Miracle-dz/UniFAR-FTUs huggingface dataset:
Ginger (Zingiber officinale) induces apoptosis in Trichomonas vaginalis in vitro

Background: Trichomoniasis is the most common sexually transmitted protozoan diseases in the worldwide. Metronidazole is the choice drug for trichomoniasis treatment, however, metronidazole resistant Trichomonas vaginalis (T.vaginalis) has been reported. Natural products are the source of most new drugs, and Zingiber officinale (Ginger) is widely used ingredient in the traditional medicine. Objective: The aim of the present study was to determine the effect of different concentrations of the ginger ethanol extract on the growth of T.vaginalis trophozoites in vitro. Materials and Methods: In this experimental study, 970 women who were attend in Kashan health centers were examined for T. vaginalis. Of them, 23 samples were infected with T.vaginalis. Three T. vaginalis isolates were cultured in a TYI-S-33 medium. The effect of ginger ethanol extracts and its toxicity in different concentrations (25, 50, 100, 200, 400, 800 µg/ml) on mouse macrophages were measured in triplicate exam by MTT [3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] assay. The effect of ginger on apoptosis induction was determined by Flow cytometry. Results: The IC50 of ginger and metronidazole were 93.8 and 0.0326 µg/ml, respectively. 12, 24 and 48 hr after adding different concentrations of extract on mouse macrophages, fatality rates in maximum dose (800 µg/ml) were 0.19, 0.26 and 0.31 respectively. Flow cytometry results showed the apoptosis rate following treatment with different concentrations of the extract after 48 hr were 17, 28.5, 42.1, 58.8, 76.3 and 100% respectively, while in the control group was 2.9%. Conclusion: Ginger ethanol extract induces programmed death in T. vaginalis. It is recommended that due to the known teratogenic effect of metronidazole, ginger can be considered as an alternative drug for metronidazole.
On accomplishing context awareness for autonomic network management

Future generation networks are characterized by a high level of complexity and dynamicity due to a relevant level of heterogeneity in terms of nodes and devices as well as provided services. In this context, network operators face the challenge of managing this complexity, while lowering the operational expenses. Context awareness becomes a necessity for the efficient management of resources, dynamic deployment of value added services towards guaranteeing the end to end quality of services. This paper presents a novel framework for the context management of future networks, that is able to collect, transform and reason on context information. Embedded in this framework, mechanisms for the building of knowledge are also introduced, with special focus on autonomic context discovery, monitoring, diagnosis and prediction.
Eye movement synthesis with 1/f pink noise

Eye movements are an essential part of non-verbal behavior. Non-player characters (NPCs), as they occur in many games, communicate with the player through dialogues and non-verbal behavior and can have a strong influence on the player experience or even on gameplay. In this paper we propose a procedural model to synthesize the subtleties of eye motions. More specifically, our model adds microsaccadic jitter and pupil unrest both modeled by 1/f or pink noise to the standard main sequence. In a perceptual two-alternative forced-choice (2AFC) experiment we explore the perceived naturalness of different parameters of pink noise by comparing synthesized motions to rendered motion of recorded eye movements at extreme close shot and close shot distances. Our results show that, on average, data-driven motion is perceived as most natural, followed by parameterized pink noise, with motion lacking microsaccadic jitter being consistently selected as the least natural in appearance.
Design, modelling and control of a hyper-redundant 3-RPS parallel mechanism

In this paper, we describe the development of a hyper-constrained serial robot-assembly, which will lead do a snake-like kinematic. The goal of this robot is to serve as an experimental platform for a medical catheter for human surgery. We have two kinds of platform kinematics, namely the microscopic one, which depends of a three-actuator-solution, which gives us a 3-DOF1 moveability of the microscopic TCP (tool center point). The assembly of those microscopic units in a serial manner finally leads to a snake-like robot kinematic. Using MATLAB, we established a mathematical model for simulation, which can be fully integrated into the control loop for the different actuators. With the help of rapid prototyping(RP), we built up a physical model, which is actually in a testing phase.
Reduction from Cost-Sensitive Ordinal Ranking to Weighted Binary Classification

We present a reduction framework from ordinal ranking to binary classification. The framework consists of three steps: extracting extended examples from the original examples, learning a binary classifier on the extended examples with any binary classification algorithm, and constructing a ranker from the binary classifier. Based on the framework, we show that a weighted 0/1 loss of the binary classifier upper-bounds the mislabeling cost of the ranker, both error-wise and regret-wise. Our framework allows not only the design of good ordinal ranking algorithms based on well-tuned binary classification approaches, but also the derivation of new generalization bounds for ordinal ranking from known bounds for binary classification. In addition, our framework unifies many existing ordinal ranking algorithms, such as perceptron ranking and support vector ordinal regression. When compared empirically on benchmark data sets, some of our newly designed algorithms enjoy advantages in terms of both training speed and generalization performance over existing algorithms. In addition, the newly designed algorithms lead to better cost-sensitive ordinal ranking performance, as well as improved listwise ranking performance.
Lowering the Barrier of Query Language Skills within Mobile and Web User Interface Environments

Many research efforts aim to provide access to database systems (through the World Wide Web). At the human end, few users have database query language skills. Most users of the Web are highly skilled at referring to tabular data. A natural inclination exists among the users for object-by-object traction to find information. Similarly, in another context, users of geographic maps tend to locate objects and path by following an item-wise (a step-wise) approach. We propose a similar approach for web information systems users. The proposed interface introduces simplicity and avoids communication ambiguities. It provides an interface between the user and the SQL query language. We compare the proposed approach with alternative approaches. The study presents an example case for a high level interface for Web information systems users
The BTeV Software Tutorial Suite

The BTeV Collaboration is starting to develop its C++ based offline software suite, an integral part of which is a series of tutorials. These tutorials are targeted at a diverse audience, including new graduate students, experienced physicists with little or no C++ experience, those with just enough C++ to be dangerous, and experts who need only an overview of the available tools. The tutorials must both teach C++ in general and the BTeV specific tools in particular. Finally, they must teach physicists how to find and use the detailed documentation. This report will review the status of the BTeV experiment, give an overview of the plans for and the state of the software and will then describe the plans for the tutorial suite.
PRET DRAM controller: Bank privatization for predictability and temporal isolation

Hard real-time embedded systems employ high-capacity memories such as Dynamic RAMs (DRAMs) to cope with increasing data and code sizes of modern designs. However, memory controller design has so far largely focused on improving average-case performance. As a consequence, the latency of memory accesses is unpredictable, which complicates the worst-case execution time analysis necessary for hard real-time embedded systems. Our work introduces a novel DRAM controller design that is predictable and that significantly reduces worst-case access latencies. Instead of viewing the DRAM device as one resource that can only be shared as a whole, our approach views it as multiple resources that can be shared between one or more clients individually. We partition the physical address space following the internal structure of the DRAM device, i.e., its ranks and banks, and interleave accesses to the blocks of this partition. This eliminates contention for shared resources within the device, making accesses temporally predictable and temporally isolated. This paper describes our DRAM controller design and its integration with a precision-timed (PRET) architecture called PTARM. We present analytical bounds on the latency and throughput of the proposed controller, and confirm these via simulation.
Simple technique to extend the bandwidth of parallel-coupled microstrip bandpass filter

This paper presents the concept of bandwidth extension in the parallel-coupled microstrip bandpass filter (BPF). By applying a λg/4 shunt-shorted stub at the middle of parallel-line section in the BPF, the wider bandwidth can be obtained. The prototype BPF is designed and implemented on an FR-4 substrate at 1GHz center frequency in the microstrip structure. The measured insertion loss is lower than −1.9dB whereas the return loss is kept below −11.8dB over the frequency range 0.59 to 1.4GHz. Both simulated and measured results have been confirmed the feasibility of the proposed structure for easy wideband response and rejection performance.
Test Access Mechanism Optimization, Test Scheduling, and Tester Data Volume Reduction for System-on-Chip

We describe an integrated framework for system-on-chip (SOC) test automation. Our framework is based on a new test access mechanism (TAM) architecture consisting of flexible-width test buses that can fork and merge between cores. Test wrapper and TAM cooptimization for this architecture is performed by representing core tests using rectangles and by employing a novel rectangle packing algorithm for test scheduling. Test scheduling is tightly integrated with TAM optimization and it incorporates precedence and power constraints in the test schedule, while allowing the SOC integrator to designate a group of tests as preemptable. Test preemption helps avoid hardware and power consumption conflicts, thereby leading to a more efficient test schedule. Finally, we study the relationship between TAM width and tester data volume to identify an effective TAM width for the SOC. We present experimental results on our test automation framework for four benchmark SOCs.
Managing Organizational Identity Through Ambidextrous Capabilities: A Dual Level Analysis

Organizations need to maintain enduring and stable organizational identity to gain long-term success while must adapt quickly to the increasingly volatile environment as a critical condition for profitability and survival. Such ongoing paradoxical challenge concerning management of organizational identity has been left unaddressed in the existing literature. Drawing on the ambidexterity and organizational identity literatures, this paper proposes two theoretical frameworks to systematically examine how organizations especially in the e-commerce industry should manage their organizational identities by leveraging on four types of balancing modes of ambidexterity. The case of Damai, which is China’s No.1 online ticket seller, was comprehensively analyzed on the basis of these two models. Our study not only contributes to knowledge of organizational identity and ambidexterity but also provides detailed means for practitioners to manage organizational identities at both strategic and operational levels.
Controlling Attribute Effect in Linear Regression

In data mining we often have to learn from biased data, because, for instance, data comes from different batches or there was a gender or racial bias in the collection of social data. In some applications it may be necessary to explicitly control this bias in the models we learn from the data. This paper is the first to study learning linear regression models under constraints that control the biasing effect of a given attribute such as gender or batch number. We show how propensity modeling can be used for factoring out the part of the bias that can be justified by externally provided explanatory attributes. Then we analytically derive linear models that minimize squared error while controlling the bias by imposing constraints on the mean outcome or residuals of the models. Experiments with discrimination-aware crime prediction and batch effect normalization tasks show that the proposed techniques are successful in controlling attribute effects in linear regression models.
Security in hybrid political contexts: an end-user approach

During the inception period of the JSRP, members of the consortium undertook a series of systematic reviews of the literature on key topics of concern to the programme. This paper is based on a systematic peer-led review of hybrid security arrangements in conflict affected areas. The authors sought to assess the extent of existing evidence for an end-user approach to security programming in such situations and to identify evidence gaps. The paper discusses the process of undertaking the evidence review and includes a detailed methodology. The authors critically assess the results and the existing evidence gaps and the implications for the JSRP agenda and for future research. The paper includes an annotated bibliography appendix.
Comparing an Integrated QA system performance-A Preliminary Model

A complex NLP application such as a question answering system requires sophisticated methods for evaluation, especially if there is a mechanism to submit factoid type queries as well as natural language (NL)-type questions. As part of our research we created an integrated tool that allows users to search two ways – using a keyword query and using a NL question. We present a method to evaluate output from the two types of searches and we explore the correlation of scores when judgments of output are made against keywords and those made against NL questions. We present a preliminary model, which may serve as a guideline to evaluate similar systems’ performance.
The Costs of Inflation

Polymeric scrap material, such as rubber from used vehicular tires, is reclaimed by comminuting the scrap and then advancing it under substantially atmospheric pressure through a heating chamber with the aid of two or more heated feed screws having interleaved threads, one screw rotating at half the speed of its neighbor and having a double thread with twice the pitch of the single thread of the latter. Residence time in the heating chamber may range between 3 and 30 minutes, at operating temperatures of 140 DEG to 300 DEG C. By relatively accelerating or retarding one of two adjoining screws, their interleaved threads are moved into a nearly contacting relationship in which they scrape adhering incrustations from each other.
Dynamics of Learning Near Singularities in Layered Networks

We explicitly analyze the trajectories of learning near singularities in hierarchical networks, such as multilayer perceptrons and radial basis function networks, which include permutation symmetry of hidden nodes, and show their general properties. Such symmetry induces singularities in their parameter space, where the Fisher information matrix degenerates and odd learning behaviors, especially the existence of plateaus in gradient descent learning, arise due to the geometric structure of singularity. We plot dynamic vector fields to demonstrate the universal trajectories of learning near singularities. The singularity induces two types of plateaus, the on-singularity plateau and the near-singularity plateau, depending on the stability of the singularity and the initial parameters of learning. The results presented in this letter are universally applicable to a wide class of hierarchical models. Detailed stability analysis of the dynamics of learning in radial basis function networks and multilayer perceptrons will be presented in separate work.
The role of stem cell factor and of alternative c-kit gene products in the establishment, maintenance and function of germ cells.

The c-kit gene plays a fundamental role during the establishment, the maintenance and the function of germ cells. In the embryonal gonad the c-kit tyrosine kinase receptor and its ligand Stem Cell Factor (SCF) are required for the survival and proliferation of primordial germ cells. In the postnatal animal, c-kit/SCF are required for the production of the mature gametes in response to gonadotropic hormones, i.e. for the survival and/or proliferation of the only proliferating germ cells of the testis, the spermatogonia, and for the growth and maturation of the oocytes. Finally, a truncated c-kit product, tr-kit, specifically expressed in post-meiotic stages of spermatogenesis and present in mature spermatozoa, causes parthenogenetic activation when microinjected into mouse eggs, suggesting that it might play a role in the final function of the gametes, fertilization.
Nuclear YB‐1 expression as a negative prognostic marker in nonsmall cell lung cancer

The human Y‐box binding protein, YB‐1, is a multifunctional protein that regulates gene expression. Nuclear expression of YB‐1 has been associated with chemoresistance and poor prognosis of tumour patients. Representative samples from autopsied material of primary tumours from 77 patients with NSCLC were investigated by immunohistochemistry for subcellular distribution of YB‐1 and p53, in order to evaluate the prognostic role of nuclear expression of YB‐1. Cytoplasmic YB‐1 expression was found in all tumour samples, whereas nuclear expression was only observed in 48%. There was no correlation with histological classification, clinical parameters or tumour size, stage and metastasis status. However, patients with positive nuclear YB‐1 expression in tumours showed reduced survival times when compared with patients without nuclear expression. Including information about the histology and mutational status for p53 increased the prognostic value of nuclear YB‐1. Patients with nuclear YB‐1 expression and p53 mutations had the worst prognosis (median survival 3 months), while best outcome was found in patients with no nuclear YB‐1 and wildtype p53 (median survival 15 months). This suggests that the combined analysis of both markers allows a better identification of subgroups with varying prognosis. Nuclear expression of Y‐box binding protien seems to be an independent prognostic marker.
ENHANCED VERIFIER-BASED PASSWORD AUTHENTICATED KEY AGREEMENT PROTOCOL FOR THREE-PARTIES

Most of password authenticated key agreement protocols have focused on the two-party setting where two communicating parties share a password. However, in the two-party setting any user may want to communicate with other users who have not shared the same password. In this paper we present an efficient verifier-based password authenticated key agreement protocol for three-parties. In the three-party setting each user only shares a password with a trusted server which authenticates two users and helps the users with different passwords share a common session key. Our proposed protocol is secure against several attacks and provides perfect forward secrecy. KEYWORD: authentication, cryptanalysis, key agreement, password, three-party.
A taxonomy of local search: semi-supervised query classification driven by information needs

Local search service (e.g. Yelp, Yahoo! Local) has emerged as a popular and effective paradigm for a wide range of information needs for local businesses; it now provides a viable and even more effective alternative to general purpose web search for queries on local businesses. However, due to the diversity of information needs behind local search, it is necessary to use different information retrieval strategies for different query types in local search. In this paper, we explore a taxonomy of local search driven by users' information needs, which categorizes local search queries into three types: business category, chain business, and non-chain business. To decide which search strategy to use for each category in this taxonomy without placing the burden on the web users, it is indispensable to build an automatic local query classifier. However, since local search queries yield few online features and it is expensive to obtain editorial labels, it is insufficient to use only a supervised learning approach. In this paper, we address these problems by developing a semi-supervised approach for mining information needs from a vast amount of unlabeled data from local query logs to boost local query classification. Results of a large scale evaluation over queries from a commercial local search site illustrate that the proposed semi-supervised method allow us to accurately classify a substantially larger proportion of local queries than the supervised learning approach.
Use of guest speakers in nursing education: an integrative review of multidisciplinary literature

Background: The purpose of this paper is to review existing literature regarding the use of guest speakers in multidisciplinary education and discuss the implication of the findings in nursing education. Method: An integrative review including 18 papers from 13 disciplines. Results: The evidence indicates that guest speakers can be invited by a variety of stakeholders with various motivations. Individuals from both discipline-related practical fields and academic institutions are frequently invited. Guest speakers have the ability to promote better teaching outcomes. Having a database of potential speakers decreases the work of selecting future guest speakers. Guest speakers can also be virtual with the use of guest speakers growing. A flow model of using guest speakers, including seven steps, has been articulated. Involving guest speakers promotes reciprocal benefits, where guest speakers, students, and professors have dual roles and contribute to and gain from each other. Conclusion: Findings from multiple disciplines regarding guest speakers in higher education can inform the best possible practices and procedures in how to get the best use of guest speakers in undergraduate nursing education. However, further research and study are warranted within the discipline of nursing to produce findings directly applicable to nursing education.
Tunable Plasmonic Nanoprobes for Theranostics of Prostate Cancer

Theranostic applications require coupling of diagnosis and therapy, a high degree of specificity and adaptability to delivery methods compatible with clinical practice. The tunable physical and biological effects of selective targeting and activation of plasmonic nanobubbles (PNB) were studied in a heterogeneous biological microenvironment of prostate cancer and stromal cells. All cells were targeted with conjugates of gold nanoparticles (NPs) through an antibody-receptor-endocytosis-nanocluster mechanism that produced NP clusters. The simultaneous pulsed optical activation of intracellular NP clusters at several wavelengths resulted in higher optical contrast and therapeutic selectivity of PNBs compared with those of gold NPs alone. The developed mechanism was termed “rainbow plasmonic nanobubbles. ” The cellular effect of rainbow PNBs was tuned in situ in target cells, thus supporting a theranostic algorithm of prostate cancer cell detection and follow-up guided destruction without damage to collateral cells. The specificity and tunability of PNBs is promising for theranostic applications and we discuss a fiber optic platform that will capitalize on these features to bring theranostic tools to the clinic.