Assessment of Bone Dimensions in the Anterior Maxilla: A Cone Beam Computed Tomography Study.

PURPOSE: To evaluate labial and palatal bone thickness at the maxillary anterior teeth as well as distance from cemento-enamel junction (CEJ) to bone crest using cone beam computed tomography (CBCT). MATERIALS AND METHODS: Measurements were obtained for maxillary anterior teeth of 120 subject CBCT volumes including thickness of labial and palatal plates of bone (coronal, middle, and apical thirds), and distance between CEJ and alveolar bone crest mid-labially, mesially, and distally. RESULTS: The mean value of bone thickness at coronal, middle, and apical thirds of the labial side for central incisor roots were respectively: 0.73, 0.69, 0.60 (mm), for lateral incisors: 0.70, 0.61, 0.49 (mm), and for canines: 0.74, 0.53, 040 (mm). The thickness of palatal bone was significantly larger. The mean distance between CEJ and mid-labial bone crest for all sites was 2.16 mm. CONCLUSION: Labial bone thickness is thin in the vast majority of maxillary anterior teeth. Use of CBCT facilitates planning for immediate implant placement and is helpful in the decision-making process when further bone augmentation is needed.

Evaluation of Bias Correction Method for Satellite-Based Rainfall Data.

With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.

Assessment of a Spatiotemporal Deep Learning Approach for Soil Moisture Prediction and Filling the Gaps in Between Soil Moisture Observations.

Soil moisture (SM) plays a significant role in determining the probability of flooding in a given area. Currently, SM is most commonly modeled using physically-based numerical hydrologic models. Modeling the natural processes that take place in the soil is difficult and requires assumptions. Besides, hydrologic model runtime is highly impacted by the extent and resolution of the study domain. In this study, we propose a data-driven modeling approach using Deep Learning (DL) models. There are different types of DL algorithms that serve different purposes. For example, the Convolutional Neural Network (CNN) algorithm is well suited for capturing and learning spatial patterns, while the Long Short-Term Memory (LSTM) algorithm is designed to utilize time-series information and to learn from past observations. A DL algorithm that combines the capabilities of CNN and LSTM called ConvLSTM was recently developed. In this study, we investigate the applicability of the ConvLSTM algorithm in predicting SM in a study area located in south Louisiana in the United States. This study reveals that ConvLSTM significantly outperformed CNN in predicting SM. We tested the performance of ConvLSTM based models by using a combination of different sets of predictors and different LSTM sequence lengths. The study results show that ConvLSTM models can predict SM with a mean areal Root Mean Squared Error (RMSE) of 2.5% and mean areal correlation coefficients of 0.9 for our study area. ConvLSTM models can also provide predictions between discrete SM observations, making them potentially useful for applications such as filling observational gaps between satellite overpasses.

Zoledronic acid and clodronate in the treatment of malignant bone metastases with hypercalcaemia; efficacy and safety comparative study.

The aim of this study is to conduct a comparison study between the efficacy and safety of zoledronic acid and clodronate in malignant hypercalcemia secondary to bone metastases in Egyptian adult patients. This is a prospective observational study conducted 80 patients (40 in each group), who were assigned to receive either zoledronic acid (4 mg over a 30 min infusion) every 3-4 weeks or clodronate (a single dose of 1,500 mg over a 4 h infusion) monthly for 3 months. The primary efficacy analysis was the proportion of patients with at least one skeletal-related event. The safety was assessed based on the frequencies of the reported adverse effects as nausea, vomiting, anemia, etc. The calcium level significantly decreased in both groups. At least one skeletal-related event occurred in 15 (37.5%) patients receiving zoledronic acid and 32 (80%) patients receiving clodronate. Radiotherapy and fractures represented the highest event observed in both groups. At least one adverse event was experienced by 20 (50%) patients treated with zoledronic acid, while 26 (65%) patients on clodronate recorded one or more adverse event. Pyrexia was the most commonly reported side effect and flare phenomena. Both treatment groups were comparable regarding the reported adverse events. Both medications did not show any significant nephrotoxicity detected by elevation in the creatinine level. Zoledronic acid and clodronate have demonstrated clinical utility in the treatment of hypercalcaemia in cancer patients. Zoledronic acid provides a more effective and convenient treatment than clodronate, while both maintaining a similar safety profile.

Single-Pass Composable 3D Lens Rendering and Spatiotemporal 3D Lenses.

We present a new 3D lens rendering technique and a new spatiotemporal lens. Interactive 3D lenses, often called volumetric lenses, provide users with alternative views of data sets within 3D lens boundaries while maintaining the surrounding overview (context). In contrast to previous multipass rendering work, we discuss the strengths, limitations, and performance costs of a single-pass technique especially suited to fragment-level lens effects, such as color mapping, lighting, and clipping. Some object-level effects, such as a data set selection lens, are also incorporated, with each object's geometry being processed once by the graphics pipeline. For a substantial range of effects, our approach supports several composable lenses at interactive frame rates without performance loss during increasing lens intersections or manipulation by a user. Other cases, for which this performance cannot be achieved, are also discussed. We illustrate possible applications of our lens system, including Time Warp lenses for exploring time-varying data sets.

Childhood apraxia of speech and multiple phonological disorders in Cairo-Egyptian Arabic speaking children: language, speech, and oro-motor differences.

Childhood apraxia of speech is a neurological childhood speech-sound disorder in which the precision and consistency of movements underlying speech are impaired in the absence of neuromuscular deficits. Children with childhood apraxia of speech and those with multiple phonological disorder share some common phonological errors that can be misleading in diagnosis. This study posed a question about a possible significant difference in language, speech and non-speech oral performances between children with childhood apraxia of speech, multiple phonological disorder and normal children that can be used for a differential diagnostic purpose. 30 pre-school children between the ages of 4 and 6 years served as participants. Each of these children represented one of 3 possible subject-groups: Group 1: multiple phonological disorder; Group 2: suspected cases of childhood apraxia of speech; Group 3: control group with no communication disorder. Assessment procedures included: parent interviews; testing of non-speech oral motor skills and testing of speech skills. Data showed that children with suspected childhood apraxia of speech showed significantly lower language score only in their expressive abilities. Non-speech tasks did not identify significant differences between childhood apraxia of speech and multiple phonological disorder groups except for those which required two sequential motor performances. In speech tasks, both consonant and vowel accuracy were significantly lower and inconsistent in childhood apraxia of speech group than in the multiple phonological disorder group. Syllable number, shape and sequence accuracy differed significantly in the childhood apraxia of speech group than the other two groups. In addition, children with childhood apraxia of speech showed greater difficulty in processing prosodic features indicating a clear need to address these variables for differential diagnosis and treatment of children with childhood apraxia of speech.