Miracle-dz/UniFAR-FTUs huggingface dataset:
Correlation Between Forehead EEG and Sensorimotor Area EEG in Motor Imagery Task

Electrodes connection on the scalp needs to apply gel or paste on the scalp and fit EEG-cap on the head and this procedure also needs to deal with the hair on it. By comparison, to fit EEG electrodes on the forehead area is much easier because there is no hair on it. If correlations of the EEGs generated from the forehead area are high with respect to EEGs from the sensorimotor area, it is then possible to achieve relatively high classification accuracy in motor imagery tasks just using EEG from forehead channels. In this way, it will help to make the procedure of motor imagery tasks much easier and convenient. Because correlation coefficients is often used to measure the similarity of two signals, it is necessary to study whether there is a high correlation between forehead channels’ EEG and EEG from sensorimotor area during MI(Motor Imagery) tasks. In this paper, EEG data from three subjects were used in the tests. Firstly, a test was conducted on the correlation between EEGs from forehead 8(Fp1-Af8) channels and EEGs from the sensorimotor area channel C3, C4 during the MI tasks. The correlation is calculated with respect to ERP (Event-Related-Potential), Spectral Power between 6-25Hz, and ERSP (Event-Related-Spectral-Perturbation) at Alpha rhythms 8-12Hz. The results of the correlation tests are mostly above 70%. In particular, for subject Sl1, the correlation coefficient of ERSP between forehead channels and C3, C4 are as high as 0.9 during the left hand movement imagery trials. Secondly, we did a test on the classification of imagined left/right hand movement tasks using EEGs from 8 electrodes in the forehead. Classification results show that the accuracy of the forehead 8 channels’ EEGs are as high as 81% for subject Sk6 comparing to 90% using 29 channels’ EEG signal neighboring to C3, C4. For subject Sk3 and subject Sl1, the accuracies are 65% and 79% comparing to 80% and 83% using EEG signals from 29 channels neighboring to C3, C4. So there are high correlation between EEGs from the forehead area and EEGs from the sensorimotor area. That is to say, we can use EEGs from forehead in some situations, such as classification of left/right imagery, because they are much easier to measure than EEG form the sensorimotor area. This will make BCI system more portable and more convenient to use.
Bayesian Inference , Minimum Description Length Principle , and Learning by Genetic Programming

The issue of parsimony has been discussed since the birth of genetic programming [8]. While the training accuracy can be used as a single measure for fitness, many empirical studies have shown that, as programs grow, it also become less and less likely for them to be general [6, 16]. In addition, large structures require more computer resources in space and time for the evolution (14]. One approach to dealing with this problem is to define and reuse submodules [9, 14]. Another approach is to take into account of structural complexity in fitness evaluation. This paper focuses on the latter approach, although a combination of both in a single system would be ideal. We use a Bayesian inference framework to derive a class of fitness measures for dealing with _problems of parsimony based on the minimum description length (MDL) principle [13]. The MDL principle has also been used in other tree-based learning algorithms such as CART (2] and ID3 [11], in which growing and pruning phases are separated and the tree complexity is considered only in the pruning phase. This is equivalent to a strategy of "first reducing the error and then reducing the complexity." However, a direct implementation of such a strategy in the context of genetic programming is not so easy, since, in the genetic programming approach, pruning and growing are interleaved between generations and during the entire learning process. Care must be taken to prune large structures, but without too much loss of structural diversity. In the second part of the paper we describe an adaptive technique for implementing the MDL principle in the framework of genetic programming. It automatically balances the ratio of training 1 Submitted to the Twelfth International Conference on Machine Learning (ML-95) Workshop on Genetic Programming, Tahoe City, California, July 9 12, 1995.
It is Possible to Just Give Money to the Poor

Meghnad Desai of the London School of Economics recently suggested that, rather than ‘giving fifty billion dollars of overseas aid’, we should simply ‘find the poor and give them one dollar a week . That would probably do more to relieve poverty than anything else’. Two experiences in Mozambique of simply handing out money show this is possible. Payments to demobilized soldiers over a two year period and single payments to flood victims were of the order of magnitude suggested by Desai. Rural people had no difficulty cashing cheques and used the money prudently. The money stimulated the rural economy and thus had a development impact. Administrative costs were between 5 and 10 per cent, much less than in other aid projects. Using the Mozambique experience, this article concludes by suggesting that Desai’s proposed one dollar per person per week could be paid as a family grant bi-monthly, which would keep administrative costs low.
Redistribution of CB1 Cannabinoid Receptors in the Acute and Chronic Phases of Pilocarpine-Induced Epilepsy

The endocannabinoid system plays a central role in retrograde synaptic communication and may control the spread of activity in an epileptic network. Using the pilocarpine model of temporal lobe epilepsy we examined the expression pattern of the Type 1 cannabinoid receptor (CB1-R) in the hippocampi of CD1 mice at survival times of 2 hours, 1 day, 3 days and 2 months (acute, latent and chronic phases). Based on the behavioral signs of the acute seizures, animals were classified as “weakly” or “strongly” epileptic using the modified Racine scale. Mice of the weak group had mild seizures, whereas seizures in the strong group were frequent with intense motor symptoms and the majority of these animals developed sclerosis in the chronic phase. In control samples the most intense staining of CB1-R-positive fibers was found in the molecular layer of the dentate gyrus and in str. pyramidale of the cornu Ammonis. In weak animals no significant changes were seen at any survival time compared to controls. In strong animals, however, in the acute phase, a massive reduction in CB1-R-stained terminals occurred in the hippocampus. In the latent phase CB1-R immunoreactivity gradually recovered. In the chronic phase, CB1-immunostaining in sclerotic samples was stronger throughout the hippocampus. Quantitative electron microscopic analysis showed an increase in the number of CB1-R-positive terminals in the dentate gyrus. Moreover, the number of immunogold particles significantly increased in GABAergic terminals. Our results suggest a proconvulsive downregulation of CB1 receptors in the acute phase most probably due to receptor internalization, followed by compensatory upregulation and sprouting in the chronic phase of epilepsy. In conclusion, the changes in CB1 receptor expression pattern revealed in this study are associated with the severity of hippocampal injury initiated by acute seizures that ultimately leads to sclerosis in the vulnerable regions in the chronic phase.
Methodologies for continuous activity classification of user through wearable devices: Feasibility and preliminary investigation

Nowadays, the possibility to use wearable devices at low-cost and with high measuring capabilities is widely spread. They are able to collect multiple physiological and physical quantities, but the information provided is generally of "low level" (series of raw data) for the end-user, caregiver or the medical staff. A smart processing and an intelligent combination of these data may lead to the identification of more refined indicators (e.g. the kind of activity performed by the user) and so easier to understand information. In this work, the authors have performed a preliminary investigation on how to discriminate different levels of physical activity (resting, walking, running) conducted by a user. The analysis has been carried out with different trials and the use of a commercial wearable sensor (BioHarness 3.0), which measures five physiological and physical quantities. Different approaches, based on classification and clustering techniques, have been tested to prove their ability in discriminating the tasks performed. Results show that a threshold-based approach, applied to the physical quantities measured, is able to identify the activities conducted by the user, with an average accuracy of 98%. Moreover, a novel indicator based on the combination of both physiological and physical quantities is proposed and discussed in the paper. The integration of physiological data (e.g. Heart Rate) could lead to more "high level" information, which should be better investigated in future works.
Exploring the relationship between participation in a structured sports program and development of gross motor skills in children ages 3 to 6 years

ABSTRACT This study looked at the relationship between participation in a structured sports program and gross-motor-skills development in children aged 3 to 6 years. Twenty-seven children participated in the study, with 16 children receiving an eight-week sports program intervention. Children were assessed at pre- and postintervention using a modified version of the Peabody Developmental Motor Scales, called the Sportball Assessment of Gross Motor Development. The two groups were comparable at baseline, but significant differences were found at posttest with increases in gross-motor scores within the experimental group. Findings from this study add to the body of evidence that can inform development of programming for promoting childhood gross-motor skills.
Hybrid of HMM and Fuzzy Logic for handwritten character recognition

This paper presents a hybrid approach of HMM and Fuzzy Logic in the field of handwritten character recognition. Fuzzy Logic is used in the recognition phase while HMM is used in the process of extracting features for the preparation of linguistic variables of the fuzzy rules. Experimental results from a few sample images give a reasonable recognition rate on a more challenging database of lower-case handwritten characters. This proved the proposed hybrid of the two techniques are compatible and can be used to complement each other effectively.
EXISTING TRENDS IN INTRUSION DETECTION - A COMPARATIVE ANALYSIS

One of the recent advances throughout this decade has been the evolution of various intrusion detection modes and the way they are used. Since a lot of work has already been done and there is still much more to do, we are focusing here on what we have currently in this area, particularly the techniques and a comparative study to highlight the prominent features to provide support for computer network security. This review paper is based upon the currently existing trends in the relevant context.
Design of unmanned vehicle advanced braking system using smart motor

Active safety systems have been gradually introduced by more car manufacturers, to wider portions of the automotive market. Many of these systems shared hardware and are integrated with other systems that do not involve automated emergency braking, such as adaptive cruise control, forward collision warning and predictive brake assist systems [1]. But in fact, there are many times when we have to face the emergency brake. So it is also necessary to design a high performance braking system. And there are a lot of issue on our unmanned vehicle deceleration controller too. In this paper we focus design of autonomous vehicle advanced braking system using DC smart servo motor torque controller. Vehicle longitudinal control model is established in Labview2012. By the real time experiments on Grandeur HG 330 made in Hyundai Motor Group Co. Ltd.
I. Identification of Trends in Transitory Variances

Trends in the Transitory Variance of Male Earnings in the U.S., 1970-2004 We estimate the trend in the transitory variance of male earnings in the U.S. using the Michigan Panel Study of Income Dynamics from 1970 to 2004. Using both an error components model as well as simpler but only approximate methods, we find that the transitory variance started to increase in the early 1970s, continued to increase through the mid-1980s, and then remained at this new higher level through the 1990s and beyond. Thus the increase mostly occurred about thirty years ago. Its increase accounts for between 31 and 49 percent of the total rise in cross-sectional variance, depending on the time period.
Applying Extreme Programming in Object Oriented Programming Lessons in Classroom

When programming in classroom in programming courses students tend to write schoolboy or schoolgirl code i.e. the products of their work have very little resemblance to products in workplaces. The assignments of their programs are first coded, then tested vaguely and superficially and finally discarded. Reliability of software is disregarded. However, after having been graduated these fellows should code reliable software to real customers. Extreme programming could not only be used in assessing the quality of students’ work but that it’s use would also assist those students who appeared to have difficulty both in mastering the proper coding methods and then adhering to them. The purpose of this study was gaining experience of extreme programming in an unbiased fashion, without having to come up with any preordained results being on the side of XP or against it. A case study of one of the cornerstones of extreme programming, pair-programming, was made.
Effects of Pseudomonas fluorescens on the Water Parameters of Mycorrhizal and Non-Mycorrhizal Seedlings of Pinus halepensis

Abstract: Inoculation of forest seedlings with mycorrhizal fungi and rhizobacteria can improve the morphological and physiological qualities of plants, especially those used for regeneration of arid areas. In this paper, under standard nursery conditions, Aleppo pine seedlings were inoculated with Pseudomonas fluorescens CECT 5281 rhizobacteria. Some of these seedlings were also inoculated with the ectomycorrhizal fungus Pisolithus tinctorius . Five months after the inoculations, we examined the growth, water parameters (osmotic potential at full turgor [Ψπfull], osmotic potential at zero turgor [Ψπ0], and the tissue modulus of elasticity near full turgor [E max ]), mycorrhizal colonisation, and concentration of macronutrients (N, P, K, Ca and Mg) in the seedlings. Subsequently, a trial was conducted to assess the root growth potential. P. fluorescens CECT 5281 decreased the cellular osmotic potential of P. halepensis seedlings but increased its elasticity.
SEED: a framework for extracting social events from press news

Everyday people are exchanging a huge amount of data through the Internet. Mostly, such data consist of unstructured texts, which often contain references to structured information (e.g., person names, contact records, etc.). In this work, we propose a novel solution to discover social events from actual press news edited by humans. Concretely, our method is divided in two steps, each one addressing a specific Information Extraction (IE) task: first, we use a technique to automatically recognize four classes of named-entities from press news: DATE, LOCATION, PLACE, and ARTIST. Furthermore, we detect social events by extracting ternary relations between such entities, also exploiting evidence from external sources (i.e., the Web). Finally, we evaluate both stages of our proposed solution on a real-world dataset. Experimental results highlight the quality of our first-step Named-Entity Recognition (NER) approach, which indeed performs consistently with state-of-the-art solutions. Eventually, we show how to precisely select true events from the list of all candidate events (i.e., all the ternary relations), which result from our second-step Relation Extraction (RE) method. Indeed, we discover that true social events can be detected if enough evidence of those is found in the result list of Web search engines.
Robust architecture for autonomous coherent optical receivers

We propose a new architecture for coherent intradyne optical receivers that autonomously identifies and decodes OOK, BPSK, QPSK, and 16-QAM modulation formats. The architecture robustly determines the total accumulated chromatic dispersion, the symbol rate that is not tightly constrained, the number of distinct modulated polarizations, and the modulation format using higher-order statistics of the sampled signal. Thus, unknown signals from noncooperating transmitters, including legacy transmitters, can be optimally demodulated yielding minimum BER. Experimental single-channel signals transmitted through 1056 km of large-area fiber are demodulated with the new autonomous receiver with essentially identical performance compared to receivers with prior knowledge of the modulation format.
Leveraging emotion detection using emotions from yes-no answers

We present a new approach for the detection of negative versus non-negative emotions from Human-computer dialogs in the specific domain of call centers. We argue that it is possible to improve emotion detection without using additional information being linguistic or contextual. We show that no-answers are emotional salient words and that it is possible to improve the accuracy of the classification of Human-computer dialogs by taking advantage of the high accuracy achieved on no-answer turns. We also show that stacked generalization using neural networks and SVM as base models improves the accuracy of each model while the combination of the no-model and the dialog model improves the accuracy of the dialog-model alone by 13%.
Pharmaceutical market access in emerging markets: concepts, components, and future

This article intends to consolidate the concepts of pharmaceutical market access and highlight its growing importance in emerging markets. Market access has gained considerable attention worldwide as countries try to contain their escalating healthcare expenditures amidst the global economic slowdown. This has resulted in governments adopting stricter measures for new product approval. Thus, pharmaceutical companies are finding it increasingly difficult to successfully address the specific challenges posed by various government and regulatory agencies and stakeholders. There is an increasing need to establish market access functions, especially in emerging markets, where the complex, dynamic healthcare landscape confounds product approval and uptake. Moreover, emerging markets are the engines of growth today, and, thus, performing in these markets is critical for the majority of pharmaceutical companies. To address the challenges posed by regulatory agencies and diverse stakeholders, a customized market access strategy is the need of the hour. A market access framework with specific tools and tactics will help companies to plan, implement, and monitor stakeholder engagement activities.
Molecular Cloning, Characterization, and Functional Analysis of Acetyl-CoA C-Acetyltransferase and Mevalonate Kinase Genes Involved in Terpene Trilactone Biosynthesis from Ginkgo biloba

Ginkgolides and bilobalide, collectively termed terpene trilactones (TTLs), are terpenoids that form the main active substance of Ginkgo biloba. Terpenoids in the mevalonate (MVA) biosynthetic pathway include acetyl-CoA C-acetyltransferase (AACT) and mevalonate kinase (MVK) as core enzymes. In this study, two full-length (cDNAs) encoding AACT (GbAACT, GenBank Accession No. KX904942) and MVK (GbMVK, GenBank Accession No. KX904944) were cloned from G. biloba. The deduced GbAACT and GbMVK proteins contain 404 and 396 amino acids with the corresponding open-reading frame (ORF) sizes of 1215 bp and 1194 bp, respectively. Tissue expression pattern analysis revealed that GbAACT was highly expressed in ginkgo fruits and leaves, and GbMVK was highly expressed in leaves and roots. The functional complementation of GbAACT in AACT-deficient Saccharomyces cerevisiae strain Δerg10 and GbMVK in MVK-deficient strain Δerg12 confirmed that GbAACT mediated the conversion of mevalonate acetyl-CoA to acetoacetyl-CoA and GbMVK mediated the conversion of mevalonate to mevalonate phosphate. This observation indicated that GbAACT and GbMVK are functional genes in the cytosolic mevalonate (MVA) biosynthesis pathway. After G. biloba seedlings were treated with methyl jasmonate and salicylic acid, the expression levels of GbAACT and GbMVK increased, and TTL production was enhanced. The cloning, characterization, expression and functional analysis of GbAACT and GbMVK will be helpful to understand more about the role of these two genes involved in TTL biosynthesis.
Incidence and Prevalence of Musculoskeletal Injury in Ballet

Background Most published studies on injuries in the ballet dancer focus on the lower extremity. The rigors of this activity require special training and care. By understanding prevalence and injury pattern to the musculoskeletal system, targeted prevention and treatment for this population can be developed. Purpose To determine the incidence and prevalence of musculoskeletal injuries in ballet. Study Design Systematic review; Level of evidence, 4. Methods A systematic review registered with PROSPERO was performed using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Level 1 through 4 evidence studies reporting incidence of musculoskeletal injuries in male and female ballet dancers were included, with the numbers and types of injuries extracted from each. Injury rates were recorded and calculated based on professional status, sex, and nature of injury. Incidence was defined as number of injuries sustained over a specific time. Prevalence was defined as proportion of subjects with an injury at a given point in time. Results The studies analyzed reported injury incidence or prevalence in more than 1365 amateur and 900 professional dancers. The mean age was 16.2 years among amateur and 27.0 years among professional dancers. The incidence of injury among amateur dancers was 0.99 and 1.09 injuries per 1000 dance hours in males and females, respectively; 75% of injuries were overuse, with similar rates among males and females. In professional dancers, the incidence of injury was 1.06 and 1.46 injuries per 1000 dance hours in males and females, respectively, and 64% of female injuries were overuse, compared with 50% in males (P < .001). Only 3 studies provided prevalence data, including 62% prevalence of lumbosacral pain, 58% painful snapping hip, and 29% patellofemoral pain. Lower extremity injuries comprised 66% to 91% of all injuries, with the foot and ankle accounting for 14% to 57%. Conclusion The overall incidence of injury among amateur and professional ballet dancers is 0.97 and 1.24 injuries per 1000 dance hours, respectively. The majority are overuse in both amateur and professional dancers, with amateur ballet dancers showing a higher proportion of overuse injuries than professionals (P < .001). Male professional dancers show a higher proportion of traumatic injuries, accounting for half of their injuries (P < .001).
Architecture-Based Assessment and Planning of Software Changes in Information and Automated Production Systems State of the Art and Open Issues

Information and automated production systems are long-living, evolvable systems. Consequently, modifications are performed to correct, improve or adapt the respective system. We introduce different approaches to analyze maintainability of software-intensive systems and propose two different case studies from the information and from the automated production systems domain as a basis to validate approaches on system evolution.