Miracle-dz/UniFAR-FTUs huggingface dataset:
The number of tree species on Earth

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and ﬁ nancial challenges and taxonomic dif ﬁ culties connected to the species concept de ﬁ nition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ∼ 73,000 tree species globally, among which ∼ 9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These ﬁ ndings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness.
Modulation of body fluids and angiotensin II receptors in a rat model of intra‐uterine growth restriction

We previously reported that sodium restriction during pregnancy reduces plasma volume expansion and promotes intra‐uterine growth restriction (IUGR) in rats while it activates the renin–angiotensin–aldosterone system (RAAS). In the present study, we proceeded to determine whether expression of the two angiotensin II (ANGII) receptor subtypes (AT1 and AT2) change in relation to maternal water–electrolyte homeostasis and fetal growth. To this end, pregnant (gestation day 15) and non‐pregnant Sprague‐Dawley rats were randomly assigned to two groups fed either normal, or Na+‐restricted diets for 7 days. At the end of the treatment period, plasma aldosterone and renin activity as well as plasma and urine electrolytes were measured. Determinations for AT1 and AT2 mRNA and protein were made by RNase protection assay and photoaffinity labelling, respectively, using a number of tissues implicated in volume regulation and fetal growth. In non‐pregnant rats, Na+ restriction decreases Na+ excretion without altering plasma volume, plasma Na+ concentration or the expression of AT1 and AT2 mRNA or protein in the tissues examined. In normally fed pregnant rats when compared to non‐pregnant controls, AT1 mRNA increases in the hypothalamus as well as pituitary and declines in uterine arteries, while AT1 protein decreases in the kidney and AT2 mRNA declines in the adrenal cortex. In pregnant rats, Na+ restriction induces a decrease in plasma Na+, an increase in plasma urea, as well as a decline in renal urea and creatinine clearance rates. Protein levels for both AT1 and AT2 in the pituitary and AT2 mRNA in the adrenal cortex are lower in the Na+‐restricted pregnant group when compared to normally fed pregnant animals. Na+ restriction also induces a decrease in AT1 protein in the placenta. In conclusion, these results suggest that pregnancy may increase sensitivity to Na+ depletion by the tissue‐specific modulation of ANGII receptors. Finally, these receptors may be implicated in the IUGR response to low Na+.
GPS-IPW observations and their assimilation into the 20-km RUC during severe weather season

Analyzing the rapidly evolving moisture field is an essential component of severe weather forecasting. GPS integrated precipitable water (GPS-IPW) observations are a new and important asynoptic data source of moisture information for data assimilation. Even in relatively observation-rich areas such as the United States, short-range numerical weather forecasts suffer from inadequate definition of the initial 3-D moisture field due to the high spatial and temporal variability of this field. Generally, there have been three observational sources for atmospheric moisture: rawinsondes, METARs, and satellite (not available in cloudy areas below cloud top). Estimates of IPW from GPS signal time delays can complement these moisture observations. GPS-IPW using zenith total delay provides only a vertically integrated value, by definition, but with at least hourly resolution and in all weather conditions, including those with cloud and even precipitation, conditions when observations are most important for forecasts of the atmospheric moisture. The NOAA Forecast Systems Laboratory has developed, over the past several years, a GPS-IPW network, which now produces high-accuracy, half-hourly, near-real-time measurements at more than 275 stations in the U.S. as of July 2004 (Fig. 1, Gutman et al. 2003).
Dynamic Deformation of Uniform Elastic Two-Layer Objects

This thesis presents a two-layer uniform facet elastic object for real-time simulation based on physics modeling method. It describes the elastic object procedural modeling algorithm with particle system from the simplest one-dimensional object, to more complex two-dimensional and three-dimensional objects. The double-layered elastic object consists of inner and outer elastic mass spring surfaces and compressible internal pressure. The density of the inner layer can be set different from the density of the outer layer; the motion of the inner layer can be opposite to the motion of the outer layer. These special features, which cannot be achieved by a single layered object, result in improved imitation of a soft body, such as tissue's liquidity non-uniform deformation. The construction of the double-layered elastic object is closer to the real tissue's physical structure. The inertial behavior of the elastic object is well illustrated in environments with gravity and collisions with walls, ceiling, and floor. The collision detection is defined by elastic collision penalty method and the motion of the object is guided by the Ordinary Differential Equation computation. Users can interact with the modeled objects, deform them, and observe the response to their action in real time.
An End-to-End Security Auditing Approach for Service Oriented Architectures

Service-Oriented Architecture (SOA) is becoming a major paradigm for distributed application development in the recent explosion of Internet services and cloud computing. However, SOA introduces new security challenges not present in the single-hop client-server architectures due to the involvement of multiple service providers in a service request. The interactions of independent service domains in SOA could violate service policies or SLAs. In addition, users in SOA systems have no control on what happens in the chain of service invocations. Although the establishment of trust across all involved partners is required as a prerequisite to ensure secure interactions, still a new end-to-end security auditing mechanism is needed to verify the actual service invocations and its conformance to the expected service orchestration. In this paper, we provide an efficient solution for end-to-end security auditing in SOA. The proposed security architecture introduces two new components called taint analysis and trust broker in addition to taking advantages of WS-Security and WS-Trust standards. The interaction of these components maintains session auditing and dynamic trust among services. This solution is transparent to the services, which allows auditing of legacy services without modification. Moreover, we have implemented a prototype of the proposed approach and verified its effectiveness in a LAN setting and the Amazon EC2 cloud computing infrastructure.
Proceedings of the Annual Meeting of the Cognitive Science Society

Child-directed language is a unique multimodal communication behaviour that differs from adult-directed language. We investigated how broadcasters organize their multimodal language production on an adult and child-directed programme to better understand the recipient design in the broadcasting context. Thirty-six future broadcasters produced live programmes for children and adults, respectively, whose linguistic features (utterance=3888), speech prosody, and gestures (N=8486) were analysed as a function of programme. We found that broadcasters used a higher mean pitch but a smaller pitch range, shorter utterances, high(er) frequency words, more questions, pointing and representational gestures but fewer pragmatic gestures in child-directed broadcasting. Gestures were also more salient and slower when addressing children audiences. However, there were no differences in lexical diversity, speaking rate, pausing, or beat gestures between programmes. In conclusion, broadcasters did engage in recipient design multimodally, but the distinction between the speaker and audience orientation is not binary but should be understood across signal channels according to contexts.
Contribution of ATM and FOXE1 (TTF2) to risk of papillary thyroid carcinoma in Belarusian children exposed to radiation

A dramatic increase in the incidence of papillary thyroid carcinoma (PTC) after childhood exposure to ionizing radiation from the Chernobyl nuclear accident has been described as the largest number of tumors of one type due to one cause that have ever occurred. inter‐individual variations in response to radiation have been documented and the role of genetics in sporadic PTC is well established, suggesting that genetic factors may also affect the risk of radiation‐related PTC. To investigate how environmental and host factors interplay to modify PTC risk, we genotyped 83 cases and 324 matched controls sampled from children living in the area contaminated by fallout from the Chernobyl power plant accident for 19 polymorphisms previously associated with PTC, thyroid biology or radiation‐induced second primary tumors. Significant association with PTC was found for rs1801516 (D1853N) in ATM (odds ratio (OR) = 0.34, 95% confidence interval (CI) 0.16, 0.73) and rs1867277 in the promoter region of FOXE1 (OR = 1.55, 95% CI 1.03, 2.34). Analysis of additional polymorphisms confirmed the association between these two genes and PTC. Our findings suggest that both DNA double‐strand break repair pathway and thyroid morphogenesis pathway or dysregulation of thyroid differentiated state maintenance are involved in the etiology of PTC, and that the studied genetic polymorphisms and radiation dose appear to act as independent multiplicative risk factors for PTC.
Determinant of earnings management practices in manufacturing companies

Research aims: This study aims to examine the effect of audit committees, independent commissioners, and the presence of women on boards, such as the chief executive officer and chief financial officer, on earnings management practices.Design/Methodology/Approach: This research used a quantitative method with a final panel data sample of 25 companies in the manufacturing sector for three years from 2020 to 2022. Hypothesis testing employed the regression model with the Common Effect Model (CEM) test. Sampling was conducted using secondary data on the Indonesia Stock Exchange (IDX) and each company's website.Research findings: The results of the study demonstrated that independent commissioners, independent audit committees, audit committee expertise, audit committee activities, and audit committee size yielded a significant effect on earnings management practices, while female CEOs and female CFOs had no significant impact on earnings management practices.Theoretical contribution/Originality: This research develops a theory that previously did not exist; in this research, the authors used asymmetric information theory to test the independent and dependent variables. Additional variables by suggestions in previous research are provided; therefore, it is hoped that this can strengthen the results of prior research. Practitioner/Policy implication: The practical implication of this research is that the existence of an independent audit committee with a positive influence on earnings management can improve the company's financial performance, make it easier for managers or internal company parties to make better decisions in the future, and meet performance targets set by other parties, such as investors and creditors. Profit management can also be used to obtain tax benefits. During the previous pandemic, the government implemented tax compensation for taxpayers who met the criteria.
Convergence rate of approximate solutions to weakly coupled nonlinear systems

We study the convergence rate of approximate solutions to nonlinear hyperbolic systems which are weakly coupled through linear source terms. Such weakly coupled 2 x 2 systems appear, for example, in the context of resonant waves in gas dynamics equations. This work is an extension of our previous scalar analysis. This analysis asserts that a One Sided Lipschitz Condition (OSLC, or Lip + -stability) together with W -1,1 -consistency imply convergence to the unique entropy solution. Moreover, it provides sharp convergence rate estimates, both global (quantified in terms of the W s,p -norms) and local. We focus our attention on the Lip + -stability of the viscosity regularization associated with such weakly coupled systems. We derive sufficient conditions, interesting for their own sake, under which the viscosity (and hence the entropy) solutions are Lip + -stable in an appropriate sense. Equipped with this, we may apply the abovementioned convergence rate analysis to approximate solutions that share this type of Lip + -stability.
Clinicopathological investigation of lymph node metastasis predictors in superficial esophageal squamous cell carcinoma with a focus on evaluation of lympho-vascular invasion

Abstract Objective. Reliable indicators of the risk of lymph node metastasis (LNM) in superficial esophageal squamous cell carcinoma (sESCC: intramucosal and submucosal invasive carcinoma) may contribute to assist optimal clinical decision-making for treating sESCC. In esophageal cancer, there is a possibility of metastasis, even in sESCC, and careful evaluation is needed when making a pathological diagnosis. In this study, we objectively evaluated predictive factors of LNM. Materials and methods. A total of 110 consecutive sESCC cases were obtained. We evaluated candidate predictive factors of LNM as follows: (1) maximum tumor diameter; (2) macroscopic type; (3) depth of tumor invasion; (4) histological differentiation; (5) infiltrative growth pattern; (6) tumor budding; (7) lymphatic invasion; (8) venous invasion and (9) lympho-vascular invasion (LVI). Both Elastica–Van Gieson staining (EVG) and immunohistochemistry (IHC: D2-40, CD31, CD34) were used to evaluate invasion into the lympho-vascular spaces. For statistical analyses, single and multiple logistic regression were performed. Results. LNM was observed in 37 cases (33.6%). LVI using EVG and IHC was the strongest independent predictor of LNM with an odds ratio of 12.01. Analysis of the relationship between LVI using EVG and IHC and LNM showed a negative predictive value of 94.6%. Conclusions. Evaluation of LVI using EVG and IHC may contribute to predict LNM in sESCC.
Amiodarone-induced enhancement of doxorubicin and 4'-deoxydoxorubicin cytotoxicity to rat colon cancer cells in vitro and in vivo.

The mechanisms of the resistance of intestinal cancer to anthracyclines were studied on an experimental model of rat colon cancer cells. The accumulation of anthracyclines in the nucleus of living cancer cells was observed by fluorescence microscopy. This accumulation depended on both the capacity of anthracyclines to penetrate into the cell and the activity of an efflux mechanism extruding the drug from the cell. We found that 4'-deoxydoxorubicin was superior to 4 other anthracyclines in its capacity to penetrate into confluent colon cancer cells. Amiodarone, an antiarrhythmic agent used in cardiology, inhibited the efflux mechanism efficiently and increased the toxicity of anthracyclines to the colon cancer cells. Association of amiodarone and 4'-deoxydoxorubicin was able to cure 5 of 13 rats that had been inoculated i.p. previously with syngeneic colon cancer cells. This association could be of interest in the treatment of human colon cancer.
Efficient Search for Interactive Statistical Machine Translation

The goal of interactive machine translation is to improve the productivity of human translators. An interactive machine translation system operates as follows: the automatic system proposes a translation. Now, the human user has two options: to accept the suggestion or to correct it. During the post-editing process, the human user is assisted by the interactive system in the following way: the system suggests an extension of the current translation prefix. Then, the user either accepts this extension (completely or partially) or ignores it. The two most important factors of such an interactive system are the quality of the proposed extensions and the response time. Here, we will use a fully fledged translation system to ensure the quality of the proposed extensions. To achieve fast response times, we will use word hypotheses graphs as an efficient search space representation. We will show results of our approach on the Verbmobil task and on the Canadian Hansards task.
Image trimming via saliency region detection and iterative feature matching

Detection of saliency regions in images is useful for object based image understanding and object localization. In our work, we investigate a saliency region detection algorithm based on the Human Visual Attention (HVA) model. In the first phase, we use mutual information and Probability-of-Boundary (PoB) for color saliency and edge detection respectively to filter SURF (Speeded Up Robust Features) key feature points found from the image. For the second phase, bipartite feature matching is deployed for further keypoint selection. We perform the two-phase keypoint filtering iteratively and give selected keypoints different weights for their importance. The final trimmed image is a rectangle region which approximates the distribution of remaining keypoints. We conduct our experiments on Corel Photo Library and MIT-CSAIL Objects and Scenes Database and demonstrate the effectiveness of our proposed algorithm.
Machine learning classification of rainfall forecasts using Austin weather data

The paper examines the machine learning classification of rainfall forecasts using Austin weather data. Rain is a natural phenomenon that is essential for the Earth's water cycle. Rain brings benefits to daily lives and also causes disasters, such as floods, which will endanger lives in addition to causing great losses. Due to this, many methods have been studied and experimented with to find a solution to predict rainfall and prevent tragedies from happening. In this research, the Austin weather dataset is applied to make predictions of rainfall through the implementation of machine learning models. The models used to predict rainfall based on the data set were Extreme Gradient Boosting, Support Vector Machine, Long Short-Term Memory, and Random Forest models. 21 variables with 1319 records were present in the dataset, but the variables used for the modelling were 18 variables from the original data, and 1 variable, “Precipitation Sum,” was converted to the variable “Precipitation Range,” which contained the classes “no rain,” “small rain,” “moderate rain,” and “heavy rain” based on specific value ranges. After training and predicting the data on the models, it was shown that Extreme Gradient Boosting gave the best results of 85.17% accuracy, 83.19% F1 score, 85.17% recall score, and 82.14% precision score, and was able to give predictions on all 4 classes of rainfall. This study and the way to implement machine learning models for rainfall prediction have the potential to provide new insights and methodologies for future studies and pave the way for finding a high-accuracy rainfall prediction method to avoid disaster.
Resting and activated T cells display different requirements for CD8 molecules

Clonotype-positive (1B2+) T cells from 2C T cell receptor (TCR) transgenic mice were used to define the role of CD8 molecules in the induction phase vs. the effector phase of the primary response to class I alloantigens. Three main findings are reported. First, in the presence of exogenous lymphokines, resting CD8+ 2C cells gave strong proliferative responses to two alloantigens, Ld and Kbm11. In the absence of added lymphokines, however, CD8+ 2C cells responded only to Ld and not to Kbm11; Ld stimulated both interleukin 2 (IL-2) and IL-2 receptor (R) synthesis, whereas Kbm11 elicited only IL-2R synthesis. The primary response of CD8+ 2C cells was thus helper-independent (HI) to Ld but helper-dependent (HD) to Kbm11, presumably reflecting that Ld is a stronger antigen than Kbm11. Second, in contrast to CD8+ cells, CD8- 2C cells mounted only an HD and not an HI response to the strong Ld antigen; conversely, selecting for a minor subset of CD8hi cells enabled 2C cells to mount an HI response to the weak Kbm11 antigen. These findings, together with experiments with heterozygous vs. homozygous stimulator cells, suggest that HI and HD responses reflect differences in the overall avidity of T antigen presenting cell (APC) interaction: high-avidity interaction leads to strong intracellular signaling and an HI response, whereas low-avidity interaction causes weak signaling and an HD response; high-avidity T/APC interaction is heavily dependent on CD8 expression. Third, CD8 expression was found to be less important for CTL activity than for primary proliferative responses. Thus, in contrast to HI proliferative responses, CTL responses of 2C cells to Ld were CD8 independent. However, 2C lysis of Ld targets became strongly CD8 dependent in the presence of limiting doses of anti-TCR (1B2) antibody. Collectively, the data suggest that, both for T cell induction and the expression of effector function, CD8 molecules play a decisive role in augmenting TCR-mediated signaling, either by promoting TCR contact with antigen or delivering kinases (p56lck) to the TCR/CD3 complex, or both.
A fast approximation algorithm for tree-sparse recovery

Sparse signals whose nonzeros obey a tree-like structure occur in a range of applications such as image modeling, genetic data analysis, and compressive sensing. An important problem encountered in recovering signals is that of optimal tree-projection, i.e., finding the closest tree-sparse signal for a given query signal. However, this problem can be computationally very demanding: for optimally projecting a length-n signal onto a tree with sparsity k, the best existing algorithms incur a high runtime of O(nk). This can often be impractical. We suggest an alternative approach to tree-sparse recovery. Our approach is based on a specific approximation algorithm for tree-projection and provably has a near-linear runtime of O(n log(kr)) and a memory cost of O(n), where r is the dynamic range of the signal. We leverage this approach in a fast recovery algorithm for tree-sparse compressive sensing that scales extremely well to high-dimensional datasets. Experimental results on several test cases demonstrate the validity of our approach.
A Metric Multidimensional Scaling-Based Nonlinear Manifold Learning Approach for Unsupervised Data Reduction

Manifold learning may be seen as a procedure aiming at capturing the degrees of freedom and structure characterizing a set of high-dimensional data, such as images or patterns. The usual goals are data understanding, visualization, classification, and the computation of means. In a linear framework, this problem is typically addressed by principal component analysis (PCA). We propose here a nonlinear extension to PCA. Firstly, the reduced variables are determined in the metric multidimensional scaling framework. Secondly, regression of the original variables with respect to the reduced variables is achieved considering a piecewise linear model. Both steps parameterize the (noisy) manifold holding the original data. Finally, we address the projection of data onto the manifold. The problem is cast in a Bayesian framework. Application of the proposed approach to standard data sets such as the COIL-20 database is presented.