Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of machine learning algorithms for breast cancer

Machine learning algorithms are computer programs that try to predict cancer type based on the past data. The eventual goal of Machine learning algorithms in cancer diagnosis is to have a trained machine learning algorithm that gives the gene expression levels from cancer patient, can accurately predict what type and severity of cancer they have, aiding the doctor in treating it. The existing technology compares three different machine learning algorithms are Decision Tree, Support Vector Machine, Bayesian Belief Network. The main drawback of these algorithms is unusual because the number of features (gene expressions) far exceeds the number of cases (samples taken from patients). Performance efficiency can be achieved by comparing two more algorithms are Random Forest and Naïve Bayes algorithms. Because Random forest and Naïve Bayes are used as feature selection method, Random Forest is used to rank the feature importance and applied for relevant feedback. The requirements are weka tool, Java and Relational Database.
DGAT2 Is a New Diacylglycerol Acyltransferase Gene Family

Acyl CoA:diacylgycerol acyltransferase (EC2.3.1.20; DGAT) catalyzes the final step in the production of triacylglycerol. Two polypeptides, which co-purified with DGAT activity, were isolated from the lipid bodies of the oleaginous fungusMortierella ramanniana with a procedure consisting of dye affinity, hydroxyapatite affinity, and heparin chromatography. The two enzymes had molecular masses of 36 and 36.5 kDa, as estimated by gel electrophoresis, and showed a broad activity maximum between pH 6 and 8. Based on partial peptide sequence information, polymerase chain reaction techniques were used to obtain full-length cDNA sequences encoding the purified proteins. Expression of the cDNAs in insect cells conferred high levels of DGAT activity on the membranes isolated from these cells. The two proteins share 54% homology with each other but are unrelated to the previously identified DGAT gene family (designated DGAT1), which is related to the acyl CoA:cholesterol acyltransferase gene family, or to any other gene family with ascribed function. This report identifies a new gene family, including members in fungi, plants and animals, which encode enzymes with DGAT function. To distinguish the two unrelated families we designate this new class DGAT2 and refer to the M. ramanniana genes asMrDGAT2A and MrDGAT2B.
Rubrics-based Writing: Liberating rather than Restricting in Many Contexts

Introduction “If you keep in mind that readers are content-driven, time-pressed, and decision-focused, you can write right-every time,” asserts Harvard Kennedy School lecturer in Public Policy, Holly Weeks (2005, p.3). She elaborates that because business audiences prefer their written messages to be clear, unembellished and to the point, business messages must not only convey the necessary information and ideas in plain English, but also make the right connections between the information and ideas for the reader. Granted, some schools of thought view the prospect of writers enabling their readers to make meaning of texts written by them as being reflective of a simplistic understanding of how individuals process information and make meaning of something that they have read, but if writing is about the “composing of texts intended to be read by people not present” (Bereiter & Scardamalia, 1987), we have to make assumptions about the reader’s process of making meaning and compose the message accordingly (p.4). I maintain, however, that such assumptions should not be random but guided not only by the writer’s understanding of the purpose for writing, the knowledge of who might be the intended reader or readers, and of the particular context within which the particular written communication is taking place, but also by a set of writing rubrics.
Analysis of vibrations in electrical machines with an optical fiber accelerometer

The vibration in induction motors is due to mechanical and electrical forces existing during the motor operation. The vibration monitoring can help to prevent wear in motors, to increase its efficiency and lowering maintenance costs. Through knowledge and accurate diagnostic procedures, it is possible to detect the cause of the vibration. This paper presents the vibration measurement analysis in the induction motor running at no-load condition using a biaxial optical fiber accelerometer. The sensor is positioned on the induction motor, and the acquired data compared with the one from a capacitive sensor. Changing the power supply frequency from 10 to 60 Hz a higher SNR was observed for both directions on the optical sensor data. The characteristics of the optical sensor, immunity to electromagnetic interference and high sensitivity, 87.848 pm.g-1 and 92.351 pm.g-1 for two directions and independent directions, favors its use for monitoring vibrations in electrical machines. The results indicate a relation between deterioration and mechanical vibration and, thus, providing the motivation for additional study and a basis for future applications.
Searching for a marker of REM sleep behavior disorder: submentalis muscle EMG amplitude analysis during sleep in patients with narcolepsy/cataplexy.

STUDY OBJECTIVES To evaluate the amplitude of submentalis muscle EMG activity during sleep in patients with narcolepsy/cataplexy with or without REM sleep behavior disorder (RBD). DESIGN Observational study with consecutive recruitment. SETTINGS Sleep laboratory. PATIENTS Thirty-four patients with narcolepsy/cataplexy and 35 age-matched normal controls. MEASUREMENTS AND RESULTS Half the patients (17 subjects) had a clinical and video polysomnographic diagnosis of RBD. The average amplitude of the rectified submentalis muscle EMG signal was used to assess muscle atonia, and the new REM sleep Atonia Index was computed. Chin muscle activations were detected and their duration and interval analyzed. REM sleep Atonia Index was lower in both patient groups (with narcolepsy patients with RBD showing the lowest values) with respect to controls, and it did not correlate with age as it did in controls. The total number of chin EMG activations was significantly higher in both patient groups than controls. No significant differences were found between the two groups of patients, although more chin EMG activations were noted in narcolepsy patients with RBD than those without. CONCLUSIONS Elevated muscle activity during REM sleep is the only polysomnographic marker of RBD. This study shows that polysomnographically evident RBD is present in many patients with narcolepsy/ cataplexy. This condition might be specific to narcolepsy/cataplexy, reflecting a peculiar form of REM sleep related motor dyscontrol (i.e., status dissociatus), paving the way to enacting dream behaviors, and correlated with the specific neurochemical and neuropathological substrate of narcolepsy/cataplexy.
Lung function and inflammatory responses in healthy young adults exposed to 0.06 ppm ozone for 6.6 hours.

RATIONALE Exposure to ozone causes a decrease in spirometric lung function and an increase in airway inflammation in healthy young adults at concentrations as low as 0.08 ppm, close to the National Ambient Air Quality Standard for ground level ozone. OBJECTIVES To test whether airway effects occur below the current ozone standard and if they are more pronounced in potentially susceptible individuals, such as those deficient in the antioxidant gene glutathione S-transferase mu 1 (GSTM1). METHODS Pulmonary function and subjective symptoms were measured in 59 healthy young adults (19-35 yr) immediately before and after exposure to 0.0 (clean air, CA) and 0.06 ppm ozone for 6.6 hours in a chamber while undergoing intermittent moderate exercise. The polymorphonuclear neutrophil (PMN) influx was measured in 24 subjects 16 to 18 hours postexposure. MEASUREMENTS AND MAIN RESULTS Subjects experienced a significantly greater (P = 0.008) change in FEV(1) (± SE) immediately after exposure to 0.06 ppm ozone compared with CA (-1.71 ± 0.50% vs. -0.002 ± 0.46%). The decrement in FVC was also greater (P = 0.02) after ozone versus CA (-2.32 ± 0.41% vs. -1.13 ± 0.34%). Similarly, changes in %PMN were greater after ozone (54.0 ± 4.6%) than CA (38.3 ± 3.7%) exposure (P < 0.001). Symptom scores were not different between ozone versus CA. There were no significant differences in changes in FEV(1), FVC, and %PMN between subjects with GSTM1-positive and GSTM1-null genotypes. CONCLUSIONS Exposure of healthy young adults to 0.06 ppm ozone for 6.6 hours causes a significant decrement of FEV(1) and an increase in neutrophilic inflammation in the airways. GSTM1 genotype alone appears to have no significant role in modifying the effects.
Oral treatment with bacteriophages reduces the concentration of Salmonella Enteritidis PT4 in caecal contents of broilers

Bacteriophages isolated from free-range chickens were tested as a therapeutic agent for reducing the concentration of Salmonella enterica serovar Enteritidis phage type 4 (S. Enteritidis PT4) in caeca of broilers. One-day-old broilers infected with S. Enteritidis PT4 by a seeder bird method were orally treated on the seventh day of age with a mixture of 1011 plaque-forming units of each of three bacteriophages. Five days after treatment the bacteriophage-treated group showed a reduction of 3.5 orders of magnitude on colony-forming units of S. Enteritidis PT4 per gram of caecal content. Samples collected at 10, 15, 20 and 25 days after treatment revealed that treated birds still had lower colony-forming units of S. Enteritidis PT4 per gram of caecal content. These data gave us compelling evidence that a mixture of bacteriophages may be efficacious in reducing S. Enteritidis PT4 concentration in broilers’ caeca and therefore reducing contamination of poultry products by this food-borne pathogen.
Robust wavelet denoising based DOA estimation with mutual coupling compensation

In this proposed work, a subspace based method of Direction of Arrival (DOA) estimation with Mutual Coupling (MC) compensation and wavelet denoising for Uniform Linear Array (ULA) is addressed. A preprocessing technique of denoising by Wavelet Transform (WT) is accomplished and followed by Mutual Coupling compensation algorithm to improve DOA estimation. A complex symmetric Toeplitz matrix is modeled and based on this matrix, mutual coupling between sensors is compensated. By denoising and mutual coupling compensation, this method accomplishes a satisfactory performance for weak signals in DOA estimation without array calibration. The effectiveness of the proposed method is studied through simulations.
Conditionality and risk for the pedestrian: modelling with the Bayesian networks

The conditional script questionnaire (CSQ) makes possible to study the conditions under which drivers find it legitimate to transgress the Highway Code. In this paper, we propose to analyse conditional respect towards the pedestrian with a new methodology based on Bayesian networks (BN). This methodology is designed to give a useful decision support tool for the analyst. Starting from data encoded in the CSQ, we use structure learning algorithms in order to build a BN. Then, we exploit it for two purposes: to extract new knowledge about the main topics expressed in the CSQ and to make inferences. This methodology helps to better understand the behaviour of drivers interacting with pedestrians and what might be the cause of their decisions of legitimate transgressions. The efficiency of the methodology proposed here is illustrated and a context-dependent ‘mapping’ of the legitimate transgressions established.
Adaptive filter design for ECG noise reduction using LMS algorithm

This paper presents the adaptive filters algorithms for removing noise from the Electrocardiogram to receive noise less pure embryo signals. Filtering ECG signals requires a filter which can automatically adapt according to changing input and noise. Adaptive filtering has been used to reduce the noise from the desired ECG signals by using LMS algorithm. Other algorithms like NLMS and RLS can also be used but LMS gives least MMSE amongst them so it can be used where accuracy is required. The measures of performance contains the optimization between the rate of convergence and MMSE by the help of MATLAB. The experimental results have shown that for small values of step size the rate of convergence increases.
Model predictive control of smart microgrids

The exploitation of renewable energy and the development of intelligent electricity network have become the main concerns worldwide. This paper aims to integrate renewable energy sources, local loads, and energy storage devices into smart microgrids. It proposes a new microgrid configuration required to realise high-performance of distributed generations and will realise innovative control techniques utilising model predictive control (MPC) to assist in coordinating the plethora of generation and load combinations, thus enable the effective exploitation of the clean renewable energy sources and provide high quality electricity for customers.
Phasic Dopamine Modifies Sensory-Driven Output of Striatal Neurons through Synaptic Plasticity

Animals are facing a complex sensory world in which only few stimuli are relevant to guide behavior. Value has to be assigned to relevant stimuli such as odors to select them over concurring information. Phasic dopamine is involved in the value assignment to stimuli in the ventral striatum. The underlying cellular mechanisms are incompletely understood. In striatal projection neurons of the ventral striatum in adult mice, we therefore examined the features and dynamics of phasic dopamine-induced synaptic plasticity and how this plasticity may modify the striatal output. Phasic dopamine is predicted to tag inputs that occur in temporal proximity. Indeed, we observed D1 receptor-dependent synaptic potentiation only when odor-like bursts and optogenetically evoked phasic dopamine release were paired within a time window of <1 s. Compatible with predictions of dynamic value assignment, the synaptic potentiation persisted after the phasic dopamine signal had ceased, but gradually reversed when odor-like bursts continued to be presented. The synaptic plasticity depended on the sensory input rate and was input specific. Importantly, synaptic plasticity amplified the firing response to a given olfactory input as the dendritic integration and the firing threshold remained unchanged during synaptic potentiation. Thus, phasic dopamine-induced synaptic plasticity can change information transfer through dynamic increases of the output of striatal projection neurons to specific sensory inputs. This plasticity may provide a neural substrate for dynamic value assignment in the striatum.
Urban Traffic Congestion Index Estimation With Open Ubiquitous Data

Traffic congestion index (i.e., TCI) is a metric for measuring urban road congestion degree. Since traffic congestion has been one of the major issues in most metropolises, it is a crucial demand to know the TCI of every road segment at every time slot. However, it is a challenging task, because the TCI sensors (e.g., road-side sensors, floating vehicles, etc.) are limited in spatial or temporal dimension, leading to sparse TCI data in the spatial-temporal space. In this paper, we propose a method for estimating the missed TCI data for any road segment at any time slot, based on the sparse TCI data reported by existing TCI sensors and a variety of open ubiquitous data. First, it extracts various urban features which have a correlation with the TCI data from the open ubiquitous data. Second, it fuses the urban features with the sparse TCI data using a collective matrix factorization algorithm, and collaboratively estimates the missed data. The advantage of our method is that it could adapt to the situation of high TCI data sparsity by incorporating external correlations from open ubiquitous data. We evaluate our method with extensive experiments based on a real-world TCI dataset and four open ubiquitous data sources. The results show the effectiveness of our method.
Influence of the Isotype of the Light Chain on the Properties of IgG1

It is widely appreciated that the isotype of the H chain of the Ab molecule influences its functional properties. We have now investigated the contribution of the isotype of the L chain to the structural and functional properties of the Ab molecule. In these studies, the L chain variable region of a murine anti-dansyl Ab was joined to either human κ or λ constant region domains and expressed with mouse-human chimeric H chains of the four human IgG isotypes. The resulting Abs were secreted as fully assembled molecules although, as has been previously observed, IgG4 with either κ or λ L chains was also secreted as HL half-molecules. However, the isotype of the L chain can influence the kinetics of intracellular assembly with IgG1λ, IgG2λ, and IgG4λ assembling more slowly than their κ counterparts. The isotype of the L chain also influenced the susceptibility of the interchain disulfide bonds to attack by reducing agents with variable effects, depending on the isotype of the H chains. For IgG2, but not for IgG1, -3, and -4, the isotype of the L chain influenced the rate of clearance in mice, with IgG2λ having a shorter in vivo half-life than IgG2κ. Only slight differences were also observed between λ and κ molecules in their kinetics of binding to and dissociation from the hapten dansyl. These studies demonstrate that the isotype of the L chain has only a slight impact on the structural and functional properties of variable region identical Abs.
The Metabolic Syndrome and Cerebrovascular Disease: Suspicion and Evidence

The metabolic syndrome (MS) is the combination of factors which, when occurring in an individual, can result in an increased risk of diabetes mellitus (DM) and of episodes of vascular disease. We present a systematic review of the diagnostic criteria, pathology, prevalence and risk of vascular disease (including stroke) associated with the MS and, if the patients have already suffered cerebral ischemia and have the MS and/or DM, the appropriate therapies from which they could benefit.
Private Education: Private Schools and Public Divisions: The Influence of Fee-Paying Education on Social Attitudes

Since 1986, support for the Conservatives has averaged 56% among privately-educated non-graduates, compared with 29% among state-educated non-graduates. Among graduates the gap is much smaller; 38% of the privately educated support the Conservatives, compared with 25% of their state-educated counterparts. 63% of the privately educated see themselves as middle or upper middle class compared with only 24% of the state educated. Even when we account for upbringing and current income and occupational status, the privately educated are nearly twice as likely as their state counterparts to describe themselves as middle class. 44% 60% State educated Privately educated See themselves as upper class 3. Private education: Upper-middle class
Transatlantic Editorial : A Comparison Between European and North American Guidelines on Myocardial Revascularization

Cardiovascular Surgery Department, University Hospital (CHU, ULg) of Li ege, Li ege, Belgium; Center for Innovation and Outcomes Research, Columbia University, New York, New York; Cardiovascular Surgery Department, University Hospital Schleswig-Holstein, Kiel, Germany; Division of Cardiothoracic Surgery, Washington University School of Medicine, St. Louis, Missouri; Department of Cardiovascular Surgery, University Heart Centre Freiburg Bad Krozingen, Bad Krozingen, Germany; and Division of Cardiac Surgery, Schulich Heart Centre, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
Large employers' new strategies in health care.

Large employers are major purchasers of health insurance and have a strong interest in maintaining the health of their employees and containing the costs of care. These efforts focus on giving employees financial incentives and data about quality to encourage them to choose lower-cost and higher-quality care. Several large employers formed a group that compiles and disseminates information about the quality of hospitals, with the goal of steering employees toward higher-quality care.
Tetranectin Levels in Patients with Acute Myocardial Infarction and Their Alterations during Thrombolytic Treatment

Tetranectin (TN), a new regulator of fibrinolysis, was studied in the plasma of 60 patients with acute myocardial infarction (AMI) and 30 healthy subjects (HS), in relation to D-dimer (DD) and α2-plasmin inhibitor (α2-PI), to investigate its possible involvement in the pathophysiology of AMI. Thirty patients underwent thrombolytic treatment with fibrin-specific plasminogen activator (rt-PA) (group A); the other 30 patients, according to the exclusion criteria, were conventionally treated (group B). Twenty of the thrombolysized patients established early recanalization (subgroup A1), while 10 failed to respond to thrombolytic treatment (subgroup A2). Median (interquartile range), baseline plasma TN levels were lower in AMI patients compared to HS [8·27 (2·75) mg/L versus 12·1 (0·55) mg/L, P <10−6]. In subgroup A1, TN increased at the end of rt-PA infusion and returned to the baseline levels 12 h later. A positive association between DD and TN release (3 h level minus baseline level) was found (r s = 0·48, P = 0·03) in subgroup A1. No significant alterations of TN levels were observed during therapy in subgroup A2 and group B. TN, DD and α2-PI concentrations in group B remained relatively constant during the study period. This study provides evidence of a significant decrease of TN levels in AMI patients compared to healthy subjects and of a remarkable difference in the evolution of TN levels during thrombolytic treatment with rt-PA between recanalized and non-recanalized AMI patients. Thus, an involvement of TN in the formation and dissolution of fibrin clot in AMI patients is worthy of further investigation.