Miracle-dz/UniFAR-FTUs huggingface dataset:
Prosumers strategy for DHC energy flow optimization

This article introduces the proposal of discrete model of district heating and cooling system (DHC) for energy flow optimization. The aim is to achieve the best solution of the objective function, usually determined by minimizing the production and distribution costs and providing meets the needs of energy consumers. The model also introduces the idea of general prosumers strategy, where all active elements within the modern DHC system are representing by prosumers object. The prosumers are perceived as objects able to actively participate in the planning of production and consumption of energy. It is assumed that the general behaviour of the object in DHC is the same, no matter how they differ in sizes and designs. Thus, all the objects are defined by two characteristics - the ability to produce and consume. The model based on this basic principle, of course, with the most accurate information about the particular values at a time, object properties and other, should provide tools for simulation and control of modern DHC, possibly superior units as Smart Energy Grids - understood as a system integrating Smart Grids (electricity) and Smart Thermal Grids (heat a cool).
Modeling and analysis for the units load regulation by condensate throttling

By condensate throttling to regulate the thermal power unit load,the store energy of the unit can be utilized effectively and the load response rate of the unit can be improved.Meanwhile this method cannot decrease unit thermal efficiency and cannot increase the thick-walled metal heat stress.According to the law of mass conservation and the law of energy conservation,the dynamic model of low-pressure heater and deaerator are constructed.And then the mechanism of condensate throttling for increasing turbine power is explained.For a 600 MW typical unit,according to the design parameters the static and dynamic characteristics of the process are analyzed,and finally the transfer function of condensate water flow versus units load is gained.The amount and the velocity of the unit releasing store energy by condensate throttling and by main steam throttling are approximately same.If this scheme is introduced in unit coordinated control system design,the stability of the unit main parameters on the variable load process will be improved.
Influence of Spacer Thickness on the Noise Performance in InP HEMTs for Cryogenic LNAs

InP high electron mobility transistors (InP HEMTs) with different spacer thickness 1 to 7 nm in the InAlAs-InGaAs heterostructure have been fabricated and characterized at 5 K with respect to electrical dc and rf properties. The InP HEMT noise performance was extracted from gain and noise measurements of a hybrid low-noise amplifier (LNA) at 5 K equipped with discrete transistors. When biased for optimal noise operation, the LNA using 5 nm spacer thickness InP HEMTs achieved the lowest average noise temperature of 1.4 K at 4–8 GHz. The InP HEMT channel noise was estimated from the drain noise temperature which confirmed the minimum in noise temperature for the 5 nm spacer thickness InP HEMT. It is suggested that the spacer thickness acts to control the degree of real-space transfer of electrons from the channel to the barrier responsible for the observed noise variation in the cryogenic InP HEMTs.
Neural Network Model Compression Algorithms for Image Classification in Embedded Systems

: This paper introduces model compression algorithms which make a deep neural network smaller and faster for embedded systems. The model compression algorithms can be largely categorized into pruning, quantization and knowledge distillation. In this study, gradual pruning, quantization aware training, and knowledge distillation which learns the activation boundary in the hidden layer of the teacher neural network are integrated. As a large deep neural network is compressed and accelerated by these algorithms, embedded computing boards can run the deep neural network much faster with less memory usage while preserving the reasonable accuracy. To evaluate the performance of the compressed neural networks, we evaluate the size, latency and accuracy of the deep neural network, DenseNet201, for image classification with CIFAR-10 dataset on the NVIDIA Jetson Xavier.
Improved Multistage Continuous-Time Pipelined Analog-to-Digital Converters and the Implicit Decimation Property

The continuous-time pipeline (CTP) analog-to-digital converter is an emerging technique that combines the benefits of pipelining with continuous-time operation. Prior-art multistage CTP ADCs have employed stages with identical transfer functions. This work proposes the use of non-identical (and appropriately chosen) transfer functions for different stages of the pipeline. We investigate the benefits of this approach when compared with conventional techniques. We also demonstrate that the sharp filtering offered by a multi-stage CTP can be exploited to implicitly decimate the output sequence of the converter. This is accomplished by clocking the back-end ADC at a lower rate, and by appropriately modifying the digital reconstruction filters. The implicit-decimation theory is supported with measurement results from a three-stage CTP designed in a 65nm CMOS process. The converter achieves 70.4dB SNDR in a 100MHz bandwidth with its front-end operating at <inline-formula> <tex-math notation="LaTeX">$f_{s}\,{=}\,800$ </tex-math></inline-formula>MHz, while the back-end samples at <inline-formula> <tex-math notation="LaTeX">$f_{s}/2$ </tex-math></inline-formula>.
Regulatory Roles of Histone Modifications in Filamentous Fungal Pathogens

Filamentous fungal pathogens have evolved diverse strategies to infect a variety of hosts including plants and insects. The dynamic infection process requires rapid and fine-tuning regulation of fungal gene expression programs in response to the changing host environment and defenses. Therefore, transcriptional reprogramming of fungal pathogens is critical for fungal development and pathogenicity. Histone post-translational modification, one of the main mechanisms of epigenetic regulation, has been shown to play an important role in the regulation of gene expressions, and is involved in, e.g., fungal development, infection-related morphogenesis, environmental stress responses, biosynthesis of secondary metabolites, and pathogenicity. This review highlights recent findings and insights into regulatory mechanisms of histone methylation and acetylation in fungal development and pathogenicity, as well as their roles in modulating pathogenic fungi–host interactions.
Sustainable Tourism in the Pandemic Era: A Case Study of Japan

The sustainable tourism concept has been evolving continually and respectively with modern society’s views on sustainability. The tourism industry constantly faces new challenges showing weak points and providing opportunities for further concept development. With the focus on Japan as a case study, this empirical research discusses the insights of key stakeholders about managing sustainable tourism development during the crisis. This research takes the COVID-19 pandemic as an example of a crisis, which provides an opportunity for the sustainable tourism concept for further evolution. The results indicated that public and private sector stakeholders have different visions of sustainable tourism development. Japan’s current public sector approach to it implies resolving the issue of overtourism in main tourism destinations and providing comfortable living for local communities. However, it does not have any implications for making tourism more resilient to external crises. The proposals of stakeholders for response measures for future sustainable tourism development and related policies included the establishment of a crisis management system in the tourism sphere, focus on the development of domestic tourism, creation of proper guidelines for the tourism industry for actions in case of crisis, revision of traditional tourism techniques, the establishment of “new lifestyle”/adaptation to “with Corona” era, focusing on online business/ tourism experience, focus on the development of small groups tours and individual tours, development of flexibility and adaptivity to changes in social conditions, incorporation of public health-related issues, non-contact content expansion, individual approach to different areas, and regional cooperation incorporation.
Endothelial Brg1 fine-tunes Notch signaling during zebrafish heart regeneration

Myocardial Brg1 is essential for heart regeneration in zebrafish, but it remains unknown whether and how endothelial Brg1 plays a role in heart regeneration. Here, we found that both brg1 mRNA and protein were induced in cardiac endothelial cells after ventricular resection, and endothelium-specific over-expression of dominant-negative Xenopus Brg1 (DN-xBrg1) inhibited myocardial proliferation and heart regeneration and increased cardiac fibrosis. RNA-seq and ChIP-seq analysis revealed that the endothelium-specific over-expression of DN-xBrg1 changed the levels of H3K4me3 modifications in the promoter regions of the zebrafish genome and induced abnormal activation of Notch family genes upon injury. Mechanistically, Brg1 interacted with lysine demethylase 7aa (Kdm7aa) to fine-tune the level of H3K4me3 within the promoter regions of Notch family genes and thus regulated Notch gene transcription. Together, this work demonstrates that the Brg1-Kdm7aa-Notch axis in cardiac endothelial cells, including the endocardium, regulates myocardial proliferation and regeneration via modulating the H3K4me3 of the Notch promoters in zebrafish.
Blockade of endocannabinoid hydrolytic enzymes attenuates precipitated opioid withdrawal symptoms in mice

Δ 9 -tetrahydrocannbinol (THC), the primary active constituent of Cannabis sativa , has long been known to reduce opioid withdrawal symptoms. Although THC produces most of its pharmacological actions through the activation of CB 1 and CB 2 cannabinoid receptors, the role these receptors play in reducing the variety of opioid withdrawal symptoms remains unknown. The endogenous cannabinoids, N -arachidonoylethanolamine (anandamide; AEA) and 2-arachidonylglycerol (2-AG), activate both cannabinoid receptors, but are rapidly metabolized by fatty acid amide hydrolase (FAAH) and monoacylglycerol lipase (MAGL), respectively. The objective of this study was to test whether increasing AEA or 2-AG, via inhibition of their respective hydrolytic enzymes, reduces naloxone-precipitated morphine withdrawal symptoms in in vivo and in vitro models of opioid dependence. Morphine-dependent mice challenged with naloxone reliably displayed a profound withdrawal syndrome, consisting of jumping, paw tremors, diarrhea, and weight loss. THC and the MAGL inhibitor, JZL184 dose-dependently reduced the intensity of most measures through the activation of CB 1 receptors. JZL184 also attenuated spontaneous withdrawal signs in morphine-dependent mice. The FAAH inhibitor, PF-3845, reduced the intensity of naloxone-precipitated jumps and paw flutters through the activation of CB 1 receptors, but did not ameliorate incidence of diarrhea or weight loss. In the final series of experiments, we investigated whether JZL184 or PF-3845 would attenuate naloxone-precipitated contractions in morphine-dependent ilea. Both enzyme inhibitors attenuated the intensity of naloxone-induced contractions, though this model does not account mechanistically for the autonomic withdrawal responses (i.e., diarrhea) observed in vivo . These results indicate that endocannabinoid catabolic enzymes are promising targets to treat opioid dependence. served as The mice weighed between 26 and 30 g and were housed 6-8 per cage in a temperature controlled (20-22 o C) environment, in an American Association for the Accreditation of Laboratory Animal Care-approved facility. The mice were kept on a 12 h light/ dark cycle, with all experiments being performed during the light cycle. Food and water were available ad libitum . The study was performed with the approval of the Institutional Animal Care and Use Committee at Virginia Commonwealth University in accordance with the Guide for the Care and Use of Laboratory Animals. measures analysis of of test of
E NERGY H ARVESTING R ECTENNA D ESIGN FOR E NHANCED N ODE LIFETIME IN WSN S

With the rising popularity and advent of many services on Wireless Sensor Networks (WSNs), there is a compelling need to have energy-efficient solutions. The sensors and devices are powered by batteries whose life is limited, and at times it is impossible to replace the batteries, especially in remote applications. In such a scenario, Energy Harvesting (EH) stands as an undisputed candidate for enhancing the network lifetime. Radio Frequency (RF) energy is the most commonly available, ubiquitous, and reliable energy source among all the available energy sources. While RF signal carries both information and energy, EH is possible for long-distance and mobile environments. This work discusses initial research in the domain of EH in wireless networks via Radio Frequency (RF) signals. The paper presents an EH rectenna for energy harvesting over 2.45 GHz (Wi-Fi band). The receiving antenna is designed to pick up the radio signal in the RF range (2.45 GHz) from the free space. The four patch elements design has an antenna substrate made with RT with a dielectric constant of 2.2. The paper presents the simulation results of the basic parameters of the antenna, such as return loss, input impedance, bandwidth, gain, directivity, and efficiency. H-shaped slot antenna and modified H-shaped antenna (with circular slot) are designed with a gain of 8.24 dB and 8.32 dB, return loss of -10 dB and -16 dB, and bandwidth of 64.8 MHz and 868 MHz. The high gain, large bandwidth, properly matched impedance for minimum return loss, and high efficiency of the modified H-shaped patch antenna makes it eligible for energy harvesting.
Feasibility Study of Smash Book based Guided Inquiry as Chemistry Learning Media on Buffer Solution Material

: Less interesting and less engaging in chemistry learning media makes chemistry learning boring and difficult. Smash book based guided inquiry on buffer solution material is an innovative development of chemistry learning media that facilitates students to studies in an interesting, active and creative way. The aim of this development research is to test the feasibility of smash book based guided inquiry media as chemistry learning media on buffer solutions material. This research uses R & D research design. Instrument in this research is questionnaire of feasibility smash book media on buffer material from validators and students. The data was analyzed using descriptive technique. The result of research and development shows that the smash book based guided inquiry is feasible to be used as chemistry learning media on buffer solutions material.
A Multi-Granularity Opinion Summarization Method

1 Existing opinion mining (OM) is limited to 2 applications on commercial reviews, with 3 aspect and sentiment of the opinions in a 4 coarse-grained form. In this paper, we 5 further explore the definition of OM by 6 extending the concepts of aspect and 7 sentiment , and propose an opinion 8 summarization method based on M ulti-9 granularity C lustering and B ERT (Jacob et 10 al., 2018), i.e., MCB for emergent online 11 discussion record in keeping with the 12 further definition. A supporting Chinese 13 corpus, ZH45 comprising 45 groups of 14 discussion, and assorted metrics are also 15 proposed. Experiments based on ZH45 16 and the metrics demonstrate that MCB 17 produces succinct and insightful opinion 18 summaries. 19
Learning Slip with a Patterned Capacitive Tactile Sensor

— The task of dynamically manipulating objects within a robotic hand presents ongoing challenges. In particular, friction and slip often dictate task success yet remain difficult to measure directly, quickly, and accurately; this includes both the detection of slip events and slip speed. Complex solutions exist that involve training a control policy using neural networks, with image-based sensors or external cameras, or when contact geometry can be inferred. Using only a capacitive sensor with a `nib`-patterned structure, we attempt to demonstrate the sensor’s ability to detect slip speed during uninterrupted contact where geometry cannot be inferred, while benefitting from faster sensing, cheaper construction, and smaller profile. We hope that by collecting vibration amplitude and frequency and applying supervised learning techniques to directly measure slip speed we can guide an implementation of manipulation controls without a priori assumptions about object properties, such as friction or geometry.
Hybrid maximum principle with regionally switching parameter

In this paper we consider a Mayer optimal control problem governed by a hybrid control system defined over a partition of the state space. We assume that the control system depends on a regionally switching parameter that remains constant in each region but that can change its value when the state position crosses interfaces. This new framework allows to deal, as a particular case, with control systems including non-control regions. In this paper our objective is to provide the corresponding necessary optimality conditions in a Pontryagin form. Our approach is based on a thorough sensitivity analysis of the hybrid control system under needle-like perturbations of the control and under convex perturbations of the parameter. To this aim we invoke implicit function arguments to deal with the interface crossings that are assumed to be transverse. The paper is concluded with a simple academic example showing that our framework allows to fill a gap in the literature.
Erythrocyte TransfusionRemedy or Poison?

1153 December 2012 I N this issue of Anesthesiology, Karkouti et al.1 use population-based administrative healthcare databases to estimate the impact of erythrocyte transfusion on postoperative outcomes after elective hip or knee replacement surgeries. They demonstrate that there is a major discrepancy in the estimation of the impact of erythrocyte transfusion according to the approach used to analyze the data. By using an approach based on logistic regression comparing transfused and not transfused patients, they observed that erythrocyte transfusion was deleterious; in contrast, using an alternative approach based on characteristics of the centers studied, erythrocyte transfusion was found to have no impact on mortality. These contradictory results require further discussion. Our focus in this editorial is to try to better understand the causes of this discrepancy and to evaluate how these findings might impact our actual clinical management of these patients and the consequences for further research.
Job Quality of Wage Employment across Developing Countries 1

Measuring the quality of employment across countries has been challenging, so much work relies on a single indicator, such as formality or wages. This paper contributes to the policy discussion by proposing a global measure of job quality for wage employment. We assemble a harmonized dataset of labor force and household surveys, across 40 developing countries, and create a measure of job quality across four dimensions: sufficient income, access to employment benefits, job stability, and adequate working conditions. Results show significant variation of job quality across countries, economic sectors, and sociodemographic characteristics including age, location, and level of education. Countries in the Latin America and the Caribbean region have relatively higher levels of job quality, while countries in Sub-Saharan Africa display the lowest levels of job quality. Most workers in the finance and business services, public administration, and utilities sectors have, on average, better jobs. Higher education matters for securing greater job quality in the form of higher earnings, benefits, and job stability. Finally, the average job quality of wage employment is relatively similar between men and women in all dimensions but income.
Distributed Generation Islanding Effect on Distribution Networks and End User Loads Using the Master-Slave Islanding Method

This study aims to address the feasibility of planned islanding operation and to investigate the effect of unplanned islanding using the master-slave islanding method for controlling the distributed generation units during grid-connected and islanding operation. Neplan desktop power simulation tool was used for the modelling and simulation of a realistic MV network with four different distributed generation technologies (diesel, gas, hydro and wind) along with their excitation and governor control systems, while an exponential model was used to represent the loads in the network. The dynamic and steady state behavior of the four distributed generation technologies were investigated during grid-connected operation and two transition modes to the islanding situation, planned and unplanned. The obtained results that validated through various case studies have shown that a suitable planned islanding transition could provide support to critical loads at the event of electricity utility outages.
Nonlinear Dynamic Characterization of Electro-statically Actuated Sub-micro Beam Resonator

Electro-statically actuated sub-micro beam resonators, which can be used as sensors in biology or filters in wireless communications, have gotten significant attention due to their simple geometries, excellent electrical and mechanical characteristics and extensively potential applications. In this paper, we present comprehensive analysis of the nonlinearity in frequency response of sub-micro cantilevers, clamped-clamped and beam resonators which are actuated by electro-static force. The spring hardening effects and softening effects are observed in the experiment. It is found that the nonlinearity is relatively independent of the AC voltage, but is markedly enhanced by increasing of DC voltage. However, the response nonlinearity of the doubly clamped beam shows different feature from that of the cantilever. The reason is also explored in this paper. A nonlinear model is introduced to explain the nonlinearity of the frequency response. This investigation provides us an understanding of the nonlinear dynamic characteristics of sub-micro beam resonators. It is helpful for us to study the sensitivity when the beam is used in a detecting system or used to be a sensor.
Few Shot Image Generation via Implicit Autoencoding of Support Sets

Recent generative models such as generative adversarial networks have achieved remarkable success in generating realistic images, but they require large training datasets and computational resources. The goal of few-shot image generation is to learn the distribution of a new dataset from only a handful of examples by transferring knowledge learned from structurally similar datasets. Towards achieving this goal, we propose the “Implicit Support Set Autoencoder” (ISSA) that adversarially learns the relationship across datasets using an unsupervised dataset representation, while the distribution of each individual dataset is learned using implicit distributions. Given a few examples from a new dataset, ISSA can generate new samples by inferring the representation of the underlying distribution using a single forward pass. We showcase significant gains from our method on generating high quality and diverse images for unseen classes in the Omniglot and CelebA datasets in few-shot image generation settings.