Evaluation of accuracy of complete-arch multiple-unit abutment-level dental implant impressions using different impression and splinting materials.

Purpose: This in vitro study evaluated the accuracy of multiple-unit dental implant casts obtained from splinted or nonsplinted direct impression techniques using various splinting materials by comparing the casts to the reference models. The effect of two different impression materials on the accuracy of the implant casts was also evaluated for abutment-level impressions. Materials and Methods: A reference model with six internal-connection implant replicas placed in the completely edentulous mandibular arch and connected to multi-base abutments was fabricated from heat-curing acrylic resin. Forty impressions of the reference model were made, 20 each with polyether (PE) and polyvinylsiloxane (PVS) impression materials using the open tray technique. The PE and PVS groups were further subdivided into four subgroups of five each on the bases of splinting type: no splinting, bite registration PE, bite registration addition silicone, or autopolymerizing acrylic resin. The positional accuracy of the implant replica heads was measured on the poured casts using a coordinate measuring machine to assess linear differences in interimplant distances in all three axes. The collected data (linear and three-dimensional [3D] displacement values) were compared with the measurements calculated on the reference resin model and analyzed with nonparametric tests (Kruskal-Wallis and Mann-Whitney). Results: No significant differences were found between the various splinting groups for both PE and PVS impression materials in terms of linear and 3D distortions. However, small but significant differences were found between the two impression materials (PVS, 91 mu m; PE, 103 mu m) in terms of 3D discrepancies, irrespective of the splinting technique employed. Conclusions: Casts obtained from both impression materials exhibited differences from the reference model. The impression material influenced impression inaccuracy more than the splinting material for multiple-unit abutment-level impressions.Article Link : http://www.ncbi.nlm.nih.gov/pubmed/2427891

Pemodelan Struktur Perlapisan Bawah Permukaan untuk Penentuan Bidang Gelincir pada Daerah Rawan Longsor. (Studi Kasus Ruas Jalan Nasional 005 Lakuan – Laulalang dan Ruas 006 Laulalang-Lingadan)

Characteristics of roads in Central Sulawesi at some point are an area of frequent landslides. The road segment in question, including the section 005 and section 006 which is a national road linking the province of Central Sulawesi and Gorontalo province. The link conditions that have often suffered landslides have disrupted access to transport and causing high transportation costs. This study aims to determine the geometry of the sliding plane at KM 509 and KM 513 using the method of geoelectric resistivity Wenner configuration with a path length measurement of 300 m and 5 m electrode spacing. The results of the study at two locations and modeling shows the layering structure resistivity value of which is at 100 Ωm - 300 Ωm and modeling results of 2-D geoelectric cross-section shows the sliding plane ground motion varies between 5 to 15 m. Value of resistance and sectional sliding obtained indicate that the location is vulnerable to landslides, and requires a comprehensive treatment to prevent landslides

Halalnet: A Deep Neural Network That Classifies the Halalness of Slaughtered Chicken from Their Images

Halal requirement in food is important for millions of Muslims worldwide especially for meat and chicken products, insuring that slaughter houses adhere to this requirement is a challenging task to do manually. In this paper a method is proposed that uses a camera that takes images of slaughtered chicken on the conveyor in a slaughter house, the images are then analyzed by a deep neural network to classify if the image is of a halal slaughtered chicken or not. However, traditional deep learning models require large amounts of data to train on, which in this case these amounts of data were challenging to collect especially the images of non-halal slaughtered chicken, hence this paper shows how the use of one shot learning (Lake, Brenden, Salakhutdinov, Ruslan, Gross & Jas, 2011) and transfer learning (Yosinski, Clune, Bengio & Lipson, 2014) can reach high accuracy on the few amounts of data that were available. The architecture used is based on the Siamese neural networks architecture which ranks the similarity between two inputs (Koch, Zemel & Salakhutdinov, 2015) while using the Xception network (Chollet, 2017) as the twin networks. We call it HalalNet. This work was done as part of SYCUT (syriah compliant slaughtering system) which is a monitoring system that monitors the halalness of the slaughtered chicken in a slaughter house. The data used to train and validate HalalNet was collected from the Azain slaughtering site (Semenyih, Selangor, Malaysia) containing images of both halal and non-halal slaughtered chicken

The Development Of High Temperature Recirculating Pump (HTRP) For Energy Savings In An Incinerator.

Tremendous increase ingeneration of Municipal Solid Waste (MSW) has become a major concern for the Malaysian government as the country experiencing rapid development. It was estimated about 16000 tones/day MSW is produced at national level and in Kuala Lumpur alone about 2500 tones/day

Microcrystalline Cellulose (MCC) from Oil Palm Empty Fruit Bunch (EFB) Fiber via Simultaneous Ultrasonic and Alkali Treatment

In this study, microcrystalline cellulose (MCC) was extracted from oil palm empty fruit bunch (EFB) cellulose which was earlier isolated from oil palm EFB fibre. In order to isolate the cellulose, the chlorination method was carried out. Then, the MCC was prepared by simultaneous ultrasonic and alkali treatment from the isolated α-cellulose. Based on mass balance calculation, the yields for MCC obtained from EFB was 44%. For fiber characterization, it is observed that the chemical composition of the hemicellulose and lignin for all samples decreased while composition for cellulose increased. The structural property of the MCC was studied by X-ray diffraction (XRD) method and the result shows that the MCC produced is a cellulose-I polymorph, with 73% crystallinity