Miracle-dz/UniFAR-FTUs huggingface dataset:
Local oceanic CO2 outgassing triggered by terrestrial carbon fluxes during deglacial flooding

Abstract. Exchange of carbon between the ocean and the atmosphere is a key process that influences past climates via glacial–interglacial variations of the CO2 concentration. The melting of ice sheets during deglaciations induces a sea level rise which leads to the flooding of coastal land areas, resulting in the transfer of terrestrial organic matter to the ocean. However, the consequences of such fluxes on the ocean biogeochemical cycle and on the uptake and release of CO2 are poorly constrained. Moreover, this potentially important exchange of carbon at the land–sea interface is not represented in most Earth system models. We present here the implementation of terrestrial organic matter fluxes into the ocean at the transiently changing land–sea interface in the Max Planck Institute for Meteorology Earth System Model (MPI-ESM) and investigate their effect on the biogeochemistry during the last deglaciation. Our results show that during the deglaciation, most of the terrestrial organic matter inputs to the ocean occurs during Meltwater Pulse 1a (between 15–14 ka) which leads to the transfer of 21.2 Gt C of terrestrial carbon (mostly originating from wood and humus) to the ocean. Although this additional organic matter input is relatively small in comparison to the global ocean inventory (0.06 %) and thus does not have an impact on the global CO2 flux, the terrestrial organic matter fluxes initiate oceanic outgassing in regional hotspots like in Indonesia for a few hundred years. Finally, sensitivity experiments highlight that terrestrial organic matter fluxes are the drivers of oceanic outgassing in flooded coastal regions during Meltwater Pulse 1a. Furthermore, the magnitude of outgassing is rather insensitive to higher carbon-to-nutrient ratios of the terrestrial organic matter. Our results provide a first estimate of the importance of terrestrial organic matter fluxes in a transient deglaciation simulation. Moreover, our model development is an important step towards a fully coupled carbon cycle in an Earth system model applicable to simulations at glacial–interglacial cycles.
Goitered Gazelle’s (Gazella Subgutturosa) Habitat Desirability Modeling by Using Maximum Entropy (Maxent) Method

The models predicting the spatial distribution of species can simulate the suitability of species habitats on different spatial scales, based on species records and site characteristics to gain insight into ecological or evolutionary drivers or to help predict habitat suitability across large scales. Species distribution models (SDMs) based on presence-absence or presence-only data use widely in biogeography to characterize the ecological niche of species and to predict the geographical distribution of their habitat. Although presence-absence data is generally of higher quality, it is also less common than presence-only data because it requires more rigorous planning to visit a set of pre-determined sites. Among the algorithms available, one of the most widely used methods of developing SDMs is the Maximum Entropy (MaxEnt) method. The MaxEnt uses entropy to generalize specific observations of presence-only data and does not require or even incorporate points where the species is absent within the theoretical framework. The purpose of this study is to predict the suitable habitat for Goitered gazelle (Gazella subgutturosa) in the Samelghan plain in northeastern Iran. The results showed that the variables of the Mediterranean climate classes, slope 0-5% class and semi-dense pastures with type Acantholimon-Astragalus are more important than other environmental variables used in modeling. The area under curve (AUC), Receiver Operating Characteristic (ROC), and the classification threshold shows model performance. Based on the ROC (AUC=0.99) results in this study, it was found that Maxent’s performance was very good. Desirability habitat was classified based on the threshold value (0.0277) and the ROC, which approx 11% of the area, predicted suitable habitat for Goitered gazelle.
Phoenix and Hive as Alternatives to RDBMS

There are many small and medium businesses with mid sized data sets that would like to implement low budget data management systems that will perform well with their exisiting budget and scale as more data is accumulated. One solution is to choose one of the many high-performing and cost effective Big Data management systems such as Hive and Phoenix. Another option is to use parallel database management systems whick are high-peformance alternatives but are expensive and can be complicated to implement. The purpose of this project was to compare Hive and Phoenix with MySQL to see if either are viable alternatives to relational database management systems for realtime data retrieval. The case study involved two complex stored procedures given by a local company, iVinci Health, and three simulated data sets with sizes ranging from 864.08 MB to 3.83 GB. The stored procedures take user input, generate and execute a complex query and then return the results. A web application was created to simulate how the data will be accessed in the real application. The results show that for this case study, MySQL outperforms both Phoenix and Hive. However, Hive will outperform MySQL as the data sets increase significantly in size.
A randomised trial of the effects on recruitment and retention of including a wet-ink signature and photograph in the patient invitation letter for a clinical trial: results from a Study Within a Trial (SWAT 3 and SWAT 53)

Background: There is uncertainty about the effects of modifications to trial patient invitation letters on recruitment and retention. However, such documents are important. Methods: A 2x2 factorial design embedded a pair of randomised Studies Within a Trial (SWAT) within a large host trial (CLEAR), to evaluate the effects of including wet-ink signatures and photographs in the patient invitation letter. Patients were randomised to receive one of four invitation letters: with a wet-ink or generic signature, and with or without a photograph. The primary outcome was the proportion of invited patients who joined the CLEAR trial. The secondary outcome was the proportion of patients retained in the trial. Results: 368 letters were given to potential participants in the CLEAR trial and 121 (33%) joined. Proportions for each randomised group were generic signature and no photograph: 38% (33/88); generic signature and photograph: 32% (28/88); wet-ink personal signature and no photograph: 29% (26/91); wet-ink personal signature and photograph: 34% (34/101). There was no evidence of a significant difference in recruitment between those receiving the patient invitation letter containing a wet-ink versus generic signature (odds ratio (OR): 0.86, 95% confidence intervals (CI): 0.55 to 1.32, p=0.49) or photograph versus no photograph (OR: 0.99, 95% CI: 0.64 to 1.53, p=0.97). Retention was similar for the wet-ink and generic signature groups (OR: 1.20, 95% CI: 0.35 to 4.16, p=0.77) but significantly better when a photograph was used (OR: 5.40, 95% CI: 1.12 to 26.15, p=0.04, based on 2 withdrawals in the photograph group versus 9 in the no photograph group). Conclusions: These SWAT add to the evidence base for the effects of modifications to clinical trial documentation on recruitment and retention. We found including a photograph may improve retention. Although these analyses are underpowered, they will contribute to meta-analysis of similar comparisons. ISRCTN registration: 89040295 (06/07/2018)
All-Trans Retinoic Acid Attenuates Transmissible Gastroenteritis Virus-Induced Apoptosis in IPEC-J2 Cells via Inhibiting ROS-Mediated P38MAPK Signaling Pathway

Transmissible gastroenteritis virus (TGEV) can cause diarrhea, dehydration, and high mortality in piglets, which is closely related to intestinal epithelial cell apoptosis caused by TGEV infection. All-trans retinoic acid (ATRA) is the active metabolite of vitamin A, which has antioxidant and anti-apoptotic properties. However, it is unknown whether ATRA can attenuate TGEV-induced IPEC-J2 cells apoptosis. Therefore, we investigated the protective effects of ATRA on TGEV-induced apoptosis of IPEC-J2 cells and explored the potential molecular mechanism. Our results indicated that TGEV infection caused IPEC-J2 cells damage and apoptosis. However, ATRA treatment attenuated TGEV-induced IPEC-J2 cells damage by upregulating the mRNA expressions of ZO-1, Occludin, and Mucin-1. ATRA treatment also attenuated TGEV-induced apoptosis in IPEC-J2 cells by downregulating the expression of Caspase-3, which is related to the inhibition of death receptor (Fas and Caspase-8) and mitochondrial (Bax, Bcl-2, and Caspase-9) pathways. Moreover, ATRA treatment prevented TGEV-induced ROS and MDA production and the upregulation of P38MAPK phosphorylation level, which is related to the increase in the activities of antioxidant enzymes (SOD, CAT, and T-AOC) and the mRNA abundance of antioxidant-related genes (GPX1, GPX2, SOD1, CAT, GCLC, and GCLM). In addition, treatment of TGEV-infected IPEC-J2 cells with the ROS inhibitors (NAC) significantly reduced the protein levels of p-P38MAPK, Fas, Bax, and Cleaved-caspase-3 and the percentage of apoptotic cells. Our results indicated that ATRA attenuated TGEV-induced apoptosis in IPEC-J2 cells via improving the antioxidant capacity, thereby inhibiting the cell damage. the mechanism of which is associated with the inhibition of ROS-mediated P38MAPK signaling pathway.
Prediction of silicon content in hot metal based on EMD-SVM nonlinear combined model

In the blast furnace(BF) ironmaking process,the silicon content in hot metal which reflects the thermal state of BF is an important index.In order to predict the silicon content in hot metal effectively and level up the forecasting accuracy,a combined model based on Empirical Mode Decomposition(EMD) and Support Vector Machine(SVM) is proposed.Firstly,the time series data of silicon content in hot metal are decomposed into a series of stationary intrinsic mode functions(IMFs) in different scale space via the EMD sifting procedure.The local features of original time series data are prominent in the IMFs.Secondly,based on the analysis of Lemple-Ziv complexity and 10-fold cross validation,the right kernel functions and their parameters are chosen to build different SVMs respectively to predict each IMF.Finally,the predicted results of all IMFs are reconstructed to obtain the final predicted result.The result shows that the prediction is successful and the hit rate increased to 90%.
Population Genomics, Transcriptional Response to Heat Shock, and Gut Microbiota of the Hong Kong Oyster Magallana hongkongensis

The Hong Kong oyster Magallana hongkongensis, previously known as Crassostrea hongkongensis, is a true oyster species native to the estuarine-coast of the Pearl River Delta in southern China. The species—with scientific, ecological, cultural, and nutritional importance—has been farmed for hundreds of years. However, there is only limited information on its genetics, stress adaptation mechanisms, and gut microbiota, restricting the sustainable production and use of oyster resources. Here, we present population structure analysis on M. hongkongensis oysters collected from Deep Bay and Lantau Island in Hong Kong, as well as transcriptome analysis on heat shock responses and the gut microbiota profile of M. hongkongensis oysters collected from Deep Bay. Single nucleotide polymorphisms (SNPs), including those on the homeobox genes and heat shock protein genes, were revealed by the whole genome resequencing. Transcriptomes of oysters incubated at 25 °C and 32 °C for 24 h were sequenced which revealed the heat-induced regulation of heat shock protein pathway genes. Furthermore, the gut microbe community was detected by 16S rRNA sequencing which identified Cyanobacteria, Proteobacteria and Spirochaetes as the most abundant phyla. This study reveals the molecular basis for the adaptation of the oyster M. hongkongensis to environmental conditions.
Understanding Virtual Gifting in Live Streaming by the Theory of Planned Behavior

Based on the theory of planned behavior (TPB), the current study developed a model to understand motivations and predictors of viewers’ virtual gifting behaviors in online live streaming. The model was tested with data from 392 live streaming viewers with previous virtual gifting experiences. The results showed that perceived pleasure, interaction with streamers, group interactions, and support for streamers can predict individual attitudes toward virtual gifting. Subjective norms learned from family and friends as well as streamers and viewers in live streaming could significantly affect virtual gifting intention. Quality of streams, the attractiveness of the streamers, and viewers’ monetary resources influenced perceived ease of virtual gifting. Overall, the proposed model predicted virtual gifting behavior well. Findings were discussed in terms of the links between online and offline subjective norms along with the relationship of perceived behavior control, virtual gifting intention, and virtual gifting behavior. We suggest that the adjusted TPB model with subjective norms both offline and online can fit the online interaction contexts well and explain online norms development. Furthermore, our model reflects how social incentive contributes to virtual gifting. These findings offer insights into the motivations of virtual gifting behavior and provide implications for virtual gifting experience design.
Effects of Real Exchange Rate Volatility on Trade: Empirical Analysis of the United States Exports to BRICS

This paper analyzes the effects of real exchange rate volatility on the United States’ exports to BRICS. It focuses on the top 20 export products (defined by the 2-digit Harmonized System codes) from the United States to Brazil, Russia, India, China, and South Africa, and uses quarterly data for period from 1993Q1 to 2021Q2. The specified panel regression model was first estimated using three estimation methods, namely, the Panel Least Squares, the Panel Fully Modified Least Squares (FMOLS), and Panel Dynamic Least Squares (DOLS). In addition, to estimate the short-run and long-run effects of real exchange rate volatility on exports, it also uses the method of the Autoregressive Distributed Lag (ARDL) approach to cointegration analysis and error-correction models. Two measures of exchange rate volatility are used in this study. According to our findings, the levels of foreign economic activity have a positive effect on exports while the real exchange rate has a negative effect on exports. In addition, exchange rate volatility has a negative effect on exports in the long run in all five countries. However, the effects of exchange volatility are found to yield mixed results in the short run regardless of which measure of exchange rate volatility was used.
Tocotrienol in Pre-Eclampsia Prevention: A Mechanistic Analysis in Relation to the Pathophysiological Framework

The pathophysiology of pre-eclampsia involves two major pathways, namely systemic oxidative stress and subsequent generalised inflammatory response, which eventually culminates in endothelial cell injury and the syndrome of pre-eclampsia with multi-organ dysfunction. Aspirin has been used to reduce the risk of pre-eclampsia, but it only possesses anti-inflammatory properties without any antioxidant effect. Hence, it can only partially alleviate the problem. Tocotrienols are a unique form of vitamin E with strong antioxidant and anti-inflammatory properties that can be exploited as a preventive agent for pre-eclampsia. Many preclinical models showed that tocotrienol can also prevent hypertension and ischaemic/reperfusion injury, which are the two main features in pre-eclampsia. This review explores the mechanism of action of tocotrienol in relation to the pathophysiology of pre-eclampsia. In conclusion, the study provides sufficient justification for the establishment of a large clinical trial to thoroughly assess the capability of tocotrienol in preventing pre-eclampsia.
Online Stochastic Principal Component Analysis

This paper studied Principal Component Analysis (PCA) in an online. The problem is posed as a subspace optimization problem and solved using gradient based algorithms. One such algorithm is the Variance-Reduced PCA (VR-PCA). The VR-PCA was designed as an improvement to the classical online PCA algorithm known as the Oja’s method where it only handled one sample at a time. The paper developed Block VR-PCA as an improved version of VR-PCA. Unlike prominent VR-PCA, the Block VR-PCA was designed to handle more than one dimension in subspace optimization at a time and it showed good performance. The Block VR-PCA and Block Oja method were compared experimentally in MATLAB using synthetic and real data sets, their convergence results showed Block VR-PCA method appeared to achieve a minimum steady state error than Block Oja method. Keywords: Online Stochastic; Principal Component Analysis; Block Variance-Reduced; Block Oja
Introduction

Marigold plant growth and orientation were improved by adding gibberellic acid (25, 50 and 100 mgL) and β-sitosterol (20, 40 and 80 mgL) as well as their interaction treatments. GA3 (25 mgL) was more effective on number of branches, fresh and dry weight of shoots and roots/plant. While, GA3 (100 mgL) significantly increased plant height. Leaf angle was more decreased with GA3 than β-sitosterol application. Both GA3 (100 mgL) or β-sitosterol (40 mgL) significantly induced flowering earliness and number of marigold plant inflorescences. While low concentration of both substances improved the other characters of inflorescences. GA3 (100 mgL) and βsitosterol (40 mgL) interaction significantly increased earliness, number and stalk length of marigold plant inflorescences. Pigments (Chl.a & b and carotenoids) and biochemical constituents (total sugars, indoles and free amino acids) were significantly enhanced with GA3 (25 mgL ) and / or β-sitosterol (20 or 40 mgL) as foliar application. However, both the highest concentration of two bioregulators gave the highest phenolic content of marigold plant leaves. Additionally, GA3 (25 mgL) and β-sitosterol (40 mgL) interaction was more effective on leaves biochemical contents (Chl.a, carotenoids, total sugars, indols and free amino acids). Phenolic content was permanent increased with the highest concentration of both growth substances. GA3 and β-sitosterol appeared positive correlation between fresh weight of inflorescences and Chl. (a+b). All the results were significantly negative attributed with phenolic content of marigold plant leaves.
A Cascade Attention Based Facial Expression Recognition Network by Fusing Multi-Scale Spatio-Temporal Features

The performance of a facial expression recognition network degrades obviously under situations of uneven illumination or partial occluded face as it is quite difficult to pinpoint the attention hotspots on the dynamically changing regions (e.g., eyes, nose, and mouth) as precisely as possible. To address the above issue, by a hybrid of the attention mechanism and pyramid feature, this paper proposes a cascade attention-based facial expression recognition network on the basis of a combination of (i) local spatial feature, (ii) multi-scale-stereoscopic spatial context feature (extracted from the 3-scale pyramid feature), and (iii) temporal feature. Experiments on the CK+, Oulu-CASIA, and RAF-DB datasets obtained recognition accuracy rates of 99.23%, 89.29%, and 86.80%, respectively. It demonstrates that the proposed method outperforms the state-of-the-art methods in both the experimental and natural environment.
A pair of isoleucyl-tRNA synthetases in Bacilli fulfill complementary roles to keep fast translation and provide antibiotic resistance

Isoleucyl-tRNA synthetase (IleRS) is an essential enzyme that covalently couples isoleucine to the corresponding tRNA. Bacterial IleRSs group in two clades, ileS1 and ileS2, the latter bringing resistance to the natural antibiotic mupirocin. Generally, bacteria rely on either ileS1 or ileS2 as a standalone housekeeping gene. However, we have found an exception by noticing that Bacillus species with genomic ileS2 consistently also keep ileS1, which appears mandatory in the family Bacillaceae. Taking Priestia (Bacillus) megaterium as a model organism, we showed that PmIleRS1 is constitutively expressed, while PmIleRS2 is stress-induced. Both enzymes share the same level of the aminoacylation accuracy. Yet, PmIleRS1 exhibited a twofold faster aminoacylation turnover (kcat) than PmIleRS2 and permitted a notably faster cell-free translation. At the same time, PmIleRS2 displayed a 104-fold increase in its Ki for mupirocin, arguing that the aminoacylation turnover in IleRS2 could have been traded-off for antibiotic resistance. As expected, a P. megaterium strain deleted for ileS2 was mupirocin-sensitive. Interestingly, an attempt to construct a mupirocin-resistant strain lacking ileS1, a solution not found among species of the family Bacillaceae in nature, led to a viable but compromised strain. Our data suggests that PmIleRS1 is kept to promote fast translation, whereas PmIleRS2 is maintained to provide antibiotic resistance when needed. This is consistent with an emerging picture in which fast-growing organisms predominantly use IleRS1 for competitive survival.
Role of Autonomous Neuropathy in Diabetic Bone Regeneration

Diabetes mellitus has multiple negative effects on regenerative processes, especially on wound and fracture healing. Despite the well-known negative effects of diabetes on the autonomous nervous system, only little is known about the role in bone regeneration within this context. Subsequently, we investigated diabetic bone regeneration in db−/db− mice with a special emphasis on the sympathetic nervous system of the bone in a monocortical tibia defect model. Moreover, the effect of pharmacological sympathectomy via administration of 6-OHDA was evaluated in C57Bl6 wildtype mice. Diabetic animals as well as wildtype mice received a treatment of BRL37344, a β3-adrenergic agonist. Bones of animals were examined via µCT, aniline-blue and Masson–Goldner staining for new bone formation, TRAP staining for bone turnover and immunoflourescence staining against tyrosinhydroxylase and stromal cell-derived factor 1 (SDF-1). Sympathectomized wildtype mice showed a significantly decreased bone regeneration, just comparable to db−/db− mice. New bone formation of BRL37344 treated db−/db− and sympathectomized wildtype mice was markedly improved in histology and µCT. Immunoflourescence stainings revealed significantly increased SDF-1 due to BRL37344 treatment in diabetic animals and sympathectomized wildtypes. This study depicts the important role of the sympathetic nervous system for bone regenerative processes using the clinical example of diabetes mellitus type 2. In order to improve and gain further insights into diabetic fracture healing, β3-agonist BRL37344 proved to be a potent treatment option, restoring impaired diabetic bone regeneration.