The conception and experimental assessment of a removable friction-based shear connector (FBSC) for precast steel-concrete composite bridges is presented. The FBSC uses pre-tensioned high-strength steel bolts that pass through countersunk holes drilled on the top flange of the steel beam. Pre-tensioning of the bolts provides the FBSC with significant frictional resistance that essentially prevents relative slip displacement of the concrete slab with respect to the steel beam under service loading. The countersunk holes are grouted to prevent sudden slip of the FBSC when friction resistance is exceeded. Moreover, the FBSC promotes accelerated bridge construction by fully exploiting prefabrication, does not raise issues relevant to precast co

The subject of this research involves studying adsorption to remove hexavalent chromium Cr(VI) from aqueous solutions. Adsorption process on bentonite clay as adsorbent was used in the Cr(VI) concentration range (10-100) ppm at different temperatures (298, 303, 308 and 313)K, for different periods of time. The adsorption isotherms were obtained by obeying Langmuir and Freundlich adsorption isotherm with R2 (0.9921-0.9060) and (0.994-0.9998), respectively. The thermodynamic parameters were calculated by using the adsorption process at four different temperatures the values of ?H, ?G and ?S was [(+6.582 ? +6.547) kJ.mol-1, (-284.560 ? -343.070) kJ.mol-1 and (+0.977 ? +1.117) kJ.K-1.mol-1] respectively. This data indicates the spontaneous sorp

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.

Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.

The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple

Alzheimer’s disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have n

 In this paper, we propose a method using continuous wavelets to study the multivariate fractional Brownian motion through the deviations of the transformed random process to find an efficient estimate of Hurst exponent using eigenvalue regression of the covariance matrix. The results of simulations experiments shown that the performance of the proposed estimator was efficient in bias but the variance get increase as signal change from short to long memory the MASE increase relatively. The estimation process was made by calculating the eigenvalues for the variance-covariance matrix of Meyer’s continuous wavelet details coefficients.

A niger, a fungus which doesn't have high ability to production lipid, this fungus has been select to investigate the non oleaginicity. In this search, there are explorations about: i) growth profile ii) enzymes profile iii) isoforms. Growth profile shows that this fungus doesn't have ability to accumulate lipid more than 6% while bio mass are around 10g/l in spite of the presence of glucose in the media till the end of cultivation time and excision of nitrogen within 24 hrs. In enzyme study, we investigate all lipogenic enzymes Malic enzyme (ME), Fatty acid synthase (FAS), ATP: Citrate lays (ACL), NAD+ isocitrate dehydrogenase (NAD+ICDH), Glucose-6-phosphate (G6PD), and 6-phosphogluconate dehydrogenase (6PGD), all these enzymes show, ac

Objectives To quantify the reproducibility of the drill calibration process in dynamic navigation guided placement of dental implants and to identify the human factors that could affect the precision of this process in order to improve the overall implant placement accuracy. Methods A set of six drills and four implants were calibrated by three operators following the standard calibration process of NaviDent® (ClaroNav Inc.). The reproducibility of the position of each tip of a drill or implant was calculated in relation to the pre-planned implants’ entry and apex positions. Intra- and inter-operator reliabilities were reported. The effects of the drill length and shape on the reproducibility of the calibration process were also investig