Miracle-dz/UniFAR-FTUs huggingface dataset:
Piezoelectric Sensors Operating at Very High Temperatures and in Extreme Environments Made of Flexible Ultrawide‐Bandgap Single‐Crystalline AlN Thin Films

Extreme environments are often faced in energy, transportation, aerospace, and defense applications and pose a technical challenge in sensing. Piezoelectric sensor based on single‐crystalline AlN transducers is developed to address this challenge. The pressure sensor shows high sensitivities of 0.4–0.5 mV per psi up to 900 °C and output voltages from 73.3 to 143.2 mV for input gas pressure range of 50 to 200 psi at 800 °C. The sensitivity and output voltage also exhibit the dependence on temperature due to two origins. A decrease in elastic modulus (Young's modulus) of the diaphragm slightly enhances the sensitivity and the generation of free carriers degrades the voltage output beyond 800 °C, which also matches with theoretical estimation. The performance characteristics of the sensor are also compared with polycrystalline AlN and single‐crystalline GaN thin films to investigate the importance of single crystallinity on the piezoelectric effect and bandgap energy‐related free carrier generation in piezoelectric devices for high‐temperature operation. The operation of the sensor at 900 °C is amongst the highest for pressure sensors and the inherent properties of AlN including chemical and thermal stability and radiation resistance indicate this approach offers a new solution for sensing in extreme environments.
Modified CTAB method for high-quality genomic DNA extraction from ship barnacle (Balanus sp.)

Presence of high amount of polysaccharide and polyphenolic compounds in barnacles restricts the isolation of high molecular weight good quality DNA. CTAB, which is a detergent used to isolate DNA from high polysaccharide containing plants, is used in this study to extract quality DNA from ship barnacle. This modified CTAB method is simple, efficient and quick enough to be carried out within 2 h. Taking DNAzol Â® isolated DNA as a reference, restriction digestion and PCR was performed to prove the absence of any enzyme inhibitory substances in the isolate. Traditional phenol-chloroform and salting out method failed to even isolate the DNA from barnacle sample. The molecular weight of the modified CTAB extracted DNA was higher than that of DNAzol Â® extracted DNA which makes it better candidate for analyses like whole genome sequencing.
Effect of betaine supplementation on haematology, serum enzymes and hormone profile in gestating sows

The study was conducted to study the effect of betaine supplementation on haematology, serum enzymes and hormones profile in gestating sows. For the study, artificially inseminated 18 crossbred (Landrace × Desi) sows were randomly distributed into 3 groups with 6 sows in each following a completely randomized design (CRD). Group T0 was fed with basal diet (control) and betaine was supplemented in group T1 and T2 @ 3 g/kg basal diet during late pregnancy (d 76 onwards till parturition) and throughout the length of gestation, respectively. The results revealed that betaine supplementation had no significant effect on the haemoglobin (Hb), packed cell volume (PCV), red blood cell (RBC) count, platelet count and white blood cells (WBC) count. Similarly, the serum enzymes such as aspartate amino transferase (AST), alanine amino transferase (ALT), alkaline phoshatase (ALP), lactate dehydogenase (LDH), and creatine kinase (CK) revealed no significant effect of betaine supplementation. The serum concentration of T3 and T4 hormone (ng/ml) of sows was significantly higher at the time of farrowing compared to the level at the time of insemination. The serum concentration of cortisol (ng/ml) of sows was significantly reduced in betaine supplemented groups compared to control. Thus, based on the results pertaining to cortisol levels in gestating, sows it can be concluded that betaine supplementation @ 3 g/kg diet, 76 day post insemination is beneficial to ameliorate the oxidative stress during pregnancy.
A Soft Fabric-based Shrink-to-fit Pneumatic Sleeve for Comfortable Limb Assistance

Upper limb impairments and weakness are com-mon post-stroke and with advanced aging. Rigid exoskeletons have been developed as a potential solution, but have had limited impact. In addition to user concerns about safety, their weight and appearance, the rigid attachment and typical anchoring methods can result in skin damage. In this paper, we present a soft, fabric-based pneumatic sleeve, which can shrink from a loose fit to a tight fit in order to anchor to the limbs temporarily, thereby enabling the application of mechanical assistance only when needed. The sleeve is comfortable, ergonomic and can be embedded unobtrusively with clothing. A mathematical model is built to simulate and design sleeves with different geometric parameters. The best sleeve was capable of generating a friction force of 98 N on the limb when inflated to 25 kPa. This sleeve was used to create a wearable assistive device, integrated with a cable-driven actuator. This device was able to lift a 1.44 kg forearm rig up to 95 degree at low pressure of 20 kPa. The device was tested with six healthy participants, in terms of fit, comfort and assistive functionality. The average acceptable sleeve pressure was found to be 33±4.7 kPa. All participants liked the appearance of the sleeve, with a high average perceived assistance score of 7.33±1.6 (out of 10). The shrink-to-fit sleeve is expected to significantly increase the development and adoption of soft robotic assistive devices and emerging powered clothing.
A systematic review of e-commerce websites literature in 2010-2020 period

In parallel with the increasing e-commerce usage rates worldwide, academic papers on e-commerce have increased in the last decade. In this regard, in this study, the papers on e-commerce indexed in the Web of Science (WOS) database between 2010 and 2020 are examined and discussed by journals, published years, countries, sample size, main purposes, theories, variables and main findings. Therefore, 70 selected research articles were examined. The selection criteria of these articles are to be research articles and to collect data from consumers using e-commerce websites. Therefore, 70 selected articles were examined and evaluated by using the content analysis method. As a result of the analysis, selected articles are summarised in Appendix 1. The selected articles have some common inferences: the reputation of websites, size of websites, familiarity, perceived ease of use, recommendations, design, convenience, perceived usefulness, system quality, service quality and information quality in e-commerce positively influence perceived trust and purchase intention of consumers. Also, the perceived trust of the consumers positively affects their purchase and repurchase intention. Besides that, perceived usefulness, perceived ease of use, perceived value and perceived risk are important determinants of consumers' purchase and repurchase intention in e-commerce. Finally, perceived risk negatively affects the perception and purchase intention of consumers.
Mapping the food environment: The reliability of volunteered geographical information and institutional data sources in France

The obesity epidemic and inequalities in access to food are prompting increasing numbers of food environment studies, which rely on secondary data sources for mapping. This article assesses the reliability of the two main food outlet data sources in France: the volunteered geographical information (VGI) collaborative map OpenStreetMap (OSM) and the national business register Sirene. Their information on food outlets was assessed through ground‐truthing in the city‐region of Montpellier. Sensitivity, positive predictive value, and concordance were computed for each database. We analyzed the socio‐spatial variability of these measures according to households' income level. The sensitivity of Sirene is good and that of OSM moderate, while the opposite holds for positive predictive value, and the concordance of both OSM and Sirene is fair. Sirene provides more reliable data on deprived neighborhoods and OSM on wealthy neighborhoods. Caution is recommended regarding the classifications on which they are based, the time required to update the institutional database, and socially influenced contributions to VGI.
Adaptive laboratory evolution for increased temperature tolerance of the diatom Nitzschia inconspicua

Outdoor microalgal cultivation for the production of valuable biofuels and bioproducts typically requires high insolation and strains with high thermal (>37°C) tolerance. While some strains are naturally thermotolerant, other strains of interest require improved performance at elevated temperatures to enhance industrial viability. In this study, adaptive laboratory evolution (ALE) was performed for over 300 days using consecutive 0.5°C temperature increases in a constant temperature incubator to attain greater thermal tolerance in the industrially relevant diatom Nitzschia inconspicua str. Hildebrandi. The adapted strain was able to grow at a constant temperature of 37.5°C; whereas this constant temperature was lethal to the parental control, which had an upper‐temperature boundary of 35.5°C before adaptive evolution. Several high‐temperature clonal isolates were obtained from the evolved population following ALE, and increased temperature tolerance was observed in the clonal, parent, and non‐clonal adapted cultures. This ALE method demonstrates the development of enhanced industrial algal strains without the production of genetically modified organisms (GMOs).
Lower hybrid resonance wave excitation by whistlers in the magnetospheric plasma

A new theory of lower hybrid resonance (LHR) wave excitation by whistlers in magnetospheric plasma is developed. Two time dependent differential equations, which have a form of linear wave interaction between quasi-longitudinal whistler-mode waves and quasi-electrostatic LHR waves in a cold plasma with small-scale density irregularities, are derived and solved by the method of successive approximations. Fundamental observational results on LHR wave excitation by whistlers, such as the lower cutoff frequency of excited waves and the pronounced spectral maximum near the LHR frequency, as well as the close connection of the excitation process with small-scale plasma density irregularities are explained by the present theory in a consistent manner.
A soybean seedlings dataset for soil condition and genotype classification

We have witnessed the exponential growth of the number of Deep Learning techniques as well as their technical and theoretical advancements. Nowadays, the researchers’ effort is also focusing on the applicability of those well-founded concepts. One target is precision agriculture, the area of farming management guided by observation, measurement, and data analysis. Generalization is a real challenge regarding the farm environment. The visual information used during the model’s test phase may be exposed to a significant variation in light and weather conditions and visual differences due to plant growth stages. Another challenge is the cost of collecting and labeling data. Convolutional Neural Networks (CNNs) have been used in many applications, such as detecting diseases, distinguishing animal species and plant genotypes, and identifying the plant’s environmental characteristics. A large volume of data is required to enable the model to generalize well in these real farm conditions. One open problem is the study of which soybean genotypes best adapt to the soil compaction condition, aiming to increase crop productivity. This problem is a candidate to be solved using CNNs; however, an image dataset is necessary to train the model. In this paper, we proposed a dataset with approximately 1,000 soybean seedlings images from 30 different genotypes grown in compacted and non-compacted soil conditions. To demonstrate the dataset representativeness, we trained classic CNN models to classify soil conditions based only on the visual information and then interpreted the model learning using visual explanation methods. We also raised possible future work for using the dataset in the precision agriculture field.
Work-in-Progress: Measuring Security Protection in Real-time Embedded Firmware

The proliferation of real-time cyber-physical systems (CPS) is making profound changes to our daily life. Many real-time CPSs are security and safety-critical because of their continuous interactions with the physical world. While the general perception is that the security protection mechanism deployment is often absent in real-time embedded systems, there is no existing empirical study that measures the adoption of these mechanisms in the ecosystem. To bridge this gap, we conduct a measurement study for real-time embedded firmware from both a security perspective and a real-time perspective. To begin with, we collected more than 16 terabytes of embedded firmware and sampled 1,000 of them for the study. Then, we analyzed the adoption of security protection mechanisms and their potential impacts on the timeliness of real-time embedded systems. Besides, we measured the scheduling algorithms supported by real-time embedded systems since they are also security-critical.
Dissolved Gases Analysis Comparison of Electrical Faults Between Rice Bran Oil and Mineral Oil Insulation Systems

Dissolved gas analysis (DGA) of transformers can reveal electrical stresses encountered by oil-immersed power transformers. DGA can identify potential transformer failures, which allows it to potentially prevent further damage from occurring. Mineral Oil (MO) and Rice Bran Oil (RBO) have both been used as conventional transformer oils for the purpose of this study, and a comparison of their DGA evaluations under electrical breakdown faults has been carried out. RBO has excellent oxidation stability and benefits in terms of both price and accessibility. Therefore, this study focuses on RBO as a sustainable option to petroleum-based MO for transformer oil. The many approaches developed for analyzing these gases and interpreting their significance include Key Gas, Duval Triangle and Pentagon Method, Doernenburg Ratio, Rogers Ratio, and IEC Ratio. The diagnostic approaches were not completely reliable for identifying electrical faults in RBO. The findings suggest that present DGA interpretation procedures for RBO or vegetable oil shall be properly modified. In the case of MO, however, DGA analysis indicated that there is a thermal crack in the oil sample that must be addressed.
Analgesic Effects of Regional Analgesic Techniques in Pediatric Inguinal Surgeries: A Systematic Review and Network Meta-Analysis of Randomized Controlled Trials

BACKGROUND: Various regional analgesic techniques have been used in pediatric inguinal surgery to facilitate postoperative recovery. However, each technique’s relative performance was undetermined owing to the lack of quantitative analysis. METHODS: We systematically searched MEDLINE, Cochrane Library, EMBASE, and Web of Science for randomized controlled trials that compared regional analgesia in pediatric inguinal surgeries. After critical study screening and selection, a random-effects network meta-analysis was performed. The primary outcome was the time to the first rescue analgesic after surgery, and the secondary outcomes were the number of patients requiring rescue analgesics after surgery, postoperative pain scores, incidence of postoperative nausea and vomiting, and other adverse events. RESULTS: This network meta-analysis included 69 randomized controlled trials (4636 patients) that compared 10 regional analgesic techniques. Our study revealed that the quadratus lumborum and transversus abdominis plane blocks had the longest time to the first rescue analgesic after pediatric inguinal surgeries, by 7.7 hours (95% confidence interval [CI], 5.0–10.3) and 6.0 hours (95% CI, 3.9–8.2) when compared with the control group, respectively. In the subgroup involving only inguinal hernia repair, the quadratus lumborum block significantly prolonged the time to the first rescue analgesic than all other regional analgesics. In contrast, in the subgroup involving orchidopexies, only the caudal block significantly prolonged the time to the first rescue analgesic when compared with the control group (4.1 hours; 95% CI, 0.7–7.5). Wound infiltration and landmark-based ilioinguinal-iliohypogastric block had relatively poor analgesic effects than other regional analgesics. No serious adverse effects related to the regional analgesic techniques were reported in any of the included studies. CONCLUSIONS: The quadratus lumborum and transversus abdominis plane blocks had the longest time to the first rescue analgesic and the least rescue analgesic requirement for pediatric inguinal surgeries. Specifically, the quadratus lumborum block had the longest analgesic duration in inguinal hernia repair, and the caudal block was found to be the only regional analgesia that extended the time to the first rescue analgesic in pediatric orchidopexy. Most included randomized controlled trials had some concern or a high risk of bias, and future studies should focus on providing high-quality evidence to further clarify the analgesic effects of regional analgesia for pediatric inguinal surgeries.
A Dynamically Calibrated Suspension System

The global automotive sector is booming, with an estimated 1.4 billion powered vehicles on the road today, with this number rising every day. Smooth riding is a crucial component of a pleasurable driving experience; it depends on several variables, the car's suspension. This is true for small commercial vehicles with 16 to 18 wheels for moving people and products, such as two-wheelers for commuting. It absorbs the energy a vehicle's wheels transmit, allowing it to travel over the suspension smoothly, even on bumpy roads. In contrast to at least partially delivering kinetic energy to your automobile's frame, the shocks or dampers absorb the impulses. To control how much kinetic energy is dissipated, the suspension's springs flex and expand quietly in the background. Additionally, they prevent the remainder of the car from excessively bouncing. When these two factors work together, your automobile ride will seem quite level and even.
Experimental Study on Impact Resistance of Multi-DOF Electro-Hydrostatic Robot Systems Using Hydracer, a 6DOF Arm

Industrial robots require force controllability and impact resistance to ensure safe physical interactions. An electro-hydrostaic actuator (EHA) is expected to be suitable for such applications because it has high backdrivability which improve both force controllability at contact and impact resistance. However, EHAs had been rarely used in multi-axes robotic systems. The previous works validated the force controllability of the EHA-driven robot Hydra. However, the impact resistance of an EHA-driven robot is still unclear. In order to evaluate the impact resistance of the high-power EHA-driven robot, we developed high-pressure EHAs employing ceramics as rigid material to reduce internal leakage, and developed the EHA-driven 6-DOF robot arm Hydracer as the platform for the evaluation. This paper describes the mechanism of Hydracer especially on the base 3-DOF mechanism, and conducts the backdrivability measurement and the impact resistance evaluation.
Global Parameter and Helioseismic Tests of Solar Variability Models

We construct models of the structure and evolution of the Sun which include variable magnetic fields and turbulence. The magnetic effects are (1) magnetic pressure, (2) magnetic energy, and (3) magnetic modulation to turbulence. The effects of turbulence are (1) turbulent pressure, (2) turbulent kinetic energy, and (3) turbulent inhibition of the radiative energy loss of a convective eddy, and (4) turbulent generation of magnetic fields. Using these ingredients we construct five types of solar variability models (including the standard solar model) with magnetic effects. These models are in part based on three-dimensional numerical simulations of the superadiabatic layers near the surface of the Sun. The models are tested with several sets of observational data, namely, the changes of (1) the total solar irradiance, (2) the photospheric temperature, (3) radius, (4) the position of the convection zone base, and (5) low- and medium-degree solar oscillation frequencies. We find that turbulence plays a major role in solar variability, and only a model that includes a magnetically modulated turbulent mechanism can agree with all the current available observational data. We find that because of the somewhat poor quality of all observations (other than the helioseismological ones), we need all data sets in order to restrict the range of models.
Neural Fault Analysis for SAT-based ATPG

Continued advances in process technology have led to a relentless increase in the design complexity of integrated circuits (ICs). In order to meet the increasing demand of low defective-parts-per-million (DPPM) and high product quality of the complex circuit designs, Boolean Satisfactory (SAT) has worked as a robust alternative to conventional APTG techniques. In SAT-based ATPG, logic cones related to the target faults are transformed to Boolean formulas, and standard SAT solving procedures are then used for solving these formulas. Recently, artificial intelligence (AI) techniques have shown great potential in speeding-up SAT solvers. However, the high diversity of the structural characteristics within the logic cones of target faults limits the AI techniques being used for SAT-based ATPG. To meet this challenge, this paper proposes a neural fault analysis technology that is made up of a multi-stage learning model and the testability classifier to highly increase the SAT-based ATPG solving efficiency. The multi-stage learning model is composed of a generative model with a topology structure discriminator and a conflict structure discriminator. It is trained for high-quality data synthesis. Then the testability classifier is trained for adaptive heuristic selection and effective initialization in SAT-based ATPG. Experimental results on both open-source and industrial circuits demonstrate that the neural fault analysis can reduce the SAT solving time by 34.79% and reduce the runtime of SAT-based ATPG by 7.43% on average. It is also shown that the proposed neural fault analysis can cover 9.14% of the faults failed by the conventional SAT-based ATPG framework with a comparable runtime.
Polynomial models of real manifolds

We construct polynomial models for germs of real submanifolds in complex space. It was shown earlier that the properties of models of degree 3 (for appropriate values of the codimension) are similar to well-known properties of tangent quadrics. In this paper we construct models of arbitrarily high degree. They have all these properties with one exception: from degree 5 onwards, they are not completely universal.