Miracle-dz/UniFAR-FTUs huggingface dataset:
Allometry in the Freshwater Pearl Mussel (Margaritifera margaritifera L.): Mussels Tend to Grow Flatter at Higher Water Speed

ABSTRACT The freshwater pearl mussel (Margaritifera margaritifera) is one of the longest-lived invertebrate species in the world and one of the most threatened freshwater animals in Europe. Its southernmost populations, located in northwestern Spain, are in a critical conservation situation and are still understudied. Here we calibrate a non-invasive method for calculating the volume of the shell and use it to study the ontogenetic scaling of shell volume on shell length. We characterized ontogenetic growth and determined allometric relationships in 16 M. margaritifera northwestern Spain populations by using ordinary least squares regression, major axis and reduced major axis methods. We estimated topographic slopes of the sampling points using a GIS system, as a proxy of water speed. We measured 803 shells and found that the volume of the shell can precisely be estimated using three linear measurements. We found evidence for negative allometry of shell volume in the global sample and in 11 populations. We hypothesized that water speed would affect allometric patterns of local populations. Results suggest a negative relationship between the allometric slope and the topographic slope of the river section inhabited by M. margaritifera. We propose that when water speed is higher, larger mussels become proportionally flatter than in locations where water current is slower, allowing them to burrow more easily in the sediment. Our method will allow estimation of M. margaritifera biomass and ontogenetic growth without killing any specimens, which will contribute to conservation programs for this species.
Review of the Genus Habeas from Brazil, with Description of Four New Species and in Which Anatomical Features Revealed That They Belong to Urocoptidae (Eupulmonata, Stylommatophora)

ABSTRACT South American land snails are relatively poorly known, but their taxonomic relationships can be illuminated with the help of detailed anatomical descriptions and comparisons. The genus Habeas Simone, 2013, species of which are associated with caves, was tentatively described in the prosobranch family Diplommatinidae. Recently collected samples that permitted anatomical investigation, revealed that Habeas actually belongs to the eupulmonate family Urocoptidae. The genus is thus reviewed, including the three so far known species: H. corpus, H. data and H. priscus, all Simone, 2013. Four new species collected in Brazil are described: Habeas lekolus (from Cônego Marinho, Minas Gerais), H. peruassus (from Januária, Minas Gerais), H. lapensis (from Bom Jesus da Lapa, Bahia) and H. claudus (from Cocos, Bahia). Anatomical description is based on H. lekolus, revealing in its most interesting features, the absence of the ureter, presence of a pallial gland, lack of anterior duct to digestive gland, small penis and epiphallus, and absence of bursa copulatrix. Species in this genus usually inhabit cave habitats and are only found in Bahia (BA) and Minas Gerais (MG) Brazilian states, in areas close to São Francisco River. A brief discussion of the family attribution to Habeas is also performed. The present seven species in a genus recently discovered in a relatively small area demonstrate how weak the knowledge on the Brazilian malacofauna is.
Are WiFi Backscatter Systems Ready for the Real World?

WiFi backscatter communication has been proposed to enable battery-free sensors to transmit data using WiFi networks. The main advantage of WiFi backscatter technologies over RFID is that data from their tags can be read using existing WiFi infrastructures instead of specialized readers. This can potentially reduce the complexity and cost of deploying battery-free sensors. Despite extensive work in this area, none of the existing systems are in widespread use today. We hypothesize that this is because WiFi-based backscatter tags do not scale well, and their range and capabilities are limited when compared with RFID. To test this hypothesis, we conduct several real-world experiments. We compare WiFi backscatter and RFID technologies in terms of energy consumption, throughput, range and scalability.
Bag-Mask Ventilation Versus Apneic Oxygenation During Tracheal Intubation in Critically Ill Adults: A Secondary Analysis of 2 Randomized Trials

Background: Hypoxemia is common during tracheal intubation in intensive care units. To prevent hypoxemia during intubation, 2 methods of delivering oxygen between induction and laryngoscopy have been proposed: bag-mask ventilation and supplemental oxygen delivered by nasal cannula without ventilation (apneic oxygenation). Whether one of these approaches is more effective for preventing hypoxemia during intubation of critically ill patients is unknown. Methods: We performed a secondary analysis of data from 138 patients enrolled in 2, consecutive randomized trials of airway management in an academic intensive care unit. A total of 61 patients were randomized to receive bag-mask ventilation in a trial comparing bag-mask ventilation to none, and 77 patients were randomized to receive 100% oxygen at 15 L/min by nasal cannula in a trial comparing apneic oxygenation to none. Using multivariable linear regression accounting for age, body mass index, severity of illness, and oxygen saturation at induction, we compared patients assigned to bag-mask ventilation with those assigned to apneic oxygenation regarding lowest oxygen saturations from induction to 2 min after intubation. Results: Patients assigned to bag-mask ventilation and apneic oxygenation were similar at baseline. The median lowest oxygen saturation was 96% (interquartile range [IQR] 89%-100%) in the bag-mask ventilation group and 92% (IQR 84%-99%) in the apneic oxygenation group. After adjustment for prespecified confounders, bag-mask ventilation was associated with a higher lowest oxygen saturation compared to apneic oxygenation (mean difference, 4.2%; 95% confidence interval, 0.7%-7.8%; P = .02). The incidence of severe hypoxemia (oxygen saturation<80%) was 6.6% in the bag-mask ventilation group and 15.6% in the apneic oxygenation group (adjusted odds ratio, 0.33; P = .09). Conclusions: This secondary analysis of patients assigned to bag-mask ventilation and apneic oxygenation during 2 clinical trials suggests that bag-mask ventilation is associated with higher oxygen saturation during intubation compared to apneic oxygenation.
News Media Image: A Typology of Audience Perspectives

The premise of this study is the timeliness of interdisciplinary approaches in news media research, specifically including the perceptions of news audiences. Using a multidisciplinary literature review and qualitative and quantitative analysis, this study adopted a multidimensional construct—news media image—to investigate how news audiences perceive news media organizations. The respondents studied here, who were representative of the general U.S. population, referenced the news media in general in their evaluation of news outlets. Results of focus groups and online surveys (factor analyses) indicated that news audiences evaluate the content and practices of news media overall based on perceptions related to seven specific criteria: usefulness, credibility, empathy, personality, usability, news selection bias, and social responsibility. Image perception encompasses rational, cognitive judgment, and affective evaluation. That news audience respondents commonly employed multiple evaluation criteria related to news media points to the need to broaden the scope of journalistic research in the direction of a new heuristic. Examining news media image, that is, investigating how “the general public” views news media as an institution in a continuously changing—and challenging—news media landscape adds value to media research. Results from a confirmatory factor analysis used in this study suggest that a positive news media image can enhance audience satisfaction and, subsequently, loyalty.
A comprehensive reliability allocation method for series systems based on failure mode and effects analysis transformed functions

In order to address the reliability allocation problem of the series system, a comprehensive reliability allocation method based on a transformed function of the failure mode and effects analysis is introduced. First, considering multiple factors that affect the reliability allocation, an allocation matrix is established by employing significance factors. Subsequently, to overcome the limitations of the conventional failure mode and effects analysis–based allocation method, non-linear transform laws of failure severity and occurrence, known as transformed functions, are established. The reliability allocation results could be adjusted appropriately by choosing transform coefficients according to the desired allocation results of the system. Then, the transformed failure mode and effects analysis and the comprehensive allocation matrix are combined to give an allocation vector. Finally, a computerized numerical controlled lathe and a spindle system are used as examples. The allocation results of the transformed method, the conventional failure mode and effects analysis method and those in the correlated references are compared to emphasize the significance of the proposed allocation method in engineering practice.
Optimally Temperature Compensated FBG-Based Sensor Dedicated to Non-Intrusive Pipe Internal Pressure Monitoring

Pipe internal pressure measurement is of utmost importance in the oil & gas industry to monitor the extraction process, and thus to prevent hydrate-plugs formation which may occur in specific temperature and pressure conditions. Traditional solutions usually rely on pressure sensors in direct contact with the fluid to monitor, therefore requiring one hole per sensor, but they also weaken the pipe structure, which may prematurely lead to significant leaks. Attempts to develop non-intrusive pressure sensors relying, for instance, on acoustic waves detection or even strain measurements (the pipe wall acting, in some way, like the membrane of a traditional intrusive sensor), are up to now not fully satisfying, mainly due to poor temperature cross-sensitivity compensation. Thus, 1 °C temperature compensation error typically leads for Fiber Bragg Grating (FBG) transducers to pressure measurement biases greater than 26% at 100 bar (e.g.: Ø 4” NPS Sch. 160 steel pipe). Consequently, if such non-intrusive, but biased, solutions could possibly have been considered to monitor, for instance, a Nuclear Power Plant (NPP) primary coolant circuit, it was with the risk of dramatic consequences since the fluid can reach temperatures up to 320 °C. On the other hand, the solution detailed here truly achieves to cancel the temperature cross-sensitivity, and potentially any additional effect on pressure measurement, provided that each effect has the same influence on all transducers. It first relies on a better understanding of the pipe behavior under hydrostatic pressure, supported by a dedicated model developed on purpose, which demonstrates that the internal pressure and the surface temperature variations of a closed pipe can be recovered with at least two direction-sensitive transducers, the temperature dependence of the pressure measurement being simply removed by a straightforward compensation process. This paper explains the underlying principle, thanks to a formal model established with only few hypotheses, but extended to more complex field conditions. It ends with a lab-test validation involving FBG transducers attached to a pressure circuit submitted to temperature variations greater than several tens of °C, and concludes about the advantages and limitations of this novel approach for non-intrusive sensing, and its potential extensions to other measurement techniques.
The Stability and Collapse of Lava Domes: Insight From Photogrammetry and Slope Stability Models Applied to Sinabung Volcano (Indonesia)

Lava domes form by the effusive eruption of high-viscosity lava and are inherently unstable and prone to collapse, representing a significant volcanic hazard. Many processes contribute to instability in lava domes and can generally be grouped into two categories: active and passive. Active collapses are driven directly by lava effusion. In contrast, passive collapses are not correlated with effusion rate, and thus represent a hazard that is more difficult to assess and forecast. We demonstrate a new workflow for assessing and forecasting passive dome collapse by examining a case study at Sinabung Volcano (North Sumatra, Indonesia). We captured visual images from the ground in 2014 and from unoccupied aerial systems (UAS) in 2018 and used structure-from-motion photogrammetry to generate digital elevation models (DEMs) of Sinabung’s evolving lava dome. By comparing our DEMs to a pre-eruption DEM, we estimate volume changes associated with the eruption. As of June 2018, the total erupted volume since the eruption began is 162 × 106 m3. Between 2014 and 2018, 10 × 106 m3 of material collapsed from the lava flow due to passive processes. We evaluate lava dome stability using the Scoops3D numerical model and the DEMs. We assess the passive collapse hazard and analyze the effect of lava material properties on dome stability. Scoops3D is able to hindcast the location and volume of passive collapses at Sinabung that occurred during 2014 and 2015, and we use the same material properties to demonstrate that significant portions of the erupted lava potentially remain unstable and prone to collapse as of late 2018, despite a pause in effusive activity earlier that year. This workflow offers a means of quantitatively assessing passive collapse hazards at active or recently active volcanoes.
A Phenomenological Study of Educators’ Experience After a Year of the COVID-19 Pandemic

This phenomenological study investigated educators’ lived experiences of teaching online in higher institutions in Malaysia. Data, which was generated through semi-structured interviews with 20 lecturers from three universities in the country, was analysed based on the thematic analysis approach guided by the Technological, Pedagogical, and Content Knowledge (TPACK)-self-efficacy framework. The findings revealed that after a year of teaching online, the potential of technology has been acknowledged by the educators after some trials and constraints were addressed. The domains related to Technology Content Knowledge (TCK), Technology Pedagogical Knowledge (TPK), and TPACK were evident in the findings. However, Pedagogical Content Knowledge (PCK) was not given emphasis, hence this manuscript argues that educators need to be constantly reminded of the significance of PCK. The findings discussed in this manuscript can be a helpful guide for educators when there is a need for them to teach online.
Microbial iron reduction does not release microplastics from organo‐metallic aggregates

Iron flocculants play a major role in the remediation of water bodies, removing particulate pollutants such as microplastics through floc formation. Such flocs are prone to microbial iron reduction while lying on top of anoxic sediments, which possibly leads the release of bound microplastics. In this study, Shewanella oneidensis was employed to simulate the impact of microbial iron reduction on the release of polyethylene spheres from sunken flocs in 120 d batch experiments. Most of the flocs iron (oxyhydr)oxides were reduced (70–90%), but this did not affect their integrity. Only a negligible proportion (0.2–2.7%) of polyethylene spheres was released, while the majority remained bound inside the floc matrix. This study exemplifies that flocs are quite stable, even when experiencing microbial iron reduction under anoxic conditions. Thereby incorporation into such aggregates may display a potential mode of long‐term microplastics storage in freshwater sediments.
El impacto de la migración internacional y las remesas en los patrones productivos: el caso del Ecuador rural The impact of international migration and remittances on agricultural production patterns: the case of rural Ecuador

This paper analyzes the effects of international migration and remittances on fertilizer expenditure and cattle acquisition in rural Ecuador. The results show that migrants’ households exhibit a higher propensity to acquire livestock than their counterparts without migrants. However, the monthly amount of remittances received by a household does not have any influence on the likelihood of cattle acquisition. These results are consistent with those of several other studies analyzing the impact of migration on farm activity choice and indicate that migrants’ households tend to switch from crop production to the less labor demanding cattle production in order to cope with household labor losses resulting from migration.
A novel erasing technology for 3.3 V flash memory with 64 Mb capacity and beyond

A novel erasing scheme has been developed to suppress the distribution of the erased cell threshold voltage (erased-V). The new 2-step erasing scheme consists of two steps of the cell gate bias conditions, that is to apply 1) negative high voltage on the control gate to erase the cell data, and successive 2) positive high voltage to inject a few electrons from the substrate back to the floating gate. The suppressing effect of the erased-V distribution was also confirmed using a 16 Kbit flash memory cell array, the erased-V/sub /distribution drastically decreases from 2.0 V by the conventional erasing scheme to 0.9 V using the 2-step erasing scheme. <<ETX>>
A Hovercraft Visual Simultaneous Localization and Mapping System Performance Evaluation for River Monitoring Application

The dynamic geographical shape of a river provides a unique challenge in adopting an autonomous hovercraft-like robot for river monitoring. Specifically, performing the mapping and localization task in such an environment is non-trivial. Few factors need to be considered including the dynamic of the hovercraft and the severity of the surrounding environment. In this study, an investigation was carried out to evaluate the performance of a visual simultaneous localization and mapping (SLAM) technique in generating the environment model of a simulated river. The main objective of this study is to build a SLAM system of a hovercraft such that the robot can traverse the river surface autonomously. A depth camera was used as the visual sensor, and acts as the main odometry in the process of mapping and localization of the hovercraft. Data from the visual sensor was tuned and optimized to adapt to the river surface environment. The performance of the tuned SLAM was measured by comparing several configuration settings to get the best output. The result of this study shows that with proper tuning and optimization, a SLAM technique can be used to generate an accurate river surface map and monitor the hovercraft trajectories.
Key Area Acquisition Training for Practical Image-based Plant Disease Diagnosis

Automatic diagnosis of plant diseases using images is a fine-grained task, and disease symptoms are often ambiguous and highly variable. Pre-extraction of the region of interest (ROI) exhibiting disease symptoms (such as one or more leaves) is known to have a certain effect on improving accuracy. However, the ROI extraction at runtime is time-consuming, resulting in issues of system usability. This paper proposes a new training method called key area acquisition training (KAAT). KAAT reduces the variation in prediction results between images before and after the extraction of the ROI. By directing the model’s attention to the ROI through learning, KAAT contributes to improved diagnostic performance without sacrificing execution time during diagnosis. In the evaluation, we conducted nine class diagnosis task (eight diseases and healthy) using 77K and 9K images of cucumber leaves (collected from different fields) for training and testing, respectively. The proposed KAAT improved diagnostic accuracy by 3.8% in macro-F1 and 2.0% in micro accuracy without increasing execution time.
Study on Prediction Methods and Its Influence Factors of Water Inflow Into Tunnels

Water into tunnels is an important reference index for design of tunnel waterproofing and drainage systems,because it not only relates to seepage forces acting on the tunnel lining,but also relates to the safety of the ecological environment.Based on the summary of 3 main prediction methods of water inflow into tunnels: theoretical analysis method,empirical formula method and numerical analysis method,influence of many factors on water inflow into tunnels is discussed,which includes permeability of surrounding rock,cavern size,water table height,permeability of lining,permeability and thickness of grouting circle, thickness of the aquifer,and cavern shapes,et al.Differences among prediction methods of water inflow into tunnels are comparatively analyzed.The limitations and conditions for application of these methods,especially for various theories analytical methods,are highlighted.The research results can definitely provide reference and technical support for prediction of water inflow into tunnels and its control measures.
Design and Development of Smart Umbrella Based on Iot Technology

The connection among things and humans through the internet for various applications like weather monitoring, healthcare systems, smart cities, home automation and traffic light control has been established by the Internet of Things (IoT). Keeping abreast of the digital world, majority of industries mainly aim to predict the changes in the market and in this study, the development of an IoT smart umbrella system for the measurement of rainfall is presented. The system is used to predict real-time weather conditions using smartphone. Such a season management system is analyzed using Temperature & Humidity sensors linked to the Raspberry pi controller, after which details of the weather are displayed in the smart phone screen through an SMS. Additionally, the system is connected with a solar system supplying the raspberry pi system that acts as a power reserve for recharging gadgets.
Power Management Scheme with Cascaded Complex Coefficient Filter Control for SyRG DG-SPV-BES Based Standalone System for Remote Areas

This paper aims to provide a complete power management strategy for an isolated microgrid (MG) for remote areas and improve the power quality of the microgrid when local loads draw unbalanced nonlinear currents from the MG. The MG under consideration consists of a synchronous reluctance generator (SyRG) based diesel generator (DG) set, a dual stage photovoltaic (PV) array, and a battery energy storage (BES). Since the DG impedance is more than the grid, the DG currents and voltages are subjected to more distortion in the presence of nonlinear loads and single phase loads. To solve these power quality problems, an improved cascaded complex coefficient filter (CCCF) based algorithm is used during the DG operation. The power management scheme ensures minimum use of the DG set for power generation and aims for maximum power extraction from the PV array as much as possible. The PV array is operated by a modified de-rated perturb and observe (MDP&O) MPPT. The DG set is operated in its fuel economic zone (FEZ). The synchronization control ensures fast transition of the system between DG connected mode, and standalone mode (SAM) such that the power is fed to the load continuously. The system simulink model is developed, and the performance is analyzed under various dynamic conditions.