Customized Versus Noncustomized Sound Therapy for Treatment of Tinnitus: A Randomized Crossover Clinical Trial.

ObjectivesTo determine the effectiveness of a customized sound therapy and compare its effectiveness to that of masking with broadband noise.MethodsSubjects were randomized to receive either customized sound therapy or broadband noise for 2 hours per day for 3 months and then switched to the other treatment after a washout period. The outcome variables were tinnitus loudness (scored 0-10), Tinnitus Handicap Inventory (THI), Beck Anxiety Inventory (BAI), minimum masking levels (MML), and residual inhibition (RI).ResultsEighteen subjects completed the study. Mean age was 53 ± 11 years, and mean tinnitus duration was 118 ± 99 months. With customized sound therapy, mean loudness decreased from 6.4 ± 2.0 to 4.9 ± 1.9 ( P = .001), mean THI decreased from 42.8 ± 21.6 to 31.5 ± 20.3 ( P < .001), mean BAI decreased from 10.6 ± 10.9 to 8.3 ± 9.9 ( P = .01), and MML decreased from 22.3 ± 11.6 dB SL to 17.2 ± 10.6 dB SL ( P = .005). After 3 months of broadband noise therapy, only BAI and, to a lesser degree, MML decreased ( P = .003 and .04, respectively).ConclusionsCustomized sound therapy can decrease the loudness and THI scores of tinnitus patients, and the results may be superior to broadband noise

Research and Development Aspects on Chemical Preparation Techniques of Photoanodes for Dye Sensitized Solar Cells

The importance of dye sensitized solar cells (DSSCs) as a low-cost and environmentally friendly photovoltaic (PV) technology has prompted many researchers to improve its efficiency and durability. The realization of these goals is impossible without taking into account the importance of the materials in DSSCs, so the focus on the preparation/deposition methods is essential. These methods can be either chemical or physical. In this study, the chemical applied methods that utilize chemical reaction to synthesize and deposit the materials are covered and categorized according to their gas phase and liquid phase precursors. Film processing techniques that can be used to enhance the materials' properties postpreparation are also included for further evaluation in this study. However, there is a variety of consideration, and certain criteria must be taken into account when selecting a specific deposition method, due to the fact that the fabrication conditions vary and are unoptimized

A scalable method for parallelizing sampling-based motion planning algorithms

Abstract—This paper describes a scalable method for paral-lelizing sampling-based motion planning algorithms. It subdi-vides configuration space (C-space) into (possibly overlapping) regions and independently, in parallel, uses standard (sequen-tial) sampling-based planners to construct roadmaps in each region. Next, in parallel, regional roadmaps in adjacent regions are connected to form a global roadmap. By subdividing the space and restricting the locality of connection attempts, we reduce the work and inter-processor communication associated with nearest neighbor calculation, a critical bottleneck for scalability in existing parallel motion planning methods. We show that our method is general enough to handle a variety of planning schemes, including the widely used Probabilistic Roadmap (PRM) and Rapidly-exploring Random Trees (RRT) algorithms. We compare our approach to two other existing parallel algorithms and demonstrate that our approach achieves better and more scalable performance. Our approach achieves almost linear scalability on a 2400 core LINUX cluster and on a 153,216 core Cray XE6 petascale machine. I

Genomic Classifier Augments the Role of Pathological Features in Identifying Optimal Candidates for Adjuvant Radiation Therapy in Patients With Prostate Cancer: Development and Internal Validation of a Multivariable Prognostic Model.

Purpose Despite documented oncologic benefit, use of postoperative adjuvant radiotherapy (aRT) in patients with prostate cancer is still limited in the United States. We aimed to develop and internally validate a risk-stratification tool incorporating the Decipher score, along with routinely available clinicopathologic features, to identify patients who would benefit the most from aRT. Patient and Methods Our cohort included 512 patients with prostate cancer treated with radical prostatectomy at one of four US academic centers between 1990 and 2010. All patients had ≥ pT3a disease, positive surgical margins, and/or pathologic lymph node invasion. Multivariable Cox regression analysis tested the relationship between available predictors (including Decipher score) and clinical recurrence (CR), which were then used to develop a novel risk-stratification tool. Our study adhered to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines for development of prognostic models. Results Overall, 21.9% of patients received aRT. Median follow-up in censored patients was 8.3 years. The 10-year CR rate was 4.9% vs. 17.4% in patients treated with aRT versus initial observation ( P \u3c .001). Pathologic T3b/T4 stage, Gleason score 8-10, lymph node invasion, and Decipher score \u3e 0.6 were independent predictors of CR (all P \u3c .01). The cumulative number of risk factors was 0, 1, 2, and 3 to 4 in 46.5%, 28.9%, 17.2%, and 7.4% of patients, respectively. aRT was associated with decreased CR rate in patients with two or more risk factors (10-year CR rate 10.1% in aRT v 42.1% in initial observation; P = .012), but not in those with fewer than two risk factors ( P = .18). Conclusion Using the new model to indicate aRT might reduce overtreatment, decrease unnecessary adverse effects, and reduce risk of CR in the subset of patients (approximately 25% of all patients with aggressive pathologic disease in our cohort) who benefit from this therapy