Miracle-dz/UniFAR-FTUs huggingface dataset:
On Symbol Error Performance of Probabilistic Shaping in Noise-Limited and Fading Channels

In this work, we present symbol error performance analysis of probabilistic shaping (PS) for wireless communications in noise-limited and fading channels. Two fading models considered are the Rayleigh and log-normal fading channels. The results are corroborated with simulation and compared with the conventional uniformly distributed input symbols. In all channel conditions, PS results in significant reductions in the SNR required to achieve a specific error probability compared to the conventional uniformly shaped symbols. For example, in a noise-limited channel, PS based quadrature amplitude modulation (QAM) signal results in SNR gains of 1.16 dB, 1.41 dB, and 1.52 dB compared to the uniformly distributed QAM symbols at equal entropy rates of 4, 6, and 8 bit/symbol and a symbol error ratio (SER) of $1\times 10^{-3}$ .
Saddle Pressures Factors in Road and Off-Road Cyclists of Both Genders: A Narrative Review

The contact point of the pelvis with the saddle of the bicycle could generate abnormal pressure, which could lead to injuries to the perineum in cyclists. The aim of this review was to summarize in a narrative way the current literature on the saddle pressures and to present the factors that influence saddle pressures in order to prevent injury risk in road and off-road cyclists of both genders. We searched the PubMed database to identify English-language sources, using the following terms: “saddle pressures”, “pressure mapping”, “saddle design” AND “cycling”. We also searched the bibliographies of the retrieved articles. Saddle pressures are influenced by factors such as sitting time on the bike, pedaling intensity, pedaling frequency, trunk and hand position, handlebars position, saddle design, saddle height, padded shorts, and gender. The jolts of the perineum on the saddle, especially on mountain bikes, generate intermittent pressures, which represent a risk factor for various pathologies of the urogenital system. This review highlights the importance of considering these factors that influence saddle pressures in order to prevent urogenital system injuries in cyclists.
MAGNETOGASDYNAMIC SPHERICAL SHOCK WAVES IN A NON- IDEAL GAS WITH RADIATION

An exact similarity solution for a spherical magnetogasdynamic shock in a non-ideal gas is obtained in the case when radiation energy, radiation pressure and radiative heat-flux are important. The total energy of the shock wave increases with time. We have shown that the non-idealness of the gas changes the flow variables, considerably, in the flow-field behind the shock. Also, it is investigates that the presence of the magnetic field reduces the effect of the non-idealness of the gas on the strength of shock and on the flow-field behind it.
Social assessment of miscanthus cultivation in Croatia: Assessing farmers' preferences and willingness to cultivate the crop

Social aspects of miscanthus cultivation have been investigated in a limited way in the scientific literature. Adopting existing frameworks for social life‐cycle assessment enables assessments to include numerous social aspects; however, the relevance of these aspects depends on the local context. This study aims to identify the most relevant social aspects from the farmers' perspective using a previously proposed framework for the assessment of the stakeholder ‘farmer’. It is based on a case study for miscanthus production in Sisak Moslavina in Croatia. The existence of abandoned lands in Croatia presents an opportunity for the cultivation of miscanthus as a potential source of biomass for the production of bio‐based materials and fuels. The study seeks to assess the feasibility of cultivating miscanthus in the region, taking into account potential challenges and opportunities, as well as farmers' willingness to adopt the crop, and to understand the reasons behind land abandonment. We conducted a survey among 44 farmers in the region and used a scoring method to identify the most relevant social aspects. The aspects most valued by the farmers were health and safety, access to water, land consolidation and rights, income and local employment, and food security. Responses to the question of whether they would adopt the crop highlight the importance of an established market, good trading conditions and profitability of cultivation. The survey also enabled an understanding of farmers' preferences with respect to the production conditions of crops. The farmers regarded the provision of subsidies as one of the main factors that render a crop attractive. Opportunities for the adoption of the miscanthus cultivation include high yields and low input requirements. Barriers include land conflicts and land availability. Despite the opportunities for miscanthus development in the region, there are important challenges to consider for successful implementation of the crop.
A Micro-Typology of Contact Effects in Four Tibeto-Burman Languages

When minority languages with similar typological profiles are in long-term contact with a genealogically unrelated socioeconomically dominant language, the perfect context is provided for investigating which observed contact effects are demonstrably allied to sociolinguistic dynamics rather than purely structural ones. This paper investigates the factors determining the different extent of contact effects in four Tibeto-Burman languages (Gurung, Gyalsumdo, Nar-Phu, and Manange) spoken in a geo-politically defined and multilingual region of Nepal. Using corpus data and sociolinguistic interviews collected in the field, we demonstrate that a range of social, economic and geo-spatial factors contribute to asymmetries where contact effects are observed in the four speech communities. These notably include factors specifically relevant in mountasin-based communities, including proximity to transport and trekking routes, outward migration effects on small settlements, and the primary economies of the different parts of the Manang District.
A Wide-Bandwidth Ultrasound Receiver and On-Chip Ultrasound Transmitter for Ultrasound Capsule Endoscopy

This article presents an ultrasound (US) transceiver IC including a highly power-efficient US receiver (RX) and a high-voltage (HV) US transmitter (TX) for US capsule endoscopy (USCE) systems for the first time. The proposed USCE system employs the developed IC, a single-element piezoelectric transducer (PZT), and a mechanically rotating reflector to obtain 360° transmural scans while traveling through the gastrointestinal (GI) tract. Since the USCE system operates with a tiny battery, power efficiency is greatly important. To reduce power consumption by decreasing the required operating speed of the analog-to-digital converter (ADC), we propose a new RX structure employing synchronized analog envelope detection. It is unlike conventional US RX ICs that necessitate power-hungry high-speed ADCs to acquire the US signal residing at a high center frequency with wide bandwidth. Instead, the proposed work employs an analog envelope detector based on a quadrature demodulation method. As a result, it uses only a single circuit path rather than two (I and Q) paths by using a demodulation carrier whose phase is synchronized with the incoming US signal. A ping-pong noise-shaping (NS) SAR ADC is adopted to improve resolution while maintaining low power consumption. Besides, the TX IC, including an on-chip charge pump, is designed to generate HV pulses to drive the PZT. The prototype IC is fabricated in a 0.18 $\mu \text{m}$ bipolar-CMOS-DMOS (BCD) process. The RX consumes 2.3 mW, and the ADC achieves a 53.71 dB SNDR and a 66.45 dB SFDR. The TX generates 25 V pulses with 25 ns pulsewidth. US B-mode images of a water tank and a custom phantom are successfully obtained by using the prototype capsule endoscopy system employing the fabricated IC chip.
Forecasting of Ionospheric Total Electron Content Data Using Multivariate Deep LSTM Model for Different Latitudes and Solar Activity

The ionospheric state is becoming increasingly important to forecast for the reliable operation of terrestrial and space-based radio-communication systems which are influenced by ionospheric space weather. In this study, we have investigated and tested a multivariate long short-term memory (LSTM) deep learning model for its forecasting accuracy over different latitudinal regions during the solar quiet and solar active years. We also tested its prediction capability during the occurrence of a geomagnetic storm. Four stations qaq1 (60.7°N, 46.04°W), baie (49.18°N, 68.26°W), mas1 (27.76°N, 15.63°W), and bogt (4.64°N, 74.08°W) in the northern hemisphere were used in this study. To optimize the feature extraction process, we used heat map to find the correlation between TEC and the various exogenous parameters and finally nine correlated parameters were used as inputs to train the LSTM model. The performance of the LSTM model was validated by comparing it with the multilayer perceptron (MLP) machine learning algorithm using root mean square error (RMSE) and mean absolute error (MAE) as evaluation indices. The results showed an accuracy improvement of 70% and 64% over MLP during the solar quiet and active years, respectively. The prediction accuracy of our LSTM model was also 74% better than MLP during the geomagnetic storm event. These findings demonstrate the effectiveness of the developed LSTM model and the right selection of the exogenous parameters in estimating TEC, and suggest that this LSTM model can be used for short-term TEC forecasting.
High - pressure polymorphs of the ferroan dolomite: possible host structures for carbon in the lower mantle

17 In this study, we investigated four different ferroan dolomite samples using in situ 18 Raman spectroscopy and powder X-ray diffraction (XRD) at high pressures up to 48 GPa and 19 at room temperature. Our results show that the transition from Dolomite-I (Dol-I) to 20 Dolomite-II (Dol-II) occurs above 13-16 GPa, and the transition pressure depends on the 21
Diagnostic Errors in Japanese Community Hospitals and Related Factors: A Retrospective Cohort Study

Diagnostic error has recently become a crucial clinical problem and an area of intense research. However, the reality of diagnostic errors in regional hospitals remains unknown. This study aimed to clarify the reality of diagnostic errors in regional hospitals in Japan. A 10-month retrospective cohort study was conducted from January to October 2021 at the emergency room of Oda Municipal Hospital in central Shimane Prefecture, Japan. Participants were divided into groups with or without diagnostic errors, and independent variables of patient, physician, and environmental factors were analyzed using Fisher’s exact test, univariate (Student′s t-test and Welch’s t-test), and logistic regression analyses. Diagnostic errors accounted for 13.1% of all eligible cases. Remarkably, the proportion of patients treated without oxygen support and the proportion of male patients were significantly higher in the group with diagnostic errors. Sex bias was present. Additionally, cognitive bias, a major factor in diagnostic errors, may have occurred in patients who did not require oxygen support. Numerous factors contribute to diagnostic errors; however, it is important to understand the trends in the setting of each healthcare facility and plan and implement individualized countermeasures.
Using the Rods as Collector and Study of its Effect on Morphology and Uniformity of Nanofibers via Electrospinning

Nanotechnology research has lacked to provide new studies on nanofibers using the electrospinning method, the reasons are attributed that all parameters have been covered by previous studies. Believing that science is in a state of constant renewal leads to the possibility to study a parameter that has not been studied before, which affects the morphology of nanofibers. One of the disadvantages of nanofibers manufacturing is the formation of beads, and controlling the parameter helps reduce these beads. Field emission scanning electron microscope (FESEM) images reveal the formation of nanofibers and surface topography observations by atom force microscopy (AFM) indicates that the roughness is improved by changing the distance between rods of the collector. The rods function as a collector for nanofibers, changing this parameter improves the morphology and diameter of the nanofibers.
Demonstration of 100Gbaud DSM Signal Transmission in C-Band IM/DD System

We present a low-cost intensity-modulated direct detection (IM/DD) system for the transmission of high-order Quadrature Amplitude Modulation (QAM) signals. By adopting the 1-bit quantized Delta-sigma modulation (DSM) technology, we quantized the Discrete Multi-Tone modulation (DMT) time-domain waveform carrying the higher-order QAM signal into on-off keying (OOK) signal, and successfully realized the transmission of the higher-order QAM signal on the IM/DD link. Thanks to the high quantization SNR of the DSM modulator, up to 4096QAM transmission is supported. In particular, through the use of Vestigial Side Band (VSB) and pre-equalization, we experimentally demonstrated the transmission of 100G baud DSM-OOK signal in C-band 50 km fiber. The experimental results show that the bit error ratio (BER) of the 1024QAM signal can reach the hard decision forward error correction (HD-FEC) threshold <inline-formula> <tex-math notation="LaTeX">$3.8 \times 10^{-3}$ </tex-math></inline-formula>, and the BER of the 4096QAM signal can reach the soft decision forward error correction (SD-FEC) threshold <inline-formula> <tex-math notation="LaTeX">$4.2 \times 10^{-2}$ </tex-math></inline-formula>. To our knowledge, this is the first experimental demonstration of high-speed DSM signal transmission on optical fiber links.
A stabilized finite element procedure for turbulent fluid–structure interaction using adaptive time–space refinement

This paper presents our effort to addressing fluid–structure interaction (FSI) problems by means of computational mechanics. A stabilized finite element formulation is used to solve the incompressible Navier–Stokes equations written in primitive variables. The structure is modelled using rigid‐body dynamic equations solved using a Runge–Kutta method. The distinctive feature of our approach is the combination of large eddy simulation (LES)—based on implicit turbulence modelling—with time–space adaptive techniques in arbitrary Lagrangian Eulerian co‐ordinates (ALE). Three representative numerical examples are presented. The first one is the simulation of turbulent vortex shedding around a fixed obstacle, comparing our two‐dimensional (2D) LES results with experiments and more refined three‐dimensional (3D) numerical solutions. The second example presents an ALE computation with moving boundaries, where we were able to detect the lock‐in phenomenon for an oscillating cylinder driven by periodic vortex shedding. Our final example is the FSI problem associated to the flow around a dominant central span section of the Rio‐Niterói bridge, where we compare our results with experiments performed in a wind tunnel. Copyright © 2004 John Wiley & Sons, Ltd.
Simple Adjoint Retrievals of Wet-Microburst Winds and Gust-Front Winds from Single-Doppler Radar Data

Abstract The simple adjoint method for retrieving the low-altitude winds from single-Doppler scans is modified and tested for two events: the wet-microburst event and the gust-front event observed simultaneously by two radars during the Federal Aviation Administration–1990 summer field experiment at Orlando Airport. For the wet microburst, 42 consecutive wind fields are retrieved from each radar and the rms errors (measured by the rms difference between the retrieved and dual-Doppler analyzed winds) range from 1.1 to 4.9 m s−1, and the averaged error is 2.4 m s−1. For the gust front, 22 consecutive wind fields are retrieved from each radar, the rms errors range from 1.2 to 2.9 m s−1, and the averaged error is 1.9 m s−1. The rms error and spatial correlation between the retrieved and analyzed cross-beam tangential winds exhibit strong temporal variations for the wet microburst and moderate temporal variations for the gust front. The rms error is found to be temporally correlated to the rms amplitude of the.
Surface Water Isoscape Modeling in the Himalayan Region: An Alternative for Moisture Source Investigation, Hydrograph Separation, and Paleolatitude Estimation

The spatial distribution of water isotopes provides essential scientific data for understanding many hydrological, paleoclimate, and ecological processes. The limited isotopic data across the Himalayan River Basins (HRB) obstructs the study of basin‐scale hydrological processes. New data of stable isotopes of oxygen and hydrogen from Indus, in combination with a comprehensive compiled data set from HRB, was used for the first time to create isoscapes (δ18O and d‐excess) for specifically representing surface water. The δ18O and d‐excess isoscape define a clear isotopic distinction along a topographic gradient from south to north and west to east that could be reproduced (predicted) by using a Geographically weighted Regression Model (GWRM) based on surface heterogeneity by considering a combination of predictors (precipitation, temperature, evapotranspiration, runoff, elevation, slope, aspect, and land use landcover). The d‐excess isoscape demonstrates more complicated spatial variability, owing to differential moisture inputs from westerlies and the Indian Summer Monsoon, as well as secondary evaporation processes in the region. GWRM isoscapes have been able to compute the fractional contributions from different water sources across HRB. The model‐derived predicted δ18O and elevation values suggest a second‐order polynomial relationship that represents the Isotopic Lapse Rate more accurately than a linear one. The GWRM predictive isoscapes are sufficiently accurate to serve as a good proxy for the influence of moisture source and runoff estimation, palaeoecological studies, climate reconstruction, and changes in hydrological processes because of climate change. Therefore, GWRM can be applied to other regions where data is lacking.
Polarization-sensitive UV detector based on a double-layer subwavelength grating of Al and ZnO

Polarization-sensitive detectors are of great importance in the fields of remote sensing and imaging, environmental monitoring, and medical diagnosis. The surface plasmon effect can the enable polarization sensitivity of photodetectors through metallic gratings. However, limited by the precision of the nano-fabrication process, it is difficult to fabricate an ultraviolet (UV) polarization-sensitive detector integrated with sub-wavelength metal gratings and the polarization extinction ratio is relatively low. In this paper, an Al–ZnO composite double-layer grating structure was designed. The ZnO active layer and the Al layer were both fabricated into same-sized grating structures. Through this design, the slit width could be enlarged to some degree, while the response to 90° polarized light remained low. It is beneficial to realize a high polarization ratio and to spare the need for rigid fabrication accuracy. In addition, the influence of the structural parameters of the grating on the performance of the detector was studied by simulation. It was found that the resonance wavelength can be adjusted by changing the slit width and grating height, respectively. This provides a useful means for polarization-sensitive detection in different wavelength ranges. The polarization extinction ratio of the detector with a double-layer composite grating can reach 52 in the UV band (365 nm). This provides a good alternative to replace the traditional framework relying on the combination of polarizers and detectors. Moreover, it is a promising structure for high-density integrated photodetectors and imaging chips in the future.
Coding Method Based on Fuzzy C-Means Clustering for Spiking Neural Network With Triangular Spike Response Function

Although spiking neural network (SNN) has the advantages of strong brain-likeness and low energy consumption due to the use of discrete spikes for information representation and transmission, its performance still needs to be improved. This article improves SNN in terms of the coding process and the spike response function by invoking fuzzy sets. In terms of coding, a new fuzzy C-means coding (FCMC) method is proposed, which breaks the limitation of uniformly distributed receptive fields of existing coding methods and automatically determines suitable receptive fields that reflect the density distribution of the input data for encoding through the fuzzy C-means clustering. In terms of spike response function, triangular fuzzy numbers instead of the commonly used alpha-type function are used as the spike response function. Different from other functions of fixed shape, width parameters of the proposed function are learnt in the iterative way like weights of synapses do. Experimental results obtained on seven benchmark datasets and two real-world datasets with eleven approaches demonstrate that SNN with triangular spike response functions (abbreviated as T-SNN) combining FCMC can achieve improved performance in terms of accuracy, F-measure, AUC, required epochs, running time, and stability.
AI Based Precision and Intelligent Farming System

The growing global population and the increasing demand for food have led to a pressing need for sustainable agricultural practices. To address this challenge, we present an AI-Based Precision and Intelligent Farming System that leverages state-of-the-art machine learning techniques to optimize resource utilization and crop yields. This study demonstrates the integration of various data sources such as satellite imagery, IoT sensors, and historical data to develop a comprehensive and adaptive system for precision agriculture. Our approach employs deep learning models, including Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks, to analyze and predict crop health, growth, and potential yield. Furthermore, we propose a reinforcement learning-based decision-making module for effective irrigation, fertilization, and pest control management. The proposed system is extensively evaluated on real-world datasets, showing significant improvements in crop yield, water efficiency, and overall sustainability compared to traditional farming methods. Our findings suggest that the AI-Based Precision and Intelligent Farming System has the potential to revolutionize agriculture and contribute to global food security while minimizing environmental impacts.
Inter-Rater Reliability of Two Trained Raters Using a Goniometer for the Measurement of Finger Joints

At the hand therapy unit at the Wellington Hospital, two of the hand therapists undertook a study to establish their intra and inter-rater reliability. Intra-rater reliability was tested on asymptomatic hands whereas inter-rater reliability was investigated using patients. For the latter, 138 finger joints were measured in extension and flexion. The results showed that intra-rater reliability was 0.999 for both raters. For inter-rater reliability, the Pearson Product Moment Correlation Coefficient was calculated to be 0.993. A second calculation, of percentage agreement, was carried out to help establish how many degrees of movement a patient is required to achieve to produce a reliable conclusion that there had been a change.