Miracle-dz/UniFAR-FTUs huggingface dataset:
Managed Futures, Hedge Fund and Mutual Fund Return Estimation: A Multi-Factor Approach

The past five years have witnessed a dramatic increase in managed futures products whose managers (commodity trading advisors) trade primarily in futures and options markets and which are available to the retail public as well as in hedge funds whose managers invest in both cash and futures markets simultaneously and which are structured primarily for pool investment and not for public sale. Despite this growth, funds invested in managed futures and hedge fund products are estimated to be less than 1% of the over 3 trillion dollar mutual fund industry. One reason for the relatively small percentage invested in managed futures or hedge fund vehicles is that little published research exists on the determinants of managed futures and hedge fund expected performance. However, while extensive literature exists on theoretical and empirical models of return expectation for stock and bonds, little academic research has directly tested for the underlying factors which explain managed futures and hedge fund return. In this paper, various factors, chosen to capture managed futures and hedge fund trading styles and investment markets, are used to explain managed futures and hedge fund performance. Similar tests are run on portfolios of traditional stock and bond funds in order to evaluate the relative explanatory power of the multiple factor models. Results indicate that for the managed futures, hedge fund, and mutual fund portfolios, a set of factors exist which help to explain managed futures, hedge fund, and mutual fund returns. These factors are based on the characteristics of the trading style (e.g., discretionary, systematic . . .) and the unique asset markets traded (e.g., currency, financial) of managed futures, hedge funds, and mutual funds. Results indicate that technical trading rule and market momentum variables are shown to explain managed futures return. In contrast, technical trading rules are shown to be less helpful in explaining return movements in traditional stock and bond funds whose returns are consistent with long positions in underlying cash markets, and hedge funds whose trading style is often based on capturing undervalued stock or bond investments. Results provide evidence that to the degree that underlying stock and bond markets provide explanatory power for traditional stock and bond managers returns but fail to describe the return patterns of managed futures and hedge fund products, while certain trend following and volatility factors help describe managed futures but not hedge fund return patterns, managed futures and hedge funds provide reasonable diversification patterns to traditional stock and bond funds as well as to each other.
Histopathological evaluation of autopsy cases with isolated pulmonary fat embolism (IPFE): is cardiopulmonary resuscitation a main cause of death in IPFE?

Background: Fat embolism (FE) may develop following many traumatic and atraumatic clinical conditions; however, fewer data exist regarding the occurrence of isolated pulmonary FE (IPFE). Cardiopulmonary resuscitation (CPR) is an emergency procedure for maintaining blood circulation and oxygenation during cardiac arrest. In this study, we aimed to evaluate the association of CPR with IPFE in autopsy cases. Methods: A total 402 cases among 4,118 autopsies were diagnosed with IPFE, and the medical background of these cases was retrospectively evaluated. Diagnosis of FE and FE grading were performed with histopathological examinations of postmortem tissue samples, and injury-severity scores of traumatic cases were assessed. Data of traumatic and atraumatic cases were statistically compared. Results: Of the IPFE cases, 298 (741%) were male and 104 (25.9%) female, with overall mean age 53.7 (2 – 99) years. Causes of death of studied subjects were traumatic for 302 (75.1%) and atraumatic reasons for 100 (24.9%) cases. CPR was performed for 277 cases of which 177 (63.9%) were traumatic and 100 (36.1%) were non-traumatic. In comparison to traumatic cases, signi ﬁ cantly higher CPR frequency was determined in atraumatic IPFE ( P =0.001). High grade FE in the traumatic cases, and mild-moderate grade of FE in the nontraumatic cases were found statistically signi ﬁ cant ( P =0.001). Conclusion: This study indicates that CPR may be one of the leading factors in the development of IPFE in atraumatic conditions, and this procedure was related to mild – moderate IPFE manifestations. Regardless of whether conditions were traumatic or atraumatic, in patients who survive following CPR for manifest ventilation/perfusion problems, it should be remembered that IPFE may have developed due to CPR.
R Index of Some Bridge Graphs

The degree of a vertex of a molecular graph is the number of first neighbors of the vertex. Sum degree and Multiplication degree of the vertex of a molecular graph is the sum of the degree of the vertices of the neighborhood vertices of the vertex and product of the degree of the vertices of the neighborhood vertices of a vertex respectively. The R degree of the vertex of a molecular graph is the sum of the sum degree of the vertex and the Multiplication degree of the vertex. The concept of degree in graph theory is closely interconnected to the concept of valence in chemistry. In this paper, some formulas are obtained for calculating the vertex based topological R index of the some Bridge graphs.
Identifying Narrative Contexts in Brazilian Popular Music Lyrics Using Sparse Topic Models: A Comparison Between Human-Based and Machine-Based Classification

Music lyrics can convey a great part of the meaning in popular songs. Such meaning is important for humans to understand songs as related to typical narratives, such as romantic interests or life stories. This understanding is part of affective aspects that can be used to choose songs to play in particular situations. This paper analyzes the effectiveness of using text mining tools to classify lyrics according to their narrative contexts. For such, we used a vote-based dataset and several machine learning algorithms. Also, we compared the classification results to that of a typical human. Last, we compare the problems of identifying narrative contexts and of identifying lyric valence. Our results indicate that narrative contexts can be identified more consistently than valence. Also, we show that human-based classification typically do not reach a high accuracy, which suggests an upper bound for automatic classification. narrative contexts. For such, we built a dataset containing Brazilian popular music lyrics which were raters voted online according to its context and valence. We approached the problem using a machine learning pipeline in which lyrics are projected into a vector space and then classified using general-purpose algorithms. We experimented with document representations based on sparse topic models [11, 12, 13, 14], which aims to find groups of words that typically appear together in the dataset. Also, we extracted part-of-speech tags for each lyric and used their histogram as features in the classification process.
Proof-of-Stake Blockchain Protocols with Near-Optimal Throughput

One of the most significant challenges in the design of blockchain protocols is increasing their transaction-processing throughput. In this work we put forth for the first time a formal execution model that enables to express transaction throughput while supporting formal security arguments regarding persistence and liveness. We then present a protocol in the proof-ofstake setting achieving near-optimal throughput under adaptive active corruption of any minority of the stake.
Cooperative Effects in Surfactant Adsorption Layers at Water/Alkane Interfaces

In the present work, the properties of dodecyl dimethyl phosphine oxide (C12DMPO) at the water/decane interface are studied and compared with those obtained earlier at the interface to hexane. To simulate the interfacial behavior, a two-component thermodynamic model is proposed, which combines the equation of state and Frumkin isotherm for decane with the reorientation model involving the intrinsic compressibility for the surfactant. In this approach, the surface activity of decane is governed by its interaction with C12DMPO. The theory predicts the influence of decane on the decrease of the surface tension at a very low surfactant concentration for realistic values of the ratio of the adsorbed amounts of decane and surfactant. The surfactant’s distribution coefficient between the aqueous and decane phases is determined. Two types of adsorption systems were used: a decane drop immersed into the C12DMPO aqueous solution, and a water drop immersed into the C12DMPO solution in decane. To determine the distribution coefficient, a method based on the analysis of the transfer of C12DMPO between water and decane is also employed.
Global Wealth Maximization Using Neuroeconomic Behavioral Drivers and GLOBAL WEALTH MAXIMIZATION USING NEUROECONOMIC BEHAVIORAL DRIVERS AND CONTINUOUS AUTOMATED TRADING

Digital technologies are ushering in an era of global market access for equity traders. Global markets, 24/7 access and an unprecedented trading opportunities have coalesced to further a need for automated trading. This paper presents a theory of stochastic price formation which is modeled by twin neural networks to simulate the psychology of high-frequency equity trading across global markets. The ex-post efficiency of the WINKS automated trading framework is calibrated by estimating quasi-elasticity coefficients. We document the relative importance of firm fundamental factors in the cognitive control of automated trading compared to the simple and less profitable buyand-hold strategy.
Advantages of Magnetic Mice over Trackballs as input devices on moving platforms

Although ergonomic studies show that cursor control with a computer mouse is faster and sometimes more accurate than cursor control with a trackball, trackballs are the standard input device for cursor movements on many moving platforms such as airplanes and ships. One reason for this is that trackballs can be fixed to the workstation, which prevents involuntary cursor movements that could otherwise be induced by movements of the platform. In this study, standard trackballs and computer mice with magnetic adhesion to the mouse pad were evaluated by 18 sailors of the German Navy after 26 days of computer operation on their moving ship. Results show that users of magnetic mice performed better and showed less muscular fatigue than trackball users. Thus, magnetic mice should be considered as the standard input device on moving platforms.
Cacheline Utilization-Aware Link Traffic Compression for Modular GPUs

Modular GPU systems are increasingly gaining attention for continued scaling of system sizes under packaging and fabrication challenges. In such systems, limited interconnect bandwidth can be a concern for system performance and energy efficiency. Compression has been widely considered as an effective means to reduce the amount of data moved. However, most prior related schemes are limited to exploiting the cacheline data values for achieving high compression ratios.We propose CUALiT: Cacheline Utilization-Aware Link Traffic compression to reduce I/O link traffic for modular GPU systems. Our approach exploits the variation in temporal and spatial utilization of individual cacheline words to achieve higher compression ratios. We utilize a novel mechanism to predict utilization of cachelines across warps at word granularity. Predicted unutilized words are dropped from responses. Furthermore, latency-critical words are compressed using traditional methods while words with temporal slack are coalesced across cachelines and compressed lazily to achieve higher compression ratios. CUALiT reduces offchip link traffic by 14% on average while achieving up to 25% lower system energy and an average 11% (up to 2x) higher performance over a compression only scheme.
Depressive symptoms and fatigue as mediators of relationship between poor sleep factors and medication adherence in HIV-positive women

Patients living with HIV commonly experience sleep disturbances, depression, excessive daytime sleepiness and fatigue, which negatively affect antiretroviral medication adherence. Few studies have examined relationships between these symptoms and medication adherence in women living with HIV or examine the mechanisms through which these symptoms affect adherence. The purpose of this study was to examine the associations between sleep quality, excessive daytime sleepiness and medication adherence, and energy/fatigue and depression as mediators of these relationships among 206 women living with HIV. Correlations, t-tests and hierarchical regression analysis were utilised. The majority of participants (93.2%) were African American or Black. The average age of participants was 43.3 years and average years infected was 9.6. More than half of the women reported poor sleep quality and, on average, participants reported moderate daytime sleepiness, high depressive symptoms and moderate levels of fatigue. Additionally, both depression and low energy/fatigue were identified as significant mediators of the relationship between sleep quality and medication adherence. Depression also significantly mediated the relationship between excessive daytime sleepiness and medication adherence. The findings from this study highlight the impact of sleep on medication adherence and associated mechanisms and emphasise the need for healthcare providers to assess and address sleep factors when providing care for patients living with HIV.
An Extensible Framework for Indoor Positioning on Mobile Devices

Recently, the domain of navigational applications has seen a huge rise. Due to the rising popularity of smartphones which are nowadays equipped with Global Positioning System (GPS) receivers, a great number of people who own these devices have the possibility to easily get information about their position and have a greater need for good navigational applications. Such applications, for example Google maps, work great when used outdoors. However, when we try to use these applications indoors, we have major problems in finding our correct position. Because the GPS needs to have an unobstructed line of sight to the GPS satellites, we encounter problems when trying to locate our position indoors. Some theoretical aspects have to be covered, concerning radiolocation and indoor positioning, before we can continue by summarising the various different solutions that already exists in other projects, each with their own use of specific technologies and techniques. We will see that most of these were created for specific hardware and using some explicit algorithm however. And despite the fact that there exist a number of frameworks, they all have their own limitations. Therefore, in this thesis we explore the notion of an Indoor Positioning System (IPS) in terms of a framework that works for various mobile devices and is extensible to be used with numerous algorithms and techniques. The design and implementation of this framework is discussed in detail and afterwards, an example IPS that uses Wireless local area network (WLAN) infrastructure and works with the Android platform is implemented using the framework. Several test were performed on the performance of this system, which are also presented.
9 B . 2 Collision-induced drop oscillations from wind-tunnel experiments

Knowledge of drop shapes and drop oscillations is of central importance for deriving retrieval algorithms for drop size distribution (DSD) parameters and rain rate as well as for attenuationcorrection at higher frequencies (C, Xbands) from polarimetric radar (e.g., Bringi and Chandrasekar 2001 and references contained therein). Earlier work using 2D video disdrometer (2DVD) measurements of drop shapes (Thurai et al. 2007) for drop diameters larger than 2 mm had lead to the derivation of the most-probable shapes as well as the shape variations due to drop oscillations. The 2DVD-based shapes had also been shown to be in good agreement with wind-tunnel measurements for D > 2 mm (Thurai et al., 2009). Moreover, a thorough examination of the 2DVD camera data in natural rain from several locations have shown that in the vast majority of cases, the most ‘probable' shapes conform to those arising primarily from the axisymmetric (2,0) oscillation mode (Beard et al. 2010). The other two oscillation modes, namely, mode (2,1) and mode (2,2), did not seem to be contributing to the probable shapes. Fig. 1 shows the most probable shapes for drop equivalent diameters of 3 and 4 mm from the 2DVD measurements in natural rain and fig. 2 shows the three oscillation modes at the various oscillation cycles. A large drop size is used to depict the three modes clearly. (a)
A Hybrid Approach to Recommend Partners in Collaborative Musical Environments

Collaboration is an important element in the human creative construction process, and takes special significance in music composition. Systems that support collaborative activities with creative focus have been growing largely lately. However, there is a lack of tools that assists users of these systems to find partners to collaborate with in their activities. In this context, this paper presents a hybrid approach – based on both content-based and collaborative filtering – to recommend partners in creative collaborative environments focused on their produced work. Its main characteristics and functionalities are demonstrated by its design on CODES, a platform for music prototyping for lay users.
Timbre spaces with sparse autoencoders

Timbre perception studies emphasize the multidimensional nature of timbre and many rely on dimensionality reduction techniques to visualize perceptual similarity evaluations or sound descriptors that encompass timbre perception. In this work, we explore the uses of sparse autoencoders to perform unsupervised learning and nonlinear dimensionality reduction to extract a spectral code representation that is used for timbre analysis and visualization. Using only one music fragment in the autoencoder learning process generates an overfitted reconstruction but gives a low dimensional neuronal activity pattern which encodes all the sound spectrum information and could be used for synthesis as a neuronal music score.
A Rapid Tapping Task on Commodity Smartphones to Assess Motor Fatigability

Fatigue is a common debilitating symptom of many autoimmune diseases, including multiple sclerosis. It negatively impacts patients' every-day life and productivity. Despite its prevalence, fatigue is still poorly understood. Its subjective nature makes quantification challenging and it is mainly assessed by questionnaires, which capture the magnitude of fatigue insufficiently. Motor fatigability, the objective decline of performance during a motor task, is an underrated aspect in this regard. Currently, motor fatigability is assessed using a handgrip dynamometer. This approach has been proven valid and accurate but requires special equipment and trained personnel. We propose a technique to objectively quantify motor fatigability using a commodity smartphone. The method comprises a simple exertion task requiring rapid alternating tapping. Our study with 20 multiple sclerosis patients and 35 healthy participants showed a correlation of rho = 0.8 with the baseline handgrip method. This smartphone-based approach is a first step towards ubiquitous, more frequent, and remote monitoring of fatigability and disease progression.
I/VOID/O: real-time sound synthesis and video processing in an interactive installation

This paper presents some technical and aesthetic aspects involved in the conception of the interactive installation I/VOID/O concerning both the visual and sonic processes generated in real-time with Max/MSP/Jitter. It mentions the main characteristics of the installation and how the patches were implemented in order to provide coherent relationships between sound and image with the aim of offering an immersive experience for the people who visit and interact with the installation.
PATHWISE STOCHASTIC TAYLOR EXPANSIONS AND STOCHASTIC VISCOSITY SOLUTIONS FOR FULLY NONLINEAR STOCHASTIC PDES BY RAINER BUCKDAHN

In this paper we study a new type of “Taylor expansion” for Itô-type random fields, up to the second order. We show that an Itô-type random field with reasonably regular “integrands” can be expanded, up to the second order, to the linear combination of increments of temporal and spatial variables, as well as the driven Brownian motion, around even a random (t, x)-point. Also, the remainder can be estimated in a “pathwise” manner. We then show that such a Taylor expansion is valid for the solutions to a fairly large class of stochastic differential equations with parameters, or even fully-nonlinear stochastic partial differential equations, whenever they exist. Using such analysis we then propose a new definition of stochastic viscosity solution for fully nonlinear stochastic PDEs, in the spirit of its deterministic counterpart. We prove that this new definition is actually equivalent to the one proposed in our previous works [2] and [3], at least for a class of quasilinear SPDEs.
OPPORTUNITIES FOR THE USE OF COMPOSITE MATERIALS IN RAIL APPLICATIONS – A CASE STUDY

Lightweighting is an increasing focus in the rail industry and attention is turning to the application of composite beams to satisfy demands. Patented technology AxontexTM, developed by Axon Automotive Ltd for the automotive sector, moves away from traditional high-waste composite solutions and offers a potential alternative to metal components currently used in the rail sector. It offers a new way of designing car bodies and bogies with flexibility in the dimensions and properties of the beam along its length, width and height, supporting end-users’ needs. This paper reviews the opportunities for the use of composite materials in rail, and includes a specific discussion around the use of braided AxontexTM beams, and their applicability to rail structural members. The quasi-static behaviour of the beams reveals advantages and benefits in using composites, with an improvement in specific stiffness of over 50 % compared to steel, whilst the environmental aging and fatigue testing needs further investigation.
Automatic Neume Transcription of Medieval Music Manuscripts using CNN/LSTM-Networks and the segmentation-free CTC-Algorithm

The automatic recognition of scanned Medieval manuscripts still represents a challenge due to degradation, non standard layouts, or notations. This paper focuses on the Medieval square notation developed around the 11th century which is composed of staff lines, clefs, accidentals, and neumes which are basically connected single notes. We present a novel approach to tackle the automatic transcription by applying CNN/LSTM networks that are trained using the segmentation-free CTC-loss-function which considerably facilitates the Ground Truth (GT)-production. For evaluation, we use three different manuscripts and achieve a diplomatic Symbol Accuracy Rate (dSAR) of 86.0% on the most difficult book and 92.2% on the cleanest one. To further improve the results, we apply a neume dictionary during decoding which yields a relative improvement of about 5%.