Miracle-dz/UniFAR-FTUs huggingface dataset:
Central Lancashire Online Knowledge (CLoK)

Background: Nonsurgical guidelines recommend implementing a correctly fitted bra when managing back pain among larger breasted women. Achieving this ischallenging with current bra solutions, sizing principles, and fitting approaches. Persistent wearing of an ill-fitting bra can cause negative health implications, including non-specific back pain. Objectives: This study investigated immediate and short-term biomechanical and pain responses to changing breast support garment among larger breasted women with non-specific back pain. Methods: Participants (n 5 24) performed a standing task, drop jumps, and seated typing tasks while bra and spinal kinematic data were recorded. Five breast support conditions were assessed: participants ’ usual bra (control), a professionally fitted bra in the immediate term (standard) and after 4 weeks wear (standard 28 ), and a bra with an alternative design, measurement, and fitting approach in both the immediate term (alternative) and after 4 weeks wear (alternative 28 ). A bra fit assessment and clinical pain/disability questionnaires were included. Results: All participants failed the bra fit assessment in the control bra, compared with 87.5% (n 5 21) in the standard and 4.2% (n 5 1) in the alternative bras. The standard 28 and alternative 28 bras provided symptomatic relief, with the alternative 28 bra improving a greater number of outcome measures. Reduced nipple-sternal-notch distance was observed only in the alternative 28 bra condition. Conclusions: Symptomatic relief may be associated with the resting position of the breast tissue on the anterior chest wall. The alternative bra may provide potential clinical benefit if implemented as part of a nonsurgical or conservative pain management strategy. Alternative breast support garments should be considered to provide solutions to the problems associated with traditional bras.
Wearable Sensing of Facial Expressions and Head Gestures

This paper provides a survey of wearable sensing approaches for detecting facial expressions and head gestures, which provides a way to measure people’s natural emotions. Reliable facial expression and head gesture detection can contribute to a better understanding of an individual’s state of mind and to enrich human–computer interaction. In this paper, we survey artifacts and discuss opportunities and challenges in wearable
MÉGALITHES ET ESPACE : POUR UNE APPROCHE ANTHROPOLOGIQUE

Cette etude utilise une definition phenomenologique du megalithe alliee a des exemples issus de la documentation ethnographique. Ainsi, l'objet vertical et monumental est approche dans la pluralite de ses formes (elements du relief arbres, monolithes). La documentation anthropologique permet d'inscrire l'objet etudie dans sa relation au paysage comme un element naturel et de gestion du terroir. Dans un second temps, le megalithe est confronte a l'importance du discours concernant l'origine et l'organisation de l'espace.
A Signature-Based Power Model for MPSoC on FPGA

This paper presents a framework for high-level power estimation of multiprocessor systems-on-chip (MPSoC) architectures on FPGA. The technique is based on abstract execution profiles, called event signatures, and it operates at a higher level of abstraction than, for example, commonly used instruction-set simulator (ISS)-based power estimation methods and should thus be capable of achieving good evaluation performance. As a consequence, the technique can be very useful in the context of early systemlevel design space exploration. We integrated the power estimation technique in a system-level MPSoC synthesis framework. Subsequently, using this framework, we designed a range of different candidate architectures which contain different numbers of MicroBlaze processors and compared our power estimation results to those from real measurements on a Virtex-6 FPGA board.
MODELING NUTRIENT TRANSPORT FROM AGRICULTURAL FIELDS FERTILIZED WITH SEWAGE SLUDGE, MAUMEE RIVER BASIN

Enrique Gomezdelcampo, Advisor Nutrient loading resulting from non-point source pollution are of concern in the Maumee River Watershed. Maumee Bay has experienced large algal blooms in the past, but reductions in point source loading of nutrients had greatly reduced the blooms until recently. Algal blooms have been occurring in Maumee Bay during the late summer and early fall months. This study examines the effect that increased sewage sludge application has on the timing and loading of nutrients into Lake Erie. The Soil and Water Assessment Tool (SWAT) model was calibrated and validated for flow, sediment, and nutrients in the watershed to investigate the impact of various sewage sludge application scenarios. Calibration and validation were performed during 1990 through 1999 and 2000 through 2006 respectively at the watershed outlet defined by the Waterville gauging site. Quantitative statistical measures were utilized to evaluate model output. Graphical plots and statistical measures indicate that the modeled flow, sediment, and nutrients compare well to the observed data. Nash-Suttcliffe model efficiencies (ENS) for weekly flow were 0.76 during calibration and 0.65 for validation. ENS values for sediment, phosphorus, and nitrogen ranged between 0.46 and 0.62 during calibration and validation with the exception of nitrogen (-0.33) during validation. This study shows that SWAT was able to predict flow, sediment, and nutrients successfully and also evaluate the impact increased sewage sludge use could have in the Maumee River Watershed. The model shows that if sewage sludge is applied in late summer months as it typically is, the increased nutrient loading coincides with cyanobacteria blooms.
Ultra-Wideband Antennas for Wireless Capsule Endoscope System: A Review

Wireless capsule endoscopy (WCE) systems are used to capture images of the human digestive tract for medical applications, especially the noninvasive diagnostics and treatments of small intestinal diseases. As an important part of the WCE system, the antenna plays a crucial role in transmitting and receiving data. To transmit diagnostic real-time images from the inside body with high resolution at a high data transmission speed, ultra-wideband (UWB) antenna designs for the WCE system have been proposed by researchers in recent years. However, to the best of our knowledge, there are few papers to systematically review the UWB antennas used in the WCE system. In this paper, a comprehensive review of different UWB antenna designs for WCE system is presented. In-body and on-body UWB antennas are classified according to the radiative performances and structure. Particular attention is also paid to the models used in simulation and experiment, as well as some key performance parameters and technologies in the process of antenna design. This extensive summary of UWB antennas for WCE systems will help to understand the prospects and challenges in this field.
What would it take to achieve the Paris temperature targets?

The 2015 Paris Agreement aims to limit warming to 2 or 1.5°C above preindustrial level, although combined Intended Nationally Determined Contributions (INDCs) are likely insufficient to achieve these targets. We propose a set of idealized emission pathways consistent with the targets. If countries reduce emissions in line with their INDCs, the 2°C threshold could be avoided only if net zero greenhouse gas emissions (GHGEs) are achieved by 2085 and late century negative emissions are considerably in excess of those assumed in Representative Concentration Pathway (RCP) 2.6 (net −5 Gt CO2/yr, compared with −1.5 Gt CO2/yr in RCP2.6). More aggressive near‐term reductions would allow 2°C to be avoided with less end‐of‐century carbon removal capacity. A 10% cut in GHGEs by 2030 (relative to 2015) could likely achieve 2°C with RCP2.6 level negative emissions. The 1.5°C target requires GHGEs to be reduced by almost a third by 2030 and net zero by 2050, while a 50 year overshoot of 1.5°C allows net zero GHGEs by 2060.
Penerapan Metode Certainty Factor Pada Diagnosa Penyakit Saraf Tulang Belakang

Dalam menganalisa sebuah informasi dimungkinkan seorang pakar mengungkapkan informasi berupa pernyataan yang tidak pasti seperti mungkin, kemungkinan besar dan hampir pasti. Salah satu metode yang dapat digunakan dalam mengatasi ketidak pastian adalah metode certainty factor. Certainty factor merupakan metode yang mendefinisikan ukuran kepastian terhadap fakta atau aturan untuk menggambarkan keyakinan seorang pakar terhadap masalah yang sedang dihadapi. Untuk membantu dan mempermudah masyarakat dalam mendiagnosa penyakit saraf tulang belakang dapat menerapkan metode certainty factor pada sistem pakar. Saraf bagian tulang belakang merupakan organ yang penting bagi manusia. Terbatas dan tidak meratanya dokter spesialis saraf tulang belakang di Indonesia mengakibatkan masyarakat kesulitan dalam mendiagnosa penyakit tersebut. Sistem pakar dapat membantu untuk diagnosa penyakit, dimana sistem ini untuk merekonstruksi keahlian dan penalaran kemampuan seorang pakar. Pada penelitian ini, certainty factor diimplementasikan pada aplikasi diagnosa penyakit saraf tulang belakang. Sistem diujicobakan pada sejumlah masukan, hasil pengujian didapatkan memberikan hasil sesuai dengan perhitungan manual. Hasil pengujian dengan uji coba pada sejumlah masukan yang dilakukan didapatkan bahwa pengujian memberikan hasil sesuai dengan perhitungan manual. Sedangkan pengujian akurasi kesesuaian dari data testing yang didapatkan oleh pakar dengan output sistempakar didapatkan hasil output yang sesuai sebanyak sebesar 90%.
Zastosowanie i walidacja krigingu resztowego do interpolacji miesięcznych sum pola opadu atmosferycznego w Polsce

Residual kriging (RK) is applied to calculate spatial patterns of monthly precipitation in Poland. RK is one of the multi-dimensional interpolation schemes being used for spatial interpolation of various climatological data. The algorithm is supported by additional explanatory variables, which reflect physical processes responsible for spatial pattern of the interpolated phenomena. Here, the algorithm is implemented in the OpenSource GIS GRASS, supported by the R statistical package. These tools are found to be very flexible and efficient for this purpose. The RK results are compared with other interpolation procedures (Inverse Distance Method and Ordinary Kriging). Both visually and in terms of cross-validation errors, RK performs better than the other interpolation algorithms tested. The general statistics, Root Mean Square Errors and Mean Absolute Errors, are lower for RK than for the other methods compared, and the differences are statistically significant. The cross-validation errors are strongly correlated with the areas of high precipitation. There is also an increase of cross-validation error with the elevation a.s. l. , but the increase is smaller for the RK than for the other interpolation algorithms used.
Class-label Locally Linear Embedding in Face Recognition

Locally Linear Embedding (LLE) is an unsupervised non-linear manifold learning method, which has spurred increased interest in face recognition research recently. However, it is commonly known that a supervised method that considering the class-specific information always outperforms the unsupervised one, especially in biometric recognition task. In this paper, we propose a supervised LLE technique, known as class-label Locally Linear Embedding (cLLE). cLLE aims to discover the nonlinearity of high-dimensional data by minimizing the global reconstruction error of the set of all local neighbours in the data set. cLLE method is using user class-specific information in neighbourhoods selection and thus preserves the local neighbourhoods. Since the locality preservation is correlated to the class discrimination, the proposed cLLE is expected superior to LLE in face recognition. Experimental results on three face databases demonstrate the success of the proposed technique.
Shape memory alloy-based flexible manipulator for miniature submersible robots

This paper presents a design for a shape memory alloy (SMA) based flexible manipulator on miniature underwater Remote Operated Vehicles (ROVs). Conventional manipulators using separate electrical motor actuators and sensors can lead to problems in installation and control of miniature ROV during underwater operation. The size, weight and dimensions of the conventional manipulators are the main reasons for load interactions between ROV and manipulator which affects the stability and control. As an alternative approach here, an SMA wire trained with two-way shape memory effect and the concept of segment actuation is presented as a flexible manipulator for miniature ROV. Forward kinematic expressions as a function of segment length are developed and used for understanding the workspace and manipulation capabilities of the manipulator. Actuation models for heating and cooling of the segments independently and the experimental validation of the analytical expressions for underwater application are presented. The effect of fluid interaction on the conventional manipulator and SMA manipulator and the stability and control effect on ROV are also discussed.
Empowering Young Athletes: Elevating Anti-Doping Education with Virtual Reality

In recent times, doping's prevalence in sports has gained substantial recognition, sparking a concerted effort from researchers, policymakers, and sports bodies to underscore the critical role of impactful anti-doping education initiatives. An exhaustive examination of current literature underscores a critical requirement for advanced educational interventions that can effectively combat the multifaceted challenges presented by doping across the spectrum of competitive and recreational athletes. In response to this exigency, this paper introduces an innovative paradigm to redefine anti-doping education through the fusion of virtual reality (VR) technology. This proposed approach seeks to leverage VR's immersive potential, offering dynamic and interactive learning experiences that authentically mirror the complexities surrounding doping decisions. By immersing athletes within lifelike scenarios, VR education aims to provide a nuanced understanding of the psychological and emotional facets associated with doping, all within a secure and controlled environment. However, while the potential of VR in anti-doping education is promising, it also necessitates addressing technical, ethical, and usability considerations, an aspect that this paper further explores.
CAT-DUnet: Enhancing Speech Dereverberation via Feature Fusion and Structural Similarity Loss

Reverberation significantly degrades speech intelligibility, posing a substantial challenge in speech processing. While deep learning advancements offer promising solutions, current methodologies often overlook the effective integration of low-level and high-level feature representations, causing detrimental effects on overall performance. Simultaneously, prior approaches heavily rely on loss functions grounded in quantitative error metrics, which may not fully capture the perceptual intricacies of speech signals. To address these concerns, we introduce CAT-DUnet, a Unet architecture that integrates channel attention, time-frequency attention, and dilated convolution blocks to enhance feature fusion. We innovatively leverage the structural similarity as the training objective to align more closely with human perception, and investigate the effect of applying various reasonable transformations to spectrograms on the performance of the loss function. Through extensive ablation experiments, we demonstrate the effectiveness of our proposed enhancements. Our model outperforms state-of-the-art models on 6 out of 7 metrics, underscoring its exceptional performance.
A Sub-50-fsrms Jitter Fractional-N CPPLL Based on a Dual-DTC-Assisted Time-Amplifying Phase-Frequency Detector With Cascadable DTC Nonlinearity Compensation Algorithm

A 24–28-GHz sub-50-fsrms jitter fractional-<inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> charge pump phase-locked loop (CPPLL) is presented in this work. A dual-digital-to-time converter (DTC)-assisted time-amplifying phase-frequency detector (TAPFD) structure is proposed to suppress the in-band noise of charge pump (CP) and cancel the quantization error (QE) simultaneously while keeping low power consumption. Moreover, a cascadable DTC gear estimation and nonlinearity compensation algorithm (NLC) is also proposed to mitigate the fractional spur. The presented PLL achieves a measured integrated rms jitter including spurs of 37.1 fs with −255.2-dB FoM<inline-formula> <tex-math notation="LaTeX">$_{J}$ </tex-math></inline-formula> for integer-<inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> channel and 45.6 fs with −253.0-dB FoM<inline-formula> <tex-math notation="LaTeX">$_{J}$ </tex-math></inline-formula> for fractional-<inline-formula> <tex-math notation="LaTeX">$N$ </tex-math></inline-formula> channel.
AN ANALYSIS USING OWAS METHOD FOR IMPROVING EMPLOYEE WORK POSTURE IN OMAH KANDANG SMES

Omah Kandang SMEs is a SMEs in Surakarta that produce handmade cat cages. The customer of Omah Kandang SMEs scattered in several cities in Indonesia. Unfortunately, the booming demand is still difficult for producer to provide these, it caused by unproductive employee because of poor working postures. This research aims to determine the level of work risk for the employee using OWAS Method and providing suggestions of ergonomics work posture for improving employee productivity. OWAS Method is a method used for body measurement with dividing work activities in several time interval to avoid musculoskeletal disorder risk. The codes in this method includes back, arms, legs and load/use factor. In this research is known that employee work posture in weaving station fall into the category 2. It means unsafe for musculoskeletal system and need an improvement in the future. It is recommended to provide table for ergonomics work posture, so the employee become more productive.
Factors affecting brand preference in passenger car buying in Nepal

In today’s complex and highly competitive marketplace, marketers, realizing a need to develop sustainable strategies, have turned to branding as a solution. Understanding the brand preferences of consumers is always under discussion. In such context, this study measured the effects of price, attributes, brand personality, appearance, and self-congruity on brand preference in buying a passenger car. A deductive reasoning approach, quantitative method, and positivist epistemology with predetermined hypotheses were used. A six-point Likert scale structured survey was utilized to gather the primary information. The sample included 411 passenger car users in Nepal. A judgmental sampling technique and a causal research design were used. Through path analysis, the effect of price, attributes, brand personality, appearance, and self-congruity on dependent variables was identified using structural equation modeling. The study’s outcome showed that attribute (β = 0.062, p &gt; 0.05), price (β = –0.041, p &gt; 0.05), and appearance (β = 0.022, p &gt; 0.05) have no significant positive impact on consumer brand preference. Moreover, the study discovered that brand preference is influenced by self-congruity (β = 0.297, p &lt; 0.05) and brand personality (β = 0.232, p &lt; 0.05) in buying passenger cars in Nepal. It is concluded that brand image and prestige are more critical for high-involvement products. These outcomes provide a road map for future scholars and business people with a view of the emerging context of market development.
Hybrid ARIMA-Spatial Autocorrelation (Moran Index and LISA) for Covid-19 Vaccination in All Indonesian Provinces

Numerous issues arise from stochastic processes with temporal and spatial index parameters. From 2020, Covid-19 has occurred worldwide. Combining time series with geographical analysis is crucial. ARIMA and spatial autocorrelation analysis using Moran’s Index and LISA are prominent models for the two analyses. ARIMA predicts future values. The ARIMA model is applied to all recorded locations since it involves a stochastic process with a time and location parameter index. Then the prediction results at each location were examined using spatial autocorrelation, starting with the Moran index to see global relationships, then LISA (to look at the relationship between locations locally, to see which locations have a significant effect). The Queen Contiguity weight matrix calculates spatial autocorrelation (assuming that locations that are directly adjacent to each other have a spatial effect). Spatial autocorrelation will divide each place into four quadrants: High-High (HH), High-Low (HL), Low-High (LH), and Low-Low (LL). This approach was applied to 2021 Indonesian vaccination rates in all 34 provinces (354 days). Hence, the ARIMA model was applied to the 34 provinces, and each location received three forecasting. Moran’s Index revealed spatial autocorrelation in the 354th and 355th time forecasts. LISA shows that Aceh (LL), West Sumatra (LH), South Sumatra (HH), Lampung (LH), and North Maluku (LL) influence other provinces (LH).
What factors control the trend of increasing AAOD over the United States in the last decade?

We examine the spatial and temporal trends of absorbing aerosol optical depth (AAOD) in the last decade over the United States (U.S.) observed by the Ozone Monitoring Instrument (OMI). Monthly average OMI AAOD has increased over broad areas of the central U.S. from 2005 to 2015, by up to a factor of 4 in some grid cells (~60 km resolution). The AAOD increases in all seasons, although the percentage increases are larger in summer (June‐July‐August) than in winter (December‐January‐February) by a factor of 3. Despite enhancements in AAOD, OMI AOD exhibits insignificant trend over most of the U.S. except parts of the central and western U.S., the latter which may partly be due to decreases in precipitation. Trends in AAOD contrast with declining trends in surface concentrations of black carbon (BC) aerosol. Interannual variability of local biomass burning emissions of BC may contribute to the positive trend in AAOD over the western U.S. Changes in both dust aerosol measured at the surface (in terms of concentration and size) and dust AAOD indicate distinct enhancements, especially over the central U.S. by 50–100%, which appears to be one of the major factors that impacts positive trends in AAOD.
Primary Quench Detection Analysis for the EU-DEMO Toroidal Field Coils

To protect the Toroidal Field Coils (TFC) of the EU DEMO tokamak, in case it will be realized with low temperature superconducting (LTS) materials, a reliable and fast quench detection system (QDS) is required. Although these TFC coils are operated in static mode, voltages across their winding pack (WP) will be generated during machine operation due to the presence of dynamic magnetic fields. Two sources of magnetic coupling, responsible for noisy signals on the quench detection circuitry in a Fast Plasma Disruption scenario, are here considered and analyzed. Due to the high electromagnetic noise environment, the co-wound (CW) technology must be adopted for the quench sensors and an aligned and twisted layout (CWA&T) is necessary due to the magnetic interaction with the superconductor (SC) strand helicity. The poloidal component of the plasma current is responsible for a noisy signal on the CW and a strategy for signal compensation will be suggested and the contribution evaluated numerically. The signal induced on a SC cable due to the helicity can be compensated adopting a CWA&T configuration. The twist pitch length (TP) of the CWA&T is a critical parameter for a proper noise compensation. Since it is challenging to obtain a reliable TP length from a numerical simulation, we here propose an experimental approach to assess the proper TP length. There is not a constraint on the TP length from the poloidal plasma current induced signal and we can conclude that a single TP, optimized for helicity compensation, will be sufficient.