDR-TB. In this systematic review, various cohort studies were searched using standardized Preferred Reporting Items for Systematic Reviews and Meta-Analyzes (PRISMA). The keywords were arranged based on Problem, Intervention, Comparison, and Outcome (PICO) . Key terms consisted of multidrug-resistant tuberculosis and short regimen therapy. Seven cohort studies were selected from 314 studies. STR has better therapeutic efficacy and shorter duration than the 2011 WHO regimen for MDR-TB with therapy success rates for each study above 50%. The most effective regimen according to studies in this review is kanamycin-high dose isoniazid-clofazimine-ethambutol-prothionamide-pyrazinamide-gatifloxacin (KM-INH-CFZ-EMB-PTH-PZA-GFX) in the intensive phase for 4 months and clofazimine-ethambutol-pyrazinamide-gatifloxacin-prothionamide (CFZ-EMB-PZA-GFX-PTH) in the continuation phase for 8 months. The four most reported side effects were gastrointestinal problems, ototoxicity, dysglycemia, and liver problems. In conclusion, STR provides good effectiveness in MDR-TB treatment, in terms of treatment success rate and short therapy duration. Therapy with STR is relatively safe, with minimal side effects that can be tolerated in the majority of individuals.
Lung Mechanics: An Inverse Modeling Approach

Preface Notation 1. Introduction 2. Collecting data 3. The linear single-compartment model 4. Resistance and elastance 5. Nonlinear single-compartment models 6. Flow limitation 7. Linear two-compartment models 8. The general linear model 9. Inverse models of lung impedance 10. Constant phase model of impedance 11. Nonlinear dynamic models 12. Epilogue References Index.
Localization of Certain Cephalometric Landmarks Using HOG and KNN

---------------------------------------------------------------------------------------------------------------------------------------ABSTRACT : Cephalometric tracing is a standard technique used by orthodontistsfor analysis and treatment planning. Important landmarks in cephalometric X-ray images are marked by experts. Measurements based on these landmark locations are used for diagnosis.Performing this process manually is tedious and hence error-prone even for experts. Therefore, fully automatic landmark localization (FALL) software has been developed. The aim of this study to help reduce the search area for landmarks to be detected by FALL software to speed up the process of localization. This study focuses on the Prn landmark detection. The potion of the image that is sure to contain the Prn landmark is divided into 16x16 pixels size windows. For each window, its histogram of oriented gradient is computed. These histograms are compared to the histograms created manually before that form the positive and negative dataset of histograms for Prn. K-nearest neighbors (KNN) algorithm is utilized for classification of the window whether it contains Prn or not. Search results are promising in that no true positives are missed and the number of false positives are minimized. The window that contains the Prn landmark is found with 100 % accuracy. A computationally more demanding algorithm could then be used to pinpoint the landmark.
HYBRID GRAY WOLF AND PARTICLE SWARM OPTIMIZATION FOR FEATURE SELECTION

The big data comprises a relatively developing area of study which is due to numerous facts gathered daily and the wishes to be helpful information for use in our day by day life. One of the most crucial pre-processing of data is the feature selection. This paper proposes a hybrid technique that combines two algorithms namely Gray Wolf Optimization (GWO) and Particle Swarm Optimization (PSO), the manner that lets in the critical functions to be recognized and lets the insigniﬁcant ones and the complexity to be erased. This enables the obligations of the gadget learning classiﬁcation while making use of training to the classiﬁer with the data set. A hybrid approach is primarily based on metaheuristics swarm intelligence algorithms, which simulate the gray wolf’s management and hunting manner in nature and PSO which people are moving impacted by their local best positions and by the global best position. This hybridization is to acquire the balance between exploitation and exploration. We used seventeen datasets from UCI machine gaining knowledge of repository within the experiments and comparisons results to assess the eﬀectiveness and quality of the GWOPSO.
ULTRASOUND TISSUE CHARACTERIZATION

ongoing to validate any predictive capabilities this technology may have and to develop optimal evaluation programs. Preliminary research has shown that while an acute increase in Type II echoes may be reversible within four days, an increase in echo Type III and IV may not be reversible within that time frame and may take 4-12 weeks, if reversal happens at all. Image courtesy of Hans van Schie.
SUBJECTIVE WELL-BEING IN ADOLESCENTS AND EMERGING ADULTS: PERSONALITY, VALUES AND SOCIAL RELATIONSHIPS

Investigating the sources of happiness dates back to the ancient times and has an important share in today's mental health research. Subjective well-being is included in the scientific definitions of happiness. Although there are many studies on subjective well-being, studies examining this concept in a developmental context are still limited. This study aims to examine the role of personality, values, and social relationships in explaining subjective well-being in adolescents and emerging adults. Research data related to the independent variables of the research was gathered by Five Factor Personality Inventory, Portrait Values Questionnaire, Network of Relationships Inventory Short Form; data on dependent variables were collected using the Satisfaction with Life Scale and the Positive-Negative Affect Scale. The sampling method of the study is convenient sampling and data was collected from a total of 716 participants, consisting of adolescents (n=372) and emerging adults (n=344). After testing the data for normal distribution and exploring no multicollinearity between variables, the main analyses were run. Pearson Product-Moment Correlation Coefficient and Hierarchical Multiple Regression Analysis were performed. Gender was assigned as the control variable in this study. Findings showed that neuroticism in both adolescents and emerging adults, conservatism in adolescents, self-enhancement in emerging adults, and positive relationship with mothers both in adolescents and emerging adults contributed to subjective well-being. In this study, social relations were limited to mothers and the closest relations. The inclusion of relationships with different people in the social networks in future studies is important for a better understanding of the social determinants of subjective well-being.
Artificial intelligence based Fake Job Recruitment Detection Using Machine Learning Approach

— To avoid fraudulent post for job in the internet, an automated tool using machine learning based classification techniques is proposed in the paper. Different classifiers are used for checking fraudulent post in the web and the results of those classifiers are compared for identifying the best employment scam detection model. It helps in detecting fake job posts from an enormous number of posts. Two major types of classifiers, such as single classifier and ensemble classifiers are considered for fraudulent job posts detection. However, experimental results indicate that ensemble classifiers are the best classification to detect scams over the single classifiers.
Large eddy simulation of primary liquid-sheet breakup

This research project aims at providing the aeronautical industry with a modelling capability to simulate the fuel injection in gas turbine combustion chambers. The path to this objective started with the review of state-of-the-art numerical techniques to model the primary breakup of liquid fuel into droplets. Based on this and keeping in mind the requirements of the industry, our modelling strategy led to the generation of a mass-conservative method for efficient atomisation modelling on unstructured meshes. This goal has been reached with the creation of high-order numerical schemes for unstructured grids, the development of an efficient numerical method that transports the liquid-vapour interface accurately while conserving mass and the implementation of an algorithm that outputs the droplet boundary conditions to separate combustion codes. Both high-order linear and WENO schemes have been created for general polyhedral meshes. The notorious complexity of high-order schemes on 3D mixed-element meshes has been handled by the creation of a series of algorithms. These include the tetrahedralisation of the mesh, which allows generality of the approach while remaining efficient and affordable, together with a novel approach to stencil generation and a faster interpolation of the solution. The performance of the scheme has been demonstrated on typical two-dimensional and three-dimensional test cases for both linear and non-linear hyperbolic partial differential equations. The conservative level set method has been extended to unstructured meshes and its performance has been improved in terms of robustness and accuracy. This was
Question-Led Semantic Structure Enhanced Attentions for VQA

The exploit of the semantic structure in the 001 visual question answering (VQA) task is a 002 trending topic where researchers are interested 003 in leveraging internal semantics and bringing 004 in external knowledge to tackle more com-005 plex questions. The prevailing approaches 006 either encode the external knowledge sepa-007 rately from the local context, which magnif-008 icently increases the complexity of the ensem-009 ble system, or use graph neural networks to 010 model the semantic structure in the context, 011 which suffers from the limited reasoning ca-012 pability due to the relatively shallow network. 013 In this work, we propose a question-led struc-014 ture extraction scheme using external knowl-015 edge and explore multiple training methods, in-016 cluding direct attention supervision, SGHMC-017 EM Bayesian multitask learning, and masking 018 strategies, to aggregate the structural knowl-019 edge into deep models without changing the ar-020 chitectures. We conduct extensive experiments 021 on two domain-specific but challenging sub-022 tasks of VrR-VG dataset and demonstrate that 023 our proposed methods achieve significant im-024 provements over strong baselines, showing the 025 promising potentials of applicability. 026
The Effect of Parental Socio-Economic Condition on the Students’ Learning Achievement at Higher Secondary Level of Education in Jamalpur District

: This investigation is conduct to know the relationship between parental socio- economic condition and students learning achievement at higher secondary school certificate examination. To find out the nature of the reality, survey research design was used for this study. The study was conducted at five (05) college of Jamalpur district. The respondent of the study consisted of One hundred twenty (120) student who were purposively selected from the study area. Data were collected through interview schedule & shown statistical table and analyzed. The study reveals that parental education, occupation, income and social status effect the learning achievement.
Polarization Insights for Active Galactic Nuclei

Optical spectropolarimetry and broadband polarimetry in other wavebands has been a key to understanding many diverse aspects of AGN. In some cases polarization is due to synchrotron radiation, and in other cases it's due to scattering. Recognition of relativistically beamed optical synchrotron emission by polarization was vital for understanding blazars (BL Lacs and Optically Violently Variable quasars), both physically and geometrically. Radio polarimetry of quiescent AGN is equally important, again for both purposes. Scattering polarization was central to the Unified Model for Seyferts, Radio Galaxies and (high ionization) Ultraluminous Infrared Galaxies. It provides a periscope for viewing AGN from other directions. Finally, if we could understand its message, polarization would also provide major insights regarding the nature of the AGN "Featureless Continuum" and Broad (emission) Line Region. I point out that high ionization ULIRGs have all the exact right properties to be called Quasar 2s. Mid-IR observations generally don't penetrate to the nucleus, greatly reducing their ability to diagnose the energy source. In particular, LINER ULIRGs aren't necessarily starburst-dominated, as has been claimed.
Electronic transport studies of single-crystalline In2O3 nanowires

Single-crystalline In2O3 nanowires were synthesized and then utilized to construct field-effect transistors consisting of individual nanowires. These nanowire transistors exhibited nice n-type semiconductor characteristics with well-defined linear and saturation regimes, and on/off ratios as high as 104 were observed at room temperature. The temperature dependence of the conductance revealed thermal emission as the dominating transport mechanism. Oxygen molecules adsorbed on the nanowire surface were found to have profound effects, as manifested by a substantial improvement of the device performance in high vacuum. Our work paved the way for In2O3 nanowires to be used as nanoelectronic building blocks and nanosensors.
Cross-Border E-commerce Application Ability and Foreign Trade Enterprise Performance

: With the help of communication technology, China ’s developed cross-border retail e-commerce B2C and B2B have broken through trade barriers and shortened the distance between buyers and sellers ,whose Online transactions have been implemented in different countries or regions of the world. China's foreign trade transformation and upgrading and stable foreign trade growth have an increasingly important strategic position. The main objective of this study was to explore Yiwu Qiaohuo Tianxia E-commerce Co., Ltd who specializes in Alibaba’s domestic and international wholesale business. A survey questionnaire was used for data collection which was applied to draw the 24 research participants from several demographic, which includes Yiwu Qiaohuo Tianxia E-commerce Co., Ltd., that were categorized into four, namely regular, quantitative method and deductive approach was used in the process to assess the validity of findings that results to a qualitative research and to understand the correlation of the quantitative findings based from the survey. With the proposed framework, the acceptability of the visualized used of Questionnaire could result to a highly sustainable China's foreign trade e-commerce B2B and B2C online and offline transactions in the country that can gratify and promote China's foreign trade e-commerce new growth in China's foreign trade e-commerce.
A far-ultraviolet variability survey of the globular cluster M 80: A far-ultraviolet variability survey of M 80

We have searched for variable sources in the core region of M 80, using far-ultraviolet (FUV) data taken with the Advanced Camera for Surveys on board the Hubble Space Telescope. We found three sources that exhibit strong signs of variability in our data. Among these is source TDK 1, which we believe to be an RR Lyrae star that reached maximum brightness during our observations. The light curve shows a ≥3 mag FUV brightening over the course of ≈5 h, with an estimated peak brightness of ≈16.7 mag, followed by a decrease to ≈20 mag. Archival optical data obtained with Wide-Field Planetary Camera 2 confirm that TDK 1 is variable in all wavebands. TDK 1's spectral energy distribution is reasonably fitted by a star with temperature T eff ≃ 6700 K and radius R ≃ 4.2 R ⊙ , consistent with the suggestion that it is an RR Lyrae. Based on the photometric and variability characteristics of the other two variables, we suggest that TDK 2 is likely to be an SX Phoenicis star with ≃55 min period, and TDK 3 is likely another RR Lyrae. Finally, we briefly discuss the FUV counterparts to two previously known variables in M 80, the classical nova T Sco and the dwarf nova DN 1.
Elastic Registration of Medical Images Using Generic Dynamic Deformation Models

Modern imaging techniques are increasingly used in healthcare and medical research. Fusion of information obtained from images of the same or different modalities and/or dimensionalities can greatly help physicians in diagnosis and treatment of diseases. To this end, the images must be spatially aligned through a procedure often referred to as “image registration”. Since soft tissue organs in the human body can undergo significant deformation between imaging sessions or during an intervention, registration techniques that would account for such non-rigid geometrical transformations are of great interest. This thesis presents a family of automatic elastic registration methods applicable to single and multimodal images of similar or dissimilar dimensions. These registration algorithms employ a generic dynamic linear elastic continuum mechanics model of the tissue deformation which is discretized using the finite element method. The dynamic deformation model provides spatial and temporal correlation between images acquired from different orientations at different times. First, a volumetric registration algorithm is presented which estimates the deformation field by balancing internal deformation forces of the elastic model against external forces derived from an intensity-based similarity/distance measure between images. The registration is achieved by iteratively solving a reduced form of the dynamic deformation equations in response to image-derived nodal forces. A general approach for automatic deformable image registration is also presented in this thesis which deals with different registration problems within a unified framework irrespective of the image modality and dimension. Using the dynamic deformation model, the problem of deformable image registration is approached as a classical state estimation problem with various image similarity/distance measures providing an observation model. With this formulation, single and multiple-modality, three-dimensional (3D)-3D and 3D2D image registration problems can all be treated within the same framework. The registration is achieved through a Kalman-like filtering process which incorporates information from the deformation model and an observation error computed from an intensity-based similarity/distance measure. Correlation ratio, normalized correlation coefficient, mutual information, modality independent neighborhood descriptor and sum of squared differences
The Hamiltonian path integrand for the charged particle in a constant magnetic field as white noise distribution

The concepts of Hamiltonian Feynman integrals in white noise analysis are used to realize as the first velocity-dependent potential of the Hamiltonian Feynman integrand for a charged particle in a constant magnetic field in coordinate space as a Hida distribution. For this purpose the velocity-dependent potential gives rise to a generalized Gauss kernel. Besides the propagators, the generating functionals are obtained.
Dark matter, dark energy, and dark radiation coupled with a transversal interaction

We investigate a cosmological scenario with three interacting components that includes dark matter, dark energy, and radiation in the spatially flat Friedmann-Robertson-Walker universe. We introduce a 3-dimensional internal space, the interaction vector $\mathbf{Q}=(Q_{x}, Q_{m}, Q_{r})$ satisfying the constraint plane $Q_{x}+ Q_{m}+ Q_{r}=0$, the barotropic index vector $ \boldmath ${\gamma}$=(\ga_x,\ga_m,\ga_r)$ and select a transversal interaction vector $\mathbf{Q_t}$ in a sense that $\mathbf{Q_t}\cdot \boldmath ${\gamma}$=0$. We exactly solve the source equation for a linear $\mathbf{Q_t}$, that depends on the total energy density and its derivatives up to third order, and find all the component energy densities. We obtain a large set of interactions for which the source equation admits a power law solution and show its asymptotic stability by constructing the Lyapunov function. We apply the $\chi^{2}$ method to the observational Hubble data for constraining the cosmic parameters, and analyze the amount of dark energy in the radiation era for the above linear $\mathbf{Q_t}$. It turns to be that our model fulfills the severe bound of $\Omega_{x}(z\simeq 1100)<0.1$ and is consistent with the future constraints achievable by Planck and CMBPol experiments.
The fractal spatial distribution of stars in open clusters and stellar associations

The Interstellar Medium has a fractal structure, in the sense that gas and dust distribute in a hierarchical and self-similar manner. Stars in new-born cluster probably follow the same fractal patterns of their parent molecular clouds. Moreover, it seems that older clusters tend to distribute their stars with radial density profiles. Thus, it is expected that clusters form with an initial fractal distribution of stars that eventually evolves toward centrally concentrated distributions. Is this really the case? This simple picture on to the origin and early evolution of star clusters and associations is very far from being clearly understood. There can be both young clusters exhibiting radial patterns and evolved clusters showing fractal structure. Additionally, the fractal structure of some open clusters is very different from that of the Interstellar Medium in the Milky Way. Here we summarize and discuss observational and numerical evidences concerning this subject.