Miracle-dz/UniFAR-FTUs huggingface dataset:
Slab buckling as a driver for rapid oscillations in plate motion and subduction rate

Plate tectonics is primarily driven by the constant gravitational pull of slabs where dense oceanic lithosphere sinks into the mantle at subduction zones. Under stable plate boundary conﬁgurations, changes in plate motion are then thought to occur gradually. Surprisingly, recent high-resolution Indian plate reconstructions revealed rapid (2-3 Ma) plate velocity oscillations of ± 50 %. Here we show, through numerical experiments, that the buckling of slabs in the mantle transition zone causes such oscillations. This buckling results from the deceleration of slabs as they sink into the lower mantle. The amplitude and period of buckling-associated oscillations depend on average subduction velocity and transition zone accommodation space. The oscillations also aﬀect the upper plate which may explain enigmatic observations of episodic deformation and ﬂuid ﬂow in subduction-related
Some statistics useful in regional frequency analysis

Regional frequency analysis uses data from a number of measuring sites. A “region” is a group of sites each of which is assumed to have data drawn from the same frequency distribution. The analysis involves the assignment of sites to regions, testing whether the proposed regions are indeed homogeneous, and choice of suitable distributions to fit to each region's data. This paper describes three statistics useful in regional frequency analysis: a discordancy measure, for identifying unusual sites in a region; a heterogeneity measure, for assessing whether a proposed region is homogeneous; and a goodness-of-fit measure, for assessing whether a candidate distribution provides an adequate fit to the data. Tests based on the statistics provide objective backing for the decisions involved in regional frequency analysis. The statistics are based on the L moments [Hosking, 1990] of the at-site data.
Klasifikasi Analisis Tekstur Citra Radiografi Panoramik Gigi Untuk Deteksi Menggunakan Metode K-Nearest Neighbor (KNN)

Osteoporosis is a degenerative disease which is characterized by a rapid decrease in bone density resulting in a decrease in the mechanical strength of the bones to support daily activities. The gold standard for bone mass measurement is Dual Energy X-ray Absorptiometry (DXA). Several previous studies provided the opportunity to utilize dental panoramic radiographic images for analysis of mandibular trabecular bone density. These results are used as an early detection tool for Bone Mineral Density (BMD) conditions. This research tries to use the feature extraction results of texture analysis using Grey Level Co-occurrence Matrix (GLCM) on dental panoramic images as input for K-Nearest Neighbor (KNN) to carry out classification. The trial was conducted using lumbar vertebral BMD data and dental panoramic images from 23 samples of women aged between 52-73 years who had entered the postmenopausal period. Classification results of normal and osteoporosis using KNN (9 training data and 14 test data) gave the best recognition with an accuracy of 78.57%, a sensitivity of 100% and a specificity of 66.67%. The best recognition is obtained by using contrast, energy, and homogeneity features and their combination as input for KNN classification .
A SIMULATION OF TRAFFIC CRASHES INTO THE 21ST CENTURY

Major reductions in the number of traffic crashes of various severities in Australia over the past 30 years have led some to think of a Zero Road Toll target as being both desirable and feasible in the near future. However, a number of demographic and travel behaviour changes have been occurring which will cast serious doubt on the feasibility of such a target. It is likely that the number of crashes involving older people may increase in the future. For this reason, this paper describes the development and application of a simulation model that predicts the number of crashes by various demographic groups in future years. The model shows that, assuming no change in crash rates within demographic groups, the number of fatal and serious injury crashes for young males and females (less than 30 years of age) remains essentially constant over the next 30 years, while middle-aged (30 to 60) males and females will show a 25 percent increase in the number of fatal and serious injury crashes. The real growth area is for people over 60, where a 175 percent increase in fatal and serious injury crashes can be expected. Males over 60 will experience a 150 percent increase in fatal and serious injury crashes, while females over 60 will experience a 200 percent increase in fatal and serious injury crashes. The analysis demonstrates that known demographic changes will place severe pressures on the vision of a Zero Road Toll. Substantial reductions in crash rates within demographic groups will be needed to counter the increases in the numbers of people in demographic groups which have a higher crash involvement rate. (a) For the covering entry of this conference, please see ITRD abstract no. E205861.
Dynamic characteristics and damage model for rock under uniaxial cyclic impact compressive loads

Experiments on dynamic mechanical performance of granite are carried out under uniaxial cyclic impact loads by using a modified large diameter split Hopkinson pressure bar(SHPB). The dynamic characteristics of the granite specimens and the laws of the energy absorption are analyzed.The cumulative damage of the granite specimens is calculated by use of the dynamic statistics damage model based on the Weibull random distribution.The laws of the cumulative damage of the granite specimens are also analyzed through the stress-strain curves.The results show that,in the cyclic impact compressive tests,with the increase of repeated action times of impact loads,the deformation modulus of granite decreases,the yield strain increases and the yield stress shows a decreasing trend.The value of cumulative specific energy increases with the increase of impact times,which increases slowly before the failure of the specimen and increases rapidly at its failure.The model curves and the test curves have good consistency,which shows that this model can reasonably reflect the relationship of the stress-strain and stress-strain rate.The value of cumulative damage increases with the increase of impact times,and its increasing rate changes from slowly to rapidly.Before the failure of the specimen,the cumulative damage increases smoothly,and the main increment occurs in the last impact when the specimen is broken.
Projected changes in land carbon store over the 21 st century: what contributions from land-use change and atmospheric nitrogen deposition?

Earth System Models (ESM) represent the time evolution of the biophysical (energy, water cycles) and 10 biogeochemical (carbon cycle) components of the Earth. When used for near-future projections in the context of the Coupled Model Intercomparison Project (CMIP), they use as forcings the evolution of greenhouse gas and other pollutant concentrations and land-use changes simulated by an ensemble of Integrated Assessment Models (IAMs) for a combination of socio-economic pathways and mitigation targets (SSPs). More precisely, only one IAM output is used as representative of a single SSP while the inter-IAM spread is large for ammonia emissions and land-use changes, for instance. This makes the comparison of key 15 ESM diagnostics among SSPs significantly noisy, without the capacity of disentangling SSP-driven and IAM-driven factors. In this paper, we quantify the projected change in land carbon store (CLCS) for the different SSPs with an advanced version of a land surface model embedded into IPSL-CM6 ESM. Through a set of land-only factorial simulations, we specifically aim at estimating the CLCS uncertainties associated with land-use change and nitrogen deposition trajectories. We showed that the spread of the simulated change in global land carbon store induced by the uncertainty on land-use changes is slightly larger 20 than the one associated with the uncertainty on atmospheric CO 2 . Globally, uncertainty associated with N depositions is responsible for a spread in CLCS lower by a factor three, than the one driven by atmospheric CO 2 or land-use
ASSOCIATION B ETWEEN A GE A T M ENARCHE AND E ARLY-LIFE N UTRITIONAL S TATUS I N RURAL B ANGLADESH

Summary. Age at menarche is associated with anthropometry in adolescence. Recently, there has been growing support for the hypothesis that timing of menarche may be set early in life but modified by changes in body size and composition in childhood. To evaluate this, a cohort of 255 girls aged <5 years recruited in 1988 were followed up in 2001 in Matlab, Bangladesh. The analysis was based on nutritional status as assessed by anthropometry and recalled age at menarche. Data were examined using lifetable techniques and the Cox regression model. The association between nutritional status indicators and age at menarche was examined in a multivariate model adjusting for potential confounding variables. Censored cases were accounted for. The median age at menarche was 15·1 years. After controlling for early-life predictors (birth size, childhood underweight, childhood stunting) it appeared that adolescent stunting stood out as the most important determinant of age at menarche. Adolescent stunting still resonates from the effect of stunting in early childhood (OR respectively 2·63 (p<0·01 CI: 1·32–5·24) and 8·47 (p<0·001 CI: 3·79–18·93) for moderately and severely stunted under-fives as compared with the reference category). Birth size was not a significant predictor of age at menarche. It is concluded that age at menarche is strongly influenced by nutritional status in adolescence, notably the level of stunting, which is in turn highly dependent on the level of stunting in early childhood. A ‘late’ menarche due to stunting may be detrimental for reproductive health in case of early childbearing because of the association between height and pelvic size.
ORIGINAL ARTICLE. PHYSICAL EDUCATION Physical exercises improve cognitive abilities of 7-8 years old chess club’s students

Background and purpose Many studies show the positive impact of playing chess on the cognitive abilities, motor skills and psychophysiological characteristics of people. On the other hand, physical exercises are of great importance for the progress of kids’ cognitive features. In view of this, our study was aimed at determining the effect of physical exercises on cognitive abilities and psychophysiological functions of young chess players
Based on MRI with Polymicrogyria and Lissencephaly Gyrification Patterns and Changes in Fetuses Automatic Quantification of Normal Brain

BACKGROUND AND PURPOSE: The current imaging assessment of fetal brain gyri ﬁ cation is performed qualitatively and subjectively using sonography and MR imaging. A few previous studies have suggested methods for quanti ﬁ cation of fetal gyri ﬁ cation based on 3D reconstructed MR imaging, which requires unique data and is time-consuming. In this study, we aimed to develop an automatic pipeline for gyri ﬁ cation assessment based on routinely acquired fetal 2D MR imaging data, to quantify normal changes with gestation, and to measure differences in fetuses with lissencephaly and polymicrogyria compared with controls. MATERIALS AND METHODS: We included coronal T2-weighted MR imaging data of 162 fetuses retrospectively collected from 2 clinical sites: 134 controls, 12 with lissencephaly, 13 with polymicrogyria, and 3 with suspected lissencephaly based on sonography, yet with normal MR imaging diagnoses. Following brain segmentation, 5 gyri ﬁ cation parameters were calculated separately for each hemisphere on the basis of the area and ratio between the contours of the cerebrum and its convex hull. Seven machine learning classi ﬁ ers were evaluated to differentiate control fetuses and fetuses with lissencephaly or polymicrogyria. RESULTS: In control fetuses, all parameters changed signi ﬁ cantly with gestational age ( P , .05). Compared with controls, fetuses with lissencephaly showed signi ﬁ cant reductions in all gyri ﬁ cation parameters ( P # .02). Similarly, signi ﬁ cant reductions were detected for fetuses with polymicrogyria in several parameters ( P # .001). The 3 suspected fetuses showed normal gyri ﬁ cation values, supporting the MR imaging diagnosis. An XGBoost-linear algorithm achieved the best results for classi ﬁ cation between fetuses with lissencephaly and control fetuses ( n ¼ 32), with an area under the curve of 0.90 and a recall of 0.83. Similarly, a random forest classi ﬁ er showed the best performance for classi ﬁ cation of fetuses with polymicrogyria and control fetuses ( n ¼ 33), with an area under the curve of 0.84 and a recall of 0.62. CONCLUSIONS: This study presents a pipeline for automatic quanti ﬁ cation of fetal brain gyri ﬁ cation and provides normal developmental curves from a large cohort. Our method signi ﬁ cantly differentiated fetuses with lissencephaly and polymicrogyria, demonstrating lower gyri ﬁ cation values. The method can aid radiologic assessment, highlight fetuses at risk, and may improve early identi ﬁ cation of fetuses with cortical malformations.
Paciﬁc–North American Teleconnection Controls on Precipitation Isotopes ( d 18 O) across the Contiguous United States and Adjacent Regions: A GCM-Based Analysis

The Paciﬁc–North American (PNA) teleconnection pattern has a strong inﬂuence on North America’s winter climate, but much less is known about how the PNA pattern controls precipitation isotopes(e.g., d 18 O) across the United States. In this study, an isotopically equipped atmospheric general circulation model (isoGSM) is used to investigate how divergent phases of the PNA affect precipitation d 18 O values across the United States. A simulation using observational climate and isotope data over the United States is evaluated ﬁrst. The simulation explains 84% of the spatial variability of winter precipitation d 18 O, with an overestimation in the northern Rocky Mountains and the Great Lakes. Temporally, the simulation explains 29%–81% of the interannual variability of winter precipitation d 18 O, with typically a higher explained variance in the east than the west. The modeled winter precipitation d 18 O exhibits a clear northwest–southeast (NW–SE) dipolelike pattern in response to shifts in the PNA pattern, with the center of positive polarity in the northwestern United States and the Canadian prairies and the center of negative polarity over the Ohio River valley. This dipolelike spatial pattern is a result of the difference in atmospheric circulation and moisture sources associated with the PNA pattern. These results highlight the importance of the PNA-associated circulation dynamics in governing precipitation isotope patterns across the United States. This understanding improves our ability to interpret paleoclimate records of water isotope/hydrologic change across the United States with a much greater appreciation of regional traits. The robust antiphase oscillation in precipitation isotopes in response to shifting the PNA pattern provides a promising opportunity to reconstruct the past variability in the PNA pattern that may be recorded in ice cores, tree rings, lake sediments, and speleothems.
Evaluation of Arithmetic Sum-of-Products Expressions in Linear Secret Sharing Schemes with a Non-Interactive Computation Phase

Among secure multi-party computation protocols, linear secret sharing schemes often do not rely on cryptographic assumptions and are among the most straightforward to explain and to implement correctly in software. However, basic versions of such schemes either limit participants to evaluating linear operations involving private values or require those participants to communicate synchronously during a computation phase. A straightforward, information-theoretically secure extension to such schemes is presented that can evaluate arithmetic sum-of-products expressions that contain multiplication operations involving non-zero private values. Notably, this extension does not require that participants communicate during the computation phase. Instead, a preprocessing phase is required that is independent of the private input values (but is dependent on the number of factors and terms in the sum-of-products expression).
An Economic Analysis of 5G Network Slicing and the Impact of Regulation

Network slicing is a key component of 5G-and-beyond networks, requiring to define a business model for resource allocation. We consider a model with a Service Provider (SP) that may purchase a slice in a wireless network, in order to offer a “premium” service where the improved quality stems from higher prices leading to less demand and less congestion than the basic service offered by the network owner, a scheme known as Paris Metro Pricing. One optimization problem for the SP is the choice of how much resource to allocate to that slice. We also compare with the case of a unique “pipe” (no premium service) and with the case of vertical integration to evaluate the impact of slicing on all actors and identify the “best” economic scenario.
Seasonal Assemblages of picocyanobacteria in the subtropical segment of the Kuroshio Current

A long-term observation has been conducted on the community composition diversity of picoplankton in the subtropical segment of Kuroshio Current from 2009 to 2015. The results showed that Synechococcus mainly distributed in the surface water layer regardless of seasonal changes, and the number of cells ranged from 10 4 to 10 5 cells mL − 1 . In contrast, the maximum value of Prochlorococcus was maintained at more than 10 5 cells mL − 1 throughout the year, and the stirring effect caused by the monsoon determined their distribution in the water layer. In the summer and the autumn, Prochlorococcus were mainly concentrated at the water layer near the bottom of the euphotic zone. In the spring and the winter, they were evenly distributed in the euphotic zone. In addition, the results of 16S rRNA gene diversity analysis showed that the seasonal changes in the relative abundance of Synechococcus and Prochlorococcus in the surface water of each station accounted for 20 to 40% of the total reads. Proteobacteria and Actinobacteria approximately accounted for 45% and 10% of the total picoplankton in the four seasons. The clade-II of Synechococcus and the High-light II of Prochlorococcus were the dominant strains in the waters all year round. These data will be important basic parameters for us to study the impact of global environmental changes on marine biogeochemical cycles in the western boundary currents in the future.
Warped-Area Reparameterization of Differential Path Integrals

Physics-based differentiable rendering is becoming increasingly crucial for tasks in inverse rendering and machine learning pipelines. To address discontinuities caused by geometric boundaries and occlusion, two classes of methods have been proposed: 1) the edge-sampling methods that directly sample light paths at the scene discontinuity boundaries, which require nontrivial data structures and precomputation to select the edges, and 2) the reparameterization methods that avoid discontinuity sampling but are currently limited to hemispherical integrals and unidirectional path tracing. We introduce a new mathematical formulation that enjoys the benefits of both classes of methods. Unlike previous reparameterization work that focused on hemispherical integral, we derive the reparameterization in the path space. As a result, to estimate derivatives using our formulation, we can apply advanced Monte Carlo rendering methods, such as bidirectional path tracing, while avoiding explicit sampling of discontinuity boundaries. We show differentiable rendering and inverse rendering results to demonstrate the effectiveness of our method.
Control of External Devices with Thoughts by Using BCI (Brain Computer Interface) for IOT-EEG Calibration System

A Brain-Computer Interface (BCI) is a device that translates neuronal information into commands capable of controlling external software or hardware such as a computer, a wheelchair, robotic arm. BCI is used to treat neurological disorders and thus helps in the restoration of sensory and motor functions. BCIs are used with assisted living devices for individuals suffering from motor or sensory impairments. With BCI, a person with all kinds of disabilities but having a functioning brain can do many things that otherwise are impossible to do. With BCI, a person without performing any muscle movement can do various activities using thoughts in the brain. BCI interface is a direct communication pathway between a human or animal brain and an external device. BCI devices are of two types: invasive and noninvasive. Here, we have used a noninvasive BCI headset device that uses Electroencephalography (EEG) to monitor and measure brain activity. In the market, devices are available that work on Functional Magnetic Resonance Imaging (fMRI) and Magnetoencephalography (MEG). All the existing devices lack an efficient way to train mental commands, maintain different human brain profiles, and a standard way to integrate with IoT devices. We have done the work to address the above problem. BCI software for EEG headsets is developed, which trains mental commands with calibration and provides easy integration with IoT devices. The BCI software developed offers an
A preliminary application of principal components and cluster analysis to internal tongue deformation patterns

This PDF receipt will only be used as the basis for generating PubMed Central (PMC) documents. PMC documents will be made available for review after conversion (approx. 2-3 weeks time). Any corrections that need to be made will be done at that time. No materials will be released to PMC without the approval of an author. Only the PMC documents will appear on PubMed Central -this PDF Receipt will not appear on PubMed Central. Journal name: Computer methods in biomechanics and biomedical engineering NIHMSID: NIHMS270820 Manuscript Title: A preliminary application of principal components and cluster analysis to internal tongue deformation patterns Principal Investigator: Maureen Stone (MSTONE@UMARYLAND.EDU) Submitter: Taylor And Francis Group (gregg.warren@tandf.co.uk)
Blockchain in Banking: Challenges and opportunities for the banking system in Vietnam.

: The research explores both the opportunities and challenges associated with applying blockchain technology in the banking systems of Vietnam. It also highlights key considerations for implementing this technology. The chosen research method is qualitative, involving the collection and analysis of documents and reports to provide a comprehensive overview of the issue. This qualitative methodology aligns with the complexity of the issues involved and provides a foundation for the development of tailored solutions to effectively address the challenges and capitalize on the opportunities presented by blockchain technology in Vietnam's banking systems.