Miracle-dz/UniFAR-FTUs huggingface dataset:
Nutrition and Cardiovascular Health

Cardiovascular disease (CVD) is the leading cause of death in Western countries, representing almost 30% of all deaths worldwide. Evidence shows the effectiveness of healthy dietary patterns and lifestyles for the prevention of CVD. Furthermore, the rising incidence of CVD over the last 25 years has become a public health priority, especially the prevention of CVD (or cardiovascular events) through lifestyle interventions. Current scientific evidence shows that Western dietary patterns compared to healthier dietary patterns, such as the ‘Mediterranean diet’ (MeDiet), leads to an excessive production of proinflammatory cytokines associated with a reduced synthesis of anti-inflammatory cytokines. In fact, dietary intervention allows better combination of multiple foods and nutrients. Therefore, a healthy dietary pattern shows a greater magnitude of beneficial effects than the potential effects of a single nutrient supplementation. This review aims to identify potential targets (food patterns, single foods, or individual nutrients) for preventing CVD and quantifies the magnitude of the beneficial effects observed. On the other hand, we analyze the possible mechanisms implicated in this cardioprotective effect.
Comparison of Analytical Approaches Predicting the Compressive Strength of Fibre Reinforced Polymers

Common analytical models to predict the unidirectional compressive strength of fibre reinforced polymers are analysed in terms of their accuracy. Several tests were performed to determine parameters for the models and the compressive strength of carbon fibre reinforced polymer (CFRP) and glass fibre reinforced polymer (GFRP). The analytical models are validated for composites with glass and carbon fibres by using the same epoxy matrix system in order to examine whether different fibre types are taken into account. The variation in fibre diameter is smaller for CFRP. The experimental results show that CFRP has about 50% higher compressive strength than GFRP. The models exhibit significantly different results. In general, the analytical models are more precise for CFRP. Only one fibre kinking model’s prediction is in good agreement with the experimental results. This is in contrast to previous findings, where a combined modes model achieves the best prediction accuracy. However, in the original form, the combined modes model is not able to predict the compressive strength for GFRP and was adapted to address this issue. The fibre volume fraction is found to determine the dominating failure mechanisms under compression and thus has a high influence on the prediction accuracy of the various models.
Association between Atmospheric Particulate Pollutants and Mortality for Cardio-Cerebrovascular Diseases in Chinese Korean Population: A Case-Crossover Study

Background: Air pollution in large Chinese cities has led to recent studies that highlighted the relationship between particulate matters (PM) and elevated risk of cardio-cerebrovascular mortality. However, it is unclear as to whether: (1) The same adverse relations exist in cities with relatively low levels of air pollution; and (2) the relationship between the two are similar across ethnic groups. Methods: We collected data of PM2.5 (PM with an aerodynamic diameter ≤ 2.5 µm) and PM10 (aerodynamic diameter ≤ 10 µm) in the Yanbian Korean Autonomous Prefecture between 1 January 2015 and 31 December 2016. Using a time-stratified case-crossover design, we investigated whether levels of particulate pollutants influence the risk of cardio-cerebrovascular disease mortality among ethnic Korean vs. ethnic Han residents residing in the Yanbian Korean Autonomous Prefecture. Results: Under the single air pollutant model, the odds ratios (ORs) of cardio-cerebrovascular disease were 1.025 (1.024–1.026) for each 10 μg/m3 increase in PM2.5 at lag0 day, 1.012 (1.011–1.013) for each 10 μg/m3 increase in PM10 at lag1 day. In the multi-pollutant model adjusted by PM10, SO2, and NO2, the ORs of cardio-cerebrovascular disease were 1.150 (1.145–1.155) for ethnic Koreans and 1.154 (1.149–1.158) for ethnic Hans for each 10 μg/m3 increase in PM2.5. In the multi-pollutant model adjusted by PM2.5, SO2, and NO2, the ORs of cardio-cerebrovascular disease were 1.050 (1.047–1.053) for ethnic Koreans and 1.041 (1.039–1.043) for ethnic Hans for each 10 μg/m3 increase in PM10. Conclusion: This study showed that PM2.5 and PM10 were associated with increased risks of acute death events in residential cardio-cerebrovascular disease in Yanbian, China.
The current role of clinical flow cytometry in the evaluation of mature B‐cell neoplasms

Flow cytometry (FC) has a well‐established role in the diagnostic evaluation of mature B‐cell neoplasms. Effective assessment for lineage associated antigens, aberrant antigen expression, and immunoglobulin light chain restriction requires a well‐designed, optimized, and controlled FC assay. However, it is important for hematopathologists to know when flow cytometry has a more limited role, and other modalities, such as immunohistochemistry, cytogenetic and molecular testing, are more important. This review will discuss the features of an optimal FC assay for the evaluation of mature B‐cell neoplasms, and the current role of FC in the diagnosis and sub‐classification, prognostic assessment, identification of therapeutic targets, and assessment for disease response to therapy. © 2018 International Clinical Cytometry Society
Expression of the sRNAs CrcZ and CrcY modulate the strength of carbon catabolite repression under diazotrophic or non-diazotrophic growing conditions in Azotobacter vinelandii

Azotobacter vinelandii is a nitrogen-fixing bacterium of the Pseudomonadaceae family that prefers the use of organic acids rather than carbohydrates. Thus, in a mixture of acetate-glucose, glucose is consumed only after acetate is exhausted. In a previous work, we investigated the molecular basis of this carbon catabolite repression (CCR) process under diazotrophic conditions. In the presence of acetate, Crc-Hfq inhibited translation of the gluP mRNA, encoding the glucose transporter in A. vinelandii. Herein, we investigated the regulation in the expression of the small non-coding RNAs (sRNAs) crcZ and crcY, which are known to antagonize the repressing activity of Hfq-Crc. Our results indicated higher expression levels of the sRNAs crcZ and crcY under low CCR conditions (i.e. glucose), in relation to the strong one (acetate one). In addition, we also explored the process of CCR in the presence of ammonium. Our results revealed that CCR also occurs under non-diazotrophic conditions as we detected a hierarchy in the utilization of the supplied carbon sources, which was consistent with the higher expression level of the crcZ/Y sRNAs during glucose catabolism. Analysis of the promoters driving transcription of crcZ and crcY confirmed that they were RpoN-dependent but we also detected a processed form of CrcZ (CrcZ*) in the RpoN-deficient strain derived from a cbrB-crcZ co-transcript. CrcZ* was functional and sufficient to allow the assimilation of acetate.
Frecuencia cardíaca como indicador de estrés calórico en pollos de engorde

Experiments were conducted in a semi-controlled environmental condition, to assess heart rate (HR) as an indicator of heat stress (HS) in broilers. Thirty two broilers (Hubbard) were used. Chickens were identified by sex and were allocated to two treatments: treatment 1 (T1); “hot room” and treatment 2 (T2); “fresh room”. Each group was constituted by 16 broilers (eight males and eight females). Chickens from each treatment were placed in four fences (repetitions) per treatment of four broilers per repetition. The “fresh room” was characterized by a maximum environmental temperature (ET) of 30oC during the experimental phase, while the maximum ET of the “hot room” was 32oC. Both, body temperature (BT) and ET were measured (four times a day) for seven days between 28 and 35 days old. The body weight (BW) and HR (beats/min) was measured on days 28 and 35. The
Quantitative multi-locus metabarcoding and waggle dance interpretation reveal honey bee spring foraging patterns in Midwest agroecosystems

We explored the pollen foraging behavior of honey bee colonies situated in the corn and soybean dominated agroecosystems of central Ohio over a month-long period using both pollen metabarcoding and waggle dance inference of spatial foraging patterns. For molecular pollen analysis we developed simple and cost-effective laboratory and bioinformatics methods. Targeting four plant barcode loci (ITS2, rbcL, trnL and trnH), we implemented metabarcoding library preparation and dual-indexing protocols designed to minimize amplification biases and index mis-tagging events. We constructed comprehensive, curated reference databases for hierarchical taxonomic classification of metabarcoding data and used these databases to train the Metaxa2 DNA sequence classifier. Comparisons between morphological and molecular palynology provide strong support for the quantitative potential of multi-locus metabarcoding. Results revealed consistent foraging habits between locations and show clear trends in the phenological progression of honey bee spring foraging in these agricultural areas. Our data suggest that three key taxa, woody Rosaceae such as pome fruits and hawthorns, Salix, and Trifolium provided the majority of pollen nutrition during the study. Spatially, these foraging patterns were associated with a significant preference for forests and tree lines relative to crop fields and herbaceous land cover.
Epigenetic Targeting of Autophagy via HDAC Inhibition in Tumor Cells: Role of p53

Tumor development and progression is the consequence of genetic as well as epigenetic alterations of the cell. As part of the epigenetic regulatory system, histone acetyltransferases (HATs) and deacetylases (HDACs) drive the modification of histone as well as non-histone proteins. Derailed acetylation-mediated gene expression in cancer due to a delicate imbalance in HDAC expression can be reversed by histone deacetylase inhibitors (HDACi). Histone deacetylase inhibitors have far-reaching anticancer activities that include the induction of cell cycle arrest, the inhibition of angiogenesis, immunomodulatory responses, the inhibition of stress responses, increased generation of oxidative stress, activation of apoptosis, autophagy eliciting cell death, and even the regulation of non-coding RNA expression in malignant tumor cells. However, it remains an ongoing issue how tumor cells determine to respond to HDACi treatment by preferentially undergoing apoptosis or autophagy. In this review, we summarize HDACi-mediated mechanisms of action, particularly with respect to the induction of cell death. There is a keen interest in assessing suitable molecular factors allowing a prognosis of HDACi-mediated treatment. Addressing the results of our recent study, we highlight the role of p53 as a molecular switch driving HDACi-mediated cellular responses towards one of both types of cell death. These findings underline the importance to determine the mutational status of p53 for an effective outcome in HDACi-mediated tumor therapy.
Sensory coding is impaired in rat absence epilepsy

Absence epilepsy is characterized by the occurrence of spike‐and‐wave discharges concomitant with an alteration of consciousness and is associated with cognitive comorbidities. In a genetic model of absence epilepsy in the rat, the genetic absence epilepsy rat from Strasbourg (GAERS), spike‐and‐wave discharges are shown to be initiated in the barrel field primary somatosensory cortex that codes whisker‐related information, therefore playing an essential role in the interactions of rodents with their environment. Sensory‐information processing is impaired in the epileptic barrel field primary somatosensory cortex of GAERS, with a delayed sensory‐evoked potential and a duplicated neuronal response to whisker stimulation in in vivo extracellular recordings. Yet, GAERS present no defaults of performance in a texture discrimination task, suggesting the existence of a compensatory mechanism within the epileptic neuronal network. The results of the present study indicate that physiological primary functions are processed differently in an epileptic cortical network.
The Primary Causes of Muscle Dysfunction Associated with the Point Mutations in Tpm3.12; Conformational Analysis of Mutant Proteins as a Tool for Classification of Myopathies

Point mutations in genes encoding isoforms of skeletal muscle tropomyosin may cause nemaline myopathy, cap myopathy (Cap), congenital fiber-type disproportion (CFTD), and distal arthrogryposis. The molecular mechanisms of muscle dysfunction in these diseases remain unclear. We studied the effect of the E173A, R90P, E150A, and A155T myopathy-causing substitutions in γ-tropomyosin (Tpm3.12) on the position of tropomyosin in thin filaments, and the conformational state of actin monomers and myosin heads at different stages of the ATPase cycle using polarized fluorescence microscopy. The E173A, R90P, and E150A mutations produced abnormally large displacement of tropomyosin to the inner domains of actin and an increase in the number of myosin heads in strong-binding state at low and high Ca2+, which is characteristic of CFTD. On the contrary, the A155T mutation caused a decrease in the amount of such heads at high Ca2+ which is typical for mutations associated with Cap. An increase in the number of the myosin heads in strong-binding state at low Ca2+ was observed for all mutations associated with high Ca2+-sensitivity. Comparison between the typical conformational changes in mutant proteins associated with different myopathies observed with α-, β-, and γ-tropomyosins demonstrated the possibility of using such changes as tests for identifying the diseases.
Method based on bitonic filtering decomposition and sparse representation for fusion of infrared and visible images

Infrared and visible images fusion based on edge-preserving can improve the fused result in a clear outline. However, there exists the performance degradation caused by some edges in the data which are smaller than the level of the noise with traditional edge-preserving decomposition. To remedy such deficiency, a method based on bitonic filtering decomposition and sparse representation is proposed for fusion of infrared and visible images. The bitonic filtering decomposition and sparse representation (BFSR) method consists of three steps: multi-scale bitonic filtering decomposition, mergence of base layers and detail layers, and reconstruction of the fused result. Compared with traditional image fusion based on edge-preserving, data-level-sensitive parameters are not included in the BFSR method, which can locally adapt to the signal and noise levels in an image. Moreover, the sparsity of images for fusing details is used in the BFSR method, which can analyse the explanatory factors hidden behind the data. As demonstrated in the experimental results, the proposed BFSR method achieves much fusion performance compared with other commonly used image fusion methods.
GVANET project: an efficient deployment of a self-powered, reliable and secured VANET infrastructure

The aim of this study is to describe the authors' efforts to accomplish the green vehicular ad hoc network (GVANET) project. The goal is to realise the concept of a self `renewably' powered communication infrastructure appropriate for intelligent transportation systems. The work in this project was started in 2009 with the intention of representing the necessary steps must be taken to achieve such system and to declare the usefulness of adopting environmental energy resources in building mission critical systems. The other objectives of this project are presenting a reasonably cost, reliable, secured and easy to install communication infrastructure. Their plan to implement the GVANET was achieved after passing two design levels: device level and system level. In the device level, they suggest that the architecture of a road side unit (RSU) must be enhanced to maintain its robustness and availability against the different failure events which may occur due to many reasons such as power supply shortage or denial of service attacks. The design philosophy in the system level concentrates on building a sustainable, secured, reliable and scalable communication infrastructure to solve the different systematic problems raised when implementing the RSU as a member of the GVANET.
TensorFlow.jl: An Idiomatic Julia Front End for TensorFlow

TensorFlow.jl is a Julia ((Bezanson, Edelman, Karpinski, & Shah, 2017)) client library for the TensorFlow deep-learning framework ((Abadi et al., 2015),(Abadi et al., 2016)). It allows users to define TensorFlow graphs using Julia syntax, which are interchangeable with the graphs produced by Google’s first-party Python TensorFlow client and can be used to perform training or inference on machine-learning models.
Tadao Ando: Complete Works

Introductory essay by Francesco dal Co - 115 projects and built works from 1969-1994 - Writings by Tadao Ando - Interview with Hiroshi Maruyama - Anthology of critical essays by: Vittorio Gregotti - Kiyoshi Takeyama - Kenneth Frampton - Peter Eisenman - Gioranao Tironi - Darrell Wayne Fields - Francois Chaslin - Tom Heneghan - Fredric Jameson - Vittorio Magnago Lampugnani - Yuzuru Tominaga - Biographical Note - Bibliography - List of Works
Electricity Theft Detection Using Generative Models

Advanced metering infrastructure (AMI) plays an important role in smart grid. On one hand, AMI makes the smart grid more vulnerable to cyber attacks. On the other hand, large amount of available usage data helps detect energy thefts using machine learning methods. In this paper, we focus on energy theft that results in customer usage pattern change in utility database. To overcome the imbalance problem between normal and anomaly behavior data, we propose an anomaly detection framework called semi-supervised generative Gaussian mixture model, which can be controlled with detection indicator thresholds to adjust the intensity of detection. Human knowledge is successfully introduced into the model using detection indicators. We analyze it with various machine learning based methods including one-class SVM and autoencoder, and show that our framework has the most effective performance validated by simulation that is based on real-world energy consumption data.
Spectra and satisfiability for logics with successor and a unary function

We investigate the expressive power of two logics, both with the successor function: first‐order logic with an uninterpreted function, and existential monadic second order logic—that is first‐order logic over words—, with multiplication by a constant b. We prove that all b‐recognizable sets are spectra of those logics. Furthermore, it is proven that some encoding of the set of halting times of a non‐deterministic 2‐counter automaton is also a spectrum. This yields undecidability of the finite satisfiability problem for those logics. Finally, it is shown that first‐order logic with one uninterpreted function and successor can encode quickly increasing functions, such as the Knuth's up‐arrows.
Opportunistic Diversity-Based Detection of Injection Attacks in Web Applications

Web-based applications delivered using clouds are becoming increasingly popular due to less demand of client-side resources and easier maintenance than desktop counterparts. At the same time, larger attack surfaces and developers’ lack of security proﬁciency or awareness leave Web applications particularly vulnerable to security attacks. On the other hand, diversity has long been considered as a viable approach to detecting security attacks since functionally similar but internally di ﬀ erent variants of an application will likely respond to the same attack in di ﬀ erent ways. However, most diversity-by-design approaches have met di ﬃ culties in practice due to the prohibitive cost in terms of both development and maintenance. In this work, we propose to employ opportunistic diversity inherent to Web applications and their database backends to detect injection attacks. We ﬁrst conduct a case study of common vulnerabilities to conﬁrm the potential of opportunistic diversity for detecting potential attacks. We then devise a multi-stage approach to examine features extracted from the database queries, their e ﬀ ect on the database, the query results, as well as the user-end results. Next, we combine the partial results obtained from di ﬀ erent stages using a learning-based approach to further improve the detection accuracy. Finally, we evaluate our approach using a real world Web application.
Deep learning features for robust facial kinship verification

Facial automatic kinship verification is a novel challenging research problem in computer vision. It performs the automatic examining of the facial attributes and expecting whether two persons have a biological kin relation or not. In this study, the authors introduce a novel learning method for kinship verification which consists of four main stages. (i) A discrete cosine transform network (DCTNet) applied to each face image in order to extract the most significant inherited facial features through convolutional layers based on 2D DCT filter bank. (ii) The response of the last layer is binarised and partitioned into non-overlapping block-wise histograms. (iii) A tied rank normalisation is used to eliminate the disparity of histogram vectors of DCTNet. (iv) The last stage is to distinguish between the different pairs. The distances between data points in the same classes (positive pairs) are as small as possible, while the distances are as large as possible between data points in different classes (negative pairs). Experiments are conducted on three public databases (UBKinFace, KinFaceW-I, and KinFaceW-II). They show significant performance improvements compared to state-of-the-art methods.
Eucalypglobulusals A-J, Formyl-Phloroglucinol-Terpene Meroterpenoids from Eucalyptus globulus Fruits.

Ten new formyl-phloroglucinol-terpene meroterpenoids, eucalypglobulusals A-J (1-10), and ten known analogues were isolated from Eucalyptus globulus fruits. The structures of 1-10 were determined by spectroscopic analysis, while their absolute configurations were established using calculated and experimental electronic circular dichroism (ECD) spectra. Eucalypglobulusal A was assigned as a new formyl-phloroglucinol-terpene meroterpenoid with a rearranged sesquiterpene skeleton, and an aldol condensation between C-3 and C-5 of the germacrene C moiety was proposed to be a key step in its putative biosynthetic pathway. Eucalypglobulusal F exhibited cytotoxicity against the human acute lymphoblastic cell line (CCRF-CEM) with an IC50 value of 3.3 μM, while eucalypglobulusal A, eucarobustol C, macrocarpal A, macrocarpal B, and macrocarpal D exhibited DNA topoisomerase I (Top1) inhibition. The compounds eucalypglobulusal A and macrocarpal A act as Top1 catalytic inhibitors and delay Top1 poison-mediated DNA double-strand damage.