Atmospheric and Space Technology Research Associates (United States)

This paper investigates the optimization of Truncated Backpropagation Through Time (TBPTT) for training neural networks in digital audio effect modeling, with a focus on dynamic range compression. The study evaluates key TBPTT hyperparameters -- sequence number, batch size, and sequence length -- and their influence on model performance. Using a convolutional-recurrent architecture, we conduct extensive experiments across datasets with and without conditionning by user controls. Results demonstrate that carefully tuning these parameters enhances model accuracy and training stability, while also reducing computational demands. Objective evaluations confirm improved performance with optimized settings, while subjective listening tests indicate that the revised TBPTT configuration maintains high perceptual quality.

This paper presents a sentiment analysis of user reviews on the Uknow.AI platform, an AI-powered educational tool aimed at assisting students in solving mathematical problems through image recognition. The study utilized a Support Vector Machine (SVM) model to classify user reviews into positive, negative, and neutral sentiments. Data was collected from user reviews on platforms like Google Play, followed by pre-processing steps including tokenization and Term Frequency-Inverse Document Frequency (TF-IDF) for feature extraction. The SVM model was evaluated based on performance metrics such as accuracy, precision, recall, and F1-score. The model achieved an accuracy of 93.42% with a recall of 99.70%, indicating robust performance in sentiment classification. Word cloud visualizations also highlighted dominant positive terms like "bagus" (good) and "membantu" (helpful), emphasizing the overall satisfaction with Uknow.AI's functionality. The study found that 92.6% of the reviews were positive, reflecting the tool’s effectiveness in enhancing student learning. Future research can focus on further improving user experience by addressing any shortcomings.

The development of the Fourth Industry is driving the manufacturing industry towards the era of smart manufacturing. In this transformation, various existing equipment, machines, processes, or devices are reinstalled with various sensors, computing, and other cyber-physical systems. In the current era of Industry 4.0, the automotive manufacturing industry continues to move towards sustainable development in a digital process framework so that real-time control and monitoring can be carried out. This study aims to reduce energy consumption and carbon emissions in the automotive manufacturing industry through the implementation of a PLC-based control and monitoring system. This system uses PLC and HMI for Industrial Fan control automation. The methodology used includes collecting energy consumption data through a power meter before and after system implementation, then analyzing the data to evaluate energy savings. The results of the study show that the system is able to reduce energy consumption by 20%, equivalent to savings of 122.66496 kWh per year, and reduce carbon emissions by 10.672 TCO2 per year. The implementation of this system supports energy efficiency and contributes to the achievement of the Sustainable Development Goals target.

Permo (Motor Company) Industry is one of the companies that operates in the automotive industry, especially motorcycles. The production process in Permo Industry requires machines to support its production process. Among all production engines, the auto front wheel is the engine with the highest downtime rate. The high downtime of the auto front wheel engine is due to an engine failure of 12,000 seconds, or 200 minutes. To reduce downtime, the study included a timetable for checking and preventive replacement of components. The aim of the research is to reduce downtime due to damage to engine components so that production runs smoothly. This step of improvement uses Plan, Do, Check, Action. (PDCA). The results of this study can eliminate 100% of the downtime damage to spring pin press bearing components. The study resulted in an average replacement of spring pin press bearing components every 18 days, a standard using spring pin press bearing components (80.621 shoot), and monitoring of spring p pinpress b bearingcomponents 14 days after replacement.

Depression is associated with lower adherence to oral pre-exposure prophylaxis (PrEP) to prevent HIV, but data are not currently available on how depression may affect use of other HIV prevention methods including the dapivirine vaginal ring (DVR). We conducted a mixed methods study using data from the Microbicide Trials Network (MTN) 042/DELIVER (n = 558) and MTN-043/B-PROTECTED (n = 197) studies to describe the prevalence of depressive symptoms and explore how depressive symptoms may have influenced attitudes about use of the monthly DVR and once-daily oral PrEP tablet among pregnant and breastfeeding persons, respectively, in Malawi, South Africa, Uganda, and Zimbabwe. Eleven participants had high Edinburgh Postnatal Depression scores ≥ 10 in MTN-042/DELIVER (2%) and four participants (2%) in MTN-043/B-PROTECTED. In interviews with 9 participants who had high scores (6 DVR, 3 oral PrEP), those with depressive symptoms described overlapping stressors which were magnified by job loss and economic instability during the COVID-19 pandemic, and by experiences of pregnancy/postpartum. These participants experienced a lack of support from partners or family members, and conflict with partners related to trust, and infidelity. While we did not find evidence of a change in product adherence, there was a strong sense of commitment and motivation to use the study products for protection from HIV for participants themselves and their baby. Although lack of social support is usually an obstacle to adherence, in this study, the participants' lives and relationships seemed to have reinforced the need for HIV prevention and motivated women to protect themselves and their babies from HIV.

IntroductionTenofovir‐based oral pre‐exposure prophylaxis is currently approved for HIV prevention; however, adherence in women has been low. A vaginal gel containing tenofovir (TFV) demonstrated partial protection to HIV but protection was not confirmed in additional studies. Vaginal rings offer user‐controlled long‐acting HIV prevention that could overcome adherence and protection challenges. TFV may also help prevent herpes simplex virus type 2 acquisition when delivered intravaginally. We evaluated the pharmacokinetics, safety, adherence and acceptability of a 90‐day TFV ring.MethodsBetween January and June 2019, Microbicide Trials Network (MTN)‐038 enrolled 49 HIV‐negative participants into a phase 1, randomized (2:1) trial comparing a 90‐day ring containing 1.4 grams (g) TFV to a placebo ring. TFV concentrations were quantified in plasma, cervicovaginal fluid (CVF), rectal fluid and cervical tissue, and TFV‐diphosphate (TFV‐DP) in cervical tissue. Used rings were analysed for residual TFV. Safety was assessed by adverse events (AEs); acceptability and adherence by self‐report.ResultsMean age was 29.5; 46 identified as cisgender‐female and three gender non‐conforming. There were no differences in the proportion of participants with grade ≥2 genitourinary AEs in the TFV versus placebo arms (p = 0.41); no grade ≥3 AEs were reported. Geometric mean TFV concentrations increased through day 34 in CVF/rectal fluid and day 59 in plasma, but declined across compartments by day 91. Geometric mean TFV‐DP tissue concentrations exceeded the 1000 fmol/mg target through day 56, but fell to 456 fmol/mg at day 91. Among 32 rings returned at the end of the study, 13 had no or low (<0.1 g) residual TFV. Residual TFV did not differ by socio‐demographics, sexual activity, Nugent Score or vaginal microbiota. Most participants reported being fully adherent to ring use: 85% and 81% in the TFV and placebo arms, respectively (p = 1.00). A majority of participants reported liking the ring (median 8 on a 10‐point Likert scale) and reported a high likelihood of using the ring in the future, if effective (median 9).ConclusionsThe 90‐day TFV ring was well‐tolerated, acceptable and exceeded target cervical tissue concentrations through day 56, but declined thereafter. Additional studies are needed to characterize the higher release from TFV rings in some participants and the optimal duration of use.

The Event Horizon Telescope (EHT) is a millimeter very long baseline interferometry (VLBI) array that has imaged the apparent shadows of the supermassive black holes M87* and Sagittarius A*. Polarimetric data from these observations contain a wealth of information on the black hole and accretion flow properties. In this work, we develop polarimetric geometric modeling methods for mm-VLBI data, focusing on approaches that fit data products with differing degrees of invariance to broad classes of calibration errors. We establish a fitting procedure using a polarimetric “m-ring” model to approximate the image structure near a black hole. By fitting this model to synthetic EHT data from general relativistic magnetohydrodynamic models, we show that the linear and circular polarization structure can be successfully approximated with relatively few model parameters. We then fit this model to EHT observations of M87* taken in 2017. In total intensity and linear polarization, the m-ring fits are consistent with previous results from imaging methods. In circular polarization, the m-ring fits indicate the presence of event-horizon-scale circular polarization structure, with a persistent dipolar asymmetry and orientation across several days. The same structure was recovered independently of observing band, used data products, and model assumptions. Despite this broad agreement, imaging methods do not produce similarly consistent results. Our circular polarization results, which imposed additional assumptions on the source structure, should thus be interpreted with some caution. Polarimetric geometric modeling provides a useful and powerful method to constrain the properties of horizon-scale polarized emission, particularly for sparse arrays like the EHT.