Miracle-dz/UniFAR-FTUs huggingface dataset:
Complex-Valued Pix2pix—Deep Neural Network for Nonlinear Electromagnetic Inverse Scattering

Nonlinear electromagnetic inverse scattering is an imaging technique with quantitative reconstruction and high resolution. Compared with conventional tomography, it takes into account the more realistic interaction between the internal structure of the scene and the electromagnetic waves. However, there are still open issues and challenges due to its inherent strong non-linearity, ill-posedness and computational cost. To overcome these shortcomings, we apply an image translation network, named as Complex-Valued Pix2pix, on the inverse scattering problem of electromagnetic field. Complex-Valued Pix2pix includes two parts of Generator and Discriminator. The Generator employs a multi-layer complex valued convolutional neural network, while the Discriminator computes the maximum likelihoods between the original value and the reconstructed value from the aspects of the two parts of the complex: real part and imaginary part, respectively. The results show that the Complex-Valued Pix2pix can learn the mapping from the initial contrast to the real contrast in microwave imaging models. Moreover, due to the introduction of discriminator, Complex-Valued Pix2pix can capture more features of nonlinearity than traditional Convolutional Neural Network (CNN) by confrontation training. Therefore, without considering the time cost of training, Complex-Valued Pix2pix may be a more effective way to solve inverse scattering problems than other deep learning methods. The main improvement of this work lies in the realization of a Generative Adversarial Network (GAN) in the electromagnetic inverse scattering problem, adding a discriminator to the traditional Convolutional Neural Network (CNN) method to optimize network training. It has the prospect of outperforming conventional methods in terms of both the image quality and computational efficiency.
Efficience Alimentaire : comment mieux la comprendre et en faire un élément de durabilité de l’élevage

L’efficience alimentaire est un caractère de première importance pour l’élevage, tant du point de vue économique que comme élément de sa durabilité. Si l’efficience alimentaire peut s’étudier à différentes échelles, le choix est fait de situer cette synthèse au niveau de l’animal et des variations individuelles. Dans un premier temps, les différentes définitions de l’efficience et des critères utilisés pour l’estimer sont abordées, en comparant les possibilités offertes par les critères de type ratio et ceux de type résidu. L’ingéré résiduel (ou « Residual Feed Intake » : RFI), critère le plus plébiscité aujourd’hui dans les études sur les ruminants, est présenté. Dans un deuxième temps, les mécanismes biologiques impliqués dans l’efficience alimentaire sont passés en revue, ainsi que les moyens de les étudier. On retrouve tout d’abord ce qui a trait à l’efficience digestive, avec notamment l’impact du temps de séjour ou de la population microbienne. Puis, les déterminants de l’efficience métabolique tels que la production de chaleur, le taux de renouvellement protéique, la respiration mitochondriale, ou encore l’influence de la composition corporelle sont également détaillés. Dans un troisième temps, nous évoquons les défis à relever afin de mettre en place une potentielle sélection sur le caractère, la difficulté majeure résidant dans le phénotypage d’un nombre suffisant d’individus. Enfin, les liens entre efficience et résilience sont explorés, afin de prendre en compte la performance de l’animal sur un pas de temps plus long et d’inclure l’importance de la durabilité.
Survey on the Antibacterial Effect of Silver Nanoparticles Deposited on Textile Fabrics

Background: According to the recent studies, the antibacterial activities of silver nanoparticles (Ag-NPs) were studied on Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli. In this study antibacterial effect of silver nanoparticles that used for coating textiles, on E.coli and S.aureus was investigated. Methods: Silver nanoparticles were coated on textile fabric by corona treatment and the antibacterial properties of fabrics were quantitatively evaluated by using a Gram-positive bacterium S. aureus and Gram-negative bacterium E. coli. Results: The textiles coated with silver nanoparticles had favorable antimicrobial effect against both E. coli and S. aureus. The value of antibacterial activity was appropriated with corona power and deposition that was used for absorption of Silver nanoparticle on samples. Conclusions: These results suggest that silver nanoparticles could be used as an effective antibacterial material.
Driving Forces of Food Consumption Water Footprint in North China

The water footprint (WF) vividly links water resources with virtual water of food, providing a novel perspective on food demand and water resources management. This study estimates the per capita WF of food consumption for six provinces in North China. Then, the study applies the logarithmic mean Divisia index method to decompose the driving forces of their WF changes. Results show that the per capita WF of food consumption in Beijing, Tianjin, and Inner Mongolia increases significantly in 2005–2017, whereas that in the other three provinces in North China varies slightly. All provinces have shown the same trend of food structure changes: the grain decreased, whereas the meat increased. In general, the urban effect was positive, and the rural effect was negative for all regions. The urban effects in Beijing and Tianjin played a leading role, whereas the rural effects in the other four provinces played a leading role from 2005–2009. However, the urban effects in all provinces played a leading role in 2010–2017. The WF efficiency increased in each province, and the effect in urban areas is stronger due to the higher water use efficiency. For most provinces, the consumption structure was positive because the diet shifted toward more meat consumption. The food consumption per capita effect was the major driving force in Beijing and Tianjin due to the increased consumption level, whereas the population proportion effect exerted a weak effect. To alleviate the pressure on water resources, further improving water use efficiency in food production and changing the planting structure should be emphasized for all regions in North China.
Coconut shell-based activated carbon as adsorbent for the removal of dye from aqueous solution: equilibrium, kinetics, and thermodynamic studies

The need to develop more efficient adsorbent, comparable to commercially available adsorbent, is attracting significant interest as promising adsorbent for waste water treatment. In this study, the potential of activated carbon prepared from waste coconut shell (CSAC) for the removal of methylene blue (Mb) from aqueous solution was reported. Batch experiments were conducted to determine the adsorption isotherm and kinetics of Mb on CSAC. Langmuir, Freundlich and Temkin isotherm models were employed to fit and analyze the adsorption equilibrium data. The result shows Langmuir isotherm model gave the best fit and an adsorption capacity of 320.5 mg/g was obtained for Mb at pH value of 7, 0.02 g adsorbent dosage and contact time of 4.5 hour. The experimental kinetic data at different initial Mb concentrations was also analyzed with pseudo-first order, pseudo-second order and intraparticle diffusion models. The obtained results showed that the pseudo-second order model fits the adsorption kinetic data with R range of 0.9985-0.9996. Finally, the thermodynamic parameters show that the adsorption of Mb on CSAC was spontaneous and endothermic in nature. This therefore suggests that (CSAC) is a viable adsorbent for effective removal of dye from wastewater effluent.
Pediatric Emergency Medicine Training

Pediatric emergency medicine (PEM) is a relatively new and rapidly evolving subspecialty in many countries. The purposes of this study were to describe the characteristics and to find common/shared practices in current available PEM fellowship programs across Latin America. Methods An electronic, multicenter survey was created and stored on Google forms. The survey was in Spanish language and included 30 questions about the characteristics of the pediatric emergency program, history of the program, and support expected from the Latin American Pediatric Emergency Society. Results A total of 11 PEM programs in 6 countries were acknowledged in Latin America. All programs are placed in pediatric tertiary care hospitals. All PEM programs were approved by the local universities and the Ministries of Health in each country. Difficulties to start a PEM program included a lack of physicians properly trained in PEM who could direct the program, physician instructors in specific topics, places to complete rotations of the future fellows, and getting the local health authorities to acknowledge the importance of the program. With regard to the duration of the program, 72.7% (8) have a 2-year curriculum and 27.3% (3) have a 1-year curriculum. Four (36.4%) program directors mentioned an admission examination as a requirement, 4 (36.4%) needed an examination plus an interview, 3 (27.3%) mentioned that it is necessary just like an interview, and 2 (18.2%) mentioned that the physicians are admitted with a scholarship. With regard to the structure of the programs and rotations included, most of the programs have rotations that are compulsory in different pediatric subspecialties. In 80% of the programs, fellows are evaluated based on different technical skill procedures that they need to learn and perform during PEM fellowship training. The PEM fellowship is recognized by different societies in emergency medicine and pediatrics, except in Dominican Republic where it is only recognized by the Ministry of Health and the university. After completion of the program in 90% (10) of the programs, graduates are not guaranteed a job, and in half, there is no mechanism implemented for recertification of the pediatric emergency physicians by the local medical council. Conclusions In Latin America, postgraduate programs in pediatric emergencies are a response to a need for health systems. Being an innovative specialty, it surpassed each country's own challenges, until it was able to reach an internationally standardized level, with a great diversity of pedagogical methodology, which the product has been to offer a high quality of emergency care to children.
Oral Biofilm and Its Impact on Oral Health, Psychological and Social Interaction

Oral health can be act as “mirror” that indicate and reflect the overall health condition, life style and oral hygiene. Oral cavity harbours arrays of microorganisms that interact with diet, oral environment, and host. This complex dynamic interaction results in microbial colonization and the subsequent oral biofilm formation. Oral biofilms are highly ordered, surface-associated assemblages of microorganisms embedded in an extracellular matrix. These surface-attached microbial communities are responsible for many oral diseases such as dental caries and periodontitis. Dental caries and periodontitis are biofilm-dependent diseases manifested within oral environment. These diseases in turn have a detrimental impact on oral health, psychology and social interaction of patients. Halitosis is a prime example of psycho-social problem resulting from oral biofilms and other health related complaints. Although oral biofilm formation is inevitable and can’t be completely eliminated, the severity can be reduced through effective oral hygiene measures. Appropriate and timely hygiene procedure for the teeth and oral cavity is the most effective and specific way to prevent dental caries and periodontal diseases. Toothbrushing, interdental cleaning, and professional scaling procedures are mechanical methods required to regularly and effectively disrupt and remove the plaque biofilm. Along with oral hygiene sugary diets, smoking and alcohol consumption must be considered critically. Furthermore, preventing bacterial attachment, manipulating cell-to-cell signalling, using effective antimicrobials, and developing inhibitors that can disrupt the matrix are the promising approaches to alleviate the problems. Generally, oral biofilm is an escalating public health, psychological, and social threat that is highly linked to the food we eat, microbes we harbor and general health status. Therefore, the aim of this review article is to provide an overview of oral biofilms and its impact on health, psychological and social interactions.
User experience designers: a study on organizational commitment, job satisfaction & self-efficacy

Every individual has a different personality. Some individuals are committed towards their work whereas others are just working for the sake of earning. They do not enjoy working or we can say, they are not satisfied with their roles in an organization. The success of the organization is only when employees stay committed to their work. Also, when the employees are satisfied with their job roles. The present study aims to study job satisfaction, job commitment and self-efficacy of User Experience Designers. The study was conducted on 30 UX Designers within the age group of 21-35years from Punjab. Standardized measures of job commitment, job satisfaction and self-efficacy were administered on participants. The findings of the study revealed that there is a positive correlation between job satisfaction and organizational commitment. But there is no significant correlation of self-efficacy with job satisfaction & organizational commitment.
Role of Fzd6 in Regulating the Osteogenic Differentiation of Adipose-derived Stem Cells in Osteoporosis

Objective: Although it has been demonstrated that adipose-derived stem cells (ASCs) from osteoporosis mice (OP-ASCs) exhibit impaired osteogenic differentiation potential, the molecular mechanism has not yet been elucidated. We found that Fzd6 was decreased in OP-ASCs compared with ASCs. This study investigates the effects and underlying mechanisms of Fzd6 in the osteogenic potential of OP-ASCs. Methods: Fzd6 expression in ASCs and OP-ASCs was measured by PCR gene chip. Fzd6 overexpression and silencing lentiviruses were used to evaluate the role of Fzd6 in the osteogenic differentiation of OP-ASCs. Real-time PCR (qPCR) and western blotting (WB) was performed to detect the expression of Fzd6 and bone-related molecules, including runt-related transcription factor 2 (Runx2) and osteopontin (Opn). Alizarin red staining and Alkaline phosphatase (ALP) staining was performed following osteogenic induction. Microscopic CT (Micro-CT), hematoxylin and eosin staining (H&E) staining, and Masson staining were used to assess the role of Fzd6 in osteogenic differentiation of osteoporosis (OP) mice in vivo.Results: Expression of Fzd6 was decreased significantly in OP-ASCs. Fzd6 silencing down-regulated the osteogenic ability of OP-ASCs in vitro. Overexpression of Fzd6 rescued the impaired osteogenic capacity in OP-ASCs in vitro. We obtained similar results in vivo.Conclusions: Fzd6 plays an important role in regulating the osteogenic ability of OP-ASCs both in vivo and in vitro. Overexpression of Fzd6 associated with the Wnt signaling pathway promotes the osteogenic ability of OP-ASCs, which provides new insights for the prevention and treatment of OP.
Interaction event network modeling based on temporal point process

Abstract Interaction event networks, which consist of interaction events among a set of individuals, exist in many areas from social, biological to financial applications. The individuals on networks interact with each other for several possible reasons, such as periodic contact or reply to former interactions. Regarding these interaction events as expectations based on previous interactions is crucial for understanding the underlying network and the corresponding dynamics. Usually, any change on individuals of the network will reflect on the pattern of their interaction events. However, the causes and expressed patterns for interaction events on networks have not been properly considered in network models. This article proposes a dynamic model for interaction event networks based on the temporal point process, which aims to incorporate the impact from historical interaction events on later interaction events considering both network structure and node connections. A network representation learning method is developed to learn the interaction event processes. The proposed interaction event network model also provides a convenient representation of the rate of interaction events for any pair of sender–receiver nodes on the network and therefore facilitates monitoring such event networks by summarizing these pairwise rates. Both simulation experiments and experiments on real-world data validate the effectiveness of the proposed model and the corresponding network representation learning algorithm.
Surface currents in operational oceanography: Key applications, mechanisms, and methods

ABSTRACT This paper reviews physical mechanisms, observation techniques and modelling approaches dealing with surface currents on short time scales (hours to days) relevant for operational oceanography. Key motivations for this article include fundamental difficulties in reliable measurements and the persistent lack of a widely held consensus on the definition of surface currents. These problems are augmented by the fact that various methods to observe and model ocean currents yield very different representations of a surface current. We distinguish between four applicable definitions for surface currents; (i) the interfacial surface current, (ii) the direct wind-driven surface current, (iii) the surface boundary layer current, and (iv) an effective drift current. Finally, we discuss challenges in synthesising various data sources of surface currents - i.e. observational and modelling – and take a view on the predictability of surface currents concluding with arguments that parts of the surface circulation exhibit predictability useful in an operational context.
The Harish-Chandra integral: An introduction with examples

This expository paper introduces the theory of Harish-Chandra integrals, a family of special functions that express the integral of an exponential function over the adjoint orbits of a compact Lie group. Originally studied in the context of harmonic analysis on Lie algebras, Harish-Chandra integrals now have diverse applications in many areas of mathematics and physics. We review a number of these applications, present several different proofs of Harish-Chandra’s celebrated exact formula for the integrals, and give detailed derivations of the specific integral formulae for all compact classical groups. These notes are intended for mathematicians and physicists who are familiar with the basics of Lie groups and Lie algebras but who may not be specialists in representation theory or harmonic analysis.
A Global Stochastic Optimization Particle Filter Algorithm

We introduce a new online algorithm for expected log-likelihood maximization in situations where the objective function is multi-modal and/or has saddle points, that we term G-PFSO. The key element underpinning G-PFSO is a probability distribution which (a) is shown to concentrate on the target parameter value as the sample size increases and (b) can be efficiently estimated by means of a standard particle filter algorithm. This distribution depends on a learning rate, where the faster the learning rate the quicker it concentrates on the desired element of the search space, but the less likely G-PFSO is to escape from a local optimum of the objective function. In order to achieve a fast convergence rate with a slow learning rate, G-PFSO exploits the acceleration property of averaging, well-known in the stochastic gradient literature. Considering several challenging estimation problems, the numerical experiments show that, with high probability, G-PFSO successfully finds the highest mode of the objective function and converges to its global maximizer at the optimal rate. While the focus of this work is expected log-likelihood maximization, the proposed methodology and its theory apply more generally for optimizing a function defined through an expectation.
ON DEFORMATION SPACES OF TORIC VARIETIES

Firstly, we see that the bases of the miniversal deformations of isolated Q-Gorenstein toric singularities are quite restricted. In particular, we classify the analytic germs of embedding dimension ≤ 2 which are the bases of the miniversal deformations of isolated Q-Gorenstein toric singularities. Secondly, we show that the deformation spaces of isolated Gorenstein toric 3-fold singularities appear, in a weak sense, as singularities of the K-moduli stack of K-semistable Fano varieties of every dimension ≥ 3. As a consequence, we prove that the number of local branches of the K-moduli stack of K-semistable Fano varieties and of the K-moduli space of K-polystable Fano varieties is unbounded in each dimension ≥ 3.
End-to-End One-Shot Human Parsing

Previous human parsing methods are limited to parsing humans into pre-defined classes, which is inflexible for practical fashion applications that often have new fashion item classes. In this paper, we define a novel one-shot human parsing (OSHP) task that requires parsing humans into an open set of classes defined by any test example. During training, only base classes are exposed, which only overlap with part of the test-time classes. To address three main challenges in OSHP, i.e., small sizes, testing bias, and similar parts, we devise an End-to-end One-shot human Parsing Network (EOP-Net). Firstly, an end-to-end human parsing framework is proposed to parse the query image into both coarse-grained and fine-grained human classes, which embeds rich semantic information that is shared across different granularities to identify the small-sized human classes. Then, we gradually smooth the training-time static prototypes to get robust class representations. Moreover, we employ a dynamic objective to encourage the network enhancing features’ representational capability in the early training phase while improving features’ transferability in the late training phase. Therefore, our method can quickly adapt to the novel classes and mitigate the testing bias issue. In addition, we add a contrastive loss at the prototype level to enforce inter-class distances, thereby discriminating the similar parts. For comprehensive evaluations on the new task, we tailor three existing popular human parsing benchmarks to the OSHP task. Experiments demonstrate that EOP-Net outperforms representative one-shot segmentation models by large margins and serves as a strong baseline for further research.
Enhancing the generalizability of predictive models with synergy of data and physics

Wind farms require predictive models for predictive maintenance. There is a need to predict values of non-observable parameters beyond ranges reflected in available data. A predictive model developed for one machine many not perform well for another similar machine. This is usually due to a lack of generalizability of data-driven models. To increase the generalizability of predictive models, this research integrates data mining with first-principle knowledge. Physics-based principles are combined with machine learning algorithms through feature engineering, strong rules and divide-and-conquer. The proposed synergy concept is illustrated with a wind turbine blade icing prediction and achieves significant predictive accuracy across different turbines. The proposed process should be widely accepted by wind energy predictive maintenance practitioners because of its simplicity and efficiency. Furthermore, the testing scores of KNN, CART and DNN algorithms are increased by 44.78%, 32.72% and 9.13%, respectively, with our proposed process. We demonstrate the importance of embedding physical principles within the machine learning process, and also highlight an important point that the need for more complex machine learning algorithms in industrial big data mining is often much less than it is in other applications, making it essential to incorporate physics and follow the ‘less is more’ philosophy.