Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of concentrated bone marrow aspirate and platelet rich plasma during minimally invasive decompression of the femoral head in the treatment of osteonecrosis

The aim of this paper is to describe our surgical procedure for the treatment of osteonecrosis of the femoral head using a minimally invasive technique. We have limited the use of this procedure for patients with pre-collapse osteonecrosis of the femoral head (Ficat Stage I or II). To treat osteonecrosis of the femoral head at our institution we currently use a combination of outpatient, minimally invasive iliac crest bone marrow aspirations and blood draw combined with decompressions of the femoral head. Following the decompression of the femoral head, adult mesenchymal stem cells obtained from the iliac crest and platelet rich plasma are injected into the area of osteonecrosis. Patients are then discharged from the hospital using crutches to assist with ambulation. This novel technique was utilized on 77 hips. Sixteen hips (21%) progressed to further stages of osteonecrosis, ultimately requiring total hip replacement. Significant pain relief was reported in 86% of patients (n = 60), while the rest of patients reported little or no pain relief. There were no significant complications in any patient. We found that the use of a minimally invasive decompression augmented with concentrated bone marrow and platelet rich plasma resulted in significant pain relief and halted the progression of disease in a majority of patients.
Active Learning of Causal Networks with Intervention Experiments and Optimal Designs

The causal discovery from data is important for various scientific investigations. Because we cannot distinguish the different directed acyclic graphs (DAGs) in a Markov equivalence class learned from observational data, we have to collect further information on causal structures from experiments with external interventions. In this paper, we propose an active learning approach for discovering causal structures in which we first find a Markov equivalence class from observational data, and then we orient undirected edges in every chain component via intervention experiments separately. In the experiments, some variables are manipulated through external interventions. We discuss two kinds of intervention experiments, randomized experiment and quasi-experiment. Furthermore, we give two optimal designs of experiments, a batch-intervention design and a sequential-intervention design, to minimize the number of manipulated variables and the set of candidate structures based on the minimax and the maximum entropy criteria. We show theoretically that structural learning can be done locally in subgraphs of chain components without need of checking illegal v-structures and cycles in the whole network and that a Markov equivalence subclass obtained after each intervention can still be depicted as a chain graph.
Indonesian Fan Girls' Perception Towards Soft Masculinity as Represented by K-pop Male Idols

This article aimed to examine how fan girls perceive this new form of masculinity represented by K-pop male idols (termed as soft masculinity). This research used a mixed method in collecting the data from a questionnaire distributed via e-mail and Line to twenty fan girls from various fandoms in April 2016. The result shows that the respondents are aware that in the entertainment business, gender identity can be modified and presented as a part of marketing strategy. In addition, they only see the soft masculinity delivered by K-pop male idols as a form of performance.
APPLICATION OF TIME-FREQUENCY METHOD IN SEISMIC SIGNALS PROCESSING

Spectral decomposition is an important tool for analysis of seismic data.This paper deals with the time-frequency analysis of non-stationary signals.Time-frequency method is a primary tool to analyze the evolving spectra of non-stationary signals. Short Time Fourier Transform (STFT) is a fundamental time-frequency method which reveals the frequency contents of the signal at each time point. The resolution in such representations directly depends on the sliding window length. The width of window employed in the STFT computation is a challenging task. In order to quantify the optimum window length, Renyi entropy is used for estimating the signal information, and it is suggested that optimum window width can be more efficient to analyze the seismic signals.
Accidental ethnography: A method for practitioner-based education research

This article presents and discusses Accidental Ethnography (AccE), a methodology for practitioners to examine past experiences and contribute their findings to scholarly discourse. Accidental ethnography is the systematic analysis of prior fieldwork. It utilizes extant data “accidentally” gathered (i.e. the data were not collected as part of a predesigned study) to provide insight into a phenomenon, culture, or way of life. The accidental ethnography method—a nascent method in research literature—was developed to provide a means of in-depth exploration of past practitioner learning experiences beyond personal reflection. This article organizes, advances, and systematizes an accidental ethnography method for practitioner–researchers. We propose here a method that encompasses broader intentionality on the part of the researcher and a potentially unorthodox chronology of steps in the ethnographic research process. For practitioners in education, where much is learned through action and reflection, accidental ethnography offers a methodological approach for rigorous reflective research by front-line practitioners who have traditionally had difficulty finding time to make rigorous contributions to the discipline. This article introduces the methodological approach, elaborates the accidental ethnography research process, situates the method within action research methodology, and provides an example of an accidental ethnography project.
International strategies of emerging market multinationals: A dynamic capabilities perspective

This paper focuses on the importance of dynamic capabilities in shaping the nature of international strategies of emerging market multinationals from mid-range economies. We argue that dynamic capabilities theory provides an insightful approach to understanding the internationalization of emerging market multinationals and their strategic choices. Drawing on dynamic capability theory and unpacking dynamic capabilities into four distinct but related dimensions or facets, we develop a typology of three internationalization strategies available to emerging market multinationals in their international expansion: sequential international ambidexterity (from exploitation to exploration, and vice versa) and structural international ambidexterity (simultaneous exploration and exploitation). Success factors associated with each of the ambidextrous internationalization strategies are also considered. We conclude with a discussion of the implications of the dynamic capabilities framework for theoretical implications and fruitful areas for future research endeavors.
AUTOMATIC EXTRACTION OF CONCEPTUAL LABELS FROM TOPIC MODELS

În această lucrare prezentăm un sistem destinat extragerii automate de etichete conceptuale pentru topice obţinute prin metode statistice. Realizând o proiecţie a unei distribuţii peste toate cuvintele din vocabular pe ontologia WordNet reuşim asocierea de concept unor grupuri de cuvinte extrase folosind modele de topice. Contribuţiile cele mai importante ale lucrării sunt legate de validarea rolului acestor concepte ca etichete ale topicelor iniţiale şi determinarea corelaţiilor care apar între valoarea acestor etichete şi puterea relaţiei dintre concepte şi topice.
Web indexing using HTML priority system

The unstructured nature and the sheer size of the World Wide Web make it a challenging task to index. This paper will discuss about how web can be incrementally indexed using Inverted Indices and Distributed Hash Table for efficiently organizing the data while incrementally build the index using the search mechanism itself, and HTML Priority System for ranking the pages to improve precision and recall. It also discusses certain challenges that a content-based ranking system must face to counter spam.
When being Weak is Brave: Privacy in Recommender Systems

We explore the conflict between personalization and privacy that arises from the existence of weak ties. A weak tie is an unexpected connection that provides serendipitous recommendations. However, information about weak ties could be used in conjunction with other sources of data to uncover identities and reveal other personal information. In this article, we use a graph-theoretic model to study the benefit and risk from weak ties.
Standing in the middle: Insider/outsider positionality while conducting qualitative research with opposing military veteran political groups

This case study describes the process and challenges of conducting qualitative research on two opposing military veteran political groups: Iraq Veterans Against the War and Vets for Freedom. The discussion is based on a dissertation project that compelled me to reflect on my simultaneous “insider” status as a military veteran and “outsider” status as a non-member of both veteran political groups. I describe negotiating my positionality throughout the research cycle, as I also shifted from trying to be “objective” to embracing the fluidity of my own identity and political views.
A new tool for multidimensional low-rank STAP filter: Cross HOSVDs

Space Time Adaptive Processing (STAP) is a two-dimensional adaptive filtering technique which uses jointly temporal and spatial dimensions to suppress disturbance. Disturbance contains both the clutter arriving from signal backscattering of the ground and the thermal noise. In practical cases, the STAP clutter can be considered to have a low rank structure, allowing to derive a low rank vector STAP filter, based on the projector onto the clutter subspace. In order to process new STAP applications (MIMO STAP, polarimetric STAP .) and keeping the multidimensional structure, we propose in this paper a new low-rank tensor STAP filter based on a generalization of the Higher Order Singular Value Decomposition (HOSVD): the Cross-HOSVDs. This decomposition uses at the same time the simple (like polarimetric) and the combined information (for example spatio-temporal). We apply the filter on polarimetric STAP and compute the SNR Loss with Monte-Carlo simulations.
A Domain ontology based service matching for CHORD based Super Peer network

One major issue in web service discovery is retrieving the desired services. Currently P2P architectures are used as a replacement of UDDI for registering and discovering web services. But P2P network structures lack semantic based query routing and have scalability issues when they are scaled to larger network. In this paper we introduce the concept of Domain ontology in CHORD based Super Peer network. The Traditional CHORD algorithm is modified by with two changes: Functionally equivalent services are evenly distributed across the network and Domain ontology is used for service matching instead of service identifiers. An ontology repository is also available in each Super node of the network which stores the domain ontologies used for service matching. At the same time, we take advantage of OWL-S to create domain ontologies and to add valuable semantic information in Web Service description. We have also modified an existing ontology matching algorithm making it compatible with CHORD structure.
Solving nonconvex SDP problems of structural optimization with stability control

The goal of this article is to formulate and solve structural optimization problems with constraints on the global stability of the structure. The stability constraint is based on the linear buckling phenomenon. We formulate the problem as a nonconvex semidefinite programming problem and introduce an algorithm based on the augmented Lagrangian method combined with the trust-region technique. The algorithm is implemented in a code PENNON. The article is concluded by a series of numerical examples.
LEDBAT performance in sub-packet regimes

Wireless Community Networks in the developing world satisfy the basic needs of remote users to information access. However, community networks in developing regions usually rely on low-bandwidth backhaul links that are shared amongst a large user base, driving these links to sub-packet regimes where the per-flow throughput is less than one packet per RTT. TCP performance significantly degrades in such conditions, resulting in severe unfairness and high packet loss rates. In this paper, we investigate the performance of scavenger transport methods, namely LEDBAT and its fair modification fLEDBAT, in the sub-packet regime of shared backhaul links in developing regions. Our intention is to explore the feasibility of using such scavenger transport methods for uploading content over bandwidth constrained backhauls. Our findings show that LEDBAT achieves higher link efficiency and fairness compared to TCP in a variety of sub-packet regime scenarios. When TCP and LEDBAT flows share the same link in the sub-packet regime, LEDBAT flows are more aggressive, consuming more resources than TCP. Therefore, we conclude that a more conservative strategy after consecutive timeouts and shared bottleneck detection mechanisms need to be incorporated into the core LEDBAT algorithm, in order to correctly adjust its congestion window in the sub-packet regime.
Style translation filter to change attribute of motion

In this paper, we propose a style translation filter that changes the attribute (style) of the motion coming from the actors' ages, genders, and so on. Using this filter, we can diversify the motions. Specifically, this filter is modeled by the Gaussian process regression that estimates the difference of pose (joint angles) between a neutral motion and the motion of a target attribute. In learning this filter, a key technique is to find pairs of corresponding posed from the sample motions. We solve this problem by employing the Multifactor Gaussian Process Model (MGPM) proposed by Wang et al. [1]. In the experiments, we constructed multiple style translation filters from several attributes of walking motions, such as genders, ages, and emotions. The obtained filters were applied to some kinds of testing motions, such as walking, jumping, kicking, and dancing. The acquired motions were verified by a questionnaire study; the most of their attributes were changed to the filters' target attributes.
A Family of Efficient Complex Halfband Filters

Halfband lowpass and bandpass filters, versatile building blocks in a multitude of DSP applications, are revisited. Linear-phase FIR and minimum-phase IIR halfband filters for sample rate alteration are recalled, their computational loads are compared, and optimum signal flow graphs are presented. The same comparisons are carried out for corresponding complex halfband filters (Hilbert-transformers) with and without an additional frequency offset by ∆Ω = ±π/4. As expected, the smaller the transition width between passband and stopband the higher the relative advantage of the IIR approach in terms of computation. Yet, there exist ranges of specifications where linearphase FIR halfband filters outperform their minimum-phase IIR counterparts.
Inducing Thought Processes: Bringing Process Measures and Cognitive Processes Closer Together

The challenge in inferring cognitive processes from observational data is to correctly align overt behavior with its covert cognitive process. To improve our understanding of this overt–covert mapping in the domain of decision making, we collected eye-movement data during decisions between gamble-problems. Participants were either free to choose or instructed to use a specific choice strategy (maximizing expected value or a choice heuristic). We found large differences in looking patterns between free and instructed choices. Looking patterns provided no support for the common assumption that attention is equally distributed between outcomes and probabilities, even when participants were instructed to maximize expected value. Eye-movement data are to some extent ambiguous with respect to underlying cognitive processes. Copyright © 2017 John Wiley & Sons, Ltd.
Adrenergic calcium signaling in astrocyte networks within the hippocampal slice

Norepinephrine (NE) and glutamate (Glu) initiate intracellular calcium ([Ca2+]i) transients, oscillations, and intracellular [Ca2+]i waves in cultured astrocytes. To further elucidate the significance of NE- and Glu-evoked astrocytic [Ca2+]i signaling to neuron-astrocyte communication in the mature CNS, [Ca2+]i of astrocyte networks within hippocampal slices (P21–42) was measured during bath application of NE and Glu receptor agonists. Astrocytes in stratum radiatum were identified by highly negative membrane potentials (75 +/- 3 mV), absence of action potentials, and dye coupling following intracellular injection of the [Ca2+]-sensitive dye calcium orange. NE (2–100 microM) evoked [Ca2+]i increases (7 of 8 slices, 24 of 24 cells in responding slices) characterized by an initial rise, 20–50 sec to peak, followed by a slower return to baseline (over approximately 8 min). The alpha 1- agonist phenylephrine (PE) (10–100 microM) evoked complex [Ca2+]i signals (22 of 26 slices, 90 of 90 cells in responding slices) composed of both a prolonged component (5.1 +/- 1.8 min), synchronized in neighboring cells, and multiple, mainly asynchronous [Ca2+]i spikes (25.0 +/- 11.6 sec). PE responses were completely blocked by the alpha 1-antagonist prazosin (200 nM, n = 4 slices), but not by the alpha 2- antagonist yohimbine (n = 3 slices). The alpha 2-agonist clonidine (10- 100 microM) did not increase [Ca2+]i (n = 4 slices). alpha 1-mediated [Ca2+]i transients were observed after removal of extracellular [Ca2+]o (n = 8 of 9 slices), indicating PE-induced Ca2+ release from intracellular stores. Adrenergic responses were mediated by alpha 1- receptors localized to astrocytes because PE and NE increased [Ca2+]i of acutely isolated hippocampal astrocytes. Glu (0.75–2.0 mM) did not increase astrocytic [Ca2+]i in slices (0 of 7), even in the presence of the Glu uptake inhibitor L-trans-pyrrollidine-2,4-dicarboxylic acid (PDC) (0 of 5 slices), or in acutely isolated astrocytes (0 of 7 cells). The metabotropic agonist t-ACPD (30 or 50 microM) did not increase astrocytic [Ca2+]i in hippocampal slices (0 of 5), while kainate (200 microM or 1 mM) induced brief (1–2 min) [Ca2+]i increases only rarely (2 of 8 applications in 6 slices). These results support a primary role of NE release and alpha 1-adrenoceptor stimulation in neuron-astrocyte communication in the mature CNS.
Query Intent Detection Based on Query Log Mining

In this paper we deal with the problem of automatic detection of query intent in search engines. We studied features that have shown good performance in the state-of-theart, combined with novel features extracted from click-through data. We show that the combination of these features gives good precision results. In a second stage, four textbased classifiers were studied to test the usefulness of text-based features. With a low rate of false positives (less than 10 %) the proposed classifiers can detect query intent in over 90% of the evaluation instances. However due to a notorious unbalance in the classes, the proposed classifiers show poor results to detect transactional intents. We address this problem by including a cost sensitive learning strategy, allowing to solve the skewed data distribution. Finally, we explore the use of classifier ensembles which allow to us to achieve the best performance for the task.
Simplifying synchronization in cooperative robot tasks - an enhancement of the Manipulation Primitive paradigm

Complex handling and assembly tasks can be gradually decomposed into simpler sub-tasks until a level of elementary 'primitive' tasks is reached, which can be expressed generically by so-called Manipulation Primitives. Manipulation Primitives can hence be utilized as the foundation of a unified paradigm to specify and execute complex sensor-based robot tasks. By embedding these Manipulation Primitives into a fully hierarchical structure, the specification and reuse of common sub-tasks can be simplified immediately. However, without appropriate synchronization mechanisms the user-friendly and effective specification of tasks for multi-robot systems based on Manipulation Primitives still remains an issue. The underlying place-transition net formalism allows for synchronization by including the notions of forks and joins into the net but this approach is neither user-friendly nor does it allow for immediate support of more sophisticated synchronization mechanisms such as range synchronization. To eliminate this drawback of the Manipulation Primitive Concept, this contribution proposes powerful but at the same time easy-to-use synchronization primitives and introduces a revised Manipulation Primitive paradigm, which takes full advantage of the developed primitives. The advantages of the proposed concepts regarding the specification of tasks for industrial multi-robot systems are illustrated with several examples.
A concept and algorithm for 3D city surface modeling

: To realize a better representation of complete three-dimensional (3D) city models in Taiwan, this paper proposes an alternative concept and algorithm for 3D geometrical city surface modelling based on wavelets and least squares adjustment. The reasons why wavelets are adopted as an alternative module are stated. Firstly in this algorithm, a wavelets-based module for surface modelling makes it convenient to depict different types of city surfaces, where it enables an operator to choose a proper father wavelet in an interactive manner. It also can describe a fractal surface if fractal wavelets are adopted. Secondly, observations are acquired manually or (semi-)automatically. Simultaneously, any observation is recorded with a predefined code that defines a specific topology relationship with others. Then, the well-known least-squares adjustment is utilized to let the adopted wavelet surface function fit all observations, where the surface parameters, namely wavelet coefficients, in a local small stereo model (image window) are directly estimated and observation errors are filtered out. The surface function and observation equations are linear so that both estimation of initial values for unknown parameters and Gauss-Newton iteration are not needed. Current personal computer (PC) makes it possible to complete all computations in a short duration of time. It also provides quality figures, namely a covariance matrix, and enables a (near) real-time visual check on a DPW (Digital Photogrammetry Workstation). The afore-mentioned processes are done in each small window. Finally, a 3D city surface in a large area can be reconstructed by collecting the results in all windows, where neighbouring windows have a proper overlap. Some preliminary test results are also shown.