Miracle-dz/UniFAR-FTUs huggingface dataset:
Microfluidic synthesis of multi-layer nanoparticles for drug and gene delivery

Multiple layer nanoparticles offers a likelihood of success in drug delivery, as it provides a solution for a more controllable drug release, as with such structures, control over the capsule wall thickness, permeability, stability, and degradation characteristics can be achieved (Kumar, 2008). Using PDMS microfluidic devices to synthesize polymeric multilayer microparticles has become popular recently. The generation of complex emulsions, such as double and triple emulsions, is also achievable with such devices (Roney et al., 2005). However, limitations with these devices are: the microchannel surface property is crucial to maintain the desired flow within the microdevice; droplets which form within the microchannels require a cross-linking agent to be solidified into particles; the size of the droplets is limited to the size of microchannels, usually around 50-100 mm, which is too large to be used for drug delivery; and the amount of droplets or particles produced is limited as the droplets/particles are formed one by one. Therefore, in this study, we present a novel technique on fast multilayer polymeric nanoparticles synthesis via surface acoustic wave (SAW) atomization using a microfluidic device. We are able to show (1) successful synthesis of multilayer polymeric structure, and (2) fast generation of monodispersed particles in nanosize. Compared to conventional methods, SAW atomization is fast and have less limitations in the usage of surfactant and templates. Compared to traditional ultrasonic atomization and electrospraying, SAW atomization driven at much higher frequency is more suitable for shear and heat sensitive drug delivery.
Phenotypic Analysis of Antigen-Specific T Lymphocytes

Identification and characterization of antigen-specific T lymphocytes during the course of an immune response is tedious and indirect. To address this problem, the peptide-major histocompatability complex (MHC) ligand for a given population of T cells was multimerized to make soluble peptide-MHC tetramers. Tetramers of human lymphocyte antigen A2 that were complexed with two different human immunodeficiency virus (HIV)-derived peptides or with a peptide derived from influenza A matrix protein bound to peptide-specific cytotoxic T cells in vitro and to T cells from the blood of HIV-infected individuals. In general, tetramer binding correlated well with cytotoxicity assays. This approach should be useful in the analysis of T cells specific for infectious agents, tumors, and autoantigens.
Pacific Coast Iris species delimitation using three species definitions: biological, phylogenetic and genealogical

Morphological characters are used to discriminate the five Oregon species of the Pacific Coast irises (Iris series Californicae). In nearly every case, fixed differences were found between species, revealing that they are good phylogenetic species. However, when the biological species concept is applied, the whole series is found to be one biological species. Sequence data were generated from the chloroplast DNA region between the atpbeta and rbcL genes. For this 700 bp region, the maximum divergence observed in the series was one percent. These sequences, together with three restriction site characters, were used to produce a cladogram for multiple individuals of all species in the group. On the resulting consensus cladogram, the different individuals from each species do not cluster together. This could result from either introgressive hybridization or the retention of ancestral polymorphism. When the genealogical species concept is applied, only one species can be identified: the whole Series Californicae. There are therefore two natural levels at which taxa can be defined. It is recommended that the phylogenetic species be used as the taxonomic species in this group.Copyright 1998 The Linnean Society of London
How Do B2B Patterns Shape IOS Application Capabilities - The Moderating Effect on IT Capability Building

In recent years, a growing number of B2B e-businesses are adopting inter-organizational information systems (IOS). IOS enable and facilitate sharing of IT resources and capabilities between two or more organizations. Scholars also agree that information technology (IT) recourses and capabilities are critical for delivering business value of IT. Although, extant literature has mainly focused on the relationship between IT capabilities and firm performance, we believe that it is also crucial to understand the IT capability building processes and examine/explore mechanisms to build IT capabilities from existing IT resources. In this study, IOS application capabilities are proposed as the main factor in creating business value of IT in B2B environment. Moreover, we try to understand the nature of B2B patterns in cooperative relationship, which are likely to moderate the IT capability building process from IOS resources to IOS application capabilities. Research framework and hypotheses are proposed drawing from organizational learning theory and relevant literature. Our work aims to provide insights on how firms build IOS capabilities in cooperative inter-organizational relationships through strategic alignment between IOS resources and B2B patterns.
The developmental level of the international student‘s psychological culture as a key point of succesful learning of the foreign language

This article discusses the impact of international student’s psychological culture on his/her learning abilities of foreign languages and incorporation into his/her multicultural learning environment. This article describes the behavior and features of the psychological culture of Turkish students. It is also shown that the psychological (internal) culture interacts with the external culture. The external culture is defined as the national that has a great impact on the attitudes, thoughts and beliefs of the international student. The Hofstede’s model enabled to describe the dimensions of Turkish culture and its connection with the learning process of the international student. The thorough analysis of behavior of international students at the language lessons gives a feedback for the teachers by planning the lesson in the multicultural group.The paper gives recommendations for teachers who are teaching Turkish students in the foreign language or are working with the international students of the multicultural group.
Empirical examination of the Greek non-government bond market

The introduction of the euro has forced the development of new products and greater investor demand for instruments with higher return/risk profiles and greater mathematical and computational complication such as credit derivatives, asset backed securities and inflation linked bonds. In Greece the bank debt securities have been the dominant force in the non-government bond market, due to the reshaping of regulatory framework under the ongoing Basel II process and the consolidation of European capital markets after the initiation of monetary union. This paper offers an empirical examination of the development of this market using macroeconomic factors such as interest rates and GDP. Furthermore, this research builds upon the existing studies by looking into the underlying factors that explain the price differential in the non-government bond market and which have implications for the mathematical modeling of individual bonds. I) Introduction After the introduction of euro many categories of investors that prefer assets denominated in the local currency where able to increase the diversification of their investment within the euro area. This case study focuses on the Greek market but for comparative purposes we include findings from the American and the European bond markets too. The government bond market still retains the leading position in the Eurobond market mainly due to the creditworthiness of the borrowers, the high liquidity of the issues and the well-developed derivatives market.
Globally Optimal Interactive Boundary Extraction Using Markov Chain Modeling

We present a novel boundary-based (discontinuity tracking) hierarchical statistical criterion to address the interactive contour extraction problem. Our criterion relies on a Markov Chain representation of the boundary and can be efficiently optimized using Dijkstra’s algorithm for solving the shortest paths problem. Unlike other criteria optimized with Dijkstra’s algorithm, ours is capable of extracting geometrically complex boundaries even when the features incorporated in the objective function are based only on user markings on a small part of the image. The critical quantity in our criterion that yields the above-mentioned results is a normalization factor that boosts the probability of a particular boundary segment based on the candidate boundary segments in its vicinity. Although similar in spirit to the technique of non-maximum suppression routinely employed in edge detection, our method boosts gradually the probability of a particular segment given its surroundings using windows of increasing size in a hierarchical fashion.
An Efficient Adaptive Scheduling Scheme for Distributed Memory Multicomputers

Traditional multiprocessor scheduling schemes have been one of either space-sharing or time-sharing. Space-sharing schemes perform better than time-sharing at low to moderate system loads. However, they have a disadvantage of wasting processing power within partitions at medium to high system loads. Time sharing schemes tend to perform better at medium to high system loads. Almost all the scheduling schemes proposed so far have been tested under ad hoc workload considerations. In light of recent knowledge about workloads, it is imperative to develop an integrated scheduling scheme that combines the advantages of space- and time-sharing while overcoming their individual drawbacks. We propose such a scheduling scheme, called Hierarchical Scheduling Policy, which is efficient as well as general enough to accommodate multiple workloads. Simulation results indicate that our scheme significantly outperforms the best space- and time-sharing mechanisms at medium to high system loads even in the absence knowledge regarding individual job characteristics.
Att forska är ett äventyr - men se upp för alla fallgropar

Jag tänker mig att du som läser detta står i begynnelsen av dina forskarstudier. Du har ett stort och mycket krävande arbete framför dig. Vad är det då som krävs? Vi som på olika lärosäten och institutioner runt om i landet arbetar med rekrytering och antagning till forskarutbildning fäster naturligtvis stor vikt vid vilka förkunskaper doktorandkandidaterna skaffat sig, och i vad mån de förefaller ha begåvning för ämnet. Dessa egenskaper i all ära får vi dock inte glömma en annan mycket viktig faktor, nämligen inställningen till forskarstudierna.
Performance analysis of cooperative cognitive radio networks with imperfect sensing

In this paper the performance of the secondary users (SUs) in an overlay cooperative cognitive radio network (CRN) with imperfect sensing is analyzed. Providing reliable communication for the SUs in CRNs requires elaborate considerations in various functionalities of the network. Here, a practical structure for the network is considered in which the cooperation among the SUs is taken into account to improve the reliability of the secondary data transmission on wireless fading channels. Furthermore, an efficient spectrum scheduling scheme is proposed which can effectively manage the data transmission for the SUs. A queueing framework is proposed to analyze the performance of the SUs in the network. Furthermore, the effects of spectrum sensing errors on the performance of the SUs are studied. The analytical results are also verified by simulations.
The research on the knowledge representation model of XBRL

XBRL (extensible business reporting language) is a language to describe the structured data of business report, especially of finance report. This essay, which is about XBRL, introduces the basic knowledge and principles of XBRL. Then the specifications and models are analyzed, including XBRL 2.1, Dimensions 1.0 and Formula 1.0. According to the work above, the paper indicates the weakness of these models in knowledge presentation, and proposes a way to solve them.
Image Spam Filtering using Support Vector Machine and Particle Swarm Optimization

Spam is most often considered to be electronic junk mail. Spam is defined as unsolicited bulk mail. Image spam is a kind of email spam where the spam text is embedded with an image. Spam email has become difficult in the survival of internet users, causing personal injury and economic losses. In this paper, we propose a feature extraction scheme which focuses on low-level features, like metadata and visual features of images. This technique makes classification better and it is an effective method because it does not depend on extracting text and examining the content of email. A SVM classifier with kernel function is used to identify an image spam and also the accuracy will be calculated. General Terms Spam image, Ham image, Support Vector Machine, Particle Swarm Optimization
Univariate and Bivariate Information Storage

The channel capacity for multidimensional absolute judgment is known to be higher than the channel capacity for unidimensional judgment, though it falls short of the sum of the respective channel capacities for individual dimensions (Miller, 1956; Slak, 1969). The question arises whether a similar relationship holds for short-term information storage capacity. To answer this question, it is necessary to devise items that can be varied in one or more than one dimension. At least two sets of univariate items are needed, each set variable in one of the two dimensions; and one set of bivariate items, independently variable in both dimensions. The purpose of this study was to compare the univariate and bivariate information storage, as measured by memory span for figural stimuli expressed in bits of information.
Fighting Marketization

As public-service unions and workers struggle against privatization, they must emphasize that their labor is distinctive because it produces use-values composed of concrete, unquantifiable labor. Use-value production responds to social needs and permits the development of a “public service ethos. ” Market mechanisms are continually eroding public-service labor and welfare services in an effort to reduce their value to that of a commodity. Case study evidence presented here shows that such marketization causes job loss, casualization, intensification, and loss of worker morale. Workers and unions have fought hard to overcome the worst effects of contracting out by cooperating with other unions, with sympathetic managers, and with the local community. To keep their service from deteriorating, they can argue that municipal labor is distinctive. The article relates the findings and arguments to municipal manual labor in the United States.
CS 224 N Final Project cRhyme : A Computer Engine for Generating Rhyming Sentences

We introduce cRhyme, a computer system that transforms pairs of sentences to make them rhyme. cRhyme takes in a pair of sentences and performs a series of syntactic transformations to one or both sentences in order to make them rhyme without altering the meaning of either. This makes cRhyme the to-go tool for amateur poets and songwriters who know what to say but have trouble expressing it in a poetic form.
Private Computation with Genomic Data for Genome-Wide Association and Linkage Studies

Genome-wide association studies (GWAS) are currently the most powerful tool for assessing associations between common single-nucleotide polymorphisms (SNPs) and common genetic diseases such as auto-immune disease, heart disease, diabetes, and others. Because genomic data is very sensitive due to the possibility of revealing information not only about the data owner but also about his or her relatives, protection of genomic data is highly recommended. In this work, we put forward a secure realization of a suite of statistical tests used in both genome-wide association and linkage studies. The optimizations are tailored toward the secret sharing setting which is suitable for both secure multi-party computation as well as secure computation outsourcing to multiple servers. The goal is to aid adoption of secure computation techniques for the purposes of genome analysis by covering the chain of statistical tests used in both GWAS and GWLS. We implement the developed protocols and demonstrate their efficiency.
Run-time parameterizable cores

As FPGAs have increased in density, the demand for predefined intellectual property has risen. Rather than re-invent commonly used circuitry, libraries of standard parts have become available from a variety of sources. Currently, all of these offerings are based on the standard ASIC design flow and are used to produce fixed designs. This paper discusses Run-Time Parameterizable or RTP Cores which are an extension of the traditional static core model. Written in the Java (tm) programming language, RTP Cores are created at run-time and may be used to dynamically modify existing circuitry. In addition to providing support for run-time reconfigurable computing, RTP Cores permit run-time parameterization of designs. This adds flexibility and portablilty unavailable in existing design environments.
Application of Single-Stage Boost Inverter for Electric Vehicles

This paper proposes a structure of electric vehicle (EV) closed-loop system fed by the single-stage boost inverter (SSBI). The SSBI uses only one-stage conversion circuit to boost the dc- link voltage by regulating shoot-through zero state, which overcomes conventional voltage source inverters' drawbacks. In order to illustrate the EV closed-loop system, fully analysis of the SSBI has been carried out. Also, the operation principle of the dc-link voltage control and the field-oriented motor control has been presented in detail. The performance of the proposed system is valid by MATLAB/SIMULINK simulation using a 1kW induction motor. The simulation results verify the effectiveness of the proposed EV closed-loop system.
Exposing the third chromosome of Burkholderia cepacia complex strains as a virulence plasmid

The Burkholderia cepacia complex (Bcc) consists of 17 closely related species of opportunistic bacterial pathogens, which are particularly problematic for cystic fibrosis patients and immunocompromised individuals. Bcc genomes consist of multiple replicons, and each strain sequenced to date has three chromosomes. In addition to genes thought to be essential for survival, each chromosome carries at least one rRNA operon. We isolated three mutants during a transposon mutagenesis screen that were non‐pathogenic in a Caenorhabditis elegans infection model. It was demonstrated that these mutants had lost chromosome 3 (c3), and that the observed attenuation of virulence was a consequence of this. We constructed a c3 mini‐replicon and used it to cure c3 from strains of several Bcc species by plasmid incompatibility, resulting in nine c3‐null strains covering seven Bcc species. Phenotypic characterization of c3‐null mutants revealed that they were attenuated in virulence in multiple infection hosts (rat, zebrafish, C. elegans, Galleria mellonella and Drosophila melanogaster), that they exhibited greatly diminished antifungal activity, and that c3 was required for d‐xylose, fatty acid and pyrimidine utilization, as well as for exopolysaccharide production and proteolytic activity in some strains. In conclusion, we show that c3 is not an essential chromosomal element, rather a large plasmid that encodes virulence, secondary metabolism and other accessory functions in Bcc bacteria.
Stratégie de déploiement d'outils de pilotage de chaines logistiques : Apport de la classification

Ce travail porte sur les apports de la classification dans le cadre du deploiement des chaines logistiques dans un groupe industriel. Le modele SCOR-model est une base de reference de processus standard qui a ete utilisee pour le deploiement du Supply Chain Management. Il a notamment servi de base pour la description des processus et pour la determination des variables quantitatives et qualitatives utilisables dans la classification d'objets autour du theme des chaines logistiques. Sur le cas de Rhodia (multinationale produisant plusieurs dizaines de milliers de produits avec plus d'une centaine de sites sur quatre continents), nous avons applique differentes methodes de classification afin d'accelerer et de faciliter le deploiement du Supply Chain Management. Parmi ces outils, nous avons utilise les arbres de decision pour etablir des classes de produits relativement a leur methode de gestion et la methode des nuees dynamiques pour definir des classes d'entreprises relativement a leurs caracteristiques propres a la gestion de la chaine logistique. Ces classifications ont servi de base au deploiement des logiques de pilotage et de SAP sur l'ensemble des entreprises du groupe. A posteriori, nous pouvons constater le gain de temps qu'elles ont occasionne en permettant d'offrir un eventail de solutions predeterminees, adaptables a chaque entreprise du groupe. Le fait d'avoir reussi un developpement du concept de gestion des chaines logistiques et l'implantation de SAP sur un groupe de cette taille en un temps si court est en soit une validation de l'approche.
Cardiac Output Assessed by Invasive and Minimally Invasive Techniques

Cardiac output (CO) measurement has long been considered essential to the assessment and guidance of therapeutic decisions in critically ill patients and for patients undergoing certain high-risk surgeries. Despite controversies, complications and inherent errors in measurement, pulmonary artery catheter (PAC) continuous and intermittent bolus techniques of CO measurement continue to be the gold standard. Newer techniques provide less invasive alternatives; however, currently available monitors are unable to provide central circulation pressures or true mixed venous saturations. Esophageal Doppler and pulse contour monitors can predict fluid responsiveness and have been shown to decrease postoperative morbidity. Many minimally invasive techniques continue to suffer from decreased accuracy and reliability under periods of hemodynamic instability, and so few have reached the level of interchangeability with the PAC.
Variational multi-phase segmentation using high-dimensional local features

We propose a novel method for multi-phase segmentation of images based on high-dimensional local feature vectors. While the method was developed for the segmentation of extremely noisy crystal images based on localized Fourier transforms, the resulting framework is not tied to specific feature descriptors. For instance, using local spectral histograms as features, it allows for robust texture segmentation. The segmentation itself is based on the multi-phase Mumford-Shah model. Initializing the high-dimensional mean features directly is computationally too demanding and ill-posed in practice. This is resolved by projecting the features onto a low-dimensional space using principle component analysis. The resulting objective functional is minimized using a convexification and the Chambolle-Pock algorithm. Numerical results are presented, illustrating that the algorithm is very competitive in texture segmentation with state-of-the-art performance on the Prague benchmark and provides new possibilities in crystal segmentation, being robust to extreme noise and requiring no prior knowledge of the crystal structure.
Anytime Representation Learning

Evaluation cost during test-time is becoming increasingly important as many real-world applications need fast evaluation (e.g. web search engines, email spam filtering) or use expensive features (e.g. medical diagnosis). We introduce Anytime Feature Representations (AFR), a novel algorithm that explicitly addresses this trade-off in the data representation rather than in the classifier. This enables us to turn conventional classifiers, in particular Support Vector Machines, into test-time cost sensitive anytime classifiers-- combining the advantages of anytime learning and large-margin classification.