Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Levodopa on Healthy Volunteers' Facial Emotion Perception: An fMRI Study

Objective:A link between the brain dopaminergic (DA) system and emotional processing seems to be supported by the DA nature of neural systems surrounding emotional recognition, the occurrence of emotional deficits in medical disorders involving a DA dysfunction, and the effect of DA agonists or antagonists on emotional processing. The authors tested the influence of levodopa administration on emotional processing in a functional MRI (fMRI) study of 10 elderly volunteers. Methods:A placebo-controlled, cross-over experimental design was used. Subjects received either levodopa (100 mg) or placebo in 2 fMRI sessions. Performance was evaluated with a passive facial emotion perception test. Results:During the placebo situation, the region-of-interest (ROI) analysis showed that emotional processing activated the bilateral amygdala. In levodopa volunteers, this activation was missing. The statistical comparison between the 2 situations (emotional vs control condition) revealed a highly significant reduction in activation of the bilateral amygdala for the levodopa fMRI session (P corrected <0.0001 in the left and P = 0.002 in the right amygdala). Conclusion:These results suggest that administration of levodopa to healthy volunteers directly or indirectly impairs the amygdalar activation during the emotional perception task. The authors hypothesized that amygdala activation may conform to an inverted U-shaped function in relation to changing dopamine levels.
A 2048 complex point FFT architecture for digital audio broadcasting system

In this paper, we propose an implementation method for a single-chip 2048 complex point FFT in terms of sequential data processing. In order to reduce the required chip area for the sequential processing of 2 K complex data, a DRAM-like pipelined commutator architecture is used. The 16-point FFT is a basic building block of the entire FFT chip, and the 2048-point FFT consists of cascaded blocks with five stages of radix-4 and one stage of radix-2. Since each stage requires rounding of the resulting bits while maintaining the proper S/N ratio, the convergent block floating point (CBFP) algorithm is used for the effective internal bit rounding.
Maximum Gaussian Mixture Model for Classification

There are a variety of models and algorithms that solves classification problems. Among these models, Maximum Gaussian Mixture Model (MGMM) is a model we proposed earlier that describes data using the maximum value of Gaussians. Expectation Maximization (EM) algorithm can be used to solve this model. In this paper, we propose a multiEM approach to solve MGMM and to train MGMM based classifiers. This approach combines multiple MGMMs solved by EM into a classifier. The classifiers trained with this approach on both artificial and real life datasets were tested to have good performance with 10-fold cross validation.
Multi-sensor image fusion using the wavelet transform

In the image fusion scheme presented in this paper, the wavelet transforms of the input images are appropriately combined, and the new image is obtained by taking the inverse wavelet transform of the fused wavelet coefficients. An area-based maximum selection rule and a consistency verification step are used for feature selection. A performance measure using specially generated test images is also suggested. <<ETX>>
TRADINNOVA: un algoritmo heurístico de compra-venta inteligente de acciones

Resumen Existen diferentes técnicas que nos aconsejan como invertir en bolsa, desde la compra de una simple acción a la elección de una cartera de acciones que dé la máxima rentabilidad con el menor riesgo posible, aunque todas estás técnicas no nos dicen nada de cuando vender las acciones compradas para probablemente comprar otras acciones diferentes. En este trabajo se propone y presenta un algoritmo heuŕıstico (TRADINNOVA), que realiza la compra-venta inteligente de acciones durante un periodo de tiempo. La elección de la acción a comprar se podrá realizar mediante diversas técnicas heuŕısticas según la preferencia del inversor. Se ha realizado una simulación en el Mercado Continuo Español ejecutando TRADINNOVA entre los años 2001 y 2004.
Effect of study setting on anticoagulation control: a systematic review and metaregression.

BACKGROUND For patients receiving therapy with oral anticoagulants (OACs), the proportion of time spent in the therapeutic range (ie, anticoagulation control) is strongly associated with bleeding and thromboembolic risk. The effect of study-level factors, especially study setting, on anticoagulation control is unknown. OBJECTIVES Describe anticoagulation control achieved in the published literature. We also used metaregressive techniques to determine which study-level factors significantly influenced anticoagulation control. STUDIES All published randomized or cohort studies that measured international normalized ratios (INRs) serially in anticoagulated patients and reported the proportion of time between INRs ranging from 1.8 to 2.0 and 3.0 to 3.5. RESULTS We identified 67 studies with 123 patient groups having 50,208 patients followed for a total of 57,154.7 patient-years. A total of 68.3% of groups were from anticoagulation clinics, 7.3% were from clinical trials, and 24.4% were from community practices. Overall, patients were therapeutic 63.6% of time (95% confidence interval [CI], 61.6 to 65.6). In the metaregression model, study setting had the greatest effect on anticoagulation control with studies in community practices having significantly lower control than either anticoagulation clinics or clinical trials (-12.2%; 95% CI, -19.5 to -4.8; p < 0.0001). Self-management was associated with a significant improvement of time spent in the therapeutic range (+7.0%; 95% CI, 0.7 to 13.3; p = 0.03). CONCLUSIONS Patients who have received anticoagulation therapy spend a significant proportion of their time with an INR out of the therapeutic range. Patients from community practices showed significantly worse anticoagulation control than those from anticoagulation clinics or clinical trials. This should be considered when interpreting the results of, and generalizing from, studies involving OACs.
PROPORCIONATIONALITY INDEX AND LOW BIRTH WEIGTH

The study between the relation with low birthweight (LBW) and mortality neonatal is most important, not only to establish precventive action, but also reduce de higth percentage of BPN in poppulations of the developmente countries. For that, a study was carried out with the purpose of verifying the influence of LBW in the mortality neonatal, appraised throught the Rohrer’s Ponderal Index (IR). The sample comprised all biological mothers and their children under 1 year of age assisted for 5 days at 22 health units of Maringa municipality, in 1998. The total of mothers was of 575. It was considered LBW (low birthweight) all children with a weight <2500g. The children with Rohrer’s Ponderal Index (IR) < 2,51 was considered disporportionate. From the total, 168(29,2%) children was considered dispropotionate. For the children LBW this percentage was 76,5%. For the others groups with insificient and adequate weigth the percentage was 53,7% and 18,3%. The association with the IR and length < 47cm was 23,2% for higth risk for death. For the LBW group the percentage was 61,9%. The higths index of the risk reinforce that is necessary the implement a prenatal service with the purpose to reduce the percentages with LBW.
Binarized Support Vector Machines

The widely used support vector machine (SVM) method has shown to yield very good results in supervised classification problems. Other methods such as classification trees have become more popular among practitioners than SVM thanks to their interpretability, which is an important issue in data mining. In this work, we propose an SVM-based method that automatically detects the most important predictor variables and the role they play in the classifier. In particular, the proposed method is able to detect those values and intervals that are critical for the classification. The method involves the optimization of a linear programming problem in the spirit of the Lasso method with a large number of decision variables. The numerical experience reported shows that a rather direct use of the standard column generation strategy leads to a classification method that, in terms of classification ability, is competitive against the standard linear SVM and classification trees. Moreover, the proposed method is robust; i.e., it is stable in the presence of outliers and invariant to change of scale or measurement units of the predictor variables. When the complexity of the classifier is an important issue, a wrapper feature selection method is applied, yielding simpler but still competitive classifiers.
DNA-based method for rapid identification of the pine pathogen, Phytophthora pinifolia.

Phytophthora pinifolia causes a needle and shoot disease in Pinus radiata, referred to as 'Daño Foliar del Pino'. This newly discovered disease requires intensive research efforts that necessitate the processing of large numbers of samples for which accurate identification, often by people not experienced in Phytophthora taxonomy, is required. The aim of this study was, therefore, to develop species-specific primers for P. pinifolia that amplify the internal transcribed spacer region of the ribosomal operon and the nuclear Ypt1 gene, respectively. The primers were tested over several Phytophthora spp. , as well as fungi isolated from P. radiata. In all cases, only P. pinifolia was amplified. In addition to the species-specific primers, a PCR-restriction fragment length polymorphism protocol using available Phytophthora genus-specific primers was also used to generate a species-specific profile for P. pinifolia. This provided a characteristic profile that allows the identification of P. pinifolia, and it could also discriminate between 27 different species of Phytophthora. Both techniques reported in this study make it possible to identify large numbers of P. pinifolia cultures accurately and efficiently, which will be important for both quarantine work and biological research on this important new pathogen.
Challenges ahead for companion diagnostics.

T he U.S. Food and Drug Administration ’ s (FDA) approval of vemurafenib (Plexxikon/Roche) last August was greeted as a milestone not only for melanoma treatment but also for personalized medicine. The drug is indicated for patients who harbor a BRAF V600 → E mutation. Vemurafenib was developed along with a companion diagnostic, in a test case for how the FDA plans to handle personalized drugs from now on. In a draft guidance issued last July 14, the FDA defined companion diagnostics as devices that provide essential information for the safe and effective use of a corresponding therapeutic product. It stated that it would review personalized drugs only in tandem with the diagnostic that was used to select patients for clinical trials, adding that personalized drug labels should refer specifically to approved diagnostics for use in selecting patients for treatment. FDA offi cials emphasize that the approach is needed to ensure that personalized drugs are given only to likely responders. But as the experience with vemurafenib shows, the new method encroaches on entrenched diagnostic turf. Hospitals, drug companies, and professional medical societies have all reacted against the guidance, claiming that it locks researchers and clinicians into infl exible protocols that stifl e innovation and limit access to treatment. They say that laboratory-developed tests (LDTs) that individual institutions create and administer can adequately determine patient eligibility for personalized care. Vemurafenib ’ s creators at Plexxikon, a Berkeley, Calif. – based biotechnology company, rank among the guidance ’ s most outspoken critics; they claim it imposes excessive burdens on early-stage drug development. However, Plexxikon also anticipated diagnostic scrutiny from the FDA even before their BRAF inhibitor, then known as PLX-4032, had shown human proof-of-concept antitumor effects. So in 2005, to accelerate the drug ’ s development, Plexxikon teamed with Roche Molecular Diagnostics (RMD), in Pleasanton, Calif. , on the development of an error-free system for detecting BRAF mutations. Producing the test took several years — partly because RMD had to devise a way to work with paraffi n-embedded, formalin-fi xed tumor samples, in which DNA is often damaged. From these efforts emerged the Cobas 4800 V600 Mutation Assay, a closed, PCRbased system that fl ags V600 → E mutations with a “yes” or “no” fl uorescence reaction. Plexxikon credits the test with propelling vemurafenib from discovery to approval in just 5 years, specifi cally by reducing the size of the trial population to V600 → E mutation carriers only. Vemurafenib ’ s label now indicates that because it was tested only in patients selected with the Cobas assay, doctors should avoid using it in BRAF-mutated patients selected using some other method. FDA spokesperson Erica Jefferson emphasized that the label doesn ’ t constitute regulation. “Product labels are intended to guide treatment decisions and provide clinical information,” she said. “The language is worded to allow for future approved tests for use in selecting patients for treatment. ”
The X-ray interpretation of denaturation and the structure of the seed globulins.

THE X-ray diffraction photographs usually obtained from apparently nonfibrous proteins have so much in common with one another and with the photographs given by certain natural protein fibres when disoriented that the inference seems clear that all proteins at some stage of their existence are fibrous in the molecular sense [Astbury, 1933; 1934,1,2]. Recently [Astbury and Lomax, 1934, 1, 2; 1935] this concept has been expressed as a generalised interpretation of denaturation in the conclusion that the two more stable and insoluble states of protein structure, the fibrous and the denatured, are based on fundamentally similar modes of molecular arrangement; that, in fact, the denatured state2 is essentially a fibrous state inasmuch as it always consists of peptide chains, often fully extended, and aggregated after coagulation in parallel bundles, as in fibroin [Meyer and Mark, 1928], f3-keratin [Astbury and Street, 1931; Astbury and Woods, 1933], /3-myosin [Astbury and Dickinson, 1935], fibrin [Katz and De Rooy, 1933] etc. Itwas found that heat-denaturation ofthe albumins, for instance, merely makes the X-ray photograph more like that of a random arrangement of fibres of/-keratin (stretched hair, horn, etc.; cf. Plate V, Figs. 1 and 3). ,B-Keratin is built from almost fully-extended polypeptide chains linked side-to-side, firstly by combinations between their side-chains ("side-chain linkage "), and secondly in a direction at right angles [Astbury and Sisson, 1935], through attractions between the =CO and =NH groups of neighbouring main-chains ("backbone linkage"). The three-dimensional structure is that of a pile of polypeptide "grids ", the average distance apart of the main-chains in the plane of each grid being about 9*8 A. ("side-chain spacing") and the distance between the grids being 4*65 A. (" backbone spacing "). These two spacings correspond respectively to the two reflections, 001 and 200, seen on the equator of Fig. 4: they are the two prin'cipal side-spacings of the ,B-keratin crystallites, whilst the reflection 020 (spacing about 3*4 A.) gives the average length of an amino-acid residue in the direction of the main-chains. Fig. 4 is a "fibre photograph" of crystallites all pointing roughly in the same direction (the fibre-axis) and taken with the X-ray beam perpendicular to this direction; but when the crystallites are
[Determination of ligustilide for quality assessment of Ligusticum chuanxiong].

OBJECTIVE To assay ligustilide content in the herb of Szechwan Lovage Rhizome (Chuanxiong, CX), which is the dried rhizome of Ligusticum chuanxiong in order to assess the quality. METHOD Ligustilide was quantitatively analyzed by high-performance liquid chromatography in 21 CX samples. An Alltima C18 column (4.6 mmx 150 mm, 5 microm) was used as the analytical column. The mobile phase consisted of water and acetonitrile (40:60). The flow rate was maintained at 1.0 mL x min(-1) with the column temperature at ambient conditions. The detection wavelength was set at 350 nm. RESULT The average content of Z-ligustilide in 21 CX samples was found to be 7.40 +/- 3.54 mg x g(-1)(x +/- s, n = 21). Therefore,the content of Z-ligustilide in CX should not be less than 0.66% (calculated on the dried basis). CONCLUSION The overall analytical procedure is rapid and accuracy which is considered suitable for the quantitative analysis of ligustilide in CX. The amount of ligustilide in CX samples collected from different cultivation areas was obviously different. However, a relatively higher content of ligustilide was generally found in the CX collected from its main cultivated areas.
Database‐independent, database‐dependent, and extended interpretation of peptide mass spectra in VEMS V2.0

The Virtual Expert Mass Spectrometrist (VEMS) program package was developed for flexible, automated, and manual de novo tandem mass spectrometry (MS/MS) protein sequencing, and includes accessory programs for matrix‐assisted laser desorption/ionization‐mass spectrometry (MS) interpretation, and generation of protein and peptide databases. VEMS V2.0 has been developed into a fast tool for combining database‐independent and ‐dependent protein assignments in an extended analysis of MS/MS‐peptide data. MS or MS/MS data can be directly recalibrated after the first search by fitting the data to the best search result using polynomial equations. The score function is an improvement of known scoring algorithms and can be adapted for any MS instrument type. In addition, VEMS offers a novel statistical model for evaluating the significance of the protein assignment. The novel features are illustrated by the analysis of the fragmentation spectra obtained by liquid chromatrography‐MS/MS analysis of peptides from an anionic peroxidase enriched protein fraction from potato root tissue. The extended analysis mode resulted in the additional assignment of spectra for nine modified tryptic peptides and nine miscleaved peptides, in addition to the 45 spectra from regular tryptic peptides. Of the nine modified peptides, three were glycosylated.
Inflammatory Muscle Disease, 15-Year Experience at Tertiary Centers

Objectives: Idiopathic inflammatory myopathies (IIM) are a group of inflammatory muscle diseases with a paucity of data and literature from Saudi Arabia. The aim was to describe the demographics, evaluate clinical features, organ involvement, investigations, treatment strategies, and to assess factors affecting remission in IIM patients. Methods: We conducted this retrospective study at 5 medical tertiary centers in Saudi Arabia to analyze the records of patients with IIM from 1999 to 2014. Results: A total of 28 patients with IIM were identified with a female to male ratio of 3:1. Pure polymyositis accounted for (32.1%), pure dermatomyositis (21.4%), juvenile dermatomyositis (10.7%), and IIM mixed with connective tissue diseases (35.7%) of the patients. The most common presentation was proximal myopathy (93.9%). The musculoskeletal system was the most commonly involved (78.6%), followed by the gastrointestinal system (39.3%). Investigations revealed an elevated CK of 2995.12 ± 3431.51 (mean ± SD), EMG was positive in (92.9%) of patient, and muscle biopsy in (42.9%). Treatment data showed a good response to Prednisolone (96.4%). Conclusion: The results of this multiregional retrospective study from Saudi Arabia on IIM patients showed similar clinical features to other reviews; however, malignancy percentages were lower. We found a strong relation between comorbid illnesses and relapse. Normalization of muscle power is a reliable prognostic factor that may help assess the efficacy of treatment.
Two distinct protein–protein interactions between the NIT2 and NMR regulatory proteins are required to establish nitrogen metabolite repression in Neurospora crassa

Nitrogen metabolism is a highly regulated process in Neurospora crassa. The structural genes that encode nitrogen catabolic enzymes are subject to nitrogen metabolite repression, mediated by the positive‐acting NIT2 protein and by the negative‐acting NMR protein. NIT2, a globally acting factor, is a member of the GATA family of regulatory proteins and has a single Cys2/Cys2 zinc finger DNA‐binding domain. The negative‐acting NMR protein interacts via specific protein–protein binding with two distinct regions of the NIT2 protein, a short alpha‐helical motif within the NIT2 DNA‐binding domain and a second motif at its carboxy terminus. Deletions of segments of NIT2 throughout most of its length result in truncated proteins, which are still functional for activating gene expression; most of these mutant NIT2 proteins still allow proper nitrogen repression of nitrate reductase synthesis. In contrast, deletions or certain amino acid substitutions within the zinc finger and the carboxy‐terminal tail result in a loss of nitrogen metabolite repression. Those mutated forms of NIT2 that are insensitive to nitrogen repression have also lost one of the NIT2–NMR protein–protein interactions. These results provide compelling evidence that the specific NIT2–NMR interactions have a regulatory function and play a central role in establishing nitrogen metabolite repression.
Immediate and Ongoing Detection of Prions in the Blood of Hamsters and Deer following Oral, Nasal, or Blood Inoculations

ABSTRACT Infectious prions traverse epithelial barriers to gain access to the circulatory system, yet the temporal parameters of transepithelial transport and persistence in the blood over time remain unknown. We used whole-blood real-time quaking-induced conversion (wbRT-QuIC) to analyze whole blood collected from transmissible spongiform encephalopathy (TSE)-inoculated deer and hamsters throughout the incubation period for the presence of common prion protein-conversion competent amyloid (PrPC-CCA). We observed PrPC-CCA in the blood of TSE-inoculated hosts throughout the disease course from minutes postexposure to terminal disease.
Opinion mining and sentiment classification: A review

With the evolution of web technology, there is a huge amount of data present in the web for the internet users. These users not only use the available resources in the web, but also give their feedback, thus generating additional useful information. Due to overwhelming amount of user's opinions, views, feedback and suggestions available through the web resources, it's very much essential to explore, analyze and organize their views for better decision making. Opinion Mining or Sentiment Analysis is a Natural Language Processing and Information Extraction task that identifies the user's views or opinions explained in the form of positive, negative or neutral comments and quotes underlying the text. Various supervised or data-driven techniques to Sentiment analysis like Naïve Byes, Maximum Entropy and SVM. For classification use support vector machine (SVM), it performs the sentiment classification task also consider sentiment classification accuracy.