Miracle-dz/UniFAR-FTUs huggingface dataset:
Bifurcations in Class 1 neuron models interconnected by inhibitory and electrical synapses

Electrical coupling has been discovered extensively between FS neurons in the neocortex. They are also coupled by bi-directional or uni-directional inhibitory synapses. However, the relationship between collective activity in interneuronal circuits and different functions of their coupling have not been revealed perfectly. To clarify the above problem, we investigate bifurcation phenomena in coupled neuron models and spatio-temporal dynamics in large scale network, which consist of two-dimensional Hindmarsh-Rose type models connected by gap junction and inhibitory synapses. As a result, we show inand anti-phase solutions and complex behavior in coupled neurons. By the interaction between electrical and inhibitory synapses, moreover, spatio-temporal complex behavior occurs in large scale network.
Differential expression of several xyloglucan endotransglucosylase/hydrolase genes regulates flower opening and petal abscission in roses

The movement of petals during flower opening (anthesis) and their separation from the parent plant during abscission requires cell wall modification at the junction (abscission zone) of the petal and thalamus. The present study shows differential ethylene mediated temporal regulation of various members of the rose XTH gene family during flower opening and abscission in the ethylene sensitive, early abscising fragrant rose and the less sensitive late abscising hybrid rose. These studies indicate that large scale changes in xyloglucan crosslinking in cell wall mediated by XTHs may facilitate movement and separation during flower opening and abscission respectively.
Status and Prospects for Combined GPS LOD and VLBI UT1 Measurements

Status and Prospects for Combined GPS LOD and VLBI UT1 Measurements A Kalman filter was developed to combine VLBI estimates of UT1-TAI with biased length of day (LOD) estimates from GPS. The VLBI results are the analyses of the NASA Goddard Space Flight Center group from 24-hr multi-station observing sessions several times per week and the nearly daily 1-hr single-baseline sessions. Daily GPS LOD estimates from the International GNSS Service (IGS) are combined with the VLBI UT1-TAI by modeling the natural excitation of LOD as the integral of a white noise process (i.e., as a random walk) and the UT1 variations as the integration of LOD, similar to the method described by Morabito et al. (1988). To account for GPS technique errors, which express themselves mostly as temporally correlated biases in the LOD measurements, a Gauss-Markov model has been added to assimilate the IGS data, together with a fortnightly sinusoidal term to capture errors in the IGS treatments of tidal effects. Evaluated against independent atmospheric and oceanic axial angular momentum (AAM + OAM) excitations and compared to other UT1/LOD combinations, ours performs best overall in terms of lowest RMS residual and highest correlation with (AAM + OAM) over sliding intervals down to 3 d. The IERS 05C04 and Bulletin A combinations show strong high-frequency smoothing and other problems. Until modified, the JPL SPACE series suffered in the high frequencies from not including any GPS-based LODs. We find, surprisingly, that further improvements are possible in the Kalman filter combination by selective rejection of some VLBI data. The best combined results are obtained by excluding all the 1-hr single-baseline UT1 data as well as those 24-hr UT1 measurements with formal errors greater than 5 μs (about 18% of the multi-baseline sessions). A rescaling of the VLBI formal errors, rather than rejection, was not an effective strategy. These results suggest that the UT1 errors of the 1-hr and weaker 24-hr VLBI sessions are non-Gaussian and more heterogeneous than expected, possibly due to the diversity of observing geometries used, other neglected systematic effects, or to the much shorter observational averaging interval of the single-baseline sessions. UT1 prediction services could benefit from better handling of VLBI inputs together with proper assimilation of IGS LOD products, including using the Ultra-rapid series that is updated four times daily with 15 hr delay.
The Culebra Algorithm for Path Planning and Obstacle Avoidance in Kat-5

Kat-5 was the fourth vehicle to successfully finish the DARPA 2005 Grand Challenge; the first time ever that autonomous vehicles were able to successfully complete such a task. In this paper, we describe the methods that were used to develop the vehicle's path planning and obstacle avoidance algorithms, which allowed Kat-5 to successfully navigate completely autonomously the 132 miles course over rough and previously unrehearsed and unknown terrain at relatively high speeds
A novel method of CT brain images segmentation

In this paper, an algorithm is developed for anatomical structures segmentation based on CT head images. The segmented structure can be used for image guide surgery navigations. In our method, intensity rescaling, the threshold algorithm, region growing method, fast-marching method (FMM) and mathematical morphology are combined and used systematically. Due to the low contrast of the CT images, intensity rescaling is applied to the images to enhance the contrast. Threshold algorithm is used to extract the intracranial area from the enhanced images. Then, FMM is adopted to segment the intracranial images of brain matter and cerebrospinal fluid (CSF). Mathematical morphology is used to correct the pre-calculated images and obtain accurate brain matter and CSF segmentations. The system has been tested with a number of real CT head images and has achieved some promising results.
Common randomness amplification: A constructive view

Common randomness is an important resource in many areas such as game theory and cryptography. We discuss the general problem of common randomness amplification between two distrustful parties connected by a communication channel and sharing some initial randomness. In this setting, both parties wish to agree on a common value distributed according to a target distribution by using their initial amount of common randomness and exchanging messages. Our results show that no protocol which is secure in a composable sense can significantly amplify the entropy initially shared by the parties.
Intelligent speed control of interior permanent magnet synchronous motors

Precise control of the permanent magnet synchronous motor over wide speed range is an engineering challenge. This paper considers the design and implementation of two novel techniques of speed control for an interior permanent magnet synchronous motor using hybrid current and artificial neural network controllers. The intelligent hybrid controller which is a combination of the hysteresis current controller for high speed operation and a ramp comparator for low speed operation is proposed. The switching between the two modes is conveniently enabled in software. This hybrid method is compared with the artificial neural network based speed control scheme incorporating the on-line weights and biases updating as well as adaptive learning rate features in software command. Systematic mathematical formulations are given. An implementation schematic using the digital signal processor board DS1102 is presented. Complete control systems have been implemented using current-controlled three-phase PWM voltage source inverter for a laboratory 1 hp interior rotor permanent magnet motor. The experimental results validate the theoretically simulated speed responses under different dynamic operating conditions.
Prefibrillar Amyloid Aggregates Could Be Generic Toxins in Higher Organisms

More than 40 human diseases are associated with fibrillar deposits of specific peptides or proteins in tissue. Amyloid fibrils, or their precursors, can be highly toxic to cells, suggesting their key role in disease pathogenesis. Proteins not associated with any disease are able to form oligomers and amyloid assemblies in vitro displaying structures and cytotoxicity comparable with those of aggregates of disease-related polypeptides. In isolated cells, such toxicity has been shown to result from increased membrane permeability with disruption of ion homeostasis and oxidative stress. Here we microinjected into the nucleus basalis magnocellularis of rat brains aggregates of an Src homology 3 domain and the N-terminal domain of the prokaryotic HypF, neither of which is associated with amyloid disease. Prefibrillar aggregates of both proteins, but not their mature fibrils or soluble monomers, impaired cholinergic neuron viability in a dose-dependent manner similar to that seen in cell cultures. Contrary to the situation with cultured cells, however, under our experimental conditions, cell stress in tissue is not followed by a comparable level of cell death, a result that is very likely to reflect the presence of protective mechanisms reducing aggregate toxicity. These findings support the hypothesis that neurodegenerative disorders result primarily from a generic cell dysfunction caused by early misfolded species in the aggregation process.
The Ubiquitination, Disaggregation and Proteasomal Degradation Machineries in Polyglutamine Disease

Polyglutamine disorders are chronic, progressive neurodegenerative diseases caused by expansion of a glutamine tract in widely expressed genes. Despite excellent models of disease, a well-documented clinical history and progression, and established genetic causes, there are no FDA approved, disease modifying treatments for these disorders. Downstream of the mutant protein, several divergent pathways of toxicity have been identified over the last several decades, supporting the idea that targeting only one of these pathways of toxicity is unlikely to robustly alleviate disease progression. As a result, a vast body of research has focused on eliminating the mutant protein to broadly prevent downstream toxicity, either by silencing mutant protein expression or leveraging the endogenous protein quality control machinery. In the latter approach, a focus has been placed on four critical components of mutant protein degradation that are active in the nucleus, a key site of toxicity: disaggregation, ubiquitination, deubiquitination, and proteasomal activity. These machineries have unique functional components, but work together as a cellular defense system that can be successfully leveraged to alleviate disease phenotypes in several models of polyglutamine toxicity. This review will highlight recent advances in understanding both the potential and role of these components of the protein quality control machinery in polyglutamine disease pathophysiology.
Heart Rate Variability Analysis in Revascularized Individuals Submitted to an Anaerobic Potency Test

The objective of this study was to analyze the behavior of autonomic modulation before, during and after the Modified Wingate Test (WanMT), through the analysis of Heart Rate Variability (HRV). Six volunteers between the ages of 40 and 70, post-revascularization procedures (angioplasty and/or surgery, mean duration 10 months), were submitted to supervised training for at least 10 to 14 months. The following protocol, divided into 5 phases, was used: 1) Rest Phase (RP): 180 seconds; 2) Submaximum Phase (SP): 30 seconds; 3) Maximum Phase (MP): 30 seconds; 4) Active Recuperation Phase (ARP); 120 seconds and; 5) Passive Recuperation Phase (PRP): 180 seconds. For the WanMT Test, we selected the load of 3.75% of corporal weight for all volunteers. To analyze the HRV, we used the following parameters: the interval RRr, MNN, SDNN, RMSSD and PNN50. We only observed results for the group according to RMSSD parameters during the rest phase of the test protocol in which the group remained in vagal presence and during all other phases in vagal depression. However, when we analyzed the PNN50, we observed that the group was in medium vagal presence during all of the phases of the test though there was no statistically significant difference (p> 0.05) between the phases. Therefore, we can say that all of the individuals had a similar profile in the autonomic response to the WanMT, confirmed by the parameters studied in the analysis of the HRV in the time domain.
Distribution of Alpha Thalassaemia Gene Variants in Diverse Ethnic Populations in Malaysia: Data from the Institute for Medical Research

Alpha thalassaemia is highly prevalent in the plural society of Malaysia and is a public health problem. Haematological and molecular data from 5016 unrelated patients referred from various hospitals to the Institute for Medical Research for α thalassaemia screening from 2007 to 2010 were retrieved. The aims of this retrospective analysis were to describe the distribution of various alpha thalassaemia alleles in different ethnic groups, along with their genotypic interactions, and to illustrate the haematological changes associated with each phenotype. Amongst the patients, 51.2% (n = 2567) were diagnosed with α thalassaemia. Of the 13 α thalassaemia determinants screened, eight different deletions and mutations were demonstrated: three double gene deletions, – – SEA, – – THAI, ––FIL; two single-gene deletions, α–3.7 and – α4. 2; and three non-deletion mutations, Cd59G > A (haemoglobin [Hb] Adana), Cd125T > C (Hb Quong Sze) and Cd142 (Hb Constant Spring). A high incidence of α–3.7 deletion was observed in Malays, Indians, Sabahans, Sarawakians and Orang Asli people. However, the – – SEA deletion was the most common cause of alpha thalassaemia in Chinese, followed by the α–3.7 deletion. As many as 27 genotypic interactions showed 1023 α thalassaemia silent carriers, 196 homozygous α+ thalassaemia traits, 973 heterozygous α0 thalassaemia carriers and 375 patients with Hb H disease. Statistical analysis showed a significant difference in the distribution of α thalassaemia determinants amongst the various ethnic groups. Hence, the heterogeneous distribution of common determinants indicated that the introduction of an ethnicity-targeted hierarchical α thalassaemia screening approach in this multi-ethnic Malaysian population would be effective.
Bimanual robotic cloth manipulation for laundry folding

The physical properties of highly deformable objects such as clothing poses a challenging problem for autonomously acting systems. Especially, grasping and manipulation require new approaches that can accommodate for an object's variable and changing appearance. In this paper, we present a system that is capable of fully autonomously transforming a clothing item from a random crumpled configuration into a folded state. We describe a method to compute valid grasp poses on the cloth which accounts for deformability. Our algorithm includes a novel fold detection and grasp generation strategy, which suggests grasp poses on cloth folds. Machine learning techniques are used to evaluate these grasp poses. In our experiments, we use a stock PR2 robot whose two arms alternatingly perform grasps on a T-shirt equipped with fiducial markers. The goal of this grasp sequence is to bring the T-shirt into a configuration from which the robot can fold it. In several experiments, we demonstrate the performance of our approach.
A Hybrid Model of Hierarchical Clustering and Decision Tree for Rule-based Classification of Diabetic Patients

Hybrid models in data mining have recently gained attention including in the study of medical research. Various studies in this domain using hybrid models have shown different results. This paper presents the new hybrid model by exploring Agglomerative Hierarchical Clustering and Decision Tree Classifier on Pima Indians Diabetes dataset. The experiments compared performance accuracy of the Decision Tree Classifier against the same classifier augmented with Hierarchical Clustering. Results showed that the hybrid model achieved higher accuracy with 80.8% as compared to 76.9% of the standard model. This is a promising result for adoption of hierarchical clustering in a rule-based classifier. Keyword- Medical Data Mining, Hierarchical Clustering, Classification, Decision Tree, Hybrid Model
Health Monitoring in Smart Grid Using Big Data Perspective

Transition from traditional power grid into a smart grid involves collecting and processing a large amount of data from generation, transmission to consumer level. Data collected at each level differs considerably in terms of the parameters under observation and frequency of collection, satisfying the 5 Vs (volume, velocity, variety, value and veracity) requirements of big data. In this paper, we have explored a health monitoring system for smart grid that can be used to prevent failures and outages from taking place. These outages are typically a consequence of cascading failures and fault propagation due to the connected nature of the power grid. To mitigate these failures, wide area monitoring and control systems are required to identify the vulnerable and critical components of the system. The proposed proactive health monitoring system monitors various electrical and non-electrical parameters at the distribution level. These parameters are then used to classify the system status into one of the four predefined stability zones/states. The state information can be used by a central unit to determine whether more data is needed, and/or any control action needs to be taken. Since the initial processing uses a smaller subset of data, the processing can be done faster. If required, large subset, i.e. (Phasor Measurement Units) PMUs can be used for further processing. This novel idea can act as an intermediate system between already deployed Supervisory Control and Data Acquisition (SCADA) and PMUs.
VLSI architecture for real time edge detection of monochrome video sequences

Edge detection is a fundamental and important operation in image processing. In this paper, we propose a VLSI architecture for detecting edges from real time monochrome video sequences. We have adopted a local threshold and global variance based method to extract initial edge map and then different edge orientations have been applied to extract true edge points. The global variance is selected as the mean of local variances thus eliminating user intervention for different scenes. Finally, an edge connection operation is done to link the closely separated discrete edge paths. Block RAM based architecture is used to implement the scheme in XILINX VIRTEX IV FPGA. A real time good quality edge extraction is achieved with scene adaptability and low hardware resource utilization.
Impacts of Temperature on the Stability of Tropical Plant Pigments as Sensitizers for Dye Sensitized Solar Cells

Natural dyes have become a viable alternative to expensive organic sensitizers because of their low cost of production, abundance in supply, and eco-friendliness. We evaluated 35 native plants containing anthocyanin pigments as potential sensitizers for DSSCs. Melastoma malabathricum (fruit pulp), Hibiscus rosa-sinensis (flower), and Codiaeum variegatum (leaves) showed the highest absorption peaks. Hence, these were used to determine anthocyanin content and stability based on the impacts of storage temperature. Melastoma malabathricum fruit pulp exhibited the highest anthocyanin content (8.43 mg/L) followed by H. rosa-sinensis and C. variegatum. Significantly greater stability of extracted anthocyanin pigment was shown when all three were stored at 4°C. The highest half-life periods for anthocyanin in M. malabathricum, H. rosa-sinensis, and C. variegatum were 541, 571, and 353 days at 4°C. These were rapidly decreased to 111, 220, and 254 days when stored at 25°C. The photovoltaic efficiency of M. malabathricum was1.16%, while the values for H. rosa-sinensis and C. variegatum were 0.16% and 1.08%, respectively. Hence, M. malabathricum fruit pulp extracts can be further evaluated as an alternative natural sensitizer for DSSCs.
Lived experiences of Black African immigrant entrepreneurs in South Yorkshire

The research investigates the lived experience of Black African Immigrant Entrepreneurs’ (BAIEs) and their challenges and opportunities in South Yorkshire within the region-specific history, economy, demography and cultural contexts. It also accounts for recent Black African Immigrants' entrepreneurship trends and challenges underpinned by the broader theoretical domain of entrepreneurship and sub-domains of ethnic and immigrant entrepreneurship. Black African Immigrants are reported to be the least studied and most underrepresented social groups among visible ethnic minorities in the UK. Moreover, previous research has been limited to large inner cities and within wellestablished communities and thus has been unable to represent the experience of outer regions and recent migrants’ experience. Among researchers of ethnic and immigrant entrepreneurship, combining together two social groups, African and Caribbean immigrants as ‘Afro-Caribbean’, is a common mistake which arguably fails to recognise the distinctiveness in their pattern and history of migration, education and background and approaches to entrepreneurship. Furthermore, these studies lack methodological diversity, relying heavily on quantitative data and failing to capture the lived experience in greater depth and breadth. This research adopts a phenomenological approach of qualitative methodology recognised as effective in exploring lived experience. Sociological based theory on "othering" and "belonging" is used as a lens to critically explore the experiences of immigrant entrepreneurship from the perspective of BAIEs. The research findings suggest that BAIEs face disproportionately high barriers from the opportunity structure as external barriers, whilst internal challenges include the fact that BAIEs are predominantly restricted to ethnic niche markets whose core customers are small in size and transient, hampering growth potential and the ability to break into the mainstream and high-growth markets. These impediments may be observed to relate to the social and cultural identity of the BAIE as an "othered" social grouping in the UK business community context, often lacking a sense of belonging and facing structural exclusion. In spite of this, the research has observed new knowledge about how BAIEs have developed entrepreneurial attributes of resilience (high tolerance to risk, uncertainty and adaptability) and cultural predisposition (high propensity and v preparedness towards enterprise) as their response to overcoming challenges and maximising opportunities in the host country and region. The research is intended to impact on advancing knowledge of diversity in entrepreneurship and to assist policy makers, BAIE managers and practitioners to make more informed decisions that align with a need to promote inclusion and diversity in line with the region’s strategic vision.
Efficient Data Selection for Bilingual Terminology Extraction from Comparable Corpora

Comparable corpora are the main alternative to the use of parallel corpora to extract bilingual lexicons. Although it is easier to build comparable corpora, specialized comparable corpora are often of modest size in comparison with corpora issued from the general domain. Consequently, the observations of word co-occurrences which are the basis of context-based methods are unreliable. We propose in this article to improve word co-occurrences of specialized comparable corpora and thus context representation by using general-domain data. This idea, which has been already used in machine translation task for more than a decade, is not straightforward for the task of bilingual lexicon extraction from specific-domain comparable corpora. We go against the mainstream of this task where many studies support the idea that adding out-of-domain documents decreases the quality of lexicons. Our empirical evaluation shows the advantages of this approach which induces a significant gain in the accuracy of extracted lexicons.