Miracle-dz/UniFAR-FTUs huggingface dataset:
Microbial Air Quality in a 50-year-old Middle School

Millions of children and adults across the nation spend their days in school buildings, and they need safe, healthy environments to thrive, learn, and succeed. Almost any building surface can nourish mold growth. Elevated levels of indoor fungal spores result in significantly higher rates of illness (6). We enumerated the biological contaminants present in the indoor environment of a water-damaged, 50-year-old middle school in the San Francisco Bay Area. Indoor and outdoor air samples were taken with an impact air sampler. Swab samples and Rodac impression plates used to culture environmental surfaces. Fungi were grown on Sabouraud Dextrose agar Agar and bacteria on Nutrient Agar. Indoor airborne fungal spores were 11 times higher than outdoor. Concentrations of indoor and airborne bacteria were equal. Fungal and bacterial density and distribution were rank-ordered and compared with nearby buildings and outdoor air. Dominant species were identified. The significance of this contamination is discussed. Aim To analyze the air quality environment in a local middle school for biological contaminants. Background
Computational materials discovery and development for Li and non-Li advanced battery chemistries

Since the discovery of batteries in the 1800s, their fascinating physical and chemical pro­perties have led to much research on their synthesis and manufacturing. Though lithium-ion batteries have been crucial for civilization, they can still not meet all the growing demands for energy storage because of the geographical distribution of lithium resources and the intrinsic limitations in the cell energy density, performance, and reliability issues. As a result, non-Li-ion batteries are becoming increasingly popular alternatives. Designing novel materials with desired properties is crucial for a quicker transition to the green energy ecosystem. Na, K, Mg, Zn, Al ion, etc. batteries are considered the most alluring and promising. This article covers all these Li, non-Li, and metal-air cell chemistries. Recently, com­putational screening has proven to be an effective tool to accelerate the discovery of active materials for all these cell types. First-principles methods such as density functional theory, molecular dynamics, and Monte Carlo simulations have become established techni­ques for the preliminary, theoretical analysis of battery systems. These computational methods generate a wealth of data that might be immensely useful in the training and vali­dating of artificial intelligence and machine learning techniques to reduce the time and capital expenditure needed for discovering advanced materials and final product develop­ment. This review aims to summarize the application of these techniques and the recent deve­lopments in computational methods to discover and develop advanced battery chemistries.
Flow: the essentials of environmental flows

An environmental flow is the water regime provided within a river, wetland or coastal zone to maintain ecosystems and their benefits where there are competing water uses and where flows are regulated. Pioneering efforts in South Africa, Australia and the United States have shown that the process to establish them poses great challenges. Second in the series of the Water & Nature Initiative, this guide draws extensively on the experiences in these countries to offer hands-on advice and practical guidance on technical issues for this emerging issue on the water resource agenda.
Deep Learning Techniques For Time Series Forecasting: An Application For Exchange Rates

Forecasting financial series, in special exchange rates, plays a key role in decision-making, portfolio allocation, risk management, and derivative pricing problems. In recent years, machine learning models have been applied to time series forecasting due to their ability to handle nonlinear relationships. This study evaluated neural network models such as MLP, LSTM, GRU, and the proposed AE-BiGRU-Swish for forecasting exchange rate series. We adjusted the parameters of these models with deep learning techniques. We compare the performance of neural network models forecast exchange rate series with traditional approaches such as ARIMA and ARFIMA models for temporal horizons of 1, 7, 14, 21, and 30 days ahead forecasting. The results indicate that the hybrid neural network model outperforms other approaches to forecast exchange rates.
Compendium of sanitation systems and technologies

Abundant information exists about sanitation solutions but it is scattered throughout hundreds of books and journals; this Compendium aims to pull it all together in one volume. By ordering and structuring a huge range of information on tried and tested technologies into one concise document, the reader is provided with a useful planning tool for making more informed decisions. Part 1 describes different system configurations for a variety of contexts. Part 2 consists of 52 different Technology Information Sheets, which describe the main advantages, disadvantages , applications and the appropriateness of the technologies required to build a comprehensive sanitation system. Each Technology Information Sheet is complemented by a descriptive illustration. Investing in sanitation and hygiene is not only about saving human lives and dignity; it is the foundation for investing in human development, especially in poor urban and peri-urban areas. However, one of the main bottlenecks encountered the world over, is the limited knowledge and awareness about more appropriate and sustainable systems and technologies that keep project costs affordable and acceptable. Abundant information exists about sanitation technologies but it is scattered throughout dozens of books, reports , proceedings and journals; this Compendium aims to pull the main information together in one volume. Another aim of the Compendium is to promote a systems approach; sanitation devices and technologies should always be considered as parts of an entire system. In 2005, Sandec and the WSSCC published Provisional Guidelines for Household-centred Environmental Sanitation (HCES), a new planning approach for implementing the Bellagio Principles on Sustainable Sanitation in Urban Environmental Sanitation. The HCES approach emphasizes the participation of all stakeholders – beginning at the household/neighbourhood – in planning and implementing sanitation systems. By ordering and structuring a huge range of information on fully and partly tested technologies into one concise document, this Compendium is an important tool for stakehold-ers to make well informed decisions during the planning process. Although this source book is primarily addressed to engineers and planners dealing with infrastructure delivery , the technology sheets also allow non-experts to understand the main advantages and limitations of different technologies and the appropriateness of different system configurations. It is our hope that this Compendium will allow all stakeholders to be involved in selecting improved sanitation technologies and to help promote people-centred solutions to real sanitation problems. This is the first edition of the Compendium and we are looking forward to receiving your feedback – …
Automatic generation of a process shutdown system fault tree using a computer program KB3 (Sonatrach-FCP)

Automated dependability analysis has become a necessity due to the scale and complexity of modern systems. In this context, this paper is devoted to using a computer program called KB3 for probabilistic modeling of an operational process shutdown system's behavior, which ensures consistency, saves time, and is even easily accessible to non-specialists. Based on a graphical description of the structure and elementary characteristics of the system under study, using a generic knowledge base written in the Figaro language, the model developed automatically constructs the associated fault tree, which is then used quantitatively to obtain the probability of dangerous failure of the entire process shutdown system and its various constituent sub-barriers. This paper analyzes the performance of a process shutdown system using KB3 software, which is crucial for preserving operational well installations' safety. Initially using the reliability block diagram (RBD) knowledge base, the modeling process ensures a simple and flexible representation of the barrier system, including common causes of failure using the binomial failure rate model. The process produces a fault tree, which is time-consuming to build manually. Quantifying this fault tree gives the average probability of failure on demand (PFDavg) of the entire system and its components, which is essential for estimating the frequencies of occurrence of scenarios. However, to assess the impact of disregarding the existing standby relationship, the system is also modeled using the Boolean logic-driven Markov process (BDMP) knowledge base, showing no significant difference in numerical results.
Racial Disparities in the Income Tax Treatment of Marriage

T AX P OL IC Y C EN T E R | URB A N I NST IT UT E & BR OOK I NGS I NST IT UT IO N i i Although it is generally blind with respect to race, the tax code can create racial disparities when factors that affect tax liability are correlated with race. In this working paper, we provide new evidence on racial differences in marriage penalties and bonuses in the income tax, using data from eight waves of the Survey of Consumer Finances. Our results support Brown’s (2021) hypothesis that, controlling for income, penalties are more frequent and larger for Black couples than white couples. We link these results to racial differences in income, relative spousal earnings, and the presence of dependents. We examine two policy reforms as well. ABOUT THE TAX POLICY CENTER The Urban-Brookings Tax Policy Center aims to provide independent analyses of current and longer-term tax issues and to communicate its analyses to the public and to policymakers in a timely and accessible manner. The Center combines top national experts in tax, expenditure, budget policy, and microsimulation modeling to concentrate on areas of tax policy that are critical to future debate. Copyright © 2023. Tax Policy Center. Permission is granted for reproduction of this file, with attribution to the Urban-Brookings Tax Policy Center.
Joint User Scheduling and Resource Optimization in MEC Networks with Asynchronous Computing

In this paper, a joint user scheduling and resource optimization framework for mobile edge computing (MEC) networks with asynchronous computing is studied. In the considered model, edge devices (EDs) offload their computational tasks to a MEC server utilizing energy harvested from the server. In particular, task offloading by EDs obey a particular order. Meanwhile, an asynchronous computing approach is adopted where the server executes a task once it is received. Intuitively, EDs offloading later can harvest more energy for transmission, while EDs uploading earlier have more computing time. An optimization problem of joint user scheduling, communication and computation resource management is formulated aiming to minimize the energy consumption of the server under the delay constraint. First, the general properties of computation resource allocation are investigated and a low-complexity frequency allocation algorithm is proposed. Then, through the General Benders Decomposition method, this mixed-integer non-linear programming problem is addressed by iteratively solving a primal problem related to continuous variables and a master problem associated with integer variables. Simulation results verify that the proposed algorithm yields significant performance gains compared with benchmark schemes, especially in resource-scarce scenarios.
Thermosensitive Polyurethane-Based Hydrogels as Potential Vehicles for Meloxicam Delivery

Meloxicam (MX) is a nonsteroidal anti-inflammatory drug (NSAID) used mainly to reduce pain, inflammation, and fever. In the present study, thermosensitive polyurethane (PU)-based hydrogels with various excipients (PEG, PVP, HPC, and essential oil) were prepared and loaded with MX. Rheological investigations were carried out on the PU-based formulations in various shear regimes, and their viscoelastic characteristics were determined. The average size of the PU micelles was 35.8 nm at 37 °C and slightly increased at 37 nm in the presence of MX. The zeta potential values of the hydrogels were between −10 mV and −11.5 mV. At pH = 6 and temperature of 37 °C, the formulated PU-based hydrogels loaded with MX could deliver significant amounts of the active substance, between 60% and 80% over 24–48 h and more than 90% within 2 weeks. It was found that anomalous transport phenomena dominated MX’s release mechanism from the PU-based networks. The results are encouraging for further studies aiming to design alternative carriers to commercial dosage forms of nonsteroidal anti-inflammatory drugs.
Response of the stratospheric temperatures and ozone to past and future increases in stratospheric humidity

Balloonsonde and aircraft in situ and remote sensing measurements in the Northern Hemisphere midlatitudes show that stratospheric humidity has been increasing since 1954. Satellite data, albeit only available over a much shorter period (1992 through 1999), also suggest that water vapor has been increasing globally over much of the stratosphere. Implications of these trends for stratospheric temperatures and ozone are explored using a two-dimensional interactive radiative-chemical-dynamical model. It is shown that the increase in humidity cools the model stratosphere, in agreement with previous studies. In the midlatitude lower stratosphere, increasing water vapor induces a temperature trend of about −0.25 to −0.35 K per decade, which is ∼30–50% of the observed cooling in this region. According to our results, such trends in water vapor have intensified Northern Hemisphere midlatitude ozone trends over the last few decades, mainly via the enhancement of ozone loss in HOx catalytic cycles and changes in chlorine partitioning (in spite of some buffering by concomitant increases in the O3 production in the methane oxidation cycle). Increasing humidity in the model accounts for additional depletion of midlatitude column ozone at a rate of −0.3% per decade and up to −0.7% (−1%) per decade enhancement of local ozone trends in the lower (upper) stratospheres, accordingly. It is important to investigate what will be the likely consequences for stratospheric climate and ozone if the water vapor trend continues. Our simulations suggest that smaller effects on ozone are to be expected over the 2000–2050 period as compared to 1979–1996 because of the projected reduction in the stratospheric chlorine (and bromine) loading. However, our model simulations assuming World Meteorological Organization future emission scenarios for halogenated compounds, CH4, N2O, and CO2, show that increasing humidity will induce further cooling of the stratosphere and result in about a decade of delay in the ozone recovery, all other factors being equal.
Reliable Belief Propagation: Recent Theoretical and Practical Advances

Belief propagation (BP) is an effective approximate inference method but lacks theoretical guarantees for loopy graphs. We discuss the optimization landscape and the message dynamics and how this helps to understand the behavior of message passing algorithms. These insights suggest several improvements. Specifically, we consider iterative initialization strategies, optimized message scheduling methods, and structural modifications, to improve the convergence behavior and accuracy while maintaining the model’s interpretability. We then evaluate the different modifications on signal detection problems in MIMO systems, which is a particularly challenging application for message passing algorithms. Our experimental results show consistent improvements over standard BP with minimal increase in computational burden.
A New Technique to Form Steerable Multibeams for Integrated Communications and Sensing

Analogue circuits for forming multibeams can be employed in integrated communications and sensing (ICAS) systems to save energy consumption and cost. These circuits are in the form of matrices. The most well-known analogue circuit for multibeams is the Butler matrix. However, the Butler matrix has severe limitations; it can only generate fixed beams with the number of beams as a power of two. In this paper, we present a new type of circuit matrix to form multiple beams, which is referred to as the generalised joined coupler (GJC) matrix. The GJC matrix can produce independently steerable multibeams as well as any number of orthogonal beams. The beams can be shaped to produce low sidelobes and deep nulls to mitigate the mutual interference between the communications and sensing beams. These unique features and their applications to ICAS are demonstrated in the paper.
Long Term Temperature Trends in Four Different Climatic Zones of Saudi Arabia

Climate change and its variation studies is a hot topic in global climatic research. The warming trend has been characterized by a decrease in the Diurnal Temperature Range (DTR) as a result of an increase in minimum temperatures experienced during night time. Many factors have been identified as possible reasons for this decrease in DTR like the cloud cover, increase in greenhouse gases, increased urbanization etc. This study aims to find out trends in the maximum and minimum temperatures observed in 4 different climatic zones of Saudi Arabia. Meteorological data for 4 cities representing separate climatic zones was collected from the Presidency of Meteorology and Environment for the period 1984-2013. The results indicate a significant rise in temperature in all the stations. However the distribution of warming trends was not uniform. The minimum temperature is generally found to increase at a higher rate compared to the maximum temperature. The decreasing trend in DTR is found to be maximum for the capital city of Riyadh followed by the new industrial city of Tabuk.
Constructing Cyber-Physical System Testing Suites Using Active Sensor Fuzzing

Cyber-physical systems (CPSs) automating critical public infrastructure face a pervasive threat of attack, motivating research into different types of countermeasures. Assessing the effectiveness of these countermeasures is challenging, however, as benchmarks are difficult to construct manually, existing automated testing solutions often make unrealistic assumptions, and blindly fuzzing is ineffective at finding attacks due to the enormous search spaces and resource requirements. In this work, we propose active sensor fuzzing, a fully automated approach for building test suites without requiring any a prior knowledge about a CPS. Our approach employs active learning techniques. Applied to a real-world water treatment system, our approach manages to find attacks that drive the system into 15 different unsafe states involving water flow, pressure, and tank levels, including nine that were not covered by an established attack benchmark. Furthermore, we successfully generate targeted multi-point attacks which have been long suspected to be possible. We reveal that active sensor fuzzing successfully extends the attack benchmarks generated by our previous work, an ML-guided fuzzing tool, with two more kinds of attacks. Finally, we investigate the impact of active learning on models and the reason that the model trained with active learning is able to discover more attacks.
Betweenness-Centrality-Based-Pinning Control Approach to Nonlinear Multi-Agent Systems

This brief proposes a novel pinning consensus method for nonlinear multi-agent systems (MASs) with node and edge betweenness centrality. The selection of pinned nodes and centrality analysis methods are introduced to explain a combined scheme. By utilizing the Lyapunov analysis, the conditions of the consensus criterion are derived from linear matrix inequality terms. Moreover, the combined consensus scheme results are given with one numerical example.
Review of Land Cover Classification System under Global Environmental Change View

The global environmental change research community requires accurate and up-to-date land cover dataset to support ecosystem assessment,biodiversity conservation,climate change and environmental modeling.It is important to establish a scientific standard classification system when we develop land cover datasets,because it can influence the integration and share of data products,as well as the application areas of the products.This paper expounds the progress of land cover classification system made in regional and global scales,as well as FAO land cover classification system.It also pointed out:① There is no unified standard classification system so far,which effects the application of data products and the detection of land cover change;② Mosaic feature is the inherent characteristic of earth surface,we should make great effort to express effectively and quantify feature of mosaic types;③ It's urgent to develop a standard land cover classification system in China which can't only be consistent with global land cover products,but also reflect the natural environmental condition of China.
Bandwidth Gain: The Missing Gain of Massive MIMO

We present a unified model for connected antenna arrays with a large number of tightly integrated (i.e., coupled) antennas in a compact space within the context of massive multiple-input multiple-output (MIMO) communication. We refer to this system as tightly-coupled massive MIMO. From an information-theoretic perspective, scaling the design of tightly-coupled massive MIMO systems in terms of the number of antennas, the operational bandwidth, and form factor was not addressed in prior art. We investigate this open research problem using a physically consistent modeling approach for far-field (FF) MIMO communication based on multi-port circuit theory. In doing so, we turn mutual coupling (MC) from a foe to a friend of MIMO systems design, thereby challenging a basic percept in antenna systems engineering that promotes MC mitigation/compensation. We show that tight MC widens the operational bandwidth of antenna arrays thereby unleashing a missing MIMO gain that we coin “bandwidth gain”. Furthermore, we derive analytically the asymptotically optimum spacing-to-antenna-size ratio by establishing a condition for tight coupling in the limit of large-size antenna arrays with quasi-continuous apertures. We also optimize the antenna array size while maximizing the achievable rate under fixed transmit power and inter-element spacing. Then, we study the impact of MC on the achievable rate of MIMO systems under line-of-sight (LoS) and Rayleigh fading channels. These results reveal new insights into the design of tightly-coupled massive antenna arrays as opposed to the widely-adopted “disconnected” designs that disregard MC by putting faith in the half-wavelength spacing rule.