Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactive Evaluation of a Music Preprocessing Scheme for Cochlear Implants Based on Spectral Complexity Reduction

Music is difficult to access for the majority of CI users as the reduced dynamic range and poor spectral resolution in cochlear implants (CI), amongst others constraints, severely impair their auditory perception. The reduction of spectral complexity is therefore a promising means to facilitate music enjoyment for CI listeners. We evaluate a spectral complexity reduction method for music signals based on principal component analysis that enforces spectral sparsity, emphasizes the melody contour and attenuates interfering accompanying voices. To cover a wide range of spectral complexity reduction levels a new experimental design for listening experiments was introduced. It allows CI users to select the preferred level of spectral complexity reduction interactively and in real-time. Ten adult CI recipients with post-lingual bilateral profound sensorineural hearing loss and CI experience of at least 6 months were enrolled in the study. In eight consecutive sessions over a period of 4 weeks they were asked to choose their preferred version out of 10 different complexity settings for a total number of 16 recordings of classical western chamber music. As the experiments were performed in consecutive sessions we also studied a potential long term effect. Therefore, we investigated the hypothesis that repeated engagement with music signals of reduced spectral complexity leads to a habituation effect which allows CI users to deal with music signals of increasing complexity. Questionnaires and tests about music listening habits and musical abilities complemented these experiments. The participants significantly preferred signals with high spectral complexity reduction levels over the unprocessed versions. While the results of earlier studies comprising only two preselected complexity levels were generally confirmed, this study revealed a tendency toward a selection of even higher spectral complexity reduction levels. Therefore, spectral complexity reduction for music signals is a useful strategy to enhance music enjoyment for CI users. Although there is evidence for a habituation effect in some subjects, such an effect has not been significant in general.
DNA Methylation Cancer Biomarkers: Translation to the Clinic

Carcinogenesis is accompanied by widespread DNA methylation changes within the cell. These changes are characterized by a globally hypomethylated genome with focal hypermethylation of numerous 5’-cytosine-phosphate-guanine-3’ (CpG) islands, often spanning gene promoters and first exons. Many of these epigenetic changes occur early in tumorigenesis and are highly pervasive across a tumor type. This allows DNA methylation cancer biomarkers to be suitable for early detection and also to have utility across a range of areas relevant to cancer detection and treatment. Such tests are also simple in construction, as only one or a few loci need to be targeted for good test coverage. These properties make cancer-associated DNA methylation changes very attractive for development of cancer biomarker tests with substantive clinical utility. Across the patient journey from initial detection, to treatment and then monitoring, there are several points where DNA methylation assays can inform clinical practice. Assays on surgically removed tumor tissue are useful to determine indicators of treatment resistance, prognostication of outcome, or to molecularly characterize, classify, and determine the tissue of origin of a tumor. Cancer-associated DNA methylation changes can also be detected with accuracy in the cell-free DNA present in blood, stool, urine, and other biosamples. Such tests hold great promise for the development of simple, economical, and highly specific cancer detection tests suitable for population-wide screening, with several successfully translated examples already. The ability of circulating tumor DNA liquid biopsy assays to monitor cancer in situ also allows for the ability to monitor response to therapy, to detect minimal residual disease and as an early biomarker for cancer recurrence. This review will summarize existing DNA methylation cancer biomarkers used in clinical practice across the application domains above, discuss what makes a suitable DNA methylation cancer biomarker, and identify barriers to translation. We discuss technical factors such as the analytical performance and product-market fit, factors that contribute to successful downstream investment, including geography, and how this impacts intellectual property, regulatory hurdles, and the future of the marketplace and healthcare system.
Ecological Attributes of Carnivore-Livestock Conflict

Mitigation of carnivore-human conflict due to domestic animal predation represents an imperative challenge. Although livestock management strategies aimed at reducing predation have recently received attention by wildlife managers and producers, the information regarding ecological attributes of studied predators and environmental characteristics of the areas where conflicts occur is largely missing. We conducted a global review to characterize the literature of carnivore-livestock conflict, identifying the set of reported predators, and assessing the ecological attributes of these species and areas where predation has occurred. A total of 391 published peer-reviewed research papers on carnivore-livestock conflict containing 783 predation study cases were evaluated. Carnivore-livestock conflict research was largely conducted in Asian and African countries (80% of published studies). Fifty-two carnivores were reported in conflict-related studies being Felidae and Canidae the most frequently studied groups (80% of study cases). Carnivores more often reported to prey on domestic animals exhibit larger home ranges and body masses, and are also subject to larger reductions in their distribution ranges. They also show a generalist habitat behavior, a strictly carnivore diet, and cathemeral activity. Predation of domestic animals consistently increased with vegetation cover, decreased with distance from human settlement and was higher in young animals. The analysis conducted separately for large and meso carnivores showed that predation on domestic animals by large carnivores (> 21.5 kg) increased near protected areas and far from human settlements. Current information regarding conflicts exhibits a notable variation in research effort towards some regions and large-bodied and broadly distributed species. This asymmetry could reflect the role of human perspectives in research based on species-level traits, research facilities and funding opportunities, though also underlies ecological processes induced by land transformation occurring in some regions across the globe. As encroached habitat increases, species with restricted distributions and behaviors, or smaller home ranges such as meso carnivores, will roam into human-dominated landscapes, increasing their probability of interacting with livestock activity. Identifying ecological attributes that distinguish carnivores and areas as “conflict-prone” may contribute to set evidence-based management approaches in frameworks ready to anticipate, reduce or prevent human-carnivore conflict, complementing the use of other strategies.
A Knowledge Processing Service for Robots and Robotics/AI Researchers

Making future autonomous robots capable of accomplishing human-scale manipulation tasks requires us to equip them with knowledge and reasoning mechanisms. We propose OPEN-EASE, a remote knowledge representation and processing service that aims at facilitating these capabilities. OPEN-EASE gives its users unprecedented access to the knowl- edge of leading-edge autonomous robotic agents. It also provides the representational infrastructure to make inhomogeneous experience data from robots and human manipulation episodes semantically accessible, and is complemented by a suite of software tools that enable researchers and robots to interpret, analyze, visualize, and learn from the experience data. Using OPEN-EASE users can retrieve the memorized experiences of manipulation episodes and ask queries regarding to what the robot saw, reasoned, and did as well as how the robot did it, why, and what effects it caused.
The impact of hospital financing on the quality of inpatient care in England

We assess the impact of the English version of prospective payment, termed Payment by Results (PbR), on hospital quality, as measured by in-hospital mortality and 28-day emergency readmission. To do this, we exploit the phased introduction of PbR across hospitals and across three treatments (hip replacement, hernia repair and stroke) which were exposed to PbR at different times. We estimate regression models to analyse factors associated with patient survival and readmission for all those admitted for hip replacement (n=499,555), hernia repair (n=414,959) or following stroke (n=487,040) between 2002/3 and 2007/8. Factors include patient and hospital characteristics and the proportion of hospital income derived from PbR. We find that the probability of survival improved over time while changes in crude readmission rates varied by condition. Patient characteristics are important at explaining survival and readmission, and hospital size and specialisation also appear significant, though not consistently so across conditions or time. The probability of surviving stroke is lower for those admitted over the weekend. Given the high mortality rate for stroke, it is critical to account for the probability of surviving the initial admission when evaluating readmissions. PbR does not appear to have influenced the probability of survival or readmission.
Hedonic Clustering Games

Clustering, the partitioning of objects with respect to a similarity measure, has been extensively studied as a global optimization problem. We investigate clustering from a game-theoretic approach, and consider the class of hedonic clustering games. Here, a self-organized clustering is obtained via decisions made by independent players, corresponding to the elements clustered. Being a hedonic setting, the utility of each player is determined by the identity of the other members of her cluster. This class of games seems to be quite robust, as it fits with rather different, yet commonly used, clustering criteria. Specifically, we investigate hedonic clustering games in two different models: fixed clustering, which subdivides into k-median and k-center, and correlation clustering. We provide a thorough analysis of these games, characterizing Nash equilibria, and proving upper and lower bounds on the price of anarchy and price of stability. For fixed clustering we focus on the existence of a Nash equilibrium, as it is a rather nontrivial issue in this setting. We study it both for general metrics and special cases, such as line and tree metrics. In the correlation clustering model, we study both minimization and maximization variants, and provide almost tight bounds on both the price of anarchy and price of stability.
Coarse grain parallelization of deep neural networks

Deep neural networks (DNN) have recently achieved extraordinary results in domains like computer vision and speech recognition. An essential element for this success has been the introduction of high performance computing (HPC) techniques in the critical step of training the neural network. This paper describes the implementation and analysis of a network-agnostic and convergence-invariant coarse-grain parallelization of the DNN training algorithm. The coarse-grain parallelization is achieved through the exploitation of the batch-level parallelism. This strategy is independent from the support of specialized and optimized libraries. Therefore, the optimization is immediately available for accelerating the DNN training. The proposal is compatible with multi-GPU execution without altering the algorithm convergence rate. The parallelization has been implemented in Caffe, a state-of-the-art DNN framework. The paper describes the code transformations for the parallelization and we also identify the limiting performance factors of the approach. We show competitive performance results for two state-of-the-art computer vision datasets, MNIST and CIFAR-10. In particular, on a 16-core Xeon E5-2667v2 at 3.30GHz we observe speedups of 8× over the sequential execution, at similar performance levels of those obtained by the GPU optimized Caffe version in a NVIDIA K40 GPU.
Evaluating a Successful Coroner Protocol

were denied for organ donation. Because this number reflected an increasing trend in the category of potential donor loss over recent years, Colorado Organ Recovery Systems, Inc (CORS), began efforts to understand and possibly reduce this problem. Initial discussions with local coroners revealed not only a need for increased education but, more importantly, the perception that significant restrictions were being placed by district attorneys on the donation process. Many coroners were supportive of the efforts of CORS, but felt that their hands were tied by the decisions and philosophies of the district attorney community. Similarly, subsequent discussions with some district attorneys revealed their intense need for education as well as their opinion that the coroners’ needs prevented them from being more supportive. In May 1992 a national organ procurement organization (OPO) survey was developed to determine practices and philosophies of coroners and medical examiners in other areas of the United States. The survey enabled CORS to demonstrate to the Colorado District Attorney Council the extent of the problem in Colorado compared with other regions. The results of the survey indicated that the coroner release issue was significant in many other areas of the country.1 Because of the survey data and increasing efforts by some transplant programs and donor families to bring this issue to the media, the Council formed a task force that included representatives from the coroner, district attorney, defense bar, and transplantation fields to study the problem and develop solutions. Although the task force considered legislative regulations similar to the statutes of New York,2 Tennessee,3 and New Jersey,4 which limit coroner interference with donation, the group decided that establishing a protocol agreed on by all involved parties would be more timely and effective. The idea of the protocol itself came from similar efforts made in San Bernardino County, Calif,5 and the Center for Organ Recovery and Education in Pittsburgh, Pa.6 However, the CORS protocol is more succinct and user-friendly. According to the protocol, the procurement coordinator must fill out a 1-page checklist (Table 1), provide a copy of the donor’s medical record, and collect blood and urine samples in a special evidence kit for the coroner’s office (Figure 1). The primary factors in the CORS protocol are defined responsibilities, established communication channels, and accountability. The following key levels of communication are described in detail in the protocol: • The donor hospital must notify the coroner’s office of a patient’s death (or impending death) as early as possible. • The OPO staff must communicate routinely with each coroner on each case to clarify expectations and any variations from the adopted protocol. • The coroners and district attorneys must communicate effectively on a timely basis to determine any potential restrictions for donation. (Poor or lacking Evaluating a successful coroner protocol
Some Aspects of Scatter-Correction in Calibration. Part I

In our previous contribution to NIR news we discussed the different classes of methods available for solving nonlinearity problems in NIR spectroscopy. One of these approaches that can be helpful is the class of scatter correction techniques, Le. derivatives and socalled multiplicative scatter correction (MSC). These are methods that in a mathematical way try to eliminate or reduce the effect of light scatter on the spectrum. The idea behind all these techniques is that for calibration purposes, spectra should contain as little irrelevant information as possible. If the light scatter information is uncorrelated with the chemical concentrations, this is certainly true and it is a useful strategy. There exist cases, however, where this strategy is less useful: NIR spectroscopy is for instance used for many types of applications where the "contituent" of interest is strongly related to scatter, for instance determination of particle size (see, for example, Ref. 1). Removing information about light scatter from spectral values can in such cases lead to loss of valuable predictive information and reduced precision of the calibration equation. It is also important to mention that there may be other arguments than improved calibration equations for applying scatter correction techniques. Better visual interpretability may be one such argument. In the following we will first describe briefly what a scatter effect is and why it causes problems. After that we will discuss one of the most important ways of reducing it, namely the multiplicative scatter correction (MSC) technique. This method was published by Geladi et al.2 and has given good results in many applications of NIR spectroscopy (see, for example, Ref. 3). The method is inspired by Kubelka-Munck theory, but must be regarded as quite empirical or pragmatic. The effects of performing "scatter correction" will be illustrated by an example from the calibration of meat data (NIR transmission). In our next contribution to NIR news we will continue by describing some other ways of reducing scatter effects in NIR calibration, for instance derivatives,
Automatic hybrid analysis technique to improve botnet code coverage using fake server

The number of newly found malware and malware variants keeps increasing every year, and malware can be analyzed through static analysis or dynamic analysis. Malware developers use various packing techniques to avoid or to hinder static analysis and dynamic analysis needs to be used to analyze packed malware. In addition, malware that uses network communications to perform malicious actions that makes more difficult to be analyzed. Malware often hides malicious behaviors which are only triggered when certain conditions are satisfied, and this trigger-based malware usually communicates with the C2(Command and Control) server. With the increasing number of daily submitted malware, various malware analysis tools have also been developed steadily. In this paper, we propose a HyImCoCo (Hybrid Improve Code Coverage) which is a detection tool of trigger-based behaviors by satisfying the triggering conditions using hybrid analysis. IDApython is utilized to extract network-based features, and network-related instructions are modified to connect to our fake server called BKserver. The server can support TCP, UDP, IRC and HTTP protocols which are commonly used protocols by malware. HyImCoCo includes five modules which is Find Path module, Patch module, BKserver module, and CFG(Control Flow Graph) module. Experiments have shown that the proposed method can improve code coverage. With this tool, HyImCoCo helps to analyze the branch after recv by attracting malicious code to BKserver. We argue that our proposed tool, HyImCoCo can contribute to reduce the overheads of dynamic analysis through triggering malicious hidden behaviors in malware and increase to code coverage this helps analyze various paths.
How Patients Manage Life and Health While Waiting for a Liver Transplant

Progress in Transplantation, Vol 13, No. 1, March 2003 Waiting for a lifesaving transplant is a unique yet largely unexamined experience. Little is known about how liver transplant candidates manage their health and what assistance they may need for life and health during the waiting period. Theorists have identified several resources for health, but what health resources are important during the transplant waiting period and how do individuals experience these resources? This study was undertaken to discover what goes on as individuals manage their life and health during the often protracted wait for a liver transplant. Greater knowledge of how individuals mobilize health resources during this time may inform the efforts of all professionals involved in transplant care, thereby guiding improved care during the waiting period.
N ov 2 01 9 Extensions of the Algorithmic Lovász Local Lemma

We consider recent formulations of the algorithmic Lovász Local Lemma by AchlioptasIliopoulos-Kolmogorov [2] and by Achlioptas-Iliopoulos-Sinclair [3]. These papers analyze a random walk algorithm for finding objects that avoid undesired “bad events” (or “flaws”), and prove that under certain conditions the algorithm is guaranteed to find a “flawless” object quickly. We show that conditions proposed in these papers are incomparable, and introduce a new family of conditions that includes those in [2, 3] as special cases. We also consider another condition that appeared in [3] in the context of sparse k-SAT formulas. This condition imposes a constraint for each variable of the problem, whereas traditional LLL formulations impose a constraint for each clause. Achlioptas et al. handled the variable-based condition via a reduction to a different condition and then applying a singleclause backtracking algorithm. We propose a new condition that directly captures the sparse k-SAT application considered in [3], and allows the use of the standard local search algorithm (which offers important advantages such as parallelization). Finally, we extend our previous notion of “commutativity” from [20] and prove several implications of commutativity using some new tools that we develop. In particular, we simplify the result of Iliopoulos [16] about approximating the LLL distribution.
Public Key Encryption with Equality Test for Heterogeneous Systems in Cloud Computing

Cloud computing provides a broad range of services like operating systems, hardware, software and resources. Availability of these services encourages data owners to outsource their intensive computations and massive data to the cloud. However, considering the untrusted nature of cloud server, it is essential to encrypt the data before outsourcing it to the cloud. Unfortunately, this leads to a challenge when it comes to providing search functionality for encrypted data located in the cloud. To address this challenge, this paper presents a public key encryption with equality test for heterogeneous systems (PKE-ET-HS). The PKE-ET-HS scheme simulates certificateless public encryption with equality test (CLE-ET) with the identity-based encryption with equality test (IBE-ET). This scheme provides the authorized cloud server the right to actuate the equivalence of two messages having their encryptions performed under heterogeneous systems. Basing on the random oracle model, we construct the security of our proposed scheme under the bilinear Diffie-Hellman (BDH) assumption. Eventually, we evaluate the size of storage, computation complexities, and properties with other related works and illustrations indicate good performance from our scheme.