Miracle-dz/UniFAR-FTUs huggingface dataset:
Molecular Mechanisms and Biomarkers of Skin Photocarcinogenesis

Skin cancer is the most commonly diagnosed malignancy in the United States and world- wide. While melanoma is the deadliest form of skin cancer, non-melanoma skin cancers, which include basal cell carcinoma and squamous cell carcinoma, are responsible for significant morbidity in millions of Americans each year. While numerous attempts have been made to reduce skin cancer risk factors related to ultraviolet radiation expo- sure, skin cancer incidence continues to rise. Improved understanding of the molecular pathways underlying skin cancer pathogenesis has led to the investigation of new approaches to skin cancer prevention. In particular, the search for ultraviolet radiation associated biomarkers of skin cancer has become a rapidly expanding and promising area of research. Advances in genetic sequencing have facilitated the discovery of novel biomarkers, which have the potential to profoundly improve patient care. Here we will review the molecular genetics of skin cancer and analyze the existing literature of pro-posed biomarkers for potential use in skin cancer diagnosis and prevention.
Synergistic Effect of Temperature and Pressure on Cement Compressive Strength

One of the challenges during oil well cementing operation is the ability to predict the compressive strength of cement. Database reports are sometimes recommended when there is insufficient time for testing prior to the execution of cementing jobs. Previous studies on the compressive strength of cement have been carried out to show the effect of temperature at a single point of pressure without considering the effect of changes on the pressure profile. At the moment, no comprehensive study has been done to demonstrate the combined effect of temperature and pressure on compressive strength of cement. Compressive strength tests are conducted in the cementing laboratory using the bottom hole static temperature (BHST) and the cumulative hydrostatic pressure of the fluids in the well at the well depth. However, since temperature and pressure increases with increasing depth of the well, it is important to understand the combined effect of these varying parameters on the compressive strength of cement in the annular space between the casing and the formation. Compressive strength tests were conducted at 80 o F and 120 o F while varying bottom hole pressures between 0psi and 20,000psi using neat cement slurry. A model was developed using the multiple regression method. The model was developed to show the relationship between compressive strength and temperature and pressure. The model can also be used to predict the compressive strength of cement with changes in temperature and pressure. Results also show that compressive strength of cement slurry increases as temperature and pressure increases. Test results indicate that changes in temperature and pressure significantly affect the compressive strength. Keywords-Temperature, Pressure, Compressive Strength, Cement
Graph embedding code prediction model integrating semantic features

With the advent of Big Code, code prediction has received widespread attention. However, the state-of-the-art code prediction techniques are inadequate in terms of accuracy, interpretability and efficiency. Therefore, in this paper, we propose a graph embedding model that integrates code semantic features. The model extracts the structural paths between the nodes in source code file? s Abstract Syntax Tree(AST). Then, we convert paths into training graph and extracted interdependent semantic structural features from the context of AST. Semantic structure features can filter predicted candidate values and effectively solve the problem of Out-of- Word(OoV). The graph embedding model converts the structural features of nodes into vectors which facilitates quantitative calculations. Finally, the vector similarity of the nodes is used to complete the prediction tasks of TYPE and VALUE. Experimental results show that compared with the existing state-of-the-art method, our method has higher prediction accuracy and less time consumption.
How can I thank you? Highlighting the benefactor’s responsiveness or costs when expressing gratitude

Despite growing evidence that showing gratitude plays a powerful role in building social connections, little is known about how to best express gratitude to maximize its relational benefits. In this research, we examined how two key ways of expressing gratitude—conveying that the benefactor’s kind action met one’s needs (responsiveness-highlighting) and acknowledging how costly the action was (cost-highlighting)—impact benefactors’ reactions to the gratitude and feelings about their relationship. Using observer ratings of gratitude expressions during couples’ live interactions (N = 111 couples), and benefactors’ self-reports across a 14-day experience sampling study (N = 463 daily reports), we found that responsiveness-highlighting was associated with benefactors’ positive feelings about the gratitude expression and the relationship. In contrast, cost-highlighting had no such effect. These findings suggest that expressing gratitude in a way that highlights how responsive benefactors were may be critical to reaping the relational benefits of gratitude and have practical implications for improving couples’ well-being.
Leaf Trait Plasticity Alters Competitive Ability and Functioning of Simulated Tropical Trees in Response to Elevated Carbon Dioxide

The response of tropical ecosystems to elevated carbon dioxide (CO2) remains a critical uncertainty in projections of future climate. Here, we investigate how leaf trait plasticity in response to elevated CO2 alters projections of tropical forest competitive dynamics and functioning. We use vegetation demographic model simulations to quantify how plasticity in leaf mass per area and leaf carbon to nitrogen ratio alter the responses of carbon uptake, evapotranspiration, and competitive ability to a doubling of CO2 in a tropical forest. Observationally constrained leaf trait plasticity in response to CO2 fertilization reduces the degree to which tropical tree carbon uptake is affected by a doubling of CO2 (up to −14.7% as compared to a case with no plasticity; 95% confidence interval [CI95%] −14.4 to −15.0). It also diminishes evapotranspiration (up to −7.0%, CI95% −6.4 to −7.7), and lowers competitive ability in comparison to a tree with no plasticity. Consideration of leaf trait plasticity to elevated CO2 lowers tropical ecosystem carbon uptake and evapotranspirative cooling in the absence of changes in plant‐type abundance. However, “plastic” responses to high CO2 which maintain higher levels of plant productivity, many of which fall outside of the observed range of response, are potentially more competitively advantageous, thus, including changes in plant type abundance may mitigate these decreases in ecosystem functioning. Models that explicitly represent competition between plants with alternative leaf trait plasticity in response to elevated CO2 are needed to capture these influences on tropical forest functioning and large‐scale climate.
In ovo supplementation of Primalac and the effects on performance and immune response of broilers

Probiotics are live nonpathogenic microorganisms capable of positively impacting the host by improving the natural gut microbial balance and promoting animal health. In ovo technology represents one means to administer probiotics and promote early colonization of beneficial bacteria for stimulating intestinal and immune system development, and warding off enteric threats. Three studies were conducted to evaluate the effects of in ovo administration of Primalac in broilers. The objective of the first study was to determine the effects of administering probiotics in ovo on hatchability, post-hatch performance and expression of immune-related genes in the ileum and cecal tonsils. On embryonic day 18, 360 eggs were injected with water, 1x10, 1x10, or 1x10 probiotic bacteria. Another 90 eggs remained uninjected as a negative control group. Measurements and tissue samples were taken on day of hatch (DOH) and days (d) 4, 6, 8, 15, and 22. A subsequent study was conducted to evaluate the effects of administering Primalac in ovo and in the diet on broiler chick hatchability, post-hatch performance, immune organ weights and ileal immune-related gene expression. At embryonic day 18, 1977 eggs were either not injected (negative control), dry-punched, or injected with 1x10 or 1x10 probiotic bacteria. Performance parameters were measured on DOH and d4, 6, 8, 14, 19, and 42, while immune organ weights and tissue samples were taken on DOH and d4, 6, 8, 14, and 20. A third study investigated the effects of in ovo administration of Primalac on hatchability, performance, immune organ weights, and lesion scores in broiler chicks exposed to Eimeria sp. At embryonic day 18, 210 eggs were injected with either sterile water or 1x10 probiotic bacteria. On d3 post-hatch, half of the chicks from each treatment group were challenged with a mixed inoculum of Eimeria acervulina, E. maxima, and E. tenella. Measurements and tissue samples were taken on DOH and d3, 9 and 15. The results of these studies suggest that in ovo Primalac supplementation does not negatively impact hatchability, enhances performance, modulates intestinal gene expression, and provides protection against a mixed Eimeria infection.
The Influence of Accounting Knowledge and Entrepreneurial Personality on Managerial Performance (Empirical Study on Customers of Bank Aceh, operational Headquarters, Banda Aceh, Indonesia )

This study aims to test; (1) the influence of accounting knowledge and entrepreneurial personality simultaneously on the managerial performance of Bank Aceh's customers, (2) the influence of accounting knowledge on the managerial performance of Bank Aceh's customers, and (3) the influence of entrepreneurial personality on the managerial performance of Bank Aceh's customers. The unit of analysis in this study was Bank Aceh at Operational Head Office. Furthermore, the unit of observation (respondents) in this study is Bank Aceh customers who have a position as manager on owned business. Sources of research data using primary data sources derived from the acquisition of research questionnaires. While the data collection technique in this research is done by the technique of spreading the questionnaire. The method of analysis used in this research is Multiple Linear Regression Analysis. The result of the research shows that (1) knowledge of accounting and entrepreneurial personality together influence to managerial performance of Bank of Aceh customer, (2) accounting knowledge has positive influence but not significant to managerial performance of Bank of Aceh customer, and (3) entrepreneurial personality has positive influence and significant to managerial performance of Bank Aceh.
ELECTRICITY CONSUMPTION AND CAPACITY UTILIZATION IN NIGERIA

The study investigated the effects of electricity consumption on capacity utilization in Nigeria from 1981 to 2017. The study made use of annual time series data which were sourced from Central Bank of Nigeria (CBN) Statistical Bulletin (2018) and World Development Indicators (WDI). Unit root test of Augmented Dickey-fuller (ADF) and Philip Perron (PP) were used for preliminary test with Johansen co-integration test. The study employed Normalized co-integration and vector error correction mechanism in analyzing the data. The unit root results indicated that all variables were stationary at differenced of order I(1), while co-integration established a long run relationship among the variables. The normalized co-integration finding revealed that lnelec, lncabem and lnelecge have positive impact on the lncpu while lncrind and lnecp have negative impact on lncpu, on average. The coefficients of lnelec, lnecp and lnelecge were statistically significant at 5% and 1% levels of significance. Vector error correction mechanism technique showed that a unit rises in inelec, incabem and inelecge decreases incpu by 0.96%, 0.20% and 0.55% respectively on average in the long run while a percentage change in inelec, incabem and inelecge decreases lncpu by 0.186, 0.020 and 0.125% respectively on average, ceteris paribus in the short run. Therefore, the study recommended policies aimed at providing reliable and stable power supply thereby creating avenue for maximum capacity utilization in Nigeria industries.
Comparison of Taxon‐Specific and Taxon‐Generic Risk Screening Tools to Identify Potentially Invasive Non‐native Fishes in the River Neretva Catchment (Bosnia and Herzegovina and Croatia)

The Freshwater Fish Invasiveness Screening Kit (FISK) v2 and Aquatic Species Invasiveness Screening Kit (AS‐ISK) risk identification screening tools were used to assess the invasiveness potential of 24 non‐native (NNS) freshwater fish species in the River Neretva catchment (Bosnia and Herzegovina and Croatia), a risk assessment (RA) area that is an important Mediterranean hotspot for fish endemism. The two assessors assigned similar scores for the invasiveness potential of the NN fishes, and both screening tools successfully distinguished invasive from non‐invasive species. Mean calibrated threshold scores were 10.25 for FISK and 10.00 for AS‐ISK, with the latter increasing to 12.62 when questions that assess the likely impact of predicted future climate conditions on the RA were taken into consideration. These relatively low threshold values are characteristic of areas with an elevated number of translocated species and suggest that NN fishes pose a considerable threat to native species and ecosystems. FISK ranked 50.0–62.6% of the species as being of ‘high risk’ compared with 58.4–59.3% using AS‐ISK. The highest scores (‘very high risk’) were attributed to gibel carp Carassius gibelio (Bloch, 1782) and pikeperch Sander lucioperca (Linnaeus, 1758). The generic screening tool for aquatic species (AS‐ISK) provided similar risk rankings to its predecessor, FISK, as regards invasiveness potential. For this reason, it is likely to be an effective tool for evaluating the potential invasion risk of NNS freshwater fishes for other RA areas in the Balkans. Copyright © 2017 John Wiley & Sons, Ltd.
Response to Interactive comment on “Aerosol–radiation–cloud interactions in a regional coupled model: the effects of convective parameterisation and resolution” by S. Archer-Nicholls et al. Anonymous Referee #1

While the paper does bring up some valid points regarding how to interpret aerosol-radiation-cloud interactions predicted by models such as WRF-Chem, I am not sure what new information is obtained from this model sensitivity exercise. Not enough context is presented regarding the present results and those published previously. Therefore, I do not think the up-front purpose and conclusions derived from this study have not been articulated well enough.
PHOSPHATE SOLUBILIZATION CAPACITY AND INDOLE ACETIC ACID PRODUCTION BY Trichoderma STRAINS FOR BIOMASS INCREASE ON BASIL AND MINT PLANTS

The use of microorganisms in medicinal plants may provide an increase in biomass. The objective of this work was to evaluate the efficiency and capacity of Trichoderma strains to solubilize phosphate and to synthesize indole acetic acid (IAA) in vitro in the biomass production of two medicinal plants, basil and mint. Cultures were inoculated with two species of Trichoderma . The crop biomass as well as the relative efficiency were determined. Trichoderma species that solubilized phosphate and produced IAA, provided significant results in the accumulation of biomass of the crops, with relative efficiency of 276% for mint and 141% for basil, in relation to the control. The Trichoderma isolates showed phosphate solubilization capacity and IAA synthesis. Therefore, the studied crops presented biomass increase. These strains verified their capacity as plant growth promoters.
The influence of startReact on long-latency reflexive muscle activation during the transition from posture to movement

Many motor tasks involve transitions from posture to movement such as shifting from holding an object to setting it on a surface. Although many movements are voluntary processes, they are facilitated through motor pathways that span the continuum between reflexive and voluntary control. The mechanisms driving the long-latency stretch reflex (LLSR) have remained hotly contested. Recently, startReact has been shown to influence the fast muscular response to perturbations (Ravichandran et. al. 2013). The objective of this study was to evaluate how the LLSR and startReact impact the muscular response during the transition from posture to movement. We hypothesized that both the LLSR and startReact would be involved throughout the transition from posture to movement; however there would be a clear transition from LLSR dominance during posture to startReact dominance near/during movement. We tested this hypothesis using perturbations of elbow posture at various times before a fast ballistic extension movement. We found clear evidence that both the LLSR and startReact components were influenced changes in the late long-latency time window. The results provide insights on how the nervous system regulates involuntary responses to perturbations during the transition from maintenance of arm posture to movement. New and Noteworthy We recently demonstrated that the startReact effect, the startled release of a planned movement, can influence the muscular response during the LLSR. Here we observe how the influence of startReact can change from the transition from posture (no/little influence) to movement (strong influence). While not all paradigms trigger a startReact effect, this work demonstrates that when present startRect can have a profound effect on the overall muscle activity - even obscuring the traditional LLSR response.
Generalization bounds for deep thresholding networks

We consider compressive sensing in the scenario where the sparsity basis (dictionary) is not known in advance, but needs to be learned from examples. Motivated by the well-known iterative soft thresholding algorithm for the reconstruction, we define deep networks parametrized by the dictionary, which we call deep thresholding networks. Based on training samples, we aim at learning the optimal sparsifying dictionary and thereby the optimal network that reconstructs signals from their low-dimensional linear measurements. The dictionary learning is performed via minimizing the empirical risk. We derive generalization bounds by analyzing the Rademacher complexity of hypothesis classes consisting of such deep networks. We obtain estimates of the sample complexity that depend only linearly on the dimensions and on the depth.
Using landscape preference models and tree-scale measurements to predict stand quality

ABSTRACT Scenic beauty estimation (SBE) models that quantify landscape aesthetics through picture-based questionnaires are complicated to develop. Therefore, precise, simple, and widely applicable models of SBE prediction based on tree and stand measurements must be developed. To investigate the application of tree- and stand-based SBE models to Chinese fir forest management, the relationships between diameter at breast height (DBH) and tree height (H) measurements and tree- (TSBE) and stand (SSBE)-based SBE predictions were assessed. TSBE and SSBE were strongly influenced by DBH and H measurements according to either a power function or linear function, depending on the variables. When the mean stand DBH was less than 8.4 cm or H was less than 9.8 m, dense canopies resulted in negative SSBE residuals. In stands with large trees and non-dense canopies, the residuals of SSBE were positive. We conclude that average H and DBH measurements within a stand can be used to predict SSBE by extrapolating the tree-based SBE model to form a stand-based SBE model. Therefore, SBE models based on individual tree measurements can provide quantitative guidance for forest landscape quality planning and evaluation.
RNA oligomers as microRNA production process regulators

The present invention relates to an RNA oligomer, methods for regulating’a microRNA (miRNA) production process and RNA oligomers used as miRNA production process regulators. More precisely, the present invention relates to use of RNA oligomers disrupting a pre-miRNA structure as miRNA production process regulators. Oligomer interactions with a miRNA precursor (pre-miRNA) change the precursor’s secondary and tertiary structure. In consequence, the pre-miRNA is not specifically recognised and cleaved by the Dicer ribonuclease, and the specific miRNA is not produced
Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search

One-shot weight sharing methods have recently drawn great attention in neural architecture search due to high efficiency and competitive performance. However, weight sharing across models has an inherent deficiency, i.e., insufficient training of subnetworks in hypernetworks. To alleviate this problem, we present a simple yet effective architecture distillation method. The central idea is that subnetworks can learn collaboratively and teach each other throughout the training process, aiming to boost the convergence of individual models. We introduce the concept of prioritized path, which refers to the architecture candidates exhibiting superior performance during training. Distilling knowledge from the prioritized paths is able to boost the training of subnetworks. Since the prioritized paths are changed on the fly depending on their performance and complexity, the final obtained paths are the cream of the crop. We directly select the most promising one from the prioritized paths as the final architecture, without using other complex search methods, such as reinforcement learning or evolution algorithms. The experiments on ImageNet verify such path distillation method can improve the convergence ratio and performance of the hypernetwork, as well as boosting the training of subnetworks. The discovered architectures achieve superior performance compared to the recent MobileNetV3 and EfficientNet families under aligned settings. Moreover, the experiments on object detection and more challenging search space show the generality and robustness of the proposed method. Code and models are available at https://github.com/microsoft/cream.git.
Initial $L^2\times\cdots\times L^2 $ bounds for multilinear operators.

The $L^p$ boundedness theory of convolution operators is \linebreak based on an initial $L^2\to L^2$ estimate derived from the Fourier transform. The corresponding theory of multilinear operators lacks such a simple initial estimate in view of the unavailability of Plancherel's identity in this setting, and up to now it has not been clear what a natural initial estimate might be. In this work we achieve exactly this goal, i.e., obtain an initial $L^2\times\cdots\times L^2\to L^{2/m}$ estimate for general building blocks of $m$-linear multiplier operators. We apply this result to deduce analogous bounds for multilinear rough singular integrals, multipliers of H\"ormander type, and multipliers whose derivatives satisfy qualitative estimates.