Miracle-dz/UniFAR-FTUs huggingface dataset:
Turfgrass and Climate Change

Agronomy Journa l • Volume 109, I s sue 4 • 2017 Climate impacts on biological systems have the potential to disrupt phenological cycles and physiological responses of plants, animals, insects, and diseases. Changes in temperature, precipitation, humidity, solar radiation, and CO2 expected to occur over the next 30 to 40 yr will affect biological systems; however, not all to the same degree. One aspect of climate change that is often understated is that future variations will not be uniform in either space or time, and require a more localized view of the impacts than broad, general statements. This will have large implications for how we consider and evaluate the impacts of climate change on turfgrasses. There is a large body of information on climate impacts on agriculture assembled by the Intergovernmental Panel on Climate Change (IPCC), and several recently published summaries have further documented the impact of a changing climate on agricultural systems (Walthall et al., 2012; Hatfield et al., 2014; Melillo et al., 2014; Porter et al., 2014); however, these have not concentrated on potential effects on turfgrasses. Changes in plant growth are not simply a direct function of climate, but from the interaction of climate with different soil factors such as soil organic matter, soil fertility, erosion, irrigation, fertilizers, and biotic stresses (insects, diseases, and weeds). The interaction of soils with climate change has the potential to increase the vulnerability of plants to climate change because of the effect of soil degradation on soil water availability and nutrient cycling (Hatfield, 2014). A comprehensive analysis of climate impacts on agricultural and horticultural crops by Hatfield et al. (2011) and on pasture and rangeland by Izaurralde et al. (2011) showed temperature and precipitation as major factors affecting plant growth and production. All plants require temperatures within their range for development and growth, and each species has their own specific temperature range. Cool-season turfgrasses have an optimum temperature range between 15 and 24°C, whereas warm-season turfgrasses have an optimum between 27 and 35°C (DiPaola and Beard, 1992). This temperature range determines where these grasses are grown; however, growth is dependent on seasonal precipitation. The ability of soils to provide adequate soil water and nutrients to crops is the foundation for climate resilience, and the integration of climate and soils will determine survivability and economic viability of turfgrasses.
Price elasticity of demand for beef and range improvement decisions.

artificial insemination, crossbreeding, and fall calving. New methods of increasing production from range and tame pasture will have become common. The rancher will have become involved in providing various recreational facilities that will contribute a significant percentage of his income. The range technician will find himself deeply involved in ecological repair of damage caused by resource exploitation and an ever-increasing urban population. WORKMAN ET AL.
The Management and Leadership in Regional Public Authorities of the Kaliningrad Region: Sociological Aspects

Current article considers leadership problems of executive authorities of the Kaliningrad region. Leader management on the basis of the reformative concept of leadership is analysed. Interactions of heads with employees it was considered on four channels of influence: the individualised attention; the inspiring motivation; intellectual stimulation; charismatic influence. During the conducted research all respondents emphasise the importance of the factors stated above though also some features of perception of leadership skills of heads depending on age of workers, gender accessory are recorded. DOI: 10.5901/mjss.2015. v6n6s7p190
Transient simulation of gaseous particle/droplet laden flows in industrial-scale devices for flue gas cleaning including two-way mass and enthalpy coupling

The method of computational fluid dynamics (CFD) is applied to spraying processes with strong enthalpy coupling. Focus is brought to industrial scale applications in the field of environmental engineering. A transient 3D finite volume solver is used, wherein the disperse phase is modeled within an Lagrangian framework. Two-way mass and enthalpy coupling is taken into account. Resulting limitations of the traditional sequential model droplet integration approach are discussed, which potentially lead to thermodynamically inconsistant or oscillatory solutions, especially in zones of dense spray. As an alternative a combined sequential-simultaneous solution algorithm is proposed. Thus obtained results show sufficient aggreement with a validated test case. Application to industrial scale reactors in the field of flue gas cleaning are demonstrated exemplarily. INTRODUCTION The application of Computational Fluid Dynamics (CFD) as a means to support reactor design activities as well as subsequent optimization tasks is getting increasingly popular in the field of plant engineering. Flue gas cleaning processes are an illustrative example out of the range of environmental technologies. Frequently water with or without other reactants is injected into the flue gas stream. The specific temperature levels depend on the technology applied. In case of the selective non catalytic reduction (SNCR) this occurs at temperatures from 800°C to 1000°C directly after the primary combustion chamber. The time span, that is needed to evaporate the NH3/liquid-mixture, determines the penetration depth of the spray and consequently – among other parameters – the spatial distribution of the reactant. Similar effects have to be considered in the selective catalytic reduction process (SCR), where ammonia is injected into the exhaust gas at temperatures from 300°C to 400°C. Semi-dry desulphurization plants with Ca(OH)2 as quasi-dry reactant are typically operated at temperatures around 150°C and elevated vapor saturation levels. Water is applied to quench the entering gas stream and additionally to activate the surface of the solid sorption medium.
Detection of cell death activity during experimentally induced bleaching of the symbiotic sea anemone Aiptasia sp.

In this study, methods of identifying and detecting different cell death pathway activity were investigated. Using a suite of techniques consisting of haematoxylin and eosin staining of tissue sections, in situ end-labelling (ISEL) of fragmented DNA, electron microscopy and confocal laser microscopy, different forms of cell death activity were indicated during the bleaching of the symbiotic sea anemone Aiptasia sp. in response to a hyperthermic stress. A hyperthermic stress of 33-34C was used to ensure bleaching, promote cell death and validate the suite of techniques that can then be applied in ongoing studies into bleaching mechanisms. It is the entire combination of these techniques that avoids ambiguity in cell death pathway detection. Cell necrosis was detected in the host endodermis tissues after 4 days of hyperthermic treatment. The in-situ degradation of zooxanthellae characterised by both cell necrosis and programmed cell death in separate cells within the same tissues was detected after 7 days. 1 Department of Marine Sciences and Coastal Management, University of Newcastle upon Tyne, NE1 7RU, UK E-mail: s.r. dunn@ncl.ac. uk
Rapid Multidimensional NMR: High Resolution by Spectral Aliasing

Spectral aliasing consists in setting the spectral window of multidimensional NMR experiments below the full range of chemical shifts in order to increase the spectral resolution. The improvement factor can reach two orders of magnitude when applied to small molecules. The ambiguities in the observed chemical shifts can be resolved using diverse sources of complementary information discussed in the article. The advantages of spectral aliasing are very easy implementation with almost any standard pulse sequence, and reliance on the classical linear sampling of data points processed using the Fourier transform. Applications to small molecules and proteins are discussed.
Three-Dimensional Motion Analysis: Relevant Concepts in Physiotherapy Movement Dysfunction Management

The explorations of typical and dysfunctional movements are recognized physiotherapy assessment and management strategies. With the development of state-of-the-art three-dimensional (3-D) motion capture systems, traditional two-dimensional and observational movement quantification are being used less frequently in research initiatives. This technology is slowly infiltrating physiotherapy practice as systems become more accessible. Knowledge of 3-D acquisition methodology will provide insight into advancing movement dysfunction theories in physiotherapy. The objective of this commentary is to introduce the clinician to 3-D motion capture while providing a basic theoretical framework for understanding this methodology. The current use of 3-D systems and the limitations of this study methodology are reviewed. Familiarization with the use of this technology and understanding the methods in capturing 3-D motion will provide the physiotherapist with the latest knowledge in movement dysfunction. These concepts are an exceptional addition to the clinical reasoning strategies currently employed in the profession of physiotherapy.
First Experimental observations from the LHC Dynamic Aperture Experiment.

Following intensive numerical simulations to compute the dynamic aperture for the LHC in the design phase, the successful beam commissioning and the ensuing beam operations opened the possibility of performing beam measurements of the dynamic aperture. In this paper the experimental set-up and the first observations based on the few experimentalsessions performed will be presented and discussed in details. DYNAMIC APERTURE MEASUREMENTS The basis of theproposedtest to probethedynamicaperture (DA) is the inverse logarithm scaling law for dynamic aperture [1, 2]. This scaling law, derived from tracking data, hasbeenused recentlyto derivea possiblerelationbetween the intensity evolution and dynamic aperture [3]. So far, no particular lifetime issues were observed at injection, thus indicating that the dynamicapertureshould be comparable to the mechanical one. This suggests that a more effective strategy for measuring the DA consists of reducing it artificially by acting on some of the non-linear circuits present in the ring. In any case, the injected beam needs to be blown-up in order to have enough particles probing high amplitudes and hence experiencing non-lineareffects. This is certainly not the only technique to measure the dynamic aperture and in future also other approaches will be attempted, such as using the aperture kicker to bring the whole bunch to high amplitude. In light of these considerations, the strategy was as follows(consideringthatonlyBeam1wasusedforthesemea
Combined Riccati-Genetic Algorithms Proposed for Non-Convex Optimization Problem Resolution – A Robust Control Model for PMSM

In this paper, is proposed a state feedback optimal control algorithm for uncertain linear systems, with norm bounded uncertainties. It is based on the use of Algebraic Riccati Equation Genetic Algorithm (ARE-GA) developed for non-convex optimization problem resolution. The case of an uncertain Permanent Magnet Synchronous Motor (PMSM) based on the use of an Extended Kalman Filter (EKF) to estimate both position and speed, without any mechanical sensor is considered to illustrate the efficiency of the proposed technique.
The half-twist for U_q(g) representations

We introduce the notion of a half-ribbon Hopf algebra, which is a ribbon Hopf algebra along with a distinguished element $t$ corresponding to twisting a ribbon by 180 degrees (the half-twist). We show that U_q(g) is a (topological) half-ribbon Hopf algebra, but only if one uses a modified ribbon element. We then discuss some consequences of using this modified ribbon element.
The Econometric Analysis of MS Models

This paper studies how to compare different microscopic simulation (MS) models and how to compare a MS model with the real world. The parameters of interest are classified and characterized, and various econometric methods are applied to make the comparison. We illustrate the methodology by comparing various specifications of the MS model developed by Levy, Levy, and Solomon (2000) and by comparing this MS model with the real world.
Parallel patch-based volumetric reconstruction from images.

Three Dimensional (3D) reconstruction relates to the creating of 3D computer models from sets of Two Dimensional (2D) images. 3D reconstruction algorithms tend to have long execution times, meaning they are ill suited to real time 3D reconstruction tasks. This is a signi cant limitation which this dissertation attempts to address. Modern Graphics Processing Units (GPUs) have become fully programmable and have spawned the eld known as General Purpose GPU (GPGPU) processing. Using this technology it is possible to ofoad certain types of tasks from the Central Processing Unit (CPU) to the GPU. GPGPU processing is designed for problems that have data parallelism. This means that a particular task can be split into many smaller tasks that can run in parallel, the results of which and are not dependent upon the order in which the tasks are completed. Therefore to properly make use of both CPU parallelism and GPGPU processing a 3D reconstruction algorithm with data parallelism was required. The selected algorithm was the Patch-Based Multi-View Stereopsis (PMVS) method, proposed and implemented by Yasutaka Furukawa and Jean Ponce. This algorithm uses small oriented rectangular patches to model a surface and is broken into four major steps: Feature detection; feature matching, expansion and ltering. The reconstructed patches are independent and as such the algorithm is data parallel. Some segments of the PMVS algorithm were programmed for GPGPU and others for CPU parallelism. Results show that the feature detection stage runs 10 times faster on the GPU than the equivalent CPU implementation. The patch creation and expansion stages also bene ted from GPU implementation. Which brought an improvement in the execution time of two times for large images, and equivalent execution times for small images, when compared to the CPU implementation. These results show that the use of GPGPU and CPU parallelism can indeed improve the performance of this 3D reconstruction algorithm.
Tropospheric ozone column retrieval from the Ozone Monitoring Instrument by means of a neural network algorithm

Ozone concentration levels in the troposphere have several impacts on both climate and air quality. Monitoring tropospheric ozone concentrations and trends, especially in highly polluted locations, is a relevant topic in recent geosciences research. To observe height-resolved ozone concentrations from satellite platform is an exciting task, owing to the global and continuous nature of the obtained information. The Ozone Monitoring Instrument represents a good chance to contribute at the understanding of ozone related phenomena, also within the troposphere, owing to the relatively small pixel size; it is also a useful means for an effective monitoring of such phenomena, owing to its daily global coverage. Different techniques have been recently proposed to monitor tropospheric ozone content from satellite using the OMI. Mainly two techniques exist within this field: the Tropospheric Ozone Residual (TOR) methodology and the Optimal Estimation (OE). Neural networks (NN) algorithms have demonstrated encouraging capabilities as an alternative tool to retrieve height-resolved ozone concentrations from satellite data. Recently, NN algorithms for both ozone concentration profiles retrieval and tropospheric ozone columns (TOC) retrievals from SCIAMACHY and GOME have been presented. NNs have some advantages over the TOR and the OE techniques. When used for the mentioned applications, NNs are intended to learn the inverse relationship between the satellite reflectance spectra and the TOC from a set of sample data, and a direct model is not necessary. Theyre also expected to be less sensitive to systematic errors on the input spectra with respect to OE. Once trained, a NN is able to operate in real time. Here we present a NN algorithm to retrieve TOCs from OMI Level 1b data, which we called the OMI-TOC NN. First results and a validation exercise will be also discussed. Our NN retrievals are also compared to co-located TOC retrievals obtained with the OE.
The Impact of Products and Processes Innovation on Business Performance of Manufacturing SMEs in Mexico

The market globalization, the high level of competitiveness and business uncertainty in; all characterize the current 21 st century, in which enterprises, primarily Small and Medium-Sized Enterprises (SMEs), seek to adapt its business strategies not only to increase its markets share but also to survive in an environment of economic turbulence. For this reason, today innovation is emerging as a business strategy that allows organizations to differentiate its products from its main competitors, as well as significantly improve its level of business performance. Thus, the results obtained in this research demonstrate that both innovation in products and innovation in processes have a significant positive impact on the business performance of SMEs in the State of Aguascalientes.
Investment in technology based small and medium sized firms in Malaysia: roles for commercial banks

Financing is an important input in every business which allows for the smooth running of day-to-day operations, asset acquisitions, expert recruitment, and development of marketing and distribution channels. This is especially the case for high-tech startups that must undergo four development stages to turn ideas into commercial products and become full-blown enterprises; concept formation, amassing of resources, product development and business development. The purpose of this research is to understand the fundamental role of banks in Malaysia in bridging the startups financing gap, thereby, helping to grow technology based small and medium sized enterprises in the country. A qualitative research approach which aims first to identify all the commercial and investment banks in the country, then with a select sample size of ten biggest banks shall administer a semi-structured/open ended questionnaire. This methodology will allow respondents to open up on critical issues to be discussed and not limiting them to certain choices as in the case with a structured form of interview. Banks in Malaysia are not willing to finance high technology small and medium enterprises since it is a high risk industry. A the findings are compared to what is obtainable in other countries and Europe and America.
Automatic Cashier System Based on Meal Plate Detection Using Deep Learning

This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). Automatic Cashier System Based on Meal Plate Detection Using Deep Learning Weibin Zheng , Shengliang Peng , Qilong Chen , Hao Ouyang , Shiheng Lin e Institute of Communications Technology, Huaqiao University, Xiamen 361021, China wb_zheng@outlook.com, peng.shengliang@gmail.com, 936964961@qq.com, oyang9595@outlook.com, hp677@qq.com
Analysis of cancer cell invasion with novel in vitro methods based on human tissues

Cancer progression is a multistep process dependent on tumour-stroma interactions. Various cell types, such as fibroblasts, endothelial, inflammatory and stem cells, as well as extracellular matrix (ECM) proteins, such as collagens, contribute to the tumour outcome. Tumour growth and invasion is accompanied by the proteolysis of ECM components mediated by various enzymes, such as matrix metalloproteases (MMPs). Proteolytic fragments released into the circulation may reflect cancer progression. The aim of this study was to develop novel in vitro methods for investigating cell invasion and for measuring cancer-associated collagen degradation. Human carcinoma cell invasion studies in vitro are often performed in organotypic cell culture models, mainly composed of rat or mouse ECM proteins. To create a human microenvironment for invasion studies, a novel organotypic model based on human uterine myoma (benign tumour) tissue was developed. Compared to the conventional collagen-based organotypic model, in the myoma model the carcinoma cell invasion depth was about eightfold and the invasion resembled, to a greater degree, the invasion pattern of dissected tissue samples of cancer patients. In addition, the invasion was easily quantified with a novel radioimmunoassay measuring type III collagen degradation products from the organotypic culture media. As human mesenchymal stem cells (MSCs) are one of the stromal cell types that may affect tumour progression, the mechanisms of stem cell invasion were also studied. On the surface of MSCs, Toll-like receptor 9 (TLR9) functions in immune defence against microbes. The activation of TLR9 with microbial DNA-resembling molecules induced human MSC invasion into the myoma tissue in a MMP-13-mediated fashion. To analyse cancer-associated soft tissue degradation, a novel enzyme immunoassay was developed. This novel assay enabled, for the first time, the measurement of type III collagen degradation products from human serum samples. In head and neck cancer patient sera, high levels of type III and type I collagen degradation products were shown to predict poor survival. In conclusion, the novel myoma model showed that the tumour microenvironment crucially affects carcinoma cell invasion. In addition, cancer-associated type III collagen degradation was successfully measured in cell cultures and in human sera by novel immunoassays.
BESTUURDERS IN ’NOPENBAREMAATSKAPPYSE COPINGMET TRANSFORMASIE

Managers play an important role in assisting organisations to manage transformation e¡ectively. The aim of this research was to determine the strategies that managers use to cope with transformation and to determine the di¡erences between the coping strategies of participants measuring high and low on psychological strengths.The Orientation to LifeQuestionnaire, Locus of ControlQuestionnaire, PersonalViews Surveyand Self-Control Scalewere administered on 46 managers. An interview based on the phenomenological paradigmwas used to determine the coping strategies of managers in contrast groups (n = 8). The results of the study showed that managers measuring high on psychological strengths used more e¡ective coping strategies than those lowon these strengths.
Rare earth cerium doping effects in nonlinear optical materials: potassium hydrogen phthalate (KHP) and tris(thiourea)zinc(II) sulfate (ZTS)

The influence of Ce(IV) doping on ZTS and KHP crystals over a concentration range from 1 to 10 mol% in the solution during crystallization, which leads to a true concentration range from few ppm to few tens of ppm in the crystals has been investigated. The XRD and FT-IR analyses indicate that the crystal undergoes considerable stress as a result of doping. Incorporation of the Ce(IV) dopant into the crystal lattice was well confirmed by energy dispersive X-ray spectroscopy (EDS) and quantified by inductively coupled plasma (ICP) technique. The high-resolution X-ray diffraction (HRXRD) studies reveal that Ce doping in KHP leads to degradation of crystal quality whereas ZTS can accommodate Ce predominantly at the substitutional sites without any degradation of crystalline perfection. The second harmonic generation (SHG) efficiency is not influenced by Ce doping in the KHP crystals while in ZTS crystals, it is enhanced to a considerable extent correlated with moderately improved crystalline perfection.
Maternal health problems such as depression and anxiety and parent-child interaction

Background: The emotional climate between mothers and their children is known to be a significant indicator for the development of childhood psychopathology. One index that allows measuring family-emotional climate is the expressed emotion measure (EE). Maternal mental strain is known to affect maternal EE, as it can shape the way a mother thinks about, and interacts with her child.