Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of Management Zone Delineation for Precision Crop Management in an Intensive Farming System

Soil is characterized by high spatiotemporal variability due to the combined influence of internal and external factors. The most efficient approach for addressing spatial variability is the use of management zones (MZs). Common approaches for delineating MZs include K-means and fuzzy C-means cluster analysis algorithms. However, these clustering methods have been used to delineate MZs independent of the spatial dependence of soil variables. Thus, the accuracy of the clustering results has been limited. In this study, six soil variables (soil pH, total nitrogen, organic matter, available phosphorus, available potassium, and soil apparent electrical conductivity) were used to characterize the spatial variability within a representative village in Suining County, Jiangsu Province, China. Two variable reduction techniques (PCA, multivariate spatial analysis based on Moran’s index; MULTISPATI-PCA) and three different clustering algorithms (fuzzy C-means clustering, iterative self-organizing data analysis techniques algorithm, and Gaussian mixture model; GMM) were used to optimize the MZ delineation. Different clustering model composites were evaluated using yield data collected after the wheat harvest in 2020. The results indicated that the variable reduction technologies in conjunction with clustering algorithms provided better performance in MZ delineation, with average silhouette coefficient (ASC) and variance reduction (VR) of 0.48–0.57, and 13.35–23.13%, respectively. Moreover, the MULTISPATI-PCA approach was more conducive to identifying variables requiring MZ delineation than traditional PCA methods. Combining MULTISPATI-PCA and the GMM algorithm yielded the greatest VR and ASC values in this study. These results can guide the optimization of MZ delineation in intensive agricultural systems, thus enabling more precise nutrient management.
RnaBench: A Comprehensive Library for In Silico RNA Modelling

RNA is a crucial regulator in living organisms and malfunctions can lead to severe diseases. To explore RNA-based therapeutics and applications, computational structure prediction and design approaches play a vital role. Among these approaches, deep learning (DL) algorithms show great promise. However, the adoption of DL methods in the RNA community is limited due to various challenges. DL practitioners often underestimate data homologies, causing skepticism in the field. Additionally, the absence of standardized benchmarks hampers result comparison, while tackling low-level tasks requires significant effort. Moreover, assessing performance and visualizing results prove to be non-trivial and task-dependent. To address these obstacles, we introduce RnaBench (RnB), an open-source RNA library designed specifically for the development of deep learning algorithms that mitigate the challenges during data generation, evaluation, and visualization. It provides meticulously curated homology-aware RNA datasets and standardized RNA benchmarks, including a pioneering RNA design benchmark suite featuring a novel real-world RNA design problem. Furthermore, RnB offers baseline algorithms, both existing and novel performance measures, as well as data utilities and a comprehensive visualization module, all accessible through a user-friendly interface. By leveraging RnB, DL practitioners can rapidly develop innovative algorithms, potentially revolutionizing the field of computational RNA research.
Dynamic security region assessment

Among a wide variety of topics that are covered by Dynamic Security Assessment (DSA), maintaining synchronous operation and acceptable voltage profiles stand out. These two stability categories are mostly jeopardized in the seconds after a large contingency occurs. Therefore, this thesis tackles the two aspects of large disturbance stability of power systems in the short-term time scale. The classical DSA methods deal with the short-term loss of synchronism by analyzing one operating point and one contingency at a time. However, a small change in operating point may turn a stable system unstable. The first part of the thesis overcomes this gap by proposing the idea of parametrizing the stability boundary. The newly introduced method constructs the parametrized security boundaries in polynomial forms based on a reduced amount of Time Domain Simulation (TDS) data. Such a method retains the positive traits of TDS while being able to estimate a measure of stability even for those points that do not belong to the “training" set. The polynomial coefficients are further improved via SIME parametrization that has a physical meaning. Finally, when being subject to a constraint by the means of Quadratic Programming (QP), SIME parametrization also becomes competitive with direct methods in the sense of conservativeness. Nevertheless, if TDS fails, any TDS-based DSA approach is useless. Most often, the dynamics of the non-linear power system is described by the set of Differential Algebraic Equations (DAE). TDS can face problems when the DAE model experiences singularity due to the loss of voltage causality. This thesis introduces Voltage Impasse Region (V IR) as the state-space area where the voltage causality is lost due to the non-linear modeling of static loads. The entrance of a dynamic trajectory to a V IR was shown to be accompanied by non-convergence issues in TDS and significant voltage drops. Appropriate Voltage Collapse Indicators (VCIs) are also derived for each load model of interest. The thesis concluded that V IR is a structural problem of the DAE model that should always be accounted for when the short-term stability is assessed.
Database Technique for Tumor Detection and Dielectric Profile Estimation

Bio-medical imaging techniques help in detection the tumor and finding the exact location of tumor cells inside the body. But these techniques are time consuming and the setup required is bulky. They also require a prior information about dielectric properties of tissue to give accurate imaging results. Quite useful bits of information regarding tumor and dielectric profile can be extracted from simple measurement and simulation procedure. Earlier, dielectric profile of biological tissue was provided using dielectric probe and waveguide fixture techniques. These methods provided reasonable estimates, but the setup which was used is limited to small portion of tissues and were not able to accommodate body part as a whole. In this paper, a new technique is devised to analyze the dielectric profile of breast tissues with and without tumor cells using free space transmission method and database approach. The measurement setup is used to obtained the transmission parameters in free space keeping the tissue under test in between the transmitter and receiver antenna. Database of simulated transmission parameter is created keeping all sets of variations in tissue types using Debye model. The complex permittivity is then arrived at by matching the measured transmission parameter data with the database. This technique was validated using simulated realistic breast phantoms and tested with results from mouse tumor cells.
Hierarchical Radio Resource Allocation for Network Slicing in Fog Radio Access Networks

Network slicing in fog radio access networks is recognized as a cost-efficient solution to support future diverse use cases. However, with the number of user equipments (UE) fast increasing, the centralized resource allocation architecture for network slicing can put heavy burdens on the global radio resource manager (GRRM), and meanwhile slice customization is not easy to achieve. To overcome the two issues, a hierarchical radio resource allocation architecture is proposed in this paper, where the GRRM is responsible for allocating subchannels to local radio resource managers (LRRMs) in slices, which then allocate the assigned resources to their UEs. Under this architecture, a hierarchical resource allocation problem is formulated, and the problem is further modeled as a Stackelberg game with the GRRM as the leader and LRRMs as followers, considering the hierarchy between the GRRM and LRRMs. Due to the NP-hardness of the followers’ problems, a process based on exhaustive search is first proposed to achieve the Stackelberg equilibrium (SE). Nevertheless, when the network scale is large, achieving SE within limited decision making time is impractical for game players. Facing this challenge, the GRRM and LRRMs are seen as bounded rational players, and low complexity algorithms are developed to help them achieve local optimal solutions that lead to a weak version of SE. Simulation results show that there exists a tradeoff between the performance of slices, and the low complexity algorithms achieve close performance to that of exhaustive search and outperform other baselines significantly.
Maximizing k-Terminal Network Reliability in Some Sparse Graphs

<inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-terminal network reliability is the probability that <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> terminal vertices are connected given that edges in the network fail independently while vertices do not fail. It depends on the distribution of these terminal vertices as well as network topology. The problem of computing <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-terminal reliability is NP-hard. Previous literature mainly focus on designing efficient algorithms to compute it in different graphs, but are lacking in the analysis for optimal distribution of <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> terminal vertices in sparse graphs, within which those with <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> nodes and <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> edges, where <inline-formula> <tex-math notation="LaTeX">$m \leq n + 1$ </tex-math></inline-formula>, are most basic classes. Hence, it is of great significance to investigate the optimal distribution of terminal vertices in these classes of graphs before considering general cases. In this paper, we prove that <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-terminal network reliability obtains the maximum if <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> terminal vertices induce a connected subgraph. Further, we give equations of maximum reliability for all possible graphs in the above classes. The experiments illlustrate the variation, with several parameters and according to our theoretical results, of maximal <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-terminal reliability, and provide observations for graphs with any number of edges.
The association between magnitude of T-SPOT.TB and clinical characteristics in active pulmonary tuberculosis: a retrospective multicenter investigation

Background: The aim of this study was to evaluate the association between magnitude of T-SPOT.TB and clinical characteristics in active pulmonary tuberculosis. Methods: In this retrospective multicenter investigation, the medical records’ archives of PTB patients were reviewed. Data including gender, age group, bacterial culture, sputum-smear microscopy, lung cavity and range of PTB were extracted from the records. The Jonckheere-Terpstra test and chi-square test for trend were used to evaluate the association between magnitude of T-SPOT.TB and clinical characteristics in active pulmonary tuberculosis. Results: A total of 1252 PTB patients were included in this study.Chi-square trend tests revealed significant positive trends between bacterial culture and magnitude of T-SPOT.TB A (χ2 =18.978, P <0.001) or T-SPOT.TB B (χ2 =19.677, P <0.001). There were significant positive trends between AFB and magnitude of T-SPOT.TB A (TJT =345784, P <0.001) or T-SPOT.TB B (TJT =336017, P <0.001). There was a significant positive trend between range of lung cavity and magnitude of T-SPOT.TB A (TJT =326079.5, P =0.023). There were significant negative trends between age group and magnitude of T-SPOT.TB A (TJT =204306, P <0.001) or T-SPOT.TB B (TJT =206572, P <0.001). Conclusions: The magnitude of T-SPOT.TB in PTB patients may reflect the condition of the patients and could be helpful for clinicians to assess the degree of infection and lung tissue damage.
Expression alteration analyses in the transgenic Arabidopsis carrying soybean Histidine-containing phosphotransmitter gene under salinity stress condition

Productivity of many crops is highly vulnerable to extreme external conditions. Environmental stress factors such as drought and salinity have become more and more serious due to climate change and appear in many areas worldwide with higher frequency. As both drought and salinity belong to osmotic stress, they have similar negative effects on plant growth, development, and productivity as well as trigger similar stress responses by plants. In a previous study analyzing the expression profile in two soybean (Glycine max) cultivars with contrasting drought-tolerant phenotypes, a member of two-component system (TCS) in soybean, GmHP08, was proposed to associate with the plant tolerance capacity to drought. Subsequent in planta study confirmed its action as a positive regulator under drought conditions, as the transgenic Arabidopsis plants ectopically expressing GmHP08 acquired better drought tolerance. Following this, the presented research further explored the possible function of GmHP08 in mediating plant response to salinity. The obtained data from RT-qPCR analyses suggested that GmHP08 might positively enhance the salt tolerance of the Arabidopsis transgenic plants by altering the transcriptional abundance of several stress-related genes, including RD29A, RD29B, ABI5, SAG13, and CSD1. Activities of these genes are known to be associated with osmoprotection, senescence process, and antioxidation, which contribute to salt-tolerance ability of the transgenic plants. These results provided the first line of molecular evidence regarding GmHP08 function in plant response to salinity conditions. Therefore, extensive studies should be conducted in future studies to elaborate on the mechanisms by which this TCS member could improve various types of osmotic stress tolerance in plants.
Ischemic preconditioning of the legs results in small improvements in peak exercise capacity at sea level, but not simulated high altitude in trained male cyclists

of a dissertation at the University of Miami Dissertation supervised by Professor Kevin Jacobs No. of pages in text (28) Ischemic preconditioning (IPC) may have profound local and systemic effects that improve blood flow and oxygen delivery to tissues, including skeletal muscle, and has the potential to improve intense aerobic exercise performance, especially that which results in arterial hypoxemia. Purpose: To determine the effects of IPC of the legs on peak exercise capacity (Wpeak), submaximal and peak cardiovascular hemodynamics, and arterial oxygen saturation (SaO2) in trained males at sea level (SL) and simulated high altitude (HA; FIO2 = 13.3%, ~3650 m). Methods: Fifteen highly trained male cyclists and triathletes completed two Wpeak tests (SL and HA) and four experimental exercise trials (10 min at 55% altitude specific Wpeak increasing by 30 W every 2 min until exhaustion) with and without IPC. Results: HA resulted in significant arterial hypoxemia during exercise compared to SL (73 ±1 vs. 93 ± 1% SaO2, p< 0.05) that was associated with 21% lower Wpeak values. IPC resulted in a 1.9 ± 0.8% higher average Wpeak value at SL compared to control (p = 0.032). While IPC resulted in a 4.7 ± 2.3% higher average Wpeak value at HA compared to control, this difference failed to reach statistical significance (p = 0.084). IPC did not significantly affect peak cardiovascular hemodynamics or SaO2 at SL or HA. Conclusions: IPC has little effect on systemic
SUNFLECKS AND PHOTOSYNTHESIS IN PLANT CANOPIES

INTRODUCTION . 421 LIGHT DYNAMICS IN CANOPIES 422 Theory . 422 Empirical Studies . 424 PHOTOSYNTHESIS IN TRANSIENT LIGHT . 425 Theory . 425 Measurement of Transient Photosynthesis . 427 Dynamics of CO2 Assimilation during Sunj1ecks . 429 Limitation of Sunj1eck Use by the P hotosynthetic Induction Requirement . 436 Modulation of Induction State in Natural Light Regimes . 440 ENVIRONMENTAL CONSTRAINTS ON SUNFLECK UTILIZATION . 442 Temperature and Water Stress . 442 Ph otoinhibition during Sunflecks. 443 CONCLUDING REMARKS 444
Empathy, Affect and Personality as Predictors of Engagement in Nursing Professionals

Background: It seems that personality traits affect engagement and the quality of professional life, which is mediated by the emotional and affective states of nursing personnel. Therefore, the objectives of this study were to analyze the relationships between the components of empathy, affect, personality, and engagement, find personality profiles, identify the variables with the most explanatory value, and analyze the mediating role of the variables susceptible to intervention in the relationship between personality and the components of engagement. Methods: A sample of 1268 nurses completed the Utrecht Work Engagement Scale, 10-item Big Five Inventory, Basic Empathy Scale, and Positive and Negative Affect Schedule. Results: Empathy, affect, and personality influence engagement factors in nurses. The vigor and absorption factors of engagement showed a positive relationship with empathy, positive affect, and all of the Big Five personality factors except neuroticism with which the relationship was negative. Personality affected the vigor, dedication, and absorption factors of engagement, and cognitive empathy mediated this relationship. Conclusions: This study shows the need to continue investigating the factors that affect and mediate in engagement of nursing professionals.
Antenatal Micronutrient Supplementation Relationship with Children’s Weight and Height from Birth up to the Age of 18 Months

Background Maternal nutritional is the most important environmental factor influencing pregnancy outcome. While studies showed association between maternal iron-micronutrient deficiencies with pregnancy outcome, data examining impact of micronutrient supplementation on growth rate beyond birth are sparse. Present study examined the relationship between iron and multivitamins supplementation on growth rate of babies up to age of 18 month. Methods: This study was a statistical analysis on data recorded through a routine procedure in health houses from 1994 to 2007. Subjects were selected by a two-stage randomization method and required data extracted from the records. Analyses were performed using STATA 10 software. Results: Data was collected for 3835 pairs of mother-baby. Mothers received 61.7±5.4 and 115.6±53.8 multivitamins and iron tablets, respectively. Analyses showed significant relationship between children’s weight and height at birth with iron supplementation and children’s height at 6, 12 and 18 month with multivitamins supplementation. Conclusions: Mechanisms of these effects are unclear but it is safe to suggest supplementation during pregnancy is necessary.
DNA damage intensity in fibroblasts in a 3-dimensional collagen matrix correlates with the Bragg curve energy distribution of a high LET particle

Purpose: The DNA double-strand break (DSB) damage response induced by high energy charged particles on lung fibroblast cells embedded in a 3-dimensional (3-D) collagen tissue equivalents was investigated using antibodies to the DNA damage response proteins gamma-histone 2AX (γ-H2AX) and phosphorylated DNA-PKcs (p-DNA-PKcs). Materials and methods: 3-D tissue equivalents were irradiated in positions across the linear distribution of the Bragg curve profiles of 307.7 MeV/nucleon, 556.9 MeV/nucleon, or 967.0 MeV/nucleon 56Fe ions at a dose of 0.30 Gy. Results: Patterns of discrete DNA damage streaks across nuclei or saturated nuclear damage were observed, with saturated nuclear damage being more predominant as samples were positioned closer to the physical Bragg peak. Quantification of the DNA damage signal intensities at each distance for each of the examined energies revealed a biological Bragg curve profile with a pattern of DNA damage intensity similar to the physical Bragg curve for the particular energy. Deconvolution microscopy of nuclei with streaked or saturated nuclear damage pattern revealed more details of the damage, with evidence of double-strand breaks radially distributed from the main particle track as well as multiple discrete tracks within saturated damage nuclei. Conclusions: These 3-D culture systems can be used as a biological substrate to better understand the interaction of heavy charged particles of different energies with tissue and could serve as a basis to model space-radiation-induced cancer initiation and progression.
Export-Led Growth in India: A Bounds Testing Approach

ABSTRACT:Neoclassical economic theory suggests there is a positive relationship between economic growth and growth in exports. An increase in exports leads to an increase in income due to the multiplier effect of production. This paper examines whether the Export-Led Growth (ELG) hypothesis is valid for India. Though the existing literature on this field is extensive, the results are ambiguous. Past studies have suffered from various methodological drawbacks. Early studies were hampered by a lack of time series data. The next stage used OLS analysis and simply assumed causation rather than testing for it. A third stage of investigations tested for Granger causality using the standard tests which was not applicable due to the presence of cointegrated variables. Therefore this paper re-investigates the ELG hypothesis for India; taking advantage the longer time series now available, with annual data from 1980 to 2013, and using more sophisticated tests. The paper tests for the presence of a long run relationship between exports and economic growth using the more robust autoregressive distributive lag (ARDL) bounds test for cointegration developed by Pesaran et al. (2001). The paper then tests for causality between exports and GDP using the Todo and Yamamoto (1995) and Dolado Lutkepohl (1996) (TYDL) causality test. The advantage of the latter test is that it indicates the direction of causality. The results indicate that exports have no significant long run impact on economic growth. While in the long run the result exhibits no relationship between exports and economic growth, the short run model is highly significant. Furthermore, the results indicate that capital formation, imports, real exchange rate and terms of trade are significant and have an impact on economic growth in the long and short run. The short run dynamics further indicate that the Indian economy recovers from a shock is relatively quickly. In addition, the causality test results show that there is a significant unidirectional causal relationship from GDP to exports but no causality is found from exports to GDP. Thus, the results show no support for the ELG hypothesis and indicate that India has not directly benefited from the trade reforms implemented in 1991. The findings suggest that to improve and sustain long run economic growth the government should target policies that further enhance domestic demand and capital accumulation.