Miracle-dz/UniFAR-FTUs huggingface dataset:
Noninvasive genome sampling in chimpanzees

The inevitable has happened: genomic technologies have been added to our noninvasive genetic sampling repertoire. In this issue of Molecular Ecology, Perry et al. (2010) demonstrate how DNA extraction from chimpanzee faeces, followed by a series of steps to enrich for target loci, can be coupled with next‐generation sequencing. These authors collected sequence and single‐nucleotide polymorphism (SNP) data at more than 600 genomic loci (chromosome 21 and the X) and the complete mitochondrial DNA. By design, each locus was ‘deep sequenced’ to enable SNP identification. To demonstrate the reliability of their data, the work included samples from six captive chimps, which allowed for a comparison between presumably genuine SNPs obtained from blood and potentially flawed SNPs deduced from faeces. Thus, with this method, anyone with the resources, skills and ambition to do genome sequencing of wild, elusive, or protected mammals can enjoy all of the benefits of noninvasive sampling.
Chandra Analysis and Mass Estimation of the Lensing Cluster of Galaxies Cl 0024+17

We present a detailed analysis of Chandra X-ray observations of the lensing cluster of galaxies Cl 0024+17 at z = 0.395. We found that the radial temperature profile is consistent with being isothermal out to ~600 kpc and that the average X-ray temperature is 4.47 keV. The X-ray surface brightness profile is represented by the sum of extended emission centered at the central bright elliptical galaxy with a small core of 50 kpc and more extended emission that can be well described by a spherical β-model with a core radius of about 210 kpc. Assuming the X-ray-emitting gas to be in hydrostatic equilibrium, we estimated the X-ray mass within the arc radius and found that it is significantly smaller than the strong lensing mass by a factor of about 2-3. We detected a strong redshifted iron K line in the X-ray spectrum from the cluster for the first time and found the metal abundance to be 0.76 solar.
Benchmarking Music Information Retrieval Systems

Our goal is to create an accurate and effective benchmarking system for music information retrieval (MIR) systems. This will serve the multiple purposes of inspiring the MIR community to add additional features and increased speed into existing projects, and to measure the performance of their work and incorporate the ideas of other works. To date, there has been no systematic rigorous review of the field, and thus there is little knowledge of when an MIR implementation might fail in a real world setting. Benchmarking MIR systems is currently hindered by the diversity of the systems, by their relatively new and unrefined nature, and by the limited number of accessible systems. Thus most of what will be described here will be introductory and will lay down the framework for future benchmarking and analysis. Particular attention will be paid to the evaluation issues surrounding retrieval of audio in test collections.
Development of leg-track hybrid locomotion to traverse loose slopes and irregular terrain

The track mechanism has high mobility on irregular terrain, and is typically used as a locomotion mechanism for all-terrain robots. However, the track mechanism sometimes slips while traversing slopes comprising loose soil. Therefore, we developed a new locomotion mechanism, referred to as surface-contact-type locomotion, which has high mobility on weak soil. It uses a simple legged mechanism that has a wide contact area with the ground so as not to corrupt the contact surface. However, it has the disadvantage of low mobility on irregular terrain. To solve the problem of the above trade-off, we developed the leg-track hybrid locomotion mechanism by fusing the two locomotion mechanisms. In this paper, we detail the developed locomotion mechanism and report some initial experiments.
Flow Digest: A State Replication Scheme for Stateful High Availability Cluster

Stateful tracking is a popular technique in firewall filtering and state replication is used to provide reliable connectivity. This paper proposes a new approach for improving existing state replication protocols which ensure state consistency amongst the nodes of a stateful HA cluster. Our goal is to develop a new scheme which reduces the update overhead in the face of both low and high connection loads in order to maximize the capacity and scalability of a high availability cluster. A new representation called flow digest is proposed. Also the ways to use flow digest structures to update state changes, recover the connections after a failover, and solve the state inconsistency are presented. The main advantage of the proposed method is to reduce the bandwidth consumption on state replication. The simulation results show that the proposed scheme reduces the number of update messages and, more importantly, eliminates typically at least 86% of bandwidth consumption compared to current solutions.
An adaptive anomaly detection of WEB-based attacks

An adaptive model is proposed, which detect WEB-based attacks via identifying normal behaviors. By describing the structural features of Request-URL and using multiple hidden Markov model, the sample set is divided into several smaller subsets by request type. The discreteness of subset is calculated by the properties. Based on this, analyze the discreteness of each WEB requests to determine whether the request is normal, and then construct the detector based on hidden Markov model. The experimental results show that the adaptive model can effectively identify WEB-based attacks and reduce false alert.
An Exploration of System Architecture on Integrating Building Management System in High-Rise Building

High-rise building is bloomed into market with a series of evolved requirements. Recently, it is of great interest to adopt the Integrating Building Management System (IBMS) in high-rise buildings. However, the current IBMS architecture solution is far from the satisfaction of performance in integrat- ing level. In the past decade, various system integrations and collaboration technologies have been developed and deployed to application domains. In this paper, we address system sensitive problems and architecture bottlenecks by observing current architectures. We provide a generic set of solutions to support the data access flow, use of information, business systems and collaborative creation. This paper presents a typical scenario for potential system architecture in high-rise building. In this paper, a discovery and analysis of the state-of-art in IBMS solutions is presented. At the same time, we conducted a series of onsite investigations for system architecture usage. It is envisaged that this research will give the readers insights into the critical concepts and issues for consideration in designing the systems in this area.
A Time Scheduling Model of Logistics Service Supply Chain Based on the Customer Order Decoupling Point: A Perspective from the Constant Service Operation Time

In mass customization logistics service, reasonable scheduling of the logistics service supply chain (LSSC), especially time scheduling, is benefit to increase its competitiveness. Therefore, the effect of a customer order decoupling point (CODP) on the time scheduling performance should be considered. To minimize the total order operation cost of the LSSC, minimize the difference between the expected and actual time of completing the service orders, and maximize the satisfaction of functional logistics service providers, this study establishes an LSSC time scheduling model based on the CODP. Matlab 7.8 software is used in the numerical analysis for a specific example. Results show that the order completion time of the LSSC can be delayed or be ahead of schedule but cannot be infinitely advanced or infinitely delayed. Obtaining the optimal comprehensive performance can be effective if the expected order completion time is appropriately delayed. The increase in supply chain comprehensive performance caused by the increase in the relationship coefficient of logistics service integrator (LSI) is limited. The relative concern degree of LSI on cost and service delivery punctuality leads to not only changes in CODP but also to those in the scheduling performance of the LSSC.
Knowledge-based Integrated Production Management Model applied to Brazilian glass industry

This paper aims to propose a framework that attempts to identify which operation management practices are more supportive to KM, especially to the blue collar workers. Shop-floor personnel interviews were conducted to identify and to confirm the factors relevance. The research was conducted in an important Brazilian glass company. Results have shown relation among knowledge management and Work and Production factors (i.e., Objective, Communication, Problem Solving Method, Standard Operating Procedure). The factors allow managers to promote a favourable context for knowledge sharing, especially tacit knowledge.
Symbolic violence in teacher education: embracing cultural diversity or cultural discrimination?

ABSTRACT The purpose of this article is to describe the experiences of culturally disparate adult learners undertaking an initial teacher education (ITE) placement in Australian school settings. Using a hybridised phenomenological methodological approach, the accounts of these students were interpreted to reveal instances of symbolic violence that victimised and failed three teacher education students as they undertook professional experience. The findings provide evidence of (a) how adult learners respond to and constantly negotiate their learning practices and how they feel about cultural diversity and discrimination, and (b) how phenomenological analysis of the accounts of individuals lived experiences can illuminate predominant findings.
Stem Cell Reports, Volume 2 Supplemental Information Identification of Specific Cell-surface Markers of Adipose-derived Stem Cells from Subcutaneous and Visceral Fat Depots

 Figure S1: Preceeding experiments done before high content screening (HCS) experiments in Figure 1  Figure S2: This is the additional 2 nd stage analysis for Figure 2  Figure S3: A is investigation of different species (mouse) from human subjects in Figure 3; B and C are complementary to Figure 3  Figure S4: A is complementary to Figure 4A. B and C are complementary to Figure 4C and 4D, respectively. D and E are also complementary to Figure 4C and 4D, respectively.  Table S3: Excel spreadsheet describing signal intensities estimated by raw fluorescence intensity values (AU) or by manual assessment through visual inspection.  Table S4: Excel spreadsheet showing detailed selection / exclusion criteria results for each cell surface marker.  Stage Selection Criteria and Statistical Consideration: This explains details of the 3 stage selection criteria, method to generate the null distribution for computing p-value, and statistical result for the 3-stage approach.
The NCAA: A Socio‐economic Analysis: The Development of the College Sports Cartel from Social Movement to Formal Organization.

Economic cartel theory and Sociological social movement theory are used to achieve a socio-economic analysis of the problems and behaviour of the National Collegiate Athletic Association (NCAA). It is demonstrated that both cartel theory and social movement theory predict substantially similar behavior on the part of the NCAA and its 800-plus member institutions. Specific issues such as “need”scholarships, the possibility that the” big-time”football powers, may leave the NCAA, and the NCAA's relation with women's athletics, are considered. It is concluded that the NCAA is not likely to persist is an organization in its current form.
PARENT-IMPLEMENTED COMMUNICATION INTERVENTION FOR PRESCHOOL-AGED CHILDREN WITH AUTISM

PARENT IMPLEMENTED COMMUNICATION INTERVENTION FOR PRESCHOOL AGED CHILDREN WITH AUTISM By Heather Coleman, Ph.D. A dissertation submitted in partial fulfillment of the requirements of the degree of Doctor of Philosophy at Virginia Commonwealth University. Virginia Commonwealth University 2018 Director: Yaoying Xu, Ph.D. Professor, Counseling and Special Education Exploring the interventions that promote expressive, verbal language for preschool-aged children with autism is essential. When a child is lacking the ability to communicate, parents express that they would like their child to speak. B.F. Skinner (1957) proposed that the mand repertoire (communicative requests) should be an initial focus of language training. Mand training has been shown to be effective for teaching children with autism to communicate. However, many studies exploring mand training utilize highly trained instructors for intervention implementation. Early childhood best practices recommend the use of family-centered interventions and teaching within the natural environment. This study followed these recommendations. This research utilized a single subject multiple baseline across participants design with two parents and their preschool aged children with autism. The purpose of this dissertation study was two fold: (1) to examine the effects of a verbal mand with direct trial instruction intervention on the verbal communication skills for children with autism, and (2) to investigate if a parent can reliably implement the intervention. Using written instructions, role play, video models, and performance feedback, the researcher taught parents how to implement the intervention with their child. The goal of the intervention was to increase verbal communication skills, specifically the production of independent verbal mands. The intervention under question involved verbal mand training using direct trial instruction (DTI). During DTI the parent taught the child to use mands utilizing a time delay, verbal prompting, and sign language. The researcher collected data during the baseline, intervention, and maintenance phases. In addition to the intervention results, the researcher collected and analyzed social validity, treatment fidelity, and parent competence data. Results from the intervention effects did not show a functional relation between the treatment and the target behavior. However, both participants increased their ability to use verbal and sign language communication. The parents were able to implement the intervention with fidelity and gained high competence scores related to intervention delivery expertise and behavioral responsiveness. The parents also reported that the intervention was extremely useful for their family. The parents generalized the intervention procedures and their children communicated more throughout their daily routines.
Dropout distillation

Dropout is a popular stochastic regularization technique for deep neural networks that works by randomly dropping (i.e. zeroing) units from the network during training. This randomization process allows to implicitly train an ensemble of exponentially many networks sharing the same parametrization, which should be averaged at test time to deliver the final prediction. A typical workaround for this intractable averaging operation consists in scaling the layers undergoing dropout randomization. This simple rule called "standard dropout" is efficient, but might degrade the accuracy of the prediction. In this work we introduce a novel approach, coined "dropout distillation", that allows us to train a predictor in a way to better approximate the intractable, but preferable, averaging process, while keeping under control its computational efficiency. We are thus able to construct models that are as efficient as standard dropout, or even more efficient, while being more accurate. Experiments on standard benchmark datasets demonstrate the validity of our method, yielding consistent improvements over conventional dropout.
An introduction to (co)algebra and (co)induction

Algebra is a well-established part of mathematics, dealing with sets with operations satisfying certain properties, like groups, rings , vector spaces, etcetera. Its results are essential throughout mathematics and other sciences. Universal algebra is a part of algebra in which algebraic structures are studied at a high level of abstraction and in which general notions like homomorphism, subalge-bra, congruence are studied in themselves, see e.g. [Coh81, MT92, Wec92]. A further step up the abstraction ladder is taken when one studies algebra with the notions and tools from category theory. This approach leads to a particularly concise notion of what is an algebra (for a functor or for a monad), see for example [Man74]. The conceptual world that we are about to enter owes much to this categorical view, but it also takes inspiration from universal algebra, see e.g. [Rut00]. In general terms, a program in some programming language manipulates data. During the development of computer science over the past few decades it became clear that an abstract description of these data is desirable, for example to ensure that one's program does not depend on the particular representation of the data on which it operates. Also, such abstractness facilitates correctness proofs. This desire led to the use of algebraic methods in computer science, in a branch called algebraic specification or abstract data type theory. The object of study are data types in themselves, using notions and techniques which are familiar from algebra. The data types used by computer scientists are often generated from a given collection of (constructor) operations. The same applies in fact to programs, which themselves can be viewed as data too. It is for this reason that " initiality " of algebras plays such an important role in computer science (as first clearly emphasised in [GTW78]). See for example [EM85, Wir90, Wec92] for more information.
A dual-core system solution for wearable health monitors

This paper presents a system design study for wearable sensor devices intended for healthcare and lifestyle applications based on ECG, EEG and activity monitoring. In order to meet the low-power requirement of these applications, a dual-core signal processing system is proposed which combines an ultra-low-power bio-medical Application Specific Instruction-set Processor (BioASIP) and a low-power general-purpose micro-controller (MSP430). To validate the merits of the proposed architecture, system-level power analysis and trade-offs are conducted using real hardware measurements of an ECG R-peak detection application. The results show that the proposed dual-core architecture consumes around 65. 38µW, about 25.8x smaller than an MSP430-only approach. Out of 65. 38µW, the BioASIP consumes only 11µW and the rest is used in the analog front-end, A/D conversion, and control tasks.
Effect of macrophage depletion on immune effector mechanisms during corneal allograft rejection in rats.

PURPOSE In rats, corneal allograft rejection is delayed for at least 100 days by clodronate liposomes. These liposomes selectively deplete macrophages. To investigate the immunologic basis for absence of graft rejection in treated rats, the effect of these liposomes on the generation of cytotoxic T lymphocytes (CTLs) and antibody production after orthotopic corneal allotransplantation was determined. METHODS Transplantations of corneal buttons from PVG rats were performed in AO rats. After surgery, one group received clodronate liposomes subconjunctivally at five time points, and the other group remained untreated. On postoperative day (POD) 3, 7, 12, or 17, rats were killed, the presence of CTLs was investigated at three different anatomic locations, and antibodies against donor antigens were tested. RESULTS No significant differences were found between the groups tested 3 and 7 days after surgery. But on POD 12 (the time of onset of rejection in the untreated group) and on POD 17, the CTL activities detected in the submandibular lymph nodes (P < or = 0.008) and the spleen (P < or = 0.009) were significantly less in the treated groups compared with the untreated groups. In the untreated groups complement-independent antibodies were present only on POD 17, whereas no antibodies were found in the treated rats. CONCLUSIONS Local treatment with clodronate liposomes was shown to downregulate local and systemic CTL responses and to prevent the generation of antibodies. Local depletion of macrophages in the initiation phase of the immune response appears to lead to a less vigorous attack on the grafted tissue and therefore to promote graft survival.
Adaptive Variable Structure Position Control for Induction Motors

An adaptive variable structure position control for induction motors using field oriented control theory is presented. The proposed sliding-mode control law incorporates an adaptive switching gain to avoid calculating an upper limit of the system uncertainties. The design incorporates a flux estimator that operates on the principle of flux and current observer. The proposed observer is basically an estimator that uses a plant model and a feedback loop with measured stator voltages and currents. The stability analysis of the proposed controller under parameter uncertainties and load disturbances is provided using the Lyapunov stability theory. Finally experimental results show that the proposed controller with the proposed observer provides high-performance dynamic characteristics and that this scheme is robust with respect to plant parameter variations and external load disturbances.
Mining Trading Partners' Preferences for Efficient Multi-Issue Bargaining in E-Business

Classical negotiation models are weak in supporting real-world business negotiations because these models often assume that the preference information of each negotiator is made public. Although parametric learning methods have been proposed for acquiring the preference information of negotiation opponents, these methods suffer from the strong assumptions about the specific utility function and negotiation mechanism employed by the opponents. Consequently, it is difficult to apply these learning methods to the heterogeneous negotiation agents participating in e-marketplaces. This paper illustrates the design, development, and evaluation of a nonparametric negotiation knowledge discovery method which is underpinned by the well-known Bayesian learning paradigm. According to our empirical testing, the novel knowledge discovery method can speed up the negotiation processes while maintaining negotiation effectiveness. To the best of our knowledge, this is the first nonparametric negotiation knowledge discovery method developed and evaluated in the context of multi-issue bargaining over e-marketplaces.
HPDBSCAN: highly parallel DBSCAN

Clustering algorithms in the field of data-mining are used to aggregate similar objects into common groups. One of the best-known of these algorithms is called DBSCAN. Its distinct design enables the search for an apriori unknown number of arbitrarily shaped clusters, and at the same time allows to filter out noise. Due to its sequential formulation, the parallelization of DBSCAN renders a challenge. In this paper we present a new parallel approach which we call HPDBSCAN. It employs three major techniques in order to break the sequentiality, empower workload-balancing as well as speed up neighborhood searches in distributed parallel processing environments i) a computation split heuristic for domain decomposition, ii) a data index preprocessing step and iii) a rule-based cluster merging scheme. As a proof-of-concept we implemented HPDBSCAN as an OpenMP/MPI hybrid application. Using real-world data sets, such as a point cloud from the old town of Bremen, Germany, we demonstrate that our implementation is able to achieve a significant speed-up and scale-up in common HPC setups. Moreover, we compare our approach with previous attempts to parallelize DBSCAN showing an order of magnitude improvement in terms of computation time and memory consumption.