Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of demethylating DNA glycosylase ROS1 from Nicotiana tabacum L.

One of the main mechanisms of epigenetic regulation in higher eukaryotes is based on the methylation of cytosine at the C5 position with the formation of 5-methylcytosine (mC), which is further recognized by regulatory proteins. In mammals, methylation mainly occurs in CG dinucleotides, while in plants it targets CG, CHG, and CHH sequences (H is any base but G). Correct maintenance of the DNA methylation status is based on the balance of methylation, passive demethylation, and active demethylation. While in mammals active demethylation is based on targeted regulated damage to mC in DNA followed by the action of repair enzymes, demethylation in plants is performed by specialized DNA glycosylases that hydrolyze the N-glycosidic bond of mC nucleotides. The genome of the model plant Arabidopsis thaliana encodes four paralogous proteins, two of which, DEMETER (DME) and REPRESSOR OF SILENCING 1 (ROS1), possess 5-methylcytosine-DNA glycosylase activity and are necessary for the regulation of development, response to infections and abiotic stress and silencing of transgenes and mobile elements. Homologues of DME and ROS1 are present in all plant groups; however, outside A. thaliana, they are poorly studied. Here we report the properties of a recombinant fragment of the ROS1 protein from Nicotiana tabacum (NtROS1), which contains all main structural domains required for catalytic activity. Using homologous modeling, we have constructed a structural model of NtROS1, which revealed folding characteristic of DNA glycosylases of the helix– hairpin–helix structural superfamily. The recombinant NtROS1 protein was able to remove mC bases from DNA, and the enzyme activity was barely affected by the methylation status of CG dinucleotides in the opposite strand. The enzyme removed 5-hydroxymethylcytosine (hmC) from DNA with a lower eff iciency, showing minimal activity in the presence of mC in the opposite strand. Expression of the NtROS1 gene in cultured human cells resulted in a global decrease in the level of genomic DNA methylation. In general, it can be said that the NtROS1 protein and other homologues of DME and ROS1 represent a promising scaffold for engineering enzymes to analyze the status of epigenetic methylation and to control gene activity.
Squalene-Rich Amaranth Oil Pickering Emulsions Stabilized by Native α-Lactalbumin Nanoparticles

The stabilization of Pickering emulsions by nanoparticles has drawn great interest in the field of food science and technology. In this study, α-Lactalbumin nanoparticles prepared by the desolvation and cross-linking method from protein solutions with initial pH values of 9 and 11 were used to stabilize squalene-rich amaranth oil Pickering o/w emulsions. The effect of different concentrations of nanoparticles on the size, size distribution, ζ potential, and emulsion stability was evaluated using dynamic light scattering, electron microscopy, and light backscattering. Dependence of the emulsions’ droplet size on the nanoparticle concentration was observed, and the critical coverage ratio was reached when 5–10% nanoparticles concentration was used. Our findings suggest that α-LA nanoparticles at a 10% concentration can be used as novel stabilizers for Pickering emulsions to provide protection for beneficial lipophilic bioactive compounds. This is the first time that native α-LA nanoparticles have been used as stabilizers of Pickering emulsions.
Oral Rehabilitation in An Adult Patient with Oligodontia with Retained Deciduous Teeth by Immediate Implant Placement

In the treatment of patients with oligodontia, factors such as patient age, developmental stage, and number of missing teeth should be considered. If the number of missing teeth is less, the patient can be treated with minimally invasive treatments, such as remaining primary teeth, autogenous tooth transplantation, and orthodontic treatment. However, when the number of missing teeth is high, conventional treatment may be limited. In this case, after extraction of the deciduous teeth, implants can be placed in the edentulous area. We report a case of oral rehabilitation with orthodontic treatment, bilateral sinus floor augmentation, and immediate implant placement in a 20-year-old man with oligodontia. The treatment was succesful, and we achieved esthetically and functionally satisfactory outcomes.
Performance Trade-offs and Operations of Electric Boosted Aircraft for 2030 Single-Aisle Market

There has been a growing interest in the development of an electric boosted distributed propulsion system that may provide aerodynamic benefits and better take-off performance. Existing in-house tools have been updated for turboelectric hybrid aircraft design and leverage the reliability of existing NASA design and analysis tools such as the Numerical Propulsion System Simulation (NPSS) and Flight Optimization System (FLOPS). The A320 is selected for this study due to its wide single-aisle market acceptance and data availability. The aim of this study is to obtain a feasible design and operational space by performing trade-offs among the airframe, thrust, power sources, distribution system (PMAD), and energy storage with the aero-propulsive benefits of distributed propulsion system. Aircraft configurations utilize ducted propulsors to achieve a 400-600 nmi design range with the best viable DC voltage and 650 W-hr/kg specific energy. Results show that aircraft performance is largely dependent on electrical components weight, which is highly correlated with DC link voltages. PMAD strategies are identified for hybrid turbo-electric single-aisle aircraft to reduce the fuel burn for selected DC voltage level for the system.
Fuzzy Controlled ZVS Asymmetrical PWM Full-bridge DC-DC Converter for Constant load High Power Applications

This paper proposes a fuzzy logic controlled new topology of high voltage gain zero voltage switching (ZVS) asymmetrical PWM full-bridge DC-DC boost converter for constant load and high power applications.The APWM full-bridge stage provides high voltage gain and soft-switching characteristics increase the efficiency and reduce the switching losses. Fuzzy logic controller (FLC) improves the performance and dynamic characteristics of the proposed converter. A comparison with a classical proportional-integral (PI) controller demonstrates the high performances of the proposed technique in terms of effective output voltage regulation under different operating conditions. Simulation is done by integrating two different simulation platforms PSIM and Matlab/Simulink by using SimCoupler tool of PSIM. Experimental results using 120W load have been provided to validate the results.
Did State Pre-Kindergarten Programs Affect the Head Start Enrollment of Children with Disabilities? A Quasi-Experimental Analysis

Little is known about how the expansion of state pre-kindergarten (pre-k) programs affects low-income children with disabilities in Head Start. Using almost 30 years of administrative data of all Head Start programs and a differences-in-differences design, this study tests the possibility that, as state pre-k differentially draws relatively more advantaged children from the pool of eligible 4-year-olds, Head Start taps into their relative programmatic strengths and serves more children with disabilities. We found that, overall, the introduction of state pre-k was associated with a 1 percentage point (7%) decrease in Head Start enrollment of children with disabilities. However, Head Start programs located in school systems did experience an increase in their enrollment of children with disabilities identified before Head Start enrollment. We also found that the decrease was primarily driven by children with speech impairment, suggesting that state pre-k might affect the Head Start enrollment of children with disabilities through “cream-skimming” because services for these children are relatively more common and less expensive. Implications for future research and practice are discussed.
Model-based Fusion of Surface Electromyography with Kinematic and Kinetic Measurements for Monitoring of Muscle Fatigue

This study proposes a novel method for monitoring muscle fatigue using muscle-specific dynamic models which relate joint time-frequency signatures extracted from the relevant electromyogram (EMG) signals with the corresponding estimated muscle forces. Muscle forces were estimated using physics-driven musculoskeletal models which incorporate muscle lengths and contraction velocities estimated from the available kinematic and kinetic measurements. For any specific individual, such a muscle-specific dynamic model is trained using EMG and movement data collected in the early stages of an exercise, i.e., during the least-fatigued behavior. As the exercise or physical activity of that individual progresses and fatigue develops, residuals yielded by that model when approximating the newly arrived data shift and change because of the fatigue-induced changes in the underlying dynamics. In this paper, we propose quantitative evaluation of those changes via the concept of a muscle-specific Freshness Index (FI) which at any given time expresses overlaps between the distribution of that muscle’s model residuals observed on the most recently collected data and the distribution of modeling residuals observed during non-fatigued behavior. The newly proposed method was evaluated using data collected during a repetitive sawing motion experiment with 12 healthy participants. The performance of the FI as a fatigue metric was compared with the performance of the instantaneous frequency of the relevant EMG signals, which is a more traditional and widely used metric of muscle fatigue. It was found that the FI reflected the progression of muscle fatigue with desirable properties of stronger monotonic trends and smaller noise levels compared to the traditional, instantaneous frequency-based metrics.
A Moving Object Tracking Technique Using Few Frames with Feature Map Extraction and Feature Fusion

Moving object tracking techniques using machine and deep learning require large datasets for neural model training. New strategies need to be invented that utilize smaller data training sizes to realize the impact of large-sized datasets. However, current research does not balance the training data size and neural parameters, which creates the problem of inadequacy of the information provided by the low visual data content for parameter optimization. To enhance the performance of moving object tracking that appears in only a few frames, this research proposes a deep learning model using an abundant encoder–decoder (a high-resolution transformer (HRT) encoder–decoder). An HRT encoder–decoder employs feature map extraction that focuses on high resolution feature maps that are more representative of the moving object. In addition, we employ the proposed HRT encoder–decoder for feature map extraction and fusion to reimburse the few frames that have the visual information. Our extensive experiments on the Pascal DOC19 and MS-DS17 datasets have implied that the HRT encoder–decoder abundant model outperforms those of previous studies involving few frames that include moving objects.
Driverless Industry: Current State, Business Model, Challenges and Prospects

Digital transformation in the automotive industry promotes the emergence of autonomous vehicles, having a significant impact on people’s daily life and microeconomic environment. This paper presents the current situation of the self-driving industry, its prospects, and the potential value chain in the future. Being the bellwether in the self-driving industry, Waymo has had the largest driverless taxi service in the world. Although there are many obstacles in the process of autonomous vehicles being the mainstream, its future is still promising. We predict the changes in the value chain mainly come from driverless technology and its convenience. This research could enable autonomous vehicle manufacturers to know which aspects should be developed into core competencies.
Genome survey of pistachio (Pistacia vera L.) accessions revealed by Start Codon Targeted (SCoT) markers

Pistachio (Pistacia vera L.) is the only cultivated and commercially important species in the genus Pistacia, consisting of a deciduous, dioeciously and wind-pollinated at least 11 tree species. Pistacia vera is native to north Afghanistan, northeast Iran, and central Asian republics. To investigate the genetic diversity of pistachio (Pistacia vera), we genotyped 30 cultivars of this species using 10 Start Codon Targeted (SCoT) markers. The SCoT markers generated 9-25 alleles (155 in total) with an average of 16 per locus. The highest value of percentage polymorphism (61.99%) was observed in Ghafori Rafsanjan (cultivars No.27) which shows high value for gene diversity (0.42) and Shanon, information index (0.39). Genotype Shahpasand (Pust Ghermez) (No.10) has the lowest value for percentage of polymorphism (20%) and the lowest value for Shanon, information index (0.15), and He (0.010). Genetic similarity values obtained from Dice’s coefficient ranged from 0.66 (between Akbari (Pust Ghermez) and Badami Dishkalaghi) to 0.88 (between populations Menghar Kalaghi and Kaleghochi (Pust Ghermez). The main objectives of this study were to assess the genetic diversity and genetic relationship of pistachio cultivars in Iran. These results could benefit Irainian pistachio germplasm collection, conservation and future breeding.
A study of tau lepton production in tt events with ATLAS at the LHC

A method is discussed for measuring the tt cross section from tau + jets events in early ATLAS data. Multivariant techniques were avoided in favour of simple cuts and the analysis was applied to 26.4pb\(^-\)\(^1\)of 2010 data. A cut and count technique was used to estimate the number of tt events in a window around the hadronic top mass peak. Subtraction of QCD background from data was performed by scaling events from a QCD enriched sample by the ratio of events in a sideband region. With the current dataset a statistical error is expected of the order of 400% and a measurement is not feasible at this stage. The systematic error on the tt selection eciency was estimated to be 50%. Simple luminosity scaling established that a measurement should become possible within the 2011-2013 LHC run. Once ATLAS has collected between 1 fb\(^-\)\(^1\) and 3 fb\(^-\)\(^1\) of data a fractional error of 20% on the expected number of signal events could be achieved. Suggestions are made for reducing the systematic uncertainty on the tt eciency.
Application of 3D Bioprinting in Urology

Tissue engineering is an emerging field to create functional tissue components and whole organs. The structural and functional defects caused by congenital malformation, trauma, inflammation or tumor are still the major clinical challenges facing modern urology, and the current treatment has not achieved the expected results. Recently, 3D bioprinting has gained attention for its ability to create highly specialized tissue models using biological materials, bridging the gap between artificially engineered and natural tissue structures. This paper reviews the research progress, application prospects and current challenges of 3D bioprinting in urology tissue engineering.
Growth of nanowire solar cells

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Nurses’ Clinical Decision-Making in a Changed COVID-19 Work Environment: A Focus Group Study

This study aims to explore how a changed COVID-19 work environment influences nurses’ clinical decision-making. Data were collected via three focus groups totaling 14 nurses working in COVID-19 pandemic wards at a Danish university hospital. The factors influencing decision-making are described in three themes; navigating in a COVID-19 dominated context, recognizing the importance of collegial fellowship, and the complexities of feeling competent. A strong joint commitment among the nurses to manage critical situations fostered a culture of knowledge-sharing and drawing on colleagues’ competencies in clinical decision-making. It is important for nurse leaders to consider multiple factors when preparing nurses not only to work in changing work environments, but also when nurses are asked to work in environments and specialties that deviate from their usual routines.
Twenty Challenges in Incident Planning

Abstract Disasters create overwhelming demands to affected communities and pose unique problems that complicate efforts of orchestrating the response. It is in such environments of uncertainty, operational friction, time-constraints and the need for interagency coordination that disaster and crisis managers are required to develop incident plans to address multiple demands. Based on observations from 50 disaster exercises, we have identified twenty critical points in incident planning, that is, those incident planning activities which are most challenging for emergency managers, are poorly implemented or otherwise constitute an area for improvement. The most challenging components of the incident planning process were information gathering from the field, running estimates of the situation, response-generated demands, resource capabilities and mobilization time, course of action development and analysis, and decision-making under uncertainty. In addition, this study identified three good practices in incident planning. First, the process is iterative and planners revisit several steps in a back-and-forth fashion. Second, both rational and intuitive decision-making processes are likely to be used during the course of any one incident, based on the time available for planning. Third, better plans are produced when flexibility is built into courses of action to address expected developments of situation or when decision-making is decentralized.
Representation of financial markets in macro-economic transition models—a review and suggestions for extensions

As the energy transition accelerates and renewable energy technologies become cost-competitive with fossil fuels in many countries, the availability of finance could become a bottleneck. Integrated assessment models (IAMs) and other macro-economic transition (MET) models typically do not feature detailed financial markets and do not sufficiently consider financing barriers and opportunities for the transition to carbon neutrality. While progress has been made in the representation of financial markets in macro-models since the financial crisis of 2008 the focus has been on financial (in)stability of the financial sector, not its ability to finance investment projects in the energy transition. Hence, a crucial gap remains, preventing macro model-based analysis of financing barriers and policy interventions that may accelerate the energy transition. In this article we review how state-of-the-art macro-economic models consider the financial sector. From this review we identify what elements are still missing to adequately model the financial dynamics and challenges for the energy transition specifically. Based on a discussion of relevant parts of the finance literature, we then propose four steps to improve the representation of finance in global IAMs and MET models more generally.
THE IMPACT OF OPEN-FIELD AND PROTECTED CULTIVATION ON BIOCHEMICAL CHARACTERISTICS OF BANANAS (Musa spp. AAA)

Bananas have been grown in both open-field and protected cultivation in the subtropics. There are a very limited number of publications focusing on the impact of cultivation systems on the physico-chemical characteristics of bananas. For this reason, we assessed these fruit characteristics including sugars, malic acid, L-ascorbic acid, macro and micro nutrients well as fat and fatty acids of green and ripe bananas (Musa spp. AAA) in both cultivation systems. Experimental results have showed that many parameters affected the fruit ripening stage more than the cultivation system. Sucrose was the most abundant sugar followed by fructose and glucose in both the unripe and the ripe fruit stages. Sugar content, malic acid and L-ascorbic acid were higher in the ripe stage compared to the green stage. The cultivation system affected only glucose content, however, malic acid and L-ascorbic acid were not affected by the cultivation system. The most abundant macro and micro elements found were potassium and iron respectively. Cultivation system affected only potassium, zinc and manganese contents. Nitrogen and phosphorous, were found to be higher in the ripe stage. However, calcium, zinc, manganese and cupper were higher in the unripe stage. The fatty acid showed low value in the unripe stage for both cultivation systems. The concentration of MUFAs were found to be higher in the unripe stage for open-field condition while SFAs and PUFAs percentage were found to be higher in both cultivation systems. Experimental results clearly showed that physico-chemical characteristics of bananas were mainly affected by the ripening stage while the cultivation systems only affected a few characteristics.
Study on the Enhanced Remediation of Petroleum-Contaminated Soil by Biochar/g-C3N4 Composites

This work developed an environmentally-friendly soil remediation method based on BC and g-C3N4, and demonstrated the technical feasibility of remediating petroleum-contaminated soil with biochar/graphite carbon nitride (BC/g-C3N4). The synthesis of BC/g-C3N4 composites was used for the removal of TPH in soil via adsorption and photocatalysis. BC, g-C3N4, and BC/g-C3N4 have been characterized by scanning electron microscopy (SEM), Brunauer–Emmett–Teller surface area analyzer (BET), FT-IR, and X-ray diffraction (XRD). BC/g-C3N4 facilitates the degradation due to reducing recombination and better electron-hole pair separation. BC, g-C3N4, and BC/g-C3N4 were tested for their adsorption and photocatalytic degradation capacities. Excellent and promising results are brought out by an apparent synergism between adsorption and photocatalysis. The optimum doping ratio of 1:3 between BC and g-C3N4 was determined by single-factor experiments. The removal rate of total petroleum hydrocarbons (TPH) by BC/g-C3N4 reached 54.5% by adding BC/g-C3N4 at a dosing rate of 0.08 g/g in a neutral soil with 10% moisture content, which was 2.12 and 1.95 times of BC and g-C3N4, respectively. The removal process of TPH by BC/g-C3N4 conformed to the pseudo-second-order kinetic model. In addition, the removal rates of different petroleum components in soil were analyzed in terms of gas chromatography–mass spectrometry (GC-MS), and the removal rates of nC13-nC35 were above 90% with the contaminated soil treated by BC/g-C3N4. The radical scavenger experiments indicated that superoxide radical played the major role in the photocatalytic degradation of TPH. This work definitely demonstrates that the BC/g-C3N4 composites have great potential for application in the remediation of organic pollutant contaminated soil.