Miracle-dz/UniFAR-FTUs huggingface dataset:
Monitoring Human Head and Neck-Based Motions From Around-Neck Creeping Wave Propagations

The ability to monitor various activities related to the human head and neck is of critical importance to medical professionals. Radio-based wireless body-area networks provide a potential method of tracking human motion patterns without compromising the comfort or privacy of users. This letter investigates the feasibility of using the electromagnetic creeping wave propagation around the human neck to monitor neck-based motions. The channel around the human neck contains information regarding the neck and head movements; therefore, it can be considered for activity classification. The changes in the transmission coefficient (S21) between two on-body antennas are measured to classify four different head- and mouth-related motions including chewing, drinking, deep breathing, and speaking. To capture the time-varying signatures of the measured S21, the joint time–frequency analysis has been applied. The spectrograms are classified by a deep convolutional neural network.
Carbon Quantum Dots: Surface Passivation and Functionalization

© 2016 Bentham Science Publishers. This review deals with the promising newest carbon-based nanomaterial; Carbon Quantum Dots (CQDs). CQDs demonstrate optoelectronic properties comparable to conventional inorganic semiconductors, however are environmental friendly and benign. They possess complicated structures, particle sizes up to 10 nm and upon surface passivation and/or functionalization their optoelectronic properties are critically improved and tuned. Although there are a few recent reviews on this topic, the majority of them emphasize on CQDs applications or even the synthetic procedures followed to acquire CQDs. In contrary, this review refers in brief to the aforementioned and focuses on the surface passivation and functionalization routes and therefore the functional groups and heteroatoms used for the development of high quality CQDs. Introduction and doping with appropriate heteroatoms is the key point to tailor made features of CQDs and thus organic chemistry provides the vital background for the essential functionalizations.
Safety and efficacy of a Labisia pumila var alata water extract on sexual well being and lipid profile of pre- and postmenopausal women: A randomized double-blind pilot study

This randomized double-blind, placebo-controlled study investigated the safety and efficacy of Labisia pumila (LP) water extract on sexual health, lipid profile and inflammatory markers in 36 healthy pre-and post-menopausal North American women. Participants were randomized to either LP (200 mg) or placebo for 12 weeks. The female sexual function index (FSFI) and short form-36 health survey (SF-36) were completed, and lipid profiles, anti-inflammatory markers, urinary antioxidants and safety parameters were assessed. There were no significant differences in FSFI and SF-36 scores after 12 weeks. Compared to placebo, women on Labisia pumila trended towards a reduction in total cholesterol after 12 weeks (p=0.077). Urinary 8-isoprostane concentrations from baseline to week 12 decreased for both groups, with women on L. pumila demonstrating a greater decrease (Δ= -144.4nmol/L) versus placebo (Δ= -125.9nmol/L). Significant decreases in serum IL-6 from baseline to week 6 were observed in Labisia pumila and placebo (p=0.006 and p=0.012 respectively) but these differences were not sustained through week 12. LP demonstrated a trend towards an improvement in TC, urinary 8-isoprostane and significant within group improvement in IL-6 and IL-1β suggesting a role for LP in improving inflammation. Future research should focus on older subjects that are sexually dysfunctional. Key words : Labisia pumila, women’s health, randomized double-blind trial, female sexual function index, blood lipid profile, cytokines.
Selecta: Heterogeneous Cloud Storage Configuration for Data Analytics

Data analytics are an important class of data-intensive workloads on public cloud services. However, selecting the right compute and storage conﬁguration for these applications is difﬁcult as the space of available options is large and the interactions between options are complex. Moreover, the different data streams accessed by analytics workloads have distinct characteristics that may be better served by different types of storage devices. We present Selecta, a tool that recommends near-optimal conﬁgurations of cloud compute and storage resources for data analytics workloads. Selecta uses latent factor collaborative ﬁltering to predict how an application will perform across different conﬁgurations, based on sparse data collected by proﬁling training workloads. We evaluate Selecta with over one hundred Spark SQL and ML applications, showing that Selecta chooses a near-optimal performance conﬁguration (within 10% of optimal) with 94% probability and a near-optimal cost conﬁguration with 80% probability. We also use Se-lecta to draw signiﬁcant insights about cloud storage systems, including the performance-cost efﬁciency of NVMe Flash devices, the need for cloud storage with support for ﬁne-grain capacity and bandwidth allocation, and the motivation for end-to-end storage optimizations.
Range Distance Requirements for Large Antenna Measurements for Square Aperture With Uniform Field Distribution

Frequency dependences of the field for constant angle of observation measured by different probes at different distances are discussed. We consider the case of the square aperture antenna with the uniform field distribution. The analysis is based on time-domain physical optics method of field calculation. We show and explain the effect of sidelobe reduction when a big square probe is placed at a finite distance from square aperture antenna. Errors of the sidelobe levels of the antenna radiation pattern (ARP) in the cases of different sizes of the probe placed at different distances are shown. We show an optimal probe size and an optimal measurement distance between antennas. We also show and explain the effect of a large distortion of the ARP first zero, measured by the big probe at the finite distance.
Active Metamaterial Transmission Line with Gain in SiGe BiCMOS Technology

─ We report the realization of an active composite right/left-handed (CRLH) metamaterial transmission line (TL) with gain. By employing the transistors in SiGe BiCMOS technology, an active CRLH TL has been realized exhibiting net gain, wideband and flat S-parameter characteristics. Effective electromagnetic parameters of the active CRLH TL, including complex propagation constant γ, effective permittivity εeff, effective permeability μeff and index of refraction n are extracted, which reveal the left handed properties of the active CRLH TL. The electric plasma frequency fpe and the magnetic plasma frequency fme are observed in the proposed TL. Index Terms─ Active, CRLH TL, metamaterial, SiGe BiCMOS.
Virtual Geographic Environment: A Workspace for Computer-Aided Geographic Experiments

A virtual geographic environment (VGE) is a type of workspace for computer-aided geographic experiments (CAGEs) and geographic analyses. By supporting geo-visualization, geo-simulation, geo-collaboration, and human participation, it provides open virtual environments that correspond to the real world to assist computer-aided geographic experiments involving both the physical and human dimensions. Based on a discussion of how VGEs can contribute to CAGEs and geographic analyses, this article proposes a clear, systematic framework for VGEs. Four subenvironments are discussed according to their different functions, pertinent issues, and corresponding solutions: (1) the data environment, (2) the modeling and simulation environment, (3) the interactive environment, and (4) the collaborative environment. Furthermore, a case on the simulation of air pollution and its analysis at different geographic scales is used to demonstrate VGEs’ ability to facilitate computer-aided geographic experiments.
Expectation Propagation-Based Active User Detection and Channel Estimation for Massive Machine-Type Communications

In massive machine-type communication (mMTC), by utilizing sporadic device activities, compressed sensing based multi-user detection (CS-MUD) can be used to recover sparse multi-user vectors in the grant-free uplink non-orthogonal multiple access (NOMA) environments. In CS-MUD, the channel state information (CSI) between each active device and the basestation should be estimated before the symbol detection. In this paper, we propose a novel Bayesian joint active user detection (AUD) and channel estimation (CE) method based on the expectation propagation (EP) algorithm. The proposed method finds the best Gaussian approximation for the computationally intractable posterior distribution of the sparse channel vector using iterative EP parameter update rules. Using the approximated distribution, identification and CSI estimation of active devices are jointly performed. We show from numerical simulations that the proposed technique greatly improves the performance of AUD and CE.
Tumor-suppressing miR-141 gene complex-loaded tissue-adhesive glue for the locoregional treatment of hepatocellular carcinoma

microRNAs (miRNAs) regulate gene expression post-transcriptionally and have been extensively tested as therapeutic molecules against several human diseases. In vivo delivery of miRNAs needs to satisfy the following conditions: safety, efficiency, and long-term therapeutic effectiveness. To satisfy these conditions, we developed a tissue-adhesive nucleotide-polymer complex (NPX-glue) for in vivo delivery of miRNAs to treat hepatocellular carcinoma (HCC). Methods: Polyallylamine (PAA), a cationic polymer, was mixed with tumor-suppressing miR-141 to form NPX and then mixed with partially oxidized alginate (OA) to form NPX-glue. Delivery efficiency of miR-141:NPX-glue was determined in cultured HCC cells and in an implanted HCC tumor model. In vivo tumor-suppressive effects of miR-141 on HCC were examined in mice upon intratumoral injection of miR-141:NPX-glue. Result: NPX-glue was generated by mixing of NPX with OA, which eliminated the inherent cytotoxic effect of NPX. NPX-glue led to the efficient delivery of miR-141 and plasmid to cultured cells and solid tumors in mice, where their expression was maintained for up to 30 days. Upon intratumoral injection of miR-141:NPX-glue, the growth of the tumors was dramatically retarded in comparison with the negative control, NCmiR:NPX-glue, (p < 0.05). Molecular examination proved miR-141:NPX-glue efficiently regulated the target genes including MAP4K4, TM4SF1, KEAP1, HDGF, and TIAM1 and finally induced apoptosis of cancer tissues. Conclusion: Here, we show that NPX-glue delivers therapeutic miR-141 to solid tumors in a safe, stable, and long-term manner and prove that locoregional treatment of HCC is possible using the NPX-glue system.
What causes cooling water temperature gradients in a forested stream reach ?

Previous studies have suggested that shading by riparian vegetation may reduce maximum water temperatures and provide refugia for temperature-sensitive aquatic organisms. Longitudinal cooling gradients have been observed during the daytime for stream reaches shaded by coniferous trees downstream of clear cuts or deciduous woodland downstream of open moorland. However, little is known about the energy exchange processes that drive such gradients, especially in semi-natural woodland contexts without confounding cool groundwater inflows. To address this gap, this study quantified and modelled variability in stream temperature and heat fluxes along an upland reach of the Girnock Burn (a tributary of the Aberdeenshire Dee, Scotland) where riparian land use transitions from open moorland to semi-natural, predominantly deciduous woodland. Observations were made along a 1050 m reach using a spatially distributed network of 10 water temperature data loggers, 3 automatic weather stations and 211 hemispherical photographs that were used to estimate incoming solar radiation. These data parameterised a high-resolution energy flux model incorporating flow routing, which predicted spatio-temporal variability in stream temperature. Variability in stream temperature was controlled largely by energy fluxes at the water-column– atmosphere interface. Net energy gains occurred along the reach, predominantly during daylight hours, and heat exchange across the bed–water-column interface accounted for < 1 % of the net energy budget. For periods when daytime net radiation gains were high (under clear skies), differences between water temperature observations increased in the streamwise direction; a maximum instantaneous difference of 2.5 C was observed between the upstream reach boundary and 1050 m downstream. Furthermore, daily maximum water temperature at 1050 m downstream was ≤ 1 C cooler than at the upstream reach boundary and lagged by > 1 h. Temperature gradients were not generated by cooling of stream water but rather by a combination of reduced rates of heating in the woodland reach and advection of cooler (overnight and early morning) water from the upstream moorland catchment. Longitudinal thermal gradients were indistinct at night and on days when net radiation gains were low (under overcast skies), thus when changes in net energy gains or losses did not vary significantly in space and time, and heat advected into the reach was reasonably consistent. The findings of the study and the modelling approach employed are useful tools for assessing optimal planting strategies for mitigating against ecologically damaging stream temperature maxima.
Comparative Study of Different Diets-Induced NAFLD Models of Zebrafish

Dietary composition has important impact on nonalcoholic fatty liver disease (NAFLD). The purpose of this study was to explore the relationship between NAFLD and major dietary components using zebrafish larvae fed different diets. Zebrafish larvae fed with high cholesterol (HC), high fructose (HF) and extra feeding (EF) diets for 10 days displayed varying degrees steatosis. The incidence and degree of steatosis were the most severe in the EF group. A HC diet severely promoted lipid deposits in the caudal vein. The triglyceride and glucose contents of zebrafish significantly increased in the HF and EF groups compared with the control group. Moreover, the mRNA expression of oxidative stress gene gpx1a, endoplasmic reticulum stress genes ddit3 and grp78, inflammatory genes tnfa, glucose metabolism genes irs2, glut1 and glut2, and lipid metabolism genes cidec, chrebp, ppara and cpt1a were significantly increased in the HF group. The HC diet was associated with upregulation of grp78, and downregulation of irs2, glut1 and glut2. The mRNA expression of lipogenesis and glucose metabolism associated genes were decreased in the EF group. In addition, the autophagy associated genes atg3, atg5, atg7, and atg12, and protein expression of ATG3 and LC3BII were reduced and P62 were elevated in the HC group. We also performed comparative transcriptome analysis of the four groups. A total of 2,492 differentially expressed genes were identified, and 24 statistically significant pathways were enriched in the diet treatment groups. This study extends our understanding of the relationships between diet ingredients and host factors that contribute to the pathogenesis of NAFLD, which may provide new ideas for the treatment of NAFLD.
Experimental characterization of a hydrogen/argon cascaded arc plasma source

A H2 /Ar cascaded arc plasma source has been experimentally characterized by determination of the efficiency, the electric field, and the pressure gradient of the arc. The results show that the efficiency of a H2/Ar cascaded arc drops when the hydrogen flow rate is increased. The electron temperature in the argon cascaded arc has been derived to be in the range 9000–12 500 K. For a hydrogen arc, the mass dissociation degree of hydrogen molecules has been derived to be above 60%.
Biogeography of soil bacteria and archaea across France

Each soil bacterial taxon exhibits a specific wide scale distribution explained by particular environmental filters. Over the last two decades, a considerable effort has been made to decipher the biogeography of soil microbial communities as a whole, from small to broad scales. In contrast, few studies have focused on the taxonomic groups constituting these communities; thus, our knowledge of their ecological attributes and the drivers determining their composition and distribution is limited. We applied a pyrosequencing approach targeting 16S ribosomal RNA (rRNA) genes in soil DNA to a set of 2173 soil samples from France to reach a comprehensive understanding of the spatial distribution of bacteria and archaea and to identify the ecological processes and environmental drivers involved. Taxonomic assignment of the soil 16S rRNA sequences indicated the presence of 32 bacterial phyla or subphyla and 3 archaeal phyla. Twenty of these 35 phyla were cosmopolitan and abundant, with heterogeneous spatial distributions structured in patches ranging from a 43- to 260-km radius. The hierarchy of the main environmental drivers of phyla distribution was soil pH > land management > soil texture > soil nutrients > climate. At a lower taxonomic level, 47 dominant genera belonging to 12 phyla aggregated 62.1% of the sequences. We also showed that the phylum-level distribution can be determined largely by the distribution of the dominant genus or, alternatively, reflect the combined distribution of all of the phylum members. Together, our study demonstrated that soil bacteria and archaea present highly diverse biogeographical patterns on a nationwide scale and that studies based on intensive and systematic sampling on a wide spatial scale provide a promising contribution for elucidating soil biodiversity determinism.
CHANGES IN ANTIOXIDANT ACTIVITIES AND COMPOUNDS DURING CULTIVATION OF SHIITAKE (LENTINULA EDODES)

Mushrooms contain a variety of secondary metabolites, including various phenolic compounds, which have been shown to act as excellent antioxidants. Recently, a specific antioxidant, ergothioneine (ERG) has been identified in various genera of mushrooms, including shiitake (Lentinula edodes). Shiitake is the second most highly consumed mushroom in the world, and present several functional properties, such as antitumor, hypocholesterolemic, antioxidant and antimicrobial potentials that have been intensively investigated. Although research was focused on its therapeutic effects, little information is available about the compounds responsible of the antioxidant properties. Our objectives were to identify changes in quality of shiitake as antioxidant source during cultivation cycles on oak woodships. The antioxidant activities and contents of potential antioxidant components, including total phenolic (TP) compounds and ERG, were analyzed in two parts of mushrooms (stipe and cap) from the successive flushes. In addition, the seasonal variations were studied. The Folin-Ciocalteu reagent was used to quantify the TP, and ERG was quantified by HPLC-DAD. The antioxidant activity was measured using the ORAC assay. Our analysis revealed only minor seasonal variations in TP and ERG contents as well as the ORAC value, excepted during the winter where these contents were 50% higher in the caps. Regarding the age of the culture, we observed a progressive decrease in the contents of TP and ERG all along the flushes, whatever the part of the mushroom. Surprisingly, the ORAC value increased in the whole mushrooms, whereas it decreased in the caps and strongly increased in the stipes. We concluded that the antioxidant activities could be largely dependent on other molecules than ERG, perhaps specific phenolic compounds. Having established the main variations in the antioxidant activity of shiitake, the chemical characteristics of the antioxidative components will be now further investigated. This study could provide valuable new opportunities for mushroom growers, since shiitake can serve as a good source of antioxidants in the human diet.
A Deep Learning Approach for Predicting Antidepressant Response in Major Depression Using Clinical and Genetic Biomarkers

In the wake of recent advances in scientific research, personalized medicine using deep learning techniques represents a new paradigm. In this work, our goal was to establish deep learning models which distinguish responders from non-responders, and also to predict possible antidepressant treatment outcomes in major depressive disorder (MDD). To uncover relationships between the responsiveness of antidepressant treatment and biomarkers, we developed a deep learning prediction approach resulting from the analysis of genetic and clinical factors such as single nucleotide polymorphisms (SNPs), age, sex, baseline Hamilton Rating Scale for Depression score, depressive episodes, marital status, and suicide attempt status of MDD patients. The cohort consisted of 455 patients who were treated with selective serotonin reuptake inhibitors (treatment-response rate = 61.0%; remission rate = 33.0%). By using the SNP dataset that was original to a genome-wide association study, we selected 10 SNPs (including ABCA13 rs4917029, BNIP3 rs9419139, CACNA1E rs704329, EXOC4 rs6978272, GRIN2B rs7954376, LHFPL3 rs4352778, NELL1 rs2139423, NUAK1 rs2956406, PREX1 rs4810894, and SLIT3 rs139863958) which were associated with antidepressant treatment response. Furthermore, we pinpointed 10 SNPs (including ARNTL rs11022778, CAMK1D rs2724812, GABRB3 rs12904459, GRM8 rs35864549, NAALADL2 rs9878985, NCALD rs483986, PLA2G4A rs12046378, PROK2 rs73103153, RBFOX1 rs17134927, and ZNF536 rs77554113) in relation to remission. Then, we employed multilayer feedforward neural networks (MFNNs) containing 1–3 hidden layers and compared MFNN models with logistic regression models. Our analysis results revealed that the MFNN model with 2 hidden layers (area under the receiver operating characteristic curve (AUC) = 0.8228 ± 0.0571; sensitivity = 0.7546 ± 0.0619; specificity = 0.6922 ± 0.0765) performed maximally among predictive models to infer the complex relationship between antidepressant treatment response and biomarkers. In addition, the MFNN model with 3 hidden layers (AUC = 0.8060 ± 0.0722; sensitivity = 0.7732 ± 0.0583; specificity = 0.6623 ± 0.0853) achieved best among predictive models to predict remission. Our study indicates that the deep MFNN framework may provide a suitable method to establish a tool for distinguishing treatment responders from non-responders prior to antidepressant therapy.
On the Feasibility of Integrating mmWave and IEEE 802.11p for V2V Communications

Recently, the millimeter wave (mmWave) band has been investigated as a means to support the foreseen extreme data rate demands of emerging automotive applications, which go beyond the capabilities of existing technologies for vehicular communications. However, this potential is hindered by the severe isotropic path loss and the harsh propagation of high-frequency channels. Moreover, mmWave signals are typically directional, to benefit from beamforming gain, and require frequent realignment of the beams to maintain connectivity. These limitations are particularly challenging when considering vehicle-to-vehicle (V2V) transmissions, because of the highly mobile nature of the vehicular scenarios, and pose new challenges for proper vehicular communication design. In this paper, we conduct simulations to compare the performance of IEEE 802.11p and the mmWave technology to support V2V networking, aiming at providing insights on how both technologies can complement each other to meet the requirements of future automotive services. The results show that mmWave-based strategies support ultra-high transmission speeds, and IEEE 802.11p systems have the ability to guarantee reliable and robust communications.