Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Environment-Aware Fall Risk Assessment: Classifying Walking Surface Conditions Using IMU-Based Gait Data and Deep Learning

Fall risk assessment (FRA) helps clinicians make decisions about the best preventative measures to lower the risk of falls by identifying the different risks that are specific to an individual. With the development of wearable technologies such as inertial measurement units (IMUs), several free-living FRA methods based on fall predictors derived from IMU-based data have been introduced. The performance of such methods could be improved by increasing awareness of the individuals’ walking environment. This study aims to introduce and analyze a 25-layer convolutional neural network model for classifying nine walking surface conditions using IMU-based gait data, providing a basis for environment-aware FRAs. A database containing data collected from thirty participants who wore six IMU sensors while walking on nine surface conditions was employed. A systematic analysis was conducted to determine the effects of gait signals (acceleration, magnetic field, and rate of turn), sensor placement, and signal segment size on the method’s performance. Accuracies of 0.935 and 0.969 were achieved using a single and dual sensor, respectively, reaching an accuracy of 0.971 in the best-case scenario with optimal settings. The findings and analysis can help to develop more reliable and interpretable fall predictors, eventually leading to environment-aware FRA methods.
Sea-level rise and flooding in coastal riverine flood plains

Abstract This work presents a method for calculating the contributions of sea-level rise and urban growth to flood risk in coastal flood plains. The method consists of hydraulic/hydrological, urban growth and flood-damage quantification modules. The hydraulic/hydrological module estimates peak annual flows to generate flood stages impacted by sea-level rise within flood plains. A model for urban growth predicts patterns of urbanization within flood plains over the period 2010–2050. The flood-damage quantification module merges flood maps and urbanization predictions to calculate the expected annual flood damage (EAFD) for given scenarios of sea-level rise. The method is illustrated with an application to the Tijuana River of southern California, USA, and northwestern Mexico, where the EAFD is predicted to increase by over US$100 million because of sea-level rise of 0.25–1.0 m and urban growth by the year 2050. It is shown that urbanization plays a principal role in increasing the EAFD in the study area for the range of sea-level rise considered. Editor Z.W. Kundzewicz Citation Garcia, E.S. and Loáiciga, H.A. , 2013. Sea-level rise and flooding in coastal riverine flood plains. Hydrological Sciences Journal, 59 (1), 204–220.
Algorithm for stitching data from a pair of sensors in the thermal and visible range with free location cameras

The paper proposes a method of inter-frame data alignment, built on the operations of pre-processing and selection of object contours and based on the following basic operations: reading data from cameras, determining parameters and dimensions; solving the problem of contouring objects and simplifying them to form a mask for subsequent processing; filtering, using a multi-criteria method based on a combination of criteria, the standard deviation of the final differences of the generated estimates and the first difference of the deviation from the input implementation; the use of NS to search for animals or/and humans; parallel detection of objects located in the range of 34°C-42°C degrees Celsius (95°F-107.6°F); the use of NN to determine the type of object by analyzing the thermal portrait; use of a mask of live objects (visual data) and thermal imaging parameters as alignment centers; determining a thermal image transformation matrix; stitching a pair of images. On a set of test sequences, studies have been carried out to increase the degree of detection of living objects when a thermal imaging camera is included in the data detector. The studies were carried out on a pair of cameras of the visible spectrum (1920x1080, RGB, 8 bit) and thermal (240x180, RGB, 8 bit).
On the budget of sea salts and sulfur in the atmosphere

An approximate estimation of the intensities of the different aerosol sources and of the budget of sea salt is carried out. Chemical composition data of frontal precipitating cloud water, the results of the research of rainout and washout processes, and the annual global precipitation amount are used in this estimation. There is good agreement between the obtained results of the estimation of sea-salt source intensity and data on river run off of chloride into ocean.
A Theoretical Analysis of Groundwater Flow in Small Drainage Basins

Theoretically, three types of flow systems may occur in a small basin: local, intermediate, and regional. The local systems are separated by subvertical boundaries, and the systems of different order are separated by subhorizontal boundaries. The higher the topographic relief, the greater is the importance of the local systems. The flow lines of large unconfined flow systems do not cross major topographic features. Stagnant bodies of groundwater occur at points where flow systems meet or branch. Recharge and discharge areas alternate; thus only part of the basin will contribute to the baseflow of its main stream. Motion of groundwater is sluggish or nil under extended flat areas, with little chance of the water being freshened. Water level fluctuations decrease with depth, and only a small percentage of the total volume of the groundwater in the basin participates in the hydrologic cycle.
A case report of cervical cancer stage Ib2 treated with radical trachelectomy

We present the case of a 34-year-old woman, with cervical cancer Stage IB2, treated with radical trachelectomy (and bilateral lymphadenectomy) instead of radical hysterectomy. Recurrence of the disease was diagnosed just a few months after the initial operation. Although the woman's desire was the preservation of fertility, it should be emphasized that best cancer treatment according to stage, is necessary to not endanger the patients’ life.
Decorrelation mechanisms in C-band SAR interferometry over boreal forest

Temporal and spatial decorrelation effects are very important in repeat pass interferometric imaging of boreal forest. Temporal decorrelation refers to changes in the strength and distribution of scattering, due to the effects of wind, rain, and moisture changes of both canopy and ground. Spatial decorrelation is a result of baseline decorrelation, volume scattering, and uncompensated topography. These effects complicate interferometric imaging and the use of interferometry for topographic mapping of forest covered regions. The differences between heights measured from interferograms over forest and a DEM (the effective tree height) are related to the coherence. Another problem is the decrease in accuracy of coherence estimates (e.g. for land use classification) when the coherence is low. Influences of various factors on coherence in interferometry using images from the ERS-1 3 day repeat cycle of 1994 are studied. A wide range of time intervals between images and of baselines is used. The coherence of various surfaces is found to vary considerably between interferograms. As the time interval increases, the coherence generally decreases. The causes of decorrelation and their relation to meteorological effects and volume scattering are investigated. Analysis of coherence over various surfaces in Northern Sweden during the winter of 1994 is performed, with particular emphasis on forest, clear cut and agricultural areas.
Deep Learning-Based Weed Detection Using UAV Images: A Comparative Study

Semantic segmentation has been widely used in precision agriculture, such as weed detection, which is pivotal to increasing crop yields. Various well-established and swiftly evolved AI models have been developed of late for semantic segmentation in weed detection; nevertheless, there is insufficient information about their comparative study for optimal model selection in terms of performance in this field. Identifying such a model helps the agricultural community make the best use of technology. As such, we perform a comparative study of cutting-edge AI deep learning-based segmentation models for weed detection using an RGB image dataset acquired with UAV, called CoFly-WeedDB. For this, we leverage AI segmentation models, ranging from SegNet to DeepLabV3+, combined with five backbone convolutional neural networks (VGG16, ResNet50, DenseNet121, EfficientNetB0 and MobileNetV2). The results show that UNet with EfficientNetB0 as a backbone CNN is the best-performing model compared with the other candidate models used in this study on the CoFly-WeedDB dataset, imparting Precision (88.20%), Recall (88.97%), F1-score (88.24%) and mean Intersection of Union (56.21%). From this study, we suppose that the UNet model combined with EfficientNetB0 could potentially be used by the concerned stakeholders (e.g., farmers, the agricultural industry) to detect weeds more accurately in the field, thereby removing them at the earliest point and increasing crop yields.
Tsunami surges around the Hawaiian Islands from the 1 April 2014 North Chile Mw 8.1 earthquake

The 1 April 2014 Iquique Mw 8.1 earthquake ruptured a segment of the megathrust fault offshore of northern Chile and generated a moderate‐size tsunami across the Pacific. Tide gauges in Hawaii recorded over 1 m of wave height despite the long distance from the source and position away from the main radiated energy lobe. Inversion of global teleseismic body waves combined with forward modeling of the tsunami at four near‐field DART stations arrives iteratively at a self‐consistent finite‐fault model with very compact dimensions. The slip distribution produces a NNE‐SSW trending seafloor uplift patch that enhances the tsunami directionality in the WNW, resulting in good matches to observed DART and tide gauge records around the Hawaiian Islands. The relatively large waves at selected locations in Hawaii can be attributed to a combination of the spatial slip distribution and the resulting short‐period waves that triggered localized resonance over the insular shelves. This event highlights the importance of characterizing detailed slip distributions in analysis or forecasting of tsunamis even for a compact source.
Assessment of the Needs of Nephrology Divisions to Implement Return of Clinically Significant Research Genetic Results: A Survey of Nephrotic Syndrome Study Network (NEPTUNE) Investigators

Introduction: There is an increasing need to return genetic testing results to patients with kidney disease who were first genotyped on a research basis. Operationalizing this process in nephrology clinics is challenged by a limited number of genetic providers with whom to partner and a general lack of support services for all clinicians. Methods: We administered a survey in March 2022 to assess the current ability and ongoing needs of nephrology divisions to return clinically significant research genetic results to patients and to implement clinical genetic testing. This survey was distributed to institutions within the Nephrotic Syndrome Study Network (NEPTUNE) as part of the planning process for return of research genetic results to participants with pathogenic variants in Mendelian nephrotic syndrome genes. Results: Twenty-seven of 28 sites (96%) completed the survey. 59% (n = 16) of sites said they could handle return of research genetic results independently, with the rest expressing hesitation about the volume and complexity of patients and the limited resources and access to genetics services. 81% (n = 22) of these institutions did have a genetics clinic and 26% (n = 7) have a nephrology genetics clinic. However, 70% (n = 10) of these clinics have a waiting time over 1 month. 89% of divisions (n = 24) were conducting genetic testing and 96% of those (n = 23) used a kidney multi-gene panel. In 46% of divisions (n = 11), nephrologists were handling logistics of obtaining genetic testing samples themselves. Conclusion: We identified specific areas of support needed for return of clinically significant genetic results from research studies. While the surveyed nephrologists were conducting genetic testing, there were limitations in the support services available. This survey will help guide other research studies that wish to return genetic results to participants and also highlight the need for increasing support to effectively operationalize genetic testing in nephrology clinics.
Is past performance a guarantee for current results? The influence of learning on business performance in manufacturing

PurposeThis paper investigates the relationship between past performance and the development of operational capabilities in manufacturing firms, focusing on the role of intra- and inter-organisational learning mechanisms.Design/methodology/approachThis study is based on a survey database collected in 208 manufacturing plants in 15 countries from three industries: electronics, machinery and transport components. The authors developed a model and tested the study hypotheses using the structural equation modelling technique with two-stage analytical procedures.FindingsIn the analysis of the overall sample, the study findings support prior literature by suggesting that firms with successful experiences may become complacent and less motivated to engage in learning, leading to a decline in performance. However, high-performance firms overcome the “success trap” by engaging supply chain partners. In contrast, low-performance firms exhibit limited learning from past poor performance, leading to organisational inertia and further declines in their current performance.Practical implicationsThis research provides practical guidance for managers in developing operational capabilities, highlighting collaboration with suppliers as an essential element for high-performance firms.Originality/valueThis study focuses on the little-researched topic of how past performance influences the development of operational capabilities in manufacturing firms. The authors highlight the path for developing capabilities in high- and low-performance firms based on intra- and inter-organisational learning mechanisms.
Multiple-Perspective Data-Driven Analysis of Online Health Communities

The growth of online health communities and socially generated health-related content has the potential to provide considerable value for patients and healthcare providers alike. For example, members of the public can acquire medical knowledge and interact with others online. However, the volume of information—and the consequent ‘noise’ associated with large data volumes—can create difficulties for users. In this paper, we present a data-driven approach to better understand these data from multiple stakeholder perspectives. We utilise three techniques—sentiment analysis, content analysis, and topic analysis—to analyse user-generated medical content related to Lyme disease. We use a supervised feature-based model to identify sentiments, content analysis to identify concepts that predominate, and latent Dirichlet allocation strategy as an unsupervised generative model to identify topics represented in the discourse. We validate that applying three different analytic methods highlights differing aspects of the information different stakeholders will be interested in based on the goals of different stakeholders, expert opinion, and comparison with patient information leaflets.
Formation, Distribution, and Prediction of Stylolites as Permeability Barriers in the Thamama Group, Abu Dhabi

In an Offshore Abu Dhabi field, an attempt has been made to predict vertical permeability through stylolite zones in uncored wells. Comparison of the stylolite intensity index, calculated from FDC/CNL logs following the method of Johnson and Budd, with measurements from whole core and plug analyses showed that a statistically valid relationship exists between these two parameters. Separate relationships have been established for stylolites above and below the oil/water contact as values in the water zone tend to be further reduced by continued cementation. The establishment of these relationships has enabled the prediction of vertical permeabilities through stylolite zones in uncored wells. Vertical permeabilities of less than 1md equate to a stylolite intensity index of 50, and in the subject field such zones are likely to severely limit fluid movement. Such geological analysis can thus provide a useful model for aiding reservoir simulation and field development.
Energy Efficient OFDM With Intelligent PAPR-Aware Adaptive Modulation

In this letter, we propose a novel peak-to-average power ratio (PAPR)-aware adaptive modulation scheme for Orthogonal Frequency Division Multiplexing (OFDM). The aim of the proposed PAPR-aware protocol is to maximize the energy efficiency of the OFDM transmission, where the energy efficiency is defined as the ratio of the OFDM throughput to the PA consumption, and is thus strongly affected by PAPR. For this purpose, we formulate the energy efficiency maximization problem with respect to power and adaptive modulation constraints per subcarrier. Due to the joint optimization of power allocation, adaptive modulation, and the non-convex terms introduced by PAPR, the problem cannot be solved by using convex optimization tools. Therefore, a solution based on online deep learning is proposed. Numerical results showcase that the energy efficiency of the proposed PAPR-aware protocol is greater up to 3-dB compared to the conventional PAPR-unaware protocol, while the PAPR is also reduced by 3-dB.
Phytoplankton pigment patterns in the Canary Islands area as determined using Coastal Zone Colour Scanner data

Data from the Nimbus-7 Coastal Zone Colour Scanner (CZCS) were analyzed to determine the phytoplankton pigment patterns in the ocean surrounding the Canary Islands. Two different pattterns were observed in this region. One pattern was associated with the influence of the northwest African coastal upwelling system on the ocean surrounding the Canary Islands and the other was associated with individual islands, probably due to the disruptive effect of the Canary Islands on the flow of the Canary Current
PEMERIKSAAN WAKTU REAKSI VISUAL DAN SOSIALISASI PERILAKU SEDENTARI PADA SISWA SEKOLAH DASAR NEGERI 2 SUMERTA DENPASAR TIMUR

Kebiasaan dari kurangnya melakukan aktivitas sehari hari sering dikategorikan sebagai perilaku sedentari yang mana perilaku sedentari ini dikatakan memberikan dampak buruk bagi anak. Salah satu dampak yang muncul dari aktivitas sedentari adalah menurunnya waktu reaksi anak. Waktu reaksi diartikan sebagai waktu yang dibutuhkan untuk munculnya suatu respon yang diinginkan dari mulai diterimanya stimulus hingga. Kecepatan reaksi visual dikatkan dengan kecepatan anak dalam membaca, yang diawali dari input sensoris dalam bentuk huruf dilanjutkan dengan mengintepretasikan input visual tersebut hingga terbentuk sebuah respon berupa pengucapan bentuk huruf dengan tepat. Tujuan dari pelaksanaan pengabdian ini adalah untuk memberika sosialisasi dampak perilaku sedentari dan pemeriksaan waktu reaksi visual pada anak sekolah dasar. Target khusus yang ingin dicapai dari kegiatan ini adalah dengan mengetahui dampak dari perilaku sedentari diharapkan orang tua dan pihak sekolah memberikan kegiatan berupa aktivitas fisik yang juga dapat melatih waktu reaksi anak. Berdasarkan pengabdian masyarakat yang telah dilakukan, didapatkan hasil sebagai berikut: (1) Sampel mengikuti pengabdian ini berjumlah 71 orang yang terdiri atas siswa kelas 4 sejumlah 24, siswa kelas 5 sejumlah 17 dansiswa kelas 6 sejumlah 30, (2) Siswa kelas 4 memiliki nilai rata-rata kecepatan waktu reaksi sebesar 533,83ms. Siswa kelas 5 memiliki nilai rata-rata kecepatan waktu reaksi sebesar 513,36ms. Siswa kelas 6 memiliki nilai rata-rata kecepatan waktu reaksi sebesar 492,77ms. Kata kunci : sosialisasi, perilaku sedentary, waktu reaksi visual
Predicting the Gas Diffusion Coefficient in Repacked Soil Water‐Induced Linear Reduction Model

Investigations of gas transport and fate processes in packed soil systems require knowledge of the gas diffusion coefficient, D p , as a function of air-filled porosity, e. On the basis of the literature, data from six studies over the porosity range of 0.1 to nearly 1.0, it is reconfirmed that the Marshall (1959) model better predicts D p (e) in completely dry, repacked porous media than do the Penman (1940) and Millington (1959) models. The smaller D p value in wet soil, as compared with dry soil at the same air-filled porosity, is accounted for by introducing a water-induced linear reduction (WLR) term, equal to the ratio of air-filled porosity to total porosity, in the D p (e) model. By adding the WLR term in each of the three D p (e) models for dry porous media, the so-called WLR(Marshall), WLR(Penman), and WLR(Millington) D p (e) models for wet soil are developed. To test the three WLR models, D p was measured at different soil-water contents in six differently textured (6-38% clay) repacked soils. The WLR (Marshall) model accurately and best described D p (e) for all six soils and additional soils from the literature. All three WLR models performed better than previous D p (e) models. This study implies that the smaller D p in a wet soil, which is due to water-induced changes in air-filled pore shape and pore connectivity, can be described by a simple, linear function of relative air-filled porosity. The WLR(Marshall) model represents a conceptual and accurate model to predict D p (e) in sieved, repacked soil.
Comparison of Three Methods to Obtain the Apparent Dielectric Constant from Time Domain Reflectometry Wave Traces

A calibration of time domain reflectometry (TDR) probes to measure soil water in a particular soil is desirable since no consistent relationship between water content and apparent dielectric constant (K a ) has been found. We compared three procedures to compute K a from TDR traces: a manual method that uses a plot of the wave trace, a derivative-based computer algorithm, and fitting a simulated TDR trace to a measured one with a simple multiple reflection model. We added a model of inertia to the multiple reflection model to approximate the rise time of the cable tester. The TDR traces were measured in situ with a Tektronix 1502B cable tester (Tektronix, Inc., Wilsonville, OR) on samples from two soils with contrasting textures, Beltsville silt loam (fine-loamy, mixed, mesic Typic Fragiudult) and Rumford loamy sand (coarse-loamy, siliceous, thermic Typic Normudult). Ten-centimeter probes with three rods were used. The water contents were measured gravimetrically with soil cores. Calibration with apparent dielectric constants obtained from the derivative-based algorithm had the smallest standard error for both soils, and the manual method was better than the wave simulation method. The intercepts and slopes of the calibration equations for the manual and derivative methods were not significantly different from each other for both soils. The wave simulation method, which gives physically meaningful values for K a , and characteristic impedances can be a useful tool for theoretical studies.