Detection and localization of Goliath grouper using their low-frequency pulse sounds.

The goal of this paper is to implement and deploy an automated detector and localization model to locate underwater marine organisms using their low-frequency pulse sounds. This model is based on time difference of arrival (TDOA) and uses a two-stage approach, first, to identify the sound and, second, to localize it. In the first stage, an adaptive matched filter (MF) is designed and implemented to detect and determine the timing of the sound pulses recorded by the hydrophones. The adaptive MF measures the signal and noise levels to determine an adaptive threshold for the pulse detection. In the second stage, the detected sound pulses are fed to a TDOA localization algorithm to compute the locations of the sound source. Despite the uncertainties stemming from various factors that might cause errors in position estimates, it is shown that the errors in source locations are within the dimensions of the array. Further, our method was applied to the localization of Goliath grouper pulse-like calls from a six-hydrophone array. It was revealed that the intrinsic error of the model was about 2 m for an array spanned over 50 m. This method can be used to automatically process large amount of acoustic data and provide a precise description of small scale movements of marine organisms that produce low-frequency sound pulses.

Deep Learning Technology to Recognize American Sign Language Alphabet.

Historically, individuals with hearing impairments have faced neglect, lacking the necessary tools to facilitate effective communication. However, advancements in modern technology have paved the way for the development of various tools and software aimed at improving the quality of life for hearing-disabled individuals. This research paper presents a comprehensive study employing five distinct deep learning models to recognize hand gestures for the American Sign Language (ASL) alphabet. The primary objective of this study was to leverage contemporary technology to bridge the communication gap between hearing-impaired individuals and individuals with no hearing impairment. The models utilized in this research include AlexNet, ConvNeXt, EfficientNet, ResNet-50, and VisionTransformer were trained and tested using an extensive dataset comprising over 87,000 images of the ASL alphabet hand gestures. Numerous experiments were conducted, involving modifications to the architectural design parameters of the models to obtain maximum recognition accuracy. The experimental results of our study revealed that ResNet-50 achieved an exceptional accuracy rate of 99.98%, the highest among all models. EfficientNet attained an accuracy rate of 99.95%, ConvNeXt achieved 99.51% accuracy, AlexNet attained 99.50% accuracy, while VisionTransformer yielded the lowest accuracy of 88.59%.

A randomized, double-blind, placebo-controlled, crossover trial of "on-demand" tramadol for treatment of premature ejaculation.

OBJECTIVES: The objective of this study is to assess the dose-related effects of tramadol on a group of patients with premature ejaculation (PE). SUBJECTS AND METHODS: During the period of months between June 2010 and July 2012, 180 PE patients presented to outpatient clinic of our hospital. Patients were randomized in a 1:1:1 fashion to receive different sequences of the three medications: placebo, 50 mg of tramadol and 100 mg of tramadol. Every patient received 10 doses of each medication for 2 months. Intra-vaginal ejaculatory latency time (IELT) was recorded in seconds initially and for each arm. Successful treatment of PE is defined if IELT exceeded 120 s. Side-effects of medications were reported. RESULTS: Of patients enrolled, 125 (69.4%) continued the study. Patients' age range was 20-55 years with PE complaint of 1 to 10 years duration. Mean IELT was 72 at presentation, 82 for placebo, 150 for tramadol 50 mg, and 272 for tramadol 100 mg (P < 0.001 for all comparisons). PE was successfully treated in only 2.4% of patients with placebo, in contrast to 53.6% and 85.6% with 50 and 100 mg tramadol, respectively (P < 0.001 for all comparisons). On multivariate logistic regression analysis, baseline IELT was the only predictor of successful treatment of PE with both tramadol 50 mg (odds ratio [OR]: 1.05, 95% confidence interval [CI]: 1.03-1.07, P < 0.001) and tramadol 100 mg (OR: 1.07, 95% CI: 1.04-1.11, P < 0.001). Postmicturition dribble annoyed 12.8% of those who received 50 mg tramadol and 33.6% of those who received 100 mg tramadol (P < 0.001). Weak scanty ejaculation was the main complaint in 7.2% versus 21.6% of those using 50 and 100 mg tramadol, respectively (P = 0.002). Two patients discontinued tramadol 100 mg due to side-effects. CONCLUSION: Tramadol hydrochloride exhibits a significant dose-related efficacy and side-effects over placebo for treatment of PE.

Hyperuricemia: a possible cause of hemospermia.

OBJECTIVE: To report our experience with hemospermia and its relation to hyperuricemia. PATIENTS AND METHODS: Between July 2005 and July 2012, 143 patients with hemospermia presented to the outpatient clinic in our hospital. History, examination, workup, treatment outcomes, and long-term follow-up were reported in a prospective database. Patients were followed up monthly by semen examination till disappearance of hemospermia, then every 3 months for 1 year. We identified 43 patients, who had 4-12 hemospermia attacks for 2-10 months before presentation with no identifiable cause for hemospermia. Of them, 22 had hyperuricemia. The association between hemospermia and hyperuricemia was examined by comparing such 22 hyperuricemic hemospermic patients with the other 21 idiopathic hemospermic patients. RESULTS: The commonest 5 findings identified as possible causes of hemospermia were bilharziasis (21.6%), hyperuricemia (15.4%), idiopathic (14.7%), tuberculosis (8.4%), and chronic prostatitis (8.4%). Hyperuricemic hemospermic patients were significantly of younger age (median of 31.5 vs 45 years), complaining of more painful ejaculation (68.2% vs 9.5%), and had higher serum uric acid (median, 9.3 vs 4.5 mg/dL) compared with those of idiopathic hemospermia. Hemospermia disappeared completely in all patients of the hyperuricemia group vs only 25% of the idiopathic group (P <.001) within a mean of 2 months (range, 1-4 months). CONCLUSION: Hyperuricemia is a new probable cause of hemospermia. Further randomized studies are mandatory for establishment of our postulation.