Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Virtual Histology and Virtual Biopsy Using Laser-scanning Confocal Microscopy

The aim of this project is to acquire a direct image of histology from in vivo gastrointestinal mucosa. In other words, the task of `endo-microscope' is to observe the cellular architecture of tissue in vivo during routine endoscopic examination. As the first step to completing this study, resected fresh specimens from the oesophagus, stomach and colon were examined by laser-scanning confocal microscopy (LCM) (Fluoview, Olympus, Tokyo). Fresh untreated mucosal specimens obtained by endoscopic pinch biopsy, polypectomy or endoscopic mucosal resection were collected and placed in normal saline and examined by LCM, collecting the reflective light of a 488-nm wavelength argon laser beam. As the second step, a probe-type LCM `endo-microscope' was designed and applied to observe the human oral-cavity mucosa. The probe has 4.5-mm outer diameter and 20-cm length, which enables easy access to oral cavity mucosa. The estimated special resolution of the probe is 1-5 μm. A real-time microscopic image directly from ex vivo fresh specimens was acquired. The acquired LCM images corresponded well with the conventional H-E light microscopic images. Cell wall, nucleus and cytoplasm were simultaneously visualized by LCM scanning. This novel method enables serial imaginary microscopic sections on fresh specimens. In addition, a probe-type LCM `endo-microscope' was designed and was applied to observe human oral cavity mucosa. Virtual histological images from the living oral squamous cell were successfully obtained. LCM images from ex vivo fresh specimens demonstrated the features of the H-E staining histological image. In the next step to accomplish our project, we developed a LCM probe with 4.5-mm outer diameter to obtain a virtual image of human oral cavity mucosa.
Anemia in old age

Background Pernicious anemia is undeniably associated with vitamin B12 deficiency, but the association between subnormal vitamin B12 concentrations and anemia in older people is unclear. The aim of this systematic review was to evaluate the association between subnormal vitamin B12 concentrations and anemia in older people. Methods Clinical queries for etiology and treatment in bibliographic databases (PubMed [01/1949-10/2009]; EMBASE [01/1980-10/2009]) were used. Reference lists were checked for additional relevant studies. Observational studies ( ≥ 50 participants) and randomized placebo-controlled intervention trials (RCTs) were considered. Results Twenty-five studies met the inclusion criteria. Twenty-one observational cross-sectional studies (total number of participants n=16185) showed inconsistent results. In one longitudinal observational study, low vitamin B12 concentrations were not associated with an increased risk of anemia (total n=423). The 3 RCTs (total n=210) were well-designed and showed no effect of vitamin B12 supplementation on hemoglobin concentrations during follow-up in subjects with subnormal vitamin B12 concentrations at the start of the study. Due to large clinical and methodological heterogeneity, statistical pooling of data was not performed. Conclusions Evidence of a positive association between a subnormal serum vitamin B12 concentration and anemia in older people is limited and inconclusive. Further well-designed studies are needed to determine whether subnormal vitamin B12 is a risk factor for anemia in older people.
Transmission Expansion Planning in Competitive Electricity Markets Using AC OPF

Transmission expansion planning (TEP) is one of the most important parts of expansion planning in power systems. Competition in these systems has resulted in essential changes in TEP models and criteria. While methods introduced so far are essentially based on DC load flow, the proposed method utilizes the AC optimal power flow (OFF) in order to model the real world condition and obtaining optimal plans. Furthermore, in order to model the operation and investment cost, transmission tariffs are used. Investigation on 8-bus system confirms the advantages of the proposed method as compared with previously presented approaches
Stages in coming to terms with reflection: student advanced nurse practitioners' perceptions of their reflective journeys.

AIM OF STUDY To explore student Advanced Nurse Practitioners' (ANPs) experiences of reflection. BACKGROUND The development of student ANPs' reflective abilities as part of the implementation of a Master's Course in Advanced Nursing Practice at Wolverhampton University provided the background to the study. Developing reflective abilities was seen as an essential component of ANP development. To facilitate this process a preentry degree level reflective practice module and a reflective component for the level 4 (Master's level) practice module were devised. RATIONALE This was a new educational initiative and this study provided the opportunity to explore students' experiences of it following completion of the reflective modules. DESIGN/METHODS A qualitative methodology was used. Fourteen ANP students were interviewed and their reflective learning contracts were analysed. Colaizzi's (1978) seven-stage model guided data analysis. FINDINGS The findings were categorized under the headings of: (i) reflection as a transforming process, (ii) reflective journeys, (iii) worldviews. This paper presents an analysis of the second category reflective journeys. It identifies a number of stages in the development of students' reflective abilities. CONCLUSIONS The conclusions have implications for those involved in reflective curriculum development, and for those seeking to develop reflective abilities in students.
Emergency obstacle avoidance module for mobile robots using a laser range finder

This paper describes the development of an emergency obstacle avoidance module for a mobile robot by using a laser range finder. To achieve safe and rapid obstacle avoidance, we apply a subsumption architecture. In the proposed system, the subsumption architecture provides four layers of simple behavior modules such as an emergency obstacle avoidance module and autonomous driving module. Since emergency obstacle avoidance module requires rapid response times, we employ an embedded microcontroller that only processes signals acquired from a laser range finder. When the emergency obstacle avoidance module detects an obstacle, the mobile robot automatically disables the autonomous driving module and executes emergency obstacle avoidance maneuvers. The proposed module is implemented on an actual mobile robot and tested in real-world situations.
An Avian Sarcoma/Leukosis Virus-Based Gene Trap Vector for Mammalian Cells

ABSTRACT RCASBP-M2C is a retroviral vector derived from an avian sarcoma/leukosis virus which has been modified so that it uses the envelope gene from an amphotropic murine leukemia virus (E. V. Barsov and S. H. Hughes, J. Virol. 70:3922–3929, 1996). The vector replicates efficiently in avian cells and infects, but does not replicate in, mammalian cells. This makes the vector useful for gene delivery, mutagenesis, and other applications in mammalian systems. Here we describe the development of a derivative of RCASBP-M2C, pGT-GFP, that can be used in gene trap experiments in mammalian cells. The gene trap vector pGT-GFP contains a green fluorescent protein (GFP) reporter gene. Appropriate insertion of the vector into genes causes GFP expression; this facilitates the rapid enrichment and cloning of the trapped cells and provides an opportunity to select subpopulations of trapped cells based on the subcellular localization of GFP. With this vector, we have generated about 90 gene-trapped lines using D17 and NIH 3T3 cells. Five trapped NIH 3T3 lines were selected based on the distribution of GFP in cells. The cellular genes disrupted by viral integration have been identified in four of these lines by using a 5′ rapid amplification of cDNA ends protocol.
A Direct Method of Nonparametric Measurement Selection

A direct method of measurement selection is proposed to determine the best subset of d measurements out of a set of D total measurements. The measurement subset evaluation procedure directly employs a nonparametric estimate of the probability of error given a finite design sample set. A suboptimum measurement subset search procedure is employed to reduce the number of subsets to be evaluated. Teh primary advantage of the approach is the direct but nonparametric evaluation of measurement subsets, for the M class problem.
Caching processor general registers

VLIW, multi-context, or windowed-register architectures may require one hundred or more processor registers. It can be difficult to design a register file with so many registers that meets processor cycle time requirements. We propose to resolve this problem by taking advantage of register values that are bypassed within a processor's pipeline, and supplementing the bypassed values with values supplied by a small register cache. If the register cache is sufficiently small then it can be designed to meet a fast target cycle time. We call this combination of bypassing and register caching the register scoreboard and cache. We develop a simple performance model and show by simulations that it can be effective for windowed-register architectures.
DFT Frequency Estimation Threshold Level with Windowed Data

Discrete Fourier transform (DFT) based frequency estimation is an important topic and an often applied method in measurement science and signal processing in general. This is due to its optimality in terms of frequency estimation error, achieving the best possible performance given by the Cramer Rao lower bound (CRLB) asymptotically and the possibility to implement it computationally efficient via a fast Fourier transform (FFT). Below a certain level of signal-to-noise ratio (SNR), the so called threshold effect occurs, and the performance of the estimator decreases quickly. In this paper, we investigate the effect of windowing the data prior to the frequency estimation process on the threshold
Disruption of aldA Influences the Developmental Process in Myxococcus xanthus

ABSTRACT Previously, we identified a gene (aldA) fromMyxococcus xanthus, which we suggested encoded the enzyme alanine dehydrogenase on the basis of similarity to known Ald protein sequences (M. J. Ward, H. Lew, A. Treuner-Lange, and D. R. Zusman, J. Bacteriol. 180:5668–5675, 1998). In this study, we have confirmed that aldA does encode a functional alanine dehydrogenase, since it catalyzes the reversible conversion of alanine to pyruvate and ammonia. Whereas an aldA gene disruption mutation did not significantly influence the rate of growth or spreading on a rich medium, AldA was required for growth on a minimal medium containing l-alanine as the major source of carbon. Under developmental conditions, the aldA mutation caused delayed aggregation in both wild-type (DZ2) and FB (DZF1) strains. Poorly formed aggregates and reduced levels of spores were apparent in the DZ2 aldA mutant, even after prolonged development.
Virtual Network Functions exploitation through a prototype resource management framework

This paper elaborates on the design of a prototype framework for the exploitation of virtual Network Functions (NFs) and virtual Network Resources (NRs) in a cloud-based network architecture. The proposed framework is based on a Marketplace approach, utilizing a centralized network architecture, where the exploitation of the available NFs/NRs is managed by a Brokerage Module. This Brokerage Module applies trading policies based on a resource predictive entity that monitors the resources, towards matching the end-user demands and providing the acceptable bandwidth required.
A near-infrared interactance model for the estimation of infant body composition

In low and middle income settings, there is a pressing need for simple, low-cost and robust ways of determining infant body composition. Measuring and monitoring body composition plays an important role in addressing the burden of child deaths under five, where depleted fat stores may put infants at risk of mortality, morbidity in later life and delayed cognitive development. In a subset of 41 infants aged between 2 and 8 months, we develop and evaluate a potential model for using near-infrared interactance (NIR) features for the estimation of infant fat mass and the deuterium dilution method as the reference method. Model evaluation demonstrates the potential of NIR to capture variability in body composition, with a correlation of R = 0.90 and Bland-Altman agreement (mean bias with 95% confidence intervals) of −8 (−553, 536) g with fat mass estimated by a four-compartment (4C) model. With continued development in the larger dataset, this model may enable simple and low-cast body composition assessment of infants in low and middle incomes settings where the burden of infant deaths is greatest.
Comparison of the antidiabetic activity of Berberis lyceum root extract and berberine in alloxan‐induced diabetic rats

Berberine has been shown to have hypoglycaemic activity in several in vitro and in vivo models, although the mechanism of action is not fully known. Berberis lyceum Royle root produces high concentrations of berberine, and in traditional medicine, the whole extract of this plant is used widely to treat diabetes. The antidiabetic activity of the ethanol root extract of Berberis lyceum was compared with pure berberine in normal and alloxan‐diabetic rats using similar doses of each. The concentration of berberine in the extract was determined to be 80% dry weight with only trace amounts of other alkaloids present. The purpose of the study was to investigate the effects of berberine and a whole extract of Berberis lyceum on blood glucose and other parameters associated with diabetes, to compare the effects of the crude extract with those of pure berberine and thus validate its use as a therapeutic agent, and finally to identify any contribution of the other components of the extract to these effects.
Etude du couvert forestier par processus ponctuels marqués. (Tree crown extraction using Marked Point Processes)

Cette these aborde le probleme de l'extraction d'arbres a partir d'images aeriennes InfraRouge Couleur (IRC) de forets. Nos modeles reposent sur l'utilisation de processus objets ou processus ponctuels marques. Il s'agit de variables aleatoires dont les realisations sont des configurations d'objets geometriques. Une fois l'objet geometrique de reference choisi, nous definissons l'energie du processus par le biais d'un terme a priori, modelisant les contraintes sur les objets et leurs interactions, ainsi qu'un terme image. Nous echantillonnons le processus objet grâce a un algorithme de type Monte Carlo par Chaines de Markov a sauts reversibles (RJMCMC), optimise par un recuit simule afin d'extraire la meilleure configuration d'objets, qui nous donne l'extraction recherchee. Dans ce manuscrit, nous proposons differents modeles d'extraction de houppiers, qui extraient des informations a l'echelle de l'arbre selon la densite du peuplement. Dans les peuplements denses, nous presentons un processus d'ellipses, et dans les zones de plus faible densite, un processus d'ellipsoides. Nous obtenons ainsi le nombre d'arbres, leur localisation, le diametre de la couronne et leur hauteur pour les zones non denses. Les algorithmes automatiques resultant de cette modelisation sont testes sur des images IRC tres haute resolution fournies par l'Inventaire Forestier National (IFN).
A linear differential formulation of friction forces for adaptive estimator algorithms

In this paper a new approach for the formulation of the friction forces velocity function is introduced. The scope of this formulation is to facilitate the implementation of control laws for systems where friction forces appear. The friction model includes the exponential decay part, the Coulomb and viscous friction. The introduced formulation is based on the observation that the friction coefficient function of velocity can be presented as the solution of a linear differential equation. Due to this linearity, the parameters of the derived differential equation can be estimated easily by an adaptive system. The estimation of these parameters is equivalent to the estimation of the friction coefficient in the full range of operational velocities. This knowledge gives to the designed control systems the potential to avoid successfully the stick-slip phenomenon. A control law for one D.O. F. system, where friction appears, is designed in order to prove the applicability of the proposed formulation of the friction model in control systems. A MRAC adaptive algorithm estimates the differential friction model parameters, using the measured friction force, while a sliding controller adjusts the motion of the mechanical system. The proposed friction model can be used in any control system where friction forces have to be compensated. The linear form of the model is suitable for common adaptive estimators. Therefore, the proposed structure is suitable for robotic applications, such as assembly, deburring, etc.
Differentiating Indexation in Dutch Pension Funds

Funded social security programs are particularly vulnerable to economic and financial market shocks. As a consequence of the recent crisis, a large fraction of the Dutch pension funds had to submit restoration plans for the recovery of their buffers. Such plans will have to rely primarily on a mix of reduced benefit indexation and increased pension contributions. Hence, a discussion has emerged whether indexation should be differentiated across the various groups of participants in a pension fund. We investigate this issue numerically, developing an applied many-generation small open-economy OLG model with heterogeneous agents. The pension system consists of a first-pillar PAYG component and a second pillar with a pension fund. In our stochastic simulations, we hit the economy with a variety of unexpected demographic, economic and financial shocks. We compare uniform indexation of pension rights across all fund participants with alternatives such as status-contingent indexation in which pensions are protected against price inflation. While the aggregate welfare consequences are small, group-specific consequences are more substantial with the workers and future born losing and retirees benefitting from a shift away from uniform indexation. The exception is a scheme which links indexation directly to the fund’s asset performance. Under this scheme the retired benefit without other groups losing. The welfare effects are primarily the result of systematic welfare redistributions rather than of shifts in the benefits of risk sharing. Contribution rates always have to rise substantially from their initial levels to maintain the system’s sustainability. An increase in the retirement age that leaves existing pension rights untouched does little to avoid this rise with its adverse labour market consequences.
Sentiment Analysis by Joint Learning of Word Embeddings and Classifier

Word embeddings are representations of individual words of a text document in a vector space and they are often use- ful for performing natural language pro- cessing tasks. Current state of the art al- gorithms for learning word embeddings learn vector representations from large corpora of text documents in an unsu- pervised fashion. This paper introduces SWESA (Supervised Word Embeddings for Sentiment Analysis), an algorithm for sentiment analysis via word embeddings. SWESA leverages document label infor- mation to learn vector representations of words from a modest corpus of text doc- uments by solving an optimization prob- lem that minimizes a cost function with respect to both word embeddings as well as classification accuracy. Analysis re- veals that SWESA provides an efficient way of estimating the dimension of the word embeddings that are to be learned. Experiments on several real world data sets show that SWESA has superior per- formance when compared to previously suggested approaches to word embeddings and sentiment analysis tasks.
Comparison of Early Cortical Networks in Efficient and Inefficient Visual Search: An Event-Related Potential Study

Functional magnetic resonance imaging studies have indicated that efficient feature search (FS) and inefficient conjunction search (CS) activate partially distinct frontoparietal cortical networks. However, it remains a matter of debate whether the differences in these networks reflect differences in the early processing during FS and CS. In addition, the relationship between the differences in the networks and spatial shifts of attention also remains unknown. We examined these issues by applying a spatio-temporal analysis method to high-resolution visual event-related potentials (ERPs) and investigated how spatio-temporal activation patterns differ for FS and CS tasks. Within the first 450 msec after stimulus onset, scalp potential distributions (ERP maps) revealed 7 different electric field configurations for each search task. Configuration changes occurred simultaneously in the two tasks, suggesting that contributing processes were not significantly delayed in one task compared to the other. Despite this high spatial and temporal correlation, two ERP maps (120190 and 250300 msec) differed between the FS and CS. Lateralized distributions were observed only in the ERP map at 250300 msec for the FS. This distribution corresponds to that previously described as the N2pc component (a negativity in the time range of the N2 complex over posterior electrodes of the hemisphere contralateral to the target hemifield), which has been associated with the focusing of attention onto potential target items in the search display. Thus, our results indicate that the cortical networks involved in feature and conjunction searching partially differ as early as 120 msec after stimulus onset and that the differences between the networks employed during the early stages of FS and CS are not necessarily caused by spatial attention shifts.
Automatic Fungal Disease Detection based on Wavelet Feature Extraction and PCA Analysis in Commercial Crops

This paper describes automatic detection and classification of v isual symptoms affected by fungal disease. Algorithms are developed to acquire and process color images of fungal disease affected on commercial crops like chili, cotton and sugarcane. The developed algorith ms are used to preprocess, segment, extract and reduce features fro m fungal affected parts of a crop. The feature extract ion is done with discrete wavelet transform (DWT) and features are further reduced by using Principal co mponent analysis (PCA). Reduced features are then used as inputs to classifiers and tests are performed to classify image samples. We have used statistical based Mahalanobis distance and Probabilistic neural network (PNN) classifiers. The average classification accuracies using Mahalanobis distance classifier are 83.17% and using PNN classifier are 86.48%.
Bloom-Filter Aided Two-Layered Structured Overlay for Highly-Dynamic Wireless Distributed Storage

In this letter, we propose a novel two-layered structured overlay, called a distributed Bloom filter table (DBFT), which is capable of substantially reducing overhead imposed by highly-dynamic peer-to-peer (P2P) distributed storage systems. More specifically, in our DBFT scheme, each node's ID remains unchanged, when the associated cluster changes due to the physical movement of the node. This provides us with an exclusive benefit of maintaining the rule of structured overlay without imposing any additional overhead to reconfigure index between saved information and its stored node, which cannot be achieved by the previous P2P techniques designed for mobile ad hoc networks. Moreover, another merit of the proposed scheme is that stored packets per node become more equally distributed than {in} the conventional schemes, because each node maintains to have its own {addressing- and content-}data when it moves within a storage area.