Miracle-dz/UniFAR-FTUs huggingface dataset:
Ameliorative Effects of Kolaviron on Behavioural Deficits and Oxidative Damage in Prefrontal Cortex and Hippocampus of Cuprizone-Induced Demyelinated Mice

Cuprizone neurotoxicity is commonly induced to mimic demyelinating disorders of the central nervous system, especially multiple sclerosis. This study assessed the role of kolaviron, a Garcinia kola biflavonoid, in restoring behavioural functions in cuprizone-induced neurotoxicity after termination of cuprizone treatment. Eighteen adult male Swiss albino mice aged between 6-8 weeks were randomly divided into 3 equal groups (A to C). Group A (control) mice were fed with normal rodent diet while groups B and C received 0.2% cuprizone diet for 5 weeks to induce demyelination; thereafter group B mice with cuprizone-induced demyelination were administered corn oil (0.5 mL), while group C mice with cuprizone-induced demyelination were administered kolaviron (200 mg/kg/d) for 14 days. The mice were assessed for learning, memory, anxiety and exploratory drive, and thereafter the concentration of malondialdehyde (MDA) and activities of superoxide dismutase (SOD) and glutathione peroxidase (GPx) in the prefrontal cortex and hippocampus of the mice were evaluated. Findings revealed improved behavioural outcomes in mice treated with kolaviron compared to control and the untreated cuprizone-induced demyelinated mice. There was significant reduction in SOD and GPx activities with significant increase in MDA concentration in the untreated cuprizone-induced mice compared to controls. However, there was significant increase in SOD and GPx activities with significant reduction in MDA concentration in the kolaviron-treated cuprizone-induced mice compared to those of untreated cuprizone-induced mice. The results suggest that kolaviron may effectively ameliorate the oxidative damage and behavioural deficits associated with cuprizone-induced neurotoxicity.
Unsupervised Disentanglement of Pitch and Timbre for Isolated Musical Instrument Sounds

Disentangling factors of variation aims to uncover latent variables that underlie the process of data generation. In this paper, we propose a framework that achieves unsupervised pitch and timbre disentanglement for isolated musical instrument sounds without relying on data annotations or pre-trained neural networks. Our framework, based on variational auto-encoders, takes as input a spectral frame, and encodes pitch and timbre as categorical and continuous variables, respectively. The input is then reconstructed by combining those variables. Under an unsupervised training setting, a major challenge is that encoders are tasked to capture factors of interest with distinct latent representations, without access to the corresponding ground-truth labels. We therefore introduce auxiliary tasks and objectives which leverage pitch shifting as a strategy to create surrogate labels, thereby encouraging the disentanglement of pitch and timbre. Through an ablation study we analyze the impact of the proposed objectives. The evaluation shows the efficacy of the proposed framework for learning disentangled representations, and verifies its applicability to unsupervised pitch classification and conditional spectral synthesis.
Evaluation of Two Cloud-Resolving Models Using Bin or Bulk Microphysics Representation for the HyMeX-IOP7a Heavy Precipitation Event

The Mediterranean region is frequently affected in autumn by heavy precipitation that causes flash-floods or landslides leading to important material damage and casualties. Within the framework of the international HyMeX program (HYdrological cycle in Mediterranean EXperiment), this study aims to evaluate the capabilities of two models, WRF (Weather Research and Forecasting) and DESCAM (DEtailed SCAvenging Model), which use two different representations of the microphysics to reproduce the observed atmospheric properties (thermodynamics, wind fields, radar reflectivities and precipitation features) of the HyMeX-IOP7a intense precipitating event (26 September 2012). The DESCAM model, which uses a bin resolved representation of the microphysics, shows results comparable to the observations for the precipitation field at the surface. On the contrary, the simulations made with the WRF model using a bulk representation of the microphysics (either the Thompson scheme or the Morrison scheme), commonly employed in NWP models, reproduce neither the intensity nor the distribution of the observed precipitation—the rain amount is overestimated and the most intense cell is shifted to the East. The different simulation results show that the divergence in the surface precipitation features seems to be due to different mechanisms involved in the onset of the precipitating system: the convective system is triggered by the topography of the Cévennes mountains (i.e., south-eastern part of the Massif Central) in DESCAM and by a low-level flux convergence in WRF. A sensitivity study indicates that the microphysics properties have impacted the thermodynamics and dynamics fields inducing the low-level wind convergence simulated with WRF for this HyMeX event.
3-Dimensional finite element modelling of asphalt mixtures for thermal conductivity determination

ABSTRACT Laboratory determination of the thermal conductivity k of asphalt materials is time consuming. Numerical determination of k is more viable practically for the purpose of mix design and paving temperature control. Researchers have applied microstructure finite element models for k determination. The method requires modelling skills and is computational resources demanding. This study shows that a simple row-column finite-element model of cubical cells can be employed to predict k with the same level of accuracy as microstructure models. Based on theoretical considerations of heat conduction mechanism and the construction and paving process of asphalt mixtures, this study reveals that exact mixture microstructure representation is unnecessary and impractical for the k determination problem. The simple proposed model, having straight-forward finite-element mesh representation and high computational efficiency, offers a practical tool for k determination to enable timely thermal evaluation of mix design, temperature analysis for paving control, and structural behaviour study under thermal loading.
SMES’ E-COMMERCE ADOPTION TOWARDS CONSUMER EXPERIENCE

This study aims to determine how the effect of e-commerce adoption on SMEs towards consumer experience in shopping online and its impact on repurchases. This research is a quantitative study with a survey method. The analytical tool used is Structural Equation Modeling. The sample size in this study is 205 respondents who have made transactions on the fashion SME e-commerce websites. The results showed that the better the adoption of e-commerce carried out by SMEs fashion, the better it is in providing a good experience for consumers, which ultimately made consumers repurchase on the website. This study provides new measurements of consumer responses in the form of experience after using SME e-commerce websites.
Data-driven innovation processes within federated networks

PurposeWithin digital innovation, there are two significant consequences of the pervasiveness of digital technology: (1) the increasing connectivity is enabling a wider reach and scope of innovation structures, such as innovation networks and (2) the unprecedented availability of digital data is creating new opportunities for innovation. Accordingly, there is a growing domain for studying data-driven innovation (DDI), especially in contemporary contexts of innovation networks. The purpose of this study is to explore how DDI processes take form in a specific type of innovation networks, namely federated networks.Design/methodology/approachA multiple case study design is applied in this paper. We draw our analysis from data collected over six months from four cases of DDI. The within-analysis is aimed at constructing the DDI process instance in each case, while the crosscase analysis focuses on pattern matching and cross-case synthesis of common and unique characteristics in the constructed processes.FindingsEvidence from the crosscase analysis suggests that the widely accepted four-phase digital innovation process (including discovery, development, diffusion and post-diffusion) does not account for the explorative nature of data analytics and DDI. We propose an extended process comprising an explicit exploration phase before development, where refinement of the innovation concept and exploring social relationships are essential. Our analysis also suggests two modes of DDI: (1) asynchronous, i.e. data acquired before development and (2) synchronous, i.e. data acquired after (or during) development. We discuss the implications of these modes on the DDI process and the participants in the innovation network.Originality/valueThe paper proposes an extended version of the digital innovation process that is more specifically suited for DDI. We also provide an early explanation to the variation in DDI process complexities by highlighting the different modes of DDI processes. To the best of our knowledge, this is the first empirical investigation of DDI following the process from early stages of discovery till postdiffusion.
The Separation of Deuterium and Tritium on PT/SDB/PS and PT/C/PTFE Hydrophobe Catalysts

The nature and performance of our patented catalysts, with platinum on carbon and polytetrafluorethylene [Pt/C/PTFE] and platinum on styrenedivynilbenzene and polystyrene [Pt/STB/PS], used in a water-hydrogen isotope exchange process are presented. The behaviour of the two catalysts in tritiated water was tested by determining their physical and structural characteristics as well as the catalytic activity before and after immersion in tritiated water. The test results emphasized that the two catalysts are highly active in the hydrogen - water vapor (H{sub 2(g)}-H{sub 2}O{sub (v)}) isotopic exchange and highly stable to tritium radiation. It was discovered that Pt/SDB/PS catalyst proved to be quite unstable in the hydrogen- water vapor - water (H{sub 2(g)}-H{sub 2}O{sub (v)}-H{sub 2}O{sub (1)}) isotopic exchange, while the Pt/C/PTFE catalyst was highly stable. Thus, the Pt/C/PTFE catalyst was chosen for hydrogen isotope separation by liquid hydrogen cryogenic distillation combined with water - hydrogen isotopic exchange in a demonstration scale plant. 5 refs., 8 figs., 2 tabs.
Optimizing Connected Target Coverage in Wireless Sensor Networks Using Self-Adaptive Differential Evolution

Wireless Sensor Networks (WSNs) are advanced communication technologies with many real-world applications such as monitoring of personal health, military surveillance, and forest wildfire; and tracking of moving objects. Coverage optimization and network connectivity are the critical design issues for many WSNs. In this study, the connected target coverage optimization in WSNs is addressed and it is solved using self-adaptive differential evolution algorithm (SADE) for the first time in literature. A simulation environment is set up to measure the performance of SADE for solving this problem. Based on the experimental settings employed, the numerical results show that SADE is highly successful for dealing with connected target coverage problem and can produce higher performance in comparison with other widely-used metaheuristic algorithms such as classical DE, ABC, and PSO.
The Chemical Composition of the Essential Oil and Alcoholic extract of Juniperus communis L. ssp. nana Syme

Abstract The chemical composition of the essential oil of Portuguese juniper berries (Juniperus communis L. ssp. nana Syme) was investigated by means of gas chromatography. This analysis was compared with that of an aqueous alcoholic extract of the juniper berries of similar origin. The qualitative composition of the oil and the alcoholic extract was found to be very similar. The major hydrocarbon components of the oil were α-pinene (20.0%), δ-cadinene (10.4%), limonene (8.7%), and myrcene (8.5%), whereas the alcoholic extract contained α-pinene (11.0%), δ-cadinene (12.8%), β-caryophyllene (9.8%) and germacrene D (9.3%). The main oxygenated constituent in both the oil and the extract was borneol (8.0–8.6% respectively).
Water Suspension Infiltration with Adsorption Including Heat Transport in Unsaturated-Saturated Porous Media

Transportation of heat and water suspension (water and silt) in unsaturated-saturated porous media is considered. Moreover, the water in suspension is contaminated and this contaminant is adsorbed by the porous media matrix. Also, the inner heat exchange between water suspension and the matrix of porous media is considered in the complex model. The deposition of silt in the matrix is characterized by a filtration function and the contaminant adsorption is modeled by a sorption isotherm. The mathematical model includes a coupled system for the water suspension infiltration, silt, and contaminant (uniformly mixed in the water) transport with dispersion and their deposition and adsorption in porous media. Filtration function expresses the rate of silt deposition depending on the amount of (immobile) deposited silt. Contaminant adsorption is modeled in terms of the contaminant concentration in suspension, the amount of adsorbed contaminant, and the rate of adsorption. The main goal is to develop a suitable numerical approximation that can be applied to the solution of direct and inverse problems. In the numerical experiments, we demonstrate the correctness and the effectiveness of the used method.
Gender Agreement and Assignment in Spanish Heritage Speakers: Does Frequency Matter?

Gender has been extensively studied in Spanish heritage speakers. However, lexical frequency effects have yet to be explored in depth. This study aimed to uncover the extent to which lexical frequency affects the acquisition of gender assignment and gender agreement and to account for possible factors behind heritage language variability. Thirty-nine English-dominant heritage speakers of Spanish completed a lexical knowledge screening task (Multilingual Naming Test (MiNT)) along with an elicited production task (EPT), a forced choice task (FCT), and a self-rating lexical frequency task (SRLFT). Heritage speakers performed more successfully with high-frequency lexical items in both the EPT and the FCT, which examined their acquisition of gender assignment and gender agreement, respectively. Noun canonicity also affected their performance in both tasks. However, heritage speakers presented differences between tasks—we found an overextension of the masculine as well as productive vocabulary knowledge effects in the EPT, whereas the FCT showed an overextension of the feminine and no productive vocabulary knowledge effects. We suggest that lexical frequency, determined by the SRLFT, and productive vocabulary knowledge, as measured by the MiNT, account for the variability in the acquisition of gender assignment but not on gender agreement, supporting previous claims that production is more challenging than comprehension for bilinguals.
Dynamic Characteristic of Ethanol Concentration Measurement System

The design of the ethanol concentration measurement system using a specific gravity approach has been previously developed. It was built for batch distillation column automation. The measurement system use a combination of 2 kinds of sensor (i.e. load cell sensor and ultrasonic sensor). However, the dynamic characteristic of the measurement system has not been evaluated. This paper is a continuation of the previous paper. This paper aims to describe the dynamic characteristics of the ethanol concentration measurement system. The dynamic characteristic is another performance analysis besides the static characteristic that present in the previous paper. The dynamic characteristic covers rise time, settling time, and overshoot. This paper also presents a transfer function, pole, and zero location by process the output and input data. This paper concern about dynamic characteristics at one-point operation (75 % of ethanol measuring with a hydrometer) then measured by the ethanol measurement system that was designed in this research. Farther the dynamic characteristic was observed from the device until the device reading was steady-state. The result revealed that the rise time of ethanol concentration of measurement system was 56.4 second, settling time 112.2 second and percentage of overshoot was 1.2%. The measurement system can present the actual data after 117.4 second. Keywords— Dynamic characteristic, ethanol concentration, overshoot, rise time, settling time _________________________________________________________________________________
Improvement of sequence coverage in peptide mass fingerprinting

In order to fully characterize and understand the biological significance of a protein (in a proteomics study), it needs to be characterized with respect to the presence of splice variants, isoforms, and posttranslational processing/modification. This requires full coverage of the protein sequence including that of minor variants of the protein. However, protein identification is often based on sequence coverages as low as 10–20%, and search for the remaining peptides is frequently like the search for the needle in the haystack. Here we present some approaches, which may be helpful for increasing the sequence coverage in proteomics studies. Keywords: peptide mass fingerprinting; sequence coverage; multiple enzymatic digestion; ion suppression; MALDI; ESI; LCMS; graphite microcolumn
The effect of fortified Dadih (fermented buffalo milk) with vitamin D3 on caecum cholesterol concentration and high sensitivity c-reactive protein (hs-CRP) level in type 2 diabetes mellitus rat model

Type 2 diabetes mellitus (T2DM) may be developed by a cardiovascular complication. T2DM and its complications associated with a decrease in levels of 25 hydroxyvitamin D below normal. The level of 25-OH-D can increase and it can be gained by probiotics supplementation. Dadih is a probiotic useful as antidiabetic, antiatherosclerotic, and it can reduce serum cholesterol. Vitamin D is beneficial for T2DM since it improves insulin production, acts as an anti-inflammatory and prevents dyslipidemia thereby preventing cardiovascular disease. This research aims to investigate the effects of giving dadih-fortified-vitamin-D3 toward caecum-cholesterol-concentration and hs-CRP-levels to T2DM-induced-rats. This study used a randomized pre-post test with control group design in 30 Wistar rats divided into 5 groups, namely T1, T2, and T3treatment-groups. T3-group was given dadih-fortified-vitamin-D3, while T1 and T2-groups were given vitamin-D3 and dadih, respectively. The control groups were healthy-control (C1), and T2DM (C2). The intervention was given through oral sonde for 28days. The variables analyzed were caecal-cholesterol-concentrations using a spectrophotometer and hsCRP using the ELISA method. The statistical tests were used for the caecum-cholesterol-concentration and hs-CRP levels. The mean of caecum-cholesterol-concentration in the T3-group (83.68 ±1.93mg.100g-1), was higher than T1 (77.99 ±1.70; p = 0.004) and C2-control (24.39 ±1.47; p = 0.0001). The mean of hs-CRP-level post-intervention in the T3-group (4.21 ±0.41 ng.mL-1), was lower than C2 (17.15 ±0.85;p = 0.0001), T1 (6.59 ±0.27; p = 0.0001) and T2 (5.43 ±0.39; p = 0.004). There is a very strong inverse correlation between the concentration of cholesterol and hs-CRP ( r = -0.979, p = 0.0001). The conclusion is dadih-fortified-vitamin-D3 –intervention is better than its single intervention as an anti-inflammation which might relate to the increased caecum-cholesterol-concentration.
Synthesis and single-crystal growth of Ca2-xSrxRuO4

For the study of the quasi-two-dimensional Mott transition system Ca{sub 2-x}Sr{sub x}RuO{sub 4}, we have succeeded in synthesizing polycrystalline samples and also growing single crystals by a floating-zone method. Details of the preparations for the entire solution range are described. The structural, transport, and magnetic properties of both polycrystalline and single-crystal samples are fully in agreement.
Navigating the Web of Informal Institutions When Investing in a Strange Land: Chinese Multinational Enterprises in Australia

Multinational enterprises (MNEs) need to understand and handle various informal institutions in host countries to survive and succeed. How MNEs effectively manage informal institutional characteristics of host countries is an important question for both practitioners and scholars. This paper addresses this important but neglected topic based on an in-depth longitudinal qualitative study. It identifies some key informal institutions in Australia, examines how such institutional distinctiveness shapes the behaviour of Chinese expatriates and MNEs and how they handle such informal institutional differences between China and Australia. Our findings challenge some taken-for-granted assumptions regarding informal institutions in the literature and demonstrate that informal institutions of host countries significantly shape the behaviour of expatriates and firm-level strategies of MNEs.
Usage of multi-objective genetic and multi-objective differential evolution algorithms on energy and spectral efficiencies in massive MIMO systems

There is a significant increase in the use of wireless communication and it is expected that this increase will continue progressively. In the near future, cellular network technologies are expected to be capable of increasing the area throughput hundreds of times in order to cope with the increase in data traffic. Increasing spectral efficiency (SE) with massive multi-input multi-output (Massive MIMO) systems is one of the main methods used to meet these expectations. SE means the amount of information transmitted successfully with each complex sample. Increasing the transmission power and the number of active antennas while increasing the SE increases the amount of energy consumed to very high levels. The fact that high energy consumption is harmful to the environment and costly makes it important to increase energy efficiency (EE). Various studies are carried out with the aim of bringing optimum levels of the SE and EE parameters which has trade-off between each other. Multi-objective intelligent optimization techniques are applied on the trade-off for detecting optimum SE-EE values. In this paper, multi-objective genetic algorithm (MOGA) and multiobjective differential evolution algorithm (MODEA) are used to obtain optimum values of certain factors (amount of transmit power, number of active antennas and number of user equipments). At the last stage, the calculations made for all values of the mentioned factors and the optimization results (performed in a relatively short time compared to these calculations) are shown on the same graph.