Miracle-dz/UniFAR-FTUs huggingface dataset:
Enzyme immunoassay for detecting Brucella antibodies in cow's milk

An enzyme immunoassay (EIA) was developed for detecting Brucella antibodies in milk of cows infected with Brucella abortus. The enzyme immunoassay using heat-killed cells of B. abortus strain 19 was of comparable sensitivity to the Brucella ring test in detecting antibodies in milk of a reference positive control cow experimentally infected with B. abortus strain 2308 and in milk of 16 naturally infected cows from which B. abortus was isolated. No detectable enzyme immunoassay reactions were present in milk of 11 noninfected controls. The enzyme immunoassay is a procedure which can be readily automated so that screening tests for brucellosis could be conducted at a reference laboratory where uniform conditions can be maintained.
Between Consumer Demand and Islamic Law: The Evolution of Islamic Credit Cards in Turkey

The elimination of interest from financial transactions has been a salient goal of Islamization movements around the world. Its proponents have had to balance this objective, which they claim to draw from Islamic law (Sharia), against consumer demand for convenient products. In general they have opted to accommodate consumer demand, but surreptitiously, using legal ruses to disguise their compromises. Turkey's experience with credit cards offers a revealing case of the obfuscation in question. Having denounced credit cards as un-Islamic, Turkey's Islamic banks have all proceeded to issue credit cards of their own in order to remain competitive with their openly interest-friendly, conventional rivals. With local variations, the Turkish pattern resembles that of other markets where Islamic credit cards have made inroads. In Malaysia and the United Arab Emirates, too, Islamic credit cards function like those of the conventional banks with which they compete for customers. The “Islamic” features of Islamic credit cards amount to branding. Contrary to the claims of their proponents, they do not involve fundamental financial innovations.
A new neural network for solving linear and quadratic programming problems

A new neural network for solving linear and quadratic programming problems is presented and is shown to be globally convergent. The new neural network improves existing neural networks for solving these problems: it avoids the parameter turning problem, it is capable of achieving the exact solutions, and it uses only simple hardware in which no analog multipliers for variables are required. Furthermore, the network solves both the primal problems and their dual problems simultaneously.
A map based estimator for inverse complex covariance matricies

A novel approach to estimate (inverse) complex covariance matrices is proposed. By considering the class of unitary invariant estimators, the main challenge lies in estimating the underlying eigenvalues from sampled versions. By exploiting that the distribution of the sample eigenvalues can be derived in closed form, a Maximum A Posteriori (MAP) based scheme is then derived. The performance of the derived estimator is simulated and results indicate that the proposed scheme shows performance similar to one of the best estimators known to date. The main advantage lies in that the proposed solution only requires numerical optimization over a P-dimensional space where P is the size of the covariance matrix.
Compact Modeling of Quasi-Ballistic Silicon Nanowire MOSFETs

A compact model for the quasi-ballistic silicon nanowire MOSFET was developed by supplementing the ballistic framework previously disclosed by us with an original carrier-scattering model. The scattering model considers elastic scattering and optical phonon emission, which is the dominant route of energy relaxation in the device. The quasi-ballistic electric current showed a remarkable decrease compared with the ballistic counterpart. The relative decrease or “ballisticity” gradually improved when the channel length was reduced, but the value remained considerably less than the ballistic limit, even in the limit of zero channel length. The transport physics underlying the device characteristics is discussed.
A generic delay tolerant routing strategy for information centric networking (ICN)

It is a paradigm shift in internet architecture from receiver centric model to the information centric networking (ICN) model to improve the end-users' latency experience. With exponential increment in number of users and data volume, efficient usage of the nodes (caches) and content forwarding methodology are key issues in an ICN architecture. In ICN intra-domain routers have storage capacity and they can act as temporary content provider, therefore it reduces average hop count and correspondingly average delay for content download. In this article, we formulate the content management issues in a cache having finite storage capability and propose an efficient content management policy that metamorphoses a node to a self-sustained cache. We address how content packets are stored in buffer of the cache before processing and how they suffer from several finite propagation delays during the processing in a cache. We simulate our proposition with deploying real-life network environment and calculate user experience metrics like average latency, throughput and good-put. From simulation results we observe that our proposed model outperforms the existing state-of-the-art on-path caching policies.
Determination of Evanescent Electric Field Decay Length of Metallic Nanodisks by Using Localized Surface Plasmon Spectroscopy

In this paper, the evanescent electric field decay length of metallic nanodisks array patterned by electron beam lithography has been determined. From localized surface plasmon resonance spectroscopy, this electric field decay length ld was obtained with the help of a simple model. It has been demonstrated that l(subscript d) increased with the aspect ratio (diameter/height). Rigourous theoretical calculations based on the finite difference time domain confirm our experimental results.
A Comparison of Classification Technique for Metacognitive Knowledge

Metcognitive learning has been developed to 1) enhance students to have awareness for conducting self study, 2) verify metacognitive knowledge and 3) provide proper lessons for each student. The test of metacognitive knowledge was implemented, and at least two out of three metacognitive knowledges; knowledge of self, knowledge of task, and knowledge of strategy, should be presented so that students’ metacognitive regulation can be proved. Therefore classification techniques were proposed to classify metacognitive knowledge of students via accuracy comparison of four classification techniques: Bayesian classifier, Decision Tree, Rule Based, and General Classification as 92.04%, 91.22%, 86.56%, and 92.87% respectively. Nonetheless, Bayesian Classifier is selected to be algorithm for metacognitive learning environment.
Tempering technostress

New technologies are so commonplace today that many organizations and businesses are faced with daunting problems of how to go about introducing these technologies. One problem lies in determining the impact of the new technology on the work processes and productivity of employees. Introducing a new technology to the workplace is a multidimensional problem that can be addressed through a number of specialized disciplines including change management, project management, and business process reengineering. A key step any organization needs to make in properly introducing a new technology to the workplace is to assess who will be impacted directly or indirectly by this change and how. This is a critical concern for organizations as they increasingly move to data rich, networked environments, since both the number of individuals affected and the pace of change will continue to increase dramatically. The article proposes a framework for introducing new technology and determining its impact on all the affected departments and staff.
Effect of carbon nanofibers content on thermal properties of ceramic nanocomposites

The thermal properties of carbon nanofibers (CNFs)-alumina and CNFs-zirconia nanocomposites densified by spark plasma sintering technique were evaluated. The influence of CNFs content and type of ceramic matrix on thermal conductivity of ceramic-CNFs materials, measured by the laser-flash method, was studied. The effect of CNFs depends noticeably on the ceramic component and thus, an increase of 83% and a decrease of 97% in thermal conductivity at room temperature is observed when 80 vol% of CNFs is added to ZrO2 and Al2O3, respectively. However, even if the thermal conductivity is lower, the efficiency of heat transfer to the environment in CNFs/Al2O3 nanocomposites is better than that corresponding to monolithic alumina. This behavior is due to CNFs arrangement in dense materials. Considering the low electrical resistivity for CNFs/ Al2O3 and CNFs/ ZrO2 materials (10−1–10−2 Ω·cm), these nanocomposites are promising candidates as thermoelectric materials that require low thermal conductivity, but high electrical conductivity.
Believing the axioms. I

§0. Introduction. Ask a beginning philosophy of mathematics student why we believe the theorems of mathematics and you are likely to hear, “because we have proofs! ” The more sophisticated might add that those proofs are based on true axioms, and that our rules of inference preserve truth. The next question, naturally, is why we believe the axioms, and here the response will usually be that they are “obvious”, or “self-evident”, that to deny them is “to contradict oneself” or “to commit a crime against the intellect”. Again, the more sophisticated might prefer to say that the axioms are “laws of logic” or “implicit definitions” or “conceptual truths” or some such thing. Unfortunately, heartwarming answers along these lines are no longer tenable (if they ever were). On the one hand, assumptions once thought to be self-evident have turned out to be debatable, like the law of the excluded middle, or outright false, like the idea that every property determines a set. Conversely, the axiomatization of set theory has led to the consideration of axiom candidates that no one finds obvious, not even their staunchest supporters. In such cases, we find the methodology has more in common with the natural scientist's hypotheses formation and testing than the caricature of the mathematician writing down a few obvious truths and preceeding to draw logical consequences. The central problem in the philosophy of natural science is when and why the sorts of facts scientists cite as evidence really are evidence. The same is true in the case of mathematics. Historically, philosophers have given considerable attention to the question of when and why various forms of logical inference are truth-preserving. The companion question of when and why the assumption of various axioms is justified has received less attention, perhaps because versions of the “self-evidence” view live on, and perhaps because of a complacent if-thenism.
In Vitro Utilization of Amylopectin and High-Amylose Maize (Amylomaize) Starch Granules by Human Colonic Bacteria

ABSTRACT It has been well established that a certain amount of ingested starch can escape digestion in the human small intestine and consequently enters the large intestine, where it may serve as a carbon source for bacterial fermentation. Thirty-eight types of human colonic bacteria were screened for their capacity to utilize soluble starch, gelatinized amylopectin maize starch, and high-amylose maize starch granules by measuring the clear zones on starch agar plates. The six cultures which produced clear zones on amylopectin maize starch- containing plates were selected for further studies for utilization of amylopectin maize starch and high-amylose maize starch granules A (amylose; Sigma) and B (Culture Pro 958N). Sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) was used to detect bacterial starch-degrading enzymes. It was demonstrated thatBifidobacterium spp. , Bacteroides spp. ,Fusobacterium spp. , and strains of Eubacterium,Clostridium, Streptococcus, andPropionibacterium could hydrolyze the gelatinized amylopectin maize starch, while only Bifidobacterium spp. and Clostridium butyricum could efficiently utilize high-amylose maize starch granules. In fact, C. butyricumand Bifidobacterium spp. had higher specific growth rates in the autoclaved medium containing high-amylose maize starch granules and hydrolyzed 80 and 40% of the amylose, respectively. Starch-degrading enzymes were cell bound on Bifidobacteriumand Bacteroides cells and were extracellular for C. butyricum. Active staining for starch-degrading enzymes on SDS-PAGE gels showed that the Bifidobacterium cells produced several starch-degrading enzymes with high relative molecular (Mr) weights (>160,000), medium-sized relative molecular weights (>66,000), and low relative molecular weights (<66,000). It was concluded that Bifidobacterium spp. andC. butyricum degraded and utilized granules of amylomaize starch.
Birthday protocols for low energy deployment and flexible neighbor discovery in ad hoc wireless networks

In this paper, we address two problems associated with static ad hoc wireless networks; methods of saving energy during a deployment of the nodes, and efficient methods of performing adjacent neighbor discovery. To meet these goals we introduce a family of "birthday protocols"which use random independent transmissions to discover adjacent nodes. Various modes of the birthday protocol are used to solve the two problems. We provide a mathematical model and analysis of two modes of the protocol and are led to a third mode which is the probabilistic analog of the deterministic round robin scheduling algorithm. We show by analysis and simulation that the birthday protocols are a promising tool for saving energy during the deployment of an ad hoc network as well as an efficient and flexible means of having the nodes discover their neighbors
Concatenated Polar codes

Polar codes have attracted much recent attention as one of the first codes with low computational complexity that provably achieve optimal rate-regions for a large class of information-theoretic problems. One significant drawback, however, is that for current constructions the probability of error decays sub-exponentially in the block-length (more detailed designs improve the probability of error at the cost of significantly increased computational complexity. In this work we show how the the classical idea of code concatenation - using “short” polar codes as inner codes and a “high-rate” Reed-Solomon code as the outer code - results in substantially improved performance. In particular, code concatenation with a careful choice of parameters boosts the rate of decay of the probability of error to almost exponential in the block-length with essentially no loss in computational complexity. We demonstrate such performance improvements for three sets of information-theoretic problems - a classical point-to-point channel coding problem, a class of multiple-input multiple output channel coding problems, and some network source coding problems.
DESIGN OF A SMART MASS FLOW SENSOR FOR COMBINE HARVESTERS

Abstract A popular method for measuring mass flows on combine harvesters is to register the induced force on a circular chute. Since this type of sensors are strongly subjected to wear and installed on difficult accessible places, it is important to know when the sensor provides wrong measurements without interrupting the process. In this study, a double, adaptive IIR notch filter is designed to track both resonance frequency and paddle rate of the feeding elevator on-line and providing a first rejection of both disturbance frequencies from the flow signal.
SWE retrieval over a forested watershed using a snow emission model inversion algorithm

For Hydro-Québec, the water contains within the snow-pack represents more than 30% of its annual energy reserve. Moreover, 97% of Hydro-Quebec's power production is hydroelectric. Thus, the knowledge of the maximum value of snow water equivalent is a crucial information to maximise hydropower generation for all Hydro-Québec's watersheds. To improve monitoring snow properties in forested areas, a model inversion scheme is adapted to incorporate the information provided by the total volume map produced by the Canadian Forest Service. The first results show that the inversion algorithm can quantify adequately the snow water equivalent during the winter period over a forested watershed.
Modelling compositional changes in nickel base alloy 602 CA during high temperature oxidation

Abstract The high chromium nickel base alloy 602 CA is used as construction material for high temperature components in aggressive environments such as gas burners or heat exchangers. The high temperature oxidation behaviour of this alloy is characterised by the formation of an external Cr2O3 scale and internal precipitation of alumina. The main goal of the present investigation was to elucidate the effect of aluminum on the subscale chromium depletion phenomena. The chromium concentration profiles were found to be flat and sometimes even increasing towards the oxide-alloy interface. The experimental observations were interpreted in terms of alloy thermodynamics, i.e. effect of oxidation induced compositional changes on chemical potentials of the alloy constituents. The concentration profiles in alloy 602 CA observed during high temperature exposure were modelled using the CALPHAD approach for thermodynamic and kinetic calculations. Thermodynamic calculations revealed that the Al depletion in the alloy subsurface due to internal alumina precipitation leads to enhanced Cr diffusion towards the alloy surface.
Rademacher Complexity Bounds for a Penalized Multiclass Semi-Supervised Algorithm

We propose Rademacher complexity bounds for multi-class classifiers trained with a two-step semi-supervised model. In the first step, the algorithm partitions the partially labeled data and then identifies dense clusters containing k predominant classes using the labeled training examples such that the proportion of their non-predominant classes is below a fixed threshold stands for clustering consistency. In the second step, a classifier is trained by minimizing a margin empirical loss over the labeled training set and a penalization term measuring the disability of the learner to predict the k predominant classes of the identified clusters. The resulting data-dependent generalization error bound involves the margin distribution of the classifier, the stability of the clustering technique used in the first step and Rademacher complexity terms corresponding to partially labeled training data. Our theoretical result exhibit convergence rates extending those proposed in the literature for the binary case, and experimental results on different multi-class classification problems show empirical evidence that supports the theory.
Resolvin D1, resolvin D2 and maresin 1 activate the GSK3β anti-inflammatory axis in TLR4-engaged human monocytes

Pro-resolving, docosahexaenoic acid-derived mediators have recently emerged as important potential therapeutic agents for the amelioration of complications arising from inflammation, such as vascular disease, asthma, acute lung injury and colitis. While resolvin D1 (RVD1), resolvin D2 (RVD2) and maresin 1 (MaR1) are established pro-resolvins, their mechanisms of action remain unclear. Here we show that, in LPS-stimulated primary human monocytes, RVD1, RVD2 and MaR1 each suppress the release of pro-inflammatory cytokines (TNF, IL-1β, IL-8) and the innate/adaptive bridging cytokine, IL-12 p40, while simultaneously augmenting the production of the anti-inflammatory cytokine, IL-10. Such resolving activity is accompanied by the increased phosphorylation (enhanced anti-inflammatory state) of glycogen synthase kinase 3β (GSK3β) along with increased phosphorylation (activation) of Akt, SGK1 and CREB but not MAPK-related molecules. Gain and loss of function experiments confirm a key role for GSK3β and CREB in the anti-inflammatory actions of resolvins. These results suggest that induction of the GSK3β anti-inflammatory axis is a common mechanism of action for RVD1, RVD2 and MaR1.
The role of dietary nutrition in stomach cancer

Stomach cancer mortality still represents a significant proportion of all cancer deaths. The majority of patients with advanced cancer experience cancer anorexia-cachexia syndrome with weight loss, reduced appetite, fatigue, and weakness. Neoplastic cachexia is a very common clinical manifestation of upper gastrointestinal (GI) tract cancer and is generally assumed to be secondary to the mechanical effects of the tumor on the upper digestive tract. The main reasons are obstruction to swallowing, early satiety, nausea and vomiting. Another reason for weight loss is the co-existence of systemic inflammation. Nutritional treatment in the group of patients with gastric cancer is still used too rarely and the knowledge about it is still very limited. Nutritional support should be given for patients both in the pre- and postoperative period. Nutrition should also be used in palliative treatment in patients with unresectable stomach cancer. The main principles of nutritional support and its influence are presented in this publication.
Fluticasone Propionate Protects against Ozone-Induced Airway Inflammation and Modified Immune Cell Activation Markers in Healthy Volunteers

Background Ozone exposure induces airway neutrophilia and modifies innate immune monocytic cell-surface phenotypes in healthy individuals. High-dose inhaled corticosteroids can reduce O3-induced airway inflammation, but their effect on innate immune activation is unknown. Objectives We used a human O3 inhalation challenge model to examine the effectiveness of clinically relevant doses of inhaled corticosteroids on airway inflammation and markers of innate immune activation in healthy volunteers. Methods Seventeen O3-responsive subjects [> 10% increase in the percentage of polymorphonuclear leukocytes (PMNs) in sputum, PMNs per milligram vs. baseline sputum] received placebo, or either a single therapeutic dose (0.5 mg) or a high dose (2 mg) of inhaled fluticasone proprionate (FP) 1 hr before a 3-hr O3 challenge (0.25 ppm) on three separate occasions at least 2 weeks apart. Lung function, exhaled nitric oxide, sputum, and systemic biomarkers were assessed 1–5 hr after the O3 challenge. To determine the effect of FP on cellular function, we assessed sputum cells from seven subjects by flow cytometry for cell-surface marker activation. Results FP had no effect on O3-induced lung function decline. Compared with placebo, 0.5 mg and 2 mg FP reduced O3-induced sputum neutrophilia by 18% and 35%, respectively. A similar effect was observed on the airway-specific serum biomarker Clara cell protein 16 (CCP16). Furthermore, FP pretreatment significantly reduced O3-induced modification of CD11b, mCD14, CD64, CD16, HLA-DR, and CD86 on sputum monocytes in a dose-dependent manner. Conclusions This study confirmed and extended data demonstrating the protective effect of FP against O3-induced airway inflammation and immune cell activation.
Adaptive controller design of piezo-stage base on neural networks

Double sigmoid activation function is adopted to improve the BP neural networks to build the piezo-stage's on-line identification model. Then based on the on-line identification model, a neural networks model reference adaptive controller is designed to realize the piezo-stage's high accuracy tracking for micro/nanopositioning. Some experiment has been done to indicate the validity of the control scheme.