Miracle-dz/UniFAR-FTUs huggingface dataset:
Occupational functional plasticity revealed by brain entropy: A resting‐state fMRI study of seafarers

Recently, functional magnetic resonance imaging (fMRI) has been increasingly used to assess brain function. Brain entropy is an effective model for evaluating the alteration of brain complexity. Specifically, the sample entropy (SampEn) provides a feasible solution for revealing the brain's complexity. Occupation is one key factor affecting the brain's activity, but the neuropsychological mechanisms are still unclear. Thus, in this article, based on fMRI and a brain entropy model, we explored the functional complexity changes engendered by occupation factors, taking the seafarer as an example. The whole‐brain entropy values of two groups (i.e., the seafarers and the nonseafarers) were first calculated by SampEn and followed by a two‐sample t test with AlphaSim correction (p < .05). We found that the entropy of the orbital‐frontal gyrus (OFG) and superior temporal gyrus (STG) in the seafarers was significantly higher than that of the nonseafarers. In addition, the entropy of the cerebellum in the seafarers was lower than that of the nonseafarers. We conclude that (1) the lower entropy in the cerebellum implies that the seafarers’ cerebellum activity had strong regularity and consistency, suggesting that the seafarer's cerebellum was possibly more specialized by the long‐term career training; (2) the higher entropy in the OFG and STG possibly demonstrated that the seafarers had a relatively decreased capability for emotion control and auditory information processing. The above results imply that the seafarer occupation indeed impacted the brain's complexity, and also provided new neuropsychological evidence of functional plasticity related to one's career.
Mind the Gap: Accounting for Measurement Error and Misclassification in Variables Generated via Data Mining

The application of predictive data mining techniques in information systems research has grown in recent years, likely because of their effectiveness and scalability in extracting information from large amounts of data. A number of scholars have sought to combine data mining with traditional econometric analyses. Typically, data mining methods are first used to generate new variables (e.g., text sentiment), which are added into subsequent econometric models as independent regressors. However, because prediction is almost always imperfect, variables generated from the first-stage data mining models inevitably contain measurement error or misclassification. These errors, if ignored, can introduce systematic biases into the second-stage econometric estimations and threaten the validity of statistical inference. In this commentary, we examine the nature of this bias, both analytically and empirically, and show that it can be severe even when data mining models exhibit relatively high performance. We then show.
Alginate microspheres obtained by the spray drying technique as mucoadhesive carriers of ranitidine

Abstract The present study is aimed at formulation of alginate (ALG) microspheres with ranitidine (RNT) by the spray drying method. Obtained microspheres were characterized for particle size, surface morphology, entrapment efficiency, drug loading, in vitro drug release and zeta potential. Mucoadhesive properties were examined by a texture analyser and three types of adhesive layers - gelatine discs, mucin gel and porcine stomach mucosa. Microspheres showed a smooth surface with narrow particle size distribution and RNT loading of up to 70.9 %. All formulations possessed mucoadhesive properties and exhibited prolonged drug release according to the first-order kinetics. DSC reports showed that there was no interaction between RNT and ALG. Designed microspheres can be considered potential carriers of ranitidine with prolonged residence time in the stomach
Enhancing Security of Wireless Sensor Network

This paper shows how we can enhance security of the wireless sensor networks. In order to send confidential data from sensor node to sink node and also physical threat is possible to sensor node. Security mechanism can be applied at sink node to protect various threats in OSI layers and also achieve the security goals. This paper suggests architecture to deal with various types of attacks based on Encryption and hardware processor for Wireless Sensor Network (WSN).
ALTERNATIVE STRUCTURES AND POWER SPECTRUM CRITERIA FOR BLIND SEGMENTATION AND SEPARATION OF CONVOLUTIVE SPEECH MIXTURES

This paper deals with the blind separation of convolutively mixed speech sources. The proposed methods take advantage of the a priori knowledge that speech signals contain silences. They consist in first detecting silence phases in these source signals and then identifying each filter of the considered separating systems in such a phase. The criteria used in both stages of these approaches are based on the power (cross)-spectra of the observations: their time-segmented coherence function is first used to detect silence phases and the filters to be identified are then expressed as the ratios of observation power (cross)-spectra. This general approach is applied to various separating systems, depending i) whether the considered structures are symmetrical, asymmetrical, or asymmetrical with a complementary part, and ii) whether they include or not a post-processing stage for filtering the extracted sources. The performance of all these approaches and of two methods from the literature is investigated by means of experimental tests performed with speech sources mixed by means of real acoustical in-car transfer functions. This shows that the proposed approaches yield an interesting performance/complexity trade-off as compared to previously reported methods.
BLIND SOURCE SEPARATION BASED ON SPACE-TIME-FREQUENCY DIVERSITY

We investigate the assumption that sources have disjoint support in the time domain, time-frequency domain, or frequency domain. We call such signals disjoint orthogonal. The class of signals that approximately satisfies this assumption includes many synthetic signals, music and speech, as well as some biological signals. We measure the disjoint orthogonality of the benchmark signals in the ICALAB Toolbox in the time, time-frequency, and frequency domains and show that most satisfy the assumption in at least one representation. In order to compare this assumption with other common source assumptions, we derive a demixing algorithm for noisy instantaneous mixtures based on disjoint orthogonality and compare its performance to the algorithms in the ICALAB Toolbox, all of which rely on the second-order statistics, non-stationarity, or higherorder statistics of the sources. The results indicate that space-timefrequency diversity is a useful assumption for the design of BSS/ICA algorithms.
An Efficient Radio Resource Re-Allocation Scheme for Delay Guaranteed Vehicle-to-Vehicle Network

To achieve low delay for vehicular communication in cellular networks, the use of direct device-to-device (D2D) communication among vehicles is regarded as a key functional requirement. When D2D users share the spectrum with regular cellular users (D2D underlay), resource allocation schemes assure the coexistence between D2D and cellular users. Due to the high mobility of the vehicles, the resources need to be reallocated, but frequent updates cause high signaling overhead and degrade the delay performance. In this paper, we present a radio resource re-allocation scheme for vehicular D2D users in a platoon scenario. The scheme reduces the re-allocation rate and gives delay guarantees for each vehicle.With the help of Lyapunov optimization, a closed form of the upper delay bound and resource re-allocation rate is also derived. The simulation results show that the proposed scheme can provide an delay upper bound and simultaneously minimizes the resource re-allocation rate.
Idiosyncrasy of nasal sounds in human speaker identification and their acoustic properties

1. Introduction Speech sounds convey not only linguistic or phonological information, but also nonlinguistic information, including the speakers' individualities [1]. It is known that the availability of the speech contents used for speaker identification differs depending on the types of sounds they contain, and it is reported that voiced sonorants, such as vowels and nasals, are most effective for speaker identification by both humans [2–4] and machines [5]. The speaker's individuality contained in speech sounds should have some acoustic correlations and their properties can be measured as acoustic parameters [6]. In this study, we conducted a human speaker identification test, and investigated the differences in the effectiveness of using various Japanese sounds in identifying the speakers. We also analysed the stimuli used in the experiment in order to explain these differences in terms of acoustical distances.
A Method for Estimating the Aerodynamic Roughness Length with NDVI and BRDF Signatures Using Multi-Temporal Proba-V Data

Aerodynamic roughness length is an important parameter for surface fluxes estimates. This paper developed an innovative method for estimation of aerodynamic roughness length (z0m) over farmland with a new vegetation index, the Hot-darkspot Vegetation Index (HDVI). To obtain this new index, the normalized-difference hot-darkspot index (NDHD) is introduced using a semi-empirical, kernel-driven bidirectional reflectance model with multi-temporal Proba-V 300-m top-of-canopy (TOC) reflectance products. A linear relationship between HDVI and z0m was found during the crop growth period. Wind profiles data from two field automatic weather station (AWS) were used to calibrate the model: one site is in Guantao County in Hai Basin, in which double-cropping systems and crop rotations with summer maize and winter wheat are implemented; the other is in the middle reach of the Heihe River Basin from the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) project, with the main crop of spring maize. The iterative algorithm based on Monin–Obukhov similarity theory is employed to calculate the field z0m from time series. Results show that the relationship between HDVI and z0m is more pronounced than that between NDVI and z0m for spring maize at Yingke site, with an R2 value that improved from 0.636 to 0.772. At Guantao site, HDVI also exhibits better performance than NDVI, with R2 increasing from 0.630 to 0.793 for summer maize and from 0.764 to 0.790 for winter wheat. HDVI can capture the impacts of crop residue on z0m, whereas NDVI cannot.
Neighbour selection and adaptation for rapid speaker-dependent ASR

Speaker dependent (SD) ASR systems have significantly lower word error rates (WER) compared to speaker independent (SI) systems. However, SD systems require sufficient training data from the target speaker, which is impractical to collect in a short time. We present a technique for training SD models using just few minutes of speaker's data. We compensate for the lack of adequate speaker-specific data by selecting neighbours from a database of existing speakers who are acoustically close to the target speaker. These neighbours provide ample training data, which is used to adapt the SI model to obtain an initial SD model for the new speaker with significantly lower WER. We evaluate various neighbour selection algorithms on a large-scale medical transcription task and report significant reduction in WER using only 5 mins of speaker-specific data. We conduct a detailed analysis of various factors such as gender and accent in the neighbour selection. Finally, we study neighbour selection and adaptation in the context of discriminative objective functions.
Low Diastolic Pressure and Risk of Dementia in Very Old People: A Longitudinal Study

Background/Aim: Midlife high blood pressure is linked to late-life dementia. We sought to investigate the temporal relation of blood pressure to the risk of dementia and Alzhei-mer’s disease (AD) among older adults. Methods: A dementia-free cohort (n = 422) aged ≥81 years was followed for 3 years to detect dementia and AD cases (Diagnostic and Statistical Manual of Mental Disorders, Third Edition, Revised criteria). The blood pressure was measured 4 times over a 9-year period starting from ≥75 years of age. The data were analyzed with Cox models controlling for potential confounders. Results: During the 954 person-years of follow- up, 89 subjects developed dementia (72 AD cases). Low diastolic pressure (<70 vs. 70–89 mm Hg) was associated with a multiadjusted hazard ratio of 2.13 [95% confidence interval (CI) = 1.05–4.32] for dementia and 2.16 (95% CI = 0.98–4.73) for AD occurring over a 6-to 9-year period, whereas high diastolic pressure (≥90 mm Hg) was marginally related to a decreased hazard ratio of 0.58 (95% CI = 0.33–1.02) for dementia and 0.57 (95% CI = 0.30–1.09) for AD. Systolic pressure was not significantly related to dementia risk. Subjects who developed dementia had a greater decline in blood pressure than persons who did not, mainly during the 3-year period before dementia diagnosis. Conclusion: Low diastolic pressure predicts the risk of dementia among very old people, and the blood pressure exhibits a substantial decline over around 3 years before the dementia syndrome becomes clinically evident.
City Research Online

Early warning systems for the identification and tracking of infections disease outbreaks have become an important tool in the field of epidemiology. While government lead initiatives to increase the sharing of surveillance data have improved early detection and control, along with advanced web monitoring and analytics services, the recent swine flu outbreak of 2009 demonstrated the important role social media has and the wealth of data it exposes. In this paper, we present an investigation into Twitter, using around 3 Million tweets gathered between May and December 2009, as a possible source of surveillance data and its feasibility to serve as an early warning system. By performing simple filtering and normalization, we demonstrate that Twitter can serve as a self-reporting tool, and hence, provide indications of increased infection spreading. Our initial findings indicate that Twitter can detect such events up to one week before conventional GP reported surveillance data.
Rhythm Classification Using Spectral Rhythm Patterns

In this paper, we study the use of spectral patterns to represent the characteristics of the rhythm of an audio signal. A function representing the position of onsets over time is first extracted from the audio signal. From this function we compute at each time a vector which represents the characteristics of the local rhythm. Three feature sets are studied for this vector. They are derived from the amplitude of the Discrete Fourier Transform, the AutoCorrelation Function and the product of the DFT and of a Frequency-Mapped ACF. The vectors are then sampled at some specific frequencies, which represents various ratios of the local tempo. The ability of the three feature sets to represent the rhythm characteristics of an audio item is evaluated through a classification task. We show that using such simple spectral representations allows obtaining results comparable to the state of the art.
Osteocyte density and histomorphometric parameters in cancellous bone of the proximal femur in five mammalian species

The species‐specific relationships between trabecular morphology and osteocyte density were investigated in the femoral heads of 30 adult animals of five mammalian species (rat, rabbit, Rhesus monkey, pig, and cow). Our hypothesis is that osteocytes are mechanosensory cells and are involved in the regulation of bone remodeling. According to the predictions from a simulation model, this hypothesis implies that the influencing distance of osteocytes, together with the magnitude of the mechanical loads, determines the thickness of trabeculae and that the number of osteocytes primarily affects the rate of bone remodeling. The number of osteocytes per bone volume ranged from 93,200 mm−3 in rat to 31,900 mm−3 in bovine cancellous bone. Osteocyte density was inversely related to the size of the species. Since basal metabolic output is related to body mass, we speculate that osteocyte density may be related to metabolic rates. Trabecular thickness was larger in the cow than in the other species, but the range of variation between species was relatively small. This agrees with the hypothesis that trabecular thickness is limited by the domain that can be regulated by an osteocyte and that this domain is of similar size regardless of the species. Only in the rat was trabecular thickness considerably smaller than in the other species. This is probably due to the presence of the cartilaginous growth plate in the femoral head of the rat. The relationships with species are different for osteocyte density than for morphometric parameters. Hence, our data support our hypothesis that osteocyte density is not directly associated with the macroscopic trabecular architecture.
Tamoxifen Resistance Trumped and Oral Selective Estrogen Receptor Degraders Arrive

Predictive tests, to refine the estrogen receptor assay, for the adjuvant treatment of breast cancer with tamoxifen and oral selective estrogen receptor degraders (SERD) are required. A splice variant of the corepressor NCOR2, BQ2313636.1 predicts tamoxifen resistance to adjuvant tamoxifen and AZ9496, the first oral SERD, completes phase I studies. Clin Cancer Res; 24(15); 3480–2. ©2018 AACR. See related articles by Gong et al., p. 3681 and Hamilton et al., p. 3510
BIOCHEMICAL AND HISTOLOGICAL EVIDENCES FOR THE ANTITUMOR POTENTIAL OF TEUCRIUM OLIVERIANUM AND RHAZYA STRICTA IN CHEMICALLY-INDUCED HEPATOCELLULAR CARCINOMA

Background: Teucrium oliverianum and Rhazya stricta are medicinal plants used in traditional and herbal medicine for the treatment of diabetes, liver diseases and inflammatory conditions. The present study was planned to investigate the antitumor efficacy of Teucrium oliverianum and Rhazya stricta in chemically-induced hepatocellular carcinoma (HCC) in rats. Materials and Methods: Forty adult male rats weighing 170-200 g were divided into four groups; each group was comprised of ten rats: (1): Normal healthy animals served as negative control group, (2): Hepatocellular carcinoma (HCC) group in which the rats were orally administered Nnitrosodiethylamine (dissolved in 0.9% normal saline), in a dose of 20 mg/kg b.wt. five times a week for six weeks, (3): HCC group treated with Teucrium oliverianum extract in a dose of 600 mg/kg b.wt for two months and (4): HCC group treated with Rhazya stricta extract in a dose of 750 mg/kg b.wt for two months. Serum alanine aminotransferase (ALT), asparatate aminotransferase (AST), alkaline phosphatase (ALP) and gammaglutamyl transferase (γ-GT) activities were estimated. Serum carcinoembyronic antigen (CEA), alpha-fetoprotein (AFP), alpha-L-fucosidase (AFU), glypican-3 (GPC-3), golgi protein 73 (Gp-73) and vascular endothelial growth factor (VEGF) levels were determined. Histopathological examination of liver tissue sections was also carried out. Results: The HCC group showed significant elevation in serum AST, ALT, ALP and γ-GT activities as well as CEA, AFP, AFU, Gpc-3, Gp 73 and VEGF levels versus the negative control group. Photomicrograph of liver tissue sections of rats in HCC revealed hepatic parenchyma with foci of anaplastic hepatocellular carcinoma as well as other foci of cystic cholangio carcinoma associated with areas of telangictasis with haemorrhage as well as individual hepatocellular necrosis. Conclusion: Treatment of HCC groups with Teucrium oliverianum or Rhazya stricta extract experienced significant improvement in the measured biochemical parameters as well as in the structural organization of the liver. In conclusion, the current study provided experimental evidences for the antitumor efficacy of Teucrium oliverianum and Rhazya stricta against hepatocellular carcinoma. Such effect could be attributed to hepatoprotective properties, antiproliferative activity and antiangiogenic potential.
Temperature Dependence of Quality Factor in MEMS Resonators

The temperature dependence of the quality factor of microelectromechanical system (MEMS) resonators is analyzed and measured. For silicon MEMS resonators, there are several energy loss mechanisms that determine the quality factor. These include air-damping, thermoelastic dissipation, and anchor and surface losses. For resonators operating at a low pressure in hermetic wafer-scale encapsulation, the effect of each energy loss mechanism is discussed. The temperature dependence of each mechanism and their contribution to the total quality factor is investigated. MEMS resonators can be designed to have either strong or weak dependence of on temperature, which is if the effects of the temperature on the dominant loss mechanisms are well understood. The sensitivity of up to 1% changes in quality factor per degree Celsius change of temperature was demonstrated by experiment. By using as the thermometer for temperature compensation, a preliminary experiment demonstrated less than 4-ppm resonant frequency variation over the 0 -70 temperature range. This indicates that the quality factor can be used as an absolute intrinsic thermometer for temperature compensation in the MEMS resonators.
Physiological Adaptations of Apnea-Conditioned Athletes and their Implications for Synchronized Swimmers' Performance

Synchronized swimming (SS) is an Olympic sport that encompasses swimming, dancing and gymnastics combined with repeated water submersions. SS programs are performed in solos, duets, trios, combos or in teams of men and women athletes. SS demands excellent swimming and sport-specific skills e.g. sculling, aerobic endurance and anaerobic power and strength, extraordinary flexibility and agility. Performance is scored equally for technical and artistic skills by a panel of judges.
Epithelial‐to‐mesenchymal transition in the context of epidermal growth factor receptor inhibition in non‐small‐cell lung cancer

The identification of oncogenic driver mutations in non‐small‐cell lung cancer (NSCLC) has led to the development of targeted drugs. Tyrosine kinase inhibitors (TKIs) directed against the epidermal growth factor receptor (EGFR) target lung tumours bearing EGFR‐activating mutations. This new therapeutic strategy has greatly improved tumour response rates. However, drug resistance invariably occurs during TKI‐based treatment. Epithelial‐to‐mesenchymal transition (EMT) is one of the resistance mechanisms identified in EGFR‐mutated NSCLC treated with TKIs. In this review we gather together the most important findings on this phenomenon in relation to cancer stem cells and cancer epigenetics. We also outline the correlation between the effects of stromal factors from the microenvironment, the transcription factors activated, the epigenetic changes in chromatin, and the evolution of cellular behaviour. Notably, EMT has already been shown to be the link between benign lung diseases such as chronic obstructive pulmonary disease and lung carcinogenesis. The various mechanisms of acquired resistance to EGFR‐TKIs are also briefly described to provide background information on EMT. Our extensive review of the scientific literature serves to highlight the cellular and molecular events that lead to the onset of EMT in NSCLC cells treated with EGFR‐TKIs. Finally, we put forward a hypothesis to explain why, in some cases, EMT rather than other known mechanisms is involved in resistance to TKIs.