The role of trust in e-government adoption: A systematic literature review

Electronic government (e-government) is a concept that has been adopted in most countries for the purposes of providing government services digitally, improving transparency between government and citizens and enabling additional communication channels with the government. Although e-government readiness in most countries is at a high level, adoption of e-government services is still considered tentative. A critical review of the literature suggests that this may be linked to citizens’ trust in government and e-government. As such, there is a need to investigate the role of trust in e-government adoption. For this purpose, a systematic literature review was conducted in order to observe research design, methodologies and approaches adopted in these studies as well as limitations identified and recommendation for future studies. The findings highlight that quantitative techniques and survey research methods appear to have been much preferred over other available alternatives such as qualitative techniques and interview methods or mixed methods in studies relating to trust in e-government adoption

Methanol fractionations of Catha edulis frosk (Celastraceae) contracted lewis rat aorta in vitro: a comparison between crimson and green leaves

The study investigated the effect of methanol extract and its fractionations obtained from Yemeni khat on the smooth muscle isometric tension in Lewis rat aortal ring preparations and compared the effects of the crimson and green leaves. Khat leaves were sorted into green (khat Light; KL) and crimson (khat Dark; KD) leaves, extracted with methanol, followed with solvent-solvent extraction (benzene, chloroform and ethylacetate). The contractile activity of the fractions was tested using aortal ring preparations. The control (phenylepherine contraction) methanol extracts contracted aortas at concentrations 250, 125 and 67.5 μg /1 ml buffer by 80.2% , 57.3%, 26.4% and 81.5%, 65.6% , 24.6% for KL and KD, respectively. Fractions of benzene (BF) and ethylacetate (EaF) contracted the aorta with 2μgm, whereas, chloroform (ChF) with 1 μgm / 1 ml buffer was less potent. The shape of contraction curve produced by EaF differed from that of ChF and BF of both (KL and KD). The EaF induced-contraction peaked after 3.3 ± 0.94 mins, whereas those of BF and CHF peaked after 18.0 ± 2.2, 19.7 ± 0.94 mins, respectively. Pre-incubation with nifedipine (10-6 M) insignificantly reduced the contraction induced by all fractionations, but prazosin (10-6 M) reduced the contraction by 81.9%, 63.1%, 71.8% with p= 0.23, 0.09, 0.15 for BF, ChF and EaF of KL, respectively. It significantly reduced contraction of ChF, 64.1%; p= 0.02, and of EaF, 73.5%; p= 0.04 of KD, while the reduction in contraction of BF was 63.1%; p= 0.06. In conclusion, fractions of green and crimson Yemeni khat leaves contracted aortas of Lewis rats. Both leaves behave almost similarly. Contraction induced by chloroform fraction produced alphasympathetic activity.Key words: Catha edulis, aorta contraction, rat, cathinone

Association of Physical Activity with Co-morbid Conditions in Geriatric Population

To find out association of physical activity with co-morbid conditions in geriatric population, a cross-sectional study was conducted in different cties of Pakistan in 2015. A total of 114 participants were inducted by non-probability convenience sampling technique. Data was collected after informed verbal consent by a validated questionnaire that is Rapid Assessment of Physical Activity (RAPA). Participants were categorized into two groups i.e. physically active and physically inactive. Data was entered and analyzed in SPSS version 20. There were 66 (57.9%) males and 48 (42.1%) females with mean age of 57.04±7.348 years. Among hypertensive individuals (n=43, 37.7%) there were 39 (90.7%) physically inactive, among individuals having angina (n=17, 14.9%) there were 15 (88.2%) physically inactive. Out of 37 (32.5%) diabetics, 35 (94.6%) were physically inactive. Among individuals suffering from arthritis (n=40, 35.1%), there were 38 (95%) physically inactive. A significant association was found between physical activity and diabetes and arthritis with p-value of 0.048 and 0.029 respectively. Physical activity is significantly associated with diabetes and arthritis in geriatric population. Adequate physical activity should be performed to reduce the risk of co-morbid conditions and improve the quality of life in geriatric population

Simultaneous Bayesian recognition of locomotion and gait phases with wearable sensors

Recognition of movement is a crucial process to assist humans in activities of daily living, such as walking. In this work, a high-level method for the simultaneous recognition of locomotion and gait phases using wearable sensors is presented. A Bayesian formulation is employed to iteratively accumulate evidence to reduce uncertainty, and to improve the recognition accuracy. This process uses a sequential analysis method to autonomously make decisions, whenever the recognition system perceives that there is enough evidence accumulated. We use data from three wearable sensors, attached to the thigh, shank, and foot of healthy humans. Level-ground walking, ramp ascent and descent activities are used for data collection and recognition. In addition, an approach for segmentation of the gait cycle for recognition of stance and swing phases is presented. Validation results show that the simultaneous Bayesian recognition method is capable to recognize walking activities and gait phases with mean accuracies of 99.87% and 99.20%. This process requires a mean of 25 and 13 sensor samples to make a decision for locomotion mode and gait phases, respectively. The recognition process is analyzed using different levels of confidence to show that our method is highly accurate, fast, and adaptable to specific requirements of accuracy and speed. Overall, the simultaneous Bayesian recognition method demonstrates its benefits for recognition using wearable sensors, which can be employed to provide reliable assistance to humans in their walking activities

Probabilistic locomotion mode recognition with wearable sensors

Recognition of locomotion mode is a crucial process for control of wearable soft robotic devices to assist humans in walking activities. We present a probabilistic Bayesian approach with a sequential analysis method for recognition of locomotion and phases of the gait cycle. Our approach uses recursive accumulation of evidence, as biological systems do, to reduce uncertainty present in the sensor measurements, and thus improving recognition accuracy. Data were collected from a wearable sensor, attached to the shank of healthy human participants, from three locomotion modes; level-ground walking, ramp ascent and ramp descent. We validated our probabilistic approach with recognition of locomotion in steady-state and gait phases in transitional states. Furthermore, we evaluated the effect, in recognition accuracy, of the accumulation of evidence controlled by increasing belief thresholds. High accuracy results achieved by our approach, demonstrate its potential for robust control of lower limb wearable soft robotic devices to provide natural and safe walking assistance to humans

Improvement of Machinability of Mild Steel during Turning Operation by Magnetic Cutting

This paper presents the details of improvement of machinability of mild steel using magnetic cutting during turning operation. Improvement of machinability was evaluated in terms of tool life, surface roughness and chip morphology. Machine tool chatter is a type of intensive self-excited vibrations of individual components of Machine-Tool-Fixture-Work (MTFW) system. Chatter causes unwanted excessive vibratory motion in between the tool and the work-piece causing adverse effects on the product quality and machine-tool and tool life. In addition to the damage of the work-piece surface due to chatter marks, the occurrence of severe chatter results in many adverse effects, which include poor dimensional accuracy of the work-piece, reduction of tool life, and damage to the machine. Chatter is formed as resonance phenomena during machining because of the instability of the closed-loop system formed by machine tool structure and metal-cutting process. In this study, magnets were used to avoid the chatter formation zone and its effect on machinability was investigated. Improvements in tool life and surface finish were observed during magnetic cutting of the mild steel. An obvious change in the chip behaviour was also present. These observations further enhance the possibility of using this magnetic cutting to eliminate the chatter formation zones and hence eliminate the adverse effect of chatter on machinability

Prediction of gait events in walking activities with a Bayesian perception system

In this paper, a robust probabilistic formulation for prediction of gait events from human walking activities using wearable sensors is presented. This approach combines the output from a Bayesian perception system with observations from actions and decisions made over time. The perception system makes decisions about the current gait events, while observations from decisions and actions allow to predict the most probable gait event during walking activities. Furthermore, our proposed method is capable to evaluate the accuracy of its predictions, which permits to obtain a better performance and trade-off between accuracy and speed. In our work, we use data from wearable inertial measurement sensors attached to the thigh, shank and foot of human participants. The proposed perception system is validated with multiple experiments for recognition and prediction of gait events using angular velocity data from three walking activities; level-ground, ramp ascent and ramp descent. The results show that our method is fast, accurate and capable to evaluate and adapt its own performance. Overall, our Bayesian perception system demonstrates to be a suitable high-level method for the development of reliable and intelligent assistive and rehabilitation robots

A Novel Splice-Site Variant in CACNA1F Causes a Phenotype Synonymous with Åland Island Eye Disease and Incomplete Congenital Stationary Night Blindness

Background: CACNA1F-related disorders encompass progressive and non-progressive disorders, including Åland island eye disease and incomplete congenital stationary night blindness. These two X-linked disorders are characterized by nystagmus, color vision defect, myopia, and electroretinography (ERG) abnormalities. Ocular hypopigmentation and iris transillumination are reported only in patients with Åland island eye disease. Around 260 variants were reported to be associated with these two non-progressive disorders, with 19 specific to Åland island eye disease and 14 associated with both Åland island eye disease and incomplete congenital stationary night blindness. CACNA1F variants spread on the gene and further analysis are needed to reveal phenotype-genotype correlation. Case Report: A complete ocular exam and genetic testing were performed on a 13-year-old boy. A novel splice-site variant, c.4294-11C>G in intron 36 in CACNA1F, was identified at hemizygous state in the patient and at heterozygous state in his asymptomatic mother and explained the phenotype synonymous with Åland island eye disease and incomplete congenital stationary night blindness observed in the patient. Conclusion: We present a novel variant in the CACNA1F gene causing phenotypic and electrophysiologic findings indistinguishable from those of AIED/CSNB2A disease. This finding further expands the mutational spectrum and our knowledge of CACNA1F-related disease