Miracle-dz/UniFAR-FTUs huggingface dataset:
A robust topology optimization for enlarging working bandwidth of acoustic devices

We propose a novel robust topology optimization for designing acoustic devices that are effective for broadband sound waves. Here, we define the objective function as the weighted sum of the acoustic response to an incident wave consisting of a single frequency and its standard deviation (SD) against the frequency perturbation. By approximating the SD, under the assumption that the incident frequency follows the normal distribution, with the high‐order Taylor expansion of the (conventional) objective function, we deal with significant frequency variations. To calculate such an approximation, we need to calculate the high‐order frequency derivatives of the state variable. Here, we define them by integral representations, which enables us to characterize them even when the state variable is defined in an unbounded domain as is often the case with wave scattering problems. We further show that, based on this definition, the high‐order derivatives can efficiently be computed by a combination of the boundary element method and automatic differentiation. We also present a derivation and calculation of the topological derivative for the newly defined objective function. We install all the proposed techniques into a topology optimization method based on the level‐set method to design wideband acoustic devices. The validity and effectiveness of the proposed topology optimization are confirmed through several numerical examples.
Cadence-Insensitive Soft Exoskeleton Design With Adaptive Gait State Detection and Iterative Force Control

Soft exoskeletons have demonstrated the potential to save energy, but their efficiency is sensitive to variations in human gait cadence. This work aims to develop adaptive gait state detection and iterative force control methods for a soft exoskeleton to reduce human walking metabolic cost consistently, while the user may change walking cadence. The proposed approach is motivated by the rhythmicity of gait and applies an iterative learning concept to enhance the exoskeleton’s adaptability to varying walking conditions. The gait state detection method proposed for the designed exoskeleton combines two feature extraction algorithms, which can learn from the present and past body kinematic data, to provide accurate user gait state detection. Based on the state, the proposed force control method iteratively adjusts the commands to keep track of the desired profile. Experiments have been conducted on healthy subjects walking with varying cadence using the soft exoskeleton. Promising results were presented in separate validation tests. Moreover, metabolic costs of subjects walking under one unpowered and two powered conditions, where the assistance profiles were produced by classical methods and the proposed methods, showed that the proposed methods can effectively improve the exoskeleton’s ability to save human energy of walking with varying cadence. Note to Practitioners—Lower limb exoskeletons have demonstrated the potential to save human energy in medical and industrial applications. The main purpose of this work is to solve the exoskeleton assistance efficiency loss problem for users walking with changing cadence. Constant cadence is unlikely maintained during natural human walking. Few existing exoskeletons could retain high efficiency under user cadence changes, limited by their control system capability. This work presents a new cable-driven cadence-insensitive soft exoskeleton, which is purposely designed with two adaptive methods to enable the device to offer consistent benefit to users walking with varying cadence. The proposed methods are inspired by the rhythmicity of human gait and can be iteratively reconfigured to perform accurate human gait state detection and assistive force tracking. The proposed methods have the potential to be integrated into other human-oriented robots to improve their adaptability. This work can greatly enhance the possibility of using the walking assist robotic devices in more practical applications.
Driving Public Investments in Construction Sector for Economic Growth in Nigeria: A Synthesis of Wagnerian and Keynesian Hypotheses

This study investigated the relationship between public investments in construction sector and economic growth in Nigeria. The study deployed econometric statistics to examine the existence of Wagner's Law and Keynesian Theory in Nigeria using published economic and construction sector data. It found that federal government capital expenditure influences economic growth negatively (t=-2.837, p(0.0084) I(0)=3.10 and I(1)=3.87); ECM(-1)=-0.196, p=0.000<0.05)); but for corruption, misapplication and diversion of capital project budgets. Although, this study partly confirmed the existence of Keynesian Theory, it cannot conclusively establish that construction investments stimulate economic growth in Nigeria. This signified that Nigerian economic models are defective and/or ineffective in transforming the huge capital spending on construction sector to economic growth, thereby making investment in construction sector an irrelevant strategy for economic policy formulation. It then placed the burden of economic rejuvenation through investments in construction sector on economic policy and decision makers in Nigeria. It recommended for diligence in budgeting and implementation of capital projects as the only way the capital expenditure can contribute to a meaningful economic growth.
Ultra-Dense Wavelength-Division Multiplexing With Microring Modulator

Silicon photonics can be used to increase the versatility of wavelength division multiplexing (WDM). Ultra-dense wavelength division multiplexing (uDWDM) shrinks channel spacing between WDM channels to decrease guard bands and increase spectral efficiency. Microring modulators (MRMs) provide a simple solution for uDWDM transmitters - they require no multiplexer/demultiplexer. When used with comb lasers, MRMs provide extremely compact and low power solutions. The spectral efficiency is limited by interchannel interference (ICI) from incomplete isolation of channels. We report an MRM-uDWDM transmitter achieving channel spacing comparable to the symbol rate in each WDM channel, reaching a spectrum occupation of 80%. By choosing the correct operating point, we demonstrate experimentally our fabricated MRM chip design causes no discernable ICI power penalty. To the best of our knowledge, this is the first demonstration of MRM-uDWDM to support such dense channel spacing.
On the Performance of Secure Underlay Cognitive Radio Networks With Energy Harvesting and Dual-Antenna Selection

In this letter, we consider a secure underlay cognitive radio network consisting of a secondary source-destination pair and a primary transmitter-receiver pair in the presence of a primary passive eavesdropper. Herein, a secondary multi-antenna full-duplex destination node acts as a jammer to the primary eavesdropper in an effort to improve the physical layer security of the primary network. In return for this favor, the energy constrained secondary source gets access to the primary network to transmit its own information so long as the interference to the latter is below a certain level. In light of the aforementioned, we evaluate the system performance in terms of the outage probability for the secondary network, the secrecy outage probability, and the probability of non-zero secrecy capacity for the primary network. Numerical results are provided to verify the correctness of the proposed analytical framework.
A GPU implementation of least-squares reverse time migration

Least-squares reverse time migration (LSRTM) is a seismic imaging method that can provide higher-resolution image of the subsurface structures compared to other methods. However, LSRTM is computationally expensive. To reduce the computational time of LSRTM, GPU can be utilized. This leads to the objective of this work which is to develop a GPU implementation of LSRTM. In this work, the two-dimensional first-order acoustic wave equations are solved using the second-order finite difference on a staggered grid and a perfectly matched layer is used as an absorbing boundary condition. The adjoint-state method is used to compute the gradient of the objective function. A linear conjugate gradient method is used to minimize the objective function. Both forward- and backward-propagation of wavefields using the finite-difference method are performed on a single GPU using the NVIDIA CUDA library. For a verification purpose, the GPU program of LSRTM was applied to a synthetic data set generated from the Marmousi model. Numerical results show that LSRTM can provide an image with a higher resolution of subsurface structure compared to a conventional RTM image. For a computational cost issue, the GPU-version of LSRTM is significantly faster than the serial CPU-version of LSRTM.
Oxidative stress profiling in repeat breeder Surti buffalo

Repeat breeding is very important infertility problem in Surti buffaloes caused by various factors which causes low milk production and reduced number of calves per animal leading to economic losses at farmer and industry levels. This study was conducted to study the oxidative stress which is an important factor of repeat breeding in Surti buffalo. The blood samples were collected at Livestock Research Station, NAU, Navsari, Gujarat and analyzed for glucose, BUN, Mg2+, Na+, K+, Ca2+ and Cl- in the control and repeat breeder Surti buffalo. These samples were analyzed for various parameters of oxidant/antioxidant status in repeat breeder buffalo. The level of malondialdehyde was significantly increased (p
A Comprehensive Study of Coke Deposits on a Pt-Sn/SBA-16 Catalyst during the Dehydrogenation of Propane

Catalytic propane dehydrogenation is an attractive method to produce propylene while avoiding the issues of its traditional synthesis via naphtha steam cracking of naphtha. In this contribution, a series of Pt-Sn/SBA-16 catalysts were synthesized and evaluated for this purpose. Bimetallic Pt-Sn catalysts were more active than catalysts containing only Pt. The catalyst with the best performance was assessed at different reaction times of 0, 60, 180, and 300 min. The evolution of coke deposits was also studied. Thermogravimetric analysis demonstrated the presence of two types of coke on the catalyst surface at low and high temperature, respectively. Raman results showed an increased coke’s crystal size from 60 to 180 min on stream, and from 180 to 300 min under reaction, Raman suggested a reduction in the crystal size of coke. Also transmission electron microscopy confirmed a more evident agglomeration of metallic particles with reaction times higher than 180 min. These results are consistent with the phenomena called “coke migration” and the cause is often explained by coke movement near the particle to the support; it can also be explained due to sintering of the metallic particle, which we propose as a more suitable explanation.
Principals’ time allocation in the context of Shanghai school administration

ABSTRACT Time allocation is a complex problem for school principals in many countries. This study examines the restrictive structure of principals’ time allocation for each task domain, as well as the explanatory structure of school administration context for their time allocation. Structural equation models were developed based on data gathered in Shanghai, China using the 2013 Teaching and Learning International Survey (TALIS). The results of the restrictive structure indicate that the administrative and leadership tasks are in the moderating position of principals’ time allocation structure. Meanwhile, principals’ interactions with students underlie their interactions with parents and community members. The outcomes of the explanatory structure signal that school administration context (in terms of principals’ work duties, power distribution and work challenges) affects their time allocation in relation to the task domains. This study illustrates the importance of school administration structure in Shanghai principals’ time allocation, characterized by a high power distance between principals and teachers.
Ship Building Construction Systems

The need for sea transportation, which includes ships, is increasing – driven by the growing competition in the economic, social, political, and defense and security sectors. This, in turn, is driving advances in ship construction techniques in Indonesia. In building a ship, several factors must be considered. In addition to planning the shape and characteristics of the hull, as well as planning the strength and arrangement of the ship itself. Ship construction in general consists of two main parts, namely the hull and the building on the ship or deck house. Keywords: Transportation, Construction System, Ship
A Novel Energy Management Strategy Based on Dual Reward Function Q-learning for Fuel Cell Hybrid Electric Vehicle

A reasonably designed energy management strategy (EMS) can guarantee the safe and stable operation of fuel cell hybrid electric vehicle (FCHEV). To optimize the energy conversion efficiency of FCHEV, this research proposes a three-level efficiency optimized EMS based on the dual reward functions Q-learning algorithm. Focused on the system overall efficiency, a hardware-in-the-loop experimental platform was built first to compare the effectiveness between the proposed EMS and other existed methods. The results shown that compared with other state-of-art methods, the proposed strategy can effectively improve the energy efficiency of the system, and can slow down the aging of the fuel cell by reducing its operating stress. To further verify the effectiveness of the proposed strategy, varying driving loads profile were tested based on a 1.2-kW hybrid electric vehicle developed in the laboratory. The FCHEV real-time experiment results indicated that the proposed EMS can achieve the average load power matching error of 0.19 W and can optimize the system average overall system efficiency to 52%. The proposed method can help to contribute to the massive commercialization and implementation of the FCHEV.
A rapid method for the direct determination of copper and iron in butter by GFAAS

A rapid method for the direct determination of copper and iron in butter by GFAAS was developed. Butter was dissolved in a BuNH 2 / water / THF mixture in the ratio of 7.5% for copper and 2% for iron. The solution (10 μL) was pipetted directly into the graphite tube. Two thermic programs were developed: for copper char-ashing at 900°C, atomization at 2450°C and for iron, including deposition and drying of the chemical modifiers (Mg(NO 3 ) 2 + NH 4 NO 3 0.1%, charashing at 1000°C and atomization at 2400°C. The calibrations were compared with the matrix-matched standard and standard addition calibration. The accuracy was proved by comparison with the mineralization method. The direct determination against aqueous standards is possible with a characteristic mass of 6.5 pg/0.0044 A.s for copper and of 5.5 pg/0.0044 A.s for iron.
PURCHASE BEHAVIOR : ONLINE TOUR PACKAGE

The purpose of this study was to analyze a model of online tour package purchasing behavior which is influenced by the perceptual aspects of review ratings, perceived risk, trust and purchase intention. The research design used a combination of exploratory, descriptive-quantitative research. The population and sample selection uses consumers in West Jakarta who will purchase tour packages online. Determining the number of samples using purposive sampling technique and will be distributed to 203 consumers. These findings prove that the rating review positive effect on trust and perceptions of risk. Perceptions of risk have a negative effect on trust and purchase intention. Trust has a positive effect on purchase intention. This is an important consideration for business actors in making future marketing strategy decisions to achieve competitive advantage.
Prevalence of Acute Kidney Injury in Pediatric Patients with Congenital Heart Disease Following Open Heart Surgery

Background: Acute kidney injury (AKI) occurs in approximately 40% of children undergoing cardiac surgery and is a risk factor for morbidity and mortality. Such injury leads to several complications, including fluid and electrolyte disturbances. Objective: To determine prevalence of acute kidney injury in pediatric patients with congenital heart disease following open heart surgery. Patients and Methods: We conducted a case control study on 20 patients with congenital heart disease (10 males and 10 females) with mean age of 3.39 ± 1.17 years old, and a range from 1 to 5 years old. They were recruited from Pediatric Cardiothoracic Unit, Zagazig University Hospital and 20 sex and age matched healthy children worked as control group. Results: The mean age of our patients was 3.39 ± 1.17 years old with a range from 1 to 5 years. 50% were males and 50 % were females with no statistically significant difference between both groups regarding age and sex. about 1/3 of the studied group had ASD (30 %), while 1/4 of them had Fallot tetralogy (25 %), and only 15% of them had VSD, subaortic membrane and PM + VSD. The mean serum creatinine level was 0.8 ± 0.15mg/dl, with a range from 0.22 - 0.9 mg/dl. 70% of the patients had no acute kidney injury, 15% developed AKI stage 1 and 15% developed stage 2 AKI. In addition, all patients with AKI needed dialysis. Conclusion: Present study identified that high percentage of pediatric patients with congenital heart disease following open-heart surgery developed acute kidney injury.
Design Method of Multisine Signal for Broadband Impedance Measurement

With the increasing penetration of renewable energy, it is important to analyze the impedance characteristic of renewable energy grid-connected system (REGS) to implement the stability analysis of the grid connection operation. In order to further improve the accuracy of the broadband impedance measurement, this article proposes a design method for the multisine signal considering both the signal-to-noise ratios (SNRs) of the perturbation signal and the response signal in the impedance measurement. By quantitatively analyzing the mathematical relationship between the SNRs and the measurement error, the principle to select the minimum SNR requirement of the perturbation and response signal can be obtained so as to guide the amplitude design of the perturbation signal, which can further improve the broadband impedance measurement accuracy. The multisine signal is adopted in this article to realize the proposed design method. In the application of the multisine signal, in order to limit the peak value of the multisine signal to avoid overmodulation, an improved phase design method for the multisine signal based on crest factor reduction algorithm is proposed. Finally, experiments based on the Typhoon control-hardware-in-loop (CHIL) platform are carried out to verify the effectiveness of the proposed design method for the multisine signal in the impedance measurement.
DeepFogSim: A Toolbox for Execution and Performance Evaluation of the Inference Phase of Conditional Deep Neural Networks with Early Exits Atop Distributed Fog Platforms

The recent introduction of the so-called Conditional Neural Networks (CDNNs) with multiple early exits, executed atop virtualized multi-tier Fog platforms, makes feasible the real-time and energy-efficient execution of analytics required by future Internet applications. However, until now, toolkits for the evaluation of energy-vs.-delay performance of the inference phase of CDNNs executed on such platforms, have not been available. Motivated by these considerations, in this contribution, we present DeepFogSim. It is a MATLAB-supported software toolbox aiming at testing the performance of virtualized technological platforms for the real-time distributed execution of the inference phase of CDNNs with early exits under IoT realms. The main peculiar features of the proposed DeepFogSim toolbox are that: (i) it allows the joint dynamic energy-aware optimization of the Fog-hosted computing-networking resources under hard constraints on the tolerated inference delays; (ii) it allows the repeatable and customizable simulation of the resulting energy-delay performance of the overall Fog execution platform; (iii) it allows the dynamic tracking of the performed resource allocation under time-varying operating conditions and/or failure events; and (iv) it is equipped with a user-friendly Graphic User Interface (GUI) that supports a number of graphic formats for data rendering. Some numerical results give evidence for about the actual capabilities of the proposed DeepFogSim toolbox.
Robust optimization of a deep drawing process

An attempt to define a robust optimization of a deep drawing process is presented in this article, based on window of plastic deformability in the area of main deformations, which is closed between the borders of damage, corresponding to necking, fracture and wrinkling. In the previous investigations of the author, this window has been determined using Finite Element – based computer simulations for technological process of deep drawing of a cylindrical cup. The influence of the stochastic character of the control variables on the quality of the output is examined. An objective function for investigating the robustness of the process, based on the quality of the detail, using numerical simulations, is suggested. The results of the model calibration and optimization run are interpreted. The flexibility of the suggested approach, potential ways to extend it and performance issues are discussed.
DETERMINING THE TECHNOLOGICAL AND PEDAGOGICAL CONTENT KNOWLEDGE LEVEL OF THE 4TH GRADE TEACHERS ON THE UNIT; ELECTRIC IN OUR LIFE*

The aim of this stud is to determine the level of the technological and pedagogical context knowledge of the fourth grade teachers in a specific unit entitled “Electiricty in Our Life”. Total of 53 teachers from the three cities contributed to this study. In order to obtain more detailed information about teachers’ TPACK levels, a mixed research method with combination of both quantitative and qualitative data collection tools was employed. For data collection, four different data collection tools were used: Questionnaire of Nature of Science, Conceptual Test related to electricity, vignette and content representations. In addition, percentages, frequencies were calculated and Pearson’s correlation analysis technique was used. The results revealed that elementary teachers did not have sufficient knowledge about the content knowledge. Moreover, insufficient knowledge was also observed in teachers’ pedagogical knowledge, learning difficulties, assesments, and learning environment, which are the components of pedagogical content knowledge. Also, according to the results, teachers had limited knowledge in overall technology knowledge and subject-related technology knowledge.