Miracle-dz/UniFAR-FTUs huggingface dataset:
Capturing Multiple Timescales of Adaptation to Second-Order Statistics With Generalized Linear Models: Gain Scaling and Fractional Differentiation

Single neurons can dynamically change the gain of their spiking responses to account for shifts in stimulus variance. Moreover, gain adaptation can occur across multiple timescales. Here, we examine the ability of a simple statistical model of spike trains, the generalized linear model (GLM), to account for these adaptive effects. The GLM describes spiking as a Poisson process whose rate depends on a linear combination of the stimulus and recent spike history. The GLM successfully replicates gain scaling observed in Hodgkin-Huxley simulations of cortical neurons that occurs when the ratio of spike-generating potassium and sodium conductances approaches one. Gain scaling in the GLM depends on the length and shape of the spike history filter. Additionally, the GLM captures adaptation that occurs over multiple timescales as a fractional derivative of the stimulus variance, which has been observed in neurons that include long timescale after hyperpolarization conductances. Fractional differentiation in GLMs requires long spike history that span several seconds. Together, these results demonstrate that the GLM provides a tractable statistical approach for examining single-neuron adaptive computations in response to changes in stimulus variance.
Geographic and Habitat-Based Variation in Lingcod (Ophiodon Elongatus) Demography and Life-History Along the U.S. West Coast

Fish populations exhibit variation in life-history and demography based on a variety of biological, environmental, and anthropogenic factors. Understanding the spatial patterns in life-history variability for commercially exploited fish stocks is important when making management decisions and designating stock boundaries. Between 2015 and 2017, 2,189 Lingcod were collected from seven geographically distinct regions along the West Coast to investigate latitudinal patterns in population distribution, growth, timing of maturity, condition, and natural and fishing mortality. Life history parameters of growth, maturity, longevity, condition, and natural and total mortality were calculated and compared for Lingcod in each region and by sex. A principle components analysis was used to relate trends in life-history parameters to coastwide environmental patterns in sea surface temperature and productivity. Non-metric multidimensional scaling ordination plot and PERMANOVA were used to identify biologically relevant breakpoint(s) for Lingcod along the U.S. West Coast. The results from this study demonstrate that Lingcod exhibit strong latitudinal patterns in life history that is consistent with Bergmann’s Rule, where Lingcod from colder, northern waters grow faster and larger, live longer, mature at larger sizes, and have lower natural mortality rates than Lingcod from warmer, southern waters. Lingcod total mortality rates did not follow a latitudinal trend but were highest in Washington and Southern California regions, which is consistent with historic fishing practices, current fishing pressure, and local patterns of productivity within those regions. Between sexes, female Lingcod were found to grow faster and larger, live longer, mature at larger sizes, and were in worse condition than male conspecifics. These findings suggest that while Lingcod life-history traits related to age, growth, and condition are strongly influenced by localized patterns of temperature and oceanography along the coast, there can be considerable variation based on a regions’ history of exploitation. A biologically relevant breakpoint for Lingcod along the U.S. West Coast was identified at the central Oregon coast, dividing the Lingcod stock into northern and southern substocks. The coastwide Lingcod population and fishery may benefit by using this boundary as a biologically appropriate break point when conducting future stock assessments. Implications for applying these findings to other federally managed groundfish species and stock assessment models are discussed.
Your Cheating Cognitions: Young Women’s Responses to Television Messages about Infidelity

The current study examined how exposure to a depiction of sexual infidelity on television influenced women’s responses to hypothetical infidelity. In addition, we examined three individual factors as moderators for these effects: experience with infidelity, infidelity concern, and loyalty concern. In a laboratory experiment, young women were exposed to a media narrative featuring either a romantic relationship, the same relationship but with one partner engaging in sex outside the relationship, or a control narrative before completing measures of reactions to hypothetical relationship transgressions. Results indicated that women who had a cheating partner and exhibited high levels of concern about infidelity reported a lower tolerance for infidelity following exposure to a television narrative featuring infidelity.
Effect of Black Seed Oil on Some Physiological Parameters in Female Rats Treated with Aflatoxin B1, B2

This study was conducted in order to determine the effect of Black seed oil on the reduction of the negative effects of the Aflatoxin B1, B2 produce from Aspergillus flavus in white rat females and effect it's on the physiological blood parameters. The results of isolation and initial diagnosis showed Aspergillus flavus and Aspergillus niger in all samples studied percentage (100%) and isolated from the seeds of rice while the percentage of the emergence of fungi Penicillium spp and Trichothecium spp and Rhizopus spp rates ranged (50, 45, 14)% respectively of the samples studied. The results showed that Black seed oil had a significant effect on the physiological parameters of blood. The rate of white blood cells (WBC) increased to (15 × 10 3 and 21 × 103) cells/mm3 when treated with Aflatoxin B1 (AFB1) and Aflatoxin B2 (AFB2) compared to control treatment. The results showed that the Black seed had decreased the rate of white blood cells when used with aflatoxin (AFB1+ 800) and (AFB2 + 800) mg/kg oil to (11.5 × 103 and 7.5× 103 cell/mm 3 respectively.
IN SITU NUTRIENT DEGRADABILITY OF BANANA (Musa sapientum) PSEUDOSTEM AND WATER HYACINTH [Eichhornia crassipess (Mart.)] IN DAIRY CATTLE

In situ degradation of banana pseudostem (BPS) and water hyacinth (WH) in cannulated dairy cattle were investigated. The samples were dried, ground and inserted into a digestion bag before they were incubated inside the rumen of the cannulated dairy cattle for 3, 6, 12, 24, 48 and 72 h. Results showed that DM degradable fractions in BPS and WH were greater compared (P<0.05) to Napier grass (NG). Degradable OM fractions were greatest in BPS which may indicate more readily available OM in BPS for rumen microorganisms. Degradable fractions of NDF were the same among the feed samples. The degradation curves of the three samples showed that banana pseudostem had the highest DM degradability of 80% at 12 h. It is also seen that after 72 h, the total DM degraded was the same for all treatments.
Prevalence and associated factors of metabolic syndrome and its individual components among adolescents

Metabolic syndrome is a growing health problem that affects the whole population including adolescents due to change in lifestyles. It is strongly associated with different lifestyle behavioral factors. The objective of the study was to investigate the magnitude and associated factors of metabolic syndrome in adolescents. School based cross-sectional study design was used. The sample size for this study was 844 and 8 high schools were randomly selected from Addis Ababa city Administration. Simple random sampling technique was used to select each participant. Data was analyzed using SPSS version 24 and descriptive summary statistics produced to present the findings. In this study among the components of metabolic syndrome, the highest prevalence was observed in high level of fasting blood glucose level 57.8%, followed by high waist circumference 32.2%. The overall prevalence of metabolic syndrome from the total study participants was 12.4%. Smoking, alcohol intake, performing vigorous or modern physical activity, body mass index and time spent for sedentary activities were factors which had significant association with individual metabolic abnormalities. In conclusions the magnitude of metabolic syndrome is common problem of adolescents in the study area.
A study on development of ear ossicles from prenatal to postnatal life of humans

Background: Malleus, incus and stapes are the three ear ossicles present in middle ear. The auditory ossicles of the middle ear have a fundamental role in transmission of sound. The aim of this study was to determine development of ear ossicles from prenatal to postnatal life which will be of great help for an ENT surgeon who should be well conversant with the anatomical details of middle ear prior to undertake reconstruction procedures for the improvement of sound conduction in conductive deafness. Methods: The study was conducted in 25 foetuses and 25 adult ossicles after removal from temporal bones of embalmed cadavers. Vernier caliperse was used to measure different morphometric parameters to study growth and development of ossicles. Results: Malleus: The average length of Malleus varies from 4 to 7.24mm in foetuses and adults respectively. The length of the anterior process was variable and some of the processes were quite long. Incus: The incus had minimum morphological variations in the ossicles. Its length ranges from 4.97-6.94mm. Stapes: The stapes had maximum morphological variations in the ossicles. The variations of stapes were in the neck, the cruses and the foot plate. The variations seen in stapes were no neck, a short or a long neck. The cruses of the stapes had symmetry or asymmetry. Length varies from 2.45-3.8mm. Conclusions: Ossicles at 20 weeks of prenatal life were cartilagenous, and at 24 weeks they were ossified and surrounded by mesenchyme. Postnatal changes were minimal. These parameters of Ossicles will help in designing of implants and treating hearing loss.
An investigation on coordination of lane departure warning based on driver behaviour characteristics

As an important part of Advanced Driver Assistance Systems (ADAS), Lane Departure Warning System (LDWS) plays a significant role in lane departure prevention and reducing traffic accidents caused by lane departure. In order to improve the warning effect of the system as well as driver acceptance, this paper describes an LDWS algorithm for personalised driving assistance. The proposed combination algorithm consists of a multi-mode Time to Lane Crossing (TLC) and a Future Offset Distance (FOD) based on driver behaviour characteristics. To detect driver's lane change intention, the steering behaviour has been developed incorporating vehicle states and road curvature. Driving simulator tests are conducted to validate the lane departure warning algorithm with multi-mode based on TLC and FOD under various driving situations. The obtained test results are consistent with the expected performance.
CDDO Me Provides Kidney Protective Impacts against Ischemia/Reperfusion Injury via Inhibition of Oxidative Stress and Inflammation by Targeting Nrf2 and NF-kB Signaling Pathways

Ischemia reperfusion injury (IRI) is a causative factor of organ failure as in renal ischemia which is associated with increasing of mortality rate. It is a popular pathological condition mainly accompanied with an aggravation of tissue injury. Oxidative stress and Inflammation participate in the pathophysiology of renal IRI. This is by increasing the production of reactive oxygen species, pro-inflammatory cytokines and chemokine and other immune mediators which intensify the kidney damage. Previous studies have demonstrated that CDDO Me has cytoprotective, antioxidant, anti-inflammatory, and immunomodulating properties. This study aims to investigate the renoprotective impacts of CDDO Me (Bardoxolone methyl) in rat model IRI by targeting of Nrf2, NF-kB signaling pathway. Rats in control and vehicle groups demonstrated significant elevation in BUN, Scr, NGAL, F2-isoprostane. Furthermore, activated NF-kB, and Nrf2 pathways, and HO-1 was increased. Kidneys of pretreated rats with CDDO Me showed histological and functional amelioration as evidenced by significant reduction in BUN, Scr and NGAL, significant reduction in F2-isoprostane. Moreover, it was found that Nrf2 pathway was significantly more activated and HO-1 more expressed in renal tissue when compared with control and vehicle groups. The anti-inflammatory effects of CDDO Me appeared clearly through the significant inhibition of NF-kB pathway. CDDO me alleviated the kidney damage that induced by bilateral renal IR, and this protective impacts may be done by activating the Nrf2 and rising its downstreamHO-1 and inhibition of NF-kB pathway.
Prediction of viscosity of ternary tin-based lead-free solder melt using BP neural network

Purpose Viscosity is an important basic physical property of liquid solders. However, because of the very complex nonlinear relationship between the viscosity of the liquid ternary Sn-based lead-free solder and its determinants, a theoretical model for the viscosity of the liquid Sn-based solder alloy has not been proposed. This paper aims to address the viscosity issues that must be considered when developing new lead-free solders. Design/methodology/approach A BP neural network model was established to predict the viscosity of the liquid alloy and the predicted values were compared with the corresponding experimental data in the literature data. At the same time, the BP neural network model is compared with the existing theoretical model. In addition, a mathematical model for estimating the melt viscosity of ternary tin-based lead-free solders was constructed using a polynomial fitting method. Findings A reasonable BP neural network model was established to predict the melt viscosity of ternary tin-based lead-free solders. The viscosity prediction of the BP neural network agrees well with the experimental results. Compared to the Seetharaman and the Moelwyn–Hughes models, the BP neural network model can predict the viscosity of liquid alloys without the need to calculate the relevant thermodynamic parameters. In addition, a simple equation for estimating the melt viscosity of a ternary tin-based lead-free solder has been proposed. Originality/value The study identified nine factors that affect the melt viscosity of ternary tin-based lead-free solders and used these factors as input parameters for BP neural network models. The BP neural network model is more convenient because it does not require the calculation of relevant thermodynamic parameters. In addition, a mathematical model for estimating the viscosity of a ternary Sn-based lead-free solder alloy has been proposed. The overall research shows that the BP neural network model can be well applied to the theoretical study of the viscosity of liquid solder alloys. Using a constructed BP neural network to predict the viscosity of a lead-free solder melt helps to study the liquid physical properties of lead-free solders that are widely used in electronic information.
Risk Management in Global CRM IT Projects

Abstract Global information technology projects are risky with failure rates for customer relationship management information technology (CRM IT) projects estimated to 70 percent. These failures are often due to multiplicity of factors including poor risk management. The project management literature points out four broad types of risks: technical, external, organizational, and other risk factors. Project manager’s basic job, therefore, becomes to manage the risks and ensure that an IT project is steered to completion while meeting the objectives. Unmanaged risks run into chances of failure and ultimately impacting the CRM project and the reputation of the consultant. Payne and Frow’s (2005) advocates the need for a structured study on the information technology implementations of these projects. The objectives of the study are to investigate: how project risks in CRM- IT implementations impact the final outcome and how the risk management process adopted by the IT project manager impacts the final outcome of the project. The research was conducted administering questionnaire to 135 project managers. It was found that project risk impact cost, time, and technical performance and risk management process impacts planning, support of customers as well as top management.
Formative evaluation on acceptance and usage of ‘e-learning’ platforms in developing countries: A case of Zimbabwe

Background: The late uptake of technology in education in developing countries has necessitated this study through an evaluation on how Performance Expectancy (PE) and Facilitating Conditions (FC) influence teachers’ behaviour on acceptance and usage of an e-learning platform called Ruzivo. Objective: To investigate teachers’ perceptions on the influence of their acceptance and use of the Ruzivo E-Learning Platform (RELP) through addressing the following key research questions: To what extent do teachers’ perceptions of the use of the RELP enhance learning outcomes? What FC support teachers’ use of the Platform? Method: Based on the Unified Theory of Acceptance and Usage of Technology (UTAUT) model and its variants, a multiple-embedded case study based on both quantitative and qualitative research approaches was designed. Three primary schools participated in a questionnaire survey which captured the knowledge, perceptions and attitudes of teachers on PE and FC. Data on teachers experience with PE and FC was sought from a total of 18 teachers, (11 female and 7 male). Results: The use of RELP has resulted in enhanced student learning outcomes and in the building of constructivist learning environments. Facilitating conditions such as the lack of adequate internet facilities, training and computer resources limit usage. Conclusion: The content of Ruzivo should be revised to align with the demands of the updated curriculum, teachers need additional training on computer, and the project needs to be scaled up to realise the ‘access to education’ goal. Further, an accelerated adoption of e-learning platforms in institutions of learning is warranted.
Voltage tracking of bridgeless PFC cuk converter using PI controller

This paper proposes a Proportional-Integral (PI) control voltage tracking of Bridgeless Power Factor Correction (BPFC) Cuk converter. In order to investigate the behaviour of different output voltages during overshoot, steady state and step response, P.I controller is designed to set the -42 V, -48 V, -54 V output voltages. The simulation results show that the proposed PI controller able to control the output voltage and achieve fast steady state and step response of BPFC Cuk converter. When the value of output voltage increase, the overshoot voltage will become higher but the steady state respond will be faster. Furthermore, BPFC Cuk converter with P.I controller have low output voltage ripples.
Li–Ni-Oxide Nanoparticle Synthesis by Induction Thermal Plasmas

Lithium nickel oxide nanoparticles were synthesized by induction thermal plasma. The forming mechanism of the nanoparticle crystal structure was investigated based on nucleation theory and thermodynamic considerations. Synthesized Li–Ni-oxide nanoparticles were nonstoichiometric Li 0.4 Ni 1.6 O 2 (space group Fm3m ) of the Li-deficient system. Stoi- chiometric LiNiO 2 was difficult to synthesize because of its lower thermodynamic stability when compared with NiO in high-temperature region of more than 2248 K. Reactions forming NiO were predominant at temperatures above 2248 K. LiNiO 2 forming reactions were unlikely to occur because Li 2 O was hard to condense onto NiO nuclei above 2248 K. There- fore, nonstoichiometric Li 0.4 Ni 1.6 O 2 is easily generated. This was because Ni had a stable divalent valence and formed a strong bond with O. The Gibbs free-energy change suggested that the divalent Ni 2 + (NiO) is more stable than trivalent Ni 3 + (LiNiO 2 ) at temperatures above 2248 K. This study investigated factors affecting the control of Li–Ni-oxide nanoparticles formed in thermal plasma.
Facial Action Unit Detection with Multilayer Fused Multi-Task and Multi-Label Deep Learning Network

Facial action units (AUs) have recently drawn increased attention because they can be used to recognize facial expressions. A variety of methods have been designed for frontal-view AU detection, but few have been able to handle multi-view face images. In this paper we propose a method for multi-view facial AU detection using a fused multilayer, multi-task, and multi-label deep learning network. The network can complete two tasks: AU detection and facial view detection. AU detection is a multi-label problem and facial view detection is a single-label problem. A residual network and multilayer fusion are applied to obtain more representative features. Our method is effective and performs well. The F1 score on FERA 2017 is 13.1% higher than the baseline. The facial view recognition accuracy is 0.991. This shows that our multi-task, multi-label model could achieve good performance on the two tasks.
Enhancing Energy Efficiency of a 4-DOF Parallel Robot Through Task-Related Analysis

Enhancing energy efficiency is one of the main challenges of today’s industrial robotics and manufacturing technology. In this paper a task-related analysis of the energetic performance of a 4-DOF industrial parallel robot is presented, and the optimal location of a predefined task with respect to the robot workspace is investigated. An optimal position of the task relative to the robot can indeed reduce the actuators’ effort and the energy consumption required to complete the considered operation. The dynamic and electro-mechanical models of the manipulators are developed and implemented to estimate the energy consumption of a parametrized motion with trapezoidal speed profile, i.e., a pick-and-place operation. Numerical results provide energy consumption maps that can be adopted to place the starting and ending points of the task in the more energy-efficient location within the robot workspace.
Evaluation of VI Index Forecasting Model by Machine Learning for Yahoo! Stock BBS Using Volatility Trading Simulation

The risk avoidance is very crucial in investment and asset management. One commonly used index as a risk index is the VI index. Suwa et al.(2017) analyzed stock bulletin board messages and predicted it rise. In our study, we developed a simulation of trading Nikkei stock index options using intra-day data and verified the validity of the VI index prediction model proposed by Suwa et al. In a period from November 18, 2014, to June 29, 2016, we conducted a simulation using a long straddle strategy. The profit and loss from trading with the instructions of their model was +3,021 yen. The benchmark’s profit and loss was -3,590 yen. The improvement with their model was +6,611 yen. Therefore, we confirmed that Suwa et al.’s VI index prediction model might be effective.
The complete chloroplast genome sequence of Acorus gramineus (Acoraceae)

Abstract The complete chloroplast genome sequence of Acorus gramineus was assembled and characterized as a resource for future genetic studies. With a total length of 152,887 bp, the chloroplast genome comprised of a large single-copy (LSC) region of 83,005 bp, a small single-copy (SSC) region of 18,230 bp, and two inverted repeat (IR) regions of 25,826 bp. The overall GC contents of the chloroplast genome were 38.7%. A total of 115 genes were predicted, consisting of 80 protein-coding genes, 31 tRNA genes, and 4 rRNA genes. In these genes, nine genes contained one intron and two genes contained two introns. Phylogenetic analysis confirmed the position of A. gramineus within the monocots.