Miracle-dz/UniFAR-FTUs huggingface dataset:
Exhaust valve profile modulation for improved diesel engine curb idle aftertreatment thermal management

Rapid warm-up of a diesel engine aftertreatment system (ATS) is a challenge at low loads. Modulating exhaust manifold pressure (EMP) to increase engine pumping work, fuel consumption, and as a result, engine-outlet temperature, is a commonly used technique for ATS thermal management at low loads. This paper introduces exhaust valve profile modulation as a technique to increase engine-outlet temperature for ATS thermal management, without requiring modulation of exhaust manifold pressure. Experimental steady state results at 800 RPM/1.3 bar BMEP (curb idle) demonstrate that early exhaust valve opening with negative valve overlap (EEVO+NVO) can achieve engine-outlet temperature in excess of 255°C with 5.7% lower fuel consumption, 12% lower engine out NOx and 20% lower engine-out soot than the conventional thermal management strategy. Late exhaust valve opening with internal EGR via reinduction (LEVO+Reinduction) resulted in engine-outlet temperature in excess of 280°C, while meeting emission constraints at no fuel consumption penalty. This work also demonstrates that LEVO in conjunction with modulation of exhaust manifold pressure results in engine-outlet temperature in excess of 340°C while satisfying desired emission constraints. Aggressive use of LEVO can result in engine-outlet temperatures of 460°C, capable of active regeneration of DPF at curb idle, without the significant increase in engine-out soot emissions seen in previously studied strategies.
How Can Teachers Build Partnerships with Lower-educated Parents in Support of Young Children’s Oral Language Development? Evaluation of an Adaptive Program

ABSTRACT Research Findings: The parental role in supporting young children’s oral language development at home is crucial for children’s language and literacy development. However, there is limited expertise in how teachers can support lower-educated parents effectively to enhance their interactions with their children and stimulate the use of language. Therefore, teachers need specific knowledge and training in how to establish partnerships with these parents and provide support adapted to the home language environment. This multiple case study describes the evaluation of a program for teachers aiming to build school-family partnerships focused on stimulating young children’s oral language development. It investigates abilities of 14 teachers to adhere to the program principles and to adapt these to parents’ needs by means of triangulation, using teacher self-reports and observations before and after implementation of the program. This study shows how teachers can increase their competences to work with parents and how this change contributes to professional satisfaction. Practice or Policy: This study contributes to understanding how an adaptive approach creates opportunities for teachers to extend their roles in classrooms and build partnerships with all parents, bridging the gap between lower-educated families and schools as the two most important domains where young children acquire language.
Microwave-assisted Functionalization of Carbon Nanostructured Materials

Microwaves have proven to be a powerful ally in any synthetic effort, shortening reaction times considerably and in some cases facilitating the reaction by offering higher yields or fewer byproducts. Since the mid '90s microwave-assisted synthesis has found its way into carbon nanostructures, offering significant advantages towards their functionalization. In this review, an overview of the lat- est trends in microwave-assisted functionalization of carbon nanostructured materials is presented covering major breakthroughs achieved in the last years for this novel, intriguing and non-conventional synthetic approach.
Biophysical and Computational Landscapes of Mycobacterial Pyrophosphatase: A Closer View of Drug Repurposing With Different Natural and Synthetic Compounds.

Mycobacterial pyrophosphatase (Mt-ppa) play essential role in bacterial in vitro and in vivo survival. This family of proteins reacts on pyrophosphates to release orthophosphates and protect bacteria from pyrophosphates toxicity. Rv3628 encodes pyrophosphate protein which is a type I pyrophosphate protein. This protein is engaged in hydrolysis of tri and diphosphates (majorly GTP, ATP and GDP) and its catalysis is metal ion dependent. Mt-ppa was showed efficient interaction with GTP molecule, whose Kd was 37. 9µM, ΔH was -11Kcal/mol and ΔG was -6.06Kcal/mol. The protein was interacted with ATP family genes that resemble that it is participator in conversion of diphosphates moiety to the residual monophosphates. W102G, V150G, F44G, I119G, L93F, F3G, F122G, I108G, L32G, M82G, Y17G, L59G, V5G, V26G, I7G, W140D, W140G, W140A, F80G, W140S, L49G, L56G, I9G, V60G, V19G, V92G, L28G, L61G, Y126E and F123G are the top 30 mutation hits and Y126G, Y42G, R30G, E8G, K16G are top mutational hits in active site of Mt-ppa. Mt-ppa is temperature and pH sensitive as increasing temperature and pH decreases protein stability. It is also the receptor for several kinases that phosphorylate this protein at different Ser/Thr/Tyr sites. Virtual screening of 700 compounds from herbal ingredient targets (HITs) subset of zinc database give ZINC000003979028, ZINC000003870413, ZINC000003870412, ZINC000150338758, ZINC0000070450948, ZINC000150338754, ZINC000095098891, ZINC000000119985, ZINC000005085286 as the top target hits and Mac0182344 and NAV_2729 as the top GTPase inhibitor that can target and hinders Mt-ppa activity.
Development of AI-Based Diagnostic Model for the Prediction of Hydrate in Gas Pipeline

For the stable supply of oil and gas resources, industry is pushing for various attempts and technology development to produce not only existing land fields but also deep-sea, where production is difficult. The development of flow assurance technology is necessary because hydrate is aggregated in the pipeline and prevent stable production. This study established a system that enables hydrate diagnosis in the gas pipeline from a flow assurance perspective. Learning data were generated using an OLGA simulator, and temperature, pressure, and hydrate volume at each time step were generated. Stacked auto-encoder (SAE) was used as the AI model after analyzing training loss. Hyper-parameter matching and structure optimization were carried out using the greedy layer-wise technique. Through time-series forecast, we determined that AI diagnostic model enables depiction of the growth of hydrate volume. In addition, the average R-square for the maximum hydrate volume was 97%, and that for the formation location was calculated as 99%. This study confirmed that machine learning could be applied to the flow assurance area of gas pipelines and it can predict hydrate formation in real time.
Notes on the earthworm species, Metaphire anomala (Michaelsen, 1907) (Clitellata, Megascolecidae) in Southern Vietnam, with descriptions of two new species

Integrative taxonomy was employed to exploit the differences between the known Metaphire anomala (Michaelsen, 1907) and other specimens collected in Vietnam. The results brought to light two new species, namely Metaphire iranomala sp. nov. and Metaphire decemtheca sp. nov. The former is easily recognised by having male pores on xix and four pairs of spermathecal pores on 5/6/7/8/9 while the latter is distinguished by having fi ve pairs of spermathecal pores on 4/5/6/7/8/9. The K2P distances of the fragment of the cytochrome c oxidase subunit I (COI) gene are 13.1% between M. iranomala sp. nov. and M. anomala (Michaelsen, 1907) and 18% between M. decemtheca sp. nov. and Metaphire grandiverticulata Nguyen & Lam, 2017. The intraspecifi c divergences are 1.5%–10.6% for M. iranomala sp. nov. and 2.1%–11.4% for M. decemtheca sp. nov.
Elucidation of the inhibitory activity of plant-derived SARS-CoV inhibitors and their potential as SARS-CoV-2 inhibitors

Abstract Several drugs are now being tested as possible therapies due to the necessity of treating SARS-CoV-2 infection. Although approved vaccines bring much hope, a vaccination program covering the entire global population will take a very long time, making the development of effective antiviral drugs an effective solution for the immediate treatment of this dangerous infection. Previous studies found that three natural compounds, namely, tannic acid, 3-isotheaflavin-3-gallate and theaflavin-3,3-digallate, are effective proteinase (3CLpro) inhibitors of SARS-CoV (IC50 <10 µM). Based on this information and due to the high sequence identity between SARS-CoV and SARS-CoV-2 3CLpro, these three compounds could be candidate inhibitors of SARS-CoV-2 3CLpro. This paper explores the structural and energetic features that guided the molecular recognition of these three compounds for dimeric SARS-CoV-2 and SARS-CoV 3CLpro, the functional state of this enzyme, using docking and MD simulations with the molecular mechanics-generalized-born surface area (MMGBSA) approach. Energetic analysis demonstrated that the three compounds reached good affinities in both systems in the following order: tannic acid > 3-isotheaflavin-3-gallate > theaflavin-3,3-digallate. This tendency is in line with that experimentally reported between these ligands and SARS-CoV 3CLpro. Therefore, tannic acid may have clinical usefulness against COVID-19 by acting as a potent inhibitor of SARS-CoV-2 3CLpro. Communicated by Ramaswamy H. Sarma
Enacting citizenship through participation in a technological society: a longitudinal three-year study among people with dementia in Sweden

Abstract The role of Everyday Technology (ET) use is presented as subsidiary or neutral in policy for age- and dementia-friendly communities; and yet, research suggests that older people, especially those with dementia, experience increased challenges using ET in their everyday lives. Through the lens of micro-citizenship, the study aims to deepen the knowledge about how use of ET outside the home, including portable ETs, relates to participation in places visited within public space among people with dementia over time. Using a longitudinal study design, 35 people with dementia were recruited at baseline and followed over three years. Data were collected through semi-structured interviews using standardised questionnaires: the Participation in ACTivities and Places OUTside Home Questionnaire (ACT-OUT) and the Everyday Technology Use Questionnaire (ETUQ). Random intercept modelling and descriptive statistics were used to analyse the data. Throughout the three-year study, decreasing use of ET outside the home, including portable ETs, was associated with decreasing participation in places visited within public space, in a statistically significant way when controlling for age (F = 7.59, p = 0.01). The findings indicate that facilitating access and use of ET outside the home, among people with dementia, should be integral to promoting and maintaining participation in age- and dementia-friendly communities.
Sheet Resistance Measurements of Conductive Thin Films: A Comparison of Techniques

Conductive thin films are an essential component of many electronic devices. Measuring their conductivity accurately is necessary for quality control and process monitoring. We compare conductivity measurements on films for flexible electronics using three different techniques: four-point probe, microwave resonator and terahertz time-domain spectroscopy. Multiple samples were examined, facilitating the comparison of the three techniques. Sheet resistance values at DC, microwave and terahertz frequencies were obtained and were found to be in close agreement.
Narcissism as a predictor of number of selfies: a cross-cultural examination of Japanese and American postings

ABSTRACT Social Networking Sites (SNS) user behavior has been discussed in association with SNS user personality characteristics, such as narcissism. However, gender and cultural influences on the relationship between selfie posting on SNS and narcissism remain unclear. Thus, the present study included gender and culture to investigate the relationship between narcissism and selfie posting using 232 Japanese and 481 American college students. The main findings include: (a) while the data failed to show a significant difference in level of narcissism across culture, significant gender differences were found in each culture; (b) our data show no significant difference in the number of selfies across culture/gender or level of narcissism; (c) self-esteem moderated the relationship between narcissism and the number of selfies for American male college students.
Framing clinical and translational science: Examining the strategic social media communications of NCATS-funded CTSAs

Abstract Introduction: Many Clinical and Translational Science Awards (CTSAs) focus their energy on operational aspects of running their hub, but may not devote enough energy and resources toward branding and effective communication. However, CTSAs have an important mission when it comes to communicating effectively with their stakeholders through social media. Using framing theory as the underpinning, the purpose of this content analysis is to investigate the ways in which CTSAs use Twitter to communicate with their various stakeholders, the type of content they post, and the type of engagement their tweets garner. Methods: We examined 349 tweets posted from January 2019 to January 2020 from 19 CTSA Twitter accounts (sampled from a total of 35 CTSA accounts). A thematic codebook was generated using tweets randomly chosen from the sample. Content analysis was performed on the entire tweet sample by four coders using the codebook (alpha = 0.89). Results: CTSAs tweeted the most about events (29.8%), and the least about study recruitment (2.01%). Most tweets included images (59.31%) and hashtags (51.29%), but received little user engagement on the average post (average: 4.38 likes and 1.94 retweets). CTSAs tweeted most from 10 a.m. to 12 p.m. PST and received the most engagement. Most CTSAs had a dedicated person (e.g., manager, coordinator) handling their communications. Discussion: Our analysis shows multiple opportunities for CTSAs to engage with stakeholders and the public, as well as standardize and improve their Twitter communications to effectively reach a broader audience.
Predictive Intelligent Decision Support Model in Forecasting of the Diabetes Pandemic Using a Reinforcement Deep Learning Approach

: Diabetes has since become global pandemic – which must be diagnosed early enough if the patients are to survive a while longer. Traditional means of detection has its limitations and defects. The adoption of data mining tools and adaptation of machine intelligence is to yield an approach of predictive diagnosis that offers solution to task, which traditional means do not proffer low-cost-effective results. The significance thus, is to investigate data feats rippled with ambiguities and noise as well as simulate model tractability in order to yield a low-cost and robust solution. Thus, we explore a deep learning ensemble for detection of diabetes as a decision support. Model achieved a 95-percent accuracy, with a sensitivity of 0.98. It also agrees with other studies that age, obesity, environ-conditions and family relation to the first/second degrees are critical factors to be watched for type-I and type-II management. While, mothers with/without previous case of gestational diabetes is confirmed if there is: (a) history of babies with weight above 4.5kg at birth, (b) resistant to insulin showing polycystic ovary syndrome, and (c) have abnormal tolerance to insulin.
Simulated Space Environmental Factors of Weightlessness, Noise and Low Air Pressure Differentially Affect the Circadian Rhythm and Gut Microbiome

Backgroundhe circadian clock extensively regulates physiology and behavior. In space, the astronauts encounter many environmental factors that are dramatically different from those on earth, however, the effects of these factors on circadian rhythms and the mechanisms remain largely unknown. The present study aimed to investigate the changes in the mouse circadian rhythm and gut microbiome under simulated space capsule conditions, including microgravity, noise and low atmospheric pressure.ResultsNoise and low atmospheric pressure were loaded in the capsule while the conditions in the animal room remained constant. The mice in the capsule showed disturbed locomotor rhythms and faster adaptation to a 6-h phase advance. RNA sequencing of hypothalamus samples revealed that microgravity simulated by hind limb unloading (HU) and exposure to noise and low atmospheric pressure led to decreases in the quantities of differentially expressed genes (DEGs), including circadian clock genes. Changes in the rhythmicity of genes implicated in pathways of cardiovascular deconditioning and more concentrated circadian phases were found under HU or noise and low atmospheric pressure. Furthermore, 16S rRNA sequencing revealed dysbiosis in the gut microbiome, and noise and low atmospheric pressure may repress the temporal discrepancy in the microbiome community structure induced by microgravity. Changes in diel oscillation were observed in a number of gut bacteria with critical physiological consequences in metabolism and immunodefense.ConclusionsOur data demonstrate that in addition to microgravity, exposure to noise and low atmospheric pressure affect the robustness of circadian rhythms and the community structure of the gut microbiome, and these factors may interfere with each other in their adaptation to respective conditions. These findings are important to further our understanding of the alteration of circadian rhythms in the space complex environment.
Factors That Influence Nitrous Oxide Emissions from Agricultural Soils as Well as Their Representation in Simulation Models: A Review

Nitrous oxide (N2O) is a long-lived greenhouse gas that contributes to global warming. Emissions of N2O mainly stem from agricultural soils. This review highlights the principal factors from peer-reviewed literature affecting N2O emissions from agricultural soils, by grouping the factors into three categories: environmental, management and measurement. Within these categories, each impact factor is explained in detail and its influence on N2O emissions from the soil is summarized. It is also shown how each impact factor influences other impact factors. Process-based simulation models used for estimating N2O emissions are reviewed regarding their ability to consider the impact factors in simulating N2O. The model strengths and weaknesses in simulating N2O emissions from managed soils are summarized. Finally, three selected process-based simulation models (Daily Century (DAYCENT), DeNitrification-DeComposition (DNDC), and Soil and Water Assessment Tool (SWAT)) are discussed that are widely used to simulate N2O emissions from cropping systems. Their ability to simulate N2O emissions is evaluated by describing the model components that are relevant to N2O processes and their representation in the model.
Case-study analysis of dielectric response for cesium lead halide perovskites

Cesium lead halide perovskites are characterized by unique dielectric response properties that are significant for potential applications. Modeling the dielectric response of these materials with respect to underlying physical processes is therefore useful. A case study analysis is presented of the dielectric response of cesium lead halide perovskites, using computational experiments and theory, helping to formulate quantitative dielectric response functions. In particular, the electronic structure and the dielectric function can be calculated using computational methods based on density function theory (DFT). Our analysis uses the Vienna Ab-initio Simulation Package (VASP), where the dielectric function is calculated by solving the Bethe-Salpeter equation on top of electronic structure calculations within the GW0 method.
Safety-Critical Event Identification on Mountain Roads for Traffic Safety and Environmental Protection Using Support Vector Machine with Information Entropy

Traffic accidents, which cause loss of life and pollution, are a social concern. The complex traffic environment on mountain roads increases the harm caused by traffic accidents. This study aimed to identify safety-critical events related to accidents on mountain roads to understand the causes of the accidents, improve traffic safety, and protect the environment. In this study, a naturalistic-driving data collection system, consisting of approximately 8000 km of naturalistic-driving data from 20 drivers driving on mountain roads, was developed. Using these data, a comparative analysis of the identification performance of the support vector machine (SVM), backpropagation neural network (BPNN), and convolutional neural network (CNN) methods was conducted. The SVM was found to yield optimal performance. To improve the identification performance, the yaw rate and information entropy of the data were added as input variables. The improved SVM method yielded an identification accuracy of 90.64%, which was approximately 15% higher than that yielded by the traditional SVM. Moreover, the false positive and false negative rates of the improved SVM were reduced by approximately 10% and 20%, respectively, compared with the traditional SVM. The results demonstrated that the improved SVM method can identify safety-critical events on mountain roads accurately and efficiently.
An Ultra-Low-Power K-Band 22.2 GHz-to-26.9 GHz Current-Reuse VCO Using Dynamic Back-Gate-Biasing Technique

An ultra-low-power K-band LC-VCO (voltage-controlled oscillator) with a wide tuning range is proposed in this paper. Based on the current-reuse topology, a dynamic back-gate-biasing technique is utilized to reduce power consumption and increase tuning range. With this technique, small dimension cross-coupled pairs are allowed, reducing parasitic capacitors and power consumption. Implemented in SMIC 55 nm 1P7M CMOS process, the proposed VCO achieves a frequency tuning range of 19.1% from 22.2 GHz to 26.9 GHz, consuming only 1.9 mW–2.1 mW from 1.2 V supply and occupying a core area of 0.043 mm2. The phase noise ranges from −107.1 dBC/HZ to −101.9 dBc/Hz at 1 MHz offset over the whole tuning range, while the total harmonic distortion (THD) and output power achieve −40.6 dB and −2.9 dBm, respectively.