Miracle-dz/UniFAR-FTUs huggingface dataset:
Tunable Consistency in MongoDB

Distributed databases oﬀer high availability but can impose high costs on client applications in order to maintain strong consistency at all times. MongoDB is a document oriented database whose replication system provides a variety of consistency levels allowing client applications to select the trade-oﬀs they want to make when it comes to consistency and latency, at a per operation level. In this paper we discuss the tunable consistency models in MongoDB replication and their utility for application developers. We discuss how the MongoDB replication system’s speculative execution model and data rollback protocol help make this spectrum of consistency levels possible. We also present case studies of how these consistency levels are used in real world applications, along with a characterization of their performance beneﬁts and trade-oﬀs.
Consensus of linear multi-agent systems with multilayer network using output feedback controller

CONSENSUS OF LINEAR MULTI-AGENT SYSTEMS WITH MULTILAYER NETWORK USING OUTPUT FEEDBACK CONTROLLER BY HYEMIN LIM DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING COLLEGE OF ENGINEERING SEOUL NATIONAL UNIVERSITY FEBRUARY 2017 Recently, there is a need for consensus of Multi-agent systems (MAS) in various engineering fields such as unmanned vehicles, cluster robot control, and sensor network. This paper is inspired by the disconnected autonomous vehicle and Connected Car. Connected cars not only get information through sensors like ordinary cars, but also receives various information of roads and traffic situation by wireless communication between vehicles or infra to increase safety of unmanned autonomous driving. However, as a common sensors in typical automobiles have limitations in physical situations such as a limitation of a measurement distance, it is common that not all agents can get information even though all the agents have same sensors. If information between vehicles are not obtained, it may cause great danger during autonomous navigation. Therefore, when the sensor can not be measured, information should be exchanged through wireless communication to realize stable unmanned autonomous driving. Therefore, it is necessary to study the control of MAS consensus considering these realistic problem situation.
A case of an extreme white coat effect

Abstract In this report, we present a challenging case of a 63-year-old Caucasian woman with an extreme stress response to blood pressure (BP) measurements. Office- and ambulatory BP measurements consistently found systolic BP above 200 mmHg. However, antihypertensive medication made her dizzy and extremely unwell, and she could barely tolerate treatment with a moderate dose of angiotensin-converting enzyme (ACE) inhibitor. Finger-cuff-based measurements (Finapres Finometer®) revealed extreme hypertension in relation to contact with medical professionals, but hypotension when the patient was seated alone unobserved. Months after, the patient suffered a hemorrhagic stroke possibly related to her extreme BP-fluctuations in stressful situations.
Data Model Verification via Theorem Proving

Author(s): Bocic, Ivan | Advisor(s): Bultan, Tevfik | Abstract: Software applications have moved from desktop computers onto the web. This is not surprising since there are many advantages that web applications provide, such as ubiquitous access and distributed processing power. However, these benefits come at a cost. Web applications are complex distributed systems written in multiple languages. As such, they are prone to errors at any stage of development, and difficult to verify, or even test. Considering that web applications store and manage data for millions (even billions) of users, errors in web applications can have disastrous effects.In this dissertation, we present a method for verifying code that is used to access and modify data in web applications. We focus on applications that use frameworks such as Ruby on Rails, Django or Spring. These frameworks are RESTful, enforce the Model-View-Controller architecture, and use Object Relational Mapping libraries to manipulate data. We developed a formal model for data stores and data store manipulation, including access control. We developed a translation of these models to formulas in First Order Logic (FOL) that allows for verification of data model invariants using off-the-shelf FOL theorem provers. In addition, we developed a method for extracting these models from existing applications implemented in Ruby on Rails. Our results demonstrate that our approach is applicable to real world applications, it is able to discover previously unknown bugs, and it does so within minutes on commonly available hardware.
Radiation as an In Situ Auto-Vaccination: Current Perspectives and Challenges

Radiotherapy is generally considered to be a local treatment, but there have been reports of rare cases demonstrating abscopal effects in which antitumor effects have been observed in cancer lesions other than the irradiated site. This result is more likely to occur when immune checkpoint inhibitors are used in addition to radiotherapy. Certain radiation-induced chemokines and cytokines have immune-enhancing effects. Immune checkpoint inhibitors may strengthen these effects by stimulating antigen-presenting cells and effector cytotoxic T cells. To date, there is no consensus regarding the applicability of the abscopal effect in the clinical setting, including optimal methods for combining immune checkpoint inhibitors and irradiation. In this review, we highlight the evidence for interactions between cancer immunotherapy and radiotherapy and discuss the potential of such interactions for use in designing novel combination therapies.
Gridless Parameter Estimation for One-Bit MIMO Radar With Time-Varying Thresholds

We investigate the one-bit MIMO (1b-MIMO) radar that performs one-bit sampling with a time-varying threshold in the temporal domain and employs compressive sensing in the spatial and Doppler domains. The goals are to significantly reduce the hardware cost, energy consumption, and amount of stored data. The joint angle and Doppler frequency estimations from noisy one-bit data are studied. By showing that the effect of noise on one-bit sampling is equivalent to that of sparse impulsive perturbations, we formulate the one-bit <inline-formula><tex-math notation="LaTeX">$\ell _1$</tex-math></inline-formula>-regularized atomic-norm minimization (1b-ANM-L1) problem to achieve gridless parameter estimation with high accuracy. We also develop an iterative method for solving the 1b-ANM-L1 problem via the alternating direction method of multipliers. The Cram<inline-formula><tex-math notation="LaTeX">$\acute{\text{e}}$</tex-math></inline-formula>r-Rao bound (CRB) of the 1b-MIMO radar is analyzed, and the analytical performance of one-bit sampling with two different threshold strategies is discussed. Numerical experiments are presented to show that the 1b-MIMO radar can achieve high-resolution parameter estimation with a largely reduced amount of data.
Imaging signatures of glioblastoma molecular characteristics: A radiogenomics review

Over the past few decades, the advent and development of genomic assessment methods and computational approaches have raised the hopes for identifying therapeutic targets that may aid in the treatment of glioblastoma. However, the targeted therapies have barely been successful in their effort to cure glioblastoma patients, leaving them with a grim prognosis. Glioblastoma exhibits high heterogeneity, both spatially and temporally. The existence of different genetic subpopulations in glioblastoma allows this tumor to adapt itself to environmental forces. Therefore, patients with glioblastoma respond poorly to the prescribed therapies, as treatments are directed towards the whole tumor and not to the specific genetic subregions. Genomic alterations within the tumor develop distinct radiographic phenotypes. In this regard, MRI plays a key role in characterizing molecular signatures of glioblastoma, based on regional variations and phenotypic presentation of the tumor. Radiogenomics has emerged as a (relatively) new field of research to explore the connections between genetic alterations and imaging features. Radiogenomics offers numerous advantages, including noninvasive and global assessment of the tumor and its response to therapies. In this review, we summarize the potential role of radiogenomic techniques to stratify patients according to their specific tumor characteristics with the goal of designing patient‐specific therapies.
Evaluation of EMG, Force and Joystick as Control Interfaces for Active Upper-Extremity Movement-Assistive Devices

Currently, many different control interfaces for the operation of active movement-assistive device exist but their respective performance capabilities and limitations remain unclear. The goal of this study was to quantitatively evaluate the performance and learning characteristics of EMG-, forceand hand joystick-based interfaces. The human operator abilities were assessed in 8 healthy subjects using a screen-based one-dimensional position-tracking task, where the interface signal was mapped to the velocity of the cursor and the target was moving according to a multi-sine signal with a flat velocity spectrum. The performance of the control interfaces was evaluated in terms of tracking error, human-operator bandwidth, information transmission rate and effort. Results showed significant differences between the control interfaces in all the performance descriptors: the joystick-based interface presented significantly higher tracking error compared to EMG(p<0.001) and force-based (p<0.005) interfaces; the EMG-based control interface showed a significantly higher bandwidth (p<0.001) than the forceand the joystick-based interfaces; the forceand joystick-based interfaces provided significantly higher information transmission rates (p<0.001) than the EMG-based interface; the force-based interface presented significantly lower effort than EMG(p<0.001) and joystick-based (p<0.005) interfaces. None of the evaluated interfaces was superior in all four performance descriptors, but the force-based interface presented more positive results than the EMGand joystick-based interfaces. However, in practice, the performance descriptors should be weighted according to the requirements of the specific application to determine which interface is the most suitable for the control of a particular active upper-extremity movementassistive device.
Text extraction from images in the wild using the Viola-Jones algorithm

Text Localization and extraction is an important issue in modern applications of computer vision. Applications such as reading and translating texts in the wild or from videos are among the many applications that can benefit results of this field. In this work, we adopt the well-known Viola-Jones algorithm to enable text extraction and localization from images in the wild. The Viola-Jones is an efficient, and a fast image-processing algorithm originally used for face detection. Based on some resemblance between text and face detection tasks in the wild, we have modified the viola-jones to detect regions of interest where text may be localized. In the proposed approach, some modification to the HAAR like features and a semi-automatic process of data set generating and manipulation were presented to train the algorithm. A process of sliding windows with different sizes have been used to scan the image for individual letters and letter clusters existence. A post processing step is used in order to combine the detected letters into words and to remove false positives. The novelty of the presented approach is using the strengths of a modified Viola-Jones algorithm to identify many different objects representing different letters and clusters of similar letters and later combine them into words of varying lengths. Impressive results were obtained on the ICDAR contest data sets.
Measuring agility in agile methodologies

Agile software methodologies are among the most rational development patterns in global economic environment on which software development enterprises rely. They help software projects to face the dynamic changing business requirements of the customers. However, there is no standard tool for measuring agility and selecting the particular agile method for a particular project. The purpose of this paper is to review the existing tools for measuring agility in agile methodologies, as well as measuring agility in software development teams. This can help in decision-making processes regarding the adoption of an appropriate agile method for a particular project.
Role of striatal ΔFosB in l-Dopa–induced dyskinesias of parkinsonian nonhuman primates

Significance l-Dopa–induced dyskinesia (LID) is a major complication of dopaminergic therapy in Parkinson’s disease. These involuntary movements have been associated with several molecular changes in the striatum, including increased levels of ΔFosB. However, whether ΔFosB upregulation plays a major role in the development of the primate LID or is an epiphenomenon of chronic l-Dopa treatment remains unknown. Using transgenic expression of ΔFosB in the striatum of parkinsonian primates, we show that elevated levels of ΔFosB lead to LID development in the absence of chronic l-Dopa exposure. The physiological and molecular changes associated with LID are also replicated in this model. These findings suggest that ΔFosB elevation is responsible for LID generation and that repressing its expression can have therapeutic value. Long-term dopamine (DA) replacement therapy in Parkinson’s disease (PD) leads to the development of abnormal involuntary movements known as l-Dopa–induced dyskinesia (LID). The transcription factor ΔFosB that is highly up-regulated in the striatum following chronic l-Dopa exposure may participate in the mechanisms of altered neuronal responses to DA generating LID. To identify intrinsic effects of elevated ΔFosB on l-Dopa responses, we induced transgenic ΔFosB overexpression in the striatum of parkinsonian nonhuman primates kept naïve of l-Dopa treatment. Elevated ΔFosB levels led to consistent appearance of LID since the initial acute l-Dopa tests. In line with this motor response, striatal projection neurons (SPNs) responded to DA with changes in firing frequency that reversed at the peak of the motor response, and these unstable SPN activity changes in response to DA are typically associated with the emergence of LID. Transgenic ΔFosB overexpression also induced up-regulation of other molecular markers of LID. These results support an autonomous role of striatal ΔFosB in the adaptive mechanisms altering motor responses to chronic DA replacement in PD.
Color Sift Descriptors to Categorize Illegal Activities in Images of Onion Domains

espanolEl reconocimiento de objetos es algo innato en el ser humano. Cuando las personas miramos una fotografia, somos capaces de detectar sin esfuerzo elementos como animales, senales, objetos de interes, etc. En el campo de la vision por computador este proceso se lleva a cabo mediante herramientas de Inteligencia Artificial, con el fin de obtener informacion sobre el contenido de una imagen. Esta tarea, aunque ampliamente investigada, aun sigue siendo un campo de estudio activo debido a los grandes retos que conlleva: la deteccion de objetos en distintas condiciones luminosas, con posibles oclusiones, distintos tamanos y perspectivas, etc. Este articulo describe las tareas a completar en el desarrollo de un sistema de reconocimiento de objetos exitoso, y proporciona al lector una serie de directrices practicas sobre como realizarlas. El trabajo viene acompanado de una serie de scripts Python para experimentar con las diferentes tecnicas descritas, pretendiendo servir de apoyo en tareas docentes o de iniciacion a cualquier entusiasta en la materia. EnglishWhen people look at pictures, we are able to effortlessly detect elements like animals, signals, objects of interest, etc. Object recognition is a computer vision technique that, through tools from Artificial Intelligence, aims to carry out such an action with the goal of retrieving information from the content of an image. This task, although widely investigated, is an active research fied due to the challenges that it has to face: the detection of objects in different lighthing conditions, with possible occlusions, different sizes and perspectives, etc. This paper describes the typical actions to be completed in the development of a successful object recognition system, and provides the reader a number of practical guidelines about how to address them. The work is accompanied by a Python script (available at https: // github. com/ jotaraul/ object_ recognition_ in_ python ) to put them into practice using state-of-the-art techniques (from libraries like Pandas or Scikit-learn ), and aims to be a valuable resource for education, or as initiation to any enthusiastic in the topic.
Implementasi Test Driven Development Dalam Pengembangan Aplikasi Berbasis Web

Sebuah perangkat lunak dikatakan siap untuk dipakai apabila sudah melalui tahap pengujian. Pada era pengembangan perangkat lunak dengan metodologi tradisional, pengujian dilakukan dengan cara mencoba satu persatu menu aplikasi ketika aplikasi yang dikembangkan sudah jadi. Cara pengujian tersebut akan membutuhkan waktu yang lama apabila developer mengerjakan proyek perangkat lunak dalam skala besar. Selain itu, cara tersebut juga tidak dapat menguji logika dan method dari suatu kelas. Salah satu metode pengembangan perangkat lunak yang dapat menghemat waktu pengujian, namun fungsionalitasnya tetap terjaga adalah test driven development (TDD). Pada metode TDD, pengembangan perangkat lunak dilakukan dengan membuat test case terlebih dahulu baru kemudian melakukan producing code. Pada penelitian ini, dikembangkan sebuah aplikasi web menggunakan TDD. Aplikasi web yang dikembangkan adalah berupa sistem informasi mengenai ulasan film lokal indonesia atau disebut Indonesia Movie Database (IMDB). Bahasa pemrograman web yang dipakai adalah ruby dengan menggunakan framework rails. Sedangkan alat yang dipakai untuk pengujian adalah Rspec. Hasil implementasi TDD membuktikan bahwa fungsi-fungsi dari aplikasi web yang dibangun dapat berkerja dengan baik. Selain itu kode program yang dihasilkan juga menjadi rapi dan mudah dibaca oleh pengembang lain karena menerapkan refactoring. Pengujian unit test menggunakan Rspec membantu pengembang dalam menangani kesalahan dan memudahkan menambah fitur baru dari aplikasi web.
Efficient Grid-based Clustering Algorithm with Leaping Search and Merge Neighbors Method

The increasing data size makes the research of clustering algorithm still an important topic in data mining. As one of the fastest algorithms, the grid clustering algorithm now still suffers from low precision problem. And the efficiency of the algorithm also needed improvement. In order to cope with these problems, this paper proposes an efficient grid-based clustering algorithm by using leaping search and Merge Neighborhood (LSMN). In the algorithm, the LSMN first divides the data space into a finite number of grids and determines the validity of the grid according to the threshold. Then, leaping search mechanism is used to find valid grids of the grid by retrieving all the odd columns and odd rows. Finally, if the number of valid grids is greater than the invalid grid, the invalid grids are merged together. In the algorithm, the time cost is reduced and the accuracy is improved by leaping search and re-judgment of the invalid grid mechanisms respectively. The experimental results have shown that the proposed algorithm exhibits relatively better performance when compared with some popularly used algorithms.
Modelling and analysis of nonlinear thermoacoustic systems using frequency and time domain methods

Thermoacoustic oscillations may arise in combustion chambers when unsteady heat release and acoustic fluctuations constructively interfere. These oscillations generally lead to undesired consequences, and need to be avoided. Linear stability analysis can be used to investigate the linear stability of a thermoacoustic system, by calculating the frequencies and growth rates of thermoacoustic modes. Adjoint methods can then be used to understand what parameters in the configuration under investigation have to be changed to make it less susceptible to thermoacoustic oscillations. Linear stability is, however, not sufficient in general to ensure safe operability conditions. This is because nonlinear and non-normal effects may trigger finite amplitude oscillations when the system is subject to finite amplitude perturbations. A thorough fully nonlinear investigation of thermoacoustic systems is prohibitively expensive both experimentally and numerically, and one needs to approximate the nonlinear response of the system. In this thesis, low-order nonlinear models for the prediction of the nonlinear behaviour of thermoacoustic systems are developed. These models are based on thermoacoustic networks, in which linear acoustics is combined with a nonlinear heat release model. The acoustic networks considered in this thesis can take into account mean flow and non-trivial acoustic reflection coefficients, and are cast in state-space form to enable analysis both in the frequency and time domains. Starting from linear analysis, the stability of thermoacoustic networks is investigated, and the use of adjoint methods for understanding the role of the system’s parameters on its stability is demonstrated. Then, a fully nonlinear analysis using various state-of-the-art methods is performed, to highlight the strengths and weaknesses of each method. Two novel frameworks that fill some gaps in the available methods are developed: the first, called Flame Double Input Describing Function (FDIDF), is an extension of the Flame Describing Function (FDF). The FDIDF approximates the flame nonlinear response when it is forced simultaneously with two frequencies, whereas the FDF is limited to one frequency. Although more expensive to obtain, the FDIDF contains more nonlinear information than the FDF, and can predict periodic and quasiperiodic oscillations. It is shown how, in some cases, it corrects the prediction of the FDF about the stability of thermoacoustic oscillations. The
Organisational Factors Affecting Employee Job Performance : An Empirical Study

With the unpredictable business environment and intense business competition, the companies are required to reach certain standards by improving their performance to align with such great demands; otherwise, a lot of problems will surface, including running the risk to close down the business. This performance relates to the firm or individual level which sees the human resource becoming the most determining factor to achieve the organizations’ objectives. In fact, an abundance of resources such as infrastructures or physical facilities are made meaningless without the support of qualified human resources that directly disrupt the continuity of the business operations. Within the framework of the professionals, good employee performance mirrors the ability to contribute through their works leading to the behavioural achievement that is in accordance with the goals of the company.