Miracle-dz/UniFAR-FTUs huggingface dataset:
Linear and Non-Linear Multimodal Fusion for Continuous Affect Estimation In-the-Wild

Automatic continuous affect recognition from multiple modality in the wild is arguably one of the most challenging research areas in affective computing. In addressing this regression problem, the advantages of the each modality, such as audio, video and text, have been frequently explored but in an isolated way. Little attention has been paid so far to quantify the relationship within these modalities. Motivated to leverage the individual advantages of each modality, this study investigates behavioral modeling of continuous affect estimation, in multimodal fusion approaches, using Linear Regression, Exponent Weighted Decision Fusion and Multi-Gene Genetic Programming. The capabilities of each fusion approach are illustrated by applying it to the formulation of affect estimation generated from multiple modality using classical Support Vector Regression. The proposed fusion methods were applied in the public Sentiment Analysis in the Wild (SEWA) multimodal dataset and the experimental results indicate that employing proper fusion can deliver a significant performance improvement for all affect estimation. The results further show that the proposed systems is competitive or outperform the other state-of-the-art approaches.
Sources and delivery of carbon, nitrogen, and phosphorus to the coastal zone: An overview of Global Nutrient Export from Watersheds (NEWS) models and their application

An overview of the first spatially explicit, multielement (N, P, and C), multiform (dissolved inorganic: DIN, DIP; dissolved organic: DOC, DON, DOP; and particulate: POC, PN, PP) predictive model system of river nutrient export from watersheds (Global Nutrient Export from Watersheds (NEWS)) is presented. NEWS models estimate export from 5761 watersheds globally as a function of land use, nutrient inputs, hydrology, and other factors; regional and global scale patterns as of 1995 are presented here. Watershed sources and their relative magnitudes differ by element and form. For example, anthropogenic sources dominate the export of DIN and DIP at the global scale, although their anthropogenic sources differ significantly (diffuse and point, respectively). Natural sources dominate DON and DOP export globally, although diffuse anthropogenic sources dominate in several regions in Asia, Europe and N. America. “Hot spots” where yield (kg km−2 yr−1) is high for several elements and forms were identified, including parts of Indonesia, Japan, southern Asia, and Central America, due to anthropogenic N and P inputs in some regions and high water runoff in others. NEWS models provide a tool to examine past, current and future river export of nutrients, and how humans might impact element ratios and forms, and thereby affect estuaries and coastal seas.
Design of a Shunt Active Power Filter with Grid Connected Inverter Control for a Photovoltaic System

In this thesis, a shunt active filter (SAF) has been designed for a PV system. Due to the presence of nonlinear load and the inverter connected to the photovoltaic system, harmonics appear in the load current. Hence, to reduce the harmonics, a shunt active filter is connected between the inverter and the load at the point of common coupling. The power quality is improved by reducing the THD. The SAPF connected to PV system has been implemented using MATLAB/SIMULINK. From the obtained results, it is seen that the PV system with shunt active filter provides reduced THD. Further, the inverter control for integrating the PV system to the grid is presented. The three phase inverter works as a multi-functional device and it is used to supply the power to the grid as power converter as well as harmonic eliminator. The inverter control has simulated using MATLAB/SIMULINK. This control strategy incorporates PQ solution as in shunt active power filter technique to reduce harmonics in the current due to non-linear loads in the system and also the THD value is reduced
An attempt for generic concepts toward human-machine cooperation

Previous works in human engineering and particularly in the air traffic control domain show three basic conditions for designing a cooperative decision support system: 1) sufficient know-how for solving problems in an autonomous way; 2) know how to cooperate and 3) adequate organizational structure integrating human and machine. Through a multi-disciplinary approach including cognitive psychology and human engineering research we discuss some basic concepts. The paper gives a definition for cooperation from works by psychologists:"two agents are cooperating if 1) each one strives towards goals and can interfere with the other (on goals, resources, procedures, etc.) and 2) each agent tries to detect and process such interferences to make the other's activities easier". Two generic structures, respectively called vertical (hierarchical) and horizontal (heterarchical), are presented. When evaluating these structures, we show that the choice of a cooperative structure is not sufficient for allowing a real cooperation between human and machine. Therefore, deriving K. Schmidt's (1991) typology of the cooperative forms and this definition, we specify the capabilities needed for managing interferences between goals (MI) and the capabilities for making other agents' goals easier (FG). We then transpose MI and FG to human-machine cooperative systems, taking into account technical limitations of artificial agents and constraints imposed by the natural structure of the human-machine organization.
Random Subsampling and Data Preconditioning for Ground Penetrating Radars

Ground penetrating radars (GPRs) for mine detection can profit from the many advantages that compressed sensing can offer through random subsampling in terms of hardware simplification, reduced data volume and measurement time, or imagery simplification. An intrinsic antenna-ground model is used, canceling the undesired reverberation effects and the very strong reflection from the air–soil interface, producing higher detection rates, or even unmasking shallowly buried mines. Extensive Monte Carlo simulations on real GPR measurements (800–2200 MHz) show an increase in the probability of detection, yielding globally promising exploitable results, whenever the principal component analysis technique is used a as preconditioner, as well as providing lower random subsampling bounds for frequency and spatial measurements (cross range), whether applied individually or combined.
Hypocitraturia Is an Untoward Side Effect of Synthetic Human Parathyroid Hormone (hPTH) 1‐34 Therapy in Hypoparathyroidism That May Increase Renal Morbidity

Subcutaneous human parathyroid hormone (hPTH) therapy can effectively manage hypocalcemia in hypoparathyroidism, with varying effects on hypercalciuria. However, little is known about its ability to decrease the renal comorbidities of hypoparathyroidism: nephrocalcinosis (NC), nephrolithiasis (NL), and renal insufficiency. Urinary citrate (Ucit) promotes the solubility of urinary calcium (UCa); hypocitraturia is a risk factor for NC/NL. Twenty‐four–hour UCa, Ucit, and UCa/Ucit were determined in 31 hypoparathyroid subjects receiving hPTH 1‐34 therapy for up to 5 years. Before hPTH 1‐34, the geometric least squares mean UCa was 346 mg/day (normal <250) and Ucit was 500 mg/day (normal 250–1190); UCa/Ucit was 0.67 mg/mg. After 6 months of hPTH 1‐34, UCa decreased (238, p < 0.001), but with a greater decrease in Ucit (268, p < 0.001), increasing UCa/Ucit, which became significant over time (p < 0.001). After stopping hPTH 1‐34 and resuming conventional therapy (follow‐up; FU), compared to the last measures on hPTH 1‐34, Ucit rose to 626 (p < 0.001), reducing UCa/Ucit to 0.44, (p < 0.05); UCa also rose (273), but was still lower than baseline (p < 0.05). Daily hPTH 1‐34 dose did not correlate with UCa, but was inversely related to Ucit, and directly related to UCa/Ucit (p < 0.01). Mean blood bicarbonate decreased significantly on hPTH 1‐34 and remained lower than baseline at FU (p < 0.01). Mean eGFR increased on hPTH 1‐34 (86 to 96 mL/min/1.73 m2, p < 0.001) and returned to baseline at FU. On renal imaging, 6 subjects did not have NC/NL, 8 had NC/NL prior to hPTH 1‐34 that remained unchanged, and 16 developed new‐onset (n = 10) or progressive (n = 6) NC/NL while on hPTH 1‐34. Our data demonstrate that treatment with subcutaneous hPTH 1‐34 may have an untoward effect of hypocitraturia and high UCa/Ucit ratio that may increase renal morbidity. With increasing use of PTH therapy in hypoparathyroidism, close monitoring and exploration for treatment of hypocitraturia seem warranted. Published 2018. This article is a U.S. Government work and is in the public domain in the USA.
Facebook Addiction: Onset Predictors

Worldwide, Facebook is becoming increasingly widespread as a communication platform. Young people especially use this social networking site daily to maintain and establish relationships. Despite the Facebook expansion in the last few years and the widespread acceptance of this social network, research into Facebook Addiction (FA) is still in its infancy. Hence, the potential predictors of Facebook overuse represent an important matter for investigation. This study aimed to deepen the understanding of the relationship between personality traits, social and emotional loneliness, life satisfaction, and Facebook addiction. A total of 755 participants (80.3% female; n = 606) aged between 18 and 40 (mean = 25.17; SD = 4.18) completed the questionnaire packet including the Bergen Facebook Addiction Scale, the Big Five, the short version of Social and Emotional Loneliness Scale for Adults, and the Satisfaction with Life Scale. A regression analysis was used with personality traits, social, family, romantic loneliness, and life satisfaction as independent variables to explain variance in Facebook addiction. The findings showed that Conscientiousness, Extraversion, Neuroticism, and Loneliness (Social, Family, and Romantic) were strong significant predictors of FA. Age, Openness, Agreeableness, and Life Satisfaction, although FA-related variables, were not significant in predicting Facebook overuse. The risk profile of this peculiar behavioral addiction is also discussed.
Protection of star connected multi-terminal HVDC systems with offshore wind farms

In this paper, a high speed protection technique is proposed for protection of star connected Multi-Terminal HVDC (MTHVDC) systems with offshore wind farms. The fault is detected using high frequency transients created in the current signals due to fault occurrence. In fault cases, the energy of the transients superimposed on current signals is high. Moreover, the faulty line incorporates more high frequency transients than the healthy lines. Therefore, faulted line can be identified by comparing Euclidean norms of the high frequency transients superimposed on line currents. The proposed technique is able to detect fault and identify faulted line in MTHVDC systems including overhead lines and underground cables. Moreover, the identification of faulted line is done in less than 0.1 ms, which means complete safety of converter semiconductor devices during fault. Simulation and relay design are done in MATLAB. Simulation results showed the robustness and reliability of the proposed algorithm.
Evaluation of the Concept of Dynamic Adaptive Streaming of Light Field Video

Light field visualization has progressed and developed significantly in the past years. At the time of this paper, light field displays are utilized in the industry and they are commercially available as well. Although their appearance on the consumer market is approaching, many potential applications of light field technology have not yet been addressed, such as video streaming. In this paper, we present our research on the dynamic adaptive streaming of light field video. In order to evaluate the presented concept of quality switching, we carried out a series of subjective tests, where test participants were shown light field videos containing stallings and switches in spatial and angular resolution.
One species to another: sympatric Bt transgene gene flow from Brassica napus alters the reproductive strategy of wild relative Brassica juncea under herbivore treatment

Background and Aims Since pollen flow or seed dispersal can contribute to transgene persistence in the environment, the sympatric presence of transgenic crops with their wild relatives is an ecological concern. In this study, we tested the hypothesis that proximate growth of a herbivore-resistant Bt crop and wild relatives coupled with the presence of herbivores can increase relative frequency of crop-to-wild transgene flow persistence outside of cultivation. Methods We conducted a field experiment using insect enclosures with and without herbivores with cultivated Bt-transgenic Brassica napus (Bt OSR) and wild brown mustard (Brassica juncea) in pure and mixed stands. Low-density diamondback moth (Plutella xylostella) caterpillar infestation treatments were applied and transgene flow and reproductive organs were measured. Key Results Bt-transgenic B. napus produced more ovules and pollen than wild mustard, but the pollen to ovule (P/O) ratio in the two species was not significantly different. Low-level herbivory had no effects on fitness parameters of Bt OSR or wild brown mustard or on the transgene flow frequency. All progeny from wild brown mustard containing the Bt transgene came from mixed stands, with a gene flow frequency of 0.66 %. In mixed stands, wild brown mustard produced less pollen and more ovules than in pure stands of brown mustard. This indicates a decreased P/O ratio in a mixed population scenario. Conclusions Since a lower P/O ratio indicates a shift in sex allocation towards relatively greater female investment and a higher pollen transfer efficiency, the presence of transgenic plants in wild populations may further increase the potential transgene flow by altering reproductive allocation of wild species.
SDF-NN: A Deep Neural Network with Semantic Dropping and Fusion for Natural Language Inference

Natural language inference (NLI) is an important task in natural language processing (NLP), and recently, several deep neural network based models have been proposed for NLI. In this work, we first make two important observations regarding NLI: (1) the existence of extra/interfering semantics and its negative impact on the correctness of final inference; and (2) the unbalanced importance of local inference results and the need to combine all local results for aggregation. Motivated by these two observations, we have designed SDF-NN, a new NLI model with two novel components: (1) a Semantic Dropping Network (SDN) to automatically discard some of the interfering semantics; and (2) a Semantic Fusion Alignment (SFA) method to effectively fuse all local inference results. Our model has achieved 88.2% accuracy on the SNLI corpus, which is currently the best performing single model.
Overproduction of the cyanobacterial hydrogenase and selection of a mutant thriving on urea, as a possible step towards the future production of hydrogen coupled with water treatment

Using a combination of various types of genetic manipulations (promoter replacement and gene cloning in replicating plasmid expression vector), we have overproduced the complex hydrogenase enzyme in the model cyanobacterium Synechocystis PCC6803. This new strain overproduces all twelve following proteins: HoxEFUYH (hydrogen production), HoxW (maturation of the HoxH subunit of hydrogenase) and HypABCDEF (assembly of the [NiFe] redox center of HoxHY hydrogenase). This strain when grown in the presence of a suitable quantities of nickel and iron used here exhibits a strong (25-fold) increase in hydrogenase activity, as compared to the WT strain growing in the standard medium. Hence, this strain can be very useful for future analyses of the cyanobacterial [NiFe] hydrogenase to determine its structure and, in turn, improve its tolerance to oxygen with the future goal of increasing hydrogen production. We also report the counterintuitive notion that lowering the activity of the Synechocystis urease can increase the photoproduction of biomass from urea-polluted waters, without decreasing hydrogenase activity. Such cyanobacterial factories with high hydrogenase activity and a healthy growth on urea constitute an important step towards the future development of an economical industrial processes coupling H2 production from solar energy and CO2, with wastewater treatment (urea depollution).
Prospective Changes in Vestibular and Ocular Motor Impairment After Concussion

Background and Purpose: The utility of prospective changes on the Vestibular/Ocular Motor Screening (VOMS) assessment are unknown, and 2 methods of scoring are published in the literature. Total scores are the total symptom scores for each VOMS component, and change scores are the difference between the pretest total symptom score and component total symptom scores. This study documented prospective changes in vestibular and ocular motor impairments and symptoms in high school athletes with concussion using the total and change scoring methods and compared the percentage of scores over clinical cutoffs using the total and change scoring methods for the VOMS. Methods: Sixty-three athletes (15.53 ± 1.06 years) completed the VOMS at baseline (ie, preinjury), 1 to 7 days, and 8 to 14 days after concussion. A series of repeated-measures multivariate analyses of variance were conducted on total and change scores. A 2-way repeated-measures analysis of variance was performed on the near-point convergence distance. A series of &khgr;2 analyses compared scores exceeding clinical cutoffs between the total and change scoring methods. Results: Total scoring revealed impairments (Wilks &lgr; = 0.39, F16,47 = 4.54, P < 0.001, &eegr;2 = 0.61) on all VOMS components at 1 to 7 and 8 to 14 days compared to baseline. Change scoring revealed postinjury impairments compared with baseline (Wilks &lgr; = 0.58, F14,49 = 2.52, P = 0.009, &eegr;2 = 0.42) on all components at 1 to 7 days; however, impairments at 8 to 14 days were revealed only for the vertical vestibular oculomotor reflex and vestibular motor sensitivity components. Total scoring identified significantly more scores over cutoffs at 1 to 7 days (&khgr;1,632 = 5.97, P = 0.02) compared with change scores. Discussion and Conclusions: Both total and change scoring methods on the VOMS are useful for identifying impairments following concussion. Video Abstract available for more insights from the authors (see Supplemental Digital Content 1, http://links.lww.com/JNPT/A230)
TSPO: An Evolutionarily Conserved Protein with Elusive Functions

TSPO (18 kDa translocator protein) was identified decades ago in a search for peripheral tissue binding sites for benzodiazepines, and was formerly called the peripheral benzodiazepine receptor. TSPO is a conserved protein throughout evolution and it is implicated in the regulation of many cellular processes, including inflammatory responses, oxidative stress, and mitochondrial homeostasis. TSPO, apart from its broad expression in peripheral tissues, is highly expressed in neuroinflammatory cells, such as activated microglia. In addition, emerging studies employing the ligands of TSPO suggest that TSPO plays an important role in neuropathological settings as a biomarker and therapeutic target. However, the precise molecular function of this protein in normal physiology and neuropathology remains enigmatic. This review provides an overview of recent advances in our understanding of this multifaceted molecule and identifies the knowledge gap in the field for future functional studies.
In Silico Genome-Wide Analysis Reveals the Potential Links Between Core Genome of Acidithiobacillus thiooxidans and Its Autotrophic Lifestyle

The coinage “pan-genome” was first introduced dating back to 2005, and was used to elaborate the entire gene repertoire of any given species. Core genome consists of genes shared by all bacterial strains studied and is considered to encode essential functions associated with species’ basic biology and phenotypes, yet its relatedness with bacterial lifestyle of the species remains elusive. We performed the pan-genome analysis of sulfur-oxidizing acidophile Acidithiobacillus thiooxidans as a case study to highlight species’ core genome and its relevance with autotrophic lifestyle of bacterial species. The mathematical modeling based on bacterial genomes of A. thiooxidans species, including a novel strain ZBY isolated from Zambian copper mine plus eight other recognized strains, was attempted to extrapolate the expansion of its pan-genome, suggesting that A. thiooxidans pan-genome is closed. Further investigation revealed a common set of genes, many of which were assigned to metabolic profiles, notably with respect to energy metabolism, amino acid metabolism, and carbohydrate metabolism. The predicted metabolic profiles of A. thiooxidans were characterized by the fixation of inorganic carbon, assimilation of nitrogen compounds, and aerobic oxidation of various sulfur species. Notably, several hydrogenase (H2ase)-like genes dispersed in core genome might represent the novel classes due to the potential functional disparities, despite being closely related homologous genes that code for H2ase. Overall, the findings shed light on the distinguishing features of A. thiooxidans genomes on a global scale, and extend the understanding of its conserved core genome pertaining to autotrophic lifestyle.
Exploring Feature Coupling and Model Coupling for Image Source Identification

Recently, there has been great interest in feature-based image source identification. Previous statistical learning-based methods usually regarded the identification process as a classification problem. They assumed the dependence of features and the dependence of models. However, the two assumptions are usually problematic because of the genuine coupling of features and models. To address the issues, in this paper, we propose a novel image source identification scheme. For the feature coupling, a coupled feature representation is adopted to analyze the coupled interaction among features. The coupling relations among features and their powers are measured with Pearson’s correlations and integrated in a Taylor-like expansion manner. Regarding model coupling, a new coupled probability representation is developed. The model coupling relationships are characterized with conditional probabilities induced by the confusion matrix and then combined with the law of total probability. The experiments carried out on the Dresden image collection confirm the effectiveness of the proposed scheme. Via mining the feature coupling and model coupling, the identification accuracy can be significantly improved.
Improved Optimization Methods for Regularized Optimal Transport

Optimal Transport (OT) is dedicated to solving how to transform one measure to another with least cost. OT has gained wide applications in machine learning. However, the heavy computation burden of primal OT distance makes it prohibitive for prevalent high-dimensional problems. Recent work imposes an entropic regularization term on primal OT, obtaining a strictly convex problem that can be addressed with stochastic optimization. We focus on the optimization methods for discrete OT and semi-discrete OT with regularization. Instead of the initial SAG method for discrete OT, we apply SAGA, which solves the biased gradient estimation problem, and SVRG, which solves the memory problem. Besides, we define the regret in semi-discrete OT problem and solve it from the perspective of online learning. Our study, to our best knowledge, is the first effort to solve the semi-discrete OT problem with follow-the-regularized-leader thought. Our FTRL-\textit{current} algorithm shows faster convergence than existing algorithms for solving semi-discrete OT problem.