Miracle-dz/UniFAR-FTUs huggingface dataset:
Market-Based Allocation of Airport Slots: The PAUSE Auction Mechanism and Extensions

During the past several months, passenger air transport has been recovering from its significant retraction during the two years Covid pandemics. If the recent significant drop in air traffic due do the Covid pandemics acted as an external mitigating factor to airport traffic congestion in several major airports around the world, with the post-pandemics air traffic recovery it is likely that airport capacity will, once again, fall short of demand and not keep pace with the growth in air traffic. That is why close to two hundred major airports worldwide, most of them in Europe, face capacity constraints and are “coordinated”. Eurocontrol predicts Europe's capacity shortage in 2050 at 500,000 flights/year in the baseline scenario, which could rise to 2.7 million in an optimistic scenario. The allocation of airport slots in Europe and elsewhere is still ruled by administrative processes, based on the IATA (International Air Transport Association) Worldwide Airport Slot Guidelines (WASG), which follow historical precedence and time adjustments of historical slots. Market mechanisms in slot allocation, as an alternative to administrative processes, are still rarely used. Several authors have highlighted the inefficiency of the current airport slot administrative allocation system, based on the IATA’s Guidelines. Several authors have suggested improvements in this administrative system, such as congestion pricing mechanisms and other market mechanisms involving auction procedures. Among the various auction mechanisms, scoring auctions and the PAUSE methodology have been suggested in the literature. In this paper, and following our previous work, we explore and extend the application of the PAUSE auction mechanism with bidding based on a score function for the auctioneer, that includes another variable in addition to the total revenue, where this variable can represent e.g., quality of the service provided. We study the application of this auction mechanism, in a gradual fashion, p.e. to the year round three level 3 international airports operating in Portugal. The different airlines using these airports would still follow the current IATA slot allocation guidelines in their use of other airports, including the slot exchange protocols. We show that some of PAUSE auction mechanism’s desirable properties, such as computability, transparency, absence of envy, and the mitigation of the “price-jump problem”, “threshold problem”, “exposure problem”, and “winner’s curse problem”, still hold.
Phenolics and Sesquiterpene Lactones Profile of Red and Green Lettuce: Combined Effect of Cultivar, Microbiological Fertiliser, and Season

The main goal of our study was to find an optimal combination of tested factors to achieve lettuce rich in bioactive compounds sustaining its pleasant taste. We examined three red and three green cultivars in a greenhouse using two microbiological fertilisers (EM Aktiv and Vital Tricho), and their combination. Plants were grown in three consecutive growing seasons (autumn, winter, and spring). Lactones accumulated in autumn, whereas phenolics’ concentration rose during winter. Red cultivars showed higher phenolics and lactone content, where chicoric acid and luteolin-7-glucoside were the most abundant in the ‘Gaugin’ winter trial. Lactucopicrin was the predominant lactone among tested cultivars with the highest value in the red cultivar ‘Carmesi’. Solely applicated, the fertiliser EM Aktiv and Vital Tricho led to significantly higher phenolic acid and dihydrolactucopicrin content, while combined, there were notably increased levels of all detected lactones. Application of single fertilisers had no effect on flavonoid content, while the combination even reduced it. A sensory analysis showed a negative correlation between overall taste and total sesquiterpene lactones, lactucopicrin, caffeoylmalic, and chlorogenic acid, indicating a less bitter taste with decreasing content of these compounds. Our findings indicate that the cultivar, fertiliser, and growing season jointly affected all of the tested parameters, highlighting the differences in the application of EM Aktiv, Vital Tricho, and their combination.
Prevalence of Luminal A, Luminal B, HER2 enriched and triple negative breast carcinoma in population of Sindh

The incidence of breast cancer has increased significantly in Asian countries in comparison to Western countries, and it is now one of the leading causes of cancer-related death among women worldwide. Each year, 1.5 million women (25% of all cancer women) are diagnosed with BC around the world, and this number is expected to rise to 2.2 million by 2025. In particular, breast cancer shows biologic heterogeneity in terms of risk factors, natural histories, responses to therapy, and prognostic features that vary considerably between ethnic and geographical groups. Many studies have focused on the distinctions between tumor subtypes because of the importance they play in guiding therapeutic decision making in breast cancer. These factors include histological grade, tumor type and size, and the presence of lymph node metastasis. As a proxy for profiling gene expression, immunohistochemical examination of breast cancer tissue with various biomarkers is employed. This method is cheap, widely accessible, reliable, and technically not demanding. The purpose of this research was to analyze the relationship between molecular subtypes of breast cancer and certain pathological characteristics.
Problem Solving Errors in Mathematics Story Questions

Daily problems are often expressed in the form of math story problems. However, mathematics is often seen as scary because it is difficult to learn, causing errors in doing math story problems. The aims of this study is analyses the types of problem-solving errors in solving math story problems and analyses the factors that cause problem solving errors in solving math story problems. This research is a type of qualitative research with a case study approach. The subjects in this study were elementary school students in grade 5 with the object of research being student errors in answering math story questions. Data collection techniques using question answer sheets and interviews. The data analysis technique uses Miles and Huberman interactive data analysis techniques. The results showed that reading errors were 39%, comprehension errors were 81%, transformation errors were 88%, process skill errors as much as 90%, and writing errors in the final answer (encoding errors) as much as 90%. Cognitive factors that cause problem solving errors in math story problems are: memory weakness; the weakness of understanding; and weak analysis. The non-cognitive factors that cause problem-solving errors in math story problems are how students learn and how to teach teachers. Based on the results of the study, teachers need to improve students' abilities to reduce process skill errors and writing errors in the final answer.
Effect of chevron nozzle penetration on aero-acoustic characteristics of jet at M = 0.8

Aero-acoustic characteristics of a high-speed jet with chevron nozzles are experimentally investigated at a Mach number of 0.8. The main focus is to examine the effects of the extent of chevron penetration and its position in the mixing layer. Chevron nozzles with three different levels of penetration employed at three different longitudinal locations from the nozzle lip are tested, and the results are compared with those of a plain baseline nozzle. The chevrons are found to produce a lobed shear layer through the notched region, thereby increasing the surface area of the jet, particularly in the close vicinity of the nozzle, which increases the mixing and reduces the potential core length. This effect becomes more prominent with increasing penetration closer to the nozzle lip in the thinner mixing layer. Near field and far field noise measurements show distinctly different acoustic features due to chevrons. The chevrons are found to effectively shift the dominant noise source upstream closer to the nozzle. Present investigation proposes a simpler method for locating the dominant noise source from the peak of the centerline velocity decay rate. The overall noise levels registered along the jet edge immediately downstream of the chevrons are higher, but further downstream they are reduced in comparison with the plain baseline nozzle. Also, the chevrons beam the noise towards higher polar angles at higher frequencies. At shallow polar angles with respect to the jet axis in the far field, chevrons suppress the noise at low frequencies with increasing penetration, but for higher polar angles, while they continue to suppress the low frequency noise, at higher frequencies the trend is found to reverse. The noise measured in the near field close to the jet edge is composed of two components: acoustic and hydrodynamic. Of these two components, the chevrons are found to reduce the hydrodynamic component in comparison with the acoustic one.
The differential response to neuronal hyperexcitation and neuroinflammation of the hippocampal neurogenic niche

Hippocampal neurogenesis is a tightly regulated process in which neural stem cells (NSCs) get activated, enter in the cell cycle and give rise to neurons after a multistep process. Quiescent and activated NSCs, neural precursors, immature and mature neurons and newborn astrocytes coexist in the neurogenic niche in a strictly controlled environment which maintains the correct functioning of neurogenesis. NSCs are the first step in the neurogenic process and are a finite and, mostly, non-renewable resource, therefore any alteration of the intrinsic properties of NSCs will impact the total neurogenic output. Neuronal hyperexcitation is a strong activator of NSCs prompting them to divide and therefore increasing neurogenesis. However, neuronal hyperactivity is not an isolated process but often also involves excitotoxicity which is subsequently accompanied by neuroinflammation. Neuroinflammation normally reduces the activation of NSCs. It is technically difficult to isolate the effect of neuronal hyperexcitation alone, but neuroinflammation without neuronal hyperexcitation can be studied in a variety of models. In order to shed light on how the balance of neuronal hyperexcitation and neuroinflammation affect NSCs we analyzed proliferation and morphology of NSCs. We used two models of neuronal hyperactivity [an epilepsy model induced by KA, and a model of traumatic brain injury (TBI)] and different models of inflammation (LPS, Poly I:C, IFN-α and IL-6). We observed that only those models that induce neuronal hyperactivity induce NSCs activation but neuroinflammation causes the opposite effect. We also analyzed the response of other cell types in the neurogenic niche, focusing on astrocytes.
REVIEW ON CLUSTERING AND LOAD-BALANCING APPROACHES IN VEHICULAR ADHOC NETWORKS

: Vehicular Adhoc Networks (VANETs) have been attracted a lot of research in recent years. In VANET, vehicles are dynamic nodes which communicating with each other by wireless technology in their own transmission range. Although VANETs are deployed in reality offering several services, the current architecture has been facing many difficulties in deployment and management because of poor connectivity, less scalability, less flexibility and less intelligence. To improve network scalability and connection reliability, a vehicle clustering algorithm, which organizes vehicles in groups, is introduced in VANET. Recently, there are various clustering and load balancing methods such as cluster-enabled capacity-based load-balancing , hybrid Ant Colony Optimization and Artificial Bee Colony (ACO-ABC) optimization, energy-aware predictive clustering approach, Vehicular Genetic Bee Clustering (VGBC), proactive load balancing mechanism, Cluster– on–Demand VANET Clustering algorithm (CDVC) along with load balancing, Link Reliability-based Clustering Algorithm (LRCA), hybrid backbone based clustering algorithm, Load Balanced Routing strategy (LBR) are analyzed and its merits and demerits are evaluated.
BIS Working Papers

The Covid-19 pandemic has been a global shock of unprecedented size that has hit most countries around the world. Central banks have responded quickly, on a massive scale. We present a novel database that provides information on central banks’ responses to Covid-19 in 39 economies, including both advanced and emerging market economies. Monetary policy announcements are listed and classified under five types of tools: interest rate measures, reserve policies, lending operations, asset purchase programmes and foreign exchange operations. Within each category, the database provides additional information such as maturity, eligible counterparties, types of assets and the availability of fiscal backup. It also indicates whether the policy tool was newly introduced or had been previously deployed. The database has a companion dashboard to visualise the data graphically.
Désingularisation des surfaces par des modifications de Nash normalisées

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Environmental sequencing of marine protistan plankton communities 1 reveals the effects of mesoscale cyclonic eddy transport on regional protistan 2 diversity in subtropical offshore waters 3

26 27 Mesoscale eddies which origin in Eastern Boundary Upwelling Systems 28 (EBUS) such as the Canary Current System entrap nutrient rich coastal water and 29 travel offshore while ageing. We have analyzed the protistan plankton community 30 structures in the deep chlorophyll maximum (DCM), sub-DCM and oxygen minimum 31 zone (OMZ) of three differently aged cyclonic EBUS eddies off Northwest Africa as 32 well as of non-eddy affected reference sites using DNA metabarcoding. Throughout 33 all water depths, we found that the investigated eddies generated local dispersal- 34 driven hotspots of protistan plankton diversity in the naturally oligotrophic subtropical 35 offshore waters off Northwest Africa. Based on the taxonomic composition of protistan 36 plankton communities, these diversity hotspots are likely to play an important role in 37 carbon sequestration and for regional food webs up to top predatory levels. Thereby, 38 the life-span of an eddy emerged as an important criterion, how local offshore protistan 39 plankton diversity is transformed quantitatively and qualitatively: each of the three 40 eddies was characterized by notably distinct protistan plankton communities. This 41 could be linked to the physicochemical water properties (predominantly 42 macronutrients, temperature and salinity) of the eddies’ cores and rings, which 43 experience pronounced changes during the eddies’ westward trajectories. 44 Furthermore, we found evidence that eddy-specific deep-water protistan communities 45 are relatively short-lived compared to the ones in the sunlit DCM. However, our results 46 do not only witness from the importance of fine-scale physical ocean features for 47 regional ecosystem processes, but they also show the complexity of these ocean 48 features and that we are still far from understanding the biological processes and their 49 driving forces in such features. 50
Scalable Neuroevolution of Ensemble Learners

In recent years, machine learning has become increasingly important in daily life. One of the most popular machine learning models used in many applications is an Artificial Neural Network (ANN). While in applications such as automatic speech recognition there is sufficient knowledge about the expected behavior for each input to use supervised learning, other applications like robot control define only an overall target so that the expected output for a given input can be ambiguous, making supervised learning inapplicable. Therefore, Topology and Weight Evolving ANN (TWEANN) has been developed in the past to evolve ANN topologies and connection weights. However, challenges of TWEANN are the design of genetic recombination and the exploration of huge search spaces for suitable solutions induced in particular by large-scale problems which can lead to impractical runtimes. To address the aforementioned issues, this paper proposes a novel evolutionary framework to evolve ensemble learners as specialized ANNs in a divide-and-conquer manner. Specifically, genetic recombination is heavily orchestrated for ANN combinations to effectively find suitable solutions in the search space restricted by ensemble methods. Experiments on various benchmark problems for solving control tasks show that the proposed framework clearly outperforms existing TWEANN algorithms.
ALIVE: Adaptive-Chromaticity for Interactive Low-light Image and Video Enhancement

Ray tracing remains of interest to Computer Graphics community with its elegant framing of how light interacts with objects, being able to easily support multiple light sources, and simple framework of merging synthetic and real cameras. Recent trends to provide implementations at the chip-level means raytracing’s constant quest of realism would propel its usage in real-time applications. AR/VR, Animations, 3DGames Industry, 3D-large scale simulations, and future social computing platforms are just a few examples of possible major impact. Raytracing is also appealing to HCI community because raytracing extends well along the 3D-space and time, seamlessly blending both synthetic and real cameras at multiple scales to support storytelling. This presentation will include a few milestones from my work such as the Slicing Extent technique and Directed Safe Zones. Our recent applications of applying machine learning techniques creating novel synthetic views, which could also provide a future doorway to handle dynamic scenes with more compute power as needed, will also be presented. It is once again renaissance for ray tracing which for last 50+ years has remained the most elegant technique for modeling light phenomena in virtual worlds at whatever scale compute power could support.
Measurement Error Proxy System Models: MEPSM v0.2

Proxy system models (PSMs) are an essential component of paleoclimate data assimilation and for testing climate field reconstruction methods. Generally, current statistical PSMs consider the noise in the output (proxy) variable only, and ignore the noise in the input (environmental) variables. This problem is exacerbated when there are several input variables. Here we develop a new PSM, the Measurement Error Proxy System Model (MEPSM), which includes noise in all variables, including noise auto- and cross-correlation. The MEPSM is calibrated using a quasi-Bayesian solution, which leverages Gaus- 5 sian conjugacy to produce a fast solution. Another advantage of MEPSM is that the prior can be used to stabilize the solution between an informative prior (e.g. with a non-zero mean) and the maximum likelihood solution. MEPSM is illustrated by calibrating a proxy model for δ 18 O coral with multiple inputs (marine temperature and salinity), including noise in all variables. MEPSM is applicable to many different climate proxies, and will improve our understanding of the effects of predictor noise on PSMs, data assimilation, and climate reconstruction.
South Asian summer monsoon enhanced by the uplift of Iranian Plateau in 1 Middle Miocene 2

The South Asian summer monsoon (SASM) remarkably strengthened during the 14 Middle Miocene (16-11 Ma), coincident with the rapid uplifts of the Iranian Plateau (IP) and 15 the Himalaya (HM). Although the development of the SASM has long been linked to the 16 topographic changes in the Tibetan Plateau (TP) region, the effects of the HM and IP uplift are 17 still vigorously debated, and the underlying mechanisms remain unclear. Based on Middle 18 Miocene paleogeography, we employ the fully coupled earth system model CESM to perform 19 a set of topographic sensitivity experiments with altered altitudes of the IP and the HM. Our 20 simulations reproduce the strengthening of the SASM in northwestern India and over the 21 Arabian Sea, largely attributing to the thermal effect of the IP uplift. The elevated IP insulates 22 the warm and moist airs from the westerlies in the south of the IP and produces a low-level 23 cyclonic circulation around the IP, which leads to the convergence of the warm and moist air 24 in the northwestern India and triggers positive feedback between the moist convection and the 25 large-scale monsoon circulation, further enhancing the monsoonal precipitation. Whereas the 26 HM uplift produces orographic precipitation without favorable circulation adjustment for the 27 SASM. We thus interpret the intensification of the Middle Miocene SASM in the western part 28 of the South Asia as a response to the IP uplift while the subtle SASM change in eastern India 29 reflects the effects of the HM uplift.
On accurate and efficient valuation of financial contracts under models with jumps

The aim of this thesis is to develop efficient valuation methods for financial contracts under models with jumps and stochastic volatility, and to present their rigorous mathematical underpinning. For efficient risk management, large books of exotic options need to be priced and hedged under models that are flexible enough to describe the observed option prices at speeds close to real time. To do so, hundreds of vanilla options, which are quoted in terms of implied volatility, need to be calibrated to market prices quickly and accurately on a regular basis. With this in mind we develop efficient methods for the evaluation of (i) vanilla options, (ii) implied volatility and (iii) common path-dependent options. Firstly, we derive a new numerical method for the classical problem of pricing vanilla options quickly in time-changed Brownian motion models. The method is based on rational function approximations of the Black-Scholes formula. Detailed numerical results are given for a number of widely used models. In particular, we use the variance-gamma model, the CGMY model and the Heston model without correlation to illustrate our results. Comparison to the standard fast Fourier option pricing method with respect to speed appears to favour our newly developed method in the cases considered. Secondly, we use this method to derive a procedure to compute, for a given set of arbitrage-free European call option prices, the corresponding Black-Scholes implied volatility surface. In order to achieve this, rational function approximations of the inverse of the Black-Scholes formula are used. We are thus able to work out implied volatilities more efficiently than is possible using other common methods. Error estimates are presented for a wide range of parameters. Thirdly, we develop a new Monte Carlo variance reduction method to estimate the expectations of path-dependent functionals, such as first-passage times and occupation times, under a class of stochastic volatility models with jumps. The method is based on a recursive approximation of the first-passage time probabilities and expected occupation times of Levy bridge processes that relies in part on a randomisation of the timeparameter. We derive the explicit form of the recursive approximation in the case of bridge processes corresponding to the class of Levy processes with mixed-exponential jumps, and