Miracle-dz/UniFAR-FTUs huggingface dataset:
Antiproliferative Activity of Hypericum perforatum, Achillea millefolium, and Aloe vera in Interaction with the Prostatic Activity of CD82.

Background In recent years, prostate cancer prevails as one of the lead cancers affecting men. Currently, prostate cancer research involves the phytochemical study of plants with anti-tumour effects. This study compares the anti-tumour effects of three plant species indigenous to Iran and their interaction with cluster of differentiation (CD)-82 protein, a therapeutic target found in prostate cancer cells. Methods The extracts of Hypericum perforatum, Achillea millefolium, and Aloe vera were prepared and their toxicological, cellular and gene expression responses were evaluated in PC-3 human prostate cancer cells and normal human chondrocyte cell line C28/I2. They were exposed to different concentrations of the plants (10 mg/mL, 5 mg/mL, 1 mg/mL, 100 µg/mL, 10 µg/mL, and 1 µg/mL) at three exposure time points (24, 48, 72 hours) to determine cancer cell cytotoxicity and gene expression profiles. Results : Half-maximal inhibitory concentration (IC50) in PC-3 cells ranged from 0.6 to 8.5 mg/mL for H. perforatum extract, from 0.4 to 7.5 mg/mL for A. Millefolium extract, and from 0.2 to 8.0 mg/mL for A. vera extract in a time-dependent manner. A. vera extract caused the highest cell death levels in PC-3 cells (94%) and C28/I2 cells (57%) after 48 hours. A 1.97-, 3.00-, and 3.48-fold increase in relative gene expression of CD82 was observed for H. perforatum, A. millefolium, and A. vera extracts, respectively. Conclusion A. vera and A. millefolium extracts are a selective inhibitor of prostate cancer cells and a potent activator of CD82 expression.
Adsorption of 2-Butanone on Pristine Graphene: A First-principles Study

This study investigates the adsorption mechanism of 2-butanone (ethyl methyl ketone) on the surface of graphene by using Density Functionals Theory (DFT). A 2-butanone molecule was chosen as a selected example of main volatile organic compounds (VOCs) in exhaled breath. To describe the absorption of 2-butanone and graphene substrate, the study performed DFT simulations including van de Waals (vdW) interactions implemented in the Vienna Ab-initio Simulation Package (VASP). The global minimum energy configurations and binding energies for a 2-butanone molecule adsorbed on graphene were determined by using Computational DFT-based Nanoscope tool for imaging the binding possibility of the adsorbed molecules on the graphene surface. The adsorption energy profiles were calculated by three functionals of van der Waals interactions: revPBE-vdW, optPBE-vdW, and vdW-DF2. The study results show that the adsorption energy was highly sensitive to the vdW functionals. The study also provides a detailed discussion of fundamental insights of the interactions between 2butanone and graphene through molecular doping, i.e., charge transfer.
Clinical characteristics and factors associated with disability and impaired quality of life in children with juvenile systemic sclerosis

Correspondence: Brandi Stevens, 699 Riley Hospital Drive, Rm 307, Indianapolis, IN 46202 stevenbe@iu.edu. DR. BRANDI EASTMAN STEVENS (Orcid ID : 0000-0001-6257-2301) DR. SUZANNE C LI (Orcid ID : 0000-0001-8276-2866) Conflicts of Interest: None HHS Public Access Author manuscript Arthritis Care Res (Hoboken). Author manuscript; available in PMC 2019 December 01. Published in final edited form as: Arthritis Care Res (Hoboken). 2018 December ; 70(12): 1806–1813. doi:10.1002/acr.23547. A uhor M anscript
Impact of hydropriming duration on seed germination and emergence indices of sweet basil

The experiment was conducted in the Department of Horticultural Technology, Enugu State Polytechnic, Iwollo, Enugu state, Nigeria to determine the impact of hydro-priming duration on seed germination and emergence indices of sweet basil (Ocimum basilicum) in August, 2018. The treatments were 6, 12, 18, and 24 hours of hydropriming. The control treatment was left un-primed. Twenty seeds from each treatment were plated in Petri dish which contained two layers of filter papers that were wetted with 10 ml of distilled water and was used for the germination studies. Twenty seeds from each of the treatment were sown in 2 kg nursery medium (poly pot) with nursery mixture of soil, well cured poultry manure and sand in the ratio of 3:2:1, respectively and was used for the emergence studies. The experiment was laid in completely randomized design with three replications. Data on germination and emergence indices were collected and analyzed using analysis of variance (ANOVA). The treatment means that were significant were separated using least significant difference at 0.05 probability level. The results showed that hydro-priming significantly (p<0.05) increased germination percentage, coefficient of velocity of germination, coefficient of uniformity of germination, emergence percentage and coefficient of velocity of emergence with 18 hour having superior values and the least values were in control. Hydro-priming also significantly decreased mean germination time, mean emergence time, days to 50% germination and days to 50% emergence with the least values obtained in 18 hours and the highest values were in control. It can be concluded that hydro-priming significantly improved germination and emergence of sweet basil (O. basilicum). The optimal hydro-priming duration for sweet basil (O. basilicum) was 18 hours, which enhanced seed germination and emergence percentage, ensured early germination and seedling emergence, and increased uniformity of emergence.
Spatial and temporal variations in glacier aerodynamic surface roughness during the melting season, as estimated at the August-one ice cap, Qilian mountains, China

Abstract. The aerodynamic roughness of glacier surfaces is an important factor governing turbulent heat transfer. Previous studies rarely estimated spatial and temporal variation in aerodynamic surface roughness ( z0 ) over a whole glacier and whole melting season. Such observations can do much to help us understand variation in z0 and thus variations in turbulent heat transfer. This study, at the August-one ice cap in the Qilian mountains, collected three-dimensional ice surface data at plot scale, using both automatic and manual close-range digital photogrammetry. Data were collected from sampling sites spanning the whole ice cap for the whole of the melting season. The automatic site collected daily photogrammetric measurements from July to September of 2018 for a plot near the center of the ice cap. During this time, snow cover gave way to ice and then returned to snow. z0 was estimated based on micro-topographic methods from automatic and manual photogrammetric data. Manual measurements were taken at sites from the terminals to the top of the ice cap; they showed that z0 was larger at the snow and ice transition zone than in areas that are fully snow or ice covered. This zone moved up the ice cap during the melting season. It is clear that persistent snowfall and rainfall both reduce z0 . Using data from a meteorological station near the automatic photogrammetry site, we were able to calculate surface energy balances over the course of the melting season. We found that high or rising turbulent heat, as a component of surface energy balance, tended to produce a smooth ice surface and a smaller z0 and that low or decreasing turbulent heat tended to produce a rougher surface and larger z0 .
An observational study of paracetamol (acetaminophen) deprescribing in patients with cancer pain receiving opioids for moderate-to-severe pain

Background. The objective of the study was to investigate the utility of deprescribing paracetamol in cancer patients receiving opioids for moderate-to-severe pain. Material and methods. Patients with well-controlled cancer pain (average pain intensity ≤ 4/10), who were receiving regular paracetamol and an opioid for moderate-to-severe pain, completed the Brief Pain Inventory — Short Form at baseline and at seven days post discontinuation of the paracetamol (or sooner if restarting the paracetamol). The study employed a Simon optimal two-stage design with the aim of reducing the number of subjects exposed to a “futile” intervention. Results. Forty-four patients were enrolled, and 40 patients completed the study. Eighteen (45%) patients restarted the paracetamol, although another four patients reported a worsening of pain control and/or an increase in the use of rescue medication. The only factor associated with restarting paracetamol was the pathophysiology of the pain, with patients with mixed pain more likely to restart paracetamol than patients with nociceptive pain (P = 0.013). Conclusions. On the basis of these results we would recommend a trial of discontinuing paracetamol in all patients receiving opioids for moderate-to-severe pain, who are deemed to be adequately pain controlled. The patients can be reassured that there is approximately a one in two chance of not needing to restart the paracetamol, and that if they do need to start the paracetamol, pain control can be re-gained within a very short period of time.
Group size experiences with enhanced pre- and postnatal development studies in the long-tailed macaque (Macaca fascicularis)

Abstract Enhanced pre- and postnatal development (ePPND) studies have become the default developmental toxicity test for biopharmaceuticals if nonhuman primates represent the relevant species. Spontaneous pregnancy losses and infant deaths can be significant in macaques such as long-tailed macaques. The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) guideline S6(R1) states that pregnancy outcome can be judged also by the normogram-based variability of reference data according to a publication by Jarvis et al. (2010) defining a study as valid with six to eight live infants in the control group on postnatal day 7 (PND7). Since the release of ICH S6(R1) (2011), ePPND studies for biologics have replaced the former separate embryo-fetal and PPND study types. This work provides a retrospective analysis of pregnancy outcomes from 21 ePPND studies and group sizes of 14–24 animals per group. All studies reached the goal of at least six to eight infants on PND7, with overall losses ranging between 5 % and 45 %. Consistently, a group size of 14–24 maternal animals yielded more than six to eight infants on PND7. Therefore, it is suggested to reduce ePPND study group sizes from 20 to 14, yielding an animal number reduction of approx. 30 %.
Reliability Optimization of Structural Deformation with Improved Support Vector Regression Model

Deformation is one important failure mode of turbine blades. The quality of a model seriously influences the reliability optimization of turbine blades in turbo machines. To improve the reliability optimization of turbine blades, this paper proposes a novel machine learning-based reliability optimization approach, named improved support vector regression (SR) model (ISRM) method, by fusing artificial bee colony (ABC), traditional SR model, and multipopulation genetic algorithm (MPGA). In this proposed method, the ABC algorithm was applied to find the optimal parameters in the SR model to establish accurate ISRM, following the thought of the surrogate model method and the randomness of constraints. Then the reliability optimization model and procedure with the ISRM method were resolved by the MPGA. Regarding many design parameters (i.e., rotor speed, temperature, and aerodynamic pressure), design objective (i.e., blade deformation), and the randomness constraints of reliability degree and boundary conditions, we performed the reliability optimization of a turbine blade deformation. From the optimization results, we find that the turbine blade deformation is reduced by 0.09329 mm, and the ISRM learning method can improve the reliability optimization design of complex structures with the emphasis on modeling precision and optimization efficiency. The works of this paper provide a machine learning-based reliability optimization approach for the reliability optimization of complex structures and enrich and develop mechanical reliability theory and methods.
Environmental Pressure from Pig Farming to Surface Water Quality Management in Yen Dung District Bac Giang Province

This study focuses on the environmental pressure of waste generated from pig farming in Yen Dung district. Terrain analysis of the digital elevation model (DEM) was used to delineate the sub-basin map where pollutants accumulated. Then we combined this map with land use map and statistical data for determining the distribution of pollutant discharged sources. Based on the pollution load coefficient prescribed by the Vietnam Environment Administration, the loads from all sources, including pig farming, were estimated for entire sub-basins within the district. The results show that the pollutant load from pig farming accounts for a large proportion and creates a major pressure on the local environment. The pollutant from pig farming greatly influences the spatial distribution of pollutant loads across sub-basins. Therefore, special attention should be paid to the waste management at pig farms (households and farm) to ensure the effectiveness of the environmental protection for the communities.
A Monte Carlo study into time-aggregation in continuous and discrete- time hazard models

The purpose of this study is to investigate the effect of time- aggregation in discrete and continuous-time hazard models. A Monte Carlo study is conducted in which data are generated according to underlying continuous and discrete-time processes, which data are aggregated into daily, weekly and monthly intervals. Under each of these conditions 400 datasets are generated, that vary in the parameters of the baseline hazard. These datasets are analyzed with flexible continuous-time and discrete-time proportional hazard models. The estimates of the structural parameter and of the baseline hazard, as well as the baseline hazard predicted by those estimates, seem robust to the form of the distribution of the data generation process when the time-aggregation window is small. Both estimates of continuous-time models and of discrete-time models suffer from time-aggregation, but the estimates of the discrete-time model are more sensitive to aggregation.
Storage Stability of Volatile Organic Compounds from Petrochemical Plant of China in Different Sample Bags

According to the emission characteristics of volatile organic compounds (VOCs) in the petrochemical plants of China, the storage stability of VOCs for two different bags, polyester aluminum (PEA) and polyvinyl fluoride (PVF), was investigated in this study by comparing the adsorption of gas samples. A series of experiments were carried out to study the impact of different factors of sampling in the petrochemical industry. The results showed that the C2∼C3 substances can be adsorbed by the Tedlar bag, and after being refilled with pure nitrogen, the VOCs adsorbed previously by the bag material can be released. The aromatic hydrocarbon VOCs with larger molecular weight had a relatively lower recovery rate than the smaller molecular weights. And the average recovery of PEA airbags was significantly better than that of PVF airbags for storing stationary VOCs in the refinery of China. More kinds of substances can be detected in the airbags that had been added with helium protective gas, and it had a higher recovery rate for both kinds of simple bags after 24 hours of storage time, which indicated that the airbags without protective gas had adsorbed these substances.
A Super-Resolution DOA Estimation Method for Fast-Moving Targets in MIMO Radar

Direction of arrival (DOA) estimation is an essential problem in the radar systems. In this paper, the problem of DOA estimation is addressed in the multiple-input and multiple-output (MIMO) radar system for the fast-moving targets. A virtual aperture is provided by orthogonal waveforms in the MIMO radar to improve the DOA estimation performance. Different from the existing methods, we consider the DOA estimation method with only one snapshot for the fast-moving targets and achieve the super-resolution estimation from the snapshot. Based on a least absolute shrinkage and selection operator (LASSO), a denoise method is formulated to obtain a sparse approximation to the received signals, where the sparsity is measured by a new type of atomic norm for the MIMO radar system. However, the denoise problem cannot be solved efficiently. Then, by deriving the dual norm of the new atomic norm, a semidefinite matrix is constructed from the denoise problem to formulate a semidefinite problem with the dual optimization problem. Finally, the DOA is estimated by peak-searching the spatial spectrum. Simulation results show that the proposed method achieves better performance of the DOA estimation in the MIMO radar system with only one snapshot.
FEASIBILITY OF THE DEFORMATION ANALYSIS OF A PLATE SUBJECTED TO VIBRATIONS USING RECENT COMPUTER VISION METHODS

: In this work, we deal with the measurement of dynamic displacements of a plate using modern photogrammetric techniques. This plate is subjected to vibrations whose frequencies can vary between 20 Hz and about 4000 Hz. Such analysis is particularly useful for studying excitations due to turbulent flows, which necessitates synchronous acquisitions of the displacement field. For that purpose, we propose a study of the feasibility of such measurements using a simple experimental scheme: two cameras and computer vision methods. The system sensitivity must be sub-millimetric in the plate normal direction. This study is realised by simulating the deformation pattern on a virtual plate and the acquired images. The performances of the simulated protocol is assessed in the case where the external parameters are know or unknown. In this last case, we use the five-point approach described in (Stewénius, 2006) and based on the Gröbner bases. The results show that this experimental scheme should allow sub-millimetric measurements.
A Recursive k-means Initialization Algorithm for Massive Data

Due to the progressive growth of the amount of data available in a wide variety of scientiﬁc ﬁelds, it has become more diﬃcult to manipulate and analyze such information. Even as datasets have grown in size, the k-means algorithm remains one of the most popular clustering methods, in spite of its dependency on the initial settings. In this work, we propose an eﬃcient initialization method, intended for massive data, that deals with this problem by reducing the entire dataset into a small set of representatives. Preliminary experimental results indicate that this method outperforms well known initialization techniques, such as the k-means++ , in both number of distance calculations and data scans.
Polyporoid fungi of Tanzania Taxonomy, transcriptomics and biochemical analyses of Kusaghiporia usambarensis and Piptoporellus baudonii

Hussein, J. M. 2020. Polyporoid fungi of Tanzania. Taxonomy, transcriptomics and biochemical analyses of Kusaghiporia usambarensis and Piptoporellus baudonii. Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology 1908. 56 pp. Uppsala: Acta Universitatis Upsaliensis. ISBN 978-91-513-0881-4. Polyporoid fungi refers to basidiomycetes with fruiting bodies with the hymenium located to the inner surfaces of pores or narrow tubes. The majority of polyporoids belongs to Polyporales. Most Polyporales are saprobes, but some are plant pathogens. The overall aim of this thesis was to study the taxonomy, systematics and chemistry of the two species Kusaghiporia usambarensis (saprobic) and Piptoporellus baudonii (a plant pathogen) collected from Tanzania, using morphological and molecular approaches, combined with transcriptomics and pharmacognostic investigations. The main contribution of this thesis includes the description a new genus with the new species K. usambarensis from the Usambara Mountains, Tanzania; investigation of the chemical composition of volatile compounds from this medicinal mushroom; isolation and structure determination of a novel and most abundant peptide in K. usambarensis, and further to elucidate the phylogenetic position of Piptoporellus baudonii (formerly known as Laetiporus baudonii) by using a four molecular markers dataset. Paper I was conducted applying a classical taxonomic approach, including both morphological and phylogenetic analyses, to describe a new genus and species K. usambarensis. Paper II, investigated volatiles and volatile derivatives in dichloromethane extracts of K. usambarensis analysed by GC-MS and NMR spectroscopy. The main elements were phenols, and esters, compounds that may explain the formerly reported antioxidant activity and traditional medicinal use of the mushroom. In paper III, screening of peptides in K. usambarensis revealed a novel cysteine-rich peptide, highly expressed at gene level and the most abundant compound in the fruiting body. Combined LC-MS and transcriptome analyses were used to determine the peptide sequence, and subsequently NMR spectroscopy to determine the 3D structure of the novel peptide, kusaghitide. In paper IV molecular techniques were used to elucidate the phylogenetic position of the parasitic Laetiporus baudonii. Phylogenetic analyses of combined 5.8S, nrLSU, nrSSU, and TEF1 gene sequences placed L. baudonii in the genus Piptoporellus, hence the new combination Piptoporellus baudonii was proposed. This thesis has contributed to build capacity in the fields of mycology, systematics and pharmacognosy in order to reinforce ecological knowledge and ethnopharmaceutical research for future drug discovery in Tanzania and Africa at large.
ICES: Data, Discovery, Better Health

ICES was founded in 1992 to study the health care system in Ontario and promote effective, efficient and equitable health care. Over 27 years later, the goal remains largely unchanged, though the institute has grown in size and impact. Originally known as the Institute for Clinical Evaluative Sciences, ICES was created as an independent not-for-profit research institute and given what was, at the time, unprecedented access to administrative health data records for the population of Ontario. ICES’ initial focus was to better understand the delivery of hospital services and translate its findings into better health care and policy. From modest beginnings with a handful of researchers located in a few hospital offices, ICES has grown to encompass a community of almost 500 scientists and staff across a network of seven physical sites in Ontario. The original focus on hospital-based services has expanded significantly and now includes research and analysis of community-based health services, health policy, Indigenous health, social determinants of health, and data science.