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This contemporary review delves into the intricate realm of temporomandibular joint (TMJ) function and dysfunction, shedding light on its multifaceted nature and offering insights into diagnostic and therapeutic strategies. The TMJ, a vital component of the craniofacial complex, plays a pivotal role in everyday activities such as chewing, speaking, and yawning. Understanding its anatomy and physiology is paramount in the treatment and management of TMJ dysfunction. The biomechanics of TMJ function, from the articular disc to the surrounding ligaments and muscles, have been explored comprehensively. A critical aspect of this review revolves around the diverse etiological factors contributing to TMJ dysfunction. Genetic predispositions, parafunctions, occlusal irregularities, and psychological stress are dissected to illuminate the roles of these factors in the development of TMJ disorders. These complexities prompted the need for a robust classification system elucidating the clinical manifestations and diagnostic criteria for various TMJ disorders. Modern diagnostic modalities, including clinical assessment, imaging techniques, and joint aspiration, are scrutinized for their indispensable roles in accurate diagnosis. The comprehensive overview included management strategies, from conservative measures to surgical interventions. In recognizing the pivotal influence of psychosocial factors, this review underscores the importance of patient-centered care and cognitive-behavioral interventions. Furthermore, regenerative therapies, minimally invasive techniques, and personalized medicine are emerging trends in TMJ research. This review provides a contemporary roadmap for comprehending, diagnosing, and managing TMJ-related conditions.

In this modern world, almost everyone uses ATM machines which allow people to transfer and withdraw cash. This study is based on executing a fingerprint method in the ATM System. We chose this field to improve safety and security for people to make the transaction easier. The fingerprints are unique for each person. There is no insecurity of losing an ATM card and no requirement to carry an ATM card with you every time. On comparison of different technologies for ATM security, the fingerprint technology operates better and safer than others. These reasons make this mechanism an effortless and secure way of transaction and also maintains a coherent ambience with users and ATM machines. This is the most latest technology in electronic cash transactions.

The Suomi National Polar‐orbiting Partnership (NPP) satellite was successfully launched on 28 October 2011. On board the Suomi NPP, the Advanced Technology Microwave Sounder (ATMS) is a cross‐track scanning instrument and has 22 channels at frequencies ranging from 23 to 183 GHz which allows for probing the atmospheric temperature and moisture under clear and cloudy conditions. ATMS inherited most of the sounding channels from its predecessors: Advanced Microwave Sounding Unit‐A (AMSU‐A) and Microwave Humidity Sounder (MHS) onboard NOAA and MetOp satellites. However, ATMS has a wider scan swath and has no gaps between two consecutive orbits. It includes one new temperature sounding channel and two water vapor sounding channels and provides more details of thermal structures in lower troposphere, especially for the storm conditions such as tropical cyclones. While ATMS temperature sounding channels have shorter integration time and therefore higher noise than AMSU‐A, the ATMS observations from their overlapping field of views are resampled to produce AMSU‐A‐like measurements. Key Points Introduce new ATMS features Depict ATMS bias characteristics for temperature sounding channels Retrieve cloud liquid water path using ATMS observations

Based on the Twentieth Century Reanalysis (20CR) dataset, the dominant modes of interdecadal variability of the East Asian summer monsoon (EASM) are investigated through a multivariate empirical orthogonal function analysis (MV-EOF). The first mode (EA1) is characterized by an anomalous cyclone centered over Taiwan and an anomalous anticyclone centered over the Bohai Sea. These phenomena are part of the meridional wave–like teleconnection pattern propagating poleward from the southern tropical western North Pacific (WNP), referred to as the interdecadal Pacific–Japan (PJ) pattern. The interdecadal PJ pattern is driven by negative anomalous convective heating over the southern tropical WNP, which is associated with the interdecadal Pacific oscillation (IPO) and the interdecadal Indian Ocean basin mode (IOBM). The amplitude of the EA1 and its contribution to the total variance of the EASM decrease remarkably after the 1960s. The second MV-EOF mode (EA2) is characterized by cyclone anomalies extending from northeastern China to Japan, which are part of a circumglobal wave train. Given the spatial scale of the wave train in the zonal direction (wavenumber 5), as well as the fact that it possesses barotropic structures and propagates along the Northern Hemispheric jet stream, it is referred to herein as the interdecadal circumglobal teleconnection (CGT) pattern. The interdecadal CGT pattern is associated with the forcing from the Atlantic multidecadal oscillation (AMO). Though the interdecadal PJ and CGT patterns are derived from the 20CR dataset, they are carefully verified through comparisons with various observational and reanalysis datasets from different perspectives.

ATM is one of the principal players of the DNA damage response. This protein exerts its role in DNA repair during cell cycle replication, oxidative stress, and DNA damage from endogenous events or exogenous agents. When is activated, ATM phosphorylates multiple substrates that participate in DNA repair, through its phosphoinositide 3-kinase like domain at the 3′end of the protein. The absence of ATM is the cause of a rare autosomal recessive disorder called Ataxia Telangiectasia characterized by cerebellar degeneration, telangiectasia, immunodeficiency, cancer susceptibility, and radiation sensitivity. There is a correlation between the severity of the phenotype and the mutations, depending on the residual activity of the protein. The analysis of patient mutations and mouse models revealed that the presence of inactive ATM, named ATM kinase-dead, is more cancer prone and lethal than its absence. ATM mutations fall into the whole gene sequence, and it is very difficult to predict the resulting effects, except for some frequent mutations. In this regard, is necessary to characterize the mutated protein to assess if it is stable and maintains some residual kinase activity. Moreover, the whole-genome sequencing of cancer patients with somatic or germline mutations has highlighted a high percentage of ATM mutations in the phosphoinositide 3-kinase domain, mostly in cancer cells resistant to classical therapy. The relevant differences between the complete absence of ATM and the presence of the inactive form in in vitro and in vivo models need to be explored in more detail to predict cancer predisposition of A-T patients and to discover new therapies for ATM-associated cancer cells. In this review, we summarize the multiple discoveries from humans and mouse models on ATM mutations, focusing into the inactive versus null ATM.

While near-inertial waves are known to be generated by atmospheric storms, recent observations in the Kuroshio Front find intense near-inertial internal-wave shear along sloping isopycnals, even during calm weather. Recent literature suggests that spontaneous generation of near-inertial waves by frontal instabilities could represent a major sink for the subinertial quasigeostrophic circulation. An unforced three-dimensional 1-km-resolution model, initialized with the observed cross-Kuroshio structure, is used to explore this mechanism. After several weeks, the model exhibits growth of 10–100-km-scale frontal meanders, accompanied by O (10) mW m −2 spontaneous generation of near-inertial waves associated with readjustment of submesoscale fronts forced out of balance by mesoscale confluent flows. These waves have properties resembling those in the observations. However, they are reabsorbed into the model Kuroshio Front with no more than 15% dissipating or radiating away. Thus, spontaneous generation of near-inertial waves represents a redistribution of quasigeostrophic energy rather than a significant sink.

This paper examines trends in the southern annular mode (SAM) and the strength, position, and width of the Southern Hemisphere surface westerly wind jet in observations, reanalyses, and models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). First the period over 1951–2011 is considered, and it is shown that there are differences in the SAM and jet trends between the CMIP5 models, the Hadley Centre gridded SLP (HadSLP2r) dataset, and the Twentieth Century Reanalysis. The relationships between these trends demonstrate that the SAM index cannot be used to directly infer changes in any one kinematic property of the jet. The spatial structure of the observed trends in SLP and zonal winds is shown to be largest, but also most uncertain, in the southeastern Pacific. To constrain this uncertainty six reanalyses are included and compared with station-based observations of SLP. The CMIP5 mean SLP trends generally agree well with the direct observations, despite some climatological biases, while some reanalyses exhibit spuriously large SLP trends. Similarly, over the more reliable satellite era the spatial pattern of CMIP5 SLP trends is in excellent agreement with HadSLP2r, whereas several reanalyses are not. Then surface winds are compared with a satellite-based product, and it is shown that the CMIP5 mean trend is similar to observations in the core region of the westerlies, but that several reanalyses overestimate recent trends. The authors caution that studies examining the impact of wind changes on the Southern Ocean could be biased by these spuriously large trends in reanalysis products.

Background Accurate prediction of traffic flow is an integral component in most of the Intelligent Transportation Systems (ITS) applications. The data driven approach using Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) models reported in most studies demands sound database for model building. Hence, the applicability of these models remains a question in places where the data availability could be an issue. The present study tries to overcome the above issue by proposing a prediction scheme using Seasonal ARIMA (SARIMA) model for short term prediction of traffic flow using only limited input data. Method A 3-lane arterial roadway in Chennai, India was selected as the study stretch and limited flow data from only three consecutive days was used for the model development using SARIMA. After necessary differencing to make the input time series a stationary one, the autocorrelation function (ACF) and partial autocorrelation function (PACF) were plotted to identify the suitable order of the SARIMA model. The model parameters were found using maximum likelihood method in R. The developed model was validated by performing 24 hrs. ahead forecast and the predicted flows were compared with the actual flow values. A comparison of the proposed model with historic average and naive method was also attempted. The effect of increase in sample size of input data on prediction results was studied. Short term prediction of traffic flow during morning and evening peak periods was also attempted using both historic and real time data. Concluding remarks The mean absolute percentage error (MAPE) between actual and predicted flow was found to be in the range of 4–10, which is acceptable in most of the ITS applications. The prediction scheme proposed in this study for traffic flow prediction could be considered in situations where database is a major constraint during model development using ARIMA.

The Pacific decadal oscillation (PDO), the dominant year-round pattern of monthly North Pacific sea surface temperature (SST) variability, is an important target of ongoing research within themeteorological and climate dynamics communities and is central to the work of many geologists, ecologists, natural resource managers, and social scientists. Research over the last 15 years has led to an emerging consensus: the PDO is not a single phenomenon, but is instead the result of a combination of different physical processes, including both remote tropical forcing and local North Pacific atmosphere–ocean interactions, which operate on different time scales to drive similar PDO-like SST anomaly patterns. How these processes combine to generate the observed PDO evolution, including apparent regime shifts, is shown using simple autoregressive models of increasing spatial complexity. Simulations of recent climate in coupled GCMs are able to capture many aspects of the PDO, but do so based on a balance of processes often more independent of the tropics than is observed. Finally, it is suggested that the assessment of PDO-related regional climate impacts, reconstruction of PDO-related variability into the past with proxy records, and diagnosis of Pacific variability within coupled GCMs should all account for the effects of these different processes, which only partly represent the direct forcing of the atmosphere by North Pacific Ocean SSTs.