Miracle-dz/UniFAR-FTUs huggingface dataset:
Fully solution-processed InSnO/HfGdO X thin-film transistor for light-stimulated artificial synapse

In recent years, the research interest in brain-inspired light-stimulated artificial synaptic electronic devices has greatly increased, due to their great potential in constructing low-power, high-efficiency, and high-speed neuromorphic computing systems. However, in the field of electronic synaptic device simulation, the development of three-terminal synaptic transistors with low manufacturing cost and excellent memory function still faces huge challenges. Here, a fully solution-processed InSnO/HfGdO X thin film transistor (TFT) is fabricated by a simple and convenient solution process to verify the feasibility of light-stimulated artificial synapses. This experiment investigated the electrical and synaptic properties of the device under light stimulation conditions. The device successfully achieved some important synaptic properties, such as paired-pulse facilitation, excitatory postsynaptic current and the transition from short-term memory to long-term memory. In addition, the device also exhibits brain-like memory and learning behaviors under different colors of light stimulation. This work provides an important strategy for the realization of light-stimulated artificial synapses and may have good applications in the field of artificial neuromorphic computing by light signals in the future.
Global Analysis of the WOX Transcription Factor Gene Family in Populus × xiaohei T. S. Hwang et Liang Reveals Their Stress−Responsive Patterns

The WUSCHEL−related homeobox (WOX) family is a group of plant−specific transcription factors that play important regulatory roles in embryo formation, stem cell stability, and organogenesis. To date, there are few studies on the molecular mechanisms involved in this family of genes in response to stress. Thus, in this study, eight WOX genes were obtained from an endemic Chinese resilient tree species, Populus × xiaohei T. S. Hwang et Liang. Bioinformatic analysis showed that the WOX genes all contained a conserved structural domain consisting of 60 amino acids, with some differences in physicochemical properties. Phylogenetic analysis revealed that WOX members were divided into three evolutionary clades, with four, one, and three members in the ancient, intermediate, and modern evolutionary clades, respectively. The conserved structural domain species as well as the organization and gene structure of WOX genes within the same subfamily were highly uniform. Chromosomal distribution and genome synteny analyses revealed seven segmental−duplicated gene pairs among the PsnWOX gene family that were mainly under purifying selection conditions. Semi−quantitative interpretation (SQ−PCR) analysis showed that the WOX gene was differentially expressed in different tissues, and it was hypothesized that the functions performed by different members were diverse. The family members were strongly and differentially expressed under CdCl2, NaCl, NaHCO3, and PEG treatments, suggesting that WOX genes function in various aspects of abiotic stress defense responses. These results provide a theoretical basis for investigating the morphogenetic effects and abiotic stress responses of this gene family in woody plants.
Joint routing and topology management for energy-efficiency on-demand Ad Hoc network

A joint routing and topology management algorithm(JRT) was proposed to solve the problems encountered while applying sleep-based energy-efficiency algorithms to the on-demand Ad Hoc networks.Associating routing operation with node sleep,JRT made the network pre-sense the traffic information.In order to keep the network connectivity,JRT adopted one conservative method which can detect local partition based on the 2-hop neighbor information.Thus it provided reliable service for packet delivery and saved energy efficiently.Simulation results show that JRT is adaptive to network traffic,and yields better network capacity and energy conservation.
Probe into the Investment Portfolio Optimization for Grid Construction Project

For the grid company,a single optimal grid construction project does not necessarily guarantee the maximum effectiveness of the entire company.Therefore,using investment portfolio optimization concept,based on the analysis and assessment of a single project,the paper build a project portfolio optimization model and definition an objective function for maximizing the economic benefits of the whole company.By simulation analysis with Matlab tools,the reliability and usability in the grid construction projects portfolio optimization of this model is validated.
Influence of mesh grid and computational domain on FDS simulation

Seeing that FDS is a fire-spreading and smoke transport simulation software widely used in scientific research and engineering projects,this paper has done investigations on how to utilize the case of Steckler room fire test and made some quantitative studies over the mesh independency property by using the relative similarity analysis method.Further discussions have also been made with the sensitivity of the simulation results to the mesh grid in the fire source area,buoyancy plume area and smoke layer area,with the impact of the computational domain on the simulation result properly interpreted.The correlation value of the simulation results tends to increase while defining the mesh grid,and finally falls into the interval between 0.99 and 1.The impact of the mesh grid size on the correlation value of the simulation is likely to be most severe in the fire source area,less in the buoyancy plume area and the least in the smoke layer area.The correlation value of the results gained from the computational domain,the same in value with the Steckler room and that from the extended domain,tends to be relatively low,whereas that between the results in the domain extended to the distinctive size should be rather high.Thus,it can be concluded that the correlation analysis can be expected to become a reasonable method to assess the mesh grid independency.However,the sensitivity to the mesh grid size tends to drop from the combustion region to the smoke layer area,which suggests the grid size shrinking in the fire area is an effective way to gain more accuracy in an acceptable executive time.In addition,the choice of the computational domain may have an evident effect on the air flow-in and flow-out in the room, which is likely to further impact the temperature and velocity distribution in the building.Therefore,reasonable extension of the computational domain has been proved to be necessary to acquire accurate results.
Individual Perception of Telehealth: Validation of a German Translation of the Telemedicine Perception Questionnaire and a Derived Short Version

Telehealth is a growing domain with particular relevance for remote patient monitoring. With respect to the biopsychosocial model of health, it is important to evaluate perception and satisfaction with new methods in telehealth as part of an integrative approach. The Telemedicine Perception Questionnaire (TMPQ) is a 17-item questionnaire measuring patients’ perception of and satisfaction with telecare. We translated this survey into German and determined its validity and reliability in 32 adolescents and adults. Furthermore, we derived a short version of the TMPQ, named Patient and Physician Satisfaction with Monitoring (PPSM), which is a 5-item questionnaire that can be administered to both patients and physicians. Validity and reliability were tested in 32 patients and 32 physicians. Crohnbach’s α for the translated TMPQ was 0.76, and the German version yielded high validity (intraclass correlation coefficient (ICC) 0.995). We tested the PPSM in both patients and physicians and found acceptable values for Crohnbach’s α (0.72 and 0.78) with excellent validity (ICC 0.965). We therefore concluded from this small study that both German versions of the TMPQ and PPSM can be used to investigate the acceptance of telehealth applications.
FAKTOR YANG MEMPENGARUHI HASIL BELAJAR SISWA MENGGUNAKAN ANALISIS DISKRIMINAN MI NURUL IMAN KOTA TANGERANG SELATAN

This study aims to determine what factors influence learning achievement. This study aimed to create a discriminant model of learning achievement from the influencing factors. The object of this research is the students of MI Nurul Iman, South Tangerang City. The variables used are six variables. The dependent variable in this study is the average report card, while the independent variables are motivation (X1), Learning Methods (X2), Teacher Competence (X3), Parental Environment (X3), School Infrastructure (X5), Community Environment (X6), which used as many as 56 samples. Based on the results of the output of the discriminant model using the SPSS version 21 program, it shows that the factors that affect student learning outcomes are School Facilities (X5). The discriminant model formed to determine the discriminant function is from the factors that affect learning achievement. Apart from 1, these variables are not used. Then the following function is obtained: D = -3,980 + 0,369X5
A Unified View of Computational Electromagnetics

This article presents a unified description of numerical methods for solving electromagnetic field problems. Traditionally, these methods are considered to be independent and alternative ways of solving Maxwell’s equations or equations derived therefrom. However, they all are projective approximations of the unknown solution by known expansion or basis functions with unknown amplitude coefficients that are determined using the so- called method of weighted residuals (MWR). This common feature forms the proposed unifying framework that may serve both as a systematic introduction to computational electromagnetics and as a way to provide insight into the nature, strengths, and limitations of the various algorithms used by present and future field solvers. For convenience, the fundamental equations and concepts of electromagnetics are summarized in order to facilitate the demonstration of the unified approach. Our aim is to provide students, designers, and researchers with a framework for developing new numerical algorithms, to guide users in the selection and application of electromagnetic design tools, and to foster informed engineering judgment. This article also serves as a review and summary of earlier theoretical works reported in different places and at different times.
The Stabilizing Effects of Publishing Strategic Central Bank Projections

Expectations are among the main driving forces for economic dynamics. Therefore, managing expectations has become a primary objective for monetary policy seeking to stabilize the business cycle. In this paper, we study whether central banks can manage private-sector expectations by means of publishing one-period ahead inflation projections in a New Keynesian learning-to-forecast experiment. Subjects in the experiment observe these projections along with the historic development of the economy and subsequently submit their own one-period ahead inflation forecasts. In this context, we find that the central bank can significantly manage private-sector expectations and that this management strongly supports monetary policy in stabilizing the economy. Moreover, published central bank inflation projections drastically reduce the probability of a deflationary spiral after strong negative shocks to the economy.
Porous Polydimethylsiloxane Elastomer Hybrid with Zinc Oxide Nanowire for Wearable, Wide-Range, and Low Detection Limit Capacitive Pressure Sensor

We propose a flexible capacitive pressure sensor that utilizes porous polydimethylsiloxane elastomer with zinc oxide nanowire as nanocomposite dielectric layer via a simple porogen-assisted process. With the incorporation of nanowires into the porous elastomer, our capacitive pressure sensor is not only highly responsive to subtle stimuli but vigorously so to gentle touch and verbal stimulation from 0 to 50 kPa. The fabricated zinc oxide nanowire–porous polydimethylsiloxane sensor exhibits superior sensitivity of 0.717 kPa−1, 0.360 kPa−1, and 0.200 kPa−1 at the pressure regimes of 0–50 Pa, 50–1000 Pa, and 1000–3000 Pa, respectively, presenting an approximate enhancement by 21−100 times when compared to that of a flat polydimethylsiloxane device. The nanocomposite dielectric layer also reveals an ultralow detection limit of 1.0 Pa, good stability, and durability after 4000 loading–unloading cycles, making it capable of perception of various human motions, such as finger bending, calligraphy writing, throat vibration, and airflow blowing. A proof-of-concept trial in hydrostatic water pressure sensing has been demonstrated with the proposed sensors, which can detect tiny changes in water pressure and may be helpful for underwater sensing research. This work brings out the efficacy of constructing wearable capacitive pressure sensors based on a porous dielectric hybrid with stress-sensitive nanostructures, providing wide prospective applications in wearable electronics, health monitoring, and smart artificial robotics/prosthetics.
How Do Young People Deal with Border Tensions When Making Climate-Friendly Food Choices? On the Importance of Critical Emotional Awareness for Learning for Social Change

If we are going to be able to fight climate change in an effective way there is a need for a profound sustainability transformation of society. The question is how everyday pro-environmental behavior such as climate-friendly food choices should be looked upon in this context: as something that hides the need for structural change, or as a starting point for a profound transformation? The aim is to discuss how emotions related to conflicts encountered when trying to make everyday climate-friendly food choices in a society that is not always sustainable can be used to promote transformational learning. Interviews were performed with 15 adolescents. Emotions felt in relation to conflicts and how the youth cope were explored. The results show that the youth mainly felt individualized emotions of guilt, helplessness, and irritation and that they coped primarily by distancing themselves from emotions felt, but also sometimes in a problem-focused way and through positive reappraisal. Results are discussed in relation to theories about critical emotional awareness and prefigurative politics. It is argued that by taking account of emotional aspects related to everyday conflicts in a critical manner, issues such as justice could be brought to the surface and transformative learning could be enhanced.
Coevolutionary theory of hosts and parasites

Host and parasite evolution are closely intertwined, with selection for adaptations and counter‐adaptations forming a coevolutionary feedback loop. Coevolutionary dynamics are often difficult to intuit due to these feedbacks and are hard to demonstrate empirically in most systems. Theoretical models have therefore played a crucial role in shaping our understanding of host–parasite coevolution. Theoretical models vary widely in their assumptions, approaches and aims, and such variety makes it difficult, especially for non‐theoreticians and those new to the field, to: (1) understand how model approaches relate to one another; (2) identify key modelling assumptions; (3) determine how model assumptions relate to biological systems; and (4) reconcile the results of different models with contrasting assumptions. In this review, we identify important model features, highlight key results and predictions and describe how these pertain to model assumptions. We carry out a literature survey of theoretical studies published since the 1950s (n = 219 papers) to support our analysis. We identify two particularly important features of models that tend to have a significant qualitative impact on the outcome of host–parasite coevolution: population dynamics and the genetic basis of infection. We also highlight the importance of other modelling features, such as stochasticity and whether time proceeds continuously or in discrete steps, that have received less attention but can drastically alter coevolutionary dynamics. We finish by summarizing recent developments in the field, specifically the trend towards greater model complexity, and discuss likely future directions for research.
Evaluation of Hepatoprotective Potential of Stem Bark of Neolamarckia cadamba against Chloroform and Over dose of Iron Dextran Induced Hepatotoxicity in Experimental Swiss Albino Mice

Background: In general, use of herbal medicines are considered as the backbone in traditional system of medicines as it has been used for food, flavoring agents and in the form of medicines. Keeping in knowledge the increasing demand of herbal drugs over their synthetic counter parts and to restrain the worldwide problem of multidrug resistance (MDR) in hepatoprotective activity. Neolamarckia cadamba that is commonly called Cadamb is a standout amongst the most significant therapeutic plants having a place with the Rubiaceae family. It is one of such Ayurvedic cure that has been referenced in numerous Indian restorative written works. The arrangement of work includes gathering and confirmation of stem bark of cadamb plant pursued by shade drying, granulating, and extraction by two-fold cool maceration, phytochemical examination lastly screening of pharmacological exercises as expressed. Aim: The present study was carried out to establish hepatoprotective activity of hydro alcoholic extract of stem bark of Neolamarckia cadamba by using two established hepatotoxic screening models in Swiss albino mice (chloroform induced hepatotoxicity and iron over dose induced hepatotoxicity). Materials and Methods: The hepatoprotective activity of Neolamarckia cadamba was screened by hydro alcoholic extract of stem bark of Neolamarckia cadamba (NCHAE). The experimental animals were treated with corn oil and chloroform for a period of 7 days at a dose of 0.75mg/kg body weight, p.o to induce hepatotoxicity. In the second experimental model over dose of iron dextran induced hepatic damage was performed by administering 100 mg/kg, i.p.upto7 days, 3 consecutive periods. Blood samples were collected for the estimation of biochemical parameters and histopathological changes in liver was also performed. Silymarin (50 mg/kg; body weight) was used as standard referral of hepatoprotective agent. Results: Chloroform and iron over dose treatment were induced higher levels of liver marker enzymes and showed damage of hepatocytes. In histopathological findings there were significant opposed treatment with Neolamarckia cadamba dose dependently. The results indicated that biochemical changes produced by both the hepatotoxicity models were restored to normal by NCHAE. In the present study, the results of NCHAE was found significant hepatoprotective effect (***p<0.01) against both the inducing agents, which was indicated by the enhancement in biochemical parameters. Conclusion: The current study confirmed the hepatoprotective effect of NCHAE against the chloroform induced hepatotoxicity and iron over dose induced hepatotoxicity models and the activity is likely related to its potent antioxidant and ironchelating property. NCHAE therefore needs to be for further in-deep studies to correlate its bioactive constituents responsible for the pharmacological activity selected.
Data-Driven Fault Diagnosis for PEM Fuel Cell System Using Sensor Pre-Selection Method and Artificial Neural Network Model

Fault diagnosis is a critical process for the reliability and durability of proton exchange membrane fuel cells (PEMFCs). Due to the complexity of internal transport processes inside the PEMFCs, developing an accurate model considering various failure mechanisms is extremely difficult. In this paper, a novel data-driven approach based on sensor pre-selection and artificial neural network (ANN) are proposed. Firstly, the features of sensor data in time-domain and frequency-domain are extracted for sensitivity analysis. The sensors with poor response to the changes of system states are filtered out. Then experimental data monitored by the remaining sensors are utilized to establish the fault diagnosis model by using the ANN model. Levenberg-Marquardt (LM) algorithm, resilient propagation (RP) algorithm, and scaled conjugate gradient (SCG) algorithm are utilized in the neural network training, respectively. The diagnostic results demonstrate that the diagnostic accuracy rate reaches 99.2% and the recall rate reaches 98.3% by the proposed methods. The effectiveness of the proposed method is verified by comparing the diagnostic results in this work and that by support vector machine (SVM) and logistic regression (LR). Besides, the high computational efficiency of the proposed method supports the possibility of online diagnosis. Meanwhile, detecting the faults in the early stage can provide effective guidance for fault tolerant control of the PEMFCs system.
Bioinformatics analysis of miRNAs identifies enrichment of axon guidance pathway genes in ovarian cancer stem cells

Ovarian cancer ranks fifth in cancer deaths among women, accounting for more deaths than any other cancer of the female reproductive system. Cancer stem cells (CSCs) are a small population of cancer cells that are believed to be the reason for cancer initiation and tumor relapse. Recently, the important role of MicroRNAs (miRNAs) in maintaining and regulating CSCs through targeting multiple oncogenic signaling pathways has been reported. Previously, we have found differentially expressed miRNAs in ovarian CSCs compared with bulk cancer cells in SKOV3 and Kuramochi cell lines. Here using online miRNA target prediction tools combined with a web interface tool MMiRNA-Tar, we identified the downstream targets of these differentially expressed miRNAs. After filtering, we found 271 novel targets of downregulated miRNAs and 442 novel targets of upregulated miRNAs, which may potentially control cancer cell stemness. Among this gene list, we further validated the potentially important role of the axon guidance pathway genes by using multiple bioinformatic analyses. In summary, our study identified that dysregulated miRNA can facilitate maintenance of CSCs by regulating the axon guidance pathway genes, which will ultimately help us find novel cancer therapeutic targets.
Combined Techniques for Bilateral Maxillary and Nasal Reconstruction After Ablative Surgery for Adenoid Cystic Carcinoma

Indolent tumor growth up to large tumor masses and broad infiltration of surrounding tissue are the most typical characteristics of malignant tumors of the nasal cavity and paranasal sinuses. If surgery is a therapeutic option, extended resections and complex reconstruction modalities have to be taken into account. We present a combination of different reconstruction techniques to restore midface integrity after bilateral maxillectomy, including parts of the nasal skeleton, for adenoid cystic carcinoma. After obtaining tumor-free margins, reconstruction was performed using a microvascular double-flap technique to achieve a neo-maxilla and soft tissue lining of the oral cavity, dental implantology with prosthetic restoration and the insertion of a patient-specific implant for nasal re-shaping and stability. In cases of extended maxillary resection, a combination of different techniques can achieve sufficient functional and aesthetic rehabilitation, and restore quality of life. Further studies are warranted to evaluate the long-term stability of such complex reconstructions. However, local tumor control remains the highest priority and will be essential for years.