Miracle-dz/UniFAR-FTUs huggingface dataset:
AM An Artificial Neural Networks Modeling Approach Applied to the Probabilistic Management of Water Resources Systems

A multivariate non-linear model for synthetic generation of monthly discharge series is presented. The time series generator is built upon a multilayer feedforward neural network with an added multivariate random component normally distributed. The usual error backpropagation algorithm is used to train the network, with a sequential training scheme using shuffled patterns for a stochastic search in the weight space. The proposed model generates inputs to a wider methodology developed for simulation of the probabilistic managing of the upper Tagus River system in Spain. The model is validated in terms of its ability to reproduce some relevant statistics directly related to important features from the water resources system managing point of view, including droughts and storage derived statistics. The generator was inserted into a decision support system, and a variety of possible future hydrological scenarios in the river system were simulated, with particular consideration of demand failures probabilities under different assumptions and previous hydrological states of the system. For comparison purposes, similar experiments were also undertaken using synthetic series generated with a second-order autoregressive multivariate model, AR(2). The results obtained show higher percentages of demand failures when inputs from the artificial neural network generator (ANN) are used. The case study illustrates another practical application of ANN approaches, adequately combined with other frequently used tools in the context of water resources systems planning and management.
Chapter 5 EVIDENCE FOR INBREEDING IN JUVENILE PLAICE , Pleuronectes platessa L . ( TELEOSTEI : PLEURONECTIDAE )

Heterozygote deficiencies have been consistently observed in plaice. To investigate possible causes of this result, we first ruled out the possibility of genotyping artefacts. We then compared temporal changes in FIS estimates by genotyping sequential cohorts of individuals collected on a biweekly basis from two genetically distinct nursery grounds in the Dutch Wadden Sea and in Iceland. Strongly positive and highly significant FIS estimates (0.151 – 0.233) were found in all ten cohorts based on 8-locus, microsatellite genotypes. Six of the eight loci showed significant single-locus FIS estimates in >80% of the cohorts. No evidence was found for a temporal Wahlund effect and a plot of multilocus FIS against age suggested no evidence for selection. The frequency of lower individual-multilocus-heterozygosity (MLH)-classes was higher than expected under random mating (P<0.001) indicating the presence of inbred individuals. Relatedness (I), was also found in two cohorts. We discuss how low effective population size, in combination with fisheries related depletion of kin-structured spawning aggregations, may have led to inbreeding in plaice. We further recommend that the finding of heterozygote deficiencies –which are common in fish population genetic surveysbe thoroughly investigated before assuming that it is due to technical artefacts as opposed to biological processes.
High sensitivity of HLA-B*5701 in Whites and Blacks in immunologically-confirmed cases of abacavir hypersensitivity (ABC HSR)

Objectives: HLA-B*5701 is highly associated with ABC HSR in Whites. However, variable sensitivities are reported across studies and races where clinical data alone defined ABC HSR. Because accurate identification of phenotype is critical for determining sensitivity, this study estimates the sensitivity of HLA-B*5701 in Whites and Blacks using skin patch testing (SPT) to supplement HSR diagnosis. Methods: Subjects who had clinically-suspected ABC HSR were retrospectively identified and then tested for HLA-B*5701 and underwent ABC SPT (Study ABC107442, clinicaltrials.gov identifier: NCT00373945). Cases were defined as (1) All ABC HSR regardless of SPT results and (2) ABC HSR with a positive SPT result. Controls were subjects who tolerated ABC for 312 weeks without HSR.
Machine learning techniques applied to US army and navy data

We apply machine learning techniques to the synthetic data (Stevens and Anderson-Cook, 2017a), which is univariate data with a binary response of passing or failing for complex munitions generated to match age and usage rate, found in US Department of Defense complex systems (the army and navy). We propose applying machine learning techniques to predict the binary response of passing or failing for the army and navy data.
Does Management Forecast Guidance Impair the Usefulness of Analyst Forecasts in Firm Valuation ?

Analyst earnings forecasts are an important input to the Residual Income Valuation model; however, these forecasts are increasingly subject to management guidance. This study examines the impact of management forecast guidance on the usefulness of analyst earnings forecasts in firm valuation. It finds that valuation models estimated using guided forecasts have less ability to explain stock price and predict future returns through value-to-price ratios than valuation models estimated using non-guided forecasts. These results provide evidence that management forecast guidance reduces the usefulness of analyst forecasts in firm valuation and impairs the performance of forecast-based valuation models to predict firm value.
Traffic Engineering and Energy-Efficient Routing in IP-Based Mobile Networks

Current IP mobile backbone networks exhibit poor power efficiency, running network devices at full capacity all the time regardless of the traffic demand and distribution over the network. Network operators usually build networks with redundant and overprovisioned links resulting in low link utilization during most of the time. While these redundant links and bandwidth greatly increase the network reliability, they also greatly reduce the network’s energy efficiency as all the network devices are powered ON at full capacity but highly under-utilized most of the time. Most research on router power management treat routers as isolated devices. An alternate approach is to facilitate power management at network level by routing traffic through different paths to adjust the workload on individual routers or links. In this thesis work focuses on intra-domain traffic engineering mechanism, EE-TE formulated based on MCF model and it is solved using the powerful optimization engine CPLEX. The EE-TE model maximizes the total power saving of routers in a network by finding energy efficient routing paths for each OD pair and also shows how to split the traffic on a chosen path depending on the actual traffic demand measured in the network. EE-TE maximizes the number of links that can be put into sleep under given performance constraints such as link utilization and traffic split ratio. Using random network topologies and traffic demand profiles, the evaluation shows that EE-TE can reduce line-cards’ power consumption by 20 % to 40 % under constraints that the maximum link utilization is below 50 % for IP-based mobile backbone networks.
An Approach in Designing 16-point DFT with Decimation in Time based on Rademacher Functions

This paper presents a circuit design for 16-point DFT algorithm with Decimation in Time based on products of Rademacher functions. The designed circuit is constructed from two 8-point DFT and four 2-point DFT. However, the operation of the design circuit is different. It utilised the advantages of the similarity of Fourier transforms, and Rademacher functions. Therefore, the proposed design is constructed from previously designed 8-point DFT which is based on products of Rademacher functions. Some analysis of the type of numbers, internal connections and the complex conjugate of the results to achieve the more efficient circuit has been made. Therefore, instead of eight, the proposed design requires only five 2-point DFTs. Therefore, six output results of the design 16-point DFT have been removed since they are equal regarding magnitude to the other results, but six negative circuits are required as compensation. Therefore, the previously designed circuit of 8- point DFT has been replaced with the new circuit design. This circuit is specially designed for non-standalone used; the circuit must be integrated inside the proposed 16-point DFT.
LEARNING TO DECIDE A FORMAL LANGUAGE : A RECURRENT NEURAL NETWORK

We use recurrent neural networks (RNNs) for deciding locally k-testable languages. We show that, when used for deciding languages, RNNs fail to generalise to unseen examples. However, using attention greatly improves the generalisation. We then implement a differentiable version of the scanner used for deciding locally k-testable languages. We show that RNNs are able to store the k-factors in its memory but not arrange then as a look-up table which is necessary for deciding languages specified by multiple k-factors.
SO links with diversity pointing errors and temporal broadening of he pulses over weak to strong atmospheric turbulence channels

Free space optical (FSO) communication systems show a growing evolution in the commercial and the research field, due to the huge information capacity they provide along with the unlicensed and secure data transmission they can support. However, several destructive effects, such as the atmospheric turbulence and attenuation, the longitudinal pulse broadening due to the time dispersion, the spatial jitter which caused by the pointing errors between the trans-receivers, among others, mitigate their performance characteristics. Thus, for the improvement of the FSO communication systems’ performance, many techniques have been proposed, studied and used. In this work, we present a performance study and we derive closed form mathematical expressions for the estimation of the probability of fade for On–Off keying FSO communication systems which use Gaussian longitudinal pulses as information bit carriers, with reception diversity, over gamma gamma or gamma modelled, atmospheric turbulence channels taking into account the pointing errors and the group velocity dispersion (GVD) effect which, affects significantly the systems performance characteristics, especially for long link lengths and high data rate transmission. Finally, the derived mathematical expressions are used in order to present performance results, using common parameter values for channel’s and systems’ characteristics. © 2015 Elsevier GmbH. All rights reserved.
15 . 4 a CSS-based mobile object locating system using sequential

With the widespread use of mobile devices equipped with various types of sensors, the need for location awareness in mobile environments is increasing. Many range-based approaches focus on localization accuracy but are vulnerable to ranging noises. In this paper, we propose a practical mechanism for a mobile object locating system. The mechanism applies the bootstrap particle filter and likelihood functions to the IEEE802.15. 4a Chirp Spread Spectrum (CSS) ranging functionality. Based on the empirical characteristics of the prototype hardware, we developed an accurate and practical localization mechanism by using a CSS-specific adaptive likelihood distribution in real environments. The simulation and experiment results show that the proposed scheme outperforms previous techniques. 2013 Elsevier B.V. All rights reserved.
Water Flow in Soils with Heterogeneous Macropore Geometries

Increasing macropore volume may decrease the final cumulative outflow. Heterogeneous macroporous geometries can be represented explicitly or implicitly. HYDRUS‐1D and SWAP performed well in soils with heterogeneous macroporous geometries. Dead‐end macropores are included by changing lateral transfer parameters with depth.
Lehmann ' s Work on Decision Theory

This chapter collects some of Erich's work on areas that attracted his attention during the early years in his professional career. Thus, the papers discuss the concepts of completeness (minimal complete families and complete sufficient statistics), minimal sufficiency, admissibility, invariance, unbiasedness, and minimaxity. In Lehmann (1947) Erich argued that, in the absence of a uniformly most powerful (UMP) test, it is then a difficult choice to select a "best" test. Since there may be too many choices, it was proposed to reduce the totality of possible tests, by restricting attention to a class of tests F such that for any test if> of a hypothesis 1{ of a given significance level, there is a corresponding test¢* in F with power uniformly larger than or equal to the power of¢; and if ¢ 1, ¢2 E F, then the power of ¢ 1 is not uniformly larger than the power of ¢2 and vice versa. That is, in the absence of a UMP test, F is the smallest class from which to select a test when the selection is made based on power. Although there are other important ideas in the paper, this concept became a central part of Wald's statistical decision theory. In Lehmann (2008), Erich writes that
Strategic contractual relationships in the automotive sector Relações contratuais estratégicas no setor automotivo Relaciones contractuales estratégicas en la industria automotriz

he aim of the present study is to understand contractual relations through the complementarity of the Transaction Costs Theory, Measurement Costs heory, and the Resource-Based View. Initially, we sought to define an analytical model appropriate to the complementarity objective, considering he categories of each approach. The proposition was: given the possibility of measuring the attributes of products, the contractual relationship an be used to guarantee property rights over assets of high specificity and strategic value, avoiding the costs of vertical integration. Secondly, qualitative descriptive cross-cut (2014 and 2015) study was carried out. In this phase, the complementarity proposition was analyzed based on ata obtained through semi-structured interviews with logistics, production, and purchasing managers of automakers located in the state of Paraná, nd some of their direct suppliers. Our proposition indicates that when there is the possibility of measuring product attributes, the contractual elationship can be used to secure property rights of high-specificity assets and strategic resources, avoiding the costs of vertical integration. This roposition was verified because, in the case of high-specificity auto parts, the measurability of their dimensions ensures protection of specific and esidual property rights. In the case of strategic resources, when there is a possibility of measurement and control, contracting is allowed, even ncluding the acquisition of innovations that bring competitive advantage (Bluetooth, integrated GPS with SD card, back-up sensor, air bags). It as observed that, even though competitive advantages constitute valuable and rare resources for automakers at their launch, this did not prevent ontracting. Verification can offer an alternative path to rational Transaction Costs Theory, as proposed by Williamson, and the use of vertical ntegration as a form of controlling strategic resources, recommended by the Resource-Based View, which still requires further studies in order to vercome persistent limitations in the model. 2017 Departamento de Administração, Faculdade de Economia, Administração e Contabilidade da Universidade de São Paulo – FEA/USP. ublished by Elsevier Editora Ltda. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
The political economy of multilateral lending to European regions

We study the political economy of allocation decisions within a major state investment bank. Our focus is the European Investment Bank (EIB) – “The Bank of the EU” – which is the largest multilateral lending (and borrowing) institution in the world. We study the behavior of about 500 national representatives at the EIB’s Board of Directors – the bank’s decisive body for loan approvals – and show that a representative’s appointment increases the probability that the sub-national region where she works receives a loan by about 17 percentage points. This “home-bias” effect is driven by large loans financing infrastructure projects. We discuss several pieces of evidence, which are consistent with the hypothesis that this home-bias lending may be due to favoritism, however, we cannot conclusively demonstrate this case of resource misallocation.
PsychRNN : An open-source Python package for training artificial recurrent neural networks on cognitive tasks

Modeling using recurrent neural networks (RNNs) is quickly becoming a popular strategy to probe the mechanisms behind cognitive tasks. RNNs are able to accomplish many popular cognitive tasks but are vastly more manipulable and observable than other classic model organisms such as monkeys and humans. Modeling is a fast, inexpensive way to investigate the abilities and limitations of proposed mechanisms behind cognitive tasks, and can lead to deeper understanding of current proposed mechanisms, as well as propose new mechanistic hypotheses. These insights can in turn guide experimental focus to better distinguish between current proposals. Here we introduce an accessible and extensible Python package for training RNNs on a variety of cognitive tasks. While our package already includes implementations of multiple cognitive tasks, we also provide an accessible framework (requiring only knowledge of Python and NumPy) for easily defining new cognitive tasks and for customizing existing tasks. The deep learning details are handled by the TensorFlow-based backend and are extensible for projects that require additional customization. We provide multiple initializations, loss functions and regularizations as well as a framework to easily add more. Our package focuses on facilitating specification of neurobiological constraints on synaptic architecture and on learning. We include optional implementations Dale’s Law, neurobiologically plausible sparse connectivity, regional connectivity differences and individual unit time-constants. The design of PsychRNN further enable novel investigations. Task modularity makes it easy to investigate how parametric variations in task demands determine network solutions. Our package additionally can return intermediate network solutions so researchers can investigate how network solutions develop over the course of training. PsychRNN allows researchers to implement task shaping (also known as curriculum learning) – training is adjusted in closed loop based on performance. Experimentalists regularly train animals to perform tasks by shaping tasks – PsychRNN allows investigation of how shaping trajectory choice could affect the observed results. PsychRNN is available at https://github.com/dbehrlich/PsychRNN.
Research Statement

With the seeming end of Moore’s law, software does not automatically get faster every year: per-core CPU performance has stagnated, and core count increases slowly. My goal is to develop and disseminate techniques to build faster systems in this challenging new world. As noted by Leiserson et al. [12], two promising methods to improve system performance are optimizing software to best use the available silicon, and using specialized hardware tuned to speci c applications. A key challenge facing computing is to create a cohesive roadmap for future hardware specialization: how far can we go with existing hardware, and when must we turn to the more expensive option of deploying specialized hardware? My work makes the case that today’s software has failed to capitalize on the performance and capabilities available within the existing hardware; we must address this failure rst before looking to specialized hardware. A directly related question concerns the division of labor between existing and specialized hardware. For example, should “smart” NICs provide functionality such as kernel-bypass networking, Remote Direct Memory Access (RDMA), and congestion control? My results suggest that while supporting kernel-bypass in NICs is crucial for performance, the latter two can be handled well by existing CPUs. Somewhat surprisingly, my work shows that in many applications for which specialized hardware—RDMA NICs, FPGAs, programmable switches, and GPUs—has been proposed, existing hardware can provide better or comparable performance. This result holds across a wide range of core systems problems: networked key-value storage and sequencing, distributed transaction processing, state machine replication, software packet processing, and regular expression matching. The di erentiating aspect of my work has been its focus on building a deeper understanding of the capabilities of hardware—both existing and specialized—through extensive micro-benchmarking and analysis. Two outcomes of these studies led to the result above. First, I created numerous new optimizations for systems running on existing hardware by leveraging hardware capabilities in novel ways. Second, I found that for several applications, the proposed specialized hardware is a bad match from the perspective of the device’s architecture, functionality, or placement. For example, a GPU accelerator placed over the slow PCIe bus is ill-suited for low-latency packet processing. Successful use of specialized hardware, such as TPUs for machine learning at Google or FPGAs for network virtualization at Microsoft, requires getting these matches right.
Persuasive evidence of market inefficiency A book / price strategy and a “ specific-return-reversal " strategy

T mL, his article reports the statistically significant abnormal performance of two strategies. One strategy is a “book/price" strategy. The strategy buys stocks with a high ratio of book value of common equity per share to market price per share and sells stocks with a low book/price ratio, where "book value” is com­ mon equity per share, including intangibles. The sec­ ond strategy is a "specific-return-reversal" strategy. This strategy calculates the difference between the investment return for the previous month on the stock and a fitted value for that return based upon common factors in the stock market in the previous month. This differential return is the "specific return" that is unique to the stock. This strategy expects the specific return to reverse in the subsequent month. It there­ fore buys stocks having negative specific returns in the prior month. We selected both strategies as interesting can­ didates for tests of market inefficiency based on data through 1980. We evaluated the prior performance of the strategies in 1980 and described them in speeches and articles in 1982 [6, 7, 10, 11]. Based on monthly returns since the completion of the prior study, both strategies have shown persuasive evidence of market inefficiency. Despite the relatively short time span, the strat­ egies have separately achieved t-statistics of 3.7 and 11.54, respectively, each implying that the null hy­ pothesis of market efficiency can be rejected at a very high level of confidence. Further, both strategies pro­ duced performance in this evaluation period that was closely consistent with their prior performance. We obtained still higher t-statistiCs when the prior data and the evaluation-period data were combined. The two strategies are also expected to be sta­ tistically independent a priori, because the results have shown a negative and statistically insignificant correlation during the evaluation period. Thus, each study is an independent test of market inefficiency, which means that the confluence of the two results suggests still stronger evidence for market inef­ ficiency. We defined the strategies and singled them out for prospective study because we felt that they arose naturally as straightforward tests of market efficiency. Each strategy can be viewed as the result of using an "instrumental variable" for pricing error. To the ex­ tent that pricing errors, for whatever cause, are pres­ ent in the U.S. stock market, we anticipated that these tests might show up that inefficiency by means of the instrumental variables (the book/price ratio and the prior m onth's specific return, respectively) that are used. We believe that this study leads to the inescap­ able conclusion that prices on the New York Stock Exchange are inefficient.