Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiple-Noise-Tolerant CO-OFDMA-PON Uplink Multiple Access Using AM-DAPSK-OFDM With Reflective ONUs

A reflective coherent orthogonal frequency-division multiple-access (OFDMA) passive optical network (PON) based on differential amplitude and phase-shift keying (DAPSK) OFDM is proposed herein. In the conventional OFDMA–PON uplink transmission, each optical network unit (ONU) signal has different channel and phase-noise characteristics. In addition, each ONU has an independent laser source; therefore, the carrier frequency offset (CFO) differs among the ONUs. These multiple noises worsen as the number of ONUs increases and adversely affect the spectral bandwidth and system complexity. The proposed system using reflective-type ONUs avoids multiple CFOs because every ONU shares the same laser source, which is transmitted from an optical line terminator. Moreover, by applying a differential modulation scheme to OFDM, we resolve the multiple channel and phase noises without spectral efficiency loss and system complexity increase. The spectral efficiency is maximized using an adaptive modulation technique. The proposed system is experimentally demonstrated in a 20-km OFDMA–PON uplink transmission link with two reflective ONUs. The results confirm the possibility of uplink multiple access without multiple-noise compensation processes. The optimal spectral efficiency in terms of bandwidth size and number of subcarriers is analyzed.
Body size and temperature effects on standard metabolic rate for determining metabolic scope for activity of the polychaete Hediste (Nereis) diversicolor

Considering the ecological importance and potential value of Hediste diversicolor, a better understanding of its metabolic rate and potential growth rates is required. The aims of this study are: (i) to describe key biometric relationships; (ii) to test the effects of temperature and body size on standard metabolic rate (as measure by oxygen consumption) to determine critical parameters, namely Arrhenius temperature (TA), allometric coefficient (b) and reaction rate; and (iii) to determine the metabolic scope for activity (MSA) of H. diversicolor for further comparison with published specific growth rates. Individuals were collected in a Mediterranean lagoon (France). After 10 days of acclimatization, 7 days at a fixed temperature and 24 h of fasting, resting oxygen consumption rates (VO2) were individually measured in the dark at four different temperatures (11, 17, 22 and 27 °C) in worms weighing from 4 to 94 mgDW (n = 27 per temperature). Results showed that DW and L3 were the most accurate measurements of weight and length, respectively, among all the metrics tested. Conversion of WW (mg), DW (mg) and L3 (mm) were quantified with the following equations: DW = 0.15 × WW, L3 = 0.025 × TL(mm) + 1.44 and DW = 0.8 × L33.68. Using an equation based on temperature and allometric effects, the allometric coefficient (b) was estimated at 0.8 for DW and at 2.83 for L3. The reaction rate (VO2) equaled to 12.33 µmol gDW−1 h−1 and 0.05 µmol mm L3−1 h−1 at the reference temperature (20 °C, 293.15 K). Arrhenius temperature (TA) was 5,707 and 5,664 K (for DW and L3, respectively). Metabolic scope for activity ranged from 120.1 to 627.6 J gDW−1 d−1. Predicted maximum growth rate increased with temperature, with expected values of 7–10% in the range of 15–20 °C. MSA was then used to evaluate specific growth rates (SGR) in several experiments. This paper may be used as a reference and could have interesting applications in the fields of aquaculture, ecology and biogeochemical processes.
Workload Alleviation Scheduling Framework to Alleviate Negative Performance Impact of Intermediate Data Skew in Small-Scale MapReduce Cloud

A MapReduce cloud becomes the essential platform in the cloud computing infrastructure today. Because applications may process input data with different algorithms and logics to produce intermediate data, a MapReduce cloud may suffer intermediate data skew by unevenly distributing intermediate data among nodes at run time. When intermediate data skew happens, a MapReduce cloud not only idles nodes to waste computation resources but also prolongs the application execution progress to hurt user experiences in cloud computing. Instead of the existing solutions that assume many available idle nodes and use computation resources in a loose way, a MapReduce cloud can use the Workload Alleviation Scheduling Framework (W ASF) proposed in this paper to alleviate the negative performance impact of intermediate data skew in a small-scale MapReduce cloud by smartly utilizing computation resources. Besides, a MapReduce cloud is verified with popular applications in experiments to have the outstanding performance improvement with W ASF when intermediate data skew happens.
Assessing the impact of bacteriophages in the treatment of Salmonella in broiler chickens

ABSTRACT Salmonellosis is one of the main bacterial infections affecting commercial poultry, causing losses to poultry production, and posing a public health concern. Samples from internal organs (liver, cecum and spleen) of one hundred diseased broiler chickens were collected and subjected to Salmonella isolation, identification and serotyping. S. typhimurium and S. enteritidis were selected from the isolated Salmonella to prepare bacteriophages from sewage water taken at broiler farms. An experimental infection of one day old specific pathogen free (SPF) chicks followed by treatment with the prepared bacteriophages isolated from both Salmonella was performed. Caecal samples from infected chicks were subjected at intervals to bacteriophage isolation and Salmonella quantitation. The effectiveness of bacteriophage treatments on Salmonella colonization in cecum of infected chicks increased after five successive doses. At 3 day post infection (dpi), cecal contents showed a marginal decrease in Salmonella loads with more reduction at 5 dpi. From 7 dpi to the end of the experiment at 15 dpi, all the chicks were cleared for both Salmonella. The findings of this study demonstrate that bacteriophage treatment is efficacious in reducing S. typhimurium and S. enteritidis colonization in broiler chickens within a short period and could be used as an alternative to antibiotics.
Quasi-Passive Reconfigurable Node for 5G Mobile Optical Backhaul Networks

A novel multi-dimensional quasi-passive reconfigurable (MD-QPAR) node for 5G mobile backhaul optical WDM mesh networks is proposed in this paper. The proposed MD-QPAR is capable of providing dynamic power and wavelength allocations for signals from any input port(s) to any output port(s). Each input/output port is connected to one possible direction or the local wireless nodes, and hence, the data rate, flexibility, robustness, and reliability requirements in 5G backhaul networks can be satisfied. In addition, the MD-QPAR is “quasi-passive,” where it only consumes power during network reconfigurations and there is no power consumption during steady-state operations, to enable high energy efficiency. Three possible MD-QPAR structures are proposed and studied. Simulations under the optical Flow traffic assumption are carried out and the signal blocking probability and the scalability are investigated. Proof-of-concept experiments are also undertaken and the MD-QPAR with Structure II is demonstrated. Results show that dynamic power and wavelength distributions from any input port(s) to any output port(s) can be realized, and the power penalty due to the MD-QPAR is limited to <0.5 dB.
Neuroprotective and neuroregenerative potential of pharmacologically-induced hypothermia with D-alanine D-leucine enkephalin in brain injury

Neurovascular disorders, such as traumatic brain injury and stroke, persist as leading causes of death and disability – thus, the search for novel therapeutic approaches for these disorders continues. Many hurdles have hindered the translation of effective therapies for traumatic brain injury and stroke primarily because of the inherent complexity of neuropathologies and an inability of current treatment approaches to adapt to the unique cell death pathways that accompany the disorder symptoms. Indeed, developing potent treatments for brain injury that incorporate dynamic and multiple disorder-engaging therapeutic targets are likely to produce more effective outcomes than traditional drugs. The therapeutic use of hypothermia presents a promising option which may fit these criteria. While regulated temperature reduction has displayed great promise in preclinical studies of brain injury, clinical trials have been far less consistent and associated with adverse effects, especially when hypothermia is pursued via systemic cooling. Accordingly, devising better methods of inducing hypothermia may facilitate the entry of this treatment modality into the clinic. The use of the delta opioid peptide D-alanine D-leucine enkephalin (DADLE) to pharmacologically induce temperature reduction may offer a potent alternative, as DADLE displays both the ability to cause temperature reduction and to confer a broad profile of other neuroprotective and neuroregenerative processes. This review explores the prospect of DADLE-mediated hypothermia to treat neurovascular brain injuries, emphasizing the translational steps necessary for its clinical translation.
Diabetes and Alzheimer's Disease: Mechanisms and Nutritional Aspects

Blood glucose homeostasis is well maintained by coordinated control of various hormones including insulin and glucagon as well as cytokines under normal conditions. However, chronic exposure to diabetic environment with high fat/high sugar diets and physical/mental stress can cause hyperglycemia, one of main characteristics of insulin resistance, metabolic syndrome, and diabetes. Hyperglycemia impairs organogenesis and induces organ abnormalities such as cardiac defect in utero. It is a risk factor for the development of metabolic diseases in adults. Resulting glucotoxicity affects peripheral tissues and vessels, causing pathological complications including diabetic neuropathy, nephropathy, vessel damage, and cardiovascular diseases. Moreover, chronic exposure to hyperglycemia can deteriorate cognitive function and other aspects of mental health. Recent reports have demonstrated that hyperglycemia is closely related to the development of cognitive impairment and dementia, suggesting that there may be a cause-effect relationship between hyperglycemia and dementia. With increasing interests in aging-related diseases and mental health, diabetes-related cognitive impairment is attracting great attention. It has been speculated that glucotoxicity can result in structural damage and functional impairment of brain cells and nerves, hemorrhage of cerebral blood vessel, and increased accumulation of amyloid beta. These are potential mechanisms underlying diabetes-related dementia. Nutrients and natural food components have been investigated as preventive and/or intervention strategy. Among candidate components, resveratrol, curcumin, and their analogues might be beneficial for the prevention of diabetes-related cognitive impairment. The purposes of this review are to discuss recent experimental evidence regarding diabetes and cognitive impairment and to suggest potential nutritional intervention strategies for the prevention and/or treatment of diabetes-related dementia.
Phylogenetic Diversity of Nitrogenase Reductase Genes and Possible Nitrogen-Fixing Bacteria in Thermophilic Chemosynthetic Microbial Communities in Nakabusa Hot Springs

Chemosynthetic microbial communities develop and form dense cell aggregates in slightly alkaline sulfidic hot springs in the temperature range of 70–86°C at Nakabusa, Japan. Nitrogenase activity has recently been detected in the microbial communities collected. To identify possible members capable of nitrogen fixation, we examined the diversities of 16S rRNA and nitrogenase reductase (NifH) gene sequences in four types of chemosynthetic communities with visually different colors and thicknesses. The results of a 16S rRNA gene analysis indicated that all four microbial communities had similar bacterial constituents; the phylum Aquificae was the dominant member, followed in abundance by Thermodesulfobacteria, Firmicutes, and Thermotogae. Most of the NifH sequences were related to sequences reported in hydrothermal vents and terrestrial hot springs. The results of a phylogenetic analysis of NifH sequences revealed diversity in this gene among the communities collected, distributed within 7 phylogenetic groups. NifH sequences affiliated with Aquificae (Hydrogenobacter/Thermocrinis) and Firmicutes (Caldicellulosiruptor) were abundant. At least two different energy metabolic pathways appeared to be related to nitrogen fixation in the communities analyzed; aerobic sulfur/hydrogen-oxidizing bacteria in Aquificae and fermentative bacteria in Firmicutes. The metabolic characteristics of these two dominant phyla differed from those previously inferred from nitrogenase activity assays on chemosynthetic communities, which were associated with hydrogen-dependent autotrophic sulfate reduction. These assays may correspond to the observed NifH sequences that are distantly related to the known species of Thermodesulfovibrio sp. (Nitrospirae) detected in the present study. The activities of nitrogen-fixing organisms in communities may depend on redox states as well as the availability of electron donors, acceptors, and carbon sources.
Optimized Hidden Markov Model based on Constrained Particle Swarm Optimization

As one of Bayesian analysis tools, Hidden Markov Model (HMM) has been used to in extensive applications. Most HMMs are solved by Baum-Welch algorithm (BWHMM) to predict the model parameters, which is difficult to find global optimal solutions. This paper proposes an optimized Hidden Markov Model with Particle Swarm Optimization (PSO) algorithm and so is called PSOHMM. In order to overcome the statistical constraints in HMM, the paper develops re-normalization and re-mapping mechanisms to ensure the constraints in HMM. The experiments have shown that PSOHMM can search better solution than BWHMM, and has faster convergence speed.
Antibiotics for amniotic-fluid colonization by Ureaplasma and/or Mycoplasma spp. to prevent preterm birth: A randomized trial

Objective To assess whether antibiotics used for treatment in asymptomatic second-trimester women positive for Mycoplasma or Ureaplasma spp. detected by amniotic-fluid PCR prevents preterm delivery. Design A randomized, double-blind, placebo-controlled trial. Setting 10 maternal fetal medicine centers in France. Population Women with a singleton pregnancy who underwent amniocentesis between 16 and 20 weeks’ gestation (weeks) for Down syndrome screening. A sample of 238 women with PCR-positive findings per treatment group was needed to show a 50% reduction in the preterm delivery rate. Methods Amniotic fluid was tested. Women with positive findings on real-time PCR of amniotic fluid for Mycoplasma hominis, Mycoplasma genitalium, Ureaplasma urealyticum and Ureaplasma parvum were randomized to receive josamycin or placebo. Amniotic fluid was also tested for 16S PCR. Main outcome measures The primary outcome was delivery before 37 weeks. Results In total, 1043 women underwent amniotic-fluid screening with specific PCR detection between July 2008 and July 2011: PCR detection failed in 27 (2.6%), and 20 (1.9%) underwent termination of pregnancy. Among the 1016 women with PCR results, 980 had available data for the primary outcome (delivery before 37 weeks) and 29 (3.0%) were positive for Ureaplasma and/or Mycoplasma spp. Because of the low rate of women with PCR-positive findings, the trial was stopped prematurely. In total, 19 women were randomized to receive placebo (n = 8) or josamycin (n = 11) and their characteristics were comparable, as was the rate of preterm delivery and secondary outcomes. In comparing all PCR-positive and -negative women regardless of treatment, PCR positivity for Ureaplasma and/or Mycoplasma spp. was not associated with any adverse pregnancy or neonatal outcome. Amniotic-fluid screening by 16S PCR showed no other bacterial colonization associated with preterm birth. Conclusions Because of a low amniotic fluid colonization rate, the trial was interrupted. Maternal amniotic-fluid colonization by Mycoplasma and/or Ureaplasma spp. at 16–20 weeks in asymptomatic women is rare and not associated with adverse pregnancy outcomes. Trial registration ClinicalTrials.gov NCT00718705
Multi-view Laplacian Eigenmaps Based on Bag-of-Neighbors For RGBD Human Emotion Recognition

Human emotion recognition is an important direction in the field of biometric and information forensics. However, most existing human emotion research are based on the single RGB view. In this paper, we introduce a RGBD video-emotion dataset and a RGBD face-emotion dataset for research. To our best knowledge, this may be the first RGBD video-emotion dataset. We propose a new supervised nonlinear multi-view laplacian eigenmaps (MvLE) approach and a multihidden-layer out-of-sample network (MHON) for RGB-D humanemotion recognition. To get better representations of RGB view and depth view, MvLE is used to map the training set of both views from original space into the common subspace. As RGB view and depth view lie in different spaces, a new distance metric bag of neighbors (BON) used in MvLE can get the similar distributions of the two views. Finally, MHON is used to get the low-dimensional representations of test data and predict their labels. MvLE can deal with the cases that RGB view and depth view have different size of features, even different number of samples and classes. And our methods can be easily extended to more than two views. The experiment results indicate the effectiveness of our methods over some state-of-art methods.
Deep Bv: A Fully Automated System for Brain Ventricle Localization and Segmentation In 3D Ultrasound Images of Embryonic Mice

Volumetric analysis of brain ventricle (BV) structure is a key tool in the study of central nervous system development in embryonic mice. High-frequency ultrasound (HFU) is the only non-invasive, real-time modality available for rapid volumetric imaging of embryos in utero. However, manual segmentation of the BV from HFU volumes is tedious, time-consuming, and requires specialized expertise. In this paper, we propose a novel deep learning based BV segmentation system for whole-body HFU images of mouse embryos. Our fully automated system consists of two modules: localization and segmentation. It first applies a volumetric convolutional neural network on a 3D sliding window over the entire volume to identify a 3D bounding box containing the entire BV. It then employs a fully convolutional network to segment the detected bounding box into BV and background. The system achieves a Dice Similarity Coefficient (DSC) of 0.8956 for BV segmentation on an unseen 111 HFU volume test set surpassing the previous state-of-the-art method (DSC of 0.7119) by a margin of 25%.
Unique MicroRNA and mRNA Interactions in EGFR-Mutated Lung Adenocarcinoma

The EGFR gene was one of the first molecules to be selected for targeted gene therapy. EGFR-mutated lung adenocarcinoma, which is responsive to EGFR inhibitors, is characterized by a distinct oncogenic pathway in which unique microRNA (miRNA)–mRNA interactions have been observed. However, little information is available about the miRNA–mRNA regulatory network involved. Both miRNA and mRNA expression profiles were investigated using microarrays in 155 surgically resected specimens of lung adenocarcinoma with a known EGFR mutation status (52 mutated and 103 wild-type cases). An integrative analysis of the data was performed to identify the unique miRNA–mRNA regulatory network in EGFR-mutated lung adenocarcinoma. Expression profiling of miRNAs and mRNAs yielded characteristic miRNA/mRNA signatures (19 miRNAs/431 mRNAs) in EGFR-mutated lung adenocarcinoma. Five of the 19 miRNAs were previously listed as EGFR-mutation-specific miRNAs (i.e., miR-532-3p, miR-500a-3p, miR-224-5p, miR-502-3p, and miR-532-5p). An integrative analysis of miRNA and mRNA expression revealed a refined list of putative miRNA–mRNA interactions, of which 63 were potentially involved in EGFR-mutated tumors. Network structural analysis provided a comprehensive view of the complex miRNA–mRNA interactions in EGFR-mutated lung adenocarcinoma, including DUSP4 and MUC4 axes. Overall, this observational study provides insight into the unique miRNA–mRNA regulatory network present in EGFR-mutated tumors. Our findings, if validated, would inform future research examining the interplay of miRNAs and mRNAs in EGFR-mutated lung adenocarcinoma.
Opinion on the Hurdles and Potential Health Benefits in Value-Added Use of Plant Food Processing By-Products as Sources of Phenolic Compounds

Plant foods, their products and processing by-products are well recognized as important sources of phenolic compounds. Recent studies in this field have demonstrated that food processing by-products are often richer sources of bioactive compounds as compared with their original feedstock. However, their final application as a source of nutraceuticals and bioactives requires addressing certain hurdles and challenges. This review discusses recent knowledge advances in the use of plant food processing by-products as sources of phenolic compounds with special attention to the role of genetics on the distribution and biosynthesis of plant phenolics, as well as their profiling and screening, potential health benefits, and safety issues. The potentialities in health improvement from food phenolics in animal models and in humans is well substantiated, however, considering the emerging market of plant food by-products as potential sources of phenolic bioactives, more research in humans is deemed necessary.
Estimation of Inverter-Based Solar PV Penetration on Medium Voltage Networks Using Grid Impedance

Installation and control of connecting inverter-based generation to medium voltage networks are constrained by network grid structure and by technical regulations that limits its penetration into the network. Medium voltage networks form the backbone to which low-voltage inverter-based generation such as solar PV systems are connect to. However, these networks generally have inconsistent impedances that vary with line lengths, conductor types and load distribution and therefore make them not as flexible and cost effective to efficiently allow adequate penetration of solar PV type distributed generation (capacity in kW) to be integrated. A generic model that mimics a medium voltage network is analyzed in this paper to determine how inverter-based generation can be maximized on the network in terms of its location by focusing on line impedance ratios to achieve voltage regulation.