Miracle-dz/UniFAR-FTUs huggingface dataset:
Exopolysaccharides of Lactic Acid Bacteria: Production, Purification and Health Benefits towards Functional Food

Lactic acid bacteria (LAB) are capable of synthesising metabolites known as exopolysaccharides (EPS) during fermentation. Traditionally, EPS plays an important role in fermented dairy products through their gelling and thickening properties, but they can also be beneficial to human health. This bioactivity has gained attention in applications for functional foods, which leads them to have prebiotic, immunomodulatory, antioxidant, anti-tumour, cholesterol-lowering and anti-obesity activity. Understanding the parameters and conditions is crucial to optimising the EPS yields from LAB for applications in the food industry. This review provides an overview of the functional food market together with the biosynthesis of EPS. Factors influencing the production of EPS as well as methods for isolation, characterisation and quantification are reviewed. Finally, the health benefits associated with EPS are discussed.
Delivery of miR-654-5p via SonoVue Microbubble Ultrasound Inhibits Proliferation, Migration, and Invasion of Vascular Smooth Muscle Cells and Arterial Thrombosis and Stenosis through Targeting TCF21

Background Abnormal proliferation of vascular smooth muscle cells (VSMCs) is an important cause of vascular stenosis. The study explored the mechanism of inhibition of vascular stenosis through the molecular mechanism of smooth muscle cell phenotype transformation. Methods Coronary heart disease-related genes were screened by bioinformatics, and the target genes of miR-654-5p were predicted by dual-luciferase method and immunofluorescence method. miR-654-5p mimic stimulation and transfection of TCF21 and MTAP into cells. SonoVue microbubble sonication was used to deliver miR-654-5p into cells. Cell proliferation, migration, and invasion were detected by CCK-8, wound scratch, and Transwell. HE and IHC staining were performed to study the effect of miR-654-5p delivery via SonoVue microbubble ultrasound on vessel stenosis in a model of arterial injury. Gene expression was determined by qRT-PCR and WB. Results TCF21 and MTAP were predicted as the target genes of miR-654-5p. Cytokines induced smooth muscle cell proliferation, migration, and invasion and promoted miR-654-5p downregulation; noticeably, downregulated miR-654-5p was positively associated with the cell proliferation and migration. Overexpression of TCF21 promoted proliferation, invasion, and migration, and mimic reversed such effects. miR-654-5p overexpression delivered by SonoVue microbubble ultrasound inhibited proliferation, migration, and invasion of cells. Moreover, in arterial injury model, we found that SonoVue microbubble ultrasound transmitted miR-654-5p into the arterial wall to inhibit arterial thrombosis and stenosis, while TCF21 was inhibited. Conclusion Ultrasound delivery of miR-654-5p via SonoVue microbubbles was able to inhibit arterial thrombosis and stenosis by targeting TCF21.
Beyond N staging in colorectal cancer: Current approaches and future perspectives

Traditionally, lymph node metastases (LNM) evaluation is essential to the staging of colon cancer patients according to the TNM (tumor–node–metastasis) system. However, in recent years evidence has accumulated regarding the role of emerging pathological features, which could significantly impact the prognosis of colorectal cancer patients. Lymph Node Ratio (LNR) and Log Odds of Positive Lymph Nodes (LODDS) have been shown to predict patients’ prognosis more accurately than traditional nodal staging and it has been suggested that their implementation in existing classification could help stratify further patients with overlapping TNM stage. Tumor deposits (TD) are currently factored within the N1c category of the TNM classification in the absence of lymph node metastases. However, studies have shown that presence of TDs can affect patients’ survival regardless of LNM. Moreover, evidence suggest that presence of TDs should not be evaluated as dichotomic but rather as a quantitative variable. Extranodal extension (ENE) has been shown to correlate with presence of other adverse prognostic features and to impact survival of colorectal cancer patients. In this review we will describe current staging systems and prognostic/predictive factors in colorectal cancer and elaborate on available evidence supporting the implementation of LNR/LODDS, TDs and ENE evaluation in existing classification to improve prognosis estimation and patient selection for adjuvant treatment.
Systemic autoinflammatory diseases in pediatric population

Background Systemic autoinflammatory diseases (SAID) are monogenic and polygenic inherited conditions characterized by dysregulation of the innate immune system. Objective We aimed to characterize the clinical features of patients with SAID. Methods This study was a retrospective chart review on the clinical and genetic features of the pediatric population with SAID observed from 1998 to 2020 in our center. Results A total of 54 patients were evaluated: 18 with periodic fever, aphthous stomatitis, pharyngitis and adenitis syndrome; 16 with Behçet disease; 13 with systemic juvenile idiopathic arthritis; 4 with syndrome of undifferentiated recurrent fever; 1 with cryopyrin associated periodic syndrome; 1 with chronic nonbacterial osteomyelitis; and 1 with Muckle-Wells syndrome. Conclusion The analysis of clinical features of our patients are similar to other studies. Our goal was to aware the medical community to early recognize and treat SAID to improve quality of life of pediatric patients.
Cross and intraband luminescence of CsCl crystals

An investigation was made of cross luminescence of CsCl, associated with radiative transitions representing recombination of electrons from the 3pCl − valence band with holes from the 5pCs + cation band created by excitation, and also of luminescence observed in the range from 7.3 to 1.7 eV and associated with radiative transitions inside the conduction band. The investigation was carried out in a wide spectral range at temperatures from 5 to 750 K by excitation with ultraviolet radiation, x rays, or nanosecond pluses of an electron beam. The cross luminescence spectrum exhibited abrupt changes in the region of a structural transition (at 740 K) from the body-centered to the face-centered lattice. The nature of other types of fast-response luminescence emitted from CsCl was analyzed
Impact of Snowpack on the Land Surface Phenology in the Tianshan Mountains, Central Asia

The accumulation and ablation processes of seasonal snow significantly affect the land surface phenology in a mountainous ecosystem. However, the ability of snow to regulate the alpine land surface phenology in the arid regions is not well described in the context of climate change. The impact of snowpack changes on land surface phenology and its driving factors were investigated in the Tianshan Mountains using the land surface phenology metrics derived from satellited products and a snow dataset from downscaled regional climate model simulations covering the period from 1983 to 2015. The results demonstrated that the annual mean start of growing season (SOS) and length of growing season (LOS) experienced a significant (p < 0.05) decrease and increase with a rate of −2.45 days/decade and 2.98 days/decade, respectively. The significantly advanced SOS and increased LOS were mainly seen in the Western Tianshan Mountains and Ili Valley regions with elevations from 2500 to 3500 m a.s. l and below 3000 m a.s. l, respectively. During the early spring, the significant decline in snow cover fraction (SCF) could advance the SOS. In contrast, snowmelt amount and annual maximum snow water equivalent (SWE) have an almost equally substantial positive correlation with annual maximum vegetation greenness. In particular, the SOS of grassland was the most sensitive to variations of snow cover fraction during early spring than that of other vegetation types, and their strong relationship was mainly located at elevations from 1500 to 2500 m a.s. l. Its greenness was significantly controlled by the annual maximum snow water equivalent in all elevation bands. Both decreased SCF and increased temperature in the early spring caused a significant advance of the SOS, consequently prolonging the LOS. Meanwhile, more SWE and snowmelt amount could significantly promote vegetation greenness by regulating the soil moisture. The results can improve the understanding of the snow ecosystem services in the alpine regions under climate change.
Anisotropic cosmological model created by quantum polarization of vacuum

A homogeneous anisotropic nonsingular space-time metric with a six-parameter symmetry group is found which can be created by the polarization of the vacuum of the quantum fields of matter by a self-consistent gravitational field in the absence of classical matter. The mean values of the energy-momentum tensors for massless conformally covariant fields and a massive scalar field are computed in this metric. The Green function for a massive scalar field is constructed.
Consequences-based graphical model for contextualized occupants’ activities estimation in connected buildings

Recently, many stochastic models have been proposed to better estimate the activities of occupants with the aim of reducing the discrepancy between estimated and actual energy consumption in residential buildings. However, these models are hybrid. They mix statistical data from different contexts that make them difficult to verify for a particular household. This contribution proposes a general approach, which takes into account particular contexts, to estimate contextualized activities, which denote activities in a specific household’s contexts. Specifically, a mobile application is developed to collect the information of activities from occupants in their house. Information Gain is used to determine major features from measured data and context information. Then, a consequences-based Bayesian Network (CBBN) with an expert structure is built to estimate contextualized occupant activities. Finally, a case study is presented with three activities cooking breakfast , cooking lunch , and cooking dinner . The results show that these activities are related not only to the time of a day but also to the movements of occupants and the usages of electrical appliances, which are involved frequently during these activities’ duration.
The efforts towards development of an energy efficiency upgrade platform

This contribution presents the efforts towards the development of an energy assessment platform to assist building engineers, energy managers, policy makers, etc., evaluate the best revenue options from energy conservation investments in commercial buildings. Portfolio assessments commonly fall into three phases: benchmarking, detailed investigation, and assessment of findings across portfolio. The methodology involves, clustering buildings within a portfolio based on their energy performance, selecting the poorest performers for further analysis, and performing detailed investigations for the selected group. This study covers the development of a platform for convenient collection of the minimum building data required to support energy efficiency upgrade and investment decision makings.
Transcriptome Analysis of Moso Bamboo (Phyllostachys edulis) Reveals Candidate Genes Involved in Response to Dehydration and Cold Stresses

Bamboo (Bambusoideae) belongs to the grass family (Poaceae) and has been utilized as one of the most important nontimber forest resources in the world. Moso bamboo (Phyllostachys edulis) is a large woody bamboo with high ecological and economic values. Global climate change brings potential challenges to the normal growth of moso bamboo, and hence its production. Despite the release of moso bamboo genome sequence, the knowledge on genome-wide responses to abiotic stress is still limited. In this study, we generated a transcriptome data set with respect to dehydration and cold responses of moso bamboo using RNA-seq technology. The differentially expressed genes (DEGs) under treatments of dehydration and cold stresses were identified. By combining comprehensive gene ontology (GO) analysis, time-series analysis, and co-expression analysis, candidate genes involved in dehydration and cold responses were identified, which encode abscisic acid (ABA)/water deficit stress (WDS)-induced protein, late embryogenesis abundant (LEA) protein, 9-cis-epoxycarotenoid dioxygenase (NCED), anti-oxidation enzymes, transcription factors, etc. Additionally, we used PeLEA14, a dehydration-induced gene encoding an “atypical” LEA protein, as an example to validate the function of the identified stress-related gene in tolerance to abiotic stresses, such as drought and salt. In this study, we provided a valuable genomic resource for future excavation of key genes involved in abiotic stress responses and genetic improvement of moso bamboo to meet the requirement for environmental resilience and sustainable production.
BiPAD: Binomial Point Process Based Energy-Aware Data Dissemination in Opportunistic D2D Networks

In opportunistic device-to-device (D2D) networks, the epidemic routing protocol can be used to optimize the message delivery ratio. However, it has the disadvantage that it causes excessive coverage overlaps and wastes energy in message transmissions because devices are more likely to receive duplicates from neighbors. We therefore propose an efficient data dissemination algorithm that can reduce undesired transmission overlap with little performance degradation in the message delivery ratio. The proposed algorithm allows devices further away than the k-th furthest distance from the source device to forward a message to their neighbors. These relay devices are determined by analysis based on a binomial point process (BPP). Using a set of intensive simulations, we present the resulting network performances with respect to the total number of received messages, the forwarding efficiency and the actual number of relays. In particular, we find the optimal number of relays to achieve almost the same message delivery ratio as the epidemic routing protocol for a given network deployment. Furthermore, the proposed algorithm can achieve almost the same message delivery ratio as the epidemic routing protocol while improving the forwarding efficiency by over 103% when k≥10.
Starmatrix: Modelling nucleosynthesis of galactic chemical elements

One of the key ingredients of galactic chemical evolution (GCE) models is the nucleosynthetic contribution returned to the interstellar medium by the evolving stellar populations and supernovae. These yields vary depending on the age and metallicity of the stars and are combined following the mass distribution of stars to represent a SSP, stars formed at the same time and having the same initial element composition. Repeating this process, adjusting for the the star formation at each time step, is one of the main mechanisms of GCE models.
Classification of EEG Signals for Prediction of Epileptic Seizures

Epilepsy is a common brain disorder that causes patients to face multiple seizures in a single day. Around 65 million people are affected by epilepsy worldwide. Patients with focal epilepsy can be treated with surgery, whereas generalized epileptic seizures can be managed with medications. It has been noted that in more than 30% of cases, these medications fail to control epileptic seizures, resulting in accidents and limiting the patient’s life. Predicting epileptic seizures in such patients prior to the commencement of an oncoming seizure is critical so that the seizure can be treated with preventive medicines before it occurs. Electroencephalogram (EEG) signals of patients recorded to observe brain electrical activity during a seizure can be quite helpful in predicting seizures. Researchers have proposed methods that use machine and/or deep learning techniques to predict epileptic seizures using scalp EEG signals; however, prediction of seizures with increased accuracy is still a challenge. Therefore, we propose a three-step approach. It includes preprocessing of scalp EEG signals with PREP pipeline, which is a more sophisticated alternative to basic notch filtering. This method uses a regression-based technique to further enhance the SNR, with a combination of handcrafted, i.e., statistical features such as temporal mean, variance, and skewness, and automated features using CNN, followed by classification of interictal state and preictal state segments using LSTM to predict seizures. We train and validate our proposed technique on the CHB-MIT scalp EEG dataset and achieve accuracy of 94%, sensitivity of 93.8%, and 91.2% specificity. The proposed technique achieves better sensitivity and specificity than existing methods.
Organic aerogel as electro‐catalytic support in low‐temperature fuel cell

Fuel cells have been developed efficiently in recent years as a secure and high‐energy conversion technology. The innovation in electrocatalysis focuses on initiatives to minimize or replace Pt electrodes used. As an alternative, organic aerogel materials are normally used as electrodes in low temperature fuel cells due to their high electronic conducting and electrocatalytic characteristics. These are usually characterized by fundamental functional elements of strong covalent C‐C bonds from organic precursors. This review will mainly focus on organic aerogel nanomaterials related to carbon aerogels, carbon nanotube aerogels, and graphene aerogels as electrocatalytic supports by surface modification or structural features in catalysis. In contrast, organic aerogel materials prove to be durable, economical, and active electrocatalysts that can provide outstanding electrocatalytic efficiency in low temperature fuel cell applications. Last, this paper recaps the challenges faced in current fuel cell applications and the use of organic aerogel materials to address these challenges.
Identifying Terpenoid Biosynthesis Genes in Euphorbia maculata via Full-Length cDNA Sequencing

The annual herb Euphorbia maculata L. produces anti-inflammatory and biologically active substances such as triterpenoids, tannins, and polyphenols, and it is used in traditional Chinese medicine. Of these bioactive compounds, terpenoids, also called isoprenoids, are major secondary metabolites in E. maculata. Full-length cDNA sequencing was carried out to characterize the transcripts of terpenoid biosynthesis reference genes and determine the copy numbers of their isoforms using PacBio SMRT sequencing technology. The Illumina short-read sequencing platform was also employed to identify differentially expressed genes (DEGs) in the secondary metabolite pathways from leaves, roots, and stems. PacBio generated 62 million polymerase reads, resulting in 81,433 high-quality reads. From these high-quality reads, we reconstructed a genome of 20,722 genes, in which 20,246 genes (97.8%) did not have paralogs. About 33% of the identified genes had two or more isoforms. DEG analysis revealed that the expression level differed among gene paralogs in the leaf, stem, and root. Whole sets of paralogs and isoforms were identified in the mevalonic acid (MVA), methylerythritol phosphate (MEP), and terpenoid biosynthesis pathways in the E. maculata L. The nucleotide information will be useful for identifying orthologous genes in other terpenoid-producing medicinal plants.
Suzuki Distributed Monostatic and Bistatic S-Band Radar Sea Clutter

Low grazing angle S-band radar sea clutter data, collected with the NetRAD multistatic radar system, are analyzed. The Suzuki distribution, a compound Gaussian model with log normal texture, is found to be a good model for both monostatic and bistatic clutter. Clutter textures from simultaneously recorded monostatic and bistatic data are interpreted using hydrodynamics, providing estimates of the water depth and wave direction.
Object-based Velocity Feedback for Dynamic Occupancy Grids

Dynamic occupancy grids (DOGs) have raised interest in the last years due to their ability to fuse information without explicit data association, to represent free space and arbitrary-shape objects and to estimate obstacles’ dynamics. Different works have presented strategies with demonstrated good performance. Most of them rely on LiDAR sensors, and some have shown that including additional velocity measurements enhance the estimation. This work aims at showing that velocity information can be directly inferred from objects displacement. Thus, a strategy using velocity feedback and its inclusion in the DOG is presented. The qualitative and quantitative analysis of results obtained from real data experimentation show a very good performance, specially in dynamic changing situations.
VLSI Architectures and Arithmetic Operations with Application to the Fermat Number Transform

Theproperties of arithmetic operations in Fermat integer quotient ringsZ m , where m , are investigated. The arithmetic operations considered are mainly those involved in the computation of the Fermat number transform. We consider somewaysof representing the binary coded integers in such rings and investigate VLSI architectures for arithmetic operations, with respect to the different element representations. The VLSI architectures are mutually compared with respect to area (A) and time (T ) complexity and area-time performance (AT ). The VLSI model chosen is a linear switch-level RC model. In the polar representation, the nonzero elements of a field are represented by the powers of a primitive element of the field. In the thesis we particularly investigate the properties of arithmetic operations and their corresponding VLSI architectures with respect to the polar representation of the elements of Fermat prime fields. Some new results regarding the applicability of the Fermat number transform when using the polar representation are also presented.
Reporting a Rural Reality: A Case Study of an Agricultural Newspaper’s Series on the Rural Opioid Epidemic

Abstract Opioid drug abuse has created an epidemic recognized as a public health emergency in 2017, and the detrimental impacts of this epidemic have reached into rural America. When it comes to presenting information via the mass media, communications professionals serve as gatekeepers for what information is passed on to media consumers. Additionally, news organizations place certain degrees of importance upon issues through the amount of coverage dedicated to an issue. In late 2016, when the Farm and Dairy newspaper editorial staff decided to dedicate a vast amount of time and resources to covering Ohio and Pennsylvania’s rural opioid epidemic, a variety of questions and concerns followed. This complicated topic was largely unfamiliar and untraditional to agricultural communications. Concerns about how to research the topic, work with sources, and manage responses from stakeholders emerged at the onset, but motivations to increase awareness, reduce stigma, and instill hope in the midst of a rural opioid epidemic brought the series to fruition. This case study details the actions taken by those involved in the series and stakeholder reactions to a unique journalistic investigation from a rural newspaper. Discussion of recommendations for future research and curricular impacts are provided.