Effect of photo-biomodulation therapy in decreasing postoperative pain after surgical removal of third molars compared to other treatment therapies: a systematic review

Post-operative pain, discomfort, and trismus are common postoperative complications after surgical extraction of third molars. Various therapeutic approaches like prescribing analgesic drugs, corticosteroids, and Non-steroidal anti-inflammatory drugs are followed to reduce these complications. Photo-biomodulation therapy (PBMT) utilizes a monochromatic light source that shows effects in all phases of inflammation by reducing edema, redness, heat, and pain. In vivo studies were searched to evaluate postoperative pain levels in patients who underwent photo-biomodulation therapy following extraction of impacted third molars. A comprehensive search was done from January 2023 to July 2023 in PubMed electronic databases. In addition, a manual search of the references mentioned in the studies and gray literature was done. The literature search yielded a total of 157 studies through a search in the electronic database PubMed. Among all the studies, 51 duplicate records were removed. Ninety-seven studies were removed after screening of titles and abstracts. A total of 9 studies were included for full-text reading. Five studies were included (one randomized single-blind study, two randomized double-blind split-mouth studies, and two randomized clinical trials) in the review. Four out of five studies that were included in this review demonstrated a positive impact of PBMT on reducing pain, especially during the post-operative period compared to other non-surgical treatment protocols. Photo-biomodulation therapy demonstrated an overall positive impact on reducing postoperative complications like edema and trismus

Design Space and Variability Analysis of SOI MOSFET for Ultra-Low Power Band-to-Band Tunneling Neurons

Large spiking neural networks (SNNs) require ultra-low power and low variability hardware for neuromorphic computing applications. Recently, a band-to-band tunneling-based (BTBT) integrator, enabling sub-kHz operation of neurons with area and energy efficiency, was proposed. For an ultra-low power implementation of such neurons, a very low BTBT current is needed, so minimizing current without degrading neuronal properties is essential. Low variability is needed in the ultra-low current integrator to avoid network performance degradation in a large BTBT neuron-based SNN. To address this, we conducted design space and variability analysis in TCAD, utilizing a well-calibrated TCAD deck with experimental data from GlobalFoundries 32nm PD-SOI MOSFET. First, we discuss the physics-based explanation of the tunneling mechanism. Second, we explore the impact of device design parameters on SOI MOSFET performance, highlighting parameter sensitivities to tunneling current. With device parameters' optimization, we demonstrate a ~20x reduction in BTBT current compared to the experimental data. Finally, a variability analysis that includes the effects of random dopant fluctuations (RDF), oxide thickness variability (OTV), and channel-oxide interface traps DIT in the BTBT, SS, and ON regimes of operation is shown. The BTBT regime shows high sensitivity to the RDF and OTV as any variation in them directly modulates the tunnel length or the electric field at the drain-channel junction, whereas minimal sensitivity to DIT is observed

KF-Loc: A Kalman Filter and Machine Learning Integrated Localization System Using Consumer-Grade Millimeter-wave Hardware

With the ever-increasing demands of e-commerce, the need for smarter warehousing is increasing exponentially. Such warehouses requires industry automation beyond Industry 4.0. In this work, we use consumer-grade millimeter-wave (mmWave) equipment to enable fast, and low-cost implementation of our localization system. However, the consumer-grade mmWave routers suffer from coarse-grained channel state information due to cost-effective antenna array design limiting the accuracy of localization systems. To address these challenges, we present a Machine Learning (ML) and Kalman Filter (KF) integrated localization system (KF-Loc). The ML model learns the complex wireless features for predicting the static position of the robot. When in dynamic motion, the static ML estimates suffer from position mispredictions, resulting in loss of accuracy. To overcome the loss in accuracy, we design and integrate a KF that learns the dynamics of the robot motion to provide highly accurate tracking. Our system achieves centimeter-level accuracy for the two aisles with RMSE of 0.35m and 0.37m, respectively. Further, compared with ML only localization systems, we achieve a significant reduction in RMSE by 28.5% and 54.3% within the two aisles

Autonomous Vehicles and Machines Conference, at IS&T Electronic Imaging

The performance of autonomous agents in both commercial and consumer applications increases along with their situational awareness. Tasks such as obstacle avoidance, agent to agent interaction, and path planning are directly dependent upon their ability to convert sensor readings into scene understanding. Central to this is the ability to detect and recognize objects. Many object detection methodologies operate on a single modality such as vision or LiDAR. Camera-based object detection models benefit from an abundance of feature-rich information for classifying different types of objects. LiDAR-based object detection models use sparse point clouds, where each point contains accurate 3D position of object surfaces. Camera-based methods lack accurate object to lens distance measurements, while LiDAR-based methods lack dense feature-rich details. By utilizing information from both camera and LiDAR sensors, advanced object detection and identification is possible. In this work, we introduce a deep learning framework for fusing these modalities and produce a robust real-time 3D bounding box object detection network. We demonstrate qualitative and quantitative analysis of the proposed fusion model on the popular KITTI dataset

Global, regional, and national life expectancy, all-cause mortality, and cause-specific mortality for 249 causes of death, 1980-2015 : a systematic analysis for the Global Burden of Disease Study 2015

Background Improving survival and extending the longevity of life for all populations requires timely, robust evidence on local mortality levels and trends. The Global Burden of Disease 2015 Study (GBD 2015) provides a comprehensive assessment of all-cause and cause-specific mortality for 249 causes in 195 countries and territories from 1980 to 2015. These results informed an in-depth investigation of observed and expected mortality patterns based on sociodemographic measures. Methods We estimated all-cause mortality by age, sex, geography, and year using an improved analytical approach originally developed for GBD 2013 and GBD 2010. Improvements included refinements to the estimation of child and adult mortality and corresponding uncertainty, parameter selection for under-5 mortality synthesis by spatiotemporal Gaussian process regression, and sibling history data processing. We also expanded the database of vital registration, survey, and census data to 14 294 geography-year datapoints. For GBD 2015, eight causes, including Ebola virus disease, were added to the previous GBD cause list for mortality. We used six modelling approaches to assess cause-specific mortality, with the Cause of Death Ensemble Model (CODEm) generating estimates for most causes. We used a series of novel analyses to systematically quantify the drivers of trends in mortality across geographies. First, we assessed observed and expected levels and trends of cause-specific mortality as they relate to the Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. Second, we examined factors affecting total mortality patterns through a series of counterfactual scenarios, testing the magnitude by which population growth, population age structures, and epidemiological changes contributed to shifts in mortality. Finally, we attributed changes in life expectancy to changes in cause of death. We documented each step of the GBD 2015 estimation processes, as well as data sources, in accordance with Guidelines for Accurate and Transparent Health Estimates Reporting (GATHER). Findings Globally, life expectancy from birth increased from 61.7 years (95% uncertainty interval 61.4-61.9) in 1980 to 71.8 years (71.5-72.2) in 2015. Several countries in sub-Saharan Africa had very large gains in life expectancy from 2005 to 2015, rebounding from an era of exceedingly high loss of life due to HIV/AIDS. At the same time, many geographies saw life expectancy stagnate or decline, particularly for men and in countries with rising mortality from war or interpersonal violence. From 2005 to 2015, male life expectancy in Syria dropped by 11.3 years (3.7-17.4), to 62.6 years (56.5-70.2). Total deaths increased by 4.1% (2.6-5.6) from 2005 to 2015, rising to 55.8 million (54.9 million to 56.6 million) in 2015, but age-standardised death rates fell by 17.0% (15.8-18.1) during this time, underscoring changes in population growth and shifts in global age structures. The result was similar for non-communicable diseases (NCDs), with total deaths from these causes increasing by 14.1% (12.6-16.0) to 39.8 million (39.2 million to 40.5 million) in 2015, whereas age-standardised rates decreased by 13.1% (11.9-14.3). Globally, this mortality pattern emerged for several NCDs, including several types of cancer, ischaemic heart disease, cirrhosis, and Alzheimer's disease and other dementias. By contrast, both total deaths and age-standardised death rates due to communicable, maternal, neonatal, and nutritional conditions significantly declined from 2005 to 2015, gains largely attributable to decreases in mortality rates due to HIV/AIDS (42.1%, 39.1-44.6), malaria (43.1%, 34.7-51.8), neonatal preterm birth complications (29.8%, 24.8-34.9), and maternal disorders (29.1%, 19.3-37.1). Progress was slower for several causes, such as lower respiratory infections and nutritional deficiencies, whereas deaths increased for others, including dengue and drug use disorders. Age-standardised death rates due to injuries significantly declined from 2005 to 2015, yet interpersonal violence and war claimed increasingly more lives in some regions, particularly in the Middle East. In 2015, rotaviral enteritis (rotavirus) was the leading cause of under-5 deaths due to diarrhoea (146 000 deaths, 118 000-183 000) and pneumococcal pneumonia was the leading cause of under-5 deaths due to lower respiratory infections (393 000 deaths, 228 000-532 000), although pathogen-specific mortality varied by region. Globally, the effects of population growth, ageing, and changes in age-standardised death rates substantially differed by cause. Our analyses on the expected associations between cause-specific mortality and SDI show the regular shifts in cause of death composition and population age structure with rising SDI. Country patterns of premature mortality (measured as years of life lost [YLLs]) and how they differ from the level expected on the basis of SDI alone revealed distinct but highly heterogeneous patterns by region and country or territory. Ischaemic heart disease, stroke, and diabetes were among the leading causes of YLLs in most regions, but in many cases, intraregional results sharply diverged for ratios of observed and expected YLLs based on SDI. Communicable, maternal, neonatal, and nutritional diseases caused the most YLLs throughout sub-Saharan Africa, with observed YLLs far exceeding expected YLLs for countries in which malaria or HIV/AIDS remained the leading causes of early death. Interpretation At the global scale, age-specific mortality has steadily improved over the past 35 years; this pattern of general progress continued in the past decade. Progress has been faster in most countries than expected on the basis of development measured by the SDI. Against this background of progress, some countries have seen falls in life expectancy, and age-standardised death rates for some causes are increasing. Despite progress in reducing age-standardised death rates, population growth and ageing mean that the number of deaths from most non-communicable causes are increasing in most countries, putting increased demands on health systems. Copyright (C) The Author(s). Published by Elsevier Ltd.Peer reviewe