Miracle-dz/UniFAR-FTUs huggingface dataset:
Sulfadoxine–pyrimethamine susceptibilities and analysis of the dihydrofolate reductase and dihydropteroate synthase of Plasmodium falciparum isolates from Côte d'Ivoire

Abstract Over a 2-year study period, three methods [a test of therapeutic efficacy, an in-vitro assay, and sequencing of the parasites' dihydrofolate-reductase (dhfr) and dihydropteroate-synthase (dhps) genes] were used to monitor sulfadoxine–pyrimethamine (SP) resistance in the Plasmodium falciparum strains infecting young children near Abidjan, the largest city in Côte d'Ivoire. Overall, 118 children aged <5 years and infected with P. falciparum were treated with SP. Twenty-one (23.5%) of the 89 children who completed the 14 days of follow-up were categorized as therapeutic failures. When P. falciparum isolates from the 61 children with adequate parasitaemias were investigated in the in-vitro assay, 24 (39.5%) were found to be highly resistant to pyrimethamine, each having a median inhibitory concentration (IC50) of at least 2000 nM. Polymorphism analysis of gene fragments of 118 P. falciparum isolates (one from each child enrolled in the study) revealed that 46 (39%) of the isolates had mutant dhfr and 111 (94%) had mutant dhps. The mutations mainly affected DHFR codon 108 (39% of the isolates) and DHPS codons 436 (65%), 437 (52%) and 613 (27%). Of the 37 DHFR mutant isolates from children who completed follow-up, 21 were from children with therapeutic failure, indicating that mutant DHFR was associated with resistance to pyrimethamine in vivo (kappa=0.61). A mutant dhfr genotype was also found to be strongly associated with resistance to pyrimethamine in vitro (kappa=0.79). There was, however, little evidence of an association between SP efficacy and dhps genotype (kappa=0.04). Resistance to SP appears to be an increasing problem in southern Côte d'Ivoire and one which may now justify a change away from this drug combination as the first- or second-line treatment for P. falciparum malaria in this area.
Novel CMOS-compatible a-Si based oscillator and threshold switch

Resistive switching devices and neuromorphic computing systems, while an attractive solution to minimize compute bottlenecks, suffer from sneak-path problem and area inefficient implementations respectively. This has prompted research in developing beyond-CMOS functional blocks that can serve as a compact single device circuit block (selector and oscillator respectively). In this work, we explore amorphous-Si based metal-semiconductor-metal (MSM) devices to serve this function. CMOS compatible Pt/a-Si/Cu stacks show negative differential resistance (NDR) that enables their operation as oscillatory elements and as non-linear threshold switches. As a first demonstration of oscillations in a-Si, we report frequency tunability from 5 kHz to 80 MHz by modulating the series ballast and by changing the source voltage. The devices show low-voltage (<; 1.2 V), low-power operation (<; 100 μW). As threshold switches, these devices show a resistance change of > 800 between ON and OFF states with a peak current density of > 0.3 MA/cm2 at 1 V. Through an analysis of the change in the snap-back time (persistence) and the peak ON-state current, we evaluate the change in the modes of operation of the device as a threshold switch and as an oscillator.
Terpene production in the peel of sweet orange fruits

Terpenoids constitute the largest and most diverse class of natural products. They are important factors for aroma and flavor, and their synthesis is basically done from two compounds: isopentenyl diphosphate and dimethylallyl diphosphate. Isopentenyl diphosphate is synthesized through two different pathways, one that occurs in the cytoplasm and one in the plastid. With the sequencing of ESTs from citrus, we were able to perform in silico analyses on the pathways that lead to the synthesis of terpenes as well as on the terpene synthases present in sweet orange. Moreover, expression analysis using real-time qPCR was performed to verify the expression pattern of a terpene synthase in plants. The results show that all the pathways for isopentenyl diphosphate are present in citrus and a high expression of terpene synthases seems to have an important role in the constitution of the essential oils of citrus.
Secure Data Retrieval Scheme in Cloud Computing Using Homomorphic Cryptographic Approach

Homomorphic encryption technology can settle a dispute of data privacy security in cloud environment, but there are many problems in the process of access the data which is encrypted by a homomorphic algorithm in the cloud. In this paper, on the premise of attribute encryption, we propose a fully homomorphic encrypt scheme which based on attribute encryption with LSSS matrix. This scheme supports finegrained cum flexible access control along with "QueryResponse" mechanism to enable users to efficiently retrieve desired data from cloud servers. In addition, the scheme should support considerable flexibility to revoke system privileges from users without updating the key client, it reduces the pressure of the client greatly. Finally, security analysis illustrates that the scheme can resist collusion attack. A comparison of the performance from existing CP-ABE scheme, indicates that our scheme reduces the computation cost greatly for users.
Exploring Citation Networks to Study Intertextuality in Classics

Referring constitutes such an essential scholarly activity across disciplines that it has been regarded by [Unsworth 2000] as one of the scholarly primitives. In Classics, in particular, the references to passages of the ancient texts - the so-called canonical citations (or references) - play a prominent role. The potential of these citations, however, has not been fully exploited to date, despite the attention that they have recently received in the field of Digital Humanities. In this paper I discuss two aspects of making such citations computable. Firstly, I illustrate how they can be extracted from text by using Natural Language Processing techniques, especially Named Entity Recognition. Secondly, I discuss the creation of a three-level citation network to formalise the web of relations between texts that canonical references implicitly constitute. As I outline in the conclusive section of this paper, the possible uses of the extracted citation network include the development of search applications and recommender systems for bibliography; the enhancement of digital environments to read primary sources with links to related secondary literature; and the application of these network to the study of intertextuality and text reception.
An efficient rank based Arabic root extractor

A morphologically-rich language such as Arabic requires deep analysis; this is due to its invaluable characteristics which are beneficial for the task of root extraction. This paper investigates employing new techniques to enumerate and rank possible roots for a given word, using linguistic rules as scoring mechanisms. The proposed technique extends the use of roots' dictionary to extract new features in order to develop a more accurate root extractor. The proposed root extractor showed an accuracy of 83.9% with at least 11.8% accuracy difference over other root extractors using a direct evaluation dataset.
Learning Visual Emotion Distributions via Multi-Modal Features Fusion

Current image emotion recognition works mainly classified the images into one dominant emotion category, or regressed the images with average dimension values by assuming that the emotions perceived among different viewers highly accord with each other. However, due to the influence of various personal and situational factors, such as culture background and social interactions, different viewers may react totally different from the emotional perspective to the same image. In this paper, we propose to formulate the image emotion recognition task as a probability distribution learning problem. Motivated by the fact that image emotions can be conveyed through different visual features, such as aesthetics and semantics, we present a novel framework by fusing multi-modal features to tackle this problem. In detail, weighted multi-modal conditional probability neural network (WMMCPNN) is designed as the learning model to associate the visual features with emotion probabilities. By jointly exploring the complementarity and learning the optimal combination coefficients of different modality features, WMMCPNN could effectively utilize the representation ability of each uni-modal feature. We conduct extensive experiments on three publicly available benchmarks and the results demonstrate that the proposed method significantly outperforms the state-of-the-art approaches for emotion distribution prediction.
A Continuos Learning for a Face Recognition System

A system of Multiple Neural Networks has been proposed to solve the face recognition problem. Our idea is that a set of expert networks specialized to recognize specific parts of face are better than a single network. This is because a single network could no longer be able to correctly recognize the subject when some characteristics partially change. For this purpose we assume that each network has a reliability factor defined as the probability that the network is giving the desired output. In case of conflicts between the outputs of the networks the reliability factor can be dynamically re-evaluated on the base of the Bayes Rule. The new reliabilities will be used to establish who is the subject. Moreover the network disagreed with the group and specialized to recognize the changed characteristic of the subject will be retrained and then forced to correctly recognize the subject. Then the system is subjected to continuous learning.
Transforming growth factor beta 1 and gamma interferon provide opposing signals to lipopolysaccharide-activated mouse macrophages

Bacterial lipopolysaccharides (LPS) are potent inducers of macrophage activation, leading to the production of a number of proinflammatory mediators. Although several cytokines that prime macrophages for enhanced LPS-triggered responses have been identified, far less is known regarding the role that cytokines play in down-regulating macrophage responses to LPS. This study was designed to determine the effects of recombinant transforming growth factor beta 1 (rTGF-beta 1) on macrophage activation by LPS. Pretreatment of either mouse peritoneal macrophages or cells of the RAW 264.7 macrophage-like cell line with rTGF-beta 1 inhibited their ability to produce both tumor necrosis factor alpha (TNF-alpha) and nitric oxide (NO) in response to LPS. These inhibitory effects were reversed by increasing the concentration of LPS or by priming cells with optimal concentrations of recombinant gamma interferon (rIFN-gamma). Pretreatment of cells with rTGF-beta 1 had only a modest inhibitory effect on the expression of TNF-alpha mRNA. By contrast, the expression of mRNA for the inducible form of nitric oxide synthase (iNOS), which is responsible for NO production in activated macrophages, was significantly inhibited by rTGF-beta 1 pretreatment. Thus, rTGF-beta 1-dependent suppression of macrophage TNF-alpha biosynthesis was manifest at a posttranscriptional level, whereas the inhibition of NO production correlated with a direct effect on iNOS gene expression. Importantly, both of these suppressive effects of rTGF-beta 1 were reversed by exposing the cells to priming concentrations of rIFN-gamma. As with NO production, immunocytochemical analysis of iNOS expression in LPS-stimulated macrophages revealed that rIFN-gamma and rTGF-beta 1 had antagonistic effects, with the former increasing, and the latter reducing, the number of iNOS-expressing cells induced by LPS. These data suggest that a balance between the priming effects of IFN-gamma and the inhibitory effects of TGF-beta 1 can determine the overall level of macrophage activation induced by LPS.
Transforming voting paradigm — The shift from inline through online to mobile voting

Traditional poll-site voting methods poise multiple administrative and logistical challenges inter alia scalability, cost and miscount. Moreover, there is a noticeable decline in the turnout rate of eligible voters, particularly the youth. This work proposes a novel mobile voting model that uses common-off-the-shelf (COTS) mobile phones, in conjunction with a Near Field Communication (NFC) tag technology and a pragmatic biometric verification scheme. The mobile voting application being proposed in this work is launched by leveraging the auto-coupling capability of NFC, which also serves for storing baseline information about voters. The auto-coupling feature mediates device familiarity requirement, which is a limiting factor for using mobile phones to administer elections satisfying transparency and ease of use. The baseline information stored in the NFC tag provides local biometric reference data that mediate intensive bandwidth consumption, computational requirement, provide for match-on-a-card features and satisfy the constraint that only the eligible voter may vote. This work notes all security requirements for this model and addresses some architecture, design and security issues that will arise if such a choice is made.
Fault-tolerant matrix arithmetic and signal processing on highly concurrent computing structures

Hardware for executing matrix arithmetic and signal processing algorithms at high speeds is in great demand in many real-time and scientific applications. With the advent of VLSI technology, large numbers of processing elements which cooperate with each other at high speed have become economically feasible. Since any functional error in a high-performance system may seriously jeopardize the operation of the system and its data integrity, some level of fault tolerance must be incorporated in order to ensure that the results of long computations are valid. Since the major computational requirements for many important real-time signal processing tasks can be reduced to a common set of basic matrix operations, the development of a unified fault-tolerant scheme for matrix operations can solve the problems of both reliable signal processing and reliable matrix operations. Earlier work proposed a low-cost checksum scheme for fault-tolerant matrix operations on multiple processor systems. However, this scheme can only correct errors in matrix multiplication; it can detect, but not correct, errors in matrix-vector multiplication, LU decomposition, matrix inversion, etc. In order to solve these problems with the checksum scheme, a very general matrix encoding scheme is proposed in this paper to achieve fault-tolerant matrix arithmetic and signal processing with linear arrays, which are believed to hold the most promise in VLSI computing structures for their flexibility, low cost, and applicability to most of the interesting algorithms. This proposed technique is, therefore, a very cost-effective encoding technique to achieve fault-tolerant matrix arithmetic and signal processing on highly concurrent VLSI computing structures.
A Systematic Review Comparing Cognitive-Behavioral Therapy and Contingency Management for Cocaine Dependence

The main objective of this review was to compare the effectiveness of cognitive-behavioral therapy and contingency management for cocaine dependence. Contingency management alone reliably reduced cocaine use during active treatment in all cited trials, whereas the positive effect of cognitive-behavioral therapy emerged after treatment in 3 of 5 trials. Synergistic effects of the combination of contingency management plus cognitive-behavioral therapy are shown in 2 trials, but another 3 trials found no additive effects. Positive, rapid, and enduring effects on cocaine use are reliably seen with contingency management interventions, whereas measurable effects of cognitive-behavioral therapy emerge after treatment and are not as reliable as effects with contingency management.
Hierarchical Soft Error Estimation Tool (HSEET)

Radiation induced soft errors have become an important reliability concern in the sub-nanometer regime. Therefore, it is imperative to devise methods to predict the soft error rates (SER) quickly and accurately in combinational circuits. In this paper, we present a novel technique and a tool to compute the SERs of designs employing hierarchical architectures such as adders and multipliers. The technique uses pre-characterized blocks for current generation and propagation and probability theory to estimate the SER in hierarchical architectures. The analysis results of different hierarchical architectures, based on characterization of basic blocks such as muxes, counters and partial product generators using the new technique, are presented in this paper. The run time for most of the designs were in the order of few minutes and we obtain an average speedup of 14084X times over HSPICE and 12.25X times over a contemporary tool SEAT-LA. We have also demonstrated the scalability of our technique for various hierarchical circuits. Our technique can also be extended to any block based architecture.
Electronic Health Records and the Evolution of Diabetes Care

Adoption of electronic health records (EHRs) has increased dramatically since the 2009 implementation of the Health Information Technology for Economic and Clinical Health (HITECH) Act. The latest data from the Centers for Disease Control and Prevention (CDC) indicate that the majority of U.S. hospitals and nearly half of U.S. health care professionals have implemented an EHR with advanced functionality.1 The goals of the HITECH act were not only to incentivize the adoption of EHRs, but also to increase the quality, safety, and efficiency of health care by promoting the concept of “meaningful use. ”2,3 The stepwise implementation of “meaningful use” is now entering the latter stages with a focus on improving patient outcomes.4
AN UNUSUAL INTIMATE RELATIONSHIP BETWEEN ENDOCRINE CELLS AND OTHER TYPES OF EPITHELIAL CELLS IN THE HUMAN STOMACH

The fine structure of human (1-4) and other mammalian (3, 5-12) gastric endocrine cells ("argyrophile," "argentaffin," "enterochromaffin," "pale," "clear," "endocrine-like") has been described . This report describes an unusual morphological and cytochernical relationship observed between human gastric endocrine cells and other types of gastric epithelial cells . The endocrine cells are frequently "embedded" within other epithelial cells and the apposing plasmalemmae exhibit an exceptionally high ATPase activity as demonstrated by cytochemistry .
Parsing Minimalist Languages with Interpreted Regular Tree Grammars

Minimalist Grammars (MGs) (Stabler, 1997) are a formalisation of Chomsky’s minimalist program (Chomsky, 1995), which currently dominates much of mainstream syntax. MGs are simple and intuitive to work with, and are mildly context sensitive (Michaelis, 1998), putting them in the right general class for human language (Joshi, 1985). 1 Minimalist Grammars are known to be more succinct than their Multiple ContextFree equivalents (Stabler, 2013), to have regular derivation tree languages (Kobele et al., 2007), and to be recognisable in polynomial time (Harkema, 2001) with a bottom-up CKY-like parser. However, the polynomial is large, O(n4k+4) where k is a grammar constant. By approaching minimalist grammars from the perspective of Interpreted Regular Tree Grammars, we show that standard chart-based parsing is substantially computationally cheaper than previously thought at O(n2k+3 · 2k).
The Treasures of Schematising : The effects of schematising in early childhood on the learning processes and outcomes in later mathematical understanding

25 A Treasure Chest 25 Research methods 28 Opening the Treasure Chest of Schematising Activities 29 Young Children’s Graphical Representations 29 Making Maps in Mathematical Education 31 Stimulating Early Mathematical Competence 32 Early Training in Mathematical Education 35 Conclusion 36 References 38 3. Schematising Activities in Early Childhood Education 41 Abstract 41 Background of the Study 41 Theoretical Framework 44 A Short Review 44 The Vygotskian Treasures 45 The Importance of Schematising Activities 48 Schematising, Static or Dynamic? 50 Conclusion 52 Methods 53 Design 53 Research Setting and Participants 53 The Intervention Process 54 Instruments 56 a. The Schematising Test 56 b. Arrow Language 58 Sampling, Data Collection and Analysis 6041 Background of the Study 41 Theoretical Framework 44 A Short Review 44 The Vygotskian Treasures 45 The Importance of Schematising Activities 48 Schematising, Static or Dynamic? 50 Conclusion 52 Methods 53 Design 53 Research Setting and Participants 53 The Intervention Process 54 Instruments 56 a. The Schematising Test 56 b. Arrow Language 58 Sampling, Data Collection and Analysis 60
Algorithms for navigation of swarm of unmanned helicopters and following a dynamic target in a complex environment

Cílem této bakalářské práce bylo nastudovat metodu [2] escape behaviour a využítj i pro sledování pohyblivého cíle rojem MAV. Řídící model použitý v této metodě byl původně navrhnut pro fungování s překážkami ve tvaru koule a tak má být do tohoto algoritmu integrována metoda pro počítání vzdálenosti mezi MAV a libovolnou překážkou. Na závěr má být ověřena tato implementace simulacemi pohybu roje v kancelářském prostředí a prozkoumáno chování roje v úzkých uličkách. Vyvinutý algoritmus má být upraven tak, aby nedocházelo ke kolizím mezi jednotlivými letouny.
Quantitative PCR Assay To MeasureAspergillus fumigatus Burden in a Murine Model of Disseminated Aspergillosis: Demonstration of Efficacy of Caspofungin Acetate

ABSTRACT Caspofungin acetate (MK-0991) is an antifungal antibiotic that inhibits the synthesis of 1,3-β-d-glucan, an essential component of the cell wall of several pathogenic fungi. Caspofungin acetate was recently approved for the treatment of invasive aspergillosis in patients who are refractory to or intolerant of other therapies. The activity of 1,3-β-d-glucan synthesis inhibitors against Aspergillus fumigatus has been evaluated in animal models of pulmonary or disseminated disease by using prolongation of survival or reduction in tissue CFU as assay endpoints. Because these methods suffer from limited sensitivity or poor correlation with fungal growth, we have developed a quantitative PCR-based (qPCR) (TaqMan) assay to monitor disease progression and measure drug efficacy. A. fumigatus added to naı̈ve, uninfected kidneys as either ungerminated conidia or small germlings yielded a linear qPCR response over at least 4 orders of magnitude. In a murine model of disseminated aspergillosis, a burden of A. fumigatus was detected in each of five different organs at 4 days postinfection by the qPCR assay, and the mean fungal load in these organs was 1.2 to 3.5 log10 units greater than mean values determined by CFU measurement. When used to monitor disease progression in infected mice, the qPCR assay detected an increase of nearly 4 log10 conidial equivalents/g of kidney between days 1 and 4 following infection, with a peak fungal burden that coincided with the onset of significant mortality. Traditional CFU methodology detected only a marginal increase in fungal load in the same tissues. In contrast, when mice were infected with Candida albicans, which does not form true mycelia in tissues, quantitation of kidney burden by both qPCR and CFU assays was strongly correlated as the infection progressed. Finally, treatment of mice with induced disseminated aspergillosis with either caspofungin or amphotericin B reduced the A. fumigatus burden in infected kidneys to the limit of detection for the qPCR assay. Because of its much larger dynamic range, the qPCR assay is superior to traditional CFU determination for monitoring the progression of disseminated aspergillosis and evaluating the activity of antifungal antibiotics against A. fumigatus.