Miracle-dz/UniFAR-FTUs huggingface dataset:
Phonon-assisted photoluminescence in wurtzite GaN epilayer

Photoluminescence of wurztite GaN epilayer was measured in the range of 4K to 300K. At low temperature, the neutral- donor bound exciton emission dominates the spectra, while with increasing temperature, free exciton emissions grow rapidly and finally become the dominant lines. The exciton linewidth due to exciton-phonon interaction was studied.Lo phonon-assisted photoluminescence associated with both the bound exciton and the free exciton were also observed. The temperature dependence of LO phonon-assisted emissions can be well explained by the phonon-assisted free exciton emission theory established for II-VI compound semiconductors. In particular, the study of 2LO phonon replica can provide information of the temperature dependence of the concentration and recombination lifetime of free excitons in GaN.
A Novel Spinel-Type Co/Mn Catalyst for Methane Oxidation at Low Temperatures

A Spinel-type Co/Mn catalyst prepared in a sol-gel process has been investigated for catalytic oxidation of methane. The reaction activity was significantly improved by either pretreating the catalyst in the presence of water vapor or addition of water vapor into the feed gas. XPS spectra show that the oxidation activity was closely related with surface Co species and the intensity ratio of lattice oxygen to adsorbed oxygen on the sample.
How Computational Modeling Can Force Theory Building in Psychological Science

Psychology endeavors to develop theories of human capacities and behaviors on the basis of a variety of methodologies and dependent measures. We argue that one of the most divisive factors in psychological science is whether researchers choose to use computational modeling of theories (over and above data) during the scientific-inference process. Modeling is undervalued yet holds promise for advancing psychological science. The inherent demands of computational modeling guide us toward better science by forcing us to conceptually analyze, specify, and formalize intuitions that otherwise remain unexamined—what we dub open theory. Constraining our inference process through modeling enables us to build explanatory and predictive theories. Here, we present scientific inference in psychology as a path function in which each step shapes the next. Computational modeling can constrain these steps, thus advancing scientific inference over and above the stewardship of experimental practice (e.g., preregistration). If psychology continues to eschew computational modeling, we predict more replicability crises and persistent failure at coherent theory building. This is because without formal modeling we lack open and transparent theorizing. We also explain how to formalize, specify, and implement a computational model, emphasizing that the advantages of modeling can be achieved by anyone with benefit to all.
Lithium−Air Battery: Promise and Challenges

The lithium−air system captured worldwide attention in 2009 as a possible battery for electric vehicle propulsion applications. If successfully developed, this battery could provide an energy source for electric vehicles rivaling that of gasoline in terms of usable energy density. However, there are numerous scientific and technical challenges that must be overcome if this alluring promise is to turn into reality. The fundamental battery chemistry during discharge is thought to be the electrochemical oxidation of lithium metal at the anode and reduction of oxygen from air at the cathode. With aprotic electrolytes, as used in Li-ion batteries, there is some evidence that the process can be reversed by applying an external potential, i.e., that such a battery can be electrically recharged. This paper summarizes the authors’ view of the promise and challenges facing development of practical Li−air batteries and the current understanding of its chemistry. However, it must be appreciated that this perspective .
Kinetics of heterogeneously catalyzed tert-amyl methyl ether reactions in the liquid phase

The kinetics of tert-amyl methyl ether (TAME, 2-methoxy-2-methylbutane) reactions was investigated using a commercial ion exchange resin (Amberlyst 16) as catalyst at temperatures between 324 and 354 K. The rates of reaction were determined experimentally in the liquid phase in a continuous stirred tank reactor at a pressure of 0.8 MPa. Kinetic equations derived for three different mechanisms were compared. In the forward reaction the adsorbed methanol reacted with isoamylene (2-methyl-l-butene or 2-methyl-2-butene) striking from the bulk liquid phase, and in the splitting reaction the adsorbed ether split to alcohol and isoamylene. The kinetic equations were written in terms of activities, and the activity coefficients were calculated by the UNIQUAC method. The activation energy was determined to be 95 kJ/mol for the splitting reaction of TAME to 2-methyl-l-butene and methanol and 100 kJ/mol for the splitting reaction of TAME to 2-methyl-2-butene and methanol.
Differential Equations: A Historical Refresher

This paper presents a brief account of the important milestones in the historical development of the theory of differential equations. The paper begins with a discussion on the date of birth of differential equations and then touches upon Newton's approach to differential equations. Then the development of the various methods for solving the first order differential equations and the second order linear differential equations are discussed. The paper concludes with a brief mention of the series solutions of differential equations and the qualitative study of differential equations.
Advances in Optical and Microwave Nonreciprocity

Modern photonic and quantum technologies demand reciprocity breaking, e.g., isolators, full-duplex systems, noise isolation in quantum computers, motivating searching for practical approaches beyond magnet-based devices. This work overviews the up-and-coming advances in optical nonreciprocity, including new materials (Weyl semimetals, topological insulators, metasurfaces), active structures, time-modulation, PT-symmetry breaking, nonlinearity, quantum nonlinearity, unidirectional gain and loss, chiral quantum states, and valley polarization.
Three-dimensional color map: a novel tool to locate the surgical transepicondylar axis

Background Accurate localization of the surgical transepicondylar axis (sTEA) in total knee arthroplasty (TKA), the most reliable anatomical reference for femoral rotation, has long been a challenge, primarily because it is intractable to locate the center of the sulcus of the medial epicondyle. This study aimed to introduce and verify a novel method to locate the sTEA more precisely. Methods This study included 26 adult femoral specimens and 80 adult patients with computed tomography (CT) scan data. Three dimensions (3D) models based on CT scans of the distal femurs were reconstructed with Mimics and imported into Geomagic Studio. The 3D color map method was applied to locate the sTEA. To further verify the accuracy of the method, the identified sTEA was transferred to the femoral specimens and compared with the points identified by the total station machine. We further compared the recognition rate of sTEA between 3D color map method and two-dimensional (2D) CT slices method. The repeatability of this novel method was also evaluated. Results The 3D color map method located the centers of the sulcus of the medial epicondyle and the most prominent point of the lateral epicondyle of all the femoral specimens, which were further identified and confirmed by patient-specific guide plates and total station machine on femoral specimens. The 3D color map method achieved a recognition rate of up to 96.23%, while the recognition rate of the 2D CT slices method was only 68.87%. The repeatability of this objective method was excellent. Conclusions The results of this study indicated that the 3D color map method could be used to accurately and objectively locate the sTEA, with high repeatability and recognition rate. However, the proposed novel method requires further validation in clinical applications.
Evaluation of a Method for Measurement of the Concentration and Size Distribution of Black Carbon Particles Suspended in Rainwater

We make detailed evaluations of a method of measuring the mass concentration and size distribution of black carbon (BC) particles suspended in water for the purpose of application to rainwater samples. Water samples were aerosolized with an ultrasonic nebulizer. Generated water droplets were dried in order to extract airborne BC particles. The mass of each BC particle was then measured by a Single Particle Soot Photometer (SP2), based on the laser-induced incandescence technique. Under the optimized operating conditions of our measurement system, the overall efficiency of the extraction of BC particles from rainwater was determined to be 11.4% ± 0.83% by mass, resulting in a total uncertainty of about ±20% for the measurement of the BC concentration in rainwater. The change in efficiency due to water-soluble species was found to be negligibly small for rainwater samples analyzed in this study. The determination of the efficiency by using standard BC solutions was necessary at an appropriate frequency because changes in the overall conditions of the system lead to changes in the efficiency in the long term. The size of BC particles in rainwater can be overestimated because of the coagulation of BC particles in the process of extraction by the nebulizer. This effect increased with the increase in BC concentration in rainwater. The effect can be minimized by dilution of rainwater samples by pure water. The volume of a rainwater sample required for BC measurement was less than 5 mL, enabling measurement for weak rain or highly time-resolved measurements during each rain event.
Synthesis, Structure, and Photochemistry of an Organic Heptamolybdate-Monomolybdate

Treatment of MoO(3) with butan-1-amine (BuNH(2)) or pyrrolidine (PyrNH(2)) results in the formation of (BuNH(3))(8)(Mo(7)O(24))-(MoO(4))center dot 3H(2)O (1; BuNH(3) = butan-1-aminium) or (PyrNH(2))(6)-(Mo(7)O(24)center dot 2H(2)O (2; PyrNH(2) = pyrrolidinium), respectively. On irradiation with sunlight, compound 1, which is an organic heptamolybdate Mo(7)O(24)(6-) that contains a cocrystallized monomolybdate MoO(4)(2-) in the same compound, is transformed to an oxido-bridged diheptamolybdate(BuNH(3))(10)(-)(Mo(7)O(22))(mu(2)-O)(2)(Mo(7)O(22))ce nter dot 5.5H(2)O (1b). The Mo(7)O(24)(6-) units in 1 and 2 are made up of edge-sharing MoO(6) octahedra, whereas the central unit in 1b is a bis(mu(2)-O)-bridged heptamolybdate dimer. Hydrogen bonding among the lattice water molecules in 1 results in the formation of a water octamer, whereas hydrogen bonding between the lattice water molecules and Mo(7)O(24)(6-) in 2 results in the formation of a one-dimensional water-linked heptamolybdate chain. Supramolecular structures, photochemistry, and thermal properties of 1, 1b, and 2 are reported. For comparison of photochemical behavior, two more polyoxomolybdates, (PrNH(3))(6)Mo(7)O(24)center dot 3H(2)O (3; PrNH(3) = propan-1-aminium) and (PentNH(3))(6)(-)Mo(7)O(24)center dot 3H(2)O (4; PentNH(3) = pentan-1-aminium), were prepared and characterized.
Malachite Green Removal from Aqueous Solution by the Peel of Cucumis sativa Fruit

This study investigates the potential use of activated carbon prepared from the peel of Cucumis sativa fruit for the removal of malachite green (MG) dye from simulated wastewater. The effects of different system variables, adsorbent dosage, initial dye concentration, pH, and contact time were investigated and optimal experimental conditions were ascertained. The results showed that when the amount of the adsorbent increased, the percentage of dye removal increased accordingly. Optimum pH value for dye adsorption was 6.0. Maximum dye was sequestered within 50 min of the start of every experiment. The adsorption ofMG followed the pseudo-second-order rate equation and fits the Langmuir, Freundlich, Dubinin-Radushkevich (D-R), and Tempkin equations well. The maximum removal of MG was obtained at pH 6 as 99.86% for adsorbent dose of 1 g/50 mL and 25 mg L -1 initial dye concentration at room temperature. Activated carbon developed from the peel of C. sativa fruit can be an attractive option for dye removal from diluted industrial effluents since test reaction made on simulated dyeing wastewater showed better removal percentage of MG.
Best Arm Identification in Graphical Bilinear Bandits

We introduce a new graphical bilinear bandit problem where a learner (or a \emph{central entity}) allocates arms to the nodes of a graph and observes for each edge a noisy bilinear reward representing the interaction between the two end nodes. We study the best arm identification problem in which the learner wants to find the graph allocation maximizing the sum of the bilinear rewards. By efficiently exploiting the geometry of this bandit problem, we propose a somehow \emph{decentralized} allocation strategy based on random sampling with theoretical guarantees. In particular, we characterize the influence of the graph structure (e.g. star, complete or circle) on the convergence rate and propose empirical experiments that confirm this dependency.
Mono, mixed or multiple strategy approach: a descriptive study of the latest published articles in the International Journal of Project Management

To develop a valid and credible research project, it is essential to define in detail the research design. It will have a meaningful strategy to answer the research question. While some researchers suggest that there might be some benefits in adopting multiple and mixed strategy approach for conducting the research, some tend to stick to mono-methods. This article tackles a descriptive study that identifies the research strategies followed by top ranked researches, by reviewing the last two years of publications of the International Journal of Project Management, the leading journal for the field of project management and organization studies. The results suggest that most researchers stick to mono-methods, predominantly with qualitative techniques. Also, there is a higher trend to use case study strategies in the field.
Evaluation and Comparison of Diffusion Models with Motif Features

Diffusion models simulate the propagation of influence in networks. The design and evaluation of diffusion models has been subjective and empirical. When being applied to a network represented by a graph, the diffusion model generates a sequence of edges on which the influence flows, such sequence forms a temporal network. In most scenarios, the statistical properties or the characteristics of a network are inferred by analyzing the temporal networks generated by diffusion models. To analyze real temporal networks, the motif has been proposed as a reliable feature. However, it is unclear how the network topology and the diffusion model affect the motif feature of a generated temporal network. In this paper, we adopt the motif feature to evaluate the temporal graph generated by a diffusion model, thence the diffusion model itself. Two benchmarks for quantitively evaluating diffusion models with motif, stability and separability, are proposed and measured on numerous diffusion models. One motif-based metric is proposed to measure the similarity between diffusion models. The experiments suggest that the motif of a generated temporal network is dominated by the diffusion model, while the network topology is almost ignored. This result indicates that more practical and reliable diffusion models have to be designed with delicacy in order to capture the propagation patterns of real temporal networks.
Paper Title (use style: paper title)

A power transformer winding is usually subject to mechanical stress and tension because of improper transportation or operation. Radial deformation (RD) is an example of mechanical stress that can impact power transformer operation through short circuit faults and insulation damages. Frequency response analysis (FRA) is a well-known method to diagnose mechanical defects in transformers. Despite the precision of FRA, the interpretation of the calculated frequency response curves is not straightforward and requires complex calculations. In this paper, a deep learning algorithm called long short-term memory (LSTM) is used as a feature extraction technique to locate RD faults in their early stages. The experimental results verify the effectiveness of the proposed method in the diagnosis and locating of RD defects. Keywords— Deep learning, frequency response analysis, long short-term memory, radial deformation, transformer winding.
Statistical matching and subclassification with a continuous dose: characterization, algorithms, and inference

Subclassification and matching are often used to adjust for observed covariates in observational studies; however, they are largely restricted to relatively simple study designs with a binary treatment. One important exception is Lu et al.(2001), who considered optimal pair matching with a continuous treatment dose. In this article, we propose two criteria for optimal subclassification/full matching based on subclass homogeneity with a continuous treatment dose, and propose an efficient polynomial-time algorithm that is guaranteed to find an optimal subclassification with respect to one criterion and serves as a 2-approximation algorithm for the other criterion. We discuss how to incorporate treatment dose and use appropriate penalties to control the number of subclasses in the design. Via extensive simulations, we systematically examine the performance of our proposed method, and demonstrate that combining our proposed subclassification scheme with regression adjustment helps reduce model dependence for parametric causal inference with a continuous treatment dose. We illustrate the new design and how to conduct randomization-based statistical inference under the new design using Medicare and Medicaid claims data to study the effect of transesophageal echocardiography (TEE) during CABG surgery on patients' 30-day mortality rate.
Cooperative Location Privacy in Vehicular Networks: Why Simple Mix Zones are Not Enough

Vehicular communications disclose rich information about the vehicles and their whereabouts. Pseudonymous authentication secures communication while enhancing user privacy. To enhance location privacy, cryptographic mix zones were proposed to facilitate vehicles covertly transition to new ephemeral credentials. The resilience to (syntactic and semantic) pseudonym linking (attacks) highly depends on the geometry of the mix zones, mobility patterns, vehicle density, and arrival rates. We introduce a tracking algorithm for linking pseudonyms before and after a cryptographically protected mix zone. Our experimental results show that an eavesdropper, leveraging standardized vehicular communication messages and road layout, could successfully link ≈73% of pseudonyms during nonrush hours and ≈62% of pseudonyms during rush hours after vehicles change their pseudonyms in a mix zone. To mitigate such inference attacks, we present a novel cooperative mix zone scheme that enhances user privacy regardless of the vehicle mobility patterns, vehicle density, and arrival rate to the mix zone. A subset of vehicles, termed relaying vehicles, is selected to be responsible for emulating nonexisting vehicles. Such vehicles cooperatively disseminate decoy traffic without affecting safety-critical operations: with 50% of vehicles as relaying vehicles, the probability of linking pseudonyms (for the entire interval) drops from ≈68% to ≈18%. On average, this imposes 28 ms extra computation overhead, per second, on the roadside unit (RSU) and 4.67 ms extra computation overhead, per second, on the (relaying) vehicle side; it also introduces 1.46 kB/s extra communication overhead by (relaying) vehicles and 45 kB/s by RSUs for the dissemination of decoy traffic. Thus, user privacy is enhanced at the cost of low computation and communication overheads.
Giant thermopower and power factor in twisted bilayer graphene at low temperature.

The phonon-drag thermopower $S^g$, diffusion thermopower $S^d$ and the power factor $PF$ are theoretically investigated in twisted bilayer graphene (tBLG) as a function of twist angle $\theta$, temperature $T$ and electron density $n_s$. As $\theta$ approaches magic angle $\theta_m$, the $S^g$ and $S^d$ are found to be highly enhanced, which is manifestation of great suppression of Fermi velocity ${\nu_F}^*$ of electrons in moire flat band near $\theta_m$. In the Bloch- Gruneisen (BG) regime, it is found that $S^g \sim {\nu_F}^{* -2}$, $T^3$ and ${n_s}^{-1/2}$. The $T^3$ and ${n_s}^{-1/2}$ dependencies are, respectively, signatures of 2D phonons and the Dirac fermions. An enhancement of $S^g$ up to $\sim$ 500 times that of monolayer graphene (MLG) is predicted at $\sim$ 1 K. This enhancement decreases with increasing $\theta$ and $T$. As $T$ increases, the power $\delta$ in $S^g \sim T^\delta$, changes from 3 to nearly zero and a maximum $S^g$ value of the order of $\sim$ 10 mV/K at $\sim$ 20 K is estimated. Simple relations of 'Kohn anomaly temperature' $T_{KA}$ with $\theta$ and $n_s$ are obtained. $S^g$ is larger (smaller) for smaller $n_s$ in low (high) temperature region. On the other hand, $S^d$, taken to be governed by Mott formula, $\sim {\nu_F}^{* -1}$, $T$ and ${n_s}^{-1/2}$ and is much greater than that in MLG. $S^g$ dominates $S^d$ very significantly for $T > \sim$ 2 K. In tBLG, $\theta$ acts as a strong tuning parameter of both $S^g$ and $S^d$, in addition to $T$ and $n_s$. Moreover, in the BG regime Herring's law is found to be satisfied in tBLG. The power factor $PF$ is also found to be strongly $\theta$ dependent and is very much larger than that in MLG. $PF$ as a function of $T$ is found to exhibit a broad maximum, which is, for example, $\sim$75 W/m-K$^2$ for $\theta = 1.2^\circ$. Consequently, possibility of a giant figure of merit is discussed.
Computing Machinery and Knowledge

The purpose of this paper is to discuss the possibilities for computing machinery, or AI agents, to know and to possess knowledge. This is done mainly from a virtue epistemology perspective and definition of knowledge. However, this inquiry also shed light on the human condition, what it means for a human to know, and to possess knowledge. The paper argues that it is possible for an AI agent to know and examines this from both current state-of-the-art in artificial intelligence as well as from the perspective of what the future AI development might bring in terms of superintelligent AI agents.
Learning over no-Preferred and Preferred Sequence of items for Robust Recommendation

In this paper, we propose a theoretically supported sequential strategy for training a large-scale Recommender System (RS) over implicit feedback, mainly in the form of clicks. The proposed approach consists in minimizing pairwise ranking loss over blocks of consecutive items constituted by a sequence of non-clicked items followed by a clicked one for each user. We present two variants of this strategy where model parameters are updated using either the momentum method or a gradient-based approach. To prevent updating the parameters for an abnormally high number of clicks over some targeted items (mainly due to bots), we introduce an upper and a lower threshold on the number of updates for each user. These thresholds are estimated over the distribution of the number of blocks in the training set. They affect the decision of RS by shifting the distribution of items that are shown to the users. Furthermore, we provide a convergence analysis of both algorithms and demonstrate their practical efficiency over six large-scale collections with respect to various ranking measures and computational time.