Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Welding Currents on Microstructure and Microhardness of Ni45 Alloy Reinforced with Spherical Tungsten Carbides (40 mass%) by Plasma Transferred Arc Welding

The Ni45 alloy reinforced with spherical tungsten carbides powder was deposited on the surface of 304L stainless steel by plasma transferred arc welding (PTAW). To determine the microstructure and microhardness of the coating with different currents, X-ray diffraction, an optical microscope, a scanning electron microscope, an electron microprobe and a hardness tester were all employed. The experimental results indicated that the microstructure of the coatings consisted mainly of different morphological strengthening phases and tungsten carbides distributed in £-Ni matrix. Uniformly dispersed tungsten carbides were mostly in their original shape. Welding currents had strong effects on dilution with the base material and also on the formation of transition zones where the tungsten carbides were completely melted near the interface. In addition, lower currents resulted in transverse cracks along the fringe of the tungsten carbides. Concerning hardness it was found that higher currents contributed to lowering the hardness of the coating because of the intermixing of Fe in the hardfacing, the dissolution of the tungsten and the re-precipitation of the secondary carbides in the matrix. However, with higher currents, the hardness in the transition zone was greater than that with lower ones, which was the result of the predominant effect of melted tungsten carbides. [doi:10.2320/matertrans.M2013263]
Regional Accuracy of ZTE-Based Attenuation Correction in Static [18F]FDG and Dynamic [18F]PE2I Brain PET/MR

Accurate MR-based attenuation correction (MRAC) is essential for quantitative PET/MR imaging of the brain. In this study, we analyze the regional bias caused by MRAC based on Zero-Echo-Time MR images (ZTEAC) compared to CT-based AC (CTAC) in static and dynamic PET imaging. In addition the results are compared to the performance of the current default Atlas-based AC (AtlasAC) implemented in the GE SIGNA PET/MR. Methods: Thirty static [18F]FDG and 11 dynamic [18}F]PE2I acquisitions from a GE SIGNA PET/MR were reconstructed using ZTEAC (using a research tool, GE Healthcare), single-subject AtlasAC (the current default AC in GE's SIGNA PET/MR) and CTAC (from a PET/CT acquisition of the same day). In the 30 static [18F]FDG reconstructions, the bias caused by ZTEAC and AtlasAC in the mean uptake of 85 anatomical volumes of interest (VOIs) of the Hammers' atlas was analyzed in PMOD. For the 11 dynamic [18}F]PE2I reconstructions, the bias caused by ZTEAC and AtlasAC in the non displaceable binding potential BPnd in the striatum was calculated with cerebellum as the reference region and a simplified reference tissue model. Results: The regional bias caused by ZTEAC in the static [18F]FDG reconstructions ranged from -8.0% to +7.7% (mean 0.1%, SD 2.0%). For AtlasAC this bias ranged from -31.6% to +16.6% (mean -0.4%, SD 4.3%). The bias caused by AtlasAC showed a clear gradient in the cranio-caudal direction (-4.2% in the cerebellum, +6.6% in the left superior frontal gyrus). The bias in the striatal BPnd for the [18F]PE2I reconstructions ranged from -0.8% to +4.8% (mean 1.5%, SD 1.4%) using ZTEAC and from -0.6% to +9.4% using AtlasAC (mean 4.2%, SD 2.6%). Conclusion: ZTEAC provides excellent quantitative accuracy for static and dynamic brain PET/MR, comparable to CTAC, and is clearly superior to the default AtlasAC currently implemented in the GE SIGNA PET/MR.
No . 3022 Fiscal Federalism and Electoral Accountability

We study the efficient allocation of spending and taxation authority in a federation in which federal politicians are exposed to electoral uncertainty. We show that centralization may, but need not, result in a loss of electoral accountability. We identify an important asymmetry between positive and negative externalities and show that centralization may not be efficient in economies with positive externalities even when regions are identical and centralization does not entail a loss of accountability. We also show that decentralization can only Pareto dominate centralization in economies with negative externalities. JEL-Code: D72, D78, H41.
Antioxidant Activity of Alginic Acid in Minced Pork Meat

In this study, the antioxidant activity of edible polysaccharides such as alginic acid, chitosan and pectin were estimated using four antioxidant assay systems: 2,2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging, ferric ion reducing activity power (FRAP), oxygen radical absorbance capacity (ORAC) assays, in minced pork meat as the storage test. Alginic acid had the strongest antioxidant ability to scavenge free radicals and reduce ferrous ion among all polysaccharides tested. Alginic acid inhibited the production of hydroperoxides and secondary oxidation products of lipids in minced pork meats during storage.
The classification of multipartite quantum correlation

In multipartite entanglement theory, the partial separability properties have an elegant, yet complicated structure, which becomes simpler in the case when multipartite correlations are considered. In this work, we elaborate this, by giving necessary and sufficient conditions for the existence and uniqueness of the class of a given class-label, by the use of which we work out the structure of the classification for some important particular cases, namely, for the finest classification, for the classification based on k-partitionability and k-producibility, and for the classification based on the atoms of the correlation properties.
Dihydropyridine receptor ( DHPR ) congenital myopathy

Vanessa Schartner*, Norma B. Romero*, Sandra Donkervoort, Susan Treves, Pinki Munot, Tyler Mark Pierson, Ivana Dabaj, Edoardo Malfatti, Irina Zaharieva, Francesco Zorzato, Osorio Abath Neto, Guy Brochier, Xavière Lornage, Bruno Eymard, Ana Lía Taratuto, Johann Böhm, Hernan Gonorazky, Leigh Ramos-Platt, Lucy Feng, Rahul Phadke, Diana Bharucha-Goebel, Charlotte Jane Sumner, Mai Thao Bui, Emmanuelle Lacene, Maud Beuvin, Clémence Labasse, Nicolas Dondaine, Raphael Schneider, Julie Thompson, Anne Boland, Jean-François Deleuze, Emma Matthews, Aleksandra Nadaj Pakleza, Caroline A. Sewry, Valérie Biancalana, Susana Quijano-Roy, Francesco Muntoni, Michel Fardeau, Carsten G. Bönnemann, Jocelyn Laporte
Detecting and Punishing Unconscious Bias

We present experimental results demonstrating how ideology shapes evaluations of technology aimed at detecting unconscious biases: (1) liberals supported use of the technology to detect unconscious racism but not unconscious anti-Americanism, whereas conservatives showed the reverse pattern, (2) liberals and conservatives opposed punishing individuals for unconscious bias but supported punishing organizations failing to use the technology to root out, respectively, racism or anti-Americanism, (3) concerns about researcher bias and false accusations mediated the effects of ideology on support for the technology, and (4) participants taking strong initial stands were likelier than moderates to reconsider their positions. Our findings demonstrate that there is substantial concern about penalizing unconscious bias at the individual level and that it will be difficult to generate broad support for regulation of unconscious bias at even the organizational level unless the technology is a reliable detector of unconscious biases that lead to frequent or serious antisocial behaviors.
Scaling Hardware Accelerated Network Monitoring to Concurrent and Dynamic Queries With *Flow

Measurement plays a key role in network operation and management. An important but unaddressed practical requirement in high speed networks is supporting concurrent applications with diverse and potentially dynamic measurement objectives. We introduce *Flow, a switch accelerated telemetry system for efficient, concurrent, and dynamic measurement. The design insight is to carefully partition processing between switch ASICs and application software. In *Flow, the switch ASIC implements a pipeline that exports telemetry data in a flexible format that allows applications to efficiently compute many different statistics. Applications can operate concurrently and dynamically on identical streams without impacting each other. We implement *Flow as a line rate P4 program for a 3.2 Tb/s commodity switch and evaluate it with four example monitoring applications. The applications can operate concurrently and dynamically, while scaling to measure terabit rate traffic with a single commodity server.
Growth and nutrient uptake among three wetland plant species occurring in Lake Victoria basin in Kenya.

Nutrient enrichment is one of the most serious threats to wetland ecosystems. Information is lacking, particularly concerning the response of wetland plants species in Kenya in regard to nutrient enrichment of wetlands. Understanding the mechanisms and adaptations that allow only certain species to thrive in the potentially stressful wetland environment requires the study of the biology of these plants. This study was carried out to investigate the growth and nutrient uptake among some selected wetland plant species in Lake Victoria basin, Kenya. Seedlings of Cyperas esculentus L. , Aframomum angustifolium (Sonn.) and Phragmites australis (Cav.) Trin. Ex Steudel) were grown outdoors in pots. The pots were arranged in a completely randomised design under out-door conditions in the Botanic garden at Maseno University. Plants were provided with four nutrient dosage levels of 0 mg [no fertiliser added], 50 mg, 100 mg, 150 mg fertilizer [N: P: K, 10:26:10] per pot and replicated five times. The plants were irrigated daily with tap water for eight weeks. Data on growth which included shoot height, stem diameter, leaf number per plant, leaf area, leaf width, leaf length, shoot and root weights were determined. Leaf N and P was also determined. The data were analysed by analysis of variance (ANOVA) in SAS statistical package. Nutrient availability treatments significantly (P ≤ 0.05) influenced the growth and biochemical parameters investigated. Cyperas esculentus and A. angustifolium had higher rate of biomass accumulation as evidenced by increase in shoot and root weights compared to P. australis. Root-shoot ratios reduced with increasing nutrient concentration in C. esculentus and A. angustifolium, while that of P. australis increased up to 100mg treatment, then slightly reduced at 150mg treatment. Phragmites australis had significantly higher foliar P and N content than the other two species with increasing nutrient availability. There were significant interactions between nutrient treatments and species in most of the parameters measured. We recommend Phragmites australis as a better agroforestry plant species for reclaiming wetland areas.
Knowledge Spillovers and the Timing of Foreign Entry

We analyze how foreign presence affects local ? firm productivity. We relax the standard implicit assumption that spillovers are immediate and permanent. We ? find that spillovers are dynamic. Foreign entry of a majority foreign owned fi? rm has a short run negative effect on the productivity of local competitors, which is more than offset by a longer run positive effect. The entry of minority foreign owned fi? rms has an immediate, though short-lived, positive effect on local suppliers. The entry of majority foreign owned fi? rms also improves the productivity of local suppliers, but the effect materializes later and lasts longer.
An Adaptive Luenberger Observer for Speed-Sensorless Estimation of Induction Machines

This work investigates the problem of speed sensorless state estimation for induction motors. We first exploit a state transformation for the induction motor model. Based on the new state coordinates, we design a new Luenberger observer, which can provide better dynamic performance compared to baseline algorithm. To address the parameter variation problem, the Lyapunov redesign method is used to achieve an adaptation with respect to the parameter $\alpha$. It is shown that the proposed observer can achieve guaranteed asymptotic stability and readily extend to the time-varying speed case. Advantages of the proposed observer include guaranteed asymptotic stability of estimation errors, parameter a adaptation, and better dynamic performance. Simulation results are presented to validate the proposed method.
Localization with random time-periodic quantum circuits

We consider a random time evolution operator composed of a circuit of random unitaries coupling even and odd neighboring spins on a chain in turn. In spirit of Floquet evolution, the circuit is time-periodic; each timestep is repeated with the same random instances. We obtain analytical results for arbitrary local Hilbert space dimension d: On a single site, average time evolution acts as a depolarising channel. In the spin 1/2 (d=2) case, this is further quantified numerically. For that, we develop a new numerical method that reduces complexity by an exponential factor. Haar-distributed unitaries lead to full depolarization after many timesteps, i.e. local thermalization. A unitary probability distribution with tunable coupling strength allows us to observe a many-body localization transition. In addition to a spin chain under a unitary circuit, we consider the analogous problem with Gaussian circuits. We can make stronger statements about the entire covariance matrix instead of single sites only, and find that the dynamics is localising. For a random time evolution operator homogeneous in space, however, the system delocalizes.
Graphene based biosensors—Accelerating medical diagnostics to new-dimensions

Graphene has emerged as a champion material for a variety of applications cutting across multiple disciplines in science and engineering. Graphene and its derivatives have displayed huge potential as a biosensing material due to their unique physicochemical properties, good electrical conductivity, optical properties, biocompatibility, ease of functionalization, and flexibility. Their widespread use in making biosensors has opened up new possibilities for early diagnosis of life-threatening diseases and real-time health monitoring. Following an introduction and discussion on the significance of fabrication protocols and assembly, this review is intended to assess why graphene is suitable to build better biosensors, the working of existing biosensing schemes and their current status toward commercialization for wearable diagnostic and prognostic devices. We believe this review will provide a critical insight for harnessing graphene as a suitable biosensor for the clinical diagnostics, its future prospects and challenges ahead.
Device-independent quantum key distribution with single-photon sources

Device-independent quantum key distribution protocols allow two honest users to establish a secret key with minimal levels of trust on the provider, as security is proven without any assumption on the inner working of the devices used for the distribution. Unfortunately, the implementation of these protocols is challenging, as it requires the observation of a large Bell-inequality violation between the two distant users. Here, we introduce novel photonic protocols for device-independent quantum key distribution exploiting single-photon sources and heralding-type architectures. The heralding process is designed so that transmission losses become irrelevant for security. We then show how the use of single-photon sources for entanglement distribution in these architectures, instead of standard entangled-pair generation schemes, provides significant improvements on the attainable key rates and distances over previous proposals. Given the current progress in single-photon sources, our work opens up a promising avenue for device-independent quantum key distribution implementations.
Ju n 20 18 Element Distinctness Revisited

The element distinctness problem is the problem of determining whether the elements of a list are distinct, that is, if x = (x1, ., xN ) is a list with N elements, we ask whether the elements of x are distinct or not. The solution in a classical computer requires N queries because it uses sorting to check whether there are equal elements. In the quantum case, it is possible to solve the problem in O(N) queries. There is an extension which asks whether there are k colliding elements, known as element k-distinctness problem. This work obtains optimal values of two critical parameters of Ambainis’ seminal quantum algorithm [SIAM J. Comput. , 37, 210-239, 2007]. The first critical parameter is the number of repetitions of the algorithm’s main block, which inverts the phase of the marked elements and calls a subroutine. The second parameter is the number of quantum walk steps interlaced by oracle queries. We show that, when the optimal values of the parameters are used, the algorithm’s success probability is 1 − O(N), quickly approaching 1. The specification of the exact running time and success probability is important in practical applications of this algorithm.
Optimisation and Kinetics Studies on the Extraction of Essential Oil from Zingiber Cassumunar

Three operating parameters of hydrodistillation have been optimised by a response surface method using a central composite design to obtain high yields of essential oil from a rhizome of the Zingiberaceae species Zingiber cassumunar (Z. cassumunar). The optimal conditions for the maximum essential oil produced (6.64 g) were found to be an extraction time of 4 hr, a solid-to-solvent ratio of 3:150 and a hydrodistillation rate of 78 ml/hr. The study was subsequently continued with the three proposed models of the extraction process. Kinetics models proposed by Milojevi et al. and Hervas et al. were suitable for the process under low (20 ml/hr) and high distillation rates (70 ml/hr), whereas the model by Ana et al. was valid for all ranges of rates studied (20-70 ml/hr). It can be concluded that the hydrodistillation rate was one of the important parameters for determining the extraction kinetics.
Path Clearance for Emergency Vehicles through the Use of Vehicle-to-Vehicle Communication

The study described in this paper evaluated and tested a new strategy to enable emergency response vehicles (EVs) to navigate through congestion at signalized intersections more efficiently. The proposed strategy involves the use of vehicle-to-vehicle communication to send messages to alert vehicles to the approach of the EV and to provide specific instructions on maneuvering to allow the EV to proceed through congested signalized intersections as quickly as possible. This movement is achieved by creation of a split in the vehicle queue in one lane at a critical location to allow the EV to proceed at its desired speed but minimize the disruption to the rest of the traffic. The proposed method uses kinematic wave theory (i.e., shock wave theory) to determine the critical point in the vehicle queue. The proposed method is simulated in a microscopic traffic simulator for evaluation. The results show that this strategy can significantly shorten the travel time for EVs through congested signalized intersections.
Factors That Influence E-Government Adoption in Selected Districts of Tanzania

Abstract: Purpose-Tanzania government has been making efforts to provide its information and services through internet. However, e-government adoption has been quite slow. Few publications explore e-government adoption in Tanzanian context; therefore, the purpose of this paper is to assess factors that influence citizen adoption of e-government in Tanzania.Design/methodology/approachA survey was administered to elicit factors for egovernment adoption in Tanzania. FindingsThe results of multiple linear regressions indicate that social influence and system quality significantly influence e-government adoption in Tanzania.Research limitation/implicationsIn light of these findings, researchers should conduct a similar study using other different models of e-government adoption, in order to identify more factors that influence e-government adoption in Tanzania. Practical implicationsPolicy makers and e-government project teams should consider these factors to facilitate e-government adoption within the country.
THE RELIABILITY OF FOREIGN LANGUAGE ANXIETY SCALE IN MALAY VERSION BASED ON CRONBACH’S ALPHA

This paper is part of a study which addresses the reliability of Foreign Language Anxiety Scale (FLCAS) in Malay version. Researchers find that the reliability of an instrument is closely associated with its validity and an instrument cannot be valid unless it is reliable. However, the reliability of an instrument does not depend on its validity. Therefore, this paper investigates the reliability of the instrument called FLCAS in Malay version. FLCAS is widely used in collecting data relating to language anxiety and perhaps the most reliable and comprehensive tool in language anxiety. This paper objectively measures the reliability of FLCAS by using Cronbach’s Alpha, the most widely used objective measure of reliability. The sampled population involved 302 respondents from the government secondary schools in Putrajaya Federal Territory, Malaysia. The items had been translated into the Malay language and back translated into English. Results show that the internal consistency of Crobanch’s Alpha 0.90. It can be concluded that FLCAS in Malay version is an appropriate instrument to measure the levels of language anxiety among the Malaysian secondary school students who learn English as a second language.
Quantum noise cancellation in asymmetric speed metres with balanced homodyne readout

The Sagnac speed metre topology has been identified as a promising technique to reduce quantum back-action in gravitational-wave interferometers. However, imbalance of the main beamsplitter has been shown to increase the coupling of laser noise to the detection port, thus reducing the quantum noise superiority of the speed metre, compared to conventional approaches, in particular at low frequencies. In this paper, we show that by implementing a balanced homodyne readout scheme with a suitable choice of the point from which the local oscillator (LO) is derived, the excess laser noise contribution is partly compensated, and the resulting speed metre can be more sensitive than state-of-the-art position metres. This is achieved by picking-off the LO from either the reflection port of the interferometer or the anti-reflective coating surface of the main beamsplitter. We show that either approach relaxes the relative intensity noise (RIN) requirement of the input laser. For example, for a beam splitter imbalance of 0.1% in the Glasgow speed metre proof of concept experiment, the RIN requirement at frequency of 100 Hz decreases from 4 × 10 − 10 / Hz to 4 × 10 − 7 / Hz , moving the RIN requirement from a value that is hard to achieve in practice, to one which is routinely obtained.
DeepPhish : Simulating Malicious AI

—In this work we describe how threat actors may use AI algorithms to bypass AI phishing detection systems. We analyzed more than a million phishing URLs to understand the different strategies that threat actors use to create phishing URLs. Assuming the role of an attacker, we simulate how different threat actors may leverage Deep Neural Networks to enhance their effectiveness rate. Using Long Short-Term Memory Networks, we created DeepPhish, an algorithm that learns to create better phishing attacks. By training the DeepPhish algorithm for two different threat actors, they were able to increase their effectiveness from 0.69% to 20.9%, and 4.91% to 36.28%, respectively.