Miracle-dz/UniFAR-FTUs huggingface dataset:
Neutrophil-Lymphocyte Ratio , as a Novel Systematic Biomarker : Predicting IntraceRebral Hemorrhage in Type 2 Diabetes Mellitus

Introduction: Chronic systematic inflammation has been suggested to be associated with the occurrence and development of cardiovascular events. Low-grade systematic inflammation persists in Type 2 Diabetes Mellitus(T2DM) patients. In addition, the risk of cerebral hemorrhage in these patients is increased compared with non-diabetic patients. Neutrophil-to-Lymphocyte Ratio (NLR) is the ratio derived by dividing the neutrophil count with the lymphocyte count from a peripheral blood sample. This study aimed to explore the relation between NLR and cerebral hemorrhage and to prove that the NLR is an independent risk factor of cerebral hemorrhage in T2DM patients. Method: In total, 429 cases of T2DM patients were included. The patients were divided into two groups depending on the presence of cerebral hemorrhage: the cerebral hemorrhage group (n=87) and the control group (n=342). Based upon clinical and laboratory data of diabetes diagnosis, this article investigates the relationship between the NLR and risk of cerebral hemorrhage. Results: The increase in the NLR was positively correlated with the incidence of cerebral hemorrhage in T2DM patients and might serve as an independent risk factor of cerebral hemorrhage in T2DM patients (OR 4.451 95% CI 2.582-7.672). NLR>2.58 might be useful in predicting the threshold value of cerebral hemorrhage risk in newly diagnosed T2DM patients (area under the curve 0.72, 95% CI 0.659-0.780, P<0.001) Conclusion: As an indicator of the degree of systematic inflammation, NLR is an independent risk factor of cerebral hemorrhage in T2DM patients. An eBook on Type 2 Diabetes 2 w w w.openssebooks. com Pe ng L
INCORPORATING UNCERTAINTY INTO TACTICAL CAPACITY PLANNING : A ROBUST OPTIMIZATION MODEL FOR AN ENGINEERING-TO-ORDER INDUSTRIAL SETTING

Production planning literature is rich of approaches and models proposed to cope with different forms of uncertainty. In traditional optimization models, specific probability distributions for random variables are assumed known. In many real-world situations, however, decision-makers do not have precise information about future demand. This is particularly critical in engineering-to-order (ETO) production systems which are associated with high complexity and uncertain situations. Within this context, the objective of this paper is to present a robust optimization reformulation of a tactical capacity planning model to incorporate information relative to process uncertainty. This study refers to an action research that was realized in a real-world ETO industrial setting. The model aims at solution robustness (or stability) and intends to enhance and support the decision-making process of the studied setting.
Architectures of Multiple-Radix Maximum-A-Posteriori and Turbo Decoders for Low-Power Wireless Communication Applications

Turbo codes perform excellently with regard to error correction in physical layer of wireless communication networks. Near Shannon limit bit-error-rate performance of turbo decoders is the key factor that makes it an important aspect of channel decoding. With the surge of expanding wireless communication and very large scale integration (VLSI) industries around the world , it is essential to design a VLSI architecture of flexible data rate channel decoder for targeting the physical layer of next generation 5G standards. With the Moore’s law approaching towards the steady state, it is high-time for the researchers to work on new architectures to enhance the performance for any application, rather relying on CMOS technology scaling. Hence, this motivates us to carry out this work on VLSI architectures for channel decoders. We propose flexible-architecture for soft-input soft-output (SISO) decoder with radix-2/4/8 modes to support multiple data-rates. This work presents designs of major internal blocks of SISO decoder using extensive steering logic to support multiple radix operating-modes. These architectures enable efficient clock-gating of our decoder for low-power consumption in different operating modes. Subsequently, we have aggregated eight SISO decoders with quadratic-permutation polynomial (QPP) interleavers/deinterleavers to design parallel turbo decoder architecture which can operate in multi-radix mode. Suggested SISO decoder is application-specific integrated-circuit (ASIC) synthesized and post layout simulated in UMC 65 nm-CMOS process. Performance analyses in additive-white Gaussian-noise (AWGN) channel environment showed that the bit error rate (BER) of 10-4 could be achieved at 5 dB and 0.8 dB for SISO and turbo decoders respectively. Implementation result shows that the suggested SISO decoder could achieve throughput in the range 270-810 Mbps with the corresponding power consumption range of 12.24-37.67 mW. In comparison to the state-of-the-art, our design achieved 38% higher throughput and 61% lower power consumption. Similarly, our multi-radix parallel-turbo decoder is hardware prototyped in 28 nm-CMOS Zynq-FPGA board. It delivers a range of data-rates from 160 to 515 Mbps operating at 160 MHz of clock frequency for 8 iterations.
Characterization of harvesting systems and development of yield maps for citrus

Citriculture is important for the Brazilian economy due to its expressive participation on exporting and for the generation of a number of job positions. Routine generation of yield mapping for citrus is necessary for implementing precision agriculture practices. The objective of this research was to promote the correct understanding of harvesting systems, their useful characteristics and limitations, also propose and test a methodology for collecting data to attain yield maps without interfering in the process. A method was evaluated and the results were considered acceptable; the method is considered simple and efficient for data collection and yield maps generation.
COPD and comorbidity

This thesis focuses on the prevalence and impact of simultaneously existing disorders or comorbid conditions in COPD patients. Common comorbid conditions in COPD patients were detected systematically. Electrocardiography showed a high prevalence of heart damage, which is associated with poorer outcome. Other comorbid conditions such as high blood sugar levels, obesity, high blood pressure, osteoporosis, anxiety and depression were found to be common as well. Comorbidity is present in almost all COPD patients and at least four simultaneously occurring comorbid conditions are present in over 50% of the patients. Patterns could be recognised and patients could be divided into five groups based on these comorbid conditions. In conclusion, it was shown that neither separate comorbid conditions nor comorbidity clusters prevent pulmonary rehabilitation from being effective in COPD patients.
Comparative Study of Wavelet Packet Algorithm for Image Denoising with Edge Detection

An image is a two dimensional function represented as F(x,y),it can be defined as an artifact that depicts or records visual perception for example two dimensional picture that has a similar appearance to some objects. All digital images contain some degree of noise. Often we suffered with noise in image that is occurred due to the sensor and circuitry of a scanner or digital camera during image acquisition and/ or transmission. In this Paper, noise removal technique is presented through the Wavelet packet algorithm along with the edge detection. Wavelet packet provides more accurate method of signal analysis. Since wavelet packet is able to divide the band into multilayer classification to further decomposition in both high & low frequency also, thus it provide more extensive application value than wavelet analysis. At the same time to preserve the features of an image such as edge information we will apply edge detection on the image. By comparing the different wavelet packets, we will find the best among them based on parameters such as PSNR (Peak signal to Noise Ratio) value, MSE (Mean Square Error) and SSI (Structural Similarity Index).
Return Decomposition ∗

In the return decomposition approach, unexpected equity return is decomposed into discount rate (DR) news and cash flow (CF) news, with the DR news directly modeled but the CF news calculated as the residual. This approach has a serious limitation because the DR news, given very limited predictive power, cannot be measured accurately enough to draw inferences on the relative importance of DR news and CF news in determining the time-series and cross-sectional variation of returns. To illustrate this point, we apply the approach to Treasury bonds that should have zero CF variance and zero CF betas. In contrast, we find that the variance of the “CF news” is larger than that of the DR news; and that bonds with longer maturities have higher “CF betas. ” Applying the approach to equity returns, we show that (i) the relative importance of CF variance and DR variance of the market portfolio is sensitive to the choice of forecasting variables; and (ii) for most forecasting-variable specifications, value stocks usually do not have higher CF betas. These results run counter to current evidence using the decomposition approach. We further decompose the CF news in the current literature into directly-modeled CF news and residual news; we show that opposite conclusions can be drawn depending on the nature of the residual news. We further reconcile our finding that value stocks in general do not have higher CF betas with the finding in a related litearture that value stocks have higher CF covariation with aggregate CFs. We finally provide a test suggesting that the lower CAPM betas of value stocks are unlikely to be DR-related. JEL Classification: G11, G12
Towards Deep Universal Dependencies

Many linguistic theories and annotation frameworks contain a deep-syntactic and/or semantic layer. While many of these frameworks have been applied to more than one language, none of them is anywhere near the number of languages that are covered in Universal Dependencies (UD). In this paper, we present a prototype of Deep Universal Dependencies, a two-speed concept where minimal deep annotation can be derived automatically from surface UD trees, while richer annotation can be added for datasets where appropriate resources are available. We release the Deep UD data in Lindat.
Model Description Genetic Parts Ontology ( RBMC ) RDFS + RBMC Rules Merge Forward Inference Dictionary Transform Templates Substitution Derivation of Declarations Host & Observables Merge Simulation Executable RDF

A central strategy of synthetic biology is to understand the basic processes of living creatures through engineering organisms using the same building blocks. Biological machines described in terms of parts can be studied by computer simulation in any of several languages or robotically assembled in vitro. In this paper we present a language, the Genetic Circuit Description Language (GCDL) and a compiler, the Genetic Circuit Compiler (GCC). This language describes genetic circuits at a level of granularity appropriate both for automated assembly in the laboratory and deriving simulation code. The GCDL follows Semantic Web practice and the compiler makes novel use of the logical inference facilities that are therefore available. We present the GCDL and compiler structure as a study of a tool for generating κ-language simulations from semantic descriptions of genetic circuits.
Optimal Scheduling of Proactive Care with Patient Deterioration

Healthcare is a limited resource environment where scarce capacity is often reserved for the most severe patients. However, there has been a growing interest in the use of preventive care to provide treatment to patients early on, before they deteriorate. On one hand, providing care for patients when they are less critical could mean that fewer resources are needed to return them to a healthy, stable state. On the other hand, utilizing limited capacity for patients who may never need care in the future takes the capacity away from other more critical patients who need it now. To understand this tension, we propose a multi-server queueing model with two patient classes: moderate and urgent. A moderate patient who does not receive treatment may recover and leave or may deteriorate and become an urgent patient. In this setting, we characterize how moderate and urgent patients should be prioritized for care when proactive care for moderate patients is an option. We identify a parameter, the modified cμ/θ-index, which plays an important role in determining the optimal scheduling policy. This index lends itself to an intuitive interpretation of how to balance holding costs, service time, abandonment, and degradation of patient class.
Antimicrobial Activity Screening of Marine Bacteria Isolated from the Machilipatnam Sea Coast of Andhra Pradesh, India -

Article history: Received on: 28/02/2016 Revised on: 09/04/2016 Accepted on: 22/04/2016 Available online: 21/06/2016 Bacterial colonies were obtained from water samples collected from sea-coast of Machilipatnam, Andhra Pradesh in South India. The isolates were cultured, named as M1, M2, M3 etc., and screened for antibacterial action. Among the 40 representative isolates obtained, three isolates showed substantial antibacterial activity with more than 10 mm of zone of inhibition against two test bacteria used in preliminary screening. These three isolates marked as M20, M22 and M23 showed most outstanding results against all the test bacteria used in further testing of antibacterial activity. The isolate M20 showed the highest activity with a zone of inhibition of 16mm against Serratia marcescens, 14 mm against E.coli and Shigella, and with 12 mm against Salmonella paratyphi and Bacillus cereus. The isolates M20, M22 and M23 were analyzed for their morphological, biochemical and physiological characteristics and tentatively identified as Alcaligenes sp. (M20), Bacillus sp. (M22) and Bacillus sp. (M23) from the performed biochemical tests.
Preparation of Amphiphilic Chitosan–Graphene Oxide–Cellulose Nanocrystalline Composite Hydrogels and Their Biocompatibility and Antibacterial Properties

Environmental-friendly nanocomposite hydrogels of carboxymethyl-hexanoyl chitosan (CHC), graphene oxide (GO) and cellulose nanocrystals (CNCs) were combined to produce a bio-hydrogel with great biocompatibility and antibacterial ability. The size of the GO nanosheets was about 200–500 nm, and the CNCs had a length of 100–200 nm and a width of 10–20 nm, as shown by transmission electron microscopy (TEM). X-ray photoelectron spectroscopy (XPS) was utilized for the analysis of the oxygen functional groups of GO. The homogeneous dispersion of the CHC/GO/CNC nanocomposite hydrogel showed significantly higher water absorption capacity and water retention capability. In addition, inhibition of a variety of microorganisms (gram-negative and gram-positive bacteria and fungi) by the introduction of the CHC/GO/CNC nanocomposite hydrogel demonstrated that there is a great opportunity to use it in the bio-medical field, such as for plastic masks and wound dressings.
Diest Could biodynamics help bridge the gap in developing farmer intuition ?

Several scientific studies indicate that farmers do not often use formalised decision support tools as expected, and many prefer to rely on their intuition to make practical management decisions. While agricultural science and education acknowledge the different types of knowledge that farmers utilize, intuition continues to receive little attention in agricultural science, indicating a gap in farmer decision-making research. The mechanism driving intuition remains under debate, but is described as a pervasive, involuntary, rapid way of knowing, offering access to tacit (internal, intangible) knowledge that complements analytic processes. Many studies agree that intuition can be trained to increase accuracy and reliability. However, the comprehensive works on intuition by Rudolf Steiner hardly feature in modern science, and yet his writings and biodynamic agriculture approach offer farmers and non-farmers guidelines for systematic development of subtle abilities like intuition. There may be value in collaborative, transdisciplinary exploration between agricultural research and biodynamic theory and practice, for supporting farmers to develop their intuitive knowing. Such an alliance could help increase the awareness and practice of biodynamics, expand the knowledge base and lexicon for the em erging research field of intuitive farming, and help reinvigorate agricultural research toward more efficient, customized and connected farming practices.
A peer-to-peer trust modeling analysis for decreasing B 2 B monitoring costs

In businesses, uncertainties and risks occur all the time. Uncertainties may come from customer’s demand, consumer purchase. Risks can come from competitor company, transport products. These can cause costs of switching and transaction. Trust can decrease transaction and switching costs. Moreover trust can increase profits too. Most business concern these trust management cause exchangeable information between internet and communication network. Grid technology is a service for sharing that information and solving problems in commercial enterprise. Grid environment is a distributed computing to perform very large tasks by using access control including policies, certificates, and private keys. In businesses, there is a need to share resources such as file sharing, document sharing, and so on. Peer-to-peer system is an appropriate architecture for these sharing in trust management affecting the performance of profit. This paper is to study appropriate models and technologies to decrease costs for Business to Business (B2B). Moreover they assure security techniques such as cryptographic for privacy retrievable information. They can share information for reducing uncertainties demand and increase duration when the quantities of orders are high. Because they can be occurred all time. The experiment of comparative studies with grid, peer-to-peer and social networks are methodologies for decrease costs. Keywords-B2B; trust; total costs; grid technology; peer-topeer; social network
ON THE PHYSICAL MODELLING OF TUNNELS IN SOFT GROUND

This paper summarizes some of the available experimental techniques used to investigate ground response to tunnelling in soft ground. Emphasis is placed on the recent developments of 1G and centrifuge models. A comparison between different tunnelling simulation methods is presented. The recently developed gravity scale model of tunnels excavated in soft ground at McGill University is also described. RÉSUMÉ L’article suivant décris les différentes approches utilisées dans le développement de modèles réduits de tunnels en terre souple. Une considération particulière sera faite pour les modèles réduits 1G et centrifuge. Une comparison des différentes méthodes de simulation de tunnels sera faite. L’article proposera aussi une nouvelle méthode pour la construction de tunnels réduits en terre souple développée a l’université McGill.
Environmental Mapping by Trinocular Vision for Self-Localization Using Monocular Vision

This paper presents a SIFT based map building and self localization method for mobile robots. 3-D positions of landmarks are useful for the robot to localize the self position, 3D input system occupies larger space and computational cost is too high to implement on the embedded system. Although motion stereo techniques using only a monocular vision system have been developed, the accuracy of the depth measurement is not enough to build navigation maps. We proposed the following scheme: First a mapping robot with trinocular camera builds the 3-D keypoint map of unknown environment with a high accuracy and then the working robot with a monocular camera localize the own position by matching the SIFT keypoints to the map. Experimental results of mapping and localization for a real indoor scene are shown.
The effect of combination of counterflow jet and spike on drag reduction for a blunt body at high Mach number flow

The present study is a numerical analysis of flow field around two spiked hemispherical nose cylinder model in a free stream Mach number of 6 with and without a counterflow jet at the nose of their spikes. The gas is injected through the nozzle at the nose of the spikes at sonic speed in opposite direction of the free stream flow. The difference between two models is the lengths of the spikes. In this numerical analysis, axisymmetric Reynoldsaveraged Navier-Stokes equations are solved by the standard k-ε turbulence model. The results for the without jet conditions are validated with an experimental study. The purpose of this paper is to study the effect of combination of counterflow jet and spike on drag coefficient over spikedblunt bodies. The results for with jet condition show a significant reduction of the total drag coefficient.
Jan 2019 Coded Caching based on Combinatorial Designs

We consider the standard broadcast setup with a single server broadcasting information to a number of clients, each of which contains local storage (called cache) of some size, which can store some parts of the available files at the server. The centralized coded caching framework, introduced in [1], consists of a caching phase and a delivery phase, both of which are carefully designed in order to use the cache and the channel together optimally. Starting from [1], various combinatorial structures have been used to construct coded caching schemes. In this work, we propose a binary matrix model to construct the coded caching scheme. The ones in such a caching matrix indicate uncached subfiles at the users. Identity submatrices of the caching matrix represent transmissions in the delivery phase. Using this model, we then propose several novel constructions for coded caching based on the various types of combinatorial designs. While most of the schemes constructed in this work (based on existing designs) have a high cache requirement (uncached fraction being Θ( 1 √ K ) or Θ( 1 K ), K being the number of users), they provide a rate that is either constant or decreasing (O( 1 K )) with increasing K, and moreover require competitively small levels of subpacketization (being O(K), 1 ≤ i ≤ 3), which is an extremely important parameter in practical applications of coded caching. We mark this work as another attempt to exploit the well-developed theory of combinatorial designs for the problem of constructing caching schemes, utilizing the binary caching model we develop.
The Role of Emotional Intelligence Training in Moderating Conflict Resolution in Virtual Teams Emergent Research Forum ( ERF ) Ayman Alfahid

Emotional Intelligence is an important ability of a person to understand and control his/her own emotions, coupling with the ability to understand and manage others’ emotions. In operating in the virtual team environment where contextual cues are limited, emotional intelligence is crucial in helping virtual team members in dealing with conflicts. Despite the importance of Emotional Intelligence in conflict resolution in the virtual team environment, there is a gap in the literature, especially when Emotional Intelligence training is needed to remedy team members who are lacking in emotionality control. In this emergency research forum paper, we propose a research to explore to examine the extent to which EI and EI training plays in conflict resolution in a virtual team environment.