Miracle-dz/UniFAR-FTUs huggingface dataset:
Extracorporeal Shock Wave Therapy for Resistant Stress Fracture in Athletes

times difficult to repair, resulting in delayed union or nonunion. For intractable cases, we often perform surgical treatment using some internal fixation device with or without bone grafting. Hulkko and Orava reported 368 stress fractures of which 26 fractures (7.1%) required surgical treatment because of dislocation or delayed union/ nonunion. However, surgical treatment can sometimes lead to complications. Consequently, there is interest in developing an effective nonsurgical technique for treating stress fracture. Recently, extracorporeal shock wave therapy (ESWT) has been reported as an effective noninvasive technique for fracture healing and delayed union/nonunion. We performed ESWT for resistant stress fractures that were not healed conservatively or operatively, and we report efficacy and short-term results. The purpose of this study was to evaluate the effects of ESWT for stress fracture, especially in resistant cases.
1 SMA 5509 : Theory of Parallel Systems Project Proposal Cache-oblivious sorting for Burrows-Wheeler Transform

Burrows and Wheeler [1] presented a lossless text compression method based on Burrows-Wheeler Transform (BWT). A computationally expensive activity during this compression is the sorting of all rotations of the block of data to be compressed. The original implementation incurs the worst case complexity of O(Nlog(N)), if there is a high degree of repetitiveness in the input file. The number of characters, N, is typically quite large and such worst case behavior is unacceptable. In [2], Sadakane has provided a sorting algorithm with a better worst case bound of O(Nlog(N)). Seward [3], however, has shown that even though Sadakane’s algorithm has better asymptotic behavior, it incurs high overheads and a tuned direct-comparison implementation of rotation sorting performs much better in practice. The tuned implementation presented in [3] mainly improves the performance of the original algorithm by minimizing the memory references, especially the cache misses for most inputs. The author concludes that these memory effects are critical for the performance of the algorithm on the modern architectures. We believe that such a heavy dependence of the performance of the algorithm on the memory effects can be minimized by developing a cache-oblivious implementation of the algorithm. Such an implementation is especially useful for the compression applications such as bzip2 based on the algorithm, which are required to perform well on a wide range of platforms and their underlying architectures. We proceed to give an overview of Cache Obliviousness and how it serves the purpose of making BWT sorting more efficient.
Privacy Preserving Naive Bayes Classifier for Horizontally Partitioned Data

The problem of secure distributed classification is an important one. In many situations, data is split between multiple organizations. These organizations may want to utilize all of the data to create more accurate predictive models while revealing neither their training data / databases nor the instances to be classified. The Naive Bayes Classifier is a simple but efficient baseline classifier. In this paper, we present a privacy preserving Naive Bayes Classifier for horizontally partitioned data.
A novel dual-band bandpass filter using nested quarter-mode substrate integrated waveguides

A novel dual-band bandpass filter using nested quarter-mode substrate integrated waveguides (QMSIW) is proposed. Two triangular QMSIW cavities of different size are nested one into another to provide a dual-resonance response. Compared to conventional dual-band SIW filters which utilize the multiple cavity modes, the proposed resonator features the advantages of compact circuit size and flexibility in controlling two resonant frequencies independently. In addition, due to the frequency-dependent mixed electric and magnetic coupling between the resonators, two transmission zeros can be observed between two passbands resulting in sharp passband selectivity and high band-to-band isolation.
Random walk on the incipient infinite cluster on trees

Let ${\cal G}$ be the incipient infinite cluster (IIC) for percolation on a homogeneous tree of degree $n_0+1$. We obtain estimates for the transition density of the continuous time simple random walk $Y$ on ${\cal G}$; the process satisfies anomalous diffusion and has spectral dimension 4/3.
KeJia Project : Towards Integrated Intelligence for Service Robots

This paper reports some progress on the project KeJia, a long-term effort aiming at integrated intelligence for service robots. We focus in this paper on the high-level cognitive functions developed on our robot KeJia, including human-robot dialogue understanding, task planning, and automatic transformation of the knowledge and information extracted from human-robot dialogues and other sources in verbal languages into the planner. We have been testing these techniques and the integrated system in RoboCup@home league competitions, as well as other case-studies involving complex tasks, general purpose service with incomplete or erroneous information, acquiring and reasoning with causal knowledge, and learning to operate a microwave oven through reading the manual.
Activation of matrix metalloproteinases in the failing human heart: breaking the tie that binds.

The process of left ventricular (LV) remodeling has been shown to be an important predictor of morbidity and mortality in patients with heart failure. Therefore, identifying the cascade of molecular and cellular events that contribute to LV remodeling is likely to provide new and novel targets for preventing disease progression in heart failure. In this issue of Circulation , Li and colleagues1 report that changes in the relative abundance of tissue inhibitors of the metalloproteinases (TIMPs) occur with the development of end-stage human heart failure, thus raising the important possibility that alterations in the extracellular matrix of the failing heart may contribute to disease progression in heart failure. The purpose of this editorial was to place the findings of the study by Li et al, as well as those of recently published reports, in perspective with what we know about myocardial extracellular remodeling in heart failure. The phenotype of dilated cardiomyopathic disease in humans can be characterized as a disproportionate increase in the ratio of LV ventricular chamber radius to wall thickness, with no increase in sarcomere length. The increased ratio of LV chamber radius to wall thickness is accompanied by increased myocardial wall stress, which can in turn promote further dilation and reduced pump function. Taken together, these observations would suggest that significant myocardial remodeling must occur within the LV free wall to allow for the chamber dilation and wall thinning that occur during the progression to severe LV dilation. Although the canonical view of LV remodeling has held that LV dilation occurs primarily as a result of an increase in myocyte size (hypertrophy), an increasing body of literature now suggests that the process of LV remodeling is far more complex than was once assumed and that important changes occur in the extracellular matrix components of the myocardium …
Automatic music mood classification via Low-Rank Representation

The problem of automatic music mood classification is addressed by resorting to low-rank representation of slow auditory spectro-temporal modulations. Recently, it has been shown that if each data class is linearly spanned by a subspace of unknown dimensions and the data are noiseless, the lowest-rank representation (LRR) of a set of test vector samples with respect to a set of training vector samples has the nature of being both dense for within-class affinities and almost zero for between-class affinities. Consequently, the LRR exactly reveals the classification of the data, resulting into the so-called Low-Rank Representation-based Classification (LRRC). The performance of the LRRC is compared against three well-known classifiers, namely the Sparse Representations-based Classifier, Support Vector Machines, and Nearest Neighbor classifiers for music mood classification by conducting experiments on the MTV and the Soundtracks180 datasets. The experimental results validate the effectiveness of the LRRC among the classifiers that is compared to.
Similarity and difference of the two successive V6 and V7 TRMM multisatellite precipitation analysis performance over China

Similarities and differences of spatial error structures of surface precipitation estimated with successive version 6 (V6) and version 7 (V7) Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) algorithms are systematically analyzed through comparison with the China Meteorological Administration's national daily precipitation analysis from June 2008 to May 2011. The TMPA products include V6 and V7 real‐time products 3B42RTV6 and 3B42RTV7 and research products 3B42V6 and 3B42V7. Both versions of research products outperform their respective real‐time counterparts. 3B42V7 clearly improves upon 3B42V6 over China in terms of daily mean precipitation; the correlation coefficient (CC) increases from 0.89 to 0.93, the relative bias (RB) improves from −4.91% to −0.05%, and the root‐mean‐square error (RMSE) improves from 0.69 mm to 0.54 mm. When considering 3 year mean precipitation, 3B42V7 shows similar spatial patterns and statistical performance to 3B42V6. Both 3B42RTV7 and 3B42RTV6 demonstrate similar bias patterns in most regions of China with overestimation by 20% in arid regions (i.e., the north and west of China) and slight underestimation in humid regions (e.g., −5.82% in southern China). However, 3B42RTV7 overestimates precipitation more than 3B42RTV6 in the cold Qinghai‐Tibetan plateau, resulting in a much higher RB of 139.95% (128.69%, 136.09%, and 121.11%) in terms of 3 year annual (spring, summer, and autumn) daily mean precipitation and an even worse performance during winter. In this region, 3B42RTV7 shows an overall slightly degraded performance than 3B42RTV6 with CC decreasing from 0.81 to 0.73 and RB (RMSE) increasing from 21.22% (0.95 mm) to 35.84% (1.27 mm) in terms of daily precipitation.
Toxicity study of oxalicumone A, derived from a marine-derived fungus Penicillium oxalicum, in cultured renal epithelial cells

Oxalicumone A (POA), a novel dihydrothiophene-condensed chromone, was isolated from the marine-derived fungus Penicillium oxalicum. Previous reports demonstrated that POA exhibits strong activity against human carcinoma cells, thus it has been suggested as a bioactive anticancer agent. To research the toxic effect of POA on cultured normal epithelial human kidney-2 (HK-2) cells and evaluate its clinical safety, cell survival was evaluated by the Cell Counting Kit-8 assay and apoptosis was evaluated by Hoechst 33258 staining, flow cytometry, caspase-3 activity assay and western blotting. 2′,7′-Dichlorofluorescin diacetate and JC-1 dye staining was used to evaluate reactive oxygen species (ROS) production and mitochondrial membrane potential (MMP), respectively. The results indicated that POA inhibited HK-2 cell growth and promoted apoptosis, by increasing levels of Fas cell surface cell receptor and the B-cell lymphoma 2 associated protein X apoptosis regulator (Bax)/B-cell lymphoma 2 apoptosis regulator (Bcl-2) ratio. POA treatment also induced release of ROS and loss of MMP in HK-2 cells. Compared with untreated control, a significant decrease was also demonstrated in superoxide dismutase activity and glutathione content with POA treatment, accompanied by enhanced release of N-acetyl-β-D-glucosaminidase, increased leakage of lactate dehydrogenase, increased malondialdehyde formation and increased release of nitric oxide. In conclusion, the present in vitro study revealed that POA exhibits antiproliferation activity on HK-2 cells, through stimulation of apoptosis and oxidative stress injury, which may be relevant to its clinical application. The present study may, therefore, offer valuable new information regarding the use of POA as a candidate novel antitumor drug for clinical use.
Diversity and disparity through time in the adaptive radiation of Antarctic notothenioid fishes

According to theory, adaptive radiation is triggered by ecological opportunity that can arise through the colonization of new habitats, the extinction of antagonists or the origin of key innovations. In the course of an adaptive radiation, diversification and morphological evolution are expected to slow down after an initial phase of rapid adaptation to vacant ecological niches, followed by speciation. Such ‘early bursts’ of diversification are thought to occur because niche space becomes increasingly filled over time. The diversification of Antarctic notothenioid fishes into over 120 species has become one of the prime examples of adaptive radiation in the marine realm and has likely been triggered by an evolutionary key innovation in the form of the emergence of antifreeze glycoproteins. Here, we test, using a novel time‐calibrated phylogeny of 49 species and five traits that characterize notothenioid body size and shape as well as buoyancy adaptations and habitat preferences, whether the notothenioid adaptive radiation is compatible with an early burst scenario. Extensive Bayesian model comparison shows that phylogenetic age estimates are highly dependent on model choice and that models with unlinked gene trees are generally better supported and result in younger age estimates. We find strong evidence for elevated diversification rates in Antarctic notothenioids compared to outgroups, yet no sign of rate heterogeneity in the course of the radiation, except that the notothenioid family Artedidraconidae appears to show secondarily elevated diversification rates. We further observe an early burst in trophic morphology, suggesting that the notothenioid radiation proceeds in stages similar to other prominent examples of adaptive radiation.
Extreme deviations from expected recovery curves and their associations with therapeutic alliance, social support, motivation, and life events in psychosomatic in-patient therapy

Abstract Objectives: Within the clinical support tools (CST) of the OQ-Analyst, the “Assessment for Signal Cases” (ASC) evaluates the therapeutic alliance, social support, motivation, and life events. We investigated whether the ASC covers domains of importance in treatment weeks with extreme deviations from expected recovery curves (ERCs). Methods: Psychosomatic in-patients were monitored weekly with the ASC and the “Outcome Questionnaire” (OQ-45). The ERCs of the OQ-45 empirical algorithm were used to define treatment weeks with extreme positive deviations (EPD), extreme negative deviations (END), or without extreme deviations (NO). Associations between the ASC scales and EPD as well as END were analyzed by multilevel models. Results: While each ASC scale was positively associated with EPD, only the social support and life events scales were negatively related to END. Conclusions: CSTs prioritizing social support and life events might be more effective in preventing treatment failure.
Lifestyle Intervention for Sleep Disturbances Among Overweight or Obese Individuals

Little is known about the effect of different lifestyle interventions on sleep disturbances among sedentary obese or overweight persons. We randomized men and women aged 35–65 to 6 months of a weight loss diet (D); or D combined with supervised exercise training Measurements were self-reported sleep disturbances, the Profile of Mood States questionnaire, BMI, total abdominal subcutaneous and visceral fat by magnetic resonance imaging, and aerobic fitness expressed as VO2peak. The groups did not differ in changes for body weight, abdominal total fat, VO2peak, and sleep disturbances. The novel finding herein is that reduced abdominal subcutaneous fat and depressive symptoms, with either D or were associated with less sleep disturbances.
Script Recognition—A Review

A variety of different scripts are used in writing languages throughout the world. In a multiscript, multilingual environment, it is essential to know the script used in writing a document before an appropriate character recognition and document analysis algorithm can be chosen. In view of this, several methods for automatic script identification have been developed so far. They mainly belong to two broad categories-structure-based and visual-appearance-based techniques. This survey report gives an overview of the different script identification methodologies under each of these categories. Methods for script identification in online data and video-texts are also presented. It is noted that the research in this field is relatively thin and still more research is to be done, particularly in the case of handwritten documents.
Optimization of the decision process in network and server-aware algorithms

Content Aware Networks define architectures capable of providing network, server context and user context-awareness to the selection of the appropriate content server, from which the Multimedia stream will be transmitted. The number and nature of the parameters involved in content server selection require enhanced multi-criteria decision algorithms in order to effectively use the whole information provided by the system. The paper proposes and analyzes by simulations a novel algorithm that enhances the so-called Reference Level decision algorithm. The added value of this paper is the extensive simulation model based on real VoD services that allows comparing different decision algorithms in Content Aware Networks. The simulation results center on comparing the proposed algorithm with a basic reference level decision algorithm and a random algorithm.
Dynamic Resource Allocation for MIMO Cognitive Networks With Low Control Traffic and Low Computational Complexity

Radio spectrum scarcity hampers the development of new wireless technologies and services. Cognitive radios have been proposed to enable unlicensed (or secondary) users to borrow locally idle bands of the spectrum provided that no significant interference is created for the licensed (or primary) users. Fast adaptation to the changing spectrum availability is naturally a major requirement in such systems. This adaptation consists of detecting the spectrum occupied by the primary users, computing a new resource allocation for the secondary network, and communicating this allocation through the network. In that context, we develop a resource allocation scheme for multi-input–multi-output wireless mesh networks. The proposed algorithm combines low computational complexity and light control traffic thanks to a combination of relevant approximations in the general nonpolynomial-hard allocation problem. The allocation consists of two steps. First, a centralized carrier allocation is performed at a coordinator node based on partial knowledge of the network parameters. Then, each node locally computes its power allocation through simple water-filling algorithms. Numerical results show that compared to state-of-the-art techniques, 10% of the total throughput of the network is sacrificed to reduce the computation time and the control traffic by two orders of magnitude.
Active Learning of Equivalence Relations by Minimizing the Expected Loss Using Constraint Inference

Selecting promising queries is the key to effective active learning. In this paper, we investigate selection techniques for the task of learning an equivalence relation where the queries are about pairs of objects. As the target relation satisfies the axioms of transitivity, from one queried pair additional constraints can be inferred. We derive both the upper and lower bound on the number of queries needed to converge to the optimal solution. Besides restricting the set of possible solutions, constraints can be used as training data for learning a similarity measure. For selecting queries that result in a large number of meaningful constraints, we present an approximative optimal selection technique that greedily minimizes the expected loss in each round of active learning. This technique makes use of inference of expected constraints. Besides the theoretical results, an extensive evaluation for the application of record linkage shows empirically that the proposed selection method leads to both interesting and a high number of constraints.
Coordination of resources using generalized state-based requirements

Abstract Control and coordination is an important aspect of the development of complex machines due to an ever increasing demand for better functionality, quality, and performance. We develop a coordinator for maintenance procedures for a high-tech Oce printer that eliminates undesired behavior which stems from unrestricted interaction of its distributed components. To this end, we extend and employ a model-based engineering framework for supervisory controller synthesis. We generalize standard state-based control requirements to increase modeling convenience. We model the use case with 23 generalized state-based requirements, which translate to 500+ requirements in the original form.
Factors influencing the interpretation of noun-noun compounds

The Competition Among Relation in Nominals theory (Gagne & Shoben, 1997) asserts that the relation frequency of the modifying noun is the primary determinant of ease of interpretation for noun-noun compounds. It also assumes that the influence of this variable is independent of the head noun. However, we suggest that both constituents exert an influence and that this influence depends on the pairing of nouns as well as the context. We present an experiment that investigates if the influence of the modifier’s relation frequency is fixed or whether it is affected by the head noun. Our results reveal that modifier relation frequency per se is not an accurate predictor of ease of interpretation: low modifier relation frequency combinations were easily interpreted in cases where the modifier’s general bias was overruled by the semantics of the head noun. As a result, we suggest that models predicting ease of interpretation must take into account the interaction of both constituents. The implications for models of conceptual combination are discussed.
Automatic Misconfiguration Troubleshooting with PeerPressure

Technical support contributes 17% of the total cost of ownership of today's desktop PCs [25]. An important element of technical support is troubleshooting miscon-figured applications. Misconfiguration troubleshooting is particularly challenging, because configuration information is shared and altered by multiple applications. In this paper, we present a novel troubleshooting system: PeerPressure, which uses statistics from a set of sample machines to diagnose the root-cause misconfigurations on a sick machine. This is in contrast with methods that require manual identification on a healthy machine for diagnosing misconfigurations [30]. The elimination of this manual operation makes a significant step towards automated misconfiguration troubleshooting. In PeerPressure, we introduce a ranking metric for misconfiguration candidates. This metric is based on empirical Bayesian estimation. We have prototyped a PeerPressure troubleshooting system and used a database of 87 machine configuration snapshots to evaluate its performance. With 20 real-world troubleshooting cases, PeerPressure can effectively pinpoint the root-cause misconfigurations for 12 of these cases. For the remaining cases, PeerPressure significantly narrows down the number of root-cause candidates by three orders of magnitude.