Miracle-dz/UniFAR-FTUs huggingface dataset:
Damage Assessment of a Building Subjected to a Terrorist Attack

An increasing threat of global terrorism has led to concerns about bombings of buildings, which could cause minor to severe structural damage. After such an event, it is important to rapidly assess the damage to the building to ensure safe and efficient emergency response. Current methods of visual inspection and non-destructive testing are expensive, subjective, and time consuming for emergency responders' usage immediately after an attack. On the other hand, vibration-based damage detection methods with wireless smart sensors could provide rapid assessment of structural characteristics with low cost. For blast analysis, structural response is usually determined using a simplified SDOF version of the undamaged structure, such as used in a Pressure-Impulse (P-I) Diagram, or using more complex FEM (finite element method) models. However, the simplified models cannot take into account damage caused by blast focus at a specific location or on a specific element, which may induce local failure leading to potential progressive collapse, and the more complex FEM models take too long to derive applicable results to be effective for a rapid structural assessment. In this paper, a new method to incorporate vibration-based damage detection methods to calculate the multi degree of freedom structural stiffness for determining structural condition is provided to create a framework for the rapid structural condition assessment of buildings after a terrorist attack. The stiffness parameters are generated from the modal analysis of the measured vibration on the building, which are then used in a numerical simulation to determine its structural response from the blast. The calculated structural response is then compared to limit conditions that have been developed from ASCE blast design codes to determine the damage assessment. A laboratory-scale building frame has been employed to validate the developed use of experimentally determined stiffness by comparing the P-I diagram using the experimental stiffness with that from numerical models. The reasonable match between the P-I diagrams from the numerical models and the experiments shows the positive potential of the method. The framework and examples of how to develop a rapid condition assessment are presented.
Tourism risk impact on the destination image of Batangas province

Over the past decades, traveling is discretionary spending of an individual or business. Consumers avoid traveling to risky tourism destination and prefer destinations with lowered perceived risks. Tourism risks express of the crises taking many shape and forms in the industry significantly affecting the destination image. The principal aim of the paper was to assess the tourism risk impact on the destination image of the Province of Batangas. Specifically, demographic profile, impact of tourist destination in terms of tourism demand, supply business and destination and policy makers, destination image in terms of man-made, natural disasters, tourist benefits, feeling experience and destination image. A questionnaire was used to collect data from the 437 tourists from top 10 tourist destinations in Batangas Province. Descriptive method was utilized to illustrate the significant relationship between the profile of the respondents and their tourist risk impact on tourist destination. Base on the results, there is high risk impact to tourist destination specifically on destination and policy makers and less impact on the tourism demand, tourism supply businesses. On the other hand, there is also tourist risk impact on the destination image in all given variables such as tourist benefits, destination image, man-made, feeling experience and natural disasters. The result of the study accentuates that tourist destination image can be enhance under the influences of external factors such as increasing awareness of the destination and improving the perception and existing associations in the minds of tourist.
Controlling Factors of Seasonal Variation of Stem Methane Emissions From Alnus japonica in a Riparian Wetland of a Temperate Forest

Tree‐mediated methane (CH4) emissions represent an uncertain pathway of the total CH4 flux released from forested ecosystems. We measured the stem CH4 fluxes from Alnus japonica in a riparian wetland of a temperate forest for a year from 2017 to 2018, using automated chambers. The stem CH4 fluxes varied seasonally, showing summertime maxima and wintertime minima. Medians of stem CH4 fluxes were 12.9, 0.5, 0.4, and 13.4 nmol m−2 s−1 during autumn, winter, spring, and summer, respectively. Dissolved CH4 concentration in groundwater beneath the trees was the major controlling factor of the stem CH4 fluxes. Temporal variations in soil environmental conditions (temperature and groundwater level) controlled dissolved CH4 concentrations in groundwater, and accordingly, stem CH4 fluxes. In addition, stem CH4 emissions were observed when the sap flux diminished during the defoliation period. These results indicate that CH4 in the rhizosphere is mainly transported in the gaseous form through intercellular space in trees. Intense rainfall occasionally caused a transient increase in the stem CH4 emissions, which was attributed to the temporal changes in the groundwater flow paths by rainfall affecting the belowground CH4 concentrations. Our findings highlight the need for continuous stem CH4 flux measurements for improved understanding of the controlling factors and future response of CH4 dynamics in forests, with regards to climate change.
Modeling of linewidth measurement in SEMs using advanced Monte Carlo software

Accurate measurement of linewidth is a critical problem in sub-100 nm semiconductor manufacturing, where required accuracy is in the range of 1 nm and below. CD-SEMs are usually used for such measurements. A cross-correlation of CD-SEMs, while demonstrating a good relative trend, is often subject to a significant absolute linewidth error, as well as the parameters of the SEM settings being used. There is no proven algorithm for edge detection in CD-SEMs. Tool manufacturers set up the edge detection voluntarily, as a rule, which is why the absolute errors in measurement occur. In this paper, we demonstrate that edge detection depends greatly on parameters of SEM settings, like beam diameter, and pattern properties, like the wall angle of a pattern. When both the signal and pattern are known, an offset for a specific SEM algorithm can be found. An algorithm for automatic edge detection in CDSEMs can be tuned for beam parameters and the type of pattern. A SEM signal was simulated using the advanced Monte Carlo software CHARIOT, which is commercially available. Input data for the modeling was 3D microstructures and e-beam parameters. A simulated signal was then compared to a known pattern. Such a comparison allowed us to define the edge position and calibrate a SEM so that any system- and pattern-dependent errors could be removed.
A comparative study of the operations strategies of globally- and domestically-oriented New Zealand manufacturing firms

There has been much written on why and how firms become involved in entering international markets. There is less material on the production/operations actions taken by such firms. This paper investigates the differences in competitive capabilities and manufacturing performance improvement plans between globally-oriented and domestically-oriented firms. It uses data collected from 140 New Zealand manufacturing companies. The results indicate that both groups emphasize the same competitive capabilities, but the globally-oriented group is placing more emphasis on some action plans involving quality assurance, improving existing processes and design for manufacture. Their most favoured action plans are similar to those of firms in most advanced manufacturing countries which participate in the Manufacturing Futures Project.
A magnet-induced buckled-beam piezoelectric generator for wideband vibration-based energy harvesting

This article presents a magnet-induced buckled-beam piezoelectric generator developed for broadband vibration-based energy harvesting at low frequencies (<60 Hz) and small excitations (<0.5g). The harvester is made of a clamped–clamped piezoelectric beam, with one end movable and subjected to a magnet-induced compressive force. Due to the magnetic force, the beam becomes buckled and bistable. The harvester works as a double-well potential oscillator under excitations, where large-amplitude inter-well oscillation is produced to enhance the energy harvesting functionality. Numerical simulations show that the proposed harvester exhibits strong nonlinearities under harmonic excitations, including snap-through motions, large-amplitude voltage outputs, and broad frequency bandwidth. A prototype harvester is fabricated and experimentally investigated to confirm the findings from numerical simulations. It is observed that for a small base excitation of 0.35g, the harvester can produce a broad frequency bandwidth of 25.0 Hz (24.0–49.0 Hz) to constantly trigger inter-well snap-through motions and to maintain a peak-to-peak voltage of >10 V over a 1.3 MΩ load resistor. For a relatively larger base excitation of 0.5g, such a frequency bandwidth can be further widened to 29.5 Hz.
Analysis and Optimization of a Hydraulic-Feedback Proportional Throttlecartridge Valve

In this work, one kind of proportional throttle cartridge valve which is based on hydraulic-feedback principle is studied comprehensively. A detailed precise mathematical model is built. Analysis of the model shows that the model varies greatly depending on the operating point chosen for the linearization. The influences of design parameters are studied through root locus method and several parameters are picked out which have great impact on the dynamic performance. Then an optimization based on iterative eigenvalue configuration is implemented. After the optimization, the performance of the valve is improved effectively.
New Factors for Capital Cost Estimation in Evolving Process Designs

Capital cost assessment is an integral part of an evolving process design. The assessment should consider installed equipment costs inclusive of plant bulk items and not solely purchased equipment costs. The ratio of installed equipment cost to purchased equipment cost varies much more widely for individual equipment items than for entire plants; the ratio depends on equipment class, design, size and construction materials as well as plant layout. The factored (IChemE) method outlined in the Institution of Chemical Engineers ’blue booklet’ is of immediate use and provides a basis for checking detailed estimates. Some experience in the application of the IChemE method by the authors is reviewed. Recommendations are made for broadening the inputs for estimating, and some factors are proposed for estimating installed costs of equipment of different classes. Quantitative data are also presented for cost breakdown in entire plants arising from project reviews by the authors.
Automatic Database Segmentation using Hybrid Spectrum -Visual Approach

: Nowadays automated segmentation of speech signals has been attracted many of the researchers all-over the world. Many speech processing systems require segmentation of speech waveform into principal acoustic units. In this research, TIMIT DataBase (DB) is utilized to carry on this process and justify its operation or results. Thus, this paper presents a novel method of segmentation of speech phonemes, where the proposed strategy helps in the selection of appropriate feature extraction technique for speech segmentation. There are three main techniques of feature extraction used in our research; the first technique is the Mel Frequency Cepstral Coefficient (MFCC), the second technique is known by Best Tree Encoding (BTE), while the third is Image Normalized Encoder (INE), which is a hybrid technique between the Best Tree Image (BTI), and the Convolution Neural Network (CNN) ResNet-50. Then, data are trained using a hybrid model that consists of Hidden Markov Model (HMM), and Gaussian Mixture Model (GMM) to improve the performance of automatic speech recognition. The proposed model is tested and verified against the most widely used feature MFCC plus delta and delta-delta coefficients (39 parameters) to evaluate its performance. This approach has the potential to be used in applications such as automatic speech recognition and automatic language identification. The experimental results show that BTE technique achieved the highest success rate ( 𝜂𝜂 ) (92.64%) than using the INE technique. However, the INE technique gives confusion success rate for Transition (Tr) and Non-Transition (NTr) of values 97.1% and 99.1%, respectively.
A complete design flow for silicon photonics

Broad adoption of silicon photonics technology for photonic integrated circuits requires standardized design flows that are similar to what is available for analog and mixed signal electrical circuit design. We have developed a design flow that combines mature electronic design automation (EDA) software with optical simulation software. An essential component of any design flow, whether electrical or photonic, is the ability to accurately simulate largescale circuits. This is particularly important when the behavior of the circuit is not trivially related to the individual component performance. While this is clearly the case for electronic circuits consisting of hundreds to billions of transistors, it is already becoming important in photonic circuits such as WDM transmitters, where signal cross talk needs to be considered, as well as optical cross-connect switches. In addition, optical routing to connect different components requires the introduction of additional waveguide sections, waveguide bends, and waveguide crossings, which affect the overall circuit performance. Manufacturing variability can also have dramatic circuit-level consequences that need to be simulated. Circuit simulations must rely on compact models that can accurately represent the behavior of each component, and the compact model parameters must be extracted from physical level simulation and experimental results. We show how large scale circuits can be simulated in both the time and frequency domains, including the effects of bidirectional and, where appropriate, multimode and multichannel photonic waveguides. We also show how active, passive and nonlinear individual components such as grating couplers, waveguides, splitters, filters, electro-optical modulators and detectors can be simulated using a combination of electrical and optical algorithms, and good agreement with experimental results can be obtained. We then show how parameters, with inclusion of fabrication process variations, can be extracted for use in the circuit level simulations. Ultimately, we show how a multi-channel WDM transceiver can be created, from schematic design to tapeout, using key features of EDA design flows such as schematic driven layout, design rule checking and layout versus schematic.
Prevalence and high-risk behaviors associated with non-fatal overdose among people who use illicit opioids: A systematic review and meta-analysis

ABSTRACT Background The aim of the present study was to determine the prevalence of non-fatal overdose among people who use illicit opioids (PWUIOs) and determine the demographic and behavioral characteristics associated with non-fatal overdose among this population. Methods Studies in English published before February 1, 2021, were searched for on PubMed, Scopus, Cochrane, and Web of Science to identify primary studies on the factors associated with non-fatal overdose among PWUIOs. After reviewing for study duplicates, the full-texts of selected papers were assessed for eligibility using PICOs criteria. Results After a detailed assessment of over 13,845 papers, a total of 67 studies met the eligibility criteria. The findings showed a past-year pooled prevalence rate of non-fatal overdose among PWUIOs of 26% (95% CI, 23% −29%). Greater odds of non-fatal overdose among PWUIOs was associated with (i) being younger, (ii) being female, (iii) being homeless, (iv) individuals who received money, goods, or drugs in exchange for sex, (v) individuals who had witnessed somebody else have an overdose, (vi) individuals who had used public spaces as primary injection locations, (vii) individuals who reported polydrug use, (vii) use of non-injection methamphetamine, and (viii) high injecting frequency (more than two daily drug injections). Conclusion Harm-reduction programs should consider the provision of education concerning overdose-related risk factors to the vulnerable and hard-to-reach PWUIOs.
Low-cost high-resolution time-domain reflectometry for monitoring the range of reflective points

A new OTDR technique to interrogate the range of reflective markers in an optical fiber (or an electrical cable) is presented. The technique has been developed to monitor strain in sections of a fiber over gauge lengths of several meters. Signal-to-noise analysis shows that current OTDR systems do not fully exploit the spatial resolution theoretically available. The available resolution is explored with a new OTDR technique. >
CapsNet meets ORB: A deformation‐tolerant baseline for recognizing distorted targets

Pattern recognition from two‐dimensional (2D) images is an indispensable tache in computer vision. However, one legacy hinders its progress: multifarious visual distortions (e.g., partially occluded signs, fisheye respective, affine or 3D projections) caused by spatiotemporal‐varying perturbations (e.g., shrunk, sharpening, overexposure, jitter, and motion) significantly degrade the performance of neural networks in terms of high‐level intelligent behaviors (e.g., target localization and recognition). Leveraging the growing availability of capsule network (CapsNet), we suppress the deformation effect to the final prediction by proposing a CapsNetORB framework to implement distorted target recognition. Two highlights, the customized Siamese CapsNet (S‐CapsNet) and vector‐based oriented fast and rotated brief (VB‐ORB), can cast a mutual positive stimulation: the former encodes capsule feature vectors for the later, whilst the later detects space‐scale invariant interval dimensions (instead of pixels) to bridge association between source standard images (high‐quality training images) and distorted ones (testing images). Thus, the category of one source standard image owning the most correspondences is the final predicted category. We believe that capsule vectors own higher representability and stability compared with conventional pixels/feature maps, which can be well exploited in feature learning while resisting visual distortions. Experimentally, we show that employing our pipeline for distorted target categorization can outperform state‐of‐the‐arts by delivering promising performance on CUB‐200‐2011, Stanford Dogs, Stanford Cars, and our hand‐crafted data set.
Soil Respiration and N-Mineralization Processes in the Patagonian Steppe Are More Responsive to Nutrient Than to Water Addition

Aims: Soil respiration and N-mineralization are key processes in C and N cycling of terrestrial ecosystems. Both processes are limited by soil temperature, moisture and nutrient content in arid and cold ecosystems, but how nutrient addition interacts with water addition requires further investigation. This study addresses the effects of water and N+P additions on soil respiration and mineralization rates in the Patagonian steppe.Methods: We measured soil respiration and N-mineralization throughout seasons in control, fertilized, irrigated and irrigated-fertilized plots. We also analyzed root density and soil physico-chemical properties.Results: The soil CO2 effluxes in the Patagonian steppe were controlled by soil temperature, soil water content and root density. Increases in water addition had no effects on soil respiration, except when combined with N+P addition. However, soil nutrient enrichment without water addition enhanced soil respiration during the plant growing season. We found a linear positive relationship between root density and soil respiration, without interaction with treatments. N+P addition had negative impacts on N-mineralization, resulting in a strong N-immobilization. However, soil ammonium and nitrate content increased with N+P addition all over the seasons.Conclusion: Moderate increases in the precipitation through small pulses lead to no long-term response of soil processes in arid and cold Patagonian ecosystems. However, soil CO2 effluxes are likely to increase with nutrient additions, such as anthropogenic N deposition, and microbial biomass could retain more nutrients in the soil. Therefore, high levels of N enrichment in arid ecosystems may strengthen the positive feedback between C cycle and climate change.
Fabrication and Tuning of a THz-Driven Electron Gun

We have developed a THz-driven field emission electron gun and beam characterization assembly. The two cell standing-wave gun operates in the 𝜋 mode at 110.08 GHz. It is designed to produce 360 keV electrons with 500 kW of input power supplied by a 110 GHz gyrotron. Multiple gun structures were electroformed in copper using a high precision diamond-turned mandrel. The field emission cathode is a rounded copper tip located in the first cell. The cavity resonances were mechanically tuned using azimuthal compression. This work will discuss details of the fabrication and tuning and present the results of low power measurements.
Biomechanical modelling of hip and its soft tissue

Hip fractures are largely considered a major health-care problem. Currently, bone density measurement with Dual X-ray Absorptiometry is the clinical standard protocol for diagnosis and prevention of osteoporosis. However, this exam does not enable us to identify all patients who will undergo a hip fracture (Schuit et al. 2004). Patient specific finite element models of the proximal femur allows to consider the material and the geometry in fracture risk analysis (Duchemin et al. 2007). Soft tissues covering the hip in such finite element models were not considered whereas majority of hip fractures result of a fall of the subject on the lateral side of the hip (Hayes et al. 1996). Therefore soft tissue has a predominant role in transmission of the mechanical load to the proximal femur (Robinovitch et al. 1995). However, muscle geometry was difficult obtain due to low contrast between soft tissue onmedical images. Usually, muscle volumewas assessedwith systematicmanualmuscle contouring on many axial images (Blemker and Delp 2005). The goal of this study to assess muscle volume and quality from CT-scan images in order to build a patientspecific model of the hip, including muscles and subcutaneous. Then preliminary evaluations with quasistatic lateral compression were performed on ten subjects to highlight the influence of soft tissue on the stress distribution within the proximal femur.
‘Those First Few Months Were Horrible’

Since the 1970s, international students have represented a growing proportion of the global student body, yet how they adjust and how universities can support them is relatively unexplored. We conducted a qualitative study of 36 international students of 11 nationalities studying in Norway and the UK and found that their experience did not fit the dominant ‘U-Curve’ of adaptation that suggests there is a honeymoon period on arrival. Confirmed with conversations with student wellbeing staff, who suggest that anxiety and culture shock are the norm, the data allows us to suggest factors that trigger adjustment and interventions to improve students’ experience. Our contribution is a ‘J-Curve’ model comprising cultural challenge, adjustment, and mastery, to reflect the reality of the international student experience.