Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and static performance measurement research for six-component piezoelectric balance

Wind tunnel balance is one of the most important measurement equipment in aerodynamic testing.For the characteristics of fast response,good following,simple structure and large measuring range,a new type of piezoelectric six-component balance is developed to measure the airloads of dynamic motion.According to the characteristics of piezoelectric balance,the method of static calibration and the derivation of calibration formula are studied. With the balance calibration platform,the single component calibration and combined loading experiments are accomplished.The calibration matrix and performance index are concluded in which the nonlinearity error and repeatability error are 0.06%,0.19%respectively,and the maximum crosstalk is 1.94%. An error analysis of experimental results and the uncertainty of measurement system are represented at last. The results obtained demonstrate that the piezoelectric balance can satisfy the requirements of measurement with good performance.
Modelling and validation of a continuous rotary motor combining shape memory wires and overrunning clutches

This article presents the conceptual design, modelling, prototyping and testing of a novel rotary motor featuring shape memory alloy wires and overrunning clutches. The device comprises a shape memory alloy wire wound around a low-friction cylindrical drum contrasted by a backup beam spring and fitted to the output shaft through an overrunning clutch. Electrical heating produces a contraction of the wire, hence a rotation of the drum which is transferred to the shaft. Thanks to the overrunning clutch, during the recoiling phase, the drum rotates backward while the shaft does not move. Spurious backward movements of the shaft are contrasted by a second overrunning clutch linking the shaft to the frame. This article develops a model for the quasi-static simulation of the motor and the experimental characterization of a prototype device featuring three active drums, a rotary sensor and an angular brake to apply the external load. Despite the low degree of optimization, the tested motor performs well in terms of specific stroke, specific output torque and specific output work per cycle. Winding of the wire on the drum impairs somewhat the fatigue life with respect to publish data on straight wires, a drawback which calls for further design refinements.
Site-Specific Earthquake Ground Motions for Seismic Design of Port Facilities in Indonesia

In Indonesia, infrastructure, such as port facilities, has been damaged by earthquakes. Therefore, evaluating rational earthquake ground motions (EGMs) for seismic design is necessary to mitigate earthquake disasters in the future. The EGMs in the Indonesian Seismic Code are stipulated based on the ASCE standards and not on site-specific ones. This study aims to propose site-specific EGMs for the seismic design of port facilities in Indonesia. The EGM records and ground data in Indonesia were used for analysis. The EGM incidents in the bedrock were evaluated with deconvolution analysis. The obtained EGMs were amplitude-adjusted to peak ground acceleration similar to that of the EGMs in the bedrock in the Indonesian Seismic Code. A seismic response analysis considering nonlinear soil characteristics was conducted, and 144 EGMs at port sites were obtained. Considering the variation in the obtained EGMs, we propose site-specific EGMs for the seismic design of port facilities. A comparison of the proposed EGMs with those in the design code reveals that the difference between them is significant.
A Calibrated Over-the-Air Measurement Method for Error Vector Magnitude Characterization

Error vector magnitude (EVM) is one of the key parameters to quantify the performance of a digital radio transmitter or receiver. However, the measurement method of EVM has not been formed properly, especially for those devices with integrated antenna, e.g., antenna in package (AiP). This article proposes a way for EVM test through the over-the-air (OTA) measurement method. First, the concepts of EVM and OTA measurement methods are reviewed; then, the composition of EVM in OTA measurement is analyzed; next, experiments are performed based on the proposed calibration method; finally, the measured results are gated and compared to those results based on traditional conductive measurement methods. The compared results indicate that our proposed method is technically feasible and has high accuracy for those devices with integrated antennas.
Historical impacts of mink fur farming on chironomid assemblages from shallow lakes in Nova Scotia, Canada

Abstract Campbell J, Libera N, Smol JP, Kurek J. 2022. Historical impacts of mink fur farming on chironomid assemblages from shallow lakes in Nova Scotia, Canada. Lake Reserv Manage. 38:80–94. Mink fur farms in southwestern Nova Scotia, Canada, are a suspected source of nutrients that have likely contributed to water quality issues in nearby lakes. Despite a decade of water quality monitoring, the cumulative effects of mink farming are not fully known due to a lack of information regarding baseline conditions. We used sedimentary midge remains and visible reflectance spectroscopy of sedimentary chlorophyll a (VRS Chl-a) to assess environmental changes prior to and following the establishment and growth of the local mink farming industry. Study lakes include hypereutrophic Nowlans Lake, with mink farms near its shoreline, mesotrophic Porcupine Lake with mink farms upstream, and oligotrophic Clearwater Lake (reference lake) with no mink farms in the catchment. We recorded a significant compositional shift in midge assemblages at Nowlans Lake (ANOSIM: 0.63, P < 0.001) following an increase in VRS Chl-a and the growth of the industry ca. 1970. Midge assemblage changes were indicative of a deterioration of benthic habitat and included increases in taxa associated with productive environments (i.e., Glyptotendipes, Endochironomus, and Cricotopus). Porcupine and Clearwater lakes, however, showed no significant assemblage shifts, suggesting relatively stable benthic conditions. VRS Chl-a increased around the 1950s in Porcupine Lake, whereas VRS Chl-a in Clearwater Lake increased around the 1980s. Our findings indicate that impacts from mink farming should be considered from a site-specific context. This study highlights the complexity of shallow lake responses associated with human activities related to >50 yr of mink farming.
The Reproductive Success of Triturus ivanbureschi × T. macedonicus F1 Hybrid Females (Amphibia: Salamandridae)

Simple Summary Two moderately related large-bodied newt species endemic to the Balkan Peninsula, the Balkan crested newt (Triturus ivanbureschi) and the Macedonian crested newt (T. macedonicus), coexist and hybridize in central Serbia. Many generations of mutual hybrid crossings and backcrossings with parental species shaped the genetic composition of hybrid populations. Natural populations have admixed nuclear DNA (nuDNA) of parental species and T. ivanbureschi mitochondrial DNA (mtDNA), which is usually maternally inherited. The mechanisms that direct gene flow and shape the first generations of hybrids could explain the formation of hybrid zones and their maintenance in nature. We followed and compared life history traits related to reproduction of the first generation of reciprocal hybrids obtained by experimental crossing. Our results suggested that possible incompatibilities between mitochondrial and nuclear genomes, which could lead to the exclusion of T. macedonicus mtDNA in natural populations, most likely act at later stages of development or subsequent hybrid generations. Results from this study add to the growing knowledge of Triturus hybrid biology and ecology, which is the baseline for conservation programs necessary to protect these highly endangered amphibians. Abstract Two large-bodied newt species, Triturus ivanbureschi and T. macedonicus, hybridize in nature across the Balkan Peninsula. Consequences of hybridization upon secondary contact of two species include species displacement and asymmetrical introgression of T. ivanbureschi mtDNA. We set an experimental reciprocal cross of parental species and obtained two genotypes of F1 hybrids (with T. ivanbureschi or T. macedonicus mtDNA). When hybrids attained sexual maturity, they were engaged in mutual crossings and backcrossing with parental species. We followed reproductive traits over two successive years. Our main aim was to explore the reproductive success of F1 females carrying different parental mtDNA. Additionally, we tested for differences in reproductive success within female genotypes depending on the crossing with various male genotypes (hybrids or parental species). Both female genotypes had similar oviposition periods, number of laid eggs and hatched larvae but different body and egg sizes. Overall reproductive success (percentage of egg-laying females and viability of embryos) was similar for both genotypes. The type of crossing led to some differences in reproductive success within female genotypes. The obtained results suggest that processes that led to exclusion of T. macedonicus mtDNA in natural populations may be related to the survival at postembryonic stages of F2 generation or reproductive barriers that emerged in subsequent hybrid generations.
Powered by Google: Widening Access and Tightening Corporate Control

The Internet and new media are often seen as constituting open spaces where cultural empowerment and free-flowing expressive creativity find emancipation from top-down political-economic power. However, this one-sided perspective is insufficient, if not even invalid: the democratization of art does not cease to confront structural obstacles in cyberspace, as is shown by this case-study of Google’s overt interventions into art and culture. Google is working to digitize museum collections at its own expense, and is making art work widely accessible on the Internet. We show how this widened access itself, however, functions as a Google market strategy for turning cultural production into a site of profit-making. Google is quietly reorganizing cultural spaces on a global scale, to incorporate them into its more encompassing business of information.
Semantic Risk-aware Costmaps for Robots in Industrial Applications using Deep Learning on Abstracted Safety Classes from Synthetic Data

: For collision and obstacle avoidance as well as trajectory planning, robots usually generate and use a simple 2 D costmap without any semantic information about the detected obstacles. Thus a robot’s path planning will simply adhere to an arbitrarily large safety margin around obstacles. A more optimal approach is to adjust this safety margin according to the class of an obstacle. For class prediction, an image processing convolutional neural network can be trained. One of the problems in the development and training of any neural network is the creation of a training dataset. The ﬁrst part of this work describes methods and free open source software, allowing a fast generation of annotated datasets. Our pipeline can be applied to various objects and environment settings and is extremely easy to use to anyone for synthesising training data from 3 D source data. We create a fully synthetic industrial environment dataset with 10k physically-based rendered images and annotations. Our dataset and sources are publicly available at https://github.com/LJMP/synthetic-industrial-dataset. Subsequently, we train a convolutional neural network with our dataset for costmap safety class prediction. We analyse different class combinations and show that learning the safety classes end-to-end directly with a small dataset, instead of using a class lookup table, improves the quantity and precision of the predictions.
Gain Scheduling for Sampled-data State Estimation over Lossy Networks

This paper proposes a design method for sampled-data state estimator over lossy networks. When a measurement signal loss is detected, the proposed estimator switches gains and continues to update the estimate based upon last received measurement. The gains are computed in advance by means of a common solution of linear matrix inequalities so that the estimation is suboptimal with respect to the mean square error in the steady state. The eﬀectiveness of the proposed method is illustrated/evaluated via numerical simulations.
Exploring the effect of supportive culture on employee's innovative behavior

Employee innovativeness in the workplace is one of the crucial factors that positively improve the long-term success of the organization. In this respect, this study proposed to investigate some of the antecedents of the innovative work behaviors in the Kurdistan Region of Iraq (KRG). To do this a survey questionnaire has been organized and in total 189 data have been collected from various companies in KRG to analyze the proposed model. The data have been evaluated by the SPSS software program, by regression analysis. The results revealed that training, supervisor support, and supportive culture have significant effects on employee innovative behaviors. Among the variables, supervisor support has the strongest impact on employee innovative behaviors. Accordingly, residential leaders are recommended to provide positive support to their followers to have innovative behaviors in the organizations.
Exploring impacts of AR on group package tours: Destination image, perceived certainty, and experiential value

With the growing demand for experience, technologies such as augmented reality (AR) have been widely adopted across fields to increase individuals’ interactive experiences. In tourism, group package tours have become a common touring approach; however, research in investigating tourists’ journey experiences facilitated by modern technologies such as AR remains rare. This study aims to examine factors affecting tourists’ behavioral intentions to choose group package tours. An extended theory of the planned behavior model with three antecedents—destination image, perceived certainty, and experiential value— is posited to evaluate the potential influence of AR. Using data of 557 survey respondents, the structural equation modeling shows a good fit for the empirical results. The findings reveal that AR gives tourists access to more explicit destination images, increases the certainty of group package tours, and creates experiential value during a trip, thereby enhancing behavioral intentions to opt for a group package tour. The study concludes with theoretical and empirical implications for tourism and related industries.
GA-SQP Algorithm for Solving Equilibrium States of Hypersonic Vehicles

In order to solve the equilibrium states of hypersonic vehicles with unstable modals,a hybrid optimization technique by the name of GA-SQP is developed.According to the performance index of the integral of time multiplied by the absolute value of error(ITAE),an improved genetic algorithm(GA) is used adopting chaos searching and elimination to calculate the equilibrium states,which are transformed into solutions of the minimum of the cost function.Furthermore,sequential quadratic programming(SQP) is introduced so as to accelerate the local optimum.The elevator deflection,throttle setting,and initial angle of attack are obtained by steps based on the Simulink dynamic model of the vehicle.Simulation results show that the GA-SQP algorithm,with desired steadiness,is able to determine the final solution accurately without being sensitive to the initial point.The algorithm provides a practical and effective method to solve the equilibrium of complex nonlinear systems.
An Efficient Preconditioning Strategy for Schur Complements Arising from Biphasic Models

We consider the mathematical modeling, the numerical simulation and an efﬁcient solution strategy of the periodontal ligament. For the modeling, we employ a biphasic approach which takes the ﬁbrous tissue in the PDL into account as well as the ﬂuid between the ﬁbres. After discretization in space and time, a coupled system with saddle point structure has to be solved at each time step. We present and discuss a preconditioning strategy for the Schur complement of this problem. And we apply it for predict-ing the behavior of realistic problems from dental biomechanics.
“Investigating the effect of obesity on adipose-derived stem cells (ASCs) using Göttingen Minipigs”

Obesity is associated with low grade inflammation, which may adversely impact the biological functions of adipose tissue and consequently of adipose-derived stem cells (ASCs). Studies in humans and rodents have described that obesity alters ASC properties and functionality, compromising their therapeutic prospects. The Göttingen Minipig (GM) is a commonly used obesity model. Nevertheless, there are no studies investigating the effect of obesity on ASCs from GM, which could constitute a valuable addition to both obesity modelling and adult stem cells investigations. In this study, we isolated subcutaneous ASCs from lean and obese GM to investigate the effect of obesity on cell behavior and differentiation capacity. During culturing, we observed an inherent difference in cell morphology between lean and obese ASCs. Upon adipogenic induction, obese-ASCs readily differentiated, developing significantly larger amounts of adipocytes than corresponding lean-ASCs, hinting at a predisposition towards adipogenic differentiation. Expression profiling of obesity-related genes in cell cultures, before and after adipogenic differentiation, revealed a tendency towards up-regulation in differentiated obese-cultures. Altogether, our results indicate that stem cells from obese donors could display different therapeutic properties. In summary, our results point towards GM as a valuable model for future ASCs investigations in healthy and obese states.
Swayed by the reviews: Disentangling the effects of average ratings and individual reviews in online word‐of‐mouth

Online word‐of‐mouth studies generally assume that a product's average rating is the primary force shaping consumers’ purchase decisions and driving sales. Similarly, practitioners place more emphasis on average ratings by displaying them at more salient places than individual reviews. In contrast, emerging evidence suggests that individual reviews also affect the decision‐making of those consumers who consult both kinds of information. However, because average ratings and individual reviews are often correlated and confounded empirically, little research has attempted to disentangle their effects. To address this empirical challenge, we construct trade‐off situations in which the average ratings and top‐ranked reviews of different product options do not align with each other. We then investigate consumers’ preferences that can indirectly reveal the relative impact of average ratings versus top reviews. Through an archival analysis of a panel dataset and two laboratory experiments, we find consistent evidence for a swaying effect of individual reviews and reveal their textual content as a likely reason. These findings challenge the commonly accepted assumption of average ratings being the primary driver of consumers’ purchase decisions and suggest that consumers may not be as rational as previous literature assumed. In addition, this paper is the first to disentangle the effects of average ratings and individual reviews on consumer decision‐making and explore a possible reason for the swaying effect of individual reviews. Our paper illustrates the importance of information accessibility in consumers’ purchase decisions, and our findings offer valuable insights for product manufacturers, online retailers, and review platforms.
Does Age, Residency, or Feeding Guild Coupled with a Drought Index Predict Avian Health during Fall Migration?

Simple Summary After a large avian mortality event occurred in New Mexico in the fall of 2020, we performed an analysis using 11 years of fall bird banding data at two locations in north-central New Mexico to investigate the influence of drought on avian health. Carcass studies after the event indicated that starvation was the primary cause of death. Using fall bird banding data along with regional drought indices, we used multiple logistic regression to predict the body health conditions of a bird during the fall migration period. We found that fat scores for younger, insectivorous, migratory birds were less likely to be greater than zero as drought severity levels increased. Our results suggest that migratory insectivores in the southwestern United States may be less resilient to drought-related climate change. Abstract Birds are good indicators of environmental change and are often studied for responses to climate. Many studies focus on breeding birds, while fewer look at the migration period, which is a critical time for many birds. Birds are more susceptible to unusual climatic events during their migration due to the metabolic stress of long-distance movements. In the fall of 2020, an unusual cold weather event coupled with drought and wildfire smoke led to a large avian mortality event in New Mexico. Later analysis pointed to the mortality being largely due to starvation. This was the impetus for our research. We used 11 years of fall bird banding data from two locations, along with local drought indices, to determine what predicts avian health during the migration period. We used fat score data from over 15,000 individual birds to assess whether drought indices, age, diet, or residency influenced avian health using multiple logistic regression. We found that the probability of positive fat scores decreased as drought severity increased for younger, insectivorous, migratory birds. Insectivores had a higher probability of receiving a fat score greater than zero relative to local drought conditions, which is important, since many North American insectivores are in steep decline. Migratory birds showed a greater response than year-round residents, and older birds showed a lower but significant response compared to hatch-year birds. Our results suggest that migratory insectivores in the southwestern United States may be less resilient to drought-related climate change.
Quality of Synthesized Speech: Impact of the Newest Coding Approaches

most widely used of them is concatenate synthesis, which is restricted to speech signal and based on combining short speech strings to form a longer one. Output of this synthesis is the most naturally sounding synthesized speech. There are three main types of concatenate synthesis: unit-selection synthesis, which uses large database of recorded pieces of speech, such as words, phrases, sentences, etc. This synthesis produces voices, which are mostly indistinguishable from naturally-produced ones. Second type is diphone synthesis. The database used for this purpose consists of all diphones found in particular language. In contrast to former approach (unit-selection synthesis), overall quality of diphone synthesis is generally worse. Finally, last approach is domain-specific synthesis; its database consists of pre-recorded words and phrases, which makes it restricted to certain scripts.