Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of salt Stress on Root Anatomy and Hydraulic Conductivity of Barley Cultivars

A hydroponic experiment was carried out to compare root anatomy and hydraulic conductivity of four barley cultivars including Valfajr, Karoon, Afzal and Zarjo under salt stress conditions. The results showed that under salt stress, the minimum diameter of vessels was observed in the peripheral metaxylem of seminal roots of Valfajr cultivar and in adventitious roots; Karoon with 19±3 µm had maximum diameter of vessels. In all barely cultivars, salt stress affected the diameter of central and peripheral metaxylem vessels more negatively in comparison to the number of the vessels. The mature xylem vessels of the seminal roots of the Valfajr and Zarjo cultivars had the most lignified cell walls. When the plants were exposed to salt stress, the casparian bands could be detected more in the seminal roots as U-shape and not in the adventitious roots. The lowest lignification thickness of cell wall (0.78 µm) was observed in the central metaxylem vessels of adventitious roots of Afzal cultivar under salt stress. Also, Afzal cultivar with highest surface area and lowest thickness of lignified cell walls, had the highest seminal root hydraulic conductivity (5.84×10-9 m s-1 MPa-1), whereas hydraulic conductivity was decreased to 3.21 and 3.17×10-9 m s-1 MPa-1 in Valfajr and Zarjo cultivars, respectively. Overall, Afzal and Karoon cultivars were found to perform better in water uptake at the early stages of growth due to less lignified cell walls of xylem in seminal and adventitious roots under salt stress conditions. Further research on hydraulic conductivity could be recommended.
The Multiple Resource Probabilistic Interdiction Median Problem

Interdiction is the deliberate act of attempting to destroy or damage a set of components of an infrastructure system to degrade its overall performance. A variety of mathematical interdiction models have been proposed in the literature to identify critical assets in supply systems. In this paper, we present an interdiction model for median systems. In this model, the outcome of an attack is uncertain, i.e. an attack is successful only with a given probability, and the probability of success depends upon the amount of resources invested in the attack. The objective is to allocate the interdiction resources among the system facilities to maximize the expected disruption. We study three modeling alternatives for this problem. We present a computational comparison of the three formulations, an analysis of the solutions obtained, and a study that identi es those parameters that in uence the time performance the most. We also test the robustness of the models to di erent probability distributions. Finally, we present results that demonstrate that the new model is more versatile than Kent Business School, University of Kent, UK. cl243@kent.ac. uk Kent Business School, University of Kent, UK. m.p.scaparra@kent.ac. uk Geography Department, University of California, Santa Barbara, USA. church@geog.ucsb. edu Department of Industrial Engineering and Management Sciences, Northwestern University, USA. m-daskin@northwestern.edu
Trends and Challenges in Developing Context-Aware Music Recommendation Systems

: The development of computer technology and the Internet influence how people buy, save, and listen to music. Today, there are millions of songs that everyone can choose to listen anytime and anywhere. One of many problems arise is, the music listeners are often spending too much time and giving much effort in choosing music to be listened, thus a music recommendation system is needed. Context are important in music recommendation system; people prefer different music for certain activities, or in other words, people would have a different music selection for a certain context. For example, a user who is exercising will prefer a loud and energizing music, a user who is relaxing will prefer a soft and soothing music.This review is focused on trends and challenges in developing context-aware music recommendation system, which uses context as primary features or data to recommend music.Developing context-aware music recommendation system is challenging, it is complicated to meet the user’s needs and requirements. The challenges are come from the great amount of data needed, how to choose context used in the research, cold start, and generating a dynamic playlist.
Phytochemical and Pharmacological Evaluation of Solanum surattense for Antidepressant Activity in Albino Mice

Depression is a heterogeneous mood disorder that has been classified and treated in variety of ways. Although a number of synthetic drugs are being used as standard treatment for clinically depressed patient, the adverse effects compromise the therapeutic outcome. In the traditional systems of medicine, many plants and formulations have been used to treat depression for thousands of years. Solanum surattense is a commonly available plant throughout India and it has been claimed in traditional literature to be valuable plant against a wide variety of diseases. Till date no scientific data was available on the antidepressant activity of this plant. So, the present study was undertaken to investigate the effect of Solanum surattense (Family: Solanaceae), on depression in mice using tail suspension test (TST) and forced swim test (FST). Alcoholic and chloroform extract (50 and100 mg/kg p.o.) of S. surattense administered orally for 14 successive days had decreased the immobility periods significantly in a dose-dependent manner in both TST and FST, showing significant antidepressant-like activity. The activities of the extracts were found to be comparable to imipramine in both FST and TST. The results of this study indicate the potential for use of SS as an adjuvant in the treatment of depression.
Breathing shoes and complementarities: How Geox has rejuvenated the footwear industry

We apply the related notions of complementarities and performance landscapes to study strategic positioning in the footwear industry. We use this theoretical framework to analyze Geox, an Italian footwear manufacturer that, in less than a decade, has grown to be one of the world largest brown shoe manufacturers, outperforming the industry in terms of market and financial results. We describe Geox’s choices within four stages along its value chain: product design, marketing and communication, production and supply chain, distribution and retail. We show that, though grounded on product innovation (the Geox breathes® patented system which allows ventilation in waterproof rubber sole shoes), Geox’s competitive advantage has not grown out of operational excellence in single activities in the business, but, rather, derives from a unique and consistent configuration of complementary activities. Such configuration represents an innovative strategic position and corresponds to a high performance peak in the footwear industry performance landscape. The case study provides anecdotal evidence in support of complementarity based economic theory, showing how complementarities among activities help understand increasing return to scale, firm size and business growth even without the standard assumptions about economies of scale. It also confirms that, in the presence of complementarities, rivals find strategy imitation and reverse engineering difficult due to the unique nature of the relationships among complementary variables. The final section draws some implications in terms of strategic management and organization design.
Chapter 22 Systems-Level Analyses of the Mammalian Innate Immune Response

The regulation of the innate immune response, our first line of defence against infectious disease, does not involve simple linear pathways but rather complex inter-connected networks of interactions, regulatory loops, and multifaceted transcriptional responses. Given this complexity, systems biology approaches to investigate the host innate immune response are essential. InnateDB (www.innatedb.com) is a publicly available database and integrated analysis platform specifically designed to facilitate systems-level analyses of the mammalian innate immune response and is one of the most comprehensive databases of all human and mouse molecular interactions (130,000+) and pathways (3,000+). Building upon this, more than 12,900 innate immunity-relevant molecular interactions have been contextually annotated through detailed review of the literature providing novel insight into the innate immunity interactome. Integrated bioinformatics solutions include the ability to investigate user-supplied quantitative data in a network and pathway context using pathway, ontology and transcription factor over-representation analyses, and network visualisation and analysis tools. In this chapter, we introduce innate immunity as a complex system and a provide a detailed step-by-step guide to using InnateDB and other bioinformatics tools to investigate the host response to infectious disease.
Light-induced states in the transient-absorption spectrum of a periodically pumped strong-field-excited system

The transient-absorption spectrum of a $V$-type three-level system is investigated, when this is periodically excited by a train of equally spaced, $\delta$-like pump pulses as, e.g., from an optical-frequency-comb laser. We show that, even though the probe pulse is not assumed to be much shorter than the pump pulses, light-induced states appear in the absorption spectrum. The frequency- and time-delay-dependent features of the absorption spectra are investigated as a function of several laser control parameters, such as the number of pump pulses used, their pulse area, and the pulse-to-pulse phase shift. We show that the frequencies of the light-induced states and the time-delay-dependent features of the spectra contain information on the action of the intense pulses exciting the system, which can thus complement the information on light-imposed amplitude and phase changes encoded in the absorption line shapes.
Monte Carlo simulations of a simple model for the electrocatalytic CO oxidation on platinum

A simple lattice-gas model for the electrocatalytic carbon monoxide oxidation on a platinum electrode is studied by dynamic Monte Carlo simulations. The CO oxidation takes place through a Langmuir–Hinshelwood reaction between adsorbed CO and an adsorbed OH radical resulting from the dissociative adsorption of water. The model enables the investigation of the role of CO surface mobility on the macroscopic electrochemical response such as linear sweep voltammetry and potential step chronoamperometry. Our results show that the mean-field approximation, the traditional but often tacitly made assumption in electrochemistry, breaks down severely in the limit of vanishing CO surface mobility. Comparison of the simulated and experimental voltammetry suggests that on platinum CO oxidation is the intrinsically fastest reaction on the surface and that CO has a high surface mobility. However, under the same conditions, the model predicts some interesting deviations from the potential step current transients derived f.
Domain Named Entity Discovery and Linking Task

This paper describes a named entity discovery and linking system, which compete the CCKS2017 question named entity discovery and linking task. We are facing challenges including short-text, small training samples and open domain, making the existing solutions unfeasible. In this paper, we propose a CRF + rules method to recognize the corresponding named entity, which employs several features, such as bag-of-word features, POS features, parsing features etc. As for entity linking, context information, popularity, word embeddings, and online public corpus are used. The experiment results show that, the F1 score of named entity discovery is 0.815, while the accuracy of the entity linking is 0.736. The overall F1 score is 0.600, which proves the effectiveness of our system.
Validity of Digital and Rapid Prototyped Orthodontic Study Models

Background: The integration of modern computer-aided design and manufacturing technologies in diagnosis, treatment planning, and appliance construction is changing the way in which orthodontic treatment is provided to patients. The aim of this study is to assess the validity of digital and rapid prototyped orthodontic study models as compared to their original stone models. Materials and methods: The sample of the study consisted of 30 study models with well-aligned, Angle Class I malocclusion. The models were digitized with desktop scanner to create digital models. Digital files were then converted to plastic physical casts using prototyping machine, which utilizes the fused deposition modeling technology. Polylactic acid polymer was chosen as the printing material. Twenty four linear measurements were taken from digital and prototyped models and were compared to their original stone models “the gold standard”, utilizing the paired sample t-test and Bland-Altman plots. Results: Eighteen of the twenty four variables showed non-significant differences when digital models were compared to stone models. The levels of agreement between the two methods showed that all differences were within the clinically accepted limits. For prototyped models, more than half of the variables differed in non-significant amount. The levels of agreement were also within the clinically accepted limits. Conclusion: Digital orthodontic study models are accurate in measuring the selected variables and they have the potential to replace conventional stone models. The selected rapid prototyping technique proved to be accurate in term of diagnosis and might be suitable for some appliance construction.
Airglow observations of dynamical (wind shear‐induced) instabilities over Adelaide, Australia, associated with atmospheric gravity waves

While several observations have been made in recent years of instability features in airglow images of atmospheric gravity waves (AGWs), such measurements are still rare. To date, these features are characterized by appearing to be aligned perpendicular to the AGW wave fronts. Multi-instrument observations confirm the theoretical prediction that such features are caused by convective instabilities where the AGW-induced temperature variation causes the total lapse rate to exceed the adiabatic lapse rate. In February 2000, airglow observations were obtained at Buckland Park, Australia, which showed instability features with a different characteristic. These images showed small-scale (less than 10 km horizontal wavelength) features aligned parallel to the larger scale AGW wave fronts. These features were only seen in OH images, not in O2A images, indicating that they originate below 90 km altitude. Simultaneous MF radar wind data reveal the presence of a mean wind shear which, during the period of the small-scale features, was aligned nearly in the direction of AGW propagation. In addition, the larger scale AGW approached a critical level near 90 km altitude. While the wind shear itself is not large enough to cause an instability, an analysis of the data suggests that the small-scale features are the result of a dynamic (wind shear-induced) instability in the 87–90 km altitude region. The instability was due to a combination of the background wind shear and the large shear induced by the passage of the larger scale AGW as it approached the critical level.
Formulation and characterization of a novel pH-triggered in-situ gelling ocular system containing Gatifloxacin

The present research work deals with the formulation and evaluation of in-situ gelling system based on sol-to-gel transition for ophthalmic delivery of an antibacterial agent gatifloxacin, to overcome the problems of poor bioavailability and therapeutic response exhibited by conventional formulations based a sol-to-gel transition in the cul-de-sac upon instillation. Carbopol 940 was used as the gelling agent in combination with HPMC and HPMC K15M which acted as a viscosity enhancing agent. The prepared formulations were evaluated for pH, clarity, drug content, gelling capacity, bioadhesive strength and in-vitro drug release. In-vitro drug release data of optimized formulation (F12) was treated according to Zero, First, Korsmeyer Peppas and Higuchi kinetics to access the mechanism of drug release. The clarity, pH, viscosity and drug content of the developed formulations were found in range 6.0-6.8, 10-570cps, 82-98% respectively. The gel provided sustained drug release over an 8 hour period. The developed formulation can be used as an in-situ gelling vehicle to enhance ocular bioavailability and the reduction in the frequency of instillation thereby resulting in better patient compliance. Key Words: In-situ gelation; Gatifloxacin; Carbopol 940; HPMC K15M. DOI: http://dx.doi. org/10.3329/icpj.v1i3. 9661 International Current Pharmaceutical Journal 2012, 1(3): 43-49
Atmospheric velocity fields in tepid main sequence stars

Context. The line profiles of the stars with ve sin i below a few km s −1 can reveal direct signatures of local velocity fields such as convection in stellar atmospheres. This effect is well established in cool main sequence stars, and has been detected and studied in three A stars. Aims. This paper reports observations of main sequence B, A and F stars (1) to identify additional stars with suffi ciently low values of ve sin i to search for spectral line profile signatures of local veloc ity fields, and (2) to explore how the signatures of the local v elocity fields in the atmosphere depend on stellar parameters such as effective temperature and peculiarity type. Methods. We have carried out a spectroscopic survey of B and A stars of low ve sin i at high resolution. Comparison of model spectra with those observed allows us to detect signatures of the loc al velocity fields such as asymmetric excess line wing absorp tion, best-fit ve sin i parameter values that are found to be larger for strong lines than for weak lines, and discrepancies between observed and modelled line profile shapes. Results. Symptoms of local atmospheric velocity fields are always det ected through a non-zero microturbulence parameter for main sequence stars having Te below about 10000 K, but not for hotter stars. Direct line profile tracers of the atmospheric velocity field are found in six very sharp-lined stars in addition to the three r eported earlier. Direct signatures of velocity fields are fo und to occur in A stars with and without the Am chemical peculiarities, although the amplitude of the effects seems larger in Am stars. Velocity fields are also directly detected in spectral line profiles of A and e arly F supergiants, but without significant line asymmetrie s. Conclusions. We confirm that several atmospheric velocity field signature s, particularly excess line wing absorption which is strong er in the blue line wing than in the red, are detectable in the spe ctral lines of main sequence A stars of suffi ciently low ve sin i. We triple the sample of A stars known to show these effects, which are found both in Am and normal A stars. We argue that the observed line distortions are probably due to convective motions reachin g the atmosphere. These data still have not been satisfactor ily explained by models of atmospheric convection, including numerical simulations.
Eddy current damping for magnetic levitation : downscaling from macro-to micro-levitation

Magnetic levitation of miniaturized objects is investigated in this paper. A magnetic levitation setup is built to implement one-dimensional magnetic levitation motion. It was observed that as the levitated object becomes smaller, magnetic levitation suffers more from undesired vibrations. As a solution, eddy current damping is offered and implemented successfully by placing conductive plates close to the levitated object. An analytical expression for damping coefficient is derived. Experimentally, it is shown that eddy current damping can reduce the RMS positioning error to the level of more than one third of its original value for a 0.386 g object levitated in an air-gap region of 290 mm. The proposed system has the potential to be used for micro-manipulation purposes in a high motion range of 39.8 mm.
Differentiated Service-Aware Group Paging for Massive Machine-Type Communication

Massive machine-type communication (mMTC) has been identified as one of the three generic 5G services, with the aim of providing connectivity to a large number of devices. The concurrent massive access in mMTC may lead to congestion due to limited access resources. Group paging (GP) is emerging as one of the promising solutions to alleviate network congestion by controlling access load. However, the performance of GP deteriorates drastically with the number of devices per paging group. This paper explores GP with a pre-backoff strategy for a general mMTC scenario in which devices are allowed to have diverse access success probability (ASP) requirements, and proposes a differentiated service-aware GP scheme with specific pre-backoff times (GPSP), with the aim of maximizing the total access rate while guaranteeing the ASP requirements for individual devices. An optimal solution to the GPSP problem is derived to provide a performance upper bound. As low-complexity algorithms are of key importance for mMTC applications, an efficient heuristic algorithm is further designed. Numerical results demonstrate that the proposed GPSP scheme can effectively improve the system performance in terms of average ASP, average access delay, and the average number of preamble transmissions.
SSFCN-DCRF: Semantic Segmentation for Biomedical Image

In this paper, we present an end-to-end solution for the task of semantic biomedical image segmentation. We use skip stride Fully Convolutional Networks to output segmentation map. To further improve the performance of the semantic segmentation, we use the dense conditional random field (DCRF) layer to fine tune the segmentation map. We also apply separable operation to the Fully Convolutional Networks to get a lightweight network. We evaluate our network on Kaggle Lung CT Dataset and UCSB Bio-Segmentation Benchmark. The results show that our network achieves state of art performance on semantic segmentation for biomedical Image.
Deep Neural Networks based Modrec: Some Results with Inter-Symbol Interference and Adversarial Examples

Recent successes and advances in Deep Neural Networks (DNN) in machine vision and Natural Language Processing (NLP) have motivated their use in traditional signal processing and communications systems. In this paper, we present results of such applications to the problem of automatic modulation recognition. Variations in wireless communication channels are represented by statistical channel models and their parameterization will increase with the advent of 5G. In this paper, we report effect of simple two path channel model on our naive deep neural network based implementation. We also report impact of adversarial perturbation to the input signal.