Miracle-dz/UniFAR-FTUs huggingface dataset:
COMPARISON OF 3 DIFFERENT TECHNIQUES TO ASSESS ANGIOGENESIS USING THE CHICK EMBRYO CHORIOALLANTOIC MEMBRANE MODEL

Angiogenesis is the growth of blood vessels from the existing vasculature. A variety of methods have been used to assess angiogenesis. One widely accepted is the Chick Chorioallantoic membrane (CAM) model. Quantification of blood vessels in the CAM model using Stereomicroscope and the Image Analysis software, is one of the easy, reproducible and validated technique, but it is not economical. Hence, there is a need for an alternative technique which has the consistency of the Image analysis method but is cost effective. Thus, the present study was aimed to compare 3 different techniques of CAM model, 2 known and one novel (Drabkin‟s method), in determining the angiogenic potential of drugs. 6-day old embryonated White Leghorn eggs were used for the CAM model. The angiogenic potential of 3 standard drugs viz. , VEGF, Erythropoietin and Heparin was assessed using 3 techniques, viz. , Drabkin‟s method, Overall quantification of blood vessels (using Stereomicroscope) and Localized quantification of blood vessels (using discs). 6-day old embryonated eggs were inoculated with the known drugs respectively, and incubated. Untreated eggs served as the normal control. On day 12, CAM was excised from the eggs and the effect of the drugs on angiogenesis was evaluated by the 3 techniques and compared. All techniques evaluated in the study demonstrated comparable results with significant Pearson‟s correlation (r = 0.9877, p <0.0001). Significant correlation between the Drabkin‟s method results and both the image analysis methods demonstrated that Drabkin‟s method is a relatively cheaper, reproducible and a reliable technique to screen drugs for their angiogenic potential.
Theory of the many-body localization transition in one dimensional systems

We formulate a theory of the many-body localization transition based on a novel real space renormalization group (RG) approach. The results of this theory are corroborated and intuitively explained with a phenomenological effective description of the critical point and of the "badly conducting" state found near the critical point on the delocalized side. The theory leads to the following sharp predictions: (i) The delocalized state established near the transition is a Griffiths phase, which exhibits sub-diffusive transport of conserved quantities and sub-ballistic spreading of entanglement. The anomalous diffusion exponent $\alpha < 1/2$ vanishes continuously at the critical point. The system does thermalize in this Griffiths phase. (ii) The many-body localization transition is controlled by a new kind of infinite randomness RG fixed point, where the broadly distributed scaling variable is closely related to the eigenstate entanglement entropy. Dynamically, the entanglement grows as $\sim\log t$ at the critical point, as it also does in the localized phase. (iii) In the vicinity of the critical point the ratio of the entanglement entropy to the thermal entropy, and its variance (and in fact all moments) are scaling functions of $L/\xi$, where $L$ is the length of the system and $\xi$ is the correlation length, which has a power-law divergence at the critical point.
Analysis of Defensive Data Transmission with Reduced Energy Expenditure in Wireless Sensor Network

- In this to propose a distributed traffic-balancing routing algorithm for multi-sink wireless sensor networks that effectively distributes traffic from sources to sinks. The proposed algorithm considers the traffic being faced by surrounding neighbors before for-warding packets to any sink using gradient search for routing and providing a balance between optimal paths and possible congestion on routes toward those sinks. Extensive simulations conducted to evaluate the performance of the proposed scheme indicate that it effectively reduces the overall packet delay, energy consumption and improves the packet delivery ratio under heavy traffic
STUDY AND ANALYSIS OF A ROUTING IN VEHICULAR AD HOC NETWORKS

In this article, we introduce the new emerging technology to achieve smart communications and the efficiency of the inter-vehicle throughput. These characteristics can be achieved only by the special network technology that is Vehicular Ad Hoc Network(VANET). It is the Integrated ad hoc network for Wireless LAN (WLAN) and Cellular Technology. These type of VANETs are developed in Hybrid Network type and hence, it is different from other networks architectures and characteristic features. This technology became popular and varies in working research challenges and designs in efficient routing protocol. Here, we describe the routing technology of VANETs and recent surveyed routing protocols and also the related models.
The Analysis of Youngster with Fever by Using Instantaneous Pulse Rate Variability

—Body temperature is an important homeothermic autoregulation of humans. Body temperature is usually controlled by autonomic nervous system (ANS). When a person has suffered a virus or bacterial infection, it causes fever. The ANS rises the body temperature by tachycardia and cutaneous vasomotion. The common non-invasive indication for ANS is based on heart rate variability (HRV) and pulse rate variability (PRV). However, these two methods are limited by the timescale of time series. Instantaneous PRV (iPRV) was proposed as a surrogate of HRV in frequency domain and breaks the restriction of timescale. In this paper, thirty subjects were recruited for the study; the body temperature and the photoplethysmography (PPG) signal were acquired in supine position for ten minutes. Fifteen fever subjects, whose body temperature was higher than 37.9 °C, are in Group Fev. , the others are in Group Ctr. The results show that the power of iPRV in normalized low frequency (nLF) in Group Fev. (0.63±0.13, p<0.05) was significantly higher than that in Group Ctr. (0.47±0.16). And the power of iPRV in normalized high frequency (nHF) in Group Fev. (0.38 ±0.13, p<0.05) was significantly lower than that in Group Ctr. (0.54±0.16). Besides, the nVHF might have a potential for indicating the peripheral circulation and providing more information about body regulation.
Memory Cells Cutting Edge: Naive T Cells Masquerading as

This study shows that naive CD8 T cells can acquire characteristics of memory T cells in the absence of stimulation with speciﬁc Ag simply by the process of homeostatic proliferation under lymphopenic conditions. This Ag-independent T cell differentiation pathway did not result in up-regulation of early activation markers (CD69, CD25, CD71), but expression of several memory markers (CD44, CD122, Ly6C) increased progressively with successive divisions. These markers were then stably expressed, and these cells also became more responsive functionally to speciﬁc Ag. Thus, all “memory” phenotype T cells in an individual may not be true Ag-experienced cells and may include naive cells masquerading as memory cells. These ﬁndings are specially relevant in cases of disease or treatment-induced lymphopenia such as in HIV-infected individuals or transplant recipients. In addition, this study may have implications for autoimmunity because homeostatic proliferation of naive T cells requires interaction with self peptide plus MHC molecules. The Journal of Immunology, 2000, 165: 1733–1737.
CCD Photometry in the Globular Cluster M4

A V, B- V composite colour-magnitude diagram, based upon CCD photometry from V∼ 12 on the red giant branch to V∼ 25 on the main-sequence has been derived for the globular cluster M4. A distance to the cluster of (m — M)v = 12.84 ± 0.19 is determined and the best match to theoretical isochrones is for the case [Fe/H]= −1.27 and an age of 16±1 Gyr. A differential age comparison with NGC 362 shows that M4 is approximately 1.7 Gyr older.
CONTROL OF ASTHMA AMONG PATIENTS IN SAUDI ARABIA

Background: Asthma Control Test (ACT) Questionnaire is developed to meet the guidelines internationally accepted for asthma management by measuring adequacy and any alteration in control of asthma, occurring spontaneously or after starting asthma management. Objectives: to assess control of asthma in a sample of patients diagnosed as asthmatics in Saudi Arabia based on Asthma Control Test (ACT) Methods: fifty asthmatic patients, from those attending the out patients clinics in Hospitals, were included in this study in the period from June to September 2018. Patients were subjected to: full clinical history and examination for clinical classification of the disease and to recognize controlled from uncontrolled patients; review for the treatment plan for each patient; (ACT) questionnaire was used to identify patients with poorly controlled asthma. Results: clinical classification of asthma showed that 20% of patients had intermittent asthma, 24% had mild persistent asthma, 32 % had moderately persistent asthma and 24% of patients got severe persistent asthma. According to ACT only 24% of patients were controlled, while the rest of patients 76% were considered uncontrolled. Conclusion: ACT was found to be a reliable tool for assessment of uncontrolled asthmatic patients when implemented. Conduct more studies in different geographical areas to assess effectiveness of the AST questionnaire in different situations and different asthmatic patients.
Digital Image Watermarking Algorithm Based on DCT and Spread Spectrum

- In this paper, an algorithm for embedding watermarks into host image based on Discrete Cosine Transform and Spread Spectrum has proposed. The proposed algorithm works by dividing the cover into blocks of equal sizes and then embeds the watermark in middle band of DCT coefficient of cover image. Performance evaluation of proposed algorithm has been made using Bit Error Rate (BER) and Peak Signal to Noise Ratio (PSNR) value for different watermark size and images: Lena, Girl, and Tank images yield similar results. This algorithm is simple and does not require the original cover image for watermark recovery. A set of systematic experiments, including JPEG compression, Gaussian filtering and addition of noise are performed to prove robustness of our algorithm.
Survey on Adaptive Task Assignment in Heterogeneous Hadoop Cluster

-Map Reduce has become ubiquitous for processing large data volume jobs. As the number and variety of jobs to be executed across heterogeneous clusters are increasing, so is the complexity of scheduling them efficiently to meet required objectives of performance. The design of adaptive job schedulers has attracted significant research attention in recent years. But despite many efforts that have been made, there are still many challenges in this area. An efficient scheduling algorithm should strike a balance between utilization and parallelism in the cluster to address performance metrics such as fairness and mean completion time. The aim of this paper is to provide a better understanding of adaptive job schedulers in Map Reduce and survey of some of the Map Reduce scheduling algorithms proposed for such complex scenarios.
Ethanol Enhances g -Aminobutyric Acid Responses in a Subpopulation of Nucleus Accumbens Neurons: Role of Metabotropic Glutamate Receptors 1

The nucleus accumbens (NAcc) may be a key area in the rewarding effects of abused drugs. We previously showed that low ethanol concentrations decreased both N -methyl- D -aspar- tate (NMDA)-induced and kainate-induced currents in NAcc core neurons (Nie et al., 1994). To explore the effects of ethanol on g -aminobutyric acid (GABA) responses in NAcc, we used intracellular voltage-clamp recordings and locally applied GABA in a slice preparation containing the NAcc. Ethanol (11– 200 mM) had no effect on resting membrane properties, but 11, 22, 44, 100, and 200 mM ethanol increased GABA currents in 17, 33, 45, 50, and 22% of cells, respectively. Superfusion of low glutamate concentrations that had no direct effect on membrane properties enhanced ethanol potentiation of GABA cur- rents in more than half the NAcc cells. Neither a -amino-3-hydroxy-5-methylisoxazole-4-propionic acid/kainate receptor nor NMDA receptor antagonists affected the percentage of cells showing ethanol enhancement of GABA responses or the degree of ethanol enhancement of GABA currents in NAcc neurons. However, in ethanol-sensitive cells, the metabotropic receptor antagonist a -methyl-4-carboxyphenylglycine (MCPG) blocked the ethanol enhancement of GABA currents. In addi- tion, the metabotropic receptor agonist trans -1-aminocyclo-pentane-1,3-dicarboxylic acid enhanced GABA responses in 50% of cells tested, an effect blocked by MCPG. These data suggest that NAcc core neurons possess both ethanol-sensi- tive and -insensitive GABA system, without disrupting the flow of the superfusate. To avoid loss of ethanol by evaporation, the solutions were diluted in gassed ACSF from sealed stock solutions of reagent grade 95% ethyl alcohol in water immediately before administration. The usual testing protocol was: recording of membrane currents with periodic local application of GABA for 10 to 15 min during superfusion of ACSF alone (“con-trol”); followed by switching to ACSF with drug [e.g., ethanol, glutamate, CNQX, D -APV, a -methyl-4-carboxyphenylglycine (MCPG)] while repeating GABA application for 5 to 20 min; then switching again to ACSF alone for 15 to 35 min with subsequent GABA current measures (“washout”). We defined ethanol potentiation of GABA responses as at least a 10% increase in peak GABA current. We obtained TTX from Calbiochem (La Jolla, CA), CNQX and MCPG from Tocris Cookson (Bristol, UK), D -APV from Research Biochemi- cals (Wayland, MA), ethanol from the Remet Corp. (La Mirada, CA), and all other drugs from Sigma Chemical Co. (St. Louis, MO). Data Analysis. Data are expressed as mean 6 S.E. For statistical analysis, we used ANOVA for repeated measures, followed by the Newman-Keuls post hoc test. We accepted P , . 05 as statistically significant.
Ultra-high-field Arterial Labeling MRI for non-contrast assessment of lesion perfusion in Multiple

: Objectives Assess the feasibility of using an optimised ultra-high-field high-spatial-resolution low-distortion ASL MRI acquisition to measure focal haemodynamic pathology in cortical lesions (CLs) in Multiple Sclerosis (MS). Twelve MS patients (8 mean range=35-64 gave and were scanned on a 7 Tesla Philips Achieva scanner. Perfusion data were collected at multiple post-labeling delay times using a single-slice flow-sensitive alternating inversion recovery ASL protocol with a balanced steady-state free precession readout CLs were identified using a high-resolution Phase-Sensitive Inversion Recovery (PSIR) scan. Significant differences in perfusion within CLs compared to immediately surrounding normal appearing grey matter (NAGM and total cortical normal appearing grey cortical ) were assessed using paired t-tests. The low contrast-to-noise ratio of ASL techniques is substantially improved when at ultra-high-field [17], allowing data at higher spatial resolution. there when ASL that require optimisation of the imaging protocol [18]. In this study, we assess the feasibility of using an optimised, ultra-high-field, high-spatial resolution, low-distortion ASL acquisition [19] to quantify perfusion in chronic CLs, demonstrating proof of concept that this technique is suitable for characterising local haemodynamic pathology in MS. high spatial resolution (0.6 mm isotropic) to minimise partial volume effects in small CLs, allowing accurate boundary detection. ASL data were acquired using a flow-sensitive alternating inversion recovery (FAIR) ASL scheme with in-plane pre-saturation using a WET (Water suppression Enhanced through T1 effects) scheme and a sinc post-saturation pulse. A balanced steady-state free precession (bSSFP) readout was used to achieve high spatial resolution (1.2x1.2x3.0 mm 3 ) with minimal distortions, essential for accurate co-registration of small CLs. A single axial imaging slice was positioned to transect one or more CLs identified from the PSIR acquisition. Single-phase ASL data were collected at post-labeling delay (PLD) of 1400 and 1800 ms to determine tissue perfusion (50 label-control pairs were acquired at each PLD, bSSFP readout collected using  /2 pulse at a time TR/2 before a train of °RF pulses with  of 50 o to reach a steady state). In addition, multi-phase ASL were acquired using a Look-Locker bSSFP readout (with flip angle  of 35°) comprising 8 PLDs of 200, 550, 900, 1250, 1600, 1960, 2300, 2650 ms (40 label-control pairs, to estimate arterial transit time and locate intravascular signal contributions). An M 0 image was acquired for both single and multi-phase bSSFP acquisitions to allow absolute perfusion quantification. studies of MS cohorts. In order to assess the repeatability of highly focal perfusion values (e.g. the spatial scale of CLs) in different control and patient cohorts, further technical development is needed to simultaneously achieve high-resolution data with whole-brain coverage by combining the bSSFP acquisition with simultaneous multislice (SMS)
Estimating active forearm pronation-supination motion by means of FE modelling

Active range of motion (ROM) of the forearm is important for completing daily life activities (ADL). Such motion could be compromised as a result of a poorly healed fracture. Although numerical models are often used to aide medical treatment, most of them are static. In addition, there is no previous model nor methodology related to forearm and its motion. In this work, a methodology to create finite element models that can evaluate active ROM is developed and validated. The biomechanical behaviour of the ligamentous structures, as a whole, was compared with data available from previous studies. The active ROM was validated against experimental measurements of active ROM. The ROM predicted with this methodology was 72º in pronation and 83º in supination; these values are within 5º from the standardised values for human ROM. In addition, this work supports the hypothesis that the muscles are limiting structures of the ROM, such task was always attributed to ligamentous structures. Nevertheless, in active ROM, muscle contraction and extension delimited the arc of motion. In summary, this work provides a methodology, mechanical properties of ligamentous structures, types of constrains and kinematic assumptions to produce a biomechanically sound model of the forearm which can be used for further study of forearm fractures.
BIROn - Birkbeck Institutional Research Online Abnormal driving detection with normalized driving behavior data: a deep learning approach.

1 Abstract — Abnormal driving may cause serious danger to both the driver and the public. Existing detectors of abnormal driving behavior are mainly based on shallow models, which require large quantities of labeled data. The acquisition and labelling of abnormal driving data are, however, difficult, labor-intensive and time-consuming. This situation inspires us to rethink the abnormal driving detection problem and to apply deep architecture models. In this study, we establish a novel deep-learning-based model for abnormal driving detection. A stacked sparse autoencoders model is used to learn generic driving behavior features. The model is trained in a greedy layer-wise fashion. As far as the authors know, this is the first time that a deep learning approach is applied using autoencoders as building blocks to represent driving features for abnormal driving detection. In addition, a method for denoising is added to the algorithm to increase the robustness of feature expression. The dropout technology is introduced into the entire training process to avoid overfitting. Experiments carried out on our self-created driving behavior dataset demonstrate that the proposed scheme achieves a superior performance for abnormal driving detection compared to the state-of-the-art.
Data Mining Classification: The Potential of Genetic Programming

—Data Mining (DM) is one of the techniques used for the process of searching through a huge volume of data in a database to uncover useful and interesting information. Classification is a commonly studied issue in data mining. It involves predicting the categorical attribute (class) value on the basis of other attributes (predicting attributes) values. One of the classification approaches to data mining is gene expression programming (GEP), which is a development of Genetic algorithm (GA) and Genetic Programming (GP). In this paper, we investigate the potential of genetic programming for data mining classification. It is therefore important to investigate the advantages and challenges associated with using tree-based Genetic Programming algorithms for data mining classification. This study determines how better data mining classification performance can be achieved using genetic programming. It demonstrates how the search scope can be refined through heuristics and machine learning methods to reduce and change the search space for our Genetic Programming classifiers. A specific design and application of GP to two classes data analysis is presented as well as a set of experimental results showing the efficiency of the suggested application .
Masters Thesis: Semi-parametric identification of manipulator dynamics in a time-varying environment

A recent trend in robotics is aimed at the cooperation between human and robot. This has led to an increased development of collaborative robot manipulators. Typical characteristics of collaborative robots are their user-friendly and lightweight design, innovative compliant mechanics, the implementation of various safety features and advanced control capabilities. These characteristics enable humans to work alongside the manipulator or interact with it. The implementation of passive compliant components such as springs and pneumatics have a beneficial effect on the level of safety for the operator. However, the added complexity often has a negative influence on the degree to which an accurate description of the system dynamics can be derived. Furthermore, the lightweight design and increasing payload-to-weight ratio amplify the effect of exogenous alterations to the system, such as attaching an object to the end effector. The work in this thesis is aimed at obtaining an accurate description of the system dynamics for control purposes. In doing so, special attention is given to dealing with instantaneous time-varying phenomena. An online semi-parametric approach is used to produce a valid description of the inverse dynamics of the considered system. The method consists of a non-parametric part which is described using Gaussian process regression (GPR) and a parametric part for which the parameters are identified using an extended Kalman filter (EKF). In this thesis, instantaneous system changes are introduced by attaching an unknown object to the end effector of the manipulator. The EKF implementation is specifically aimed at rapidly compensating for the response induced by this object. The GPR is used to compensate for remaining modeling errors. The performance of the proposed methods is evaluated in simulation. The semi-parametric description achieves high modeling accuracy, fast adaptation to instantaneous system changes and reasonable generalization capabilities. Implementing the proposed solution in real-time applications requires additional research on the subject of online GPR. Master of Science Thesis N.L. D. Marck