Miracle-dz/UniFAR-FTUs huggingface dataset:
NLP for Climate Policy: Creating a Knowledge Platform for Holistic and Effective Climate Action

Climate change is a burning issue of our time, with the Sustainable Development Goal (SDG) 13 of the United Nations demanding global climate action. Realizing the urgency, in 2015 in Paris, world leaders signed an agreement committing to taking voluntary action to reduce carbon emissions. However, the scale, magnitude, and climate action processes vary globally, especially between developed and developing countries. Therefore, from parliament to social media, the debates and discussions on climate change gather data from wide-ranging sources essential to the policy design and implementation. The downside is that we do not currently have the mechanisms to pool the worldwide dispersed knowledge emerging from the structured and unstructured data sources. The paper thematically discusses how NLP techniques could be employed in climate policy research and contribute to society's good at large. In particular, we exemplify symbiosis of NLP and Climate Policy Research via four methodologies. The first one deals with the major topics related to climate policy using automated content analysis. We investigate the opinions (sentiments) of major actors' narratives towards climate policy in the second methodology. The third technique explores the climate actors' beliefs towards pro or anti-climate orientation. Finally, we discuss developing a Climate Knowledge Graph. The present theme paper further argues that creating a knowledge platform would help in the formulation of a holistic climate policy and effective climate action. Such a knowledge platform would integrate the policy actors' varied opinions from different social sectors like government, business, civil society, and the scientific community. The research outcome will add value to effective climate action because policymakers can make informed decisions by looking at the diverse public opinion on a comprehensive platform.
On Ohm’s law in reduced plasma fluid models

Drift-reduced MHD models are widely used to study magnetised plasma phenomena, in particular for magnetically confined fusion applications, as well as in solar and astrophysical research. This letter discusses the choice of Ohm’s law in these models, the resulting dispersion relations for the dynamics parallel to the magnetic field, and the implications for numerical simulations. We find that if electron pressure is included in Ohm’s law, then both electromagnetic and finite electron mass effects must also be included in order to obtain physical dispersion relations. A simple modification to the plasma vorticity is also found which improves handling of low density regions, of particular relevance to the simulation of the boundary region of magnetised plasmas.
Deep and Shallow Covariance Feature Quantization for 3D Facial Expression Recognition

Facial expressions recognition (FER) of 3D face scans has received a significant amount of attention in recent years. Most of the facial expression recognition methods have been proposed using mainly 2D images. These methods suffer from several issues like illumination changes and pose variations. Moreover, 2D mapping from 3D images may lack some geometric and topological characteristics of the face. Hence, to overcome this problem, a multi-modal 2D + 3D feature-based method is proposed. We extract shallow features from the 3D images, and deep features using Convolutional Neural Networks (CNN) from the transformed 2D images. Combining these features into a compact representation uses covariance matrices as descriptors for both features instead of single-handedly descriptors. A covariance matrix learning is used as a manifold layer to reduce the deep covariance matrices size and enhance their discrimination power while preserving their manifold structure. We then use the Bag-of-Features (BoF) paradigm to quantize the covariance matrices after flattening. Accordingly, we obtained two codebooks using shallow and deep features. The global codebook is then used to feed an SVM classifier. High classification performances have been achieved on the BU-3DFE and Bosphorus datasets compared to the state-of-the-art methods.
An efficient projection neural network for $\ell_1$-regularized logistic regression

$\ell_1$ regularization has been used for logistic regression to circumvent the overfitting and use the estimated sparse coefficient for feature selection. However, the challenge of such a regularization is that the $\ell_1$ norm is not differentiable, making the standard algorithms for convex optimization not applicable to this problem. This paper presents a simple projection neural network for $\ell_1$-regularized logistics regression. In contrast to many available solvers in the literature, the proposed neural network does not require any extra auxiliary variable nor any smooth approximation, and its complexity is almost identical to that of the gradient descent for logistic regression without $\ell_1$ regularization, thanks to the projection operator. We also investigate the convergence of the proposed neural network by using the Lyapunov theory and show that it converges to a solution of the problem with any arbitrary initial value. The proposed neural solution significantly outperforms state-of-the-art methods with respect to the execution time and is competitive in terms of accuracy and AUROC.
Online POMDP Planning via Simplification

In this paper, we consider online planning in partially observable domains. Solving the corresponding POMDP problem is a very challenging task, particularly in an online setting. Our key contribution is a novel algorithmic approach, Simplified Information Theoretic Belief Space Planning (SITH-BSP), which aims to speed-up POMDP planning considering belief-dependent rewards, without compromising on the solution's accuracy. We do so by mathematically relating the simplified elements of the problem to the corresponding counterparts of the original problem. Specifically, we focus on belief simplification and use it to formulate bounds on the corresponding original belief-dependent rewards. These bounds in turn are used to perform branch pruning over the belief tree, in the process of calculating the optimal policy. We further introduce the notion of adaptive simplification, while re-using calculations between different simplification levels and exploit it to prune, at each level in the belief tree, all branches but one. Therefore, our approach is guaranteed to find the optimal solution of the original problem but with substantial speedup. As a second key contribution, we derive novel analytical bounds for differential entropy, considering a sampling-based belief representation, which we believe are of interest on their own. We validate our approach in simulation using these bounds and where simplification corresponds to reducing the number of samples, exhibiting a significant computational speedup while yielding the optimal solution.
FDAN: Flow-guided Deformable Alignment Network for Video Super-Resolution

Most Video Super-Resolution (VSR) methods enhance a video reference frame by aligning its neighboring frames and mining information on these frames. Recently, deformable alignment has drawn extensive attention in VSR community for its remarkable performance, which can adaptively align neighboring frames with the reference one. However, we experimentally find that deformable alignment methods still suffer from fast motion due to locally loss-driven offset prediction and lack explicit motion constraints. Hence, we propose a Matching-based Flow Estimation (MFE) module to conduct global semantic feature matching and estimate optical flow as coarse offset for each location. And a Flow-guided Deformable Module (FDM) is proposed to integrate optical flow into deformable convolution. The FDM uses the optical flow to warp the neighboring frames at first. And then, the warped neighboring frames and the reference one are used to predict a set of fine offsets for each coarse offset. In general, we propose an end-to-end deep network called Flow-guided Deformable Alignment Network (FDAN), which reaches the state-of-the-art performance on two benchmark datasets while is still competitive in computation and memory consumption.
Effect of high-fluoride dentifrice and bracket bonding composite material on enamel demineralization adjacent to orthodontic brackets in vitro

Background There is a lack of information about the association of high-fluoride dentrifrice and fluoride-containing bonding material to prevent enamel white spot lesions development adjacent to brackets. The aim of this in vitro study was to evaluate the effect of high-fluoride dentifrice and fluoride-containing bonding material on enamel demineralization adjacent to orthodontic brackets. Material and Methods Forty-eight enamel specimens with 7x7x2 mm were obtained from bovine incisors. Orthodontic brackets were bonded with fluoride-containing resin composite (OrthoCem®) or fluoride-free low viscosity resin. The specimens were submitted to an 8-day pH cycling that consisted in the daily immersion of specimens in the demineralizing solution for 4 h and in artificial saliva for 20 h in an incubator at 37° C. The treatments consisted in 5 min-immersion between the cycles of fluoride (F) suspensions containing 275 µg F/mL, 1,250 µg F/mL or distilled water (negative control). The 275 and 1,250 µg F/mL concentrations were used to simulate salivary dilution of 1,100 and 5,000 µg F/g dentifrices during toothbrushing. After the experiment, cross-sectional hardness was performed to analyze the lesion area of the specimens. Tukey post hoc test after two-way ANOVA with p at 5% was used as statistical analysis. Results The specimens treated with high-fluoride dentifrice showed significantly less demineralization in comparison with the other treatments (p>0.05). There was a significant difference in the cross-sectional hardness values for the specimens bonded with OrthoCem when compared to the low viscosity resin (p>0,05). Conclusions The use of high-fluoride dentifrice associated with fluoride-containing bonding material promoted a greater reduction of enamel demineralization adjacent to orthodontic brackets. Key words:Demineralization, dentifrice, fluoride, bonding materials, orthodontic brackets.
Hermetia illucens Protein Conjugated with Glucose via Maillard Reaction: Antioxidant and Techno-Functional Properties

The food industry is considering novel sources of proteins with enhanced functionalities to meet the increasing demand and population growth. Edible insect proteins have emerged as an alternative that is environmentally friendly and economically viable and thus could make a significant contribution to global food security. This study was aimed to establish the effect of conjugation via the Maillard reaction on the antioxidant and techno-functional properties of black soldier fly larvae protein concentrate. Reaction mixtures containing black soldier fly larvae protein concentrate and glucose (2 : 1 weight ratio) were wet-heated at 50, 70, and 90°C for 2, 4, 6, 8, and 10 h, respectively, with an initial pH of 9. The results showed that the browning indices of the black soldier fly larvae-glucose (BSFL-Glu) model system increased with an increase in reaction time and temperature, with conjugates formed at 90°C exhibiting the highest browning intensity at 420 nm. At 50°C, the DPPH-RS of the conjugates ranged from 15.47 to 32.37%. The ABTS+ radical scavenging activity of BSFL-Glu conjugates produced at 90°C exhibited significantly (p < 0.05) higher scavenging activity as a function of reaction time. The foaming capacity of BSFL-Glu conjugates produced at 70°C showed a significant increase (p < 0.05) as a function of reaction time. Principal component analysis was applied to browning and antioxidant indices. Component 1 of the score plot accounted for 89%, while component 2 accounted for 8% of the observed variability and allowed discrimination/differentiation of the samples based on the heating temperature. These findings provide a practical means to improve the functionality of novel edible insect proteins for food application.
Laparoscopic Cholecystectomy for Gallbladder Dysfunction and Polyps: Incidence and Follow up

Aim: This study aims to evaluate the incidence, indications, management, and long term follow up of cholecystectomy in patients with no gallstones, other than acalculous acute cholecystitis. Methods: Prospectively collected data of 5675 patients undergoing laparoscopic cholecystectomy (LC) over 28 years was extracted and analyzed. Patients with biliary symptoms, no stones on ultrasound scans and abnormal hepatobiliary iminodiacetic acid scans, and those with confirmed gallbladder polyps (GBP) were included. Results: Two percent of cholecystectomies were performed in patients with acalculous pathology [1.3% functional gallbladder disorder (FGBD) and 0.7% GBP]. The 114 patients were younger, had lower American Society of Anesthesiologists classification, and had fewer previous biliary admissions than those with gallstones (5560). The clinical presentations of FGBD were chronic biliary symptoms (93.1%) and acute biliary pain (6.9%). GBP patients presented with chronic biliary symptoms. LC in 98.6% FGBD and 92.8% GBP were significantly easier than those for gall stones (P < 0.0001). They were significantly (P < 0.0001 FGBD and P < 0.001 GBP) less likely to have adhesions to the gallbladder. This ease was reflected in shorter operation times and lower utilization of abdominal drains. Polyp numbers ranged from 1 to 30 and sizes from 1 mm to 11 mm. No malignant polyps were encountered. In 95.8% FGBD and 95% GBP, patients had a good symptomatic response to LC. Conclusions: FGBD and GBP are uncommon in patients undergoing LC. FGBD should be considered during evaluation of right upper quadrant pain with no gall stones. Laparoscopic cholecystectomy may be considered as it achieves long term symptomatic relief in most patients with FGBD and GBP.
Micellar liquid chromatographic method for the determination of ephedrine and pseudoephedrine in human serum by direct inject of the sample with simple dilution

ABSTRACT A micellar high-performance liquid chromatographic method was developed to simultaneously determine ephedrine and pseudoephedrine in human serum. The serum sample pretreatment was a simple dilution in a micellar solution, filtration, and direct injection, thus avoiding time-consuming and tedious steps. Hence, there is no need to use an internal standard. The serum samples were analyzed using a mobile phase containing 1.50 × 10−1 mol/L sodium dodecyl sulfate and 0.02 mol/L sodium dihydrogen phosphate with 7.5% (v/v) 1-propanol at pH 3.0, running at 1.0 mL/min by an Inertsil C18 (150 × 4.6 mm, 5 µm) column at 30°C. The UV wavelength was set at 210 nm. The developed method was validated by linearity (r > 0.9990) and intra- and inter-day precisions of ephedrine and pseudoephedrine (relative standard deviation; RSD%, 0.04–10.40, and RSD %, 0.30–10.25, respectively), LODs for ephedrine and for pseudoephedrine was 2.63 and 2.70 µg/mL, respectively; lower limit of quantification for ephedrine and for pseudoephedrine was 4.38 and 4.51 µg/mL, respectively. Finally, the proposed method was applied to investigate ephedrine and pseudoephedrine in real human serum samples after oral administration of Kechuanning Koufye including Ephedra herb. It is environmentally friendly, easy-to-handle, and feasible method for routine analysis in clinical laboratory. GRAPHICAL ABSTRACT
The Correlation between Demographical and Lifestyle Factors and Traditional Chinese Medicine Constitution among Macau Elderly Individuals

Objectives To measure the distributed characteristics of Traditional Chinese Medicine (TCM) constitutions, as well as related factors with biased TCM constitutions among the elderly individuals in Macau. Methods The elderly individuals from elderly healthcare centers located in Macao Peninsula, Taipa, and Coloane were selected as research samples. The basic information questionnaire and the Constitution in Chinese Medicine Questionnaire (CCMQ) for elderly were employed. Descriptive analysis was applied to illustrate demographical characteristics and TCM constitution distribution. Exploratory factor analysis (EFA) was conducted to explore potential factors influencing biased constitutions, and weight of each variable for constitution was further calculated. Results A total of 313 participants were recruited. Eighty-six (27.48%) elderly were identified as balanced constitution; others were biased constitutions accounting for 72.52%. Distribution differences related to gender and age were identified among participants with unbalanced constitutions. Four biased constitutions were further analyzed with EFA. For qi-stagnation and yang-deficiency constitutions, three similar factors were determined in the domains of education, sleeping habits, and lifestyle behaviors, successively. Although four factors were identified in phlegm-dampness constitution, the latter two belonged to lifestyle behaviors and the former two were education and sleeping habits. For yin-deficiency constitution, education, tobacco-alcohol consumption, sleeping habits, and exercise were four dimensions of potential influential factors. Tobacco consumption, sleep, and exercise duration weighted the most for qi-stagnation constitution; sleep duration, education level, and sugar-containing beverage intake for phlegm-dampness; length of education, alcohol consumption, and education level for yang-deficiency constitution; and weekly exercise hours, sleep duration, and education level for yin-deficiency constitution. Conclusion The prevalence rate of biased constitutions was relatively high among elderly residents in Macau. Relations between demographical and lifestyle behavioral factors and biased constitutions were identified in this study. Controlling these influential factors might be beneficial for health management of Macau elderly individuals.
Transcriptome analysis of the liver of Eospalax fontanierii under hypoxia

Hypoxia can induce cell damage, inflammation, carcinogenesis, and inhibit liver regeneration in non-adapted species. Because of their excellent hypoxia adaptation features, subterranean rodents have been widely studied to clarify the mechanism of hypoxia adaptation. Eospalax fontanierii, which is a subterranean rodent found in China, can survive for more than 10 h under 4% O2 without observable injury, while Sprague-Dawley rats can survive for less than 6 h under the same conditions. To explore the potential mechanism of hypoxia responses in E. fontanierii, we performed RNA-seq analysis of the liver in E. fontanierii exposed to different oxygen levels (6.5% 6h, 10.5% 44h, and 21%). Based on the bioinformatics analysis, 39,439 unigenes were assembled, and 56.78% unigenes were annotated using public databases (Nr, GO, Swiss-Prot, KEGG, and Pfam). In total, 725 differentially expressed genes (DEGs) were identified in the response to hypoxia; six with important functions were validated by qPCR. Those DEGs were mainly involved in processes related to lipid metabolism, steroid catabolism, glycolysis/gluconeogenesis, and the AMPK and PPAR signaling pathway. By analyzing the expression patterns of important genes related to energy associated metabolism under hypoxia, we found that fatty acid oxidation and gluconeogenesis were increased, while protein synthesis and fatty acid synthesis were decreased. Furthermore, the upregulated expression of specific genes with anti-apoptosis or anti-oxidation functions under hypoxia may contribute to the mechanism by which E. fontanierii tolerates hypoxia. Our results provide an understanding of the response to hypoxia in E. fontanierii, and have potential value for biomedical studies.
Nanoparticles for Oral Cancer Diagnosis and Therapy

Oral cancer is the sixth most common malignant cancer, affecting the health of people with an unacceptably high mortality rate. Despite numerous clinical methods in the diagnosis and therapy of oral cancer (e.g., magnetic resonance imaging, computed tomography, surgery, and chemoradiotherapy), they still remain far from optimal. Therefore, an urgent need exists for effective and practical techniques of early diagnosis and effective therapy of oral cancer. Currently, various types of nanoparticles have aroused wide public concern, representing a promising tool for diagnostic probes and therapeutic devices. Their inherent physicochemical features, including ultrasmall size, high reactivity, and tunable surface modification, enable them to overcome some of the limitations and achieve the expected diagnostic and therapeutic effect. In this review, we introduce different types of nanoparticles that emerged for the diagnosis and therapy of oral cancers. Then, the challenges and future perspectives for nanoparticles applied in oral cancer diagnosis and therapy are presented. The objective of this review is to help researchers better understand the effect of nanoparticles on oral cancer diagnosis and therapy and may accelerate breakthroughs in this field.
Stable isotope and fatty acid analyses reveal significant differences in trophic niches of smooth hammerhead Sphyrna zygaena (Carcharhiniformes) among three nursery areas in northern Humboldt Current System

Fishery pressure on nursery areas of smooth hammerhead in northern Peruvian coast have become a serious threat to sustainability of this resource. Even though, some management actions focused on conservation of the smooth hammerhead populations were proposed in recent years, their scientific foundations are often limited, and biomass of smooth hammerhead in Peruvian waters continues to decrease. To inform management and conservation, this study aims to evaluate the trophic niche of smooth hammerhead juveniles from three nursery areas in the northern Peruvian coast using stable isotope and fatty acid analyses. First, we compared the environmental characteristics of each nursery area (i.e., sea surface temperature and chlorophyll-a concentration) and concluded that nursery areas differed significantly and consistently in sea surface temperature. Subsequently, we evaluated isotopic composition of carbon and nitrogen and fatty acid profiles of muscle and liver tissues collected from juvenile smooth hammerhead from each nursery area. We found that juvenile smooth hammerhead captured in San José were enriched in heavier 13C and 15N isotopes compared to those captured in Máncora and Salaverry. Furthermore, the broadest isotopic niches were observed in juveniles from Máncora, whereas isotopic niches of juveniles from Salaverry and San José were narrower. This difference is primarily driven by the Humboldt Current System and associated upwelling of cold and nutrient rich water that drives increased primary production in San José and, to a less extent, in Salaverry. Compared to smooth hammerhead juveniles from Máncora, those from San José and Salaverry were characterised by higher essential fatty acid concentrations related to pelagic and migratory prey. We conclude that smooth hammerhead juveniles from three nursery areas in the northern Peruvian coast differ significantly in their trophic niches. Thus, management and conservation efforts should consider each nursery area as a unique juvenile stock associated with a unique ecosystem and recognize the dependence of smooth hammerhead recruitment in San José and Salaverry on the productivity driven by the Humboldt Current System.