Miracle-dz/UniFAR-FTUs huggingface dataset:
Developing Functional Relationships between Soil Moisture Content and Corn Early-Season Physiology, Growth, and Development

Drought is a severe threat to agriculture production that affects all growth stages of plants, including corn (Zea mays L.). Any factor affecting early seedling growth and development will significantly impact yield. Despite the recurrence of low rainfall during the growing seasons, corn responses to different early-season soil moisture content levels have not been investigated. In this study, we investigated how corn morpho-physiological and biomass traits responded to varied soil moisture content during the early vegetative stage. Two corn hybrids were grown in a pot-culture facility under five different soil moisture treatments (0.15, 0.12, 0.09, 0.06, and 0.03 m3 m−3 volumetric water content, VWC) to assess the growth and developmental responses to varied soil moisture content during early-season growth (V2 to V7) stage. Sub-optimal soil moisture content limited plant growth and development by reducing physiological and phenotypic expression. Stomatal conductance and transpiration were decreased by an average of 65% and 59% across stress treatments relative to optimum conditions. On average, soil moisture deficit reduced the total leaf area by 71% and 72% compared to the control in ‘A6659VT2RIB’ and ‘P1316YHR’, respectively. Shoot and root dry weights were reduced by 74% and 43% under 0.03 m3 m−3 VWC. An increase in the root-to-shoot ratio was noticed under low VWC conditions compared to the control. Based on the stress tolerance index, the physiology and leaf growth parameters were more sensitive to soil moisture deficit. Our results highlight the impact of sub-optimal soil moisture on physiology and morphological traits during early-season growth. ‘P1316YHR’ demonstrated better physiological performance under stress conditions, while ‘A6659VT2RIB’ produced relatively better root growth. The findings suggest that biomass partitioning between shoot and root components is dynamic and depends on stress intensity. The current findings can help to prioritize traits associated with the early-season drought tolerance in corn. The functional relationships developed between soil moisture content and growth and developmental responses can be integrated into corn crop modeling to allow better irrigation management decisions.
Effectiveness measurement of spectral clustering algorithm

After the Kuwil method was found for applying the spectral clustering algorithm, we need a way to make sure of the results, because in many cases the nature of data is not compatible with the algorithm; also, when the data contain more than three dimensions (3D) the results cannot be displayed on the monitor. So I found two techniques, first, for measuring the strength and effectiveness of S.C. A, such as some comparative relationships that measure the following: Effectiveness of algorithm applying, the strength of every cluster and the effectiveness of data correlation inside every cluster. Secondly, analysis of variance (ANOVA) for S.C. A; this depends on distance variance instead of values variance. I applied the methods above to calculate the strength and effectiveness of S.C. A, and they showed good results, so they can offer more reliability for the outputs of the algorithm. Using these relations and ANOVA for S.C. A help us to measure the data receptivity for applying the algorithm by ‘Kuwil method’, so the outputs will be more reliable and that will help to spread the use of this algorithm among researchers, analysts and other users.
On the empirics of microfinance institutions and local economic development in Africa

ABSTRACT The link between finance and growth is a well-researched area, yet this relationship at the local level has received little empirical scrutiny. We trace the operations of Microfinance Institutions (MFIs) in Africa. We examine the role played by MFIs on local economic development using a model capturing both local geography and MFIs dynamics for the periods 1992–2015. Our sample is representative of 2,170 MFIs operating in 144 cities, 154 towns, and 14 villages in Africa. Using night time data to capture economic growth, our key hypothesis is that MFIs drive local economic progress. Conditioning on the geographical location of MFIs, we find that the presence and density of MFIs increase as the growth in light density and the estimate retains its statistical significance. The results suggest that MFIs operations may foster local economic activity.
RESUDIAL STRESSES IN I-BEAMS AND ITS EFFECT ON RODS BUCKLING

Stability calculation of steel rods should consider residual stresses, as well as local imperfections (bends, buckling). Codes of EU, USA, PCR considering difference between welded and rolled I-beams on compression and compression with bending. Coefficient of longitudinal bending has values that consider the presence of different values of residual stresses for welded and rolled I-beams. Russian code for the design of steel structures (SP 16.13330) for conditionally centrally compressed rods does not distinguish between methods of I-beams production. To determine residual stresses, a wide range of Russian profiles with different thin-walled was studied. Residual stresses for small-sized profiles were carried out by partitioning, for large I-beams - by drilling blind holes. The actual values of residual stresses in flanges and walls are established; most suitable curves for their approximation are selected. The actual shape of I-beams was also measured with a laser scanner. According to the results of curvature measuring, the limit and average values of local flanges deflection are established. Considering experimental studies, FE-modeling of rods with residual stresses was performed for both rolled and welded I-beams. In addition to code eccentricities, local shape imperfections were modeled. It is established that rolled I-beams show higher values of critical forces than welded ones by 8-16%. This is true for steels C355 and C390 with a lambda-factor of more than 4, and for C255 with lambda-factor more than 3. According to the study, a coefficient is proposed that increases the bearing capacity of rolled I-beams for medium and large flexibilities.
Error estimate of L1-ADI scheme for two-dimensional multi-term time fractional diffusion equation

A two-dimensional multi-term time fractional diffusion equation $ {D}_{t}^{\mathit{\boldsymbol{\alpha}}} u(x, y, t)- \Delta u(x, y, t) = f(x, y, t) $ is considered in this paper, where $ {D}_{t}^{\mathit{\boldsymbol{\alpha}}} $ is the multi-term time Caputo fractional derivative. To solve the equation numerically, L1 discretisation to each fractional derivative is used on a graded temporal mesh, together with a standard finite difference method for the spatial derivatives on a uniform spatial mesh. We provide a rigorous stability and convergence analysis of a fully discrete L1-ADI scheme for solving the multi-term time fractional diffusion problem. Numerical results show that the error estimate is sharp.
Analysis of a model to control the co-dynamics of Chlamydia and Gonorrhea using Caputo fractional derivative

This paper investigates a fractional derivative model of Chlamydia-Gonorrhea co-infection using Caputo derivative definition. The positivity boundedness of the model is established using Laplace transform. Additionally, we investigated the existence and uniqueness of the model using methods established by some fixed point theorems. We concluded that the model is Ulam-Hyers-Rassias stable. Furthermore, we obtained plots of the model at different fractional derivative orders, which show the significant role played by the fractional order on various classes of the model as it varies. We observe distinct results for each class in different orders, highlighting the importance of considering the fractional order in modeling Chlamydia-Gonorrhea co-infection. Moreover, the fractional model presented in this paper can be used to study the dynamics of Chlamydia-Gonorrhea co-infection in a more accurate and realistic way compared to traditional integer-order models.
Brevetoxin versus Brevenal Modulation of Human Nav1 Channels

Brevetoxins (PbTx) and brevenal are marine ladder-frame polyethers. PbTx binds to and activates voltage-gated sodium (Nav) channels in native tissues, whereas brevenal antagonizes these actions. However, the effects of PbTx and brevenal on recombinant Nav channel function have not been systematically analyzed. In this study, the PbTx-3 and brevenal modulation of tissue-representative Nav channel subtypes Nav1.2, Nav1.4, Nav1.5, and Nav1.7 were examined using automated patch-clamp. While PbTx-3 and brevenal elicit concentration-dependent and subtype-specific modulatory effects, PbTx-3 is >1000-fold more potent than brevenal. Consistent with effects observed in native tissues, Nav1.2 and Nav1.4 channels were PbTx-3- and brevenal-sensitive, whereas Nav1.5 and Nav1.7 appeared resistant. Interestingly, the incorporation of brevenal in the intracellular solution caused Nav channels to become less sensitive to PbTx-3 actions. Furthermore, we generated a computational model of PbTx-2 bound to the lipid-exposed side of the interface between domains I and IV of Nav1.2. Our results are consistent with competitive antagonism between brevetoxins and brevenal, setting a basis for future mutational analyses of Nav channels’ interaction with brevetoxins and brevenal. Our findings provide valuable insights into the functional modulation of Nav channels by brevetoxins and brevenal, which may have implications for the development of new Nav channel modulators with potential therapeutic applications.
Pharmacokinetics of Curcumin Delivered by Nanoparticles and the Relationship with Antitumor Efficacy: A Systematic Review

Curcumin is a polyphenolic compound, derived from Curcuma longa, and it has several pharmacological effects such as antioxidant, anti-inflammatory, and antitumor. Although it is a pleiotropic molecule, curcumin’s free form, which is lipophilic, has low bioavailability and is rapidly metabolized, limiting its clinical use. With the advances in techniques for loading curcumin into nanostructures, it is possible to improve its bioavailability and extend its applications. In this review, we gather evidence about the comparison of the pharmacokinetics (biodistribution and bioavailability) between free curcumin (Cur) and nanostructured curcumin (Cur-NPs) and their respective relationships with antitumor efficacy. The search was performed in the following databases: Cochrane, LILACS, Embase, MEDLINE/Pubmed, Clinical Trials, BSV regional portal, ScienceDirect, Scopus, and Web of Science. The selected studies were based on studies that used High-Performance Liquid Chromatography (HPLC) as the pharmacokinetics evaluation method. Of the 345 studies initially pooled, 11 met the inclusion criteria and all included studies classified as high quality. In this search, a variety of nanoparticles used to deliver curcumin (polymeric, copolymeric, nanocrystals, nanovesicles, and nanosuspension) were found. Most Cur-NPs presented negative Zeta potential ranging from −25 mV to 12.7 mV, polydispersion index (PDI) ranging from 0.06 to 0.283, and hydrodynamic diameter ranging from 30.47 to 550.1 nm. Selected studies adopted mainly oral and intravenous administrations. In the pharmacokinetics analysis, samples of plasma, liver, tumor, lung, brain, kidney, and spleen were evaluated. The administration of curcumin, in nanoparticle systems, resulted in a higher level of curcumin in tumors compared to free curcumin, leading to an improved antitumor effect. Thus, the use of nanoparticles can be a promising alternative for curcumin delivery since this improves its bioavailability.
Intermittent and partial synchrony of coupled augmented Rössler oscillators

Inspired by the augmented Lorenz equations, we have designed a star network of Rössler oscillators, referred to as augmented Rössler equations, in which each Rössler oscillator is coupled with the other oscillators via a single variable y as the central node of the whole network. We investigate the dynamical nature of the augmented Rössler equations in terms of the bifurcation diagram of a single augmented Rössler oscillator and the chaotic synchronizability of coupled augmented Rössler oscillators, and show that intermittent synchronization between identical augmented Rössler oscillators as well as partial synchronization between nonidentical ones can be achieved via direct coupling of the central nodes. We also show that nonidentical augmented Rössler oscillators coupled via intermittent mutual diffusive coupling exhibit partial synchrony, despite the intermittency of the diffusive coupling. We discuss possible application of such synchronous behavior in terms of chaos-based secret key distribution.
VFogSim: A Data-Driven Platform for Simulating Vehicular Fog Computing Environment

Edge/fog computing is a key enabling technology in 5G and beyond for fulfilling the tight latency requirements of emerging vehicle applications, such as cooperative and autonomous driving. Vehicular fog computing (VFC) is a cost-efficient deployment option that complements stationary fog nodes with mobile ones carried by moving vehicles. To plan the deployment and manage the VFC resources in the real world, it is essential to consider the spatiotemporal variations in both demand and supply of fog computing capacity and the tradeoffs between achievable quality-of-services and potential deployment and operating costs. The existing edge/fog computing simulators, such as IFogSim, IoTSim, and EdgeCloudSim, cannot provide a realistic technoeconomic investigation to analyze the implications of VFC deployment options due to the simplified network models in use, the lack of support for fog node mobility, and limited testing scenarios. In this article, we propose an open-source simulator VFogSim that allows real-world data as input for simulating the supply and demand of VFC in urban areas. It follows a modular design to evaluate the performance and cost efficiency of deployment scenarios under various vehicular traffic models, and the effectiveness of the diverse network and computation schedulers and prioritization mechanisms under user-defined scenarios. To the best of our knowledge, our platform is the first one that supports the mobility of fog nodes and provides realistic modeling of vehicle-to-everything in 5G and beyond networks in the urban environment. Furthermore, we validate the accuracy of the platform using a real-world 5G measurement and demonstrate the functionality of the platform taking VFC capacity planning as an example.
On the Influence of Surface Phenomena Upon Charge Transport in Te‐Based Glassy Semiconductors

The effect of surface phenomena caused by adsorption of NO2, CO2, and H2O vapor on the charge transport in thin films of chalcogenide glassy semiconductors (ChGS) of the As2S3Ge8–Te system has been studied. The investigations have been carried out by measuring the dynamic conductivity of these films in a large (5 to 107 Hz) frequency range, in both dry air and its mixture with controlled concentrations of the above mentioned gases at different temperatures. In addition to this, the temperature dependence of DC conductivity has also been measured for an unambiguous interpretation of the results. It is shown that depending on material's composition, the AC conductivity in dry air can either be frequency independent across the full range or be frequency independent until ≈104 Hz, with increasing σ(ω) ≈ ωn (n ≈ 0.7) at higher frequencies. This behavior demonstrates that for these glassy films there is a competition of several transport mechanisms, so that depending on frequency at normal temperatures the charge is carried: by free holes or by tunneling between localized states at either valence band edge or those near the Fermi level. An estimation has been made for the density of states at the Fermi level of As2S3Ge8Te13 that appears to be N(EF) ≈ 1.3 × 1021 eV−1 cm−3. Changes of environmental conditions either in air humidification or application of even very small (ppm) concentration of NO2 dramatically influence the spectra of dynamic conductivity that, on the other hand, remain nearly unaffected upon CO2 vapor application. This is evidence that for some chalcogenide materials the surface phenomena disturb the energetic distribution of states adjacent to surface, changing the transport mechanisms.
Modeling the Biological Diversity of Pig Carcasses

This thesis applies methods from medical image analysis for modeling the biological diversity of pig carcasses. The Danish meat industry is very focused on improving product quality and productivity by optimizing the use of the carcasses and increasing productivity in the abattoirs. In order to achieve these goals there is a need for more detailed information about pig carcasses in relation to measures of quality. Non-invasive imaging such as X-ray Computed Tomography (CT) can provide this very detailed information discerning the major tissue types. Medical image analysis provides the tools for extracting and modeling meaningful information from the vast amount of information available from non-invasive imaging data. The lean meat percentage (LMP) is a common standard for measuring the quality of pig carcasses. Measuring the LMP using CT and using this as a reference for calibration of online equipment is investigated, without the need for a calibration against a less accurate manual dissection. The rest of the contributions regard the construction and use of point distribution models (PDM). PDM’s are able to capture the shape variation of a population of shapes, in this case a 3D surface of a specific bone structure in the ham. These models can assist developers of robotic tools by enabling population based testing before actual construction of the tools. Sparse models are compared to the standard PCA based model and a method for fitting PDM’s to sparse data is proposed. The former provides more spatially localized modes of variation that are easier interpretable and the latter enables the use of PDM’s without the need for full point correspondence of new data. There is great potential in applying CT as non-invasive modality in the meat industry, e.g. in population based studies, for shape modeling and for analyzing carcass composition. In the future online CT applications can be used to make decisions on the use of each specific carcass by obtaining improved quality measures.
Prediction techniques based on non-parametric methods. Application to energy series

The prediction of the electric energy demand is a problem of great importance for the electric industry, considering that, given the results of these predictions, different market agents take the most appropriate decisions. This is especially relevant for power companies that generate electric energy, because this way they’re able to generate the amount needed in order to supply the market without exposing themselves to overproduction, which supposes a huge saving in economic costs. This paper proposes a method to predict the electric power demand using techniques based on non-parametric regression. An empirical study focusing on the UK electricity market is presented. The main objective of this research is to obtain a solid predictor for the electric power demand that essentially captures the intrinsic particularities of the electric power demand series and serves us to obtain future predictions. The methodology followed in order to obtain said predictor is based in using a training set in order to make and empirical adjustment of the predictor. The adjustment is obtained by selecting the set of hyperparameters that minimize the prediction error. The proposed predictor is validated and compared with others predictors through a validation set. The results support the goodness of the proposal made in this work. JEL classification: C14, C51, C53, C63, L94, Q41
Efficient Hedging in Bates Model Using High-Order Compact Finite Differences

We evaluate the hedging performance of a high-order compact finite difference scheme from [4] for option pricing in Bates model. We compare the scheme's hedging performance to standard finite difference methods in different examples. We observe that the new scheme outperforms a standard, second-order central finite difference approximation in all our experiments.
The Third Atmospheric Scientific Experiment for Understanding the Earth–Atmosphere Coupled System over the Tibetan Plateau and Its Effects

AbstractThis paper presents the background, scientific objectives, experimental design, and preliminary achievements of the Third Tibetan Plateau (TP) Atmospheric Scientific Experiment (TIPEX-III) for 8–10 years. It began in 2013 and has expanded plateau-scale observation networks by adding observation stations in data-scarce areas; executed integrated observation missions for the land surface, planetary boundary layer, cloud–precipitation, and troposphere–stratosphere exchange processes by coordinating ground-based, air-based, and satellite facilities; and achieved noticeable progress in data applications. A new estimation gives a smaller bulk transfer coefficient of surface sensible heat over the TP, which results in a reduction of the possibly overestimated heat intensity found in previous studies. Summer cloud–precipitation microphysical characteristics and cloud radiative effects over the TP are distinguished from those over the downstream plains. Warm rain processes play important roles in the devel.
Developing the Wheel Image Similarity Application with Deep Metric Learning: Hyundai Motor Company Case

The global automobile market experiences quick changes in design preferences. In response to the demand shifts, manufacturers now try to apply new technologies to bring a novel design to market faster. In this paper, we introduce a novel application that performs a similarity verification task of wheel designs using an AI model and cloud computing technology. At Jan 2022, we successfully implemented the application to the wheel design process of Hyundai Motor Company’s design team and shortened the similarity verification time by 90% to a maximum of 10 minutes. We believe that this study is the first to build a wheel image database and empirically prove that the cross-entropy loss does similar tasks as the pairwise losses do in the embedding space. As a result, we successfully automated Hyundai Motor’s verification task of wheel design similarity. With a few clicks, the end-users in Hyundai Motor could take advantage of our application.