Miracle-dz/UniFAR-FTUs huggingface dataset:
Reducing airport emissions through aircraft gas turbine water injection at take-off

Airport related air pollution has become a global concern. Around Mexico City’s Benito Juarez International Airport, the Nitrogen Oxide (NOx) levels double the concentration suggested by international authorities. At Heathrow Airport in London, airliners are charged more than £15.00 per kilogram of NOx emitted every time one of their aircraft takes-off. This contaminant is associated with respiratory diseases, and it has been recognized to damage the local vegetation and wildlife. Cooling the aircraft’s engine by compressor water injection is a way to reduce this pollutant in almost 50 %. This study explains by means of an analytical method applied to the compressor, the physical mechanism behind the cooling of the thermodynamic cycle. The method is validated against other publications and used to evaluate the potential NOx decrease on a common aircraft’s power plant. It is shown how a 2-spool engine can benefit from a decrease in operating temperature in the order of 10 %, which can lead to a NOx reduction of 45 %. For an Airport like Heathrow this can represent a reduction in total NOx emissions of 12 %.
FAUNA DE ELASMOBRÂNQUIOS DO LITORAL DO ESTADO DE SERGIPE, BRASIL

In spite of the great ecological and fisheries importance of the Elasmobranchs (sharks and rays), information on these animals off Sergipe State are insufficient. With the objective of knowing the species of sharks and rays that occur in the coast of Sergipe, since August, 2000 fishing trips have been performed in the Mosqueiro Beach and around the Aracaju fishing harbor. A total of 27 Elasmobranch species were registered, out of which 20 sharks and 7 rays, belonging to 13 families and 15 genera, with a not iceable presence of typical species of the Northeastern fauna.
Mountain glaciers under a changing climate

Mountain glaciers are found around the world in ranges such as the Himalaya, the Andes and the European Alps. The majority of mountain glaciers world‐wide are shrinking. However, the rugged alpine topography through which these glaciers flow governs their dynamics and impacts on the regional climate systems that modify glacier mass balance. As a result, the response of mountain glaciers to climate change is difficult to predict, and highly spatially variable even across one mountain range, particularly where orography controls precipitation distributions. To understand how mountain glaciers behave and change, geologists combine many different techniques based on direct observations and dating of glacial geology, measurements of present‐day glaciers, and predictive numerical (computer) models. Recent advances in these techniques and their applications to glacial environments have demonstrated that the glacial geological record is a rich archive of information about how climate has changed in the past, and gives greater confidence in predictions of glacier change in the future, which is required if populations living in glacerised catchments are able to adapt to the rapid response of glaciers to a changing climate.
Theory of model-based geophysical survey and experimental design

Enormous sums of money are invested by industry and scientific funding agencies every year in seismic, well logging, electromagnetic, earthquake monitoring and microseismic surveys, and in laboratory-based experiments. For each survey or experiment a design process must first take place. An efficient design is usually a compromise—a suitable trade-off between information that is expected to be retrieved about a model of interest and the cost of data acquisition and processing. In some fields of geophysics, advanced methods from design theory are used, not only to optimize the survey design, but also to shift this entire trade-off relationship between information and cost. In others, either crude rules of thumb are used or, indeed, expected model information is not optimized at all.
Study protocol of translation into Spanish and cross‐cultural adaptation and validation of the problem areas in diabetes—Pediatric version (PAID‐Peds) survey

Abstract Aim The metabolic and psychological management of paediatric type 1 diabetes mellitus (T1DM) can be challenging over time given that T1DM may cause a negative emotional burden and, consequently, result in poor metabolic control of the disease. The objectives of this study are to translate the Problem Area in Diabetes Survey–Pediatric version (PAID‐Peds) into Spanish, adapt it culturally and validate it. Design Multicenter cross sectional study. Methods 636 patients aged 8–17 years, diagnosed with T1DM, under treatment with insulin and follow‐up at the Miguel Servet University Hospital in Zaragoza (Aragón, Spain), the Ramón y Cajal University Clinical Hospital in Madrid (Spain) and at the Sant Joan de Déu Hospital in Barcelona (Catalonia, Spain) between 1 January 2023 and 31 December 2024 will be included. This study will consist of two phases: (1) Translation and cultural adaptation of the original PAID‐Peds® survey into Spanish following eight steps; (2) Validation of the Spanish version of the PAIS‐Peds® survey. The statistical analysis will be performed using Jamovi® 2.1. 23. The reliability or internal consistency will be calculated using Cronbach's alpha index (considering an index higher than 0.8 to be good) and the test–retest will be evaluated using the intraclass correlation coefficient. For validity, confirmatory factor analysis will be calculated. This study has been approved by the ethics and research committees at each centre. Results The translation and validation into Spanish language of the Problem Area in Diabetes Survey‐Pediatric version will be feasible, valid and reliable to detecting the youth‐perceived burden of T1DM. Therapeutic education in diabetes—recommended by the WHO and the Diabetes Education Study Group—has shown encouraging results in glycaemia and psychosocial and behavioural factors in T1DM.
Changes in trophic structure along a gradient of water availability in temperate montane grasslands

ii Preface . iii Table of contents . iv List of figures . x List of abbreviations . xvi Glossary . xvii Acknowledgements . xxii Chapter 1: Introduction . 1 1.1 Trophic cascades . 3 1.2 Gradients . 6 1.3 Resource subsidies . 8 1.4 Dissertation overview . 11 Chapter 2: Temperate grassland songbird species accumulate incrementally along a gradient of water availability to plants . 15 2.
Soil health and climate change: Implications for food security in Sub-Saharan Africa

Climate change and increasing climate variability present new challenges affecting human society in the 21st century. In an unfortunate twist of fate, the poorest countries whose economies and livelihoods largely rely on natural resources in sub-Saharan Africa (SSA) are amongst the most vulnerable. The impact of climate change and climate variability on crop growth and yields is largely determined by their impact on soil health and the capacity of crop varieties to adapt to the changing climate and weather patterns. Success stories of improved land productivity and climate resilience as a function of integrated soil fertility management (ISFM) interventions are widespread in subSaharan Africa. In a trial carried out across four districts in western Kenya, improved cereal-legume intercrop technologies increased maize yield by between 2.8 and 3.3 t/ha (≈ 300%). Further, across varying agroecosystems in 5 sub-Saharan African countries (Kenya, Uganda, Rwanda, Tanzania, Ghana), P fertilization + innoculation increased soybean crop yields by more than 200% in each country. Similarly, maize yield increases of up to 300% were observed in the drought stricken Sadore and Dasso regions in Niger upon use of appropriate fertilizers. The carbon input to the soil from these systems exceeded 2 t/ha implying that these systems are capable of mitigating climate change through carbon sequestration. The observed improved yields were linked to the capacity of ISFM to improve soil fertility, enhance soil organic matter, boost the soil water holding capacity and water use efficiency. The soil organic matter is crucial in soil nutrient processing and soil water retention. A number of challenges, related to inputs, information and markets constrain wide scale use of ISFM in SSA. Bringing these ISFM benefits to scale require agricultural policy reforms on access to appropriate fertilizer and seed inputs, agricultural advisory services and access to output markets.
Impact Assessment of Habitat and Hydromorphological Alterations in Two Heavily Modified Lakes

A description of hydromorphological pressures is required by the Water Framework Directive, however, there is not a commonly accepted assessment method. This study aims to explore a description tool application, not used before in Greece, for the quantification of the human impact extent on natural environment. Thus, in lakes Kastoria and Pamvotis, the Lake Habitat Survey was applied in the field and remotely to map the pressures, to examine confidence, suitability and ease of applicability through plot quantitative description, to calculate the “Lake Habitat Quality Assessment”, “Lake Habitat Modification Score” and “Alteration of Lake Morphology Score” indices.
Precipitation over the Tibetan Plateau during recent decades: a review based on observations and simulations

The Tibetan Plateau (TP) has a significant influence on local, regional, and even global weather and climate systems. Precipitation on the TP plays a critical role in the energy and water cycle and terrestrial ecosystem. This study reviewed recent research progress in precipitation changes in recent decades and explored their mechanisms involved based on observations (meteorological station data and satellite remote sensing data) and simulations [global climate models (GCMs) and downscaling modelling]. Our review suggested that the TP precipitation decreases progressively from southeast to northwest, mainly occurs in summer (June–August), accounting for ∼60–70% of annual total, and marginally occurs in winter (December–February), accounting for less than 10%. Diurnal variation of precipitation and convective activity are obvious on the TP. The TP has experienced an overall surface air wetting trend since the 1960s, but with apparent regional and seasonal differences. Projected precipitation on the TP from GCMs and statistical downscaling methods (SDMs) generally increases, while from dynamic downscaling methods (DDMs) slightly increases or even decreases as greenhouse gas emissions continue in the future. Influencing factors such as the TP' and Asian land heating, large‐scale atmospheric circulations, climate warming, aerosols, and land surface conditions all exert prominent but complicated effects on precipitation changes on the TP. More efforts should be made to improve the reliabilities and accuracies of precipitation observational data sets, GCMs, and downscaling modelling. Finally, directions for future research are discussed based on the various means covering high‐quality precipitation observations and more skilful simulations, which are synthetically used to investigate the TP precipitation and its driving mechanisms. It is expected that this review and its results will be beneficial for hydrological and precipitation studies over the TP.
Model-based and Model-free RL for Robot Control

The previous chapter introduced the deterministic and stochastic sequential decision making problems, and demonstrated how these problems can be solved by dynamic programming. While dynamic programming is a powerful algorithm, it also suffers from several practical challenges. This chapter briefly introduces some of the key ideas in reinforcement learning1,2, a set of ideas which 1 D. Bertsekas. Reinforcement learning and optimal control. Athena Scientific, 2019 2 R. Sutton and A. Barto. Reinforcement learning: An introduction. MIT Press, 2018 aims to solve a more general problem of behaving in an optimal way within a given unknown environment. That is, the reinforcement learning setting assumes only the ability to (1) interact with an unknown environment and (2) receive a reward signal from it. How the actions affect the future state evolution or the future reward is not known a priori. Reinforcement learning includes a class of approximation algorithms which can be much more practical than dynamic programming in real world applications.
Uranium Concentration in Soil of some Eastern Iraqi Regions using Nuclear Track Detector (CR-39)

The concentration of the natural uranium (U) varied from region to anther according to geological structure and to the accumulated amounts of fertilizer, which used in agriculture. Al-Fallujah is one of the major cities in Al-Anbar Governorate belonging to the Iraq, exposed to DU. Therefore, this work dedicated to measure the concentration of U in the soil of Al-Fallujah city.28 soil samples collected from the districts of Al-Fallujah city were measured against U concentration using CR-39 detector. Each sample was taken from three different depths; 15, 30, and 45 cm, to study the distribution of U in soil. The results showed that the maximum values of the specific activity (S.A) of U were 45.52, 37.29, and 27.22 Bq/kg, and the minimum values were 8.97, 10.62, and 4.44 Bq/kg, for the three depths, respectively. Whereas, the average values were 31.98, 22.30, and 15.55 Bq/kg, respectively.
Developers ’ Code Context Models for Change Tasks

Software developers spend substantial time searching and navigating through code to understand relevant parts of a system for a particular change task [2, 6]. During this process of understanding and then changing code, developers implicitly build code context models that consist of the relevant code elements and the relations between these elements, often more generally referred to as task context. Since these models mainly stay implicit in developers’ heads and are not persistent [3], developers have to continuously spend a significant amount of their time creating context models for newly assigned change tasks from scratch. Researchers have suggested that more explicit context models for change tasks can be used to support developers in their work [4]. To form these explicit context models, existing approaches have used methods ranging from a developer manually specifying the context (e.g., [5]) to automatically inferring the context from a developer’s interaction with a development environment (e.g., [1]). While these approaches have been shown to support developers with change tasks, little is understood about the implicit code context models that developers build and their characteristics. With a better understanding of the characteristics of developers’ code context models, we can help developers in the initial creation of these models for change tasks, saving time and effort.
THE SECOND AVOIDS DECLARING ERRORS ON BENIGN FAULTS . APPLYING THESE TECHNIQUES TO A MICROPROCESSOR INSTRUCTION QUEUE SIGNIFICANTLY REDUCES ITS ERROR RATE WITH ONLY MINOR PERFORMANCE DEGRADATION . REDUCING THE SOFT-ERROR RATE OF A HIGH-PERFORMANCE MICROPROCESSOR

Single-bit upsets from transient faults have emerged as a key challenge in microprocessor design. These faults arise from energetic particles—such as neutrons from cosmic rays and alpha particles from packaging material—generating electron-hole pairs as they pass through a semiconductor device. Transistor source and diffusion nodes can collect these charges. A sufficient amount of accumulated charge can invert the state of a logic device, such as an SRAM cell, a latch, or a gate, thereby introducing a logical fault into the circuit’s operation. Because this type of fault does not reflect a permanent device failure, we call it soft or transient. Soft errors will be an increasing burden for microprocessor designers as the number of on-chip transistors continues to grow exponentially. The raw error rate per latch or SRAM bit is projected to remain roughly constant or decrease slightly for the next several technology generations. Thus, unless we add error protection mechanisms or use a more robust technology (such as siliconon-insulator), a microprocessor’s error rate will grow in direct proportion to the number of devices we add to it in each succeeding generation. A direct approach to reducing error rates involves adding error correction or recovery mechanisms to a design. Unfortunately, these mechanisms come at a significant cost in power, performance, and area. Furthermore, these techniques might be overkill for most of the microprocessor market, which requires good reliability but not bulletproof operation. This article focuses on an alternative approach to reducing a microprocessor’s soft-error rate: reducing the likelihood that a transient fault will cause the processor to declare an error Christopher T. Weaver Joel Emer Shubhendu S. Mukherjee
CUR Decomposition for Compression and Compressed Sensing of Large-Scale Traffic Data

Intelligent Transportation Systems (ITS) often operate on large road networks, and typically collect traffic data with high temporal resolution. Consequently, ITS need to handle massive volumes of data, and methods to represent that data in more compact representations are sorely needed. Subspace methods such as Principal Component Analysis (PCA) can create accurate low-dimensional models. However, such models are not readily interpretable, as the principal components usually involve a large number of links in the traffic network. In contrast, the CUR matrix decomposition leads to low-dimensional models where the components correspond to individual links in the network; the resulting models can be easily interpreted, and can also be used for compressed sensing of the traffic network. In this paper, the CUR matrix decomposition is applied for two purposes: (1) compression of traffic data; (2) compressed sensing of traffic data. In the former, only data from a “random” subset of links and time instances is stored. In the latter, data for the entire traffic network is inferred from measurements at a “random” subset of links. Numerical results for a large traffic network in Singapore demonstrate the feasibility of the proposed approach.
Utilising Bayesian networks to demonstrate the potential consequences of a fuel gas release from an offshore gas-driven turbine

This research proposes the application of Bayesian networks in conducting quantitative risk assessment of the integrity of an offshore gas driven turbine, used for electrical power generation. The focus of the research is centred on the potential release of fuel gas from a turbine and the potential consequences that follow the said release, such as fire, explosion and damage to equipment within the electrical generation module. The Bayesian network demonstrates the interactions of potential initial events and failures, hazards, barriers and consequences involved in a fuel gas release. This model allows for quantitative analysis to demonstrate partial verification of the model. The verification of the model is demonstrated in a series of test cases and through sensitivity analysis. Test case 1 demonstrates the effects of individual and combined control system failures within the fuel gas release model; 2 demonstrates the effects of the 100% probability of a gas release on the Bayesian network model, along with the effect of the gas detection system not functioning; and 3 demonstrates the effects of inserting evidence as a consequence and observing the effects on prior nodes.
Automatic Conﬁguration of State-of-the-art Multi-objective Optimizers Using the TPLS+PLS Framework

The automatic conﬁguration of algorithms is a dynamic ﬁeld of research. Its potential for producing highly performing algorithms may change the way we design algorithms. So far, automatic algorithm con-ﬁguration tools have almost exclusively been applied to conﬁgure single-objective algorithms. In this paper, we investigate the usage of automatic algorithm conﬁguration tools to improve multi-objective algorithms. In fact, this is the ﬁrst article we are aware of where new state-of-the-art multi-objective optimizers are conﬁgured in an automatic way. This automatic conﬁguration is done for ﬁve variants of multi-objective ﬂow-shop problems. Our experimental results show that we can reach at least the same and often a better ﬁnal quality than a recently proposed state-of-the-art algorithm for these problems.
Semantic Information Integration in the Large: Adaptability, Extensibility, and Scalability of the Context Mediation Approach

There is pressing need for effectively integrating information from an ever increasing number of available sources both on the web and in other existing systems. A key difficulty of achieving this goal comes from the pervasive heterogeneities in all levels of information systems. Existing and emerging technologies, such as the Web, ODBC, XML, and Web Services, provide essential capabilities in resolving heterogeneities in the hardware and software platforms, but they do not address the semantic heterogeneity of the data itself. A robust solution to this problem needs to be adaptable, extensible, and scalable. In this paper, we identify the deficiencies of traditional approaches that address this problem using hand-coded programs or require complete data standardization. The COntext INterchange (COIN) approach overcomes these deficiencies by declaratively representing data semantics and using a mediator to create the necessary conversion programs using a small number of conversion rules. The capabilities of COIN is demonstrated using an intelligence information integration example consisting of 150 data sources, where COIN can automatically generate the over 22,000 conversion programs needed to enable semantic integration using only six pa
Sensor Based Automatic Drip Irrigation System

The developments in the agricultural field are the buzzword in the market. In the field of agriculture, use of proper method of irrigation is important and it is well known that irrigation by drip is very economical and efficient. In the conventional drip irrigation system, the farmer has to keep watch on irrigation timetable, which is different for different crops and it is very difficult. This paper mainly focuses on designing of an accurate & cost effective Global System for Mobile (GSM) Based Automatic Drip Irrigation System using micro-controller. In order to fulfill these objectives we have used relay and solenoid valve along with a 16×2 Liquid Crystal Display (LCD) that can be connected to the microcontroller, which will displays the soil moisture level and ambient temperature. The developed irrigation method removes the need for workmanship for flooding irrigation. Efficient water management plays an important role in the irrigated agricultural cropping systems. Time based control mechanism; volume based control mechanism and priority based mechanism can be designed in one system.
AIS Electronic

Action research is seen as one of the solutions to the lack of relevance in the field of information systems because action research has as its primary goal to combine successful intervention in real-world settings with the development of scientific knowledge. The rigor of action research, however, has been questioned regularly. The IS field lacks a set of generally agreed guidelines and criteria to assess action research. This paper builds on earlier efforts to arrive at a set of principles and criteria to assess the rigor of action research and provides the first comprehensive evaluation of 30 recently published AR field studies in mainstream IS journals to test whether such a set of principles and criteria proves to be useful. The objective is to provide a reference framework on which AR design choices can be made and AR papers can be reviewed. The framework proposed in this paper has proven to be applicable to different types of AR and many of its principles are followed in action research field studies. Based on the framework and the review of the field studies, recommendations are made to increase the rigor of action research to achieve more relevance.