Miracle-dz/UniFAR-FTUs huggingface dataset:
Development, structural and rheological characterization, and in vitro evaluation of the zinc-doped 45S5 bioactive glass-vaseline ointment for potential wound healing applications

Bioactive glass (BG) has recently been proposed to be used for wound healing with Vaseline®. To accelerate the wound healing by incorporation of the Zinc (Zn) into BG, undoped and 5 wt% zinc-doped 45S5 BG (16 wt%) were prepared with Vaseline® to create the ointments for wound healing as a VBG and VBG-Zn, respectively. The results showed that desired composition, irregular form, and no porous surface have obtained for BGs. FT-IR spectrum of Zn-doped BG demonstrates increasing Network Connectivity due to Zn incorporation. Ointments exhibited pseudoplastic behaviour and viscoelastic characteristic, indicating that ointments have good topical application. Ointments did not toxic effect towards L929 cells in terms of biocompatibility for topical applications. In vitro wound healing assays revealed that VBG-Zn promotes wound healing thanks to incorporation of the Zn accelerates skin wound closure. All findings point to VBG-Zn ointment having a greater potential for wound healing applications. Graphical abstract
Robust Scheduling of Thermostatically Controlled Loads With Statistically Feasible Guarantees

Flexible resources are increasingly significant for the reliable operation of power grids due to the high penetration of renewable energy. Thermostatically controlled loads (TCLs) are one of the common flexible resources, whose control has been extensively studied. Yet, much can be improved. We investigate the scheduling of TCLs facing uncertain temperatures and dynamic prices. Classical approaches often employ the chance-constrained program or robust optimization to handle such uncertainties. However, these approaches either require specific distribution knowledge or yield too conservative solutions. The distribution knowledge can be rather challenging to obtain especially when the uncertainties from different sources are correlated. To this end, we adopt the notion of statistical feasibility and propose a robust sample-based scheduling scheme for TCLs. Such a sample-based scheme relieves the reliance on the distribution knowledge and is able to characterize the coupling effects of the two uncertainty sources. Besides, through integrating the real-time domain knowledge into uncertainty set reconstruction, we relax the solutions’ conservation by exploring the consumers’ tolerance to the room temperature. Numerical studies highlight the remarkable performance of our proposed scheme. Specifically, our approach is able to simultaneously effectively reduce the electricity bills of consumers and satisfy the consumers’ tolerance to the room temperature.
Comparison of Asymmetry between Perceptual, Ocular, and Postural Vestibular Screening Tests

Background: A better understanding of how vestibular asymmetry manifests across tests is important due to its potential implications for balance dysfunction, motion sickness susceptibility, and adaptation to new environments. Objective: We report the results of multiple tests for vestibular asymmetry in 32 healthy participants. Methods: Asymmetry was measured using perceptual reports during unilateral centrifugation, oculomotor responses during visual alignment tasks, vestibulo-ocular reflex gain during head impulse tests, and body rotation during stepping tests. Results: A significant correlation was observed between asymmetries of subjective visual vertical and verbal report during unilateral centrifugation. Another significant correlation was observed between the asymmetries of ocular alignment, vestibulo-ocular reflex gain, and body rotation. Conclusions: These data suggest that there are underlying vestibular asymmetries in healthy individuals that are consistent across various vestibular challenges. In addition, these findings have value in guiding test selection during experimental design for assessing vestibular asymmetry in healthy adults.
Approximating a coupled-task scheduling problem in the presence of compatibility graph and additional tasks

This paper introduces a coupled-task scheduling problem in the presence of a compatibility graph and additional tasks on a single processor. We investigate a specific configuration, in which the coupled-tasks have an idle time of two. The complexity of these problems will be studied according to the presence or absence of triangles in the compatibility graph. Using the results given by Kelmans (1997) on an optimal packing problem of induced stars in a graph, we develop a polynomial-time algorithm which consists of minimising the number of non-covered vertices by covering vertices with edges or paths of length two in the compatibility graph. This type of covering will be called the two-cover technique. According to the compatibility graph type, the two-cover technique provides a polynomial-time ρ-approximation algorithm with (resp. in the presence (resp. absence) of triangles.
Sample Average Approximation Over Function Spaces: Statistical Consistency and Rate of Convergence

This paper considers sample average approximation (SAA) of a general class of stochastic optimization problems over a function space constraint set and driven by “regulated” Gaussian processes. We estab-lish statistical consistency by proving equiconvergence of the SAA estimator via a sophisticated sample complexity result. Next, recognizing that implementation over such infinite-dimensional spaces is possible only if numerical optimization is performed over a finite-dimensional subspace of the constraint set, and if sample paths of the driving process can be generated over a finite grid, we identify the decay rate of the SAA estimator's expected optimality gap as a function of the optimization error, Monte Carlo sampling error, path generation approximation error, and subspace projection error.
Average conditions of thermal stress in Mexican cities with more than one million inhabitants in the face of climatic change

Human bioclimatic scenarios are presented for Mexican cities with more than a million inhabitants. For this, both urban and global warming were considered, the former having been inferred from demographic data, and the latter from the output of general circulation models. Thus, it was possible to estimate increases in temperature and modifications in hygrometric conditions, which were then used to estimate the human bioclimate for the period of 1981-2000 and the decades of 2030 and 2050, as well as the domestic electrical consumption for air-conditioning in housing resulting there from.
Second-order sufficiency and statistical invariants

SUMMARY For samples from a regular distribution depending on one parameter a second-order sufficient statistic is introduced, and its characteristic function obtained correct to this order. With a canonical choice of parameter it is shown that the cumulants of this statistic are functions of basic statistical invariants including 'curvature' terms. The distribution of the maximum likelihood estimator given an approximate ancillary statistic is discussed for translation families and general distributions.
Minimizing the Energy Imports in Sports Complexes by Implementing the Microgrid Concept

Sports centers compose a special case of large-scale buildings which need significant amounts of energy. This is related not only to the specific requirements of the thermal environment regarding the type of activities taking place as well to the considerable high load demands enforced by the presence of people. This paper evaluates the energy consumption of the Olympic Athletic Center of Athens (OAKA), extracts energy baselines as a reference for the following studies and proposes a new strategy to improve and optimize its energy system operation. In particular, the concept of a microgrid is introduced in the grid of OAKA, where load demand is exclusively served by energy imports from the external local grid. Therefore, the highest possible autonomous operation of the internal grid is examined, minimizing the imports from the city’s grid. To achieve this, the maximum possible installation of PV combined with battery storage units is examined, using as backup units the existing gensets of the facilities.
RUemo - The Classification Framework for Russia-Ukraine War-Related Societal Emotions on Twitter through Machine Learning

The beginning of this decade brought utter international chaos with the COVID-19 pandemic and the Russia-Ukraine war (RUW). The ongoing war has been building pressure across the globe. People have been showcasing their opinions through different communication media, of which social media is the prime source. Consequently, it is important to analyze people’s emotions toward the RUW. This paper therefore aims to provide the framework for automatically classifying the distinct societal emotions on Twitter, utilizing the amalgamation of Emotion Robustly Optimized Bidirectional Encoder Representations from the Transformers Pre-training Approach (Emoroberta) and machine-learning (ML) techniques. This combination shows the originality of our proposed framework, i.e., Russia-Ukraine War emotions (RUemo), in the context of the RUW. We have utilized the Twitter dataset related to the RUW available on Kaggle.com. The RUemo framework can extract the 27 distinct emotions of Twitter users that are further classified by ML techniques. We have achieved 95% of testing accuracy for multilayer perceptron and logistic regression ML techniques for the multiclass emotion classification task. Our key finding indicates that:First, 81% of Twitter users in the survey show a neutral position toward RUW; second, there is evidence of social bots posting RUW-related tweets; third, other than Russia and Ukraine, users mentioned countries such as Slovakia and the USA; and fourth, the Twitter accounts of the Ukraine President and the US President are also mentioned by Twitter users. Overall, the majority of tweets describe the RUW in key terms related more to Ukraine than to Russia.
80×80 VPD PbSe: the first uncooled MWIR FPA monolithically integrated with a Si-CMOS ROIC

In this work a breakthrough in the field of low cost uncooled infrared detectors is presented: an 80x80 MWIR VPD PbSe detector monolithically integrated with the corresponding Si-CMOS circuitry. Fast speed of response and high frame rates are, until date, non existing performances in the domain of low cost uncooled IR imagers. The new detector presented fills the gap. The device is capable to provide MWIR images to rates as high as 2 KHz, full frame, in real uncooled operation which converts it in an excellent solution for being used in applications where short events and fast transients dominate the system dynamics to be studied or detected. VPD PbSe technology is unique because combines all the main requirements demanded for a volume ready technology: 1. Simple processing 2. Good reproducibility and homogeneity 3. Processing compatible with big areas substrates 4. Si-CMOS compatible (no hybridation needed) 5. Low cost optics and packagin The new FPA represents a milestone in the road towards affordable uncooled MWIR imagers and it is the demonstration of VPD PbSe technology has reached industrial maturity. The device presented in the work was processed on 8-inch Si wafers with excellent results in terms of manufacturing yield and repeatability. The technology opens the MWIR band to SWaP concept.
Biological activities and chemical composition of essential oil of Achillea maritima (L.) Ehrend. & Y.P.Guo

ABSTRACT This study aimed to describe the chemical composition of the essential oil (EO) of stems, leaves and flowers of A. maritima collected from Turkey, and verify its antimicrobial and antioxidant properties. The EO was analyzed by GC-FID and GC-MS. Fifty-nine compounds representing to 98.1% of the EO were identified. The antimicrobial activities were determined against seven bacteria and two yeast species by using disc diffusion and MIC techniques. According to the results, it was observed that there was no effect of the EO against Gram-positive bacteria. The EO showed a low effect (8–9 mm) against Gram-negative bacteria, but the EO had a high effect (20–22 mm) against the tested fungi. In addition, according to the MIC test results, the EO presented effects against C. krusei, C. parapsilosis at a concentration of 50 µl/ml. The antioxidant activity of the EO was determined as IC50 = 31.9 µl/mL.
Magnetic blow-off in armature transition

Magnetic blow-off forces play an important role in arcing and failure of electrical joints and contacts in electrical systems under high current fault conditions. Magnetic blow-off forces arise from concentration of current in the contact interface and tend to blow the contacts apart, causing separation and arcing. Simple models have been developed to predict the magnitude of these forces and permit the design of joints and contacts that can successfully resist the forces. In this paper, the role of magnetic blow-off in railgun armature contacts is explored. It is shown that magnetic blow-off forces are important and may be the final step in a series of events that ultimately leads to transition. Models that predict the conditions under which blow-off will occur are developed, and supporting experimental data is described.
Research on coupling process and technology of lensed fiber and optical chip

As a key link in the practical application of optical modules, the packaging technology of optoelectronic devices plays a crucial role in the performance of products. Among them, the optical coupling technology is an important link in the packaging design process, and the lensed fiber coupling method still occupies a large proportion in the packaging technology due to its simple structure and low cost. In this paper, by adjusting the parameters of the taper angle and curvature radius of the lensed fiber, a simulation model of the optical coupling between the lensed fiber and commercial lasers is established, and the optical coupling efficiency and optical tolerance of the lensed fiber under different horizontal coupling distances and angular offsets are analyzed in detail. In addition, the coupling performance of the lensed fiber with two different manufacturing processes, the ground- cone lensed fiber (GCLF) and the fused-cone lensed fiber (FCLF), was compared and analyzed. According to the comparative analysis results, under the optimal parameters, the maximum coupling efficiency of GCLF reaches 89.35%, and the maximum coupling efficiency of FCLF reaches 85.59%. By adjusting the alignment angle of the laser light source in the horizontal and vertical directions, the 3db alignment tolerances of GCLF in two directions are 2. 17μm and 2. 05μm, respectively, and the 3db alignment tolerances of FCLF in two directions are 2. 08μm and 1. 96μm, respectively. From this, it can be seen that GCLF has higher coupling performance than FCLF, and a higher alignment tolerance during the package alignment process.
Data-rate dependence of suppression of reflection-induced intensity noise in Fabry-Perot semiconductor lasers

We demonstrate experimentally that intensity noise caused by optical feedback to a Fabry-Perot semiconductor laser can be suppressed by digital modulation, and that this suppression is bit-rate dependent. We use a multimode rate equation model of the laser to explain the mechanism for the bit-rate dependence of the suppression. We conclude that, if the delay time of the reflected light is much greater than the modulation bit period, the intensity noise is suppressed. >
High-power single mode (>1W) continuous wave operation of longitudinal photonic band crystal lasers with a narrow vertical beam divergence

We report on 980nm InGaAs∕AlGaAs lasers with a broad waveguide based on a longitudinal photonic band crystal concept. The beam divergence measured as full width at half maximum was as narrow as 15W pulsed operation as limited by the current source. Significantly increased modal spot size enabled stable single lateral mode operation in broad ridge 10μm stripes. Maximum continuous wave power in single mode regime of 1.3W for 10μm wide stripe lasers was obtained, being limited by the catastrophic degradation of the unpassivated laser facets.
Microplane Model for Brittle-Plastic Material: I. Theory

A generalized microplane model for brittle-plastic heterogeneous materials such as concrete, which describes not only tensile cracking but also nonlinear triaxial response in compression and shear, is presented. The constitutive properties are characterized separately on planes of various orientations within the material, called the microplanes, on which there are only few stress and strain components and no tensorial, requirements need to be observed. These requirements are satisfied automatically by integration over all spatial directions. The state of each microplane is characterized by normal deviatoric and volumetric strains and shear strain, which makes it possible to match any Poisson ratio. The microplane strains are assumed to be the resolved components of the macroscopic strain tensor. The central assumption is that on the microplane level the stress-strain diagrams for monotonic loading are path-independent and that all the path dependence on the macrolevel is due to unloading, which happens selectively on microplanes of some orientations. The response on the microplane is assumed to depend on the lateral normal strain which does no work. in consequence, the incremental elastic moduli tensor is nonsymmetric, which is necessary to model friction and dilatancy. This tensor is also generally anistropic and fully populated (i.e., none of its elements can be prescribed as zero). The model involves many fewer free material parameters than the existing comprehensive macroscopic phenomenologic constitutive models for concrete.
Ambient-Measurement-Based Equivalent Inertia Constant Identification Via Tikhonov Regularization Algorithm

The optimal operation of a power system with high penetrations of renewable energy sources requires an effective tool to monitor the inertia level of the power system. With this goal, the paper proposes an ambient measurement-based equivalent inertia constant identification method for both synchronous and non-synchronous inertia providers via Tikhonov regularization algorithm basing on the existing techniques. A modified WSCC 9-bus system serves to validate the accuracy and the robustness of the proposed method against the measurement noise.
Machine Learning Approach to Predict Building Thermal Load Considering Feature Variable Dimensions: An Office Building Case Study

An accurate and fast building load prediction model is critically important for guiding building energy system design, optimizing operational parameters, and balancing a power grid between energy supply and demand. A physics-based simulation tool is traditionally used to provide the building load demand; however, it is constrained by its complex model development process and requirement for engineering judgments. Machine learning algorithms (i.e., data-driven models) based on big data can bridge this gap. In this study, we used the massive energy data generated by a physics-based tool (EnergyPlus) to develop three data-driven models (i.e., LightGBM, random forest (RF), and long-short term memory (LSTM)) and compared their prediction performances. The physics-based models were developed using office prototype building models as baselines, and ranges were provided for selected key input parameters. Three different input feature dimensions (i.e., six-, nine-, and fifteen-input feature selections) were investigated, aiming to meet different demands for practical applications. We found that LightGBM significantly outperforms the RF and LSTM algorithms, not only with respect to prediction accuracy but also in regard to computation cost. The best prediction results show that the coefficient of variation of the root mean squared error (CVRMSE), squared correction coefficient (R2), and computation time are 5.25%, 0.9959, and 7.0 s for LightGBM, respectively, evidently better than the values for the algorithms based on RF (18.54%, 0.9482, and 44.6 s) and LSTM (22.06%, 0.9267, and 758.8 s). The findings demonstrate that a data-driven model is able to avoid the process of establishing a complicated physics-based model for predicting a building’s thermal load, with similar accuracy to that of a physics-based simulation tool.
A variable time-step IMEX-BDF2 SAV scheme and its sharp error estimate for the Navier-Stokes equations

We generalize the implicit-explicit (IMEX) second-order backward difference (BDF2) scalar auxil- iary variable (SAV) scheme for Navier-Stokes equation with periodic boundary conditions [11, Huang and Shen, SIAM J. Numer. Anal. , 2021] to a variable time-step IMEX-BDF2 SAV scheme, and carry out a rigorous stability and convergence analysis. The key ingredients of our analysis are a new modified discrete Grönwall inequality, exploration of the discrete orthogonal convolution (DOC) kernels, and the unconditional stability of the proposed scheme. We derive global and local optimal H 1 error estimates in 2D and 3D, respectively. Our analysis provides a theoretical support for solv- ing Navier-Stokes equations using variable time-step IMEX-BDF2 SAV schemes. We also design an adaptive time-stepping strategy, and provide ample numerical examples to confirm the effectiveness and eﬀiciency of our proposed methods.
Local sourcing embeddedness, manufacturing relocation, and firm attitudes toward the US-China trade war: A survey analysis of China-based MNC subsidiaries

Abstract This paper examines the attitudes of multinational corporations (MNCs) toward the U.S.-China trade war through an original survey of China-based MNC subsidiaries in the manufacturing industry. Our argument is in two parts. First, firms that have relocated production outside of China or are considering such moves should be less likely to oppose the trade war as they possess outside options that reduce their vulnerability to trade restrictions. Second, firms’ tendency toward production relocation can in turn be explained by their local sourcing dependence, as measured by the level of such dependence and the degree to which their operations require supplier certification. This is because firms more heavily embedded in local supplier networks face stronger resource dependence that increases organizational inertia, reducing their ability to switch to alternative suppliers and therefore relocating production to other destinations. Our findings corroborate our hypotheses, highlighting how the heterogeneity in MNCs’ supply chain relationships may influence both their manufacturing relocation decisions and trade policy preferences.
Gate length scaling beyond Si: Mono-layer 2D Channel FETs Robust to Short Channel Effects

We explore 2D channel FET scaling down to Source-to-Drain contact spacing (LS-D) of 25 nm, comparable to state-of-the-art Si technology. Single gated devices show an uptick in subthreshold slope (SS) when scaling below $\mathrm{L}_{S-D}\,=34\mathrm{nm}$. Double gate devices, fabricated by use of a thin high-k bilayer ALD process optimized for 2D material surfaces, enhance electrostatics to achieve steep SS sat of 75 mV/dec and low DIBL of 12 mV/V for long LS-D devices. Nearly zero hysteresis and preliminary BTI studies show gate oxide health is promising, but improvements are needed to match Si. TCAD simulations fitted to the experimental data confirm 2D channel transistors as suitable candidates for the replacement of Si to enable a long future of Moore's Law scaling.