Miracle-dz/UniFAR-FTUs huggingface dataset:
Propagation of Medicinal Plants for Sustainable Livelihoods, Economic Development, and Biodiversity Conservation in South Africa

South Africa is blessed with vast plant resources and unique vegetation types. Indigenous South African medicinal plants have been well-harnessed to generate income in rural communities. Many of these plants have been processed into natural products to heal a variety of diseases, making them valuable export commodities. South Africa has one of the most effective bio-conservation policies in Africa, which has protected the South African indigenous medicinal vegetation. However, there is a strong link between government policies for biodiversity conservation, the propagation of medicinal plants as a source of livelihood, and the development of propagation techniques by research scientists. Tertiary institutions nationwide have played a crucial role in the development of effective propagation protocols for valuable South African medicinal plants. The government-restricted harvest policies have also helped to nudge natural product companies and medicinal plant marketers to embrace the cultivated plants for their medicinal uses, and thus have helped support the South African economy and biodiversity conservation. Propagation methods used for the cultivation of the relevant medicinal plants vary according to plant family and vegetation type, among others. Plants from the Cape areas, such as the Karoo, are often resuscitated after bushfires, and propagation protocols mimicking these events have been established through seed propagation protocols with controlled temperatures and other conditions, to establish seedlings of such plants. Thus, this review highlights the role of the propagation of highly utilized and traded medicinal plants in the South African traditional medicinal system. Some valuable medicinal plants that sustain livelihoods and are highly sought-after as export raw materials are discussed. The effect of South African bio-conservation registration on the propagation of these plants and the roles of the communities and other stakeholders in the development of propagation protocols for highly utilized and endangered medicinal plants are also covered. The role of various propagation methods on the bioactive compounds’ composition of medicinal plants and issues of quality assurance are addressed. The available literature, media online news, newspapers, and other resources, such as published books and manuals, were scrutinized for information.
Moving Away from 12:12; the Effect of Different Photoperiods on Biomass Yield and Cannabinoids in Medicinal Cannabis

The standard practice to initiate flowering in medicinal cannabis involves reducing the photoperiod from a long-day period to an equal duration cycle of 12 h light (12L)/12 h dark (12D). This method reflects the short-day flowering dependence of many cannabis varieties but may not be optimal for all. We sought to identify the effect of nine different flowering photoperiod treatments on the biomass yield and cannabinoid concentration of three medicinal cannabis varieties. The first, “Cannatonic”, was a high cannabidiol (CBD)-accumulating line, whereas the other two, “Northern Lights” and “Hindu Kush”, were high Δ9-tetrahydrocannabinol (THC) accumulators. The nine treatments tested, following 18 days under 18 h light/6 h dark following cloning and propagation included a standard 12L:12D period, a shortened period of 10L:14D, and a lengthened period of 14L:10D. The other six treatments started in one of the aforementioned and then 28 days later (mid-way through flowering) were switched to one of the other treatments, thus causing either an increase of 2 or 4 h, or a decrease of 2 or 4 h. Measured parameters included the timing of reproductive development; the dry weight flower yield; and the % dry weight of the main target cannabinoids, CBD and THC, from which the total g cannabinoid per plant was calculated. Flower biomass yields were highest for all lines when treatments started with 14L:10D; however, in the two THC lines, a static 14L:10D photoperiod caused a significant decline in THC concentration. Conversely, in Cannatonic, all treatments starting with 14L:10D led to a significant increase in the CBD concentration, which led to a 50–100% increase in total CBD yield. The results show that the assumption that a 12L:12D photoperiod is optimal for all lines is incorrect as, in some lines, yields can be greatly increased by a lengthened light period during flowering.
La Via Campesina – transforming agrarian and knowledge politics, and co-constructing a field: a laudatio

ABSTRACT La Via Campesina has revalorized agrarian politics, transformed knowledge politics, and co-constructed the field of Critical Agrarian Studies. It has shown the important role of agrarian movements in anti-capitalist struggles and the radical reimagination and construction of a positive future. The significance of LVC is found not in the shrinking numerical size of farming populations or in agriculture’s dwindling macroeconomic contributions to national economies, in relative terms, but in the political heft of what it represents in terms of an alternative future that is so different from the current agrarian world.
Lorentz transmission electron microscopy of focused ion beam patterned magnetic antidot arrays

A focused-ion beam has been used to pattern magnetic antidot arrays containing different sized antidots and spacings in Ni80Fe20 films. Their magnetic domain structure has been studied using Lorentz transmission electron microscopy, which has shown that the edges of the antidots pin the domain walls during magnetization reversal. The remanent domain structure was found to depend strongly on the antidot size and spacing, from domains pinned between the corners of adjacent rows of antidots for large sizes to domains pinned between the edges of adjacent antidots for small sizes. The relevance of such structures for high density recording is discussed.
R-Diffset vs. IR-Diffset: Comparison Analysis in Dense and Sparse Data

—The mining of concealed information from databases using Association Rule Mining seems to be promising. The successful extraction of this information will give a hand to many areas by aiding them in the process of finding solutions, economic projecting, commercialization policies, medical inspections, and numbers of other problems. ARM is the most outstanding method in the mining of remarkable related configurations from any groups of information. The important patterns encountered are categorized as recurrent/frequent and non-recurrent/infrequent. Most of the previous data mining methods concentrated on horizontal data set-ups. Nevertheless, recent studies have shown that vertical data formats are becoming the main concerns. One example of vertical data format is Rare Equivalence Class Transformation (R-Eclat). Due to its efficacy, R-Eclat algorithms have been commonly applied for the processing of large datasets. The R-Eclat algorithm is actually comprised of four types of variants. However, our work will only focus on the R-Diffset variant and Incremental R-Diffset (IR-Diffset). The performance analysis of the R-Diffset and IR-Diffset algorithms in the mining of sparse and dense data are compared. The processing time for R-Diffset algorithm, especially for sequential processing is very long. Thus, the incremental R-Diffset (IR-Diffset) has been established to solve this problem. While R-Diffset may only process the non-recurrent itemsets mining process in sequential form, IR-Diffset on the other hand has the capability to execute sequential data that have been fractionated. The advantages of this newly developed IR-Diffset may become a potential candidate in providing a time-efficient data mining process, especially those involving the large sets of data.
T‐optimum designs for discrimination between two multiresponse dynamic models

Summary. The paper is concerned with a problem of finding an optimum experimental design for discriminating between two rival multiresponse models. The criterion of optimality that we use is based on the sum of squares of deviations between the models and picks up the design points for which the divergence is maximum. An important part of our criterion is an additional vector of experimental conditions, which may affect the design. We give the necessary conditions for the design and the additional parameters of the experiment to be optimum, we present the algorithm for the numerical optimization procedure and we show the relevance of these methods to dynamic systems, especially to chemical kinetic models.
Fatty Acid Binding Proteins 3 and 4 Predict Both All-Cause and Cardiovascular Mortality in Subjects with Chronic Heart Failure and Type 2 Diabetes Mellitus

Subjects with type 2 diabetes mellitus (T2D) are at increased risk for heart failure (HF). The cardiac-specific (FABP3) and adipose-tissue-specific (FABP4) types of the fatty acid binding proteins have been associated with both all-cause and cardiovascular (CV) mortality. The aim of this study was to explore the prognosis value of FABP3 and FABP4 in ambulatory subjects with chronic HF (CHF), with and without T2D. A prospective study involving 240 ambulatory CHF subjects was performed. Patients were followed-up for a mean of 5.78 ± 3.30 years and cause of death (if any) was recorded. Primary endpoints were defined as all-cause and CV death, and a composite endpoint that included CV death or hospitalization for HF was included as a secondary endpoint. Baseline serum samples were obtained and the serum FABP3 and FABP4 concentrations were assessed by sandwich enzyme-linked immunosorbent assay. Survival analysis was performed with multivariable Cox regressions, using Fine and Gray competing risks models when needed, to explore the prognostic value of FABP3 and FABP4 concentrations, adjusting for potential confounders. Type 2 diabetes mellitus was highly prevalent, accounting for 47.5% for total subjects with CHF. Subjects with T2D showed higher mortality rates (T2D: 69.30%; non-T2D: 50.79%, p = 0.004) and higher serum FABP3 (1829.3 (1104.9–3440.5) pg/mL vs. 1396.05 (820.3–2362.16) pg/mL, p = 0.007) and FABP4 (45.5 (27.6–79.8) ng/mL vs. 34.1 (24.09–55.3) ng/mL, p = 0.006) concentrations compared with non-T2D CHF subjects. In the whole study cohort, FABP3 was independently associated with all-cause death, and both FABP3 and FABP4 concentrations were associated with CV mortality. The predictive values of these two molecules for all-cause (FABP3: HR 1.25, 95% CI 1.09–1.44; p = 0.002. FABP4: HR 2.21, 95% CI 1.12–4.36; p = 0.023) and CV mortality (FABP3: HR 1.28, 95% CI 1.09–1.50; p = 0.002. FABP4: HR 4.19, 95% CI 2.21–7.95; p < 0.001) were only statistically significant in the subgroup of subjects with T2D. Notably, FABP4 (HR 2.07, 95% CI 1.11–3.87; p = 0.022), but not FABP3, also predicted the occurrence of the composite endpoint (death or hospitalization for HF) only in subjects with T2D. All these associations were not found in CHF subjects without T2D. Our findings support the usefulness of serum FABP3 and FABP4 concentrations as independent predictors for the occurrence of all-cause and CV mortality in ambulatory subjects with CHF with T2D.
Alterations in Fecal Microbiota Linked to Environment and Sex in Red Deer (Cervus elaphus)

Simple Summary The gut microbiota forms a complex microecosystem in vertebrates and is affected by various factors. Wild and captive red deer currently live in the same region but have vastly different diets. In this study, the 16S rRNA sequencing technology was performed to evaluate variations in the fecal microbiota of wild and captive individuals of both sexes of red deer. It was found that the composition and function of fecal microbiota in wild and captive environments were significantly different. As a key intrinsic factor, sex has a persistent impact on the formation and development of gut microbiota. Overall, this study reveals differences in the in the fecal microbiota of red deer based on environment and sex. These data could guide future applications of population management in red deer conservation. Abstract Gut microbiota play an important role in impacting the host’s metabolism, immunity, speciation, and many other functions. How sex and environment affect the structure and function of fecal microbiota in red deer (Cervus elaphus) is still unclear, particularly with regard to the intake of different diets. In this study, non-invasive molecular sexing techniques were used to determine the sex of fecal samples from both wild and captive red deer during the overwintering period. Fecal microbiota composition and diversity analyses were performed using amplicons from the V4–V5 region of the 16S rRNA gene sequenced on the Illumina HiSeq platform. Based on Picrust2 prediction software, potential function distribution information was evaluated by comparing the Kyoto Encyclopedia of Genes and Genome (KEGG). The results showed that the fecal microbiota of the wild deer (WF, n = 10; WM, n = 12) was significantly enriched in Firmicutes and decreased in Bacteroidetes, while the captive deer (CF, n = 8; CM, n = 3) had a significantly higher number of Bacteroidetes. The dominant species of fecal microbiota in the wild and captive red deer were similar at the genus level. The alpha diversity index shows significant difference in fecal microbiota diversity between the males and females in wild deer (p < 0.05). Beta diversity shows significant inter-group differences between wild and captive deer (p < 0.05) but no significant differences between female and male in wild or captive deer. The metabolism was the most important pathway at the first level of KEGG pathway analysis. In the secondary pathway of metabolism, glycan biosynthesis and metabolism, energy metabolism, and the metabolism of other amino acids were significantly different. In summary, these compositional and functional variations in the fecal microbiota of red deer may be helpful for guiding conservation management and policy decision-making, providing important information for future applications of population management and conservation.
Retrieval of Raindrop and Cloud Particle Size Distributions with 14 GHz and 95 GHz Radars

We have developed a sequential algorithm to retrieve vertical profiles of cloud and rainfall microphysical information from radar reflectivities of a 14 GHz precipitation radar, and a 95 GHz cloud profiling radar. This sequential algorithm retrieves the number density NT, the mean volume diameter Dm and the liquid water content LWC from the nearest to the farthest ranges considering the significant attenuation and Mie scattering. To avoid the accumulation of numerical errors, the retrieval is computed in adjacent ranges assuming NT to be constant in each pair. We demonstrate that our method retrieves NT and Dm stably, even if the raindrop size distribution is different from our assumption, or even if some bias errors are appended to the radar constant. The method is applied to collocated ground-based observation by a 14 and a 95 GHz radar, and the retrieved results are evaluated by comparing them against disdrometer-derived size distributions, where the rainfall rate was from 0.1 to 4.6 mm/hr. The retrieved Dm, and the disdrometer-derived Dm, agree to within 30%. The retrieved log10 LWC, and the disdrometer-derived log10 LWC, also agree to within 30% when the rainfall rate is greater than 0.5 mm/hr.
LYAPROSEN: MATLAB function to calculate Lyapunov exponent

This code uses Rosenstein et al. method with some modifications based on below references. It allow to user select embedding lag( tau) and embedding dimension(m), but if a user cannot give any value to this parameters the code will select automatically this values. For the selection of tau methods of autocorrelation function and minimum mutual information is used in the code. Also two methods namely False Nearest Neighbors and Symplectic Geometry is used for choosing proper value of embedding dimension. -Rosenstein,M. T. , J. J. Collins and C. J. De Luca,(1993). A practical method for calculating largest Lyapunov exponents from small data sets. Physica D. -Hai-Feng Liu, Zheng-Hua Dai, Wei-Feng Li, Xin Gong, Zun-Hong Yu(2005) Noise robust estimates of the largest Lyapunov exponent,Physics Letters A 341, 119O127 -Sprott,J. C. (2003). Chaos and Time Series Analysis. Oxford University Press. -Lei, M. , Wang Z. , Feng Z. A method of embedding dimension estimation based on symplectic geometry, Physics Letters A 303 (2002) 179O189. -Zeng,X. , R. Eykholt, and R. A. Pielke (1991)Estimating the Lyapunov-Exponent Spectrum from Short Time Series of Low Precision, Physical Review Letters, Vol. 66, Number 25.
Recent optical activity in the nucleus of the X-ray Seyfert galaxy MCG 8-11-11.

The X-ray Seyfert galaxy, MCG 8--11--11, is shown to exhibit significant variations in its colors and optical flux on time scales ranging from two days to several months. These variations place limits on the size of the emitting region at less than 1.75 x 10/sup -3/pc. In its bright phase, the colors and luminosity of MCG 8--11--11 are similar to those of 3C 120. However, significantly different colors are found when the galaxy is fainter.
Papaver somniferum and Papaver rhoeas Classification Based on Visible Capsule Images Using a Modified MobileNetV3-Small Network with Transfer Learning

Traditional identification methods for Papaver somniferum and Papaver rhoeas (PSPR) consume much time and labor, require strict experimental conditions, and usually cause damage to the plant. This work presents a novel method for fast, accurate, and nondestructive identification of PSPR. First, to fill the gap in the PSPR dataset, we construct a PSPR visible capsule image dataset. Second, we propose a modified MobileNetV3-Small network with transfer learning, and we solve the problem of low classification accuracy and slow model convergence due to the small number of PSPR capsule image samples. Experimental results demonstrate that the modified MobileNetV3-Small is effective for fast, accurate, and nondestructive PSPR classification.
Editorial: Leishmania genome variability: Impacts on parasite evolution, parasitism and leishmaniases control

COPYRIGHT © 2023 Tosi, Denny, De Oliveira and Damasceno. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Editorial PUBLISHED 06 March 2023 DOI 10.3389/fcimb.2023. 1171962
Metabolic Health, Obesity, and Intraocular Pressure

Obesity has been associated with increased intraocular pressure (IOP), but the results are inconsistent. Recently, a subgroup of obese individuals with good metabolic profiles were suggested to have better clinical outcomes than normal-weight individuals with metabolic diseases. The relationships between IOP and different combinations of obesity and metabolic health status have not been investigated. Therefore, we investigated the IOP among groups with different combinations of obesity status and metabolic health status. We examined 20,385 adults aged 19 to 85 years at the Health Promotion Center of Seoul St. Mary’s Hospital between May 2015 and April 2016. Individuals were categorized into four groups according to obesity (body mass index (BMI) ≥ 25 kg/m2) and metabolic health status (defined based on prior medical history or abdominal obesity, dyslipidemia, low high-density lipoprotein cholesterol, high blood pressure, or high fasting blood glucose levels upon medical examination). ANOVA and ANCOVA were performed to compare the IOP among the subgroups. The IOP of the metabolically unhealthy obese group (14.38 ± 0.06 mmHg) was the highest, followed by that of the metabolically unhealthy normal-weight group (MUNW, 14.22 ± 0.08 mmHg), then, the metabolically healthy groups (p < 0.001; 13.50 ± 0.05 mmHg and 13.06 ± 0.03 mmHg in the metabolically healthy obese (MHO) and metabolically healthy normal-weight groups, respectively). Subjects who were metabolically unhealthy showed higher IOP compared to their counterparts who were metabolically healthy at all BMI levels, and there was a linear increase in IOP as the number of metabolic disease components increased, but no difference between normal-weight vs. obese individuals. While obesity, metabolic health status, and each component of metabolic disease were associated with higher IOP, those who were MUNW showed higher IOP than those who were MHO, which indicates that metabolic status has a greater impact than obesity on IOP.
Conservative Bladder Management and Medical Treatment in Chronic Spinal Cord Injury Patients

To review the available data on non-surgical management for neurogenic lower urinary tract dysfunction (NLUTD) in patients with chronic spinal cord injury (SCI) and provide the most updated knowledge for readers. We categorized the bladder management approaches into storage and voiding dysfunction separately; both are minimally invasive, safe, and efficacious procedures. The main goals for NLUTD management are to achieve urinary continence; improve quality of life; prevent urinary tract infections and, last but not least, preserve upper urinary tract function. Annual renal sonography workups and regular video urodynamics examinations are crucial for early detection and further urological management. Despite the extensive data on NLUTD, there are still relatively few novel publications and there is a lack of high-quality evidence. There is a paucity of new minimally invasive and prolonged efficacy treatments for NLUTD, and a partnership between urologists, nephrologists and physiatrists is required to promote and ensure the health of SCI patients in the future.
A New Approach to Empirical Mode Decomposition Based on Akima Spline Interpolation Technique

The objective of this research work is to extend the scope of the empirical mode decomposition (EMD) algorithm, as an efficient tool to decompose the nonlinear and non-stationary time series. For EMD to be widely applicable, the extension utilizes both clean and noisy data sets. When constructing upper and lower envelopes, the proposed algorithm utilizes the Akima spline interpolation technique rather than a cubic spline. The proposed EMD is called Akima-EMD, which is used to identify non-informative fluctuations in the signal, such as noise, outliers, and ultra-high frequency components, and to break down the clean and chaotic data into various components to avoid distortion. It has been shown through synthetic as well as real-world time series data analysis that the proposed method successfully extracts noise in the form of the first IMF from the data.
Quantum mechanical transition state theory and a new semiclassical model for reaction rate constants

An ``exact'' quantum mechanical transition state theory is defined, i.e., a model which invokes the basic transition state idea to calculate the rate of a chemical reaction but which is free of any auxiliary approximations. Most importantly, for example, it is not necessary to assume that the Hamiltonian is separable about the saddle point. It is argued that this model should provide an accurate description of the threshold region of the reaction where quantum effects are most significant. Finally, an even more general model, a new kind of semiclassical approximation, is presented which is essentially a synthesis of this quantum mechanical transition state model and the completely classical trajectory procedure for determining the rate constant; at sufficiently high temperatures, quantum effects become negligible, so that the correct rate constant is obtained; while at low temperature, the correct result is obtained because the transition state model becomes valid.