Miracle-dz/UniFAR-FTUs huggingface dataset:
A Rare Occurrence: Crohn’s Disease Associated with Pemphigus Vulgaris

Crohn’s disease is a chronic inflammatory bowel disease with an unknown etiology that may affect any segment of the digestive tract, from the oropharyngeal to the perianal region. It is characterized by a discontinuous and transmural pattern of inflammation that involves all tissue layers of the digestive tract. Common mucocutaneous manifestations of Crohn’s disease involve erythema nodosum and erythema multiforme. Pemphigus vulgaris is a chronic autoimmune mucocutaneous disease, caused by an autoimmune mechanism in which antibodies against desmoglein 1 and desmoglein 3, disrupt the normal components of the keratinocyte cell membrane. It represents the most common and most serious type of pemphigus. It manifests, initially, with blisters and erosions on the oral mucosa, with subsequent lesions and intraepithelial vesicles on other mucous and cutaneous surfaces and eventually, entire body dissemination. We present a case of a patient with a decade-long history of Pemphigus Vulgaris, in whom Crohn’s disease was diagnosed 10 years later.
An Explicit Discrete-Time Large- and Small-Signal Modeling of the Dual Active Bridge DC–DC Converter Based on the Time Scale Methodology

The conventional method to model a dc–dc converter is by averaging its state variable over a switching period. However, due to the dc–ac–dc structure of the dual active bridge converter (DABC), the average value of the inductor current over a switching cycle is zero. Therefore, the conventional methodology cannot be applied to the DABC. The time-scale discrete-time modeling of the DABC is proposed to mitigate the zero average state variable problem. The time-scale methodology simplifies the analysis of the DABC by segregating the fast state variable inductor current and slow state variable output voltage. The proposed model has the advantage of the explicit large signal in terms of the circuit parameter, like the average value model. The explicit steady-state circuit expression from the large-signal model helps in the study of the soft-switching range of the DABC. Moreover, the small-signal model from the proposed method results in an explicit small-signal model. The model incorporates semiconductor on-resistance, inductor equivalent series resistance, transformer resistance, and leakage inductance. The effect of the converter net equivalent resistance on the small-signal model is thoroughly studied. Finally, the model accuracy in the steady-state, open-loop, and the small-signal are verified in both the switching simulation model and experimental setup.
Invariance Matters: Exemplar Memory for Domain Adaptive Person Re-Identification

This paper considers the domain adaptive person re-identification (re-ID) problem: learning a re-ID model from a labeled source domain and an unlabeled target domain. Conventional methods are mainly to reduce feature distribution gap between the source and target domains. However, these studies largely neglect the intra-domain variations in the target domain, which contain critical factors influencing the testing performance on the target domain. In this work, we comprehensively investigate into the intra-domain variations of the target domain and propose to generalize the re-ID model w.r. t three types of the underlying invariance, i.e., exemplar-invariance, camera-invariance and neighborhood-invariance. To achieve this goal, an exemplar memory is introduced to store features of the target domain and accommodate the three invariance properties. The memory allows us to enforce the invariance constraints over global training batch without significantly increasing computation cost. Experiment demonstrates that the three invariance properties and the proposed memory are indispensable towards an effective domain adaptation system. Results on three re-ID domains show that our domain adaptation accuracy outperforms the state of the art by a large margin. Code is available at: https://github.com/zhunzhong07/ECN
Model Slicing for Supporting Complex Analytics with Elastic Inference Cost and Resource Constraints

Deep learning models have been used to support analytics beyond simple aggregation, where deeper and wider models have been shown to yield great results. These models consume a huge amount of memory and computational operations. However, most of the large-scale industrial applications are often computational budget constrained. In practice, the peak workload of inference service could be 10x higher than the average cases, with the presence of unpredictable extreme cases. Lots of computational resources could be wasted during off-peak hours and the system may crash when the workload exceeds system capacity. How to support deep learning services with dynamic workload cost-efficiently remains a challenging problem. In this paper, we address the challenge with a general and novel training scheme called model slicing , which enables deep learning models to provide predictions within the prescribed computational resource budget dynamically. Model slicing could be viewed as an elastic computation solution without requiring more computational resources. Succinctly, each layer in the model is divided into groups of contiguous block of basic components (i.e. neurons in dense layers and channels in convolutional layers), and then partially ordered relation is introduced to these groups by enforcing that groups participated in each forward pass always starts from the first group to the dynamically-determined rightmost group. Trained by dynamically indexing the rightmost group with a single parameter slice rate , the network is engendered to build up group-wise and residual representation. Then during inference, a sub-model with fewer groups can be readily deployed for efficiency whose computation is roughly quadratic to the width controlled by the slice rate. Extensive experiments show that models trained with model slicing can effectively support on-demand workload with elastic inference cost.
Credibility distribution based R-norm fuzzy information measures in noiseless coding theorems

ABSTRACT In the present communication, a parametric R-norm fuzzy entropy of a fuzzy variable and subsequently R-norm fuzzy directed divergence measure of fuzzy variables by taking the credibility distribution measure into account have been proposed along with their proof of validity. Based on the proposed information measures, some new results along with its various properties and the monotonic behavior have been studied in detail. Further, some important results and inequalities related to their corresponding noiseless coding theorems have been well established. Some particular cases related to the proposed fuzzy information measures and fuzzy mean codeword length in terms of existing results have also been discussed. In view the monotonic behavior of the fuzzy mean codeword length, an application to chose the appropriate value of the parameter R to reduce the fuzzy mean codeword length significantly for optimal code has been presented with a possible variability.
The Effect of Dark Matter–Dark Radiation Interactions on Halo Abundance: A Press–Schechter Approach

We study halo mass functions with the Press–Schechter formalism for interacting dark matter models, where matter power spectra are damped due to dark acoustic oscillations in the early universe. After adopting a smooth window function, we calibrate the analytical model with numerical simulations from the “effective theory of structure formation” (ETHOS) project and fix the model parameters in the high-mass regime, Mh ≳ 3 × 1010 M⊙. We also perform high-resolution cosmological simulations with halo masses down to Mh ∼ 108 M⊙ to cover a wide mass range for comparison. Although the model is calibrated with ETHOS1 and cold dark matter simulations for high halo masses at redshift z = 0, it successfully reproduces simulations for two other ETHOS models in the low-mass regime at low and high redshifts. As an application, we compare the cumulative number density of halos to that of observed galaxies at z = 6, and find that the interacting dark matter models with a kinetic decoupling temperature below 0.5 keV is disfavored. We also perform the abundance-matching analysis and derive the stellar–halo mass relation for these models at z = 4. Suppression in halo abundance leads to less massive halos that host observed galaxies in the stellar mass range M * ≃ 10 5 – 10 7 M ⊙ .
A Set of Experience-Based Smart Synergy Security Mechanism in Internet of Vehicles

Abstract In this article, we introduce a novel security mechanism, the Smart Synergy Security (3S). The mechanism uses the Set of Experience Knowledge Structure (SOEKS) and the synergy of security methods in different domains to provide the global optimal security strategy. The proposed strategy is taking into account the characteristics of information security (i.e. confidentiality, integrity, availability, controllability, and reviewability) imposed in different domains in Internet of Vehicles (IoV). The SOEKS is used to represent knowledge, and is combined with the data flow in each domain. Initial experiments demonstrate that the proposed approach is able to find the optimal solution under different conditions for multi-domain security problems in IoV.
Automatically Generating Complete Reading Level Metadata

Digital library collections usually hold resources describing a limited set of topics spanning a wide range of reading levels, requiring complete reading level metadata to filter relevant resources from the collection. In order to suggest the reading level for all resources in the test collection, we propose an SVM-based classification tool which predicts the specific reading level with an F-Measure of 0.70 for all resources, outperforming other classification methods and readability formulas under evaluation. To measure the impact of reading level metadata completeness on retrieval performance, a knowledge based system retrieves documents from three collections containing different reading level completeness: one with complete reading level information generated by the proposed SVM method, one missing all reading level information, and the final collection containing limited, human-expert provided metadata. The dataset with automatically identified complete reading level exceeds the performance of collection-provided reading level metadata for all five sample tasks.
Generalization of a class of cyclic inequalities

While studying Cvetkovski’s book ”Inequalities: Theorems, Techniques and Selected Problems”, we noticed a pattern from several three variable cyclic inequalities with sums of fractions. Using mathematical induction and AM-GM inequality, we proved our assertion of this pattern. We also used rearrangement inequality, Chebyshev’s sum inequality and a weighted Hölder’s inequality to generalize our results to the case when the exponents in these fractions are positive real numbers. Mathematics Subject Classification: 26D15
On the capacity dimension of the boundary of CAT(0) spaces

In this paper, we study the capacity dimension of the boundary of $CAT(0)$ spaces. We first compare the two metrics on the boundary of a hyperbolic $CAT(0)$ space, i.e., the visual metric and Moran's metric, and prove that they give the same capacity dimension of the boundary. Then we study the capacity dimension of the boundary of buildings, which is an important class of $CAT(0)$ spaces. Finally, we give a possible method to prove the finiteness of the asymptotic dimension of $CAT(0)$ spaces.
Forests and their importance in the global carbon and nitrogen balance – a review with reflections

Carbon (C) and reactive nitrogen (Nr) are two elements increasing in the Biosphere due to human activity. CO2 in atmosphere is increasing due to deforestation for at least 150 years, and burning of fossil fuels since about 100 years at an increasing speed. C is a dominating element in Biosphere, and the biggest stores of C appear in forest biomass and forest soils. The forest growth per hectare has increased, due to increases of CO2, temperature and Nr-deposition, but total global C-sequestration in forests has nevertheless decreased due to deforestation and burning, and in spite many new plantations. Nr is the limiting element for growth in most forests, but is found in much lower amounts as C, usually in specific C/N-relations. Estimates suggest on an average 40 times less Nr in forest ecosystems compared to C. The Nr fluxes and accumulation has increased relatively much more than the C-fluxes, which significantly supported the C-sequestration in forests. In future both CO2 increase (associated with temperature increase), and N-deposition are suggested to increase even more, and this might have detrimental effects on tree species and the whole forest ecosystem, especially in the temperate zones.
Defeats GAN: A Simpler Model Outperforms in Knowledge Representation Learning

The goal of knowledge representation learning is to embed entities and relations into a low-dimensional, continuous vector space. How to push a model to its limit and obtain better results is of great significance in knowledge graph's applications. We propose a simple and elegant method, Trans-DLR, whose main idea is dynamic learning rate control during training. Our method achieves remarkable improvement, compared with recent GAN-based method. Moreover, we introduce a new negative sampling trick which corrupts not only entities, but also relations, in different probabilities. We also develop an efficient way, which fully utilizes multiprocessing and parallel computing, to speed up evaluation of the model in link prediction tasks. Experiments show that our method is effective.
An Evaluation of Container Ports in China and Korea with the Analytic Hierarchy Process

Since China adopted its liberalized economic policy, the average growth rate of Chinese economy has exceeded 10% per annum. Especially, port development and advancement in China are conspicuous in the case which refers to import and export, as China handles approximately 90% of the relevant cargo by relying upon maritime transport. Such remarkable growth in China gives an impetus to Korean ports, since both China and Korea are located at the same region in Northeast Asia, and the two lie in direct competition. In this respect, the purpose of this study is to figure out the order of competitive power of container ports, which are situated on China's east and south coasts, even including ports of Korea. The Analytic Hierarchy Process(AHP) method has been adopted as the methodology of this study, which is a method of problem solving-decision making.
First-harmonic diffusion-based model applied to a polyvinyl-alcohol- acrylamide-based photopolymer

The photopolymerization diffusion models give accurate comprehension of the mechanism of hologram formation inside photopolymer materials. Although several models have been proposed, these models share the common assumption that there is an interplay between the processes of monomer polymerization and monomer diffusion. Nevertheless, most of the studies to check the validity of the theoretical models have been done by using photopolymers of the DuPont™ type, or photopolymer materials with values of the monomer diffusion time similar to those of the DuPont material. We check the applicability of a modified diffusion-based model to a polyvinyl alcohol–acrylamide photopolymer. This material has the property of longer diffusion times for the monomer to travel from the unexposed to the exposed zones than in the case of other polymeric materials. Some interesting effects are observed and theoretically treated by using the modified first-harmonic diffusion-based model we propose.
Influence of Service Quality of Agricultural Products E-Commerce Platform on Customer Loyalty - The Mediating Role of Customer Engagement

With the popularity of computer networks and advances in information technology, online shopping has become a major way. The net purchase of agricultural products is becoming a new growth trend. The speed of China's agricultural development of the electronic business platform is very fast, from the customer's perspective on how to improve the experience and level of service of the electronic business platform to achieve engagement and loyalty, become the focus of attention of scholars. Existing research results show that electronic service quality directly affects customer loyalty. Based on existing theory, this paper focuses on the influence of electronic service quality and customer loyalty. At the same time, customer engagement is also considered and together established a new model. The empirical test is conducted by using the data processing software SPSS 26.0 and AMOS 24.0 to analyze the 433 questionnaires gained from random interviews and online fill out. AMOS (version 24.0) was used to estimate both the measurement and structural models. The test shows that the electronic service quality (process quality, outcome quality, recovery quality) has a prominent positive effect on customer engagement and so does the engagement to loyalty. Service recovery quality can not only directly affect customer loyalty, but also indirectly affect customer loyalty through customer engagement, while service process quality and service result quality affect customer loyalty through customer engagement. On one hand, these theories rich the traditional customer relation model by introducing customer engagement as an intervening variable, which is more correspondent to the current online shopping environment. On the other hand, this paper is conducted with the premier of electronic agriculture product business background, the result can supply some practical management advice for developing customer loyalty in this field. This paper takes the e-commerce platform of agricultural products as the research object, verifies the strengthening effect of service quality on customer loyalty, and predicts customer loyalty through the fit between service quality and customer. The research results provide ideas and theoretical guidance for the development of customer loyalty on the e-commerce platform of agricultural products, and also lay a foundation for the further maintenance of loyal customers, which has certain guiding significance. This paper analyzes the different dimensions of service quality of agricultural products e-commerce platform and the influence path of customer loyalty through customer engagement. Although the research of this paper extends the research of customer loyalty of agricultural products e-commerce platform to a certain extent, there are still the following deficiencies, and as the direction of further research.
Mesons with beauty and charm: New horizons in spectroscopy

The $B_c ^+$ family of $(c\bar{b})$ mesons with beauty and charm is of special interest among heavy quarkonium systems. The $B_c ^+$ mesons are intermediate between $(c\bar{c})$ and $(b\bar{b})$ states both in mass and size, so many features of the $(c\bar{b})$ spectrum can be inferred from what we know of the charmonium and bottomonium systems. The unequal quark masses mean that the dynamics may be richer than a simple interpolation would imply, in part because the charmed quark moves faster in $B_c$ than in the $J/\psi$. Close examination of the $B_c ^+$ spectrum can test our understanding of the interactions between heavy quarks and antiquarks and may reveal where approximations break down.
Practical Ray Tracing

In 1979, Turner Whitted [Whitted 1980] revolutionised our thinking about high quality picture production. He didn't actually invent ray tracing, but he suggested a practical illumination model that made synthetic images of photographic quality easy to compute from basic geometrical models. The images produced by ray tracers typically show variation of shading on curved surfaces, shadows and reflections. Because of the high quality of these images, a lot of people have wrongly gained the impression that ray tracing is 'difficult'. It is easier to write a ray tracer than a Z-buffer or A-buffer rendering system. The real cost of ray traced images is in the computer time needed to create them and even this is not as great as is popularly supposed.
Balance in social support exchange and discontinuation of young-old’s personal relationships in three birth cohorts

Societal changes and an increase in personal resources are likely to have an impact on the personal relationships of cohorts coming of age. We expect that, in recent times, (1) relationships more often strike a balance in exchanged instrumental and emotional support and (2) relationships are discontinued more often when there is no balance in exchanged instrumental and emotional support, particularly among nonkin. We compare three birth cohorts from the Longitudinal Aging Study Amsterdam, aged 55–64 years at baseline (early cohort: born in 1928–1937, interviewed in 1992; middle cohort: born in 1938–1947, interviewed in 2002; late cohort: born in 1948–1957, interviewed in 2012). The results indicate that, in the middle and late birth cohorts, personal relationships are more often characterized by a balance in social support exchanges compared to the early cohort. No cohort differences in the effect of balance on relationship discontinuation are observed. The results suggest increased opportunities and preferences of young-olds to maintain balance in their personal relationships.
Population genetic analysis of two Polylepis microphylla (Wedd.) Bitter (Rosaceae) forests in Ecuador

ABSTRACT Habitat fragmentation is a severe problem that negatively affects forests around the world. This phenomenon has consequences at a genetic level in populations such as genetic diversity and gene flow reduction. As a result, population fitness decreases, and the possibility of extinction increases. Polylepis (Rosaceae) forests are endemic to the Andes and their distribution reflects hundreds of years of human activities. Polylepis microphylla is the most endangered species of the genus in Ecuador and is represented by only two known forests in Chimborazo province, separated from each other by 1,6 km. The present study focused on i) exploring the genetic structure and connectivity, ii) analyzing the genetic diversity patterns in these two forests of P. microphylla. Parameters such as Fixation index, molecular variance (AMOVA) and genetic diversity estimators were calculated from the haplotypic sequences of one chloroplastic DNA region (trnG intron), one nuclear DNA region (ITS), and the concatenation of both. We found that DNA regions used were highly polymorphic with a total of nine, four and thirteen segregation sites, respectively, and nine, six and fifteen haplotypes, respectively. Also, we detected that both forest work as a single population unit due to low fixation index values (Fst = 0,03822, −0,03883 and −0,00469, respectively), which indicate high gene flow between these two forests. In addition, we detected high genetic diversity reflected by haplotype diversity in both forest (hd = 0,54204, 0,63664 and 0,81682, respectively). Likewise, haplotype relationships were visualized in networks, which demonstrated limited spatial structuring between haplotypes, corroborating the low genetic differentiation among these forests. In conclusion, our results suggest there is a single population unit of P. microphylla in Ecuador. Habitat fragmentation does not seem to have negative effects on the genetic diversity of this species. Nevertheless, the species may be vulnerable to rapid environmental fluctuations despite having relatively high genetic diversity. Its long generational time causes increased susceptibility of P. microphylla to environmental changes and may eventually lead to the extinction of the species in Ecuador.