Miracle-dz/UniFAR-FTUs huggingface dataset:
New Insights on Application of Return Loss Measurement for Starch Content Estimation in Cassava

This research explores the use of radio frequency (RF) return loss measurement to characterize cassava quality and estimate the starch content of cassava roots, with new equivalent circuit models presented. While pure starch is non-conductive, the content of charged ions in the raw composite cassava flour provides a potential marker for estimating the starch content of cassava, which is important for the design of quality measurement devices based on the return loss method. The study also raises questions for further exploration, such as understanding the pattern of distribution of the electrolytic components in a fresh root and exploring the relationships between these ions and other properties of cassava. Overall, these new findings offer new directions for research and development in the field of food quality assessment.
Mixed-Precision Arrangement via CRB for DOA Estimation Using SLA

We consider a mixed analog-to-digital converter (ADC) based architecture for the direction of arrival (DOA) estimation under sparse linear arrays (SLAs) with arbitrary structure. Given the fixed number of ADCs, the arrangement of high-precision and one-bit ADCs in SLA is analyzed using Cramér-Rao bound (CRB). To obtain the optimal mixed-precision arrangement, we simplify the problem into a 0–1 integer quadratic programming and efficiently solve it by using the alternating direction method of multipliers (ADMM) algorithm. Simulation results validate the effectiveness of our approach. Furthermore, SLAs, such as the nested and co-prime array, can achieve a lower CRB with the optimal mixed-precision arrangement.
Coquandite, Sb6O8(SO4).H2O, a new mineral from Pereta, Tuscany, Italy, and two other localities

Abstract Coaquandite, a new antimony oxy-sulphate hydrate, occurs as spheroidal knobs of silky fibres or, rarely, as tiny transparent colourless lamellar crystals on stibnite at the Pereta mine, Tuscany, Italy; it is associated with klebelsbergite, peretaite, valentinite, sulfur, gypsum, stibiconite, and senarmontite. Coquandite is triclinic P1, with a 11.434(7), b 29.77(4), c 11.314(4) Å, α 91.07(7)°, β 119.24(3)° γ 92.82(1)° . It has a cell volume of 3352(5)Å3 with Z = 12 and a calculated density of 5.78 g cm−3. The crystals, elongated along [001] and flattened on {010}, display polysynthetic twinning with (010) as the twin plane. Optically, they are biaxial (+) with z ≈ c, 2V ≫ 60° n = 2.08(5). The strongest lines of the X-ray powder pattern are [d in Å, (I), (hkl)] 14.84(50)(020), 9.27(41)(111, 110), 6.81(67)130, 3.304(93)(090), 3.092(100)(330). Coquandite has also been found at the Cetine mine, Tuscany, Italy, and at the Lucky Knock mine, Tonasket, Okanogan County, Washington, USA. 22 microprobe chemical analyses (elemental microanalysis for H) gave Sb2O3 88.91, SO3 8.35, CaO 0.04, Na2O 0.03, H2O 1.43, total 98.76 wt. %, corresponding to the empirical formula (Sb + S = 7) Sb5.98Ca0. 01Na0.01O7. 96(SO4)1.02. 0·78H2O, and to the idealised formula Sb6O8(SO4). H2O. The I.R. spectrum, which confirms the presence of water in the formula, is given. A partial structural arrangement is also given: the Sb polyhedra lie in nine layers perpendicular to [010] and form 'hexagonally' shaped groups surrounded by SO4 tetrahedra.
Numerical modelling of the relationship between the present tectonic stress field and the earthquakes in the Western Pacific Subduction Zone

The tectonic stress field of the Western Pacific Subduction Zone (WPSZ) has been affected by the interaction among the Euro‐Asian, Philippine and Pacific Plates, and the effect is manifested by the occurrence of huge earthquakes in this region. Here, using numerical simulation of the finite element method, attempts were made to evaluate the NW‐directed subduction of the Western Pacific Plate on the three secondary subduction zones, namely the Japan Subduction Zone, the Izu‐Bonin Subduction Zone and the Mariana Subduction Zone. In these zones, the structural geometry and viscoelastic property of the model were determined, as well as two main megathrust fault planes identified, by means of a comprehensive structural analysis of tomography and Crustal 2.0 data. This study shows that the tectonic stress field and earthquakes in the three secondary subduction zones have different distribution features under continuous NW‐directed subduction of the Western Pacific Plate; i.e. (1) the strong coupling area in the Japan Subduction Zone reflected subducted seamounts, ocean ridges or other topographic highs that control the frequent occurrence of historical large earthquakes and stress concentration; (2) in Izu‐Bonin Subduction Zone, there were fewer earthquakes compared with the Japan Subduction Zone, the reason for this kind of distribution is that the contact area and properties have been changed between the subducting Pacific Oceanic Plate and the overlying Philippine Oceanic Plate; and (3) earthquakes that happened in the Mariana Subduction Zone have complicated types, including thrust‐type, normal‐type and strike‐slip‐type earthquakes, which are triggered by the subducting and retreating of the Pacific Oceanic Plate, and an angular difference between the subducting direction of the Pacific Oceanic Plate and the strike of the Mariana Trench. In summary, formation of differences among the tectonic stress field and earthquake distribution of the three subduction zones are correlated not only to the geometrical structures of the major faults but also to the subducted seamounts and the strike directions of the trenches. Copyright © 2016 John Wiley & Sons, Ltd.
Journal Pre-proof SARS-CoV-2 nasopharyngeal viral load in individuals infected with BA.2, compared to Alpha, Gamma, Delta and BA.1 variants: a single-center comparative analysis

Background. SARS-CoV-2 has evolved, leading to the emergence of new Variants Of 64 Concern (VOCs) with significant impact on transmissibility. Although the transmission 65 process is complex, higher nasopharyngeal viral load (NP-VL) can be considered as a proxy for greater transmissibility. to compare across a set of representative VOCs observed in mildly symptomatic patients. based vaccination, CTs for Gamma were lower than those seen for Alpha and higher than Delta, for 79 Delta were similar to BA.1, for BA.2 were lower than Delta and BA.1. 80 Conclusions. Our analysis shows higher NP-VL of BA.2 compared to previously circulating 81 VOCs, even after controlling for factors potentially contributing to the amount of 82 nasopharyngeal viral RNA, included vaccination, supporting the increased transmissibility of 83 BA.2. Further studies are necessary to clarify this mechanism and to provide guidance for 84 public health measures.
Risk preferences and development revisited: A field experiment in Vietnam

We obtain rich measures of risk preferences of poor farmers in Vietnam, and estimate structural models that capture risk preferences over different probability levels and across different domains (gains and losses). The results break radically with the previous literature on risk preferences, in developed and developing countries alike. Far from being particularly risk averse, our Vietnamese farmers are on average risk neutral. At the same time, we find our preference measures to perform well at predicting behavior, from the purchase of lottery tickets to risk management on the farm. We also find strong direct evidence of a risk-income paradox. While risk aversion is strongly decreasing in income within our farmer subject population, our Vietnamese farmers are significantly less risk averse than subjects in Western countries according to measurements obtained using the same decision tasks and procedures.
Enabling High-Speed Connectivity in Urban Environments Through Composite Base Stations and Dynamic Spectrum Scheduling

The combination of Composite Base Stations (CBSs) and Dynamic Spectrum Scheduling (DSS) can enable high-speed connectivity in urban environments, providing seamless connectivity to users and supporting a wide range of high-bandwidth applications. This paper investigates the performance of CBSs combining Fifth Generation (5G) cellular network and Fourth Generation (4G) Long-Term Evolution (LTE) modes in an urban environment such as a university campus. The comparison considers sub-6GHz and mmWave frequencies (28GHz) and a DSS to improve network performance and increase overall system capacity. The results show that the CBS approach improves network performance, increasing system capacity and provides high-speed connectivity to users. Additionally, this research highlights the potential of mmWave frequencies for use in heterogeneous networks to improve coverage over a large area. The findings of this study offer valuable insights for network planners and operators, demonstrating the benefits and challenges of CBS deployment
Exploring the Influence of Pre-Processing Techniques in Obtaining Labelled Data from Twitter Data

Pre-processing input text play a crucial role in text classification by reducing dimensionality and removing unnecessary content. Different text pre-processing techniques affect prediction models' input vocabulary and documents. Many of the decisions that affect model performance are made during data pre-processing. The notion of data pre-processing affecting the outcome of a prediction task is widely accepted, yet not much work has been done on measuring this impact. In this study, six different text pre-processing techniques were applied, resulting in five types of labelled datasets used in classification. Three machine learning classifiers, Naive Bayes (NB), Random Forest and Logistic Regression (LG), were used. The accuracy of the classifiers after applying to the different datasets were calculated. Results showed that Naive Bayes, Random Forest and Logistic regression accuracy significantly improved after using only stemming and removing Stop Words. Naive Bayes achieved the highest accuracy of 90.71% when the dataset was stemmed and Stop Words removed. Similarly, Random Forest and Logistic Regression gained a higher accuracy of 94.5% and 93.5% when the dataset was stemmed, and Stop Words removed. In addition, accuracy of classifiers on labelled dataset which was tokenized and lemmatized reduced to 88.44% for Naive Bayes, 92.94% for Random Forest and 92.23% for Logistic Regression. The study concludes that the removal of Stop Words, stemming and lemmatization affect data labelling and prediction model accuracy.
Impact of the National Energy and Climate Plan on the Italian Distribution Networks Infrastructure

To achieve the 2030 decarbonization objectives, a rapid growth is expected in distributed generation and demand electrification (e.g., heat pumps, electric vehicles). This will result in significant investments to upgrade the distribution network and the need for a proper planning, able to consider both traditional infrastructure reinforcement and local flexibility. Due to the lack of public detailed information on the network infrastructure and connected users, the limited data available is used to create a synthetic distribution system, which, according to previous analyses, was found to be a reasonable approximation of the actual Italian distribution system. Based on this model, a simplified planning procedure is applied to estimate the necessary investments to reinforce the network and to determine the benefits of smart solutions in scenarios of load and generation growth. The results show that the planning costs depend on the geographical position of new users and that they could be reduced by adopting smart grid solutions, such as on-load tap changers, active and reactive power control of local resources, EVs overnight charging.
The oldest Mammut (Mammalia: proboscidea) from New Mexico

We redescribe and reillustrate the holotype of Mammut (=Mastodon) raki (Frick, 1933), and establish its provenance as the Palomas Formation near the western shore of Elephant Butte Lake in Sierra County, south-central New Mexico. This specimen represents a very primitive Mammut of probable Blancan age, the oldest representative of the genus from New Mexico.
The attitude of nurses towards inpatient aggression in psychiatric care

Professional skills to adequately manage patient aggression are a pre-requisite for nurses working in psychiatric hospitals. These ‘technical’ skills, however, are necessary but not sufficient for an effective nurse intervention. The nurses’ attitude towards client aggression also contributes to their response to the patient’s behaviour. In order to study the domains (types) of attitudes towards aggression, a sample was taken of nurses working in the fields of general psychiatry ( n =288), psychiatry for children and adolescents ( n =242) and psychogeriatrics ( n =88). A cross-sectional survey design was adopted for the study. The Attitudes Towards Aggression Scale (atas) consisting of 32 items is presented, representing three types of attitudes towards aggression: aggression as a ‘harming’ reaction, a ‘normal’ and a ‘functional’ reaction. The strongest predictors of the type of attitude respondents had towards the aggressive behaviour of their clients were 1 the field, 2 the setting they worked in, 3 the gender and 4 the type of shifts they predominantly had. Although the measure of domains of nurses’ attitudes towards aggression needs further psychometric testing, it can be a useful tool in clinical practice for the assessment of staff attitudes towards aggression. This can support the decision-making about the management of aggressive behaviour on a ward.
The Effect of Chemotherapy Treatment on Bone Marrow Mesenchymal Stromal Cell Adipocyte Differentiation

In an effort to understand the cause of late onset cardiac, metabolic, and musculoskeletal conditions in paediatric acute lymphoblastic leukaemia (ALL) survivors, the adipogenic differentiation of bone marrow (BM) mesenchymal stromal cells (MSCs) has been studied. There is a complex network of factors influencing adipogenesis, which to date is not completely understood. Hence, the overall aim is to better understand the cellular and molecular basis behind the development of these conditions in survivors. To this end, we asked whether treating BM MSCs in vitro with cancer drugs, Doxorubicin and Dexamethasone, will initiate a skewed differentiation towards adipogenesis. BM MSCs were analysed with respect to lipid accumulation, gene expression, and adipokine production. In general, our hypothesis was not confirmed. No lipid accumulations were detected in the cells. In analysis of gene expression of the adipogenic transcription factors PPARγ and C/EBPα, certain changes were seen; however, due to lack of biological replicates, no statistical analyses could be applied to the results. Lastly, the inflammation and adipogenesis associated cytokine IL-6 displayed a slight increase, whereas the cytokines IL-8 and TNF-α were undetectable.
Carbon Price Prediction in the European Market using Deep Learning

Greenhouse gas emissions (GHG) generated by human activities have negative impacts such as climate change, global warming, threats to food security, natural disasters, and rising sea levels. Several countries have implemented measures to reduce GHG emissions, including reforestation, environmentally friendly industries, and providing incentives to initiatives that reduce GHG emissions. A carbon price prediction is provided to optimize carbon incentives for investors. Carbon price fluctuation on global market conditions requires methods to predict the prices accurately. The methods utilize carbon price data from European Energy Exchange (EEX) carbon market. The data employed in this research encompasses the closing prices of carbon. This research applies two algorithms, Deep Multilayer Perceptron (DMLP) and Long Short-Term Memory (LSTM), to forecast carbon prices in time series predictions. These models use the closing price variable. The simulation results show that the Deep Multilayer Perceptron method is more accurate than the Long Short-Term Memory method. The method with higher performance will result in better risk measurement of carbon price.
Multi-Modal Microfluidic Bend Sensor for Soft and Robotic Sensing Applications*

Bend sensors play a pivotal role in gaining insights into the dynamic behavior of flexible mechanical systems and bolstering safety considerations. This paper introduces a novel microfluidic-based multi-modal bend sensor that offers tremendous potential for a wide range of applications, especially in robotics and microsystems. Our bend sensor features a flexible substrate embedded with a liquid metal-filled microchannel filled. The fabrication process utilizes simple and cost-effective 3D printing and soft-lithography techniques. As the microchannel deforms, the sensor measures changes in electrical resistance across its terminals, providing reliable indications of bending intensity and direction. By incorporating rectangular through-voids in close proximity underneath the serpentine microchannel, the bending-induced change in the length and cross-sectional area of the microchannel is magnified. This resulted in an enhanced bending sensitivity. Experimental characterizations demonstrate the sensor's effectiveness and versatility under various bending conditions. Furthermore, the sensor is capable of detecting the amount of applied pressure as well as the degree of twisting, expanding its functionality. With its soft and flexible nature, the novel multi-modal bend sensor can be seamlessly integrated into wearable technology and soft robotics applications, offering real-time insights into bending, pressure, and twisting for improved safety and control.
Energy Consumption for Cognitive Radio Network Enabled Multi-Access Edge Computing

This article discusses optimizing energy Consumption in CRN-enabled Multi-access Edge Computing (MEC) systems, presenting a novel approach to optimize the energy Consumption of a cognitive radio network-enabled MEC system using iterative optimization techniques. The proposed model aims to minimize the system's energy consumption while maintaining its performance and quality of service requirements. The iterative optimization algorithm is used to find the optimal allocation of resources, such as computing, communication, and power, among different nodes in the MEC system. As a result, the cognitive radio network enables efficient spectrum utilization by dynamically allocating available spectrum to different users based on their requirements. The performance evaluation approach is evaluated through simulations, and the results show that it can significantly improve the energy consumption of the MEC system while maintaining its performance and QoS requirements. This article contributes to developing sustainable and energy-efficient communication systems for future wireless networks.
Systematic Search for Stabilizing Dopants in ZrO₂ and HfO₂ Using First-Principles Calculations

In this study, we performed a systematic search for dopants to stabilize the tetragonal structure of HfO2 and ZrO2 by using high-throughput first-principles calculations. By exhaustively exploring all possible impurity configurations for over 12,000 systems, we obtained the expected most stable doping status for various dopants at different doping levels. The stabilization effect of dopants are investigated and compared. The results show that Si or Ge significantly stabilize the tetragonal phase.
The behavior of Li and B during planetary basalt crystallization

Abstract Light-lithophile-element zoning patterns in pyroxene in the Shergotty and Zagami martian basaltic meteorites have previously been presented as evidence for pre-eruptive martian water. We investigate the partitioning of Li and B in martian igneous minerals experimentally, using a composition approximating that of the Queen Alexandria Range (QUE) 94201 martian basalt in one-atmosphere gas-mixing furnaces. Partition coefficients obtained for pyroxene (DLi = 0.2, DB = 0.023), plagioclase (DLi = 0.37, DB = 0.024), olivine (DLi = 0.27, DB = 0.007) and merrillite (DLi = 0.7, DB = 0.03), measured using Secondary Ion Mass Spectrometry of experimental charges, demonstrate that Li and B are incompatible in these minerals. As a test of our experimentally determined, anhydrous partition coefficients, we analyzed pyroxene in the Pasamonte eucrite, an asteroidal basalt with an anhydrous petrogenesis. Coupling of the partition coefficients with Pasamonte pyroxene analyses gives B parental melt concentrations in relative agreement with bulk rock analyses; however, Li parental melt concentrations and bulk analyses do not agree, suggestive of post-crystallization modification of Li zoning trends. Our results demonstrate that Li and B zoning patterns in pyroxene in martian basalts cannot be explained by the uptake of Li and B by co-crystallizing plagioclase, olivine, or merrillite, and suggest that the petrogeneses of Shergotty and Zagami involved something other than simple, one-atmosphere, anhydrous crystallization
Germination characteristics of prairie dropseed, blanketflower, and hairy goldaster in response to prechill and temperature treatments

Germination Characteristics of Prairie Dropseed, Blanketflower, and Hairy Goldaster in Response to Prechill and Temperature Treatment Aurora Rose Roemmich May 2011 Native plant materials centers across the United States create concentrated sources of native species seeds, cuttings, and plants that are readily available for use in restoration, landscaping, and other revegetation projects. In addition, these centers provide materials from local genetic sources that are adapted to the environmental conditions of the target site which makes them less likely to aggressively compete with, or decrease the genetic fitness of, extant native vegetation. Despite the increased desire to use native plant materials for re-vegetation, a general lack of information regarding germination and propagation requirements for many native species has restricted their usage. A better understanding of dormancy and germination patterns for these native species will make them increasingly available and affordable. As part of an effort to develop a native plant materials center for the Black Hills, three native species (Sporobolus heterolepis, Heterotheca villosa, and Gaillardia aristata) were selected to determine optimum germination conditions. Germination trials were conducted following two pre-treatment conditions (2-week prechill at 5°C and no prechill), under six temperature treatments in 2008 and seven temperature treatments in 2009. Tetrazolium
A Three-Phase Hybrid Multilevel Inverter for Medium Voltage Applications

Multilevel inverters (MLIs) have gained significance for medium and high-power applications. Traditional topologies yield sinusoidal-like output voltages, but complexity escalates with higher output levels. Thus, research has focused on developing MLIs with reduced switch counts to simplify control while maintaining target total harmonic distortion (THD). This paper extends the application of a 1-phase hybrid MLI (HMLI) to 3-phase HMLI systems and incorporates an output filter to meet the THD requirements. The suggested 3-phase HMLI achieves 7-, 9-, and 11-level outputs without altering the base topology by controlling the sequence of switching operations. The 3-phase HMLI is compatible with battery and solar sources and suitable for medium-voltage applications. The performance is thoroughly validated using MATLAB/Simulink, including output filter analysis, various modulation index values, and modulation techniques (PD. POD. APOD) and different output levels.