Computer Evaluation of Real-Time X-Ray and Acoustic Images

The weakest link in the inspection process is the subjective interpretation of data by inspectors. To overcome this troublesome fact computer based analysis systems have been developed. In the field of nondestructive evaluation (NDE) there is a large class of inspections that can benefit from computer analysis. X-ray images (both film and fluoroscopic) and acoustic images lend themselves to automatic analysis as do the one-dimensional signals associated with ultrasonic, eddy current and acoustic emission testing. Computer analysis can enhance and evaluate subtle details. Flaws can be located and measured, and acceptance decisions made by computer in a consistent and objective manner. This paper describes the interactive, computer-based analysis of real-time x-ray images and acoustic images of graphite/epoxy adhesively bonded structures

Collegiate Competition and the Propensity for Gender Bias

Since the dawn of time gender has played a starring role in human behavior. The behavioral implications of an individual’s sex have permeated research findings in a wide variety of academic disciplines. This preliminary investigation will explore the concept and definition of gender, gender bias, and gender stereotype on actions and conduct. Specifically, this inquiry will determine the scope and types of gender bias/stereotypes that exist in the business world with a primary concentration on the area of professional sales. The ultimate objective is to discover the type and level of influence a person’s gender contributes to evaluation, performance and judging in student sales competition

Mammalian Cell-Derived Vesicles for the Isolation of Organelle Specific Transmembrane Proteins to Conduct Single Molecule Studies

Cell-derived vesicles facilitate the isolation of transmembrane proteins in their physiological membrane maintaining their structural and functional integrity. These vesicles can be generated from different cellular organelles producing, housing, or transporting the proteins. Combined with single molecule imaging, isolated organelle specific vesicles can be employed to study the trafficking and assembly of the embedded proteins. Here we present a method for organelle specific single molecule imaging via isolation of ER and plasma membrane vesicles from HEK293T cells by employing OptiPrep gradients and nitrogen cavitation. The isolation was validated through Western blotting, and the isolated vesicles were used to perform single molecule studies of oligomeric receptor assembly

A COMPARISON OF THE EFFECTIVENESS OF THE “TOOTHKEEPER’ AND A TRADITIONAL DENTAL HEALTH EDUCATION PROGRAM

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66303/1/j.1752-7325.1975.tb04031.x.pd

Hubungan antara Motivasi dan Self-regulated Learning Siswa Selama Pembelajaran Jarak Jauh di Kota Kupang

Penerapan  pembelajaran  jarak  jauh  di  sekolah-sekolah  merupakan  hal  baru  bagi siswa dan guru, butuh waktu bagi siswa dan guru untuk beradaptasi. Keberhasilan pelaksanaan pembelajaran jarak jauh dipengaruhi oleh banyak faktor. Beberapa faktor yang mempengaruhi adalah motivasi dan self regulated learning. Penelitian ini bertujuan untuk mengetahui hubungan antara motivasi dengan self regulated learning siswa selama pembelajaran jarak jauh di kota kupang. Penelitian ini berjenis korelasional dengan pendekatan kuantitatif. Instrumen penelitian menggunakan kuesioner self regulated learning Jansen et al., (2017) dan kuesioner motivasi Garcia (1996). Responden dalam penelitian ini berjumlah 178 siswa di kota Kupang yang berasal dari jenjang pendidikan Sekolah Dasar, Sekolah Menengah Pertama, dan Sekolah Menengah Atas. Teknik analisis data menggunakan korelasi product moment. Hasil penelitian menunjukkan bahwa terdapat hubungan signifikan dan positif antara motivasi dengan self regulated learning dengan besar koefisien korelasi 0.780. Uji  koefisien  determinasi  menunjukkan  motivasi menjadi prediktor self regulated learning sebesar 0.608 atau 60,8%. Penelitian ini menyimpulkan bahwa terdapat hubungan antara motivasi dengan self regulated learning siswa selama pembelajaran jarak jauh di kota kupang

The effects of a tea tree oil-containing gel on plaque and chronic gingivitis

The document attached has been archived with permission from the Australian Dental Association. An external link to the publisher’s copy is included.Background: This clinical study assessed the effects of topically applied tea tree oil (TTO)-containing gel on dental plaque and chronic gingivitis. Methods: This was a double-blind, longitudinal, non-crossover study in 49 medically fit non-smokers (24 males and 25 females) aged 18–60 years with severe chronic gingivitis. Subjects were randomly assigned to three groups and given either TTO-gel (2.5 per cent), chlorhexidine (CHX) gel (0.2 per cent), or a placebo gel to apply with a toothbrush twice daily. Treatment effects were assessed using the Gingival Index (GI), Papillary Bleeding Index (PBI) and plaque staining score (PSS) at four and eight weeks. Results: No adverse reactions to any of the gels were reported. The data were separated into subsets by tooth (anterior and posterior) and tooth surface (buccal and lingual). The TTO group had significant reduction in PBI and GI scores. However, TTO did not reduce plaque scores, which tended to increase over the latter weeks of the study period. Conclusion: Although further studies are required, the anti-inflammatory properties of TTO-containing gel applied topically to inflamed gingival tissues may prove to be a useful non-toxic adjunct to chemotherapeutic periodontal therapy.S Soukoulis and R Hirsc

Temporal Recurrent Networks for Online Action Detection

Most work on temporal action detection is formulated as an offline problem, in which the start and end times of actions are determined after the entire video is fully observed. However, important real-time applications including surveillance and driver assistance systems require identifying actions as soon as each video frame arrives, based only on current and historical observations. In this paper, we propose a novel framework, Temporal Recurrent Network (TRN), to model greater temporal context of a video frame by simultaneously performing online action detection and anticipation of the immediate future. At each moment in time, our approach makes use of both accumulated historical evidence and predicted future information to better recognize the action that is currently occurring, and integrates both of these into a unified end-to-end architecture. We evaluate our approach on two popular online action detection datasets, HDD and TVSeries, as well as another widely used dataset, THUMOS'14. The results show that TRN significantly outperforms the state-of-the-art