Miracle-dz/UniFAR-FTUs huggingface dataset:
Plant species diversity, structure, and regeneration status of Dengago Mountain in Eastern Hararghe Zone, Ethiopia

The study was conducted at Dengago Mountain in Eastern Ethiopia to identify and analyze species' diversity, population structure, and regeneration status along altitudinal gradients. A systematic sampling procedure was employed with 6 transect lines and 45 quadrats established along the transect lines. Data were collected on the tree, shrubs, climbers, and herbaceous plants along altitudinal gradients. The vegetation data were statistically analyzed in one-way ANOVA using R software (version 4.0.5). A total of 49 species within 23 families and 34 genera were identified of which 42.8% were shrubs, 40.8% trees, 10.2% climbers, and 6.1% tree/shrubs. Tiliaceae was the dominant and Lower Altitude had significantly higher plant density than MA and UA. On the other hand, Middle altitude had a significantly higher Shannon’s diversity index value and the Jaccard’s similarities index showed the highest species similarity between MA and UA. The diameter and height class distribution of the population exhibited an inverted J-shape and the regeneration status of the forest was in fair condition. The study identified the presence of anthropologic disturbances and suggest the conservation the of Dengego mountain.
Spatial pattern and its influencing factors of specialized villages and towns in China

: Specialized villages and towns has significance to agricultural transformation & upgrading and rural vitalization strategy. With the data of "One Village One Product" Demonstration Villages and Towns from the Ministry of Agriculture and Rural Affairs of the People's Republic of China, this paper revealed the spatial pattern of specialized villages and towns in the whole country. It also analyzed village- level factors (i.e. topography, resource, location) and region-level factors (i.e. market and economic foundation) from the national and agricultural regionalization scale using Geodetector model. The results showed that: (1) 83.64% of specialized villages and towns mainly concentrated to the southeast of the "Hu Line", presenting central agglomeration and gradient descent from the North China Plain-the Lower Reaches of Yangtze River Plain to south and then to northwest. (2) The products of specialized villages and towns were mainly fruits and vegetables, accounting for 59.45%. They were distributed mainly in the Huang- Huai- Hai Plain, Guanzhong Plain, the Middle- lower Reaches of Yangtze River Plain, Sichuan Basin, etc., as well as circle distribution centered on the provincial capitals. (3) The distribution of specialized villages and towns was more influenced by region-level factors than by village-level factors, and the explanatory value of market and economic factors was 0.30 and 0.19, respectively. The influence of topographic factor was more obvious than that of other village- level factors, with the explanatory value being 0.15. (4) These factors presented regional differences. The main factor affecting the distribution of specialized villages and towns was market in the northern plain and hilly region; topographic and resource factors dominated the agro- pastoral ecotone and plateau region; market, economic foundation and location factors had a joint effect in the northwestern and Tibetan Plateau regions. There were no prominent factors in the southern hilly and plateau area. This study has important scientific reference value for improving agriculture's level of specialization, identifying and cultivating specialized villages & towns and rural revitalization poles, and realizing the rural vitalization strategy.
Comparing the Effect of Low-frequency High-intensity Interval Training (HIIT) with Moderate-intensity continuous Training (MICT) on Visceral Fat Reduction in Centrally Obese Adults

Background: Obesity is a disease affecting people worldwide with prevalence surging especially in recent few decades. Central obesity is the type of obesity with accumulation of visceral fat at the abdominal region and is highly associated with heightened risk of comorbidities. Exercise to increase physical activity is well-established as a major lifestyle modification component to treat obesity. Moderate-intensity continuous training (MICT) and high-intensity interval training (HIIT) are two forms of aerobic exercises practiced at different intensities but with at least comparable benefits in reducing visceral fat. Preliminary evidence has even suggested superiority of HIIT in reducing adiposity despite requiring less time commitment. Contradicting to most findings that suggested HIIT delivered at a frequency of 3 times weekly to be the minimal requirement for reducing body fat, our research team recently demonstrated the effectiveness of once-weekly HIIT over MICT in improving body composition. Purpose: Therefore, to validate the contradicting evidence on the minimal amount of HIIT required, this study compared the effect of low-frequency HIIT and MICT on reducing visceral fat in centrally obese adults. Methods: Twenty-three adults with central obesity (BMI≥25; with waist circumference ≥90 cm for men and ≥80 cm for women) aged 18-60 were randomized into the control group (n=7), HIIT group (HIIT x1/week; n=8) or MICT group (MICT x1/week; n=8) for 3 months. Visceral fat (VAT) and subcutaneous fat (SAT) volumes were measured at baseline and after 3-months intervention using Magnetic Resonance Imaging (MRI). Results: VAT volume reduction was the greatest in the HIIT group, while SAT volume reduction was the greatest in the MICT group. Intervention effects on the reduction in VAT and SAT volumes, as well as differences between groups however were not statistically significant. Conclusion: Results showed that both low-frequency HIIT and MICT were not effective in reducing abdominal visceral fat, and the difference between the effects of HIIT and MICT on eliminating visceral adiposity was minimal. Thus, studies with greater sample sizes and longer durations are required to detect true differences. Future research should also aim at finding the minimal amount of HIIT required for effectively reducing abdominal visceral adiposity in centrally obese adults to facilitate application in clinical settings.
Higgs-mediated τ→μ and τ→e transitions in II Higgs doublet model and supersymmetry

We study the phenomenology of the e−μ lepton flavor violation (LFV) in a general two Higgs Doublet Model (2HDM) including the supersymmetric case. We compute the decay rate expressions of μ→eγ, μ→eee, and μ→e conversion in nuclei at two loop level. In particular, it is shown that μ→eγ is generally the most sensitive channel to probe Higgs-mediated LFV. The correlations among the decay rates of the above processes are also discussed.
Optimal galaxy survey for detecting the dipole in the cross-correlation with 21 cm Intensity Mapping

We investigate the future perspectives of the detection of the relativistic dipole by cross-correlating the 21 cm emission in Intensity Mapping (IM) and galaxy surveys at low redshift. We model the neutral hydrogen (HI) and the galaxy population by means of the halo model to relate the parameters that affect the dipole signal such as the biases of the two tracers and the Poissonian noise. We investigate the behavior of the signal-to-noise as a function of the galaxy and magnification biases, for two fixed models of the neutral hydrogen. In both cases we found that the signal-to-noise does not grow by increasing the difference between the biases of the two tracers, due to the larger shot-noise yields by highly biased tracers. We also study and provide an optimal luminosity-threshold galaxy catalogue to enhance the signal-to-noise ratio of the relativistic dipole. Interestingly, we show that the maximum magnitude provided by the survey does not lead to the maximum signal-to-noise for detecting relativistic effects and we predict the optimal value for the limiting magnitude. Our work suggests that an optimal analysis could increase the signal-to-noise ratio up to a factor five compared to a standard one.
On the Analysis of Quantile Forward Regression

In this paper, we study the theoretical properties of K -step and t -threshold quantile forward regressions in a linear quantile regression model with high-dimensional covariates. The model under our investigation is assumed potentially misspeciﬁed and we consider the best sparse approximation using quantile forward regressions. We provide non-asymptotic prediction bounds for both methods, and show asymptotic convergence results and the asymptotic eﬃcacy of K step quantile forward regression. In our asymptotic framework, we allow the number of covariates and the number of steps to diverge at diﬀerent rates with the sample size. We demonstrate superior ﬁnite sample performance of quantile forward regressions to commonly-used penalization methods in terms of prediction accuracy and variable selection through extensive Monte Carlo simulations. We illustrate the usage of quantile forward regressions by two empirical applications: growth-at-risk forecasting and testing the convergence hypothesis of international economic growth. pn both results asymptotic show good the approximation to the optimality in terms of quantile loss our numerical simulation we compare the performance of K -step quantile forward regression with l 1 -penalized quantile regression under diﬀerent data generating process (DGP) settings. Our Monte Carlo simulation results show that the K -step quantile forward regression outperforms l 1 -penalized quantile regression under both sparse and dense models in terms of the average quantile prediction accuracy and the eﬀectiveness in variable selection. To show the promising usage of our method, we apply K -step quantile forward regression into two empirical examples with real macroeconomic data. The ﬁrst application considers a growth-at-risk (GaR) prediction example with high dimensional macroeconomic series. Our result suggests that K -step quantile forward regression can provide more accurate quantile forecasting than l 1 -penalized quantile regression. In the second application, we examine the international growth convergence hypothesis from the quantile perspective with relatively high dimensional, country-speciﬁc, and cross-sectional data. We ﬁrst select relevant conditioning covariates by our K -step quantile forward regression and then the estimate of the eﬀect across diﬀerent quantiles. and t -threshold quantile forward regression. We show that quantile forward regressions are useful in dealing with high-dimensionality issues in the linear quantile regression model. Under the non-asymptotic framework, we are able to show that the quantile forward
Cross-Validated Conditional Density Estimation and Continuous Difference-in-Differences Models

In this paper, we study conditional density estimation based on a series representation. In this series representation, each term takes the form of a multiplication of a known function and its conditional expectation. These conditional expectations can be estimated using various machine learning methods for high-dimensional conditioning variables with suitable structures. We propose a data-driven method of selecting the series terms based on a modified cross-validation procedure, and we establish an oracle inequality on the estimation error of such an estimator. Conditional densities have a wide range of applications in various fields of economics, and we add to this literature a new application to nonparametric difference-in-differences models with continuous treatments. For this application, we establish identification, estimation, and inference results under the double/debiased machine learning framework, and we illustrate our methods by revisiting an empirical study by Duflo (2001) on a large policy intervention in Indonesia.
Benefits of Ginger as Medicine for COVID-19: Literature Study

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) affects other systems, including the digestive, circulatory, urogenital, and even the central nervous systems, as its receptor Angiotensin-Converting Enzyme-2 (ACE-2) is expressed in several organs, such as lungs, intestine, heart, esophagus, kidneys, bladder, testes, liver and brain. Different mechanisms, in particular, massive virus replication, extensive apoptosis and necrosis of lung-related epithelial and endothelial cells, vascular leakage, hyperinflammatory responses, overproduction of proinflammatory mediators, cytokine storm, oxidative stress, the downregulation of ACE2 and impairment of the renin-angiotensin system contribute to the pathogenesis of COVID-19. Currently, COVID-19 is a global pandemic with no specific antiviral treatment. The favorable abilities of ginger were indicated in patients suffering from osteoarthritis, neurodegenerative disorders, rheumatoid arthritis, type 2 diabetes, respiratory distress, liver diseases, and primary dysmenorrhea. Ginger or its compounds exhibited strong anti-inflammatory and antioxidant influences in numerous animal models. This review provides evidence regarding the potential effects of ginger against SARS-CoV-2 infection and highlights its antiviral, anti-inflammatory, antioxidant, and immunomodulatory impacts in an attempt to consider this plant as an alternative therapeutic agent for the treatment of COVID-19.
Microarray Analysis Reveals Overexpression of both Integral Membrane and Cytosolic Tight Junction Genes in Endometrial Cancer Cell Lines

Deregulation of tight junction (TJ) proteins and the associated disruption of TJ function has been demonstrated to play a role in the development of endometrial cancer. In the current study, we have shown overexpression of claudin-3 and -4 mRNA (by RT-PCR) and protein (by immunoblotting) in a panel of 9 human endometrial cancer cell lines. To further expand our understanding of the complex role of TJ deregulation in endometrial cancer, we also investigated the expression of 84 TJ and TJ-associated genes (encoding the array of proteins that function within the TJ network from the membrane to nuclear signaling pathways) by microarray analysis. Consistent with the claudin-3 and -4 RT-PCR and immunoblot findings described above, we observed overexpression of the claudin-3 and -4 genes by microarray analysis. Further, we observed overexpression of an additional three genes in 8 of the 9 endometrial cancer cell lines: OCLN (occludin), F11R (JAM-A) and TJP3 (ZO-3). OCLN and F11R encode integral membrane proteins whereas TJP3 encodes a cytosolic scaffolding protein that indirectly links membrane TJ proteins to the actin cytoskeleton and cell signaling pathways. Our data suggest that the structural disruption of TJs coupled with the downstream deregulation of signaling pathways involved in cellular proliferation and migration may contribute to the development of endometrial cancer.
Search for rings and satellites around the exoplanet CoRoT-9b using Spitzer photometry

Using Spitzer photometry at 4.5 microns, we search for rings and satellites around the long period transiting planet CoRoT-9b. We observed two transits in 2010 and 2011. From their non-detection, we derive upper limits on the plausible physical characteristics of these objects in the planet environment. We show that a satellite larger than about 2.5 Earth radii is excluded at 3 σ for a wide range of elongations at the two epochs of observations. Combining the two observations, we conclude that rings are excluded for a wide variety of sizes and inclination. We find that for a ring extending up to the Roche limit, its inclination angle from the edge-on configuration as seen from the Earth must be lower than 13° in the case of silicate composition and lower than 3° in the case of material with water ice density.
Gas Contents of Galaxy Groups from Thermal Sunyaev–Zel’dovich Effects

A matched filter technique is applied to the Planck all-sky Compton y-parameter map to measure the thermal Sunyaev–Zel’dovich (tSZ) effect produced by galaxy groups of different halo masses selected from large redshift surveys in the low-z universe. Reliable halo mass estimates are available for all of the groups, which allows us to bin groups of similar halo masses to investigate how the tSZ effect depends on halo mass over a large mass range. Filters are simultaneously matched for all groups to minimize projection effects. We find that the integrated y-parameter and the hot gas content it implies are consistent with the predictions of the universal pressure profile model only for massive groups above , but much lower than the model prediction for low-mass groups. The halo mass dependence found is in good agreement with the predictions of a set of simulations that include strong active galactic nucleus feedback, but simulations including only supernova feedback significantly overpredict the hot gas contents in galaxy groups. Our results suggest that hot gas in galaxy groups is either effectively ejected or in phases much below the virial temperatures of the host halos.
1993 Superoutburst of LL Andromedae

We present time-resolved CCD photometry of LL And during its 1993 outburst. The observation revealed the presence of superhumps with a period of 0.05697(3)d. This period is one of the smallest among the hydrogen-rich dwarf novae. Although LL And has been proposed to be a WZ Sge-type dwarf nova based on its low outburst frequency, our new analysis indicates that the outburst amplitude (∼5mag) and outburst duration (9 ±2d) are much smaller and shorter than in typical WZ Sge-type dwarf novae. We suspect that the unusual outburst properties of LL And might be explained by assuming a “leaky disk” in quiescence, which was originally proposed to explain the prototypical WZ Sge-type outbursts. By combining with the recent suggestion of the orbital period, the fractional superhump excess is found to be 3.5(1)%, which is unusually large for this short-period system. LL And may be an object filling the gap in the evolutionary track, which has recently been proposed to explain the unusual ultracompact binaries with an evolved mass donor.
A Novel Double-Sided Pulse Interval Modulation (DS-DS-PIM) Aided SIM-OFDM for 6G Light Fidelity (LiFi) Networks

Subcarrier Index Modulation is an OFDM variant that provides superior power and bandwidth efficiency. In this paper, we present a novel, double-sided pulse interval modulation (DS-PIM)-based SIM OFDM technique. The proposed technique exploits the variable symbol size of DPIM to provide a variable sub-block size and enable dynamic assignment of subcarriers rather than the fixed size of conventional SIM OFDM. In comparison with conventional Subcarrier Index-Modulated OFDM (SIM-OFDM), the proposed approach shows a 12.5% reduction in bandwidth usage for a 2-bit index word. On average, 3.5 subcarriers are employed by the proposed technique per sub-block, in comparison with 4 subcarriers for the conventional technique. The proposed technique provides a superior spectral efficiency compared with conventional SIM-OFDM, even for higher-order modulation.
Backreaction and the Unruh effect: New insights from exact solutions of uniformly accelerated detectors

Using nonperturbative results obtained recently for a uniformly accelerated Unruh-DeWitt detector, we discover new features in the dynamical evolution of the detector's internal degree of freedom, and identified the Unruh effect derived originally from time-dependent perturbation theory as operative in the ultraweak coupling and ultrahigh acceleration limits. The mutual interaction between the detector and the field engenders entanglement between them, and tracing out the field leads to a mixed state of the detector even for a detector at rest in Minkowski vacuum. Our findings based on this exact solution show clearly the differences from the ordinary result where the quantum field's backreaction is ignored in that the detector no longer behaves like a perfect thermometer. From a calculation of the evolution of the reduced density matrix of the detector, we find that the transition probability from the initial ground state over an infinitely long duration of interaction derived from time-dependent perturbation theory is existent in the exact solution only in transient under special limiting conditions corresponding to the Markovian regime. Furthermore, the detector at late times never sees an exact Boltzmann distribution over the energy eigenstates of the free detector, thus in the non-Markovian regime covering a wider range ofmore » parameters the Unruh temperature cannot be identified inside the detector. « less
Discrete superconducting transition temperatures and pronounced T-c depression related to the 1/8 problem in Bi2Sr2-xLaxCuO6+delta single crystals

By measuring the in-plane resistance on overdoped Bi2Sr2-xLaxCuO6+y single crystals, we observed a giant dissipation peak below the zero-field superconducting transition temperature when applying an external magnetic field. The temperature dependence of the fields corresponding to zero resistance exhibits an upward curvature which is related to the so-called "anomalous H-c2" behavior. Furthrrmore, an obvious current-effect was observed under the dissipation maximum. Intensive data analysis reveals that these phenomena indicate strong evidence for the: existence of superconducting islands in the: Cu-O planes, which is caused by phase separation and lead to the Josephson-coupling-type dissipative mechanism of in-plane transport in overdoped high temperature superconductors.
MAPPING WETLANDS USING GIS AND REMOTE SENSING TECHNIQUES, A CASE STUDY OF WETLANDS IN GREATER ACCRA, GHANA

Peter Gorsevski, Committee Chair The goal of this study is to explore land use and land cover (LULC trends in Greater Accra Metropolitan Area (GAMA, a highly urbanized coastal region in Ghana by analyzing historical change rates and forecasting future scenarios. As industrialization and basic anthropological necessities increase in the region, natural land resources, specifically wetlands, are undergoing adverse changes. With the help of Modules for Land Use Change Evaluation (MOLUSCE which is a plugin in QGIS, the study identifies land-use changes in GAMA for 2002, 2013, and 2020 as well as forecasts and establishes potential land-use changes in 2030 and 2040. The presented approach incorporates well-known algorithms such as artificial neural networks (ANN for computing transition potential maps coupled with cellular automata (CA simulation. To analyze their impact on LULC between 2002 and 2013, five criteria were used in the CA-ANN framework, including elevation, slope, distance from roads, distance from towns, and distance from rivers. The validation of simulated LULC maps for 2020 indicates a good level of accuracy, with a kappa value of 0.70 and a correctness percentage of 78.50%. The future scenarios between 2020 and 2040 indicate that urban development and sprawl are expected to increase annually at a dynamic degree rate of 0.86% at the expense of natural land covers such as wetlands and vegetation. The major road network in GAMA spearheads the growth of developed areas, while slope and elevation act as constraints. A high ratio of impervious to pervious surfaces confirms the rapid urbanization of the area. Urbanization is likely to have a more detrimental effect on natural habitats in the near future less so in the distant future. This study iv emphasizes the importance of establishing appropriate urban planning policies and management methods for sustainable environmental conservation.