A Survey of Attention Deficit Hyperactivity Disorder Identification Using Psychophysiological Data

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common neurological disorders among children, that affects different areas in the brain that allows executing certain functionalities. This may lead to a variety of impairments such as difficulties in paying attention or focusing, controlling impulsive behaviours and overreacting. The continuous symptoms may have a severe impact in the long-term. This paper explores the ADHD identification studies using eye movement data and functional Magnetic Resonance Imaging (fMRI). This study discusses different machine learning techniques, existing models and analyses the existing literature. We have identified the current challenges and possible future directions to provide computational support for early identification of ADHD patients that enable early treatments

Determination of selenium content in selected edible green leaves

The selenium (Se) contents in seven conventional Edible Green Leaves (EGL) that consumed by Sri Lankans were determined using Hydride Generation Atomic Absorption Spectrometric method (HGAAS). The EGLs that were grown in five districts under different climatic conditions in Sri Lanka were collected from Gampaha, Kandy, Kurunegala, Anuradhapura and Puttalam areas. The EGL that were subjected to current study are Centella asiatica (Sin. Gotukola), Alternanthra sessilis (Sin. Mukunuwenna), Basella alba (Sin. Nivithi/ Spinach), Boerhavia diffusa (Sin. Sarana), Ipomoea aquatica (Sin. Kankun), Amaranthus spinosus (Sin. Thampala) and Hygrophila schulli (Sin. Neeramulliya). Soil samples corresponding to each EGL sample were also collected from Gampaha, Kandy and Anuradhapura districts in order identify a relationship between the Se content in plants and soils. Prior to the analysis EGL samples and corresponding soil samples were subjected to acid digestion with nitric acid. Se contents in the EGL were in the range of 31.2 – 103.2 μg kg-1 on dry weight basis. According to the results, Centella asiatica and Hygrophila schulli varieties showed relatively higher Se content, while Hygrophila schulli shown the highest value and the lowest was reported in Boerhavia diffusa. The Se content in corresponding soil samples were ranged from 96.4 to 133.9 μg kg-1 on dry weight basis. The Se content in soil was higher than that in plants, but there was no significant correlation between the Se content in soil and EGLs

Centralized Scheduling with Sum-Rate optimization in Flexible Half-Duplex Networks

In this paper, we focus on maximization of the instantaneous sum-rate in flexible half-duplex networks, where nodes have the flexibility to choose to either transmit, receive or be silent in a given time slot. Since the corresponding optimization problem is NP-hard, we design low-cost algorithms that give sub-optimal solutions with good performance. We first consider two existing approximation techniques to simplify the sum-rate optimization problem: arithmetic-geometric means inequality and another utilising the tight lower bound approximation. We then propose a novel pattern search algorithm that performs close to exhaustive search but with significantly lower complexity. Comparing the performance of the proposed algorithm with respect to existing resource allocation techniques, we observe that our proposed algorithm provides significant sum-rate gains

A Rule-based system for adhd identification using eye movement data

Attention Deficit Hyperactivity Disorder (ADHD) is one of the common psychiatric disorder in childhood, which can continue to adulthood. The ADHD diagnosed population has been increasing, causing a negative impact on their families and society. This paper addresses the effective identification of ADHD in early stages. We have used a rulebased approach to analyse the accuracies of decision tree classifiers in identifying ADHD subjects. The dataset consists of eye movements and eye positions of different gaze event types. The feature extraction process considers fixations, saccades, gaze positions, and pupil diameters. The decision tree-based algorithms have shown a maximum accuracy of 84% and classification rule algorithms have shown an accuracy of 82% using eye movement measurements. Thus, both algorithms have shown high accuracy with the rule-based component

Real time data analytics platform for power grid smart applications

The main objective of this paper is to elucidate issues that concern the integration of existing software systems and platforms into an open-source, open-architecture simulation engine that delivers large scale data analytics for the efficiency and stability of next generation power distribution grids. Our objective is achieved through the design and the implementation of a prototype simulation engine that couples state-of-the-art software from both the electrical engineering and information sciences. The effectiveness of our system is examined through two realistic large and detailed simulation scenarios which also involve machine learning and game theory. © 2017 IEEE

Effect of Storage Temperature on Storage Life and Sensory Attributes of Packaged Mustard Microgreens

Short shelf life limits the commercial value of mustard microgreens. The present study was conducted to evaluate the effects of different storage temperatures on postharvest quality and sensory attributes of mustard microgreens to identify the optimum storage temperature. Mustard microgreens were stored at 5, 10, 15, 20, and 25 °C in 150 µm polyethylene bags. Samples were drawn at 0, 1, 2, 4, 7, 10, and 14 days and tested for changes in total chlorophyll content, tissue electrolyte leakage, weight loss, antioxidant activity, and sensory attributes. Storage temperature significantly (p < 0.05) affected the product quality, shelf life, and sensory quality. When stored at 5 °C, mustard microgreens showed no significant changes in antioxidant activity or tissue electrolyte leakage and minimal change in other parameters and maintained good overall sensory quality for 14 days. Samples stored at 10 and 15 °C retained good overall sensory quality for 4 and 2 days, respectively. When stored at 20 and 25 °C, microgreens deteriorated beyond consumption within one day. A storage temperature of 5 °C in 150 µm polythene bags can preserve high postharvest quality and sensory attributes for 14 days

Media Me: Body and personal media interaction

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)4740 LNCS407-41

Effect of Storage Temperature on Storage Life and Sensory Attributes of Packaged Mustard Microgreens

Short shelf life limits the commercial value of mustard microgreens. The present study was conducted to evaluate the effects of different storage temperatures on postharvest quality and sensory attributes of mustard microgreens to identify the optimum storage temperature. Mustard microgreens were stored at 5, 10, 15, 20, and 25 °C in 150 µm polyethylene bags. Samples were drawn at 0, 1, 2, 4, 7, 10, and 14 days and tested for changes in total chlorophyll content, tissue electrolyte leakage, weight loss, antioxidant activity, and sensory attributes. Storage temperature significantly (p < 0.05) affected the product quality, shelf life, and sensory quality. When stored at 5 °C, mustard microgreens showed no significant changes in antioxidant activity or tissue electrolyte leakage and minimal change in other parameters and maintained good overall sensory quality for 14 days. Samples stored at 10 and 15 °C retained good overall sensory quality for 4 and 2 days, respectively. When stored at 20 and 25 °C, microgreens deteriorated beyond consumption within one day. A storage temperature of 5 °C in 150 µm polythene bags can preserve high postharvest quality and sensory attributes for 14 days

Comparison of the kinetics and magnitude of antibody responses to different SARS-CoV-2 proteins in Sinopharm/BBIBP-CorV vaccinees following the BNT162b2 booster or natural infection.

The kinetics and magnitude of antibody responses to different proteins of the SARS-CoV-2 virus in Sinopharm/BBIBP-CorV vaccinees has not been previously studied. Therefore, we investigated antibody responses to different SARS-CoV-2 proteins at 2 weeks, 3 months, and 6 months post-second dose in previously infected (n = 20) and uninfected (n = 20) Sinopharm/BBIBP-CorV vaccinees. The IgG antibodies to the S, S1 and S2 and N were several folds higher in those who had natural infection compared to uninfected individuals at all time points. We then compared the persistence of antibody responses and effect of natural omicron infection or BNT162b2 booster in Sinopharm/BBIBP-CorV vaccinees. We measured the total antibodies to the RBD, ACE2 blocking antibodies and antibody responses to different SARS-CoV-2 proteins in Sinopharm vaccinees at 7 months post second dose, including those who remained uninfected and not boosted (n = 21), or those who had previous infection and who did not obtain the booster (n = 17), those who were not infected, but who received a BNT162b2 booster (n = 30), or those who did not receive the booster but were infected with omicron (n = 29). At 7 months post second dose uninfected (no booster) had the lowest antibody levels to the RBD, while omicron infected vaccinees showed significantly higher anti-RBD antibody levels (p = 0.04) than vaccinees who received the booster. Only 3/21 cohort A (14.3%) had ACE2 blocking antibodies, while higher frequencies were observed in naturally infected individuals (100%), those who received the booster (18/21, 85.7%), and omicron infected individuals (100%). Pre-vaccination, naturally infected had the highest antibody levels to the N protein. These data suggest that those previously infected Sinopharm/BBIBP-CorV vaccinees have a robust antibody response, 7 months post vaccination, while vaccinees who were naturally infected with omicron had a similar immune response to those who received the booster. It will be important to investigate implications for subsequent clinical protection