Miracle-dz/UniFAR-FTUs huggingface dataset:
UAV-Based Estimation of Grain Yield for Plant Breeding: Applied Strategies for Optimizing the Use of Sensors, Vegetation Indices, Growth Stages, and Machine Learning Algorithms

Non-destructive in-season grain yield (GY) prediction would strongly facilitate the selection process in plant breeding but remains challenging for phenologically and morphologically diverse germplasm, notably under high-yielding conditions. In recent years, the application of drones (UAV) for spectral sensing has been established, but data acquisition and data processing have to be further improved with respect to efficiency and reliability. Therefore, this study evaluates the selection of measurement dates, sensors, and spectral parameters, as well as machine learning algorithms. Multispectral and RGB data were collected during all major growth stages in winter wheat trials and tested for GY prediction using six machine-learning algorithms. Trials were conducted in 2020 and 2021 in two locations in the southeast and eastern areas of Germany. In most cases, the milk ripeness stage was the most reliable growth stage for GY prediction from individual measurement dates, but the maximum prediction accuracies differed substantially between drought-affected trials in 2020 (R2 = 0.81 and R2 = 0.68 in both locations, respectively), and the wetter, pathogen-affected conditions in 2021 (R2 = 0.30 and R2 = 0.29). The combination of data from multiple dates improved the prediction (maximum R2 = 0.85, 0.81, 0.61, and 0.44 in the four-year*location combinations, respectively). Among the spectral parameters under investigation, the best RGB-based indices achieved similar predictions as the best multispectral indices, while the differences between algorithms were comparably small. However, support vector machine, together with random forest and gradient boosting machine, performed better than partial least squares, ridge, and multiple linear regression. The results indicate useful GY predictions in sparser canopies, whereas further improvements are required in dense canopies with counteracting effects of pathogens. Efforts for multiple measurements were more rewarding than enhanced spectral information (multispectral versus RGB).
Optimizing the two-coil mutual inductance measurement of the superconducting penetration depth in thin films

When a pair of coils is positioned on opposite sides of a superconducting thin film, measurement of their mutual inductance may in principle be used to infer the penetration depth λ in the superconductor. We have studied how to optimize this measurement with respect to coil design, and have found that the approach that has been generally used is far from the optimum. Useful simplifications to the expression relating mutual inductance to penetration depth are derived. An analysis of the sources of uncertainty in determining λ is presented. For an optimized coil set, the major source of uncertainty often is uncertainty of the thickness of the film. The sensitivity to changes in λ is also studied; it is shown that this can approach 1 pm for a typical high temperature superconductor sample. Finally, it is shown that the analysis may be extended to normal metal films, with the skin depth playing a role similar to that of the penetration depth in superconductors. Measurement of a high conductivity normal metal .
A Comparative Analysis of Classification Algorithms for Cyberbullying Crime Detection: An Experimental Study of Twitter Social Media in Indonesia

Purpose: This research aims to identify content that contains cyberbullying on Twitter. We also conducted a comparative study of several classification algorithms, namely NB, DT, LR, and SVM. The dataset we use comes from Twitter data which is then manually labeled and validated by language experts. This study used 1065 data with a label distribution, namely 638 data with a non-bullying label and 427 with a bullying label.Methods: The weighting process for each word uses the bag of word (BOW) method, which uses three weighting features. The three-word vector weighting features used include unigram, bigram, and trigram. The experiment was conducted with two scenarios, namely testing to find the best accuracy value with the three features. The following scenario looks at the overall comparison of the algorithm's performance against all the features used.Result: The experimental results show that for the measurement of accuracy weighting based on features and algorithms, the SVM classification algorithm outperformed other algorithms with a percentage of 76%. Then for the weighting based on the average recall, the DT classification algorithm outperformed the other algorithms by an average of 76%. Another test for measuring overall performance (F-measure) based on accuracy and precision, the SVM classification algorithm, managed to outperform other algorithms with an F-measure of 82%. Value: Based on several experiments conducted, the SVM classification algorithm can detect words containing cyberbullying on social media.
Mass spectrometry instrumentation for chemists and biologists

Like Gaul, a mass spectrometer may be divided into three parts: source, analyser and detector system. The status of each is reviewed. Recent developments concerning the ion source region include improved techniques for chemical ionization (c.i.), field desorption (f.d.) and negative ion formation. There has also been significant work with pyrolysis probes, high pressure liquid chromatography (h.p.l.c.) interfaces and improved fast pumping for use with atmospheric pressure ionization (a.p.i.) and direct coupling of capillary column gas chromatographs. Commonly used analysers are now either the quadrupole r.f. filter or single/double focusing magnetic deflexion instruments. Magnetic instrument developments reviewed include improvements to sensitivity (Z-focusing and image curvature correction), higher scan speeds (laminated magnets), mass indication and marking, peak jumping when using multiple ion detection (m.i.d.) and reverse geometries (permitting mass analysed ion kinetic energy spectroscopy; MIKES) and linked scan (providing metastable ion information). Detection systems are discussed in detail and include consideration of computer data acquisition and display. Important are simultaneous foreground/background systems, library search, wide dynamic range, precision mass measurement at low resolution (higher sensitivity) and multiple ion detection at either low or high resolution. The use of linked scan and MIKES as specific ion detectors is considered.
‘We do things together': exploring a household perspective on early integration processes of recent refugees

ABSTRACT People are not isolated, but embedded in ongoing social networks of which the household is a crucial one. Yet, integration trajectories and outcomes are often measured and evaluated on the individual level. To nuance previous research’ preoccupation with a somewhat disconnected individual, we explore a household perspective to better understand early integration trajectories. We depart from the idea that refugees regard their direct families extremely important in early settlement times and employ the notion of embeddedness and the Family Investment Model to guide this investigation. Based on qualitative work among recent Syrian refugees to the Netherlands, we showcase four particular stories that reveal that individual integration trajectories are (also) the product of the households in which these are embedded as individuals exchange integration goals among each other and view integration as a joint venture of all household members. A household perspective succeeds to uncover important mechanisms in integration processes, most notably the fact that the expectations and ambitions that refugees set for themselves and their families is an important driver of individual integration trajectories. We conclude that the integration of individuals needs to be considered more often in the context of households in order to better understand and support them.
Covalent bonds and their crucial effects on pseudogap formation in α-Al(Mn, Re)Si icosahedral quasicrystalline approximant

X-ray charge densities of Al-based icosahedral quasicrystalline approximant crystals α-AlReSi, α-AlMnSi, and Al 1 2 Re were observed by a combination of the maximum entropy method with the Rietveld method. We successfully obtained the clear images of interatomic covalent bonds between Al and transition metals (Mn, Re) and those in the Al (or Si) icosahedron in Mackay icosahedral clusters of both α-AlReSi and α-AlMnSi approximant crystals. The bonding nature of the three kinds of glue atom sites connecting Mackay icosahedral clusters was also clarified. This covalent bonding nature should strongly relate with the enhancement of the electron density-of-states pseudogap near the Fermi level. In addition, the interatomic covalent bonds of α-AlReSi are stronger than those of α-AlMnSi. This fact leads to the low effective carrier density of α-AlReSi in comparison with that of α-AlMnSi. Unlike the covalent bonding nature of an icosahedron in α-AlReSi and α-AlMnSi crystals, the Al icosahedron with an Re center atom exhibits no Al-Al interatomic covalent bonds in the Al 1 2 Re crystal. The tendency for metallic-covalent bonding conversion in the Al icosahedron, which is related to the atom site occupancy of the icosahedral cluster center, is also strongly supported.
Selection of Investment Mode for Cross-border O2O Channel Construction Based on Cloud Model

In the era of rapid development of the Internet, cross-border electronic commerce is becoming more and more prosperous, and many enterprises are beginning to invest abroad in the form of cross-border online-to-offline (O2O) to explore foreign markets. Under this background, this paper focuses on the choice of foreign investment mode of enterprises when they build cross-border O2O channels, and establishes an appropriate evaluation system of investment mode for cross-border O2O channel construction. On the basis of the evaluation system, Cloud Model is used to analyze and compare Greenfield investment, Joint Venture investment and Merger & Acquisition investment, so as to determine the best investment mode of cross-border O2O channel construction for enterprises. Moreover, cross-border O2O channel management proposals are put forward. This paper can provide guidance and reference for Sichuan-style enterprises or other types of domestic enterprises to choose the investment mode when constructing cross-border O2O channels.
Impact of climate change on Melipona beecheii and socioeconomic assessment of meliponiculture in the mexican southeast

The present study aimed to show the impact of climate change on Melipona bees in the Yucatan Peninsula and the socioeconomic situation of Melipona honey producers. Meliponiculture is a very important activity for some Mayans in the Yucatan Peninsula. However, the production of Melipona honey and its territorial distribution has decreased in recent decades, compared to the last century. Fieldwork was carried out in the east of the state of Yucatan to assess honey production activities and the socioeconomic situation of the population that depends on them. Data from Worldclim was used to generate distribution models for Melipona bees as well as scenarios of the impact of climate change on these species in the next seven decades. The scenarios that assume the continued presence of Melipona bees in the next seven decades show disappointing results in the face of climate change. It is necessary to implement effective public policies that help promote the well-being of both Melipona bees and the population that depends on them.
Challenges for Management of Dilated Cardiomyopathy during COVID-19 Pandemic—A Telemedicine Application

Background and Objectives: The 2019 coronavirus pandemic (COVID-19) represented a significant challenge for the medical community. The first aim of this study was to examine the COVID-19 impact on the follow-up of patients with dilated cardiomyopathy (DCM) and to establish the advantages of multiparametric home monitoring. Also, we tried to establish the main prognostic predictors at 2-years follow-up and the value of LV diastolic filling pattern (LVDFP) in increasing mortality and morbidity. Materials and Methods: We conducted a prospective study of 142 patients with DCM assessed by in-patient visit in the pre-pandemic period and hybrid (face-to-face, online consultation and telemedicine home monitoring with a dedicated application) during the pandemic period. The statistical analysis compared the strategy used in the pre-pandemic with management during the pandemic, in terms of clinical assessment, hospitalizations/emergency room visits due to HF exacerbation and total mortality. Results: We did not observe significant changes in blood pressure (BP), heart rate (FC), weight and symptoms or an increased rate of adverse drug events between the two periods. We successfully titrated HF medications with close monitoring of HF decompensations, which were similar in number, but were mostly managed at home during the pandemic. There was also no statistically significant difference in emergency room visits due to severe decompensated HF. Mortality in the first and second year of follow-up was between 12.0 and 13%, similar in the pre-pandemic and pandemic periods, but significantly higher in patients with restrictive LVDFP. Clinical improvement or stability after 2 years was more frequent in patients with nonrestrictive LVDFP. The main prognostic predictors at 1 and 2-years follow-up were: the restrictive LVDFP, significantly dilated LV, comorbidities (DM, COPD), older age, associated severe mitral regurgitation and pulmonary hypertension. Conclusions: The pandemic restrictions determined a marked decrease of the healthcare use, but no significant change in the clinical status of DCM patients under multiparametric home monitoring. At 2-years follow-up, the presence of the restrictive LVDFP was associated with an increased risk of death and with a worse clinical status in DCM patients.
Self-mixing diode laser interferometry for velocity measurements of different targets

Supersonic gas jets can be used as a profile monitor for charged particle beams, as well as a cold target for collision experiments. For the optimisation of these experiments, it is important to know the velocity and density distribution of the jet. In these applications, gas jet velocities can be up to 2000 m/s. A diode laser velocimeter based on laser self-mixing method is currently being developed as an easy to build and compact alternative measurement technique. The technique seems a promising way for a complete characterisation of the gas jet parameters. It should be pointed out, however, that laser self-mixing is usually used for measurement of low velocities and vibrations. In this contribution, the heterodyne principle and design of the laser diode velocimeter are first discussed. The laser velocimeter is a self-aligning device, based on the self-mixing method where the laser is both, transmitter and receiver of the signal. The here presented theoretical analysis shows the possibility to extend measurement capabilities also to high velocities by altering the design. Experimental results from measurements with different targets are presented. The set-up for testing the sensor allows investigations into the limitation of the method to be made as well as the amount of feedback which is required for a detailed study of a gas jet.
Proving the Gauss-Markov Theorem Without Using the Explicit Functional Form of the OLS Estimator in the CLR Model

> 0] = Prb,, > -*£/3 M/l where F(.) denotes the cumulative distribution function (c.d.f.) of vit, which is symmetric around 0. This could be the Normal c.d. f. , which is denoted by 4>, or the logistic c.d. f. , which is denoted by A. It is important in panel data regressions to test for Ho; n,r = 0 for ii = 1,. ,N. If Ho is not rejected, the estimation procedure is simple and utilizes the usual logit and probit procedures. However, if Ho is rejected, the maximum likelihood (ML) procedure is complicated by the presence of the fixed effects. For the logit model, Chamberlain (1980) suggested a conditional ML procedure, which yields enormous computational simplifications. Unfortunately, this conditional ML approach does not yield similar computational simplifications for the fixed effects probit model. Davidson and MacKinnon (1984) suggested a binary response model regression (BRMR), which can be particularly useful in this context for testing Ho. The reader is asked to derive the BRMR to test for Ho; p, = 0, for / = 1,. ,N. Show that if F(.) is the Logistic (or Normal) c.d. f. then this BRMR is simply a weighted least-squares regression of logit (or probit) residuals, ignoring the fixed effects, on the matrix of regressors X and the matrix of individual dummies. The test statistic in this case is the explained sum of squares from this BRMR.
Compritol-Based Alprazolam Solid Lipid Nanoparticles for Sustained Release of Alprazolam: Preparation by Hot Melt Encapsulation

The current study was designed to investigate the feasibility of incorporating the water-insoluble lipophilic drug Alprazolam (Alp) into solid lipid nanoparticles (SLNs) to offer the combined benefits of the quick onset of action along with the sustained release of the drug. Therefore, compritol-based alprazolam-loaded SLNs (Alp-SLNs) would provide early relief from anxiety and sleep disturbances and long-lasting control of symptoms in patients with depression, thereby enhancing patient compliance. The optimized Alp-SLNs analyzed by DLS and SEM showed consistent particle size of 92.9 nm with PI values and standard deviation of the measurements calculated at <0.3 and negative surface charge. These characteristic values demonstrate the desired level of homogeneity and good physical stability of Alp-SLNs. The SLNs had a good entrapment efficiency (89.4%) and high drug-loading capacity (77.9%). SEM analysis revealed the smooth spherical morphology of the SLNs. The physical condition of alprazolam and absence of interaction among formulation components in Alp-SLNs was confirmed by FTIR and DSC analyses. XRD analysis demonstrated the molecular dispersion of crystalline alprazolam in Alp-SLNs. The in vitro release study implied that the release of Alp from the optimized Alp-SLN formulation was sustained as compared to the Alp drug solution because Alp-SLNs exhibited sustained release of alprazolam over 24 h. Alp-SLNs are a promising candidate to achieve sustained release of the short-acting drug Alp, thereby reducing its dosing frequency and enhancing patient compliance.
Symmetric laser compression of argon-filled glass shells to densities of 4--6 g/cm/sup 3/

Argon-filled plastic-coated glass shells were imploded with the six-beam ZETA laser system using short ( approx. 50-psec) pulses of energy approx. 100 J. Densities in the range 4--6 g/cm/sup 3/ (N/sub e/1.0-1.5(ts)= x 10/sup 24/ cm/sup -3/) temperatures approx. 1 keV were deduced from the Stark profiles of various Ar/sup 16 +/,Ar/sup 17 +/ x-ray lines. These densities are achieved because of the shell thickness and radiational cooling of the high-Z fill gas and show that symmetric illumination can lead to high-volume convergence (>1000).
Consumer Industry in this Turn’s Monetary Policy: Evidence from Necessity and Non-Necessity Goods in US

The US Federal Reserve's interest rates have been acting as main factors that influence the economy, especially the consumers' consumption aspect of the market, since its very beginning. This paper researches the impact of Federal Reserve's interest rates hike on the consumption goods market. While the scale of the consumption goods market as a whole has too many niche industries that does not necessarily affect the common consumers, and there are too many factors to control for. Necessity goods market and non-necessity goods market data from the S&P 500 Index are chosen to be the dependent variables to represent the research purpose. On the other hand, Federal Reserve’s interest rates consists multiple variables and they all have different effects on the economy, the exchange rate between US dollars and Chinese RMB is chosen to be the independent variable in this research for its stability and strong link to the interest rates change. This paper uses VAR model and ARMA-GARCH Model to estimate such impact. The result shows that the effects of Federal Reserve's interest rates hike on necessity goods and non-necessity goods are overall negative effects. In particular, the interest rates hike affects non-necessity goods market way more than it affects the necessity goods market.
Improved direct torque and flux control of induction motor drive

Purpose – The aim of the paper is to conduct an analytical study of a new method of induction motor torque and flux direct control with nonlinear controllers.Design/methodology/approach – The method is based on the inverter state predictive determination in order to minimize the torque and flux errors.Findings – The proposed method allows one to eliminate known DTC disadvantages, i.e. the hexagonal flux shape and nonsinusoidal current at a low motor speed, and also secures a decrease of torque and flux pulsation.Practical implications – This new method enables a more precise reproduction of the motor torque and flux command signals, working with the same sampling frequency of the control processor as in the case of the standard DTC method. The decreased torque pulsations cause a decrease of the motor speed pulsation.Originality/value – An innovative optimal control method is presented. The correctness of the initial assumptions as well as the expected final results have been verified in practice.
Cloud radiative forcing ratio

The ratio of the cloud radiative forcing at the surface to the cloud radiative forcing at the top of the atmosphere has been recently deduced from a set of satellite and surface measurements, and calculated using detailed radiative transfer models. We use an adding method of radiative transfer to derive an analytical expression for the cloud radiative forcing ratio. The advantage of an analytical expression is its simplicity. The analytical expression provides insight onto how the cloud radiative forcing ratio depends on surface albedo, cloud microphysics, and atmospheric composition.