Miracle-dz/UniFAR-FTUs huggingface dataset:
Acid Gas Removal Unit in Waste-to-energy Plants: Data-driven Models for Advanced Control

Flue gas cleaning is a crucial step in waste-to-energy (WtE) plants that process municipal solid waste. This paper analyzes the acid gas removal line of an Italian WtE plant, based on the injection of dry alkaline solid sorbents (calcium hydroxide Ca(OH)2 and sodium bicarbonate NaHCO3) for the abatement of hydrogen chloride, HCl. The aim of the study is to develop different data-driven models for the description of the acid gas treatment process with the final goal of implementing them in model-based controllers for optimizing the feed rate of alkaline reactants thus minimizing solid waste production. System identification and validation techniques have been applied to process data. Different input-output and state-space models are identified by optimizing related model orders and validated on different routine data. The comparison of two system structures (sequential and holistic) evidenced the importance of measuring additional internal variables to maintain low system orders and delays. Anyway, results appear reliable and promising for control purposes, making different modeling approaches and control structures possible.
Moving away from the “Repression-Resistance” Paradigm: The Effects of Civil/Uncivil Disagreements on Political Deliberation in China

This study engages in the academic effort of moving beyond the “repression-resistance” lens by shedding light on the civic function of exposure to cross-cutting arguments and their (in-) civility on individual’s expression willingness and discursive quality in China’s cyberspace. While civility and dissonant-viewpoint exposure are viewed as the hallmark of political deliberation and public sphere in most Western societies, whether their potential could be realised in a censored yet increasingly pluralist media space in China remains a question. Through experiment method (N = 1064), participants were exposed to dissonant (civil/uncivil) viewpoints that were selected, manipulated, and presented as original Weibo posts, regarding a controversial marital policy. Our results illustrate that exposure to civil yet reasoned cross-cutting information significantly provokes individuals’ willingness to engage in a manner of reciprocal civility. Implications are discussed for deliberation studies and internet governance.
A Scalable Blockchain Framework for Secure Transactions in IoT-Based Dynamic Applications

The essential characteristics of blockchain, such as immutability and auditability, are leading to its increasing incorporation into society. The Internet of Things (IoT) aims to create a decentralized framework for IoT and enhance security. The processing of transactions for different IoT applications poses challenges for the convergence of IoT and blockchain due to varying performance requirements. In addition, it is important to note that the dispersed IoT system’s membership may change when an IoT device adds or departs from it. As the system becomes dynamic, it presents new difficulties for managing devices. Accordingly, a dynamic application block generation (DABG) scheme for blockchain-enabled IoT with dynamic device management and conditional traceability is proposed. To begin, it is necessary to construct a framework for an IoT system based on a consortium blockchain. This framework should consist of structures for dynamic application transactions and blocks, as well as a consensus mechanism. Miners are presented in distinct ways to adaptively process urgent and routine application transactions. A protocol based on group signature, known as DABG, is proposed for this framework. It is possible to achieve nonframeability, traceability, and anonymity by the use of the group signature. The suggested method may quickly validate transactions, manage devices in a dynamic manner, enable conditional traceability while maintaining data security, and keep users’ privacy intact. This is made possible by merging time-bound keys in the group signatures and node in the blockchain. Extensive testing has shown that the strategy in question has the potential to achieve very high levels of effectiveness.
Cooperative Partial Task Offloading and Resource Allocation for IIoT Based on Decentralized Multiagent Deep Reinforcement Learning

Edge computing has become increasingly important to fulfill the diversified Quality-of-Service (QoS) or Quality-of-Experience (QoE) demands for Industrial Internet of Things (IIoT) applications, such as machine condition monitoring, fault diagnosis, intelligent production scheduling, and production quality control. Due to the heterogeneity of IIoT systems, it is of urgent necessity to concentrate on the cloud–edge–end cooperative partial task offloading and resource allocation (CPTORA) problem for realizing workload balancing, efficient resource utilization, and better QoS/QoE of IIoT applications. However, the challenge lies in how to make real-time, accurate, decentralized task offloading (TO) and resource allocation (RA) decisions for dynamic and device-intensive IIoT. Therefore, this work examines the CPTORA problem for IIoT, aiming at minimizing its long-run overall delay and energy costs. To lower the problem complexity, this problem is decomposed into the TO subproblem and the RA subproblem. Then, an improved soft actor–critic-based decentralized multiagent deep reinforcement learning (MADRL) algorithm is proposed to address the TO subproblem, where each IIoT device can learn its globally optimal policy and make its decisions independently. This algorithm innovatively combines the divergence regularization, the distributional reinforcement learning, and the value function decomposition methods to improve convergence speed and accuracy of the existing MADRL methods. After receiving the TO decisions of every IIoT device, every edge server employs the Lagrange multiplier method and Karush–Kuhn–Tucker condition to solve its RA subproblem. The experimental results show that the proposed algorithm decreases the overall delay and energy costs more effectively, compared to the other state-of-the-art MADRL approaches.
Impact of a pyridazine derivative on tripartite synapse ultrastructure in hippocampus: a three-dimensional analysis

Introduction We previously discovered a pyridazine derivative compound series that can improve cognitive functions in mouse models of Alzheimer’s disease. One of the advanced compounds from this series, LDN/OSU-0215111-M3, was selected as the preclinical development candidate. This compound activates local protein translation at the perisynaptic astrocytic process (PAP) and enhances synaptic plasticity sequentially. While biochemical evidence supports the hypothesis that the compound enhances the structural plasticity of the tripartite synapse, its direct structural impact has not been investigated. Methods Volume electron microscopy was used to study the hippocampal tripartite synapse three-dimensional structure in 3-month-old wild-type FVB/NJ mice after LDN/OSU-0215111-M3 treatment. Results LDN/OSU-0215111-M3 increased the size of tertiary apical dendrites, the volume of mushroom spines, the proportion of mushroom spines containing spine apparatus, and alterations in the spine distribution across the surface area of tertiary dendrites. Compound also increased the number of the PAP interacting with the mushroom spines as well as the size of the PAP in contact with the spines. Furthermore, proteomic analysis of the isolated synaptic terminals indicated an increase in dendritic and synaptic proteins as well as suggested a possible involvement of the phospholipase D signaling pathway. To further validate that LDN/OSU-0215111-M3 altered synaptic function, electrophysiological studies showed increased long-term potentiation following compound treatment. Discussion This study provides direct evidence that pyridazine derivatives enhance the structural and functional plasticity of the tripartite synapse.
Geocoded data structures and their applications to Earth science investigations

A geocoded data structure is a means for digitally representing a geographically referenced map or image. The characteristics of representative cellular, linked, and hybrid geocoded data structures are reviewed. The data processing requirements of Earth science projects at the Goddard Space Flight Center and the basic tools of geographic data processing are described. Specific ways that new geocoded data structures can be used to adapt these tools to scientists' needs are presented. These include: expanding analysis and modeling capabilities; simplifying the merging of data sets from diverse sources; and saving computer storage space.
Understanding the drivers of destination equity in the post-pandemic era: the case of Australia

ABSTRACT Drawing on the appraisal theory of emotions and based on an online Qualtrics survey conducted among members of the Australian consumer panel (n = 357), this study examined destination equity considering the changing travel preferences in the post COVID-19 pandemic era. The findings empirically support that in addition to conventional destination equity drivers, tourists in the post-pandemic era consider the internal environment when deciding on a travel destination. Peace of mind was identified as a key manoeuvring factor influencing tourists’ behaviours such as higher payment and share-of-wallet. Theoretical and managerial implications of the findings are presented.
Etude d'un problème d'interaction fluide-structure : modélisation, analyse, stabilisation et simulations numériques

Ce travail de these porte sur l'etude d'un systeme d'interaction fluide-structure. Nous en traitons de nombreux aspects allant de sa modelisation jusqu'a l'etude de sa stabilisation et de sa simulation numerique. Le premier chapitre du manuscrit aborde la modelisation du systeme ainsi que l'existence de solutions fortes en temps petits. Le fluide est represente par les equations de Navier-Stokes incompressibles. La structure est deformable et depend d'un nombre fini de parametres. Nous obtenons ses equations en appliquant un principe des travaux virtuels. Le systeme d'equations final est non lineaire. Nous prouvons l'existence locale d'une solution a ce systeme, dans un premier temps sur le systeme linearise autour de l'etat nul. Puis, nous prouvons l'existence de solutions en temps petits au systeme non lineaire grâce a un argument de point fixe. Le deuxieme chapitre traite de la stabilisation par feedback autour d'un etat stationnaire non nul du systeme presente dans le Chapitre 1. L'operateur de feedback est determine a partir de l'analyse du probleme linearise autour de l'etat stationnaire et de la resolution d'une equation de Riccati. Le resultat de stabilisation portant sur le systeme non lineaire requiert des donnees petites et est obtenu par un argument de point fixe. Le troisieme chapitre se concentre sur les aspects numeriques de ce probleme. La construction de l'operateur de feedback correspond a la version discretisee de celle proposee dans le Chapitre 2. Le systeme fluide-structure est simule en utilisant une methode de domaines fictifs.
Ultrasensitive photodetector based on 2D WS2/AgInGaS quantum dots heterojunction with interfacial charge transfer

Tungsten disulfide (WS2), as a typical member of transition metal chalcogenides (TMDs), has attracted extensive research interest in optoelectronics, especially photodetectors. However, the performance of photodetectors based on monolayer WS2 is restricted to weak light absorption. Here, AgInGaS quantum dots (AIGS-QDs) with a large absorption coefficient and high quantum efficiency are integrated onto WS2 atomic layers to achieve excellent photoelectric performance. Notably, the observed photoluminescence (PL) quenching and the reduction of the decay time of PL in the WS2/AIGS-QDs heterojunction confirm the interfacial charge transfer from AIGS-QDs to WS2 layer. The results show that type II energy band arrangement leads to the efficient separation of photoexcited carriers at the interface between WS2 and AIGS-QDs. This WS2/AIGS-QDs photodetector achieves an ultrahigh responsivity (R) of 3.3 × 103 A W−1, an external quantum efficiency (EQE) of 7.8 × 106% and a detectivity (D*) of 1.3 × 1013 Jones. Our work provides promising potential for future high-performance monolayer TMD-based photodetectors.
BUILT ENVIRONMENT: MODELLING THE URBAN SPACE

Abstract. In urban areas, the “built” is defined by many different elements. Not only buildings but also open spaces containing green areas, viability, urban furniture, underground facilities. While the H-BIM sector focuses, rightly, on buildings of great historical significance, in our case it is been consider a part of the built that it usually not analyse: the urban open space. One of the interesting themes is the possibility of having a single tool that integrates the different objects present in a complex environment such as the urban area. The process with BIM model could allow a huge saving in terms of time and costs considering public tender, maintenance or construction phase of a project. Facility management operating through BIM is another relevant theme considering the whole life of a construction. Finally, another important theme is the connections between elements above the ground (visible elements) and subsoil (not visible elements), not only for the administrations but also if related to the HBIM environment.The paper reports the analysis of the experience performed, particularly related to questions about detail and accuracy of the BIM model.A methodology for modelling open spaces is been assuming, it is described possible improvements and considerations on the result.
Selenium Partitioning and Food-Chain Transfer at the Salton Sea

With the habitat at the Salton Sea, California, expected to decline to conditions unsuitable for wildlife as the Sea shrinks in coming years, efforts are being made to restore this valuable wildlife area. Current plans involve construction of a series of Species Conservation Habitat (SCH) ponds at the south end of the Sea to replace some of the habitat lost and evaluate options for further restoration. There is concern for the accumulation of selenium (Se) in the SCH ponds to levels potentially toxic to the birds they are meant to protect.In order to evaluate potential Se risk in the SCH ponds, this study employed a novel selenium modeling approach in which Se concentrations in food web organisms were linked to stable isotope data. Two freshwater lakes in Imperial County, CA, Finney Lake and Ramer Lake, were chosen as surrogates for the proposed SCH ponds. Organisms from the aquatic food webs of the two lakes were collected and analyzed for both Se concentration and carbon and nitrogen stable isotope composition. Se concentration was plotted against delta 15N for each lake to develop an empirical relationship between position in the food web and Se concentration that was then used to predict Se concentrations in piscivore and invertivore birds.Results provide direct evidence for the bioaccumulation of Se in freshwater habitats at the Salton Sea, but indicate that birds should be at little or no risk from Se toxicity in freshwater systems such as those at Finney and Ramer Lakes. Even though multiple food web components had Se concentrations above established toxicity thresholds, predicted bird concentrations were either below or only slightly above a widely used threshold for reduced hatchability.
Machine Learning Solutions to Regional Surface Ocean δ18O‐Salinity Relationships for Paleoclimatic Reconstruction

Stable isotope‐based reconstructions of past ocean salinity and hydroclimate depend on accurate, regionally constrained relationships between the stable oxygen isotopic composition of seawater (δ18Osw) and salinity in the surface ocean. An increasing number of δ18Osw observations suggest greater spatial variability in this relationship than previously considered, highlighting the need to reassess these relationships on a global scale. Here, we use available, paired δ18Osw and salinity data (N = 11,119) to create global interpolations of each variable. We then use a self‐organizing map, a specialized form of machine learning, to define 19 regions with unique δ18Osw‐salinity relationships in the surface (<50 m) ocean. Inclusion of atmospheric moisture‐related variables and oceanic tracer data in additional self‐organizing map experiments indicates global surface δ18Osw‐salinity spatial patterns are strongly forced by the atmosphere, as the SOM spatial output is highly similar despite no overlapping input data. Our approach is a useful update to the previously delimited regions, and highlights the utility of neural network pattern extraction in spatiotemporally sparse data sets.
Petiveria alliacea Reduces Tumor Burden and Metastasis and Regulates the Peripheral Immune Response in a Murine Myeloid Leukemia Model

The poor response, adverse effects and drug resistance to treatment of acute myeloid leukemia (AML) have led to searching for safer and more effective therapeutic alternatives. We previously demonstrated that the alcoholic extract of Petiveria alliacea (Esperanza) has a significant in vitro antitumor effect on other tumor cells and also the ability to regulate energy metabolism. We evaluated the effect of the Esperanza extract in vitro and in vivo in a murine model of AML with DA-3/ER-GM cells. First, a chemical characterization of the extract was conducted through liquid and gas chromatography coupled with mass spectrometry. In vitro findings showed that the extract modulates tumor metabolism by decreasing glucose uptake and increasing reactive oxygen species, which leads to a reduction in cell proliferation. Then, to evaluate the effect of the extract in vivo, we standardized the mouse model by injecting DA-3/ER-GM cells intravenously. The animals treated with the extract showed a lower percentage of circulating blasts, higher values of hemoglobin, hematocrit, and platelets, less infiltration of blasts in the spleen, and greater production of cytokines compared to the control group. These results suggest that the antitumor activity of this extract on DA-3/ER-GM cells can be attributed to the decrease in glycolytic metabolism, its activity as a mitocan, and the possible immunomodulatory effect by reducing tumor proliferation and metastasis.
Connecting with Future Talent: A Review of Employer Value Propositions and Digital Media Channels for Sustainable Companies Targeting Generations Y and Z

Objective: This literature review aims to provide a comprehensive understanding of the employer value proposition of ethical and sustainable companies and the effective digital media channels that sustainable companies can use to attract and communicate with Generation Y and Z candidates. Design/Methods/Approach: The PRISMA systematic literature review method was combined with content analysis of selected articles from the Scopus and Web of Science databases. The selected articles were limited to those published within the last six years and in English. Findings: This study found that sustainable companies need to offer a corporate value proposition that prioritizes clear career progression, work-life balance, a supportive work atmosphere, and ethical aspects, such as reducing carbon footprint and promoting diversity and inclusion. These values are essential to Generations Y and Z, although the priority dimensions of their value propositions may differ. Companies utilize Digital media channels, including owned digital media, paid digital media by using paid endorsers or enhanced profiles on career websites, and earned digital media such as honest reviews on job board platforms and private social media from employees. Originality/Value: This review adds to the existing literature by comprehensively discussing the combined issues of employer value proposition, generational differences, and sustainability. Practical/Policy implication: This review's findings have implications for business and research practice, as sustainable companies can use this information to develop the most relevant corporate value propositions and communication strategies for future targeted talent. Companies can attract and retain top personnel and establish a positive employer brand by effectively communicating their sustainability practices and values. Additional empirical research could investigate the impact of other demographic and psychographic factors on the preferences and priorities of job seekers.
Performance Evolution of Combined Grid-Forming and Grid-Following Inverters with Different Filtering Mechanisms

This paper discusses the challenges faced by electric power systems due to the increasing use of inverter-based renewable energy resources (IBRs) operating in grid-following mode (GFL) and the limited support they provide for the grid’s reliability and stability. With increased IBRs connected to the grid, electric utilities are increasingly requiring IBRs to behave like traditional grid-forming (GFM) synchronous generators to provide support for inertia, frequency, voltage, black start capability, and more. The paper focuses on developing GFM inverter technologies with L, LC, and LCL filters and investigates the performance of combined GFM and GFL inverters with different filtering mechanisms when supplying different types of loads. It also emphasizes achieving voltage controllability at the point of common coupling of the GFM with the rest of an AC system. EMT simulation is utilized to investigate the interaction of combined GFM and GFL inverters with different filtering mechanisms. The research results will assist electric utilities in ensuring the reliability and stability of electric power systems in the future.
CirSAT: An Efficient Circuit-based SAT Solver via Fanout-driven Decision Heuristic

Circuit-based Boolean satisfiability (SAT) solver is efficient for solving electronic design automation (EDA) problems. Compared to widely-used conjunctive normal form (CNF)based SAT solvers, circuit-based SAT is rarely publicly available. In this paper, we propose an open-source circuit-based SAT solver, CirSAT, which implements several efficient SAT algorithms directly on circuits. In particular, we make use of the fanout of logic gates as a heuristic to guide conflict decision. Experimental results on ISCAS’85 benchmark suites indicate our method achieves 47.7x (upto 267. 8x) CPU time acceleration and saves 18.9x time compared to MiniSAT.
A Decentralized Super App

The massive usage of mobile phones connected to the internet over the last years has changed the business model of all sort of companies and services around the globe. By turning on your mobile phone and connecting it to the internet, it is possible to reach a countless amount of information and the products are literally at your fingertips. In view of this new reality, the concept of a mobile app that aggregates services (i.e., super apps) seems to be the next game-changer for the mobile apps industry, and the challenges related to security and privacy are key aspects for keeping user data safe. In this paper, we propose a complete auditable decentralised super app architecture in order to prevent the risks of a centralised ownership, to provide a full log of shared data and to control data access between the stakeholders. An environment containing all the proposed implementations were built and successfully tested to prove the feasibility of deploying such architecture in real world applications.