Miracle-dz/UniFAR-FTUs huggingface dataset:
Cerebrospinal Fluid Analyses in Migraine Patients and Controls

To investigate the role of central neurotransmitters in the pathogenesis of migraine, we measured cerebrospinal fluid (CSF) levels of certain amino acids (glycine, taurine, glutamine) and metabolites of biogenic amines (5-hydroxyindoleacetic acid and homovanillic acid) in 38 migraine patients and compared them with the levels from 10 headache-free controls. The levels of taurine, glycine and glutamine were significantly higher in the migraine patients (p < 0.0001 for taurine and glycine; p < 0.0009 for glutamine); there were no significant differences among the three migraine subgroups (infrequent migraine, frequent migraine and transformed migraine). In seven patients subsequently treated with divalproex sodium, CSF taurine levels decreased significantly from pretreatment baseline values. These data support the concept that migraine is at least in part a disorder of central neurotransmission.
Short Term Electric Load Forecasting of 132/33KV Maiduguri Transmission Substation using Adaptive Neuro-Fuzzy Inference System (ANFIS)

article provides a way of accurately predicting one-hour- ahead load of a utility company located in the North Eastern region of Nigeria based on Adaptive Neuro-Fuzzy Inference System (ANFIS). The inputs to the ANFIS are the next-hour temperature, next-hour humidity, day of the week, hour of the day, and the current-hour load. The output is the next-hour load of the entire system. All the data used span the period 2009 to 2012 (4 years). These parameters are non-linear, stochastic (random) and uncertain in nature. Adaptive Neuro- fuzzy based Inference System (ANFIS), an integrated system, comprising of fuzzy logic and Neural Network was used to model the next hour load, because it can address and solve problems related to non-linearity, randomness and uncertainty of data. 75% of the data was used for training and 25% for checking. From the analysis carried out on the ANFIS-based model; Mean absolute percentage error (MAPE) for a typical Monday, Wednesday and Friday was found to be 12.61%, 12.76% and 12.12%. The Mean absolute error (MAPE) on the entire test data was 24.76%. The analysis shows satisfactory level of accuracy with regards to the ANFIS-based model developed in forecasting the next hour load especially with a correlation (r) value of 84.64%.
Stability of Carbon Nanoonion C20@C60@C240: Molecular Dynamics Simulations

The structural stability of carbon nanoonion C20@C60@C240 has been investigated by performing molecular dynamics computer simulations. Calculations have been realized by using an empirical many-body potential energy function for carbon. It has been found that carbon nanoonion is not so resistive against heat treatment, nor is it as strong as isolated single carbon nanoballs. Although single nanoballs resist heat treatment up to 4300 K, nanoonion disintegrates after 2600 K.
Two-variable first order logic with modular predicates over words

We consider first order formulae over the signature consisting of the symbols of the alphabet, the symbol < (interpreted as a linear order) and the set MOD of modular numerical predicates. We study the expressive power of FO^2[<,MOD], the two-variable first order logic over this signature, interpreted over finite words. We give an algebraic characterization of the corresponding regular languages in terms of their syntactic morphisms and we also give simple unambiguous regular expressions for them. It follows that one can decide whether a given regular language is captured by FO^2[<,MOD]. Our proofs rely on a combination of arguments from semigroup theory (stamps), model theory (Ehrenfeucht-Fraisse games) and combinatorics.
Parser for protein folding units

General patterns of protein structural organization have emerged from studies of hundreds of structures elucidated by X‐ray crystallography and nuclear magnetic resonance. Structural units are commonly identified by visual inspection of molecular models using qualitative criteria. Here, we propose an algorithm for identification of structural units by objective, quantitative criteria based on atomic interactions. The underlying physical concept is maximal interactions within each unit and minimal interaction between units (domains). In a simple harmonic approximation, interdomain dynamics is determined by the strength of the interface and the distribution of masses. The most likely domain decomposition involves units with the most correlated motion, or largest interdomain fluctuation time. The decomposition of a convoluted 3‐D structure is complicated by the possibility that the chain can cross over several times between units. Grouping the residues by solving an eigenvalue problem for the contact matrix reduces the problem to a one‐dimensional search for all reasonable trial bisections. Recursive bisection yields a tree of putative folding units. Simple physical criteria are used to identify units that could exist by themselves. The units so defined closely correspond to crystallographers' notion of structural domains. The results are useful for the analysis of folding principles, for modular protein design and for protein engineering. © 1994 Wiley‐Liss, Inc.
The Molecular Basis of Lecithin:Cholesterol Acyltransferase Deficiency Syndromes: A Comprehensive Study of Molecular and Biochemical Findings in 13 Unrelated Italian Families

Objective—To better understand the role of lecithin:cholesterol acyltransferase (LCAT) in lipoprotein metabolism through the genetic and biochemical characterization of families carrying mutations in the LCAT gene. Methods and Results—Thirteen families carrying 17 different mutations in the LCAT gene were identified by Lipid Clinics and Departments of Nephrology throughout Italy. DNA analysis of 82 family members identified 15 carriers of 2 mutant LCAT alleles, 11 with familial LCAT deficiency (FLD) and 4 with fish-eye disease (FED). Forty-four individuals carried 1 mutant LCAT allele, and 23 had a normal genotype. Plasma unesterified cholesterol, unesterified/total cholesterol ratio, triglycerides, very-low-density lipoprotein cholesterol, and pre-&bgr; high-density lipoprotein (LDL) were elevated, and high-density lipoprotein (HDL) cholesterol, apolipoprotein A-I, apolipoprotein A-II, apolipoprotein B, LpA-I, LpA-I:A-II, cholesterol esterification rate, LCAT activity and concentration, and LDL and HDL3 particle size were reduced in a gene–dose-dependent manner in carriers of mutant LCAT alleles. No differences were found in the lipid/lipoprotein profile of FLD and FED cases, except for higher plasma unesterified cholesterol and unesterified/total cholesterol ratio in the former. Conclusion—In a large series of subjects carrying mutations in the LCAT gene, the inheritance of a mutated LCAT genotype causes a gene–dose-dependent alteration in the plasma lipid/lipoprotein profile, which is remarkably similar between subjects classified as FLD or FED.
A Heart and A Mind: Self-distancing Facilitates the Association Between Heart Rate Variability, and Wise Reasoning

Cardiac vagal tone (indexed via resting heart rate variability [HRV]) has been previously associated with superior executive functioning. Is HRV related to wiser reasoning and less biased judgments? Here we hypothesize that this will be the case when adopting a self-distanced (as opposed to a self-immersed) perspective, with self-distancing enabling individuals with higher HRV to overcome bias-promoting egocentric impulses and to reason wisely. However, higher HRV may not be associated with greater wisdom when adopting a self-immersed perspective. Participants were randomly assigned to reflect on societal issues from a self-distanced- or self-immersed perspective, with responses coded for reasoning quality. In a separate task, participants read about and evaluated a person performing morally ambiguous actions, with responses coded for dispositional vs. situational attributions. We simultaneously assessed resting cardiac recordings, obtaining six HRV indicators. As hypothesized, in the self-distanced condition, each HRV indicator was positively related to prevalence of wisdom-related reasoning (e.g., prevalence of recognition of limits of one’s knowledge, recognition that the world is in flux/change, consideration of others’ opinions and search for an integration of these opinions) and to balanced vs. biased attributions (recognition of situational and dispositional factors vs. focus on dispositional factors alone). In contrast, there was no relationship between these variables in the self-immersed condition. We discuss implications for research on psychophysiology, cognition, and wisdom.
Low power logic synthesis for XOR based circuits

An abundance of research efforts in low power logic synthesis have so far been focused on AND/OR or NAND/NOR based logic. A typical approach is to first generate an initial multi level AND/OR or NAND/NOR representation of a Boolean function. Next, the representation, is optimized in terms of power. However, there are major classes of circuits such as arithmetic functions which have sizable AND/OR representations but have very compact AND/XOR representations. For these functions, the AND/OR based optimization approach often yields poor results. We propose a paradigm for low power logic synthesis based on AND/XOR representations of Boolean functions. Specifically, we propose transforming a Boolean function into a Fixed Polarity Reed Muller form that allows us to efficiently synthesize XOR trees and AND trees with provably minimum switching activity. Preliminary experimental results show that we attain good power savings with negligible area overhead and often area reduction when compared to conventional AND/XOR based synthesis methods and the Berkeley SIS system.
Ieee Transactions on Evolutionary Computation Reusing Building Blocks of Extracted Knowledge to Solve Complex, Large-scale Boolean Problems

—Evolutionary computation techniques have had limited capabilities in solving large-scale problems due to the large search space demanding large memory and much longer training times. In the work presented here, a genetic programming like rich encoding scheme has been constructed to identify building blocks of knowledge in a learning classifier system. The fitter building blocks from the learning system trained against smaller problems have been utilized in a higher complexity problem in the domain in order to achieve scalable learning. The proposed system has been examined and evaluated on four different Boolean problem domains, i.e. multiplexer, majority-on, carry, and even-parity problems. The major contribution of this work is to successfully extract useful building blocks from smaller problems and reuse them to learn more complex, large-scale problems in the domain, e.g. 135-bits multiplexer problem, where the number of possible instances is 2 135 ≈ 4 × 10 40 , is solved by reusing the extracted knowledge from the learnt lower level solutions in the domain. Autonomous scaling is, for the first time, shown to be possible in learning classifier systems. It improves effectiveness and reduces the number of training instances required in large problems, but requires more time due to its sequential build-up of knowledge.
Lipid Screening and Cardiovascular Health in Childhood

This clinical report replaces the 1998 policy statement from the American Academy of Pediatrics on cholesterol in childhood, which has been retired. This report has taken on new urgency given the current epidemic of childhood obesity with the subsequent increasing risk of type 2 diabetes mellitus, hypertension, and cardiovascular disease in older children and adults. The approach to screening children and adolescents with a fasting lipid profile remains a targeted approach. Overweight children belong to a special risk category of children and are in need of cholesterol screening regardless of family history or other risk factors. This report reemphasizes the need for prevention of cardiovascular disease by following Dietary Guidelines for Americans and increasing physical activity and also includes a review of the pharmacologic agents and indications for treating dyslipidemia in children.
Inhibition of endothelial Cdk5 reduces tumor growth by promoting non-productive angiogenesis

Therapeutic success of VEGF-based anti-angiogenic tumor therapy is limited due to resistance. Thus, new strategies for anti-angiogenic cancer therapy based on novel targets are urgently required. Our previous in vitro work suggested that small molecule Cdk5 inhibitors affect angiogenic processes such as endothelial migration and proliferation. Moreover, we recently uncovered a substantial role of Cdk5 in the development of lymphatic vessels. Here we pin down the in vivo impact of endothelial Cdk5 inhibition in angiogenesis and elucidate the underlying mechanism in order to judge the potential of Cdk5 as a novel anti-angiogenic and anti-cancer target. By the use of endothelial-specific Cdk5 knockout mouse models and various endothelial and tumor cell based assays including human tumor xenograft models, we show that endothelial-specific knockdown of Cdk5 results in excessive but non-productive angiogenesis during development but also in tumors, which subsequently leads to inhibition of tumor growth. As Cdk5 inhibition disrupted Notch function by reducing the generation of the active Notch intracellular domain (NICD) and Cdk5 modulates Notch-dependent endothelial cell proliferation and sprouting, we propose that the Dll4/Notch driven angiogenic signaling hub is an important and promising mechanistic target of Cdk5. In fact, Cdk5 inhibition can sensitize tumors to conventional anti-angiogenic treatment as shown in tumor xenograft models. In summary our data set the stage for Cdk5 as a drugable target to inhibit Notch-driven angiogenesis condensing the view that Cdk5 is a promising target for cancer therapy.
Pedal Timing and Tempo in Expressive Piano Performance: A Preliminary Investigation

The timing of pedal depressions and releases was measured relative to key depressions and releases in two pianists' performances of Robert Schumann's Tr-dutnerei on an electronic instrument. Each pianist provided nine complete performances, three at each of three tempi, which were analysed by examining in detail those positions in the music in which the pedal was used consistently. The principal questions were whether and how pedal timing adjusts to changes in global tempo (across performances) and in local tempo (within performnances): Do pedal-release times, onset times, or change (onset minus release) times exhibit absolute orrelative invariance across either or both of these tempo changes? The results do not suggest any simple answer, since neither type of invariance was observed consistently. Pedal timing emerges as having a complex pattern that is sensitive to local and global tempo changes in varying degrees, yet exhibits consistency across repeated performances by the same pianist. There were striking differences in pedal timing between the two pianists, who differed in level of skill.
Parenteral Nutrition in the Very-Low-BirthWeight Infant

In preterm infants an optimal nutritional supply must be provided early during the neonatal period. Indeed, undernutrition leads to growth retardation which may be hazardous for brain development (18). Growth rate is maximum during the last trimester of gestation and corresponds to about 60 cm/year (19). Therefore, contrary to young children, preterm infants after an arrest of growth, whatever the cause, cannot achieve a complete return to normal growth. This fact is clearly illustrated by the follow-up of very-small-for-gestational age infants in spite of a high protein, mineral, and energy intake. Oral nutrition alone cannot maintain adequate growth in very-low-birth-weight (VLBW) infants because of their poor clinical condition and the immaturity of their gastrointestinal tract. Total or supplemental parenteral nutrition has been shown to improve the neonatal growth of VLBW infants by enhancing their caloric and nitrogen supply (4,24). In this chapter, we shall present some guidelines about nitrogen, amino acid, energy, and mineral intakes for infants on total parenteral nutrition (TPN).
A New Stochastic Model for the Boundary Layer Clouds and Stratocumulus Phase Transition Regimes: Open Cells, Closed Cells, and Convective Rolls

Adequate forecasting, nowcasting, and parameterization of fog and low clouds is still challenging despite being the focus of intensive research for a long time. Stratocumulus clouds have the ability to self‐organize into a variety of topological structures, including closed and open convection cells, convection rolls, and scattered cumulus. A lot is known about the large‐scale conditions in which shallow clouds and fog develop and decay. However, because of the various complex interactions with the environment, transitions between these various cloud regimes are hard to capture in numerical models. Recent work viewed these cloud regimes as the equilibrium states of phase transition in a stochastic model. Here we build on this idea to propose a new stochastic model based on the lattice particles‐Ising model of statistical mechanics, bringing in important improvements by allowing, for example, multiple equilibria and for direct feedback onto the large‐scale dynamics. Idealized numerical simulations demonstrate that the new model reproduces qualitatively the observed regimes of stratocumulus when the external forcing is varied. The new model forms a metastable dynamical system where transitions between extreme regimes occur dynamically, that is, within the same numerical simulation, for a large range of fixed parameter values, and sometimes lead to the co‐occurrence of mixed states with pockets of closed cells and open cells intercepted by regions of scattered cloudiness, resembling the emergence of convection rolls in nature. This is believed to be a step forward in improving the parameterization of shallow clouds in climate models.
Relative validation of the dietary intake of fatty acids among adults in the Swedish National Dietary Survey using plasma phospholipid fatty acid composition

Abstract The aims of a national dietary study are several-fold. One purpose is to monitor the intake of foods and nutrients in the population and to compare intakes with dietary recommendations. It is, however, difficult to measure dietary fat intake and plasma biomarker fatty acid (FA) composition may be used as an objective measure of dietary fat intake. Thus, the relative ability of a diet record to capture habitual fat intake was validated against biomarker FA. Dietary fat intake was measured in a novel self-assisted web-based 4-d food record – the ‘Riksmaten’ method. Spearman rank correlations between dietary FA, certain food groups (fish-shellfish, dairy products, meat and sausages, and spreads) and the fat content of these food groups and biomarker FA were explored. Participants were 150 women and 129 men, aged 18–80 years, who took part in the Swedish National Dietary Survey, Riksmaten adults 2010–11. Blood samples were collected on average 20 d after the diet record and FA composition was measured in plasma phospholipids by GLC. Total n-3 FA (r 0·31), EPA (r 0·34) and DHA (r 0·42) were correlated between plasma and diet (all P ≤ 0·001). Adjustment for covariates attenuated the relationships. Linoleic acid was only marginally correlated (r 0·15; P = 0·06) in women. Plasma pentadecaenoic acid and heptadecaenoic acid were correlated with dairy product intake as previously reported. In conclusion, the Riksmaten method appears valid for the purpose of collecting data on dietary fat composition, at least in a healthy adult population.
Towards Efficient Electric Vehicle Charging Using VANET-Based Information Dissemination

The design of an efficient charging management system for on-the-move Electric Vehicles (EVs) has become an emerging research problem, in future connected vehicle applications given their mobility uncertainties. Major technical challenges here involve decision-making intelligence for the selection of Charging Stations (CSs), as well as the corresponding communication infrastructure for necessary information dissemination between the power grid and mobile EVs. In this article, we propose a holistic solution that aims to create high impact on the improvement of end users’ driving experiences (e.g., to minimize EVs’ charging waiting time during their journeys) and charging efficiency at the power grid side. Particularly, the CS-selection decision on where to charge is made by individual EVs for privacy and scalability benefits. The communication framework is based on a mobile Publish/Subscribe (P/S) paradigm to efficiently disseminate CSs condition information to EVs on-the-move. In order to circumvent the rigidity of having stationary Road Side Units (RSUs) for information dissemination, we promote the concept of Mobility as a Service (MaaS) by exploiting the mobility of public transportation vehicles (e.g. buses) to bridge the information flow to EVs, given their opportunistic encounters. We analyze various factors affecting the possibility for EVs to access CSs information via opportunistic Vehicle-to-Vehicle (V2V) communications, and also demonstrate the advantage of introducing buses as mobile intermediaries for information dissemination, based on a common EV charging management system under the Helsinki city scenario. We further study the feasibility and benefit of enabling EVs to send their charging reservations involved for CS-selection logic, via opportunistically encountered buses as well. Results show this advanced management system improves both performances at CS and EV sides.
Fast Chirplet Transform to Enhance CNN Machine Listening - Validation on Animal calls and Speech

The scattering framework offers an optimal hierarchical convolutional decomposition according to its kernels. Convolutional Neural Net (CNN) can be seen asan optimal kernel decomposition, nevertheless it requires large amount of trainingdata to learn its kernels. We propose a trade-off between these two approaches: a Chirplet kernel as an efficient Q constant bioacoustic representation to pretrainCNN. First we motivate Chirplet bioinspired auditory representation. Second we give the first algorithm (and code) of a Fast Chirplet Transform (FCT). Third, we demonstrate the computation efficiency of FCT on large environmental data base: months of Orca recordings, and 1000 Birds species from the LifeClef challenge. Fourth, we validate FCT on the vowels subset of the Speech TIMIT dataset. The results show that FCT accelerates CNN when it pretrains low level layers: it reduces training duration by -28% for birds classification, and by -26% for vowels classification. Scores are also enhanced by FCT pretraining, with a relative gain of +7.8% of Mean Average Precision on birds, and +2.3% of vowel accuracy against raw audio CNN. We conclude on perspectives on tonotopic FCT deep machine listening, and inter-species bioacoustic transfer learning to generalise the representation of animal communication systems.