Miracle-dz/UniFAR-FTUs huggingface dataset:
Contribution of Nitric Oxide Synthases 1, 2, and 3 to Airway Hyperresponsiveness and Inflammation in a Murine Model of Asthma

Asthma is a chronic disease characterized by increased airway responsiveness and airway inflammation. The functional role of nitric oxide (NO) and the various nitric oxide synthase (NOS) isoforms in human asthma is controversial. To investigate the role of NO in an established model of allergic asthma, mice with targeted deletions of the three known isoforms of NOS (NOS1, 2, and 3) were studied. Although the inducible (NOS2) isoform was significantly upregulated in the lungs of ovalbumin (OVA)-sensitized and -challenged (OVA/OVA) wild-type (WT) mice and was undetectable in similarly treated NOS2-deficient mice, airway responsiveness was not significantly different between these groups. OVA/OVA endothelial (NOS3)-deficient mice were significantly more responsive to methacholine challenge compared with similarly treated NOS1 and NOS1&3-deficient mice. Airway responsiveness in OVA/OVA neuronal (NOS1)-deficient and neuronal/endothelial (NOS1&3) double-deficient mice was significantly less than that observed in similarly treated NOS2 and WT groups. These findings demonstrate an important function for the nNOS isoform in controlling the inducibility of airway hyperresponsiveness in this model of allergic asthma.
Analysis of Indoor Rowing Motion using Wearable Inertial Sensors

In this exploratory work the motion of rowers is analyzed while rowing on a rowing machine. This is performed using inertial sensors that measure the orientation at several positions on the body. Using these measurements, this work provides a preliminary analysis of the differences between experienced and novice rowers, or between a good and a bad technique. The analysis shows that the measured postural angles show no clear trend that would set apart experienced and novice rowers or a bad and a good technique. However, there are clear differences in absolute postural angle's consistency and timing consistency of strokes between novice and experienced rowers. We also applied a machine learning technique to the data to find the similarities between different rowers and an experienced reference rower. The results can be used to compare the quality of the rowing technique with respect to a reference. In this paper, we present our initial results as well as the challenges that need to be further explored.
XPath queries on streaming data

We present the design and implementation of the XSQ system for querying streaming XML data using XPath 1.0. Using a clean design based on a hierarchical arrangement of pushdown transducers augmented with buffers, XSQ supports features such as multiple predicates, closures, and aggregation. XSQ not only provides high throughput, but is also memory efficient: It buffers only data that must be buffered by any streaming XPath processor. We also present an empirical study of the performance characteristics of XPath features, as embodied by XSQ and several other systems.
Black seed, Nigella sativa, deserves more attention.

Nigella sativa (N. sativa) seed, called as ‘Black Seed’ in English language, ‘Al-Habba Al-Sauda’ or ‘AlHabba Al-Barakah’ in Arabic and ‘Kalvanji’ in Urdu and some local languages in the Indian Subcontinent, is well known in the Middle East, Middle Asia and Far East as a natural remedy for many ailments and as a flavouring agent in bread and prickles. An authentic saying of the Prophet Muhammad (Peace Be Upon Him) about black seed is also quoted in Al-Bukhari:
LEARNING : TOWARDS A DESIGN SCIENCE

Research into organizational learning and knowledge management tends to be based on science and the humanities. Science helps to understand organized systems by uncovering laws and forces that determine their characteristics, functioning and outcomes. Research drawing on the humanities helps to understand, and critically reflect on, the human experience of actors inside organized systems. This paper argues that scholars operating in this field should adopt design as one of their primary modes of engaging in research. Design is characterized by its emphasis on solution finding, guided by broader purposes and ideal target systems. Moreover, design develops, and draws on, propositions that are tested in pragmatic experiments and grounded in organization and management science. Drawing on Herbert Simon’s work, the development of a design science is therefore advocated.
Derived vocalizations of geladas (Theropithecus gelada) and the evolution of vocal complexity in primates

Primates are intensely social and exhibit extreme variation in social structure, making them particularly well suited for uncovering evolutionary connections between sociality and vocal complexity. Although comparative studies find a correlation between social and vocal complexity, the function of large vocal repertoires in more complex societies remains unclear. We compared the vocal complexity found in primates to both mammals in general and human language in particular and found that non-human primates are not unusual in the complexity of their vocal repertoires. To better understand the function of vocal complexity within primates, we compared two closely related primates (chacma baboons and geladas) that differ in their ecology and social structures. A key difference is that gelada males form long-term bonds with the 2–12 females in their harem-like reproductive unit, while chacma males primarily form temporary consortships with females. We identified homologous and non-homologous calls and related the use of the derived non-homologous calls to specific social situations. We found that the socially complex (but ecologically simple) geladas have larger vocal repertoires. Derived vocalizations of geladas were primarily used by leader males in affiliative interactions with ‘their’ females. The derived calls were frequently used following fights within the unit suggesting that maintaining cross-sex bonds within a reproductive unit contributed to this instance of evolved vocal complexity. Thus, our comparison highlights the utility of using closely related species to better understand the function of vocal complexity.
“Field cancerization” in oral stratified squamous epithelium. Clinical implications of multicentric origin

QUAMOUS-CELL, OR EPIDERMOID carcinoma is S the most common cancer affecting the human body. This tumor prototype may originate in more anatomical sites than any other form of carcinoma, since it is the usual cancer of the skin, lip, oral cavity, pharynx, larynx, bronchi, esophagus, anus, vulva, vagina, cervix, urethra, penis, and even bladder and renal pelvis. Rarely, it may occur primarily or as a metaplastic variant in other organs. Since the behavior patterns of this morphological entity would seem to have many similar characteristics in its differing locations and microscopic variations, detailed knowledge of the natural history of this disease is of some importance. As our most readily available source of squamous-cell carcinoma, oral cancers were studied from the standpoint of their origins and manner of spread. Tumors of the lip, oral cavity, and pharynx in 783 patients have been reviewed, with findings that reinforce the concept of multifocal growth of these tumors. The mu1 ticen tric origin of epidermoid carcinoma is not widely accepted, although such occurrence in the skin is generally recognized and studies of in situ carcinoma of the cervix uteri are indicative of this origin.
Predicting Cognitive Decline in Older Adults Through Multi-Voxel Pattern Analysis

PREDICTING COGNITIVE DECLINE IN OLDER ADULTS THROUGH MULTI-VOXEL PATTERN ANALYSIS Nathan Hantke, M.S. Marquette University, 2014 Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that is associated with cognitive and structural decline beyond what is seen in normal, healthy aging. Functional magnetic resonance imaging (fMRI) research indicates that prior to the onset of measureable cognitive impairment, individuals at-risk for AD demonstrate different patterns of neural activation than individuals at lower risk. Thus, differences in task-activated fMRI may be beneficial in predicting cognitive decline at a “presymptomatic” stage. The present study utilizes multi-voxel pattern analysis (MVPA) of baseline fMRI task-related activation to predict cognitive decline, with the hypothesis that famous and non-famous name task activation will discriminate older adults who go on to experience cognitive decline from those who do not. Ninety-nine cognitively intact older adults underwent neuropsychological testing and a semantic memory fMRI task (famous name discrimination). After follow-up neuropsychological testing 18-months later, participants were grouped as “Stable” (n = 65) or “Declining” (n = 34) based on > 1.0 SD decline in performance on cognitive measures. MVPA classification accuracy was 90% for stimulus type (famous and non-famous names), thereby supporting the general approach. Mean MVPA classification accuracy for famous and non-famous names was 83% for both the Stable and Declining groups. Finally, MVPA produced greater than chance classification accuracy of participant groups for both famous name activation (56%) and non-famous name activation (55%) as determined via binomial distribution. The results of the current study suggest that MVPA possesses potential in predicting cognitive decline in older adults.
An approximation algorithm to find a Dom-chromatic set and the Dom-chromatic number of a graph

A set S ⊆ V is said to be a dominating set of G if for each u ∈ V − S, there exists a vertex v ∈ S such that u is adjacent to v. The minimum cardinality of a dominating set in G is called the domination number of G and is denoted by γ (G). A proper coloring of G is an assignment of colors to the vertices of G such that no two adjacent vertices receive the same color. G is said to be k-colorable if it is has proper coloring using k colors. The minimum k such that G is k-colorable is called the chromatic number of G, denoted by χ(G). A subset S of V is called a domchromatic set if S is a dominating set and χ(< S >) = χ(G). In this paper, it is shown that the problem of finding the dom-chromatic set of a graph is NP-Complete and also an approximation algorithm is proposed to find the Dom-chromatic set and the Dom-chromatic number of a graph. AMS subject classification:
HIGH CONFIDENCE SOFTWARE AND SYSTEMS RESEARCH NEEDS

ions and Mechanisms. New abstractions are needed to simplify the incorporation of robustness into high confidence systems. New mechanisms that allow systems to tolerate various types of faults and anomalies while continuing to satisfy other high confidence properties are needed. Existing fault tolerance methods need to be rethought to accommodate operation under real-time and security constraints and encapsulated as reusable (but customizable) services and middleware. Innovative new methods of robustly interfacing software components are also needed to automatically “impedance match” components by ascribing explicit semantics and constraint to interface definitions. Active interfaces, for example, could not only handle mismatches in data types and formats, but could further include mechanisms to address timing and synchronization issues, incomplete data, and propagation of information on the uncertainty or “quality” of the data. Architecture. Techniques are needed to enable the systematic design of failure or degraded modes of operation that can limit some aspects of function or performance in order to assure system survival. Architectural constructs that allow isolation of faults or malicious behavior and limit propagation of errors or uncertainties are needed. Human System Interaction. High confidence systems must be developed at every stage with consideration of human-machine interface issues, because the human operator eventually becomes a critical part of the operational system. Methods must also be developed for designing tolerance to human errors or malicious actions into the system. Formal methods could be explored for precisely representing to operators the behavior of systems with complex functions and modes and in supporting automated processes that assist in their training.
Phenology of the Western Cherry Fruit Fly (Diptera: Tephritidae) in Utah and Washington

The flight period of the western cherry fruit fly, Rhagoletis indifferens Curran, was investigated in Utah tart cherry, Prunus cerasus L. , orchards from 1983 to 1989 and in Washington sweet cherry, Prunus avium L. , orchards between 1982 and 1988. In Utah, flies were first detected on 31 May 1989, but the average time of first detection was 9 June across nine site-years. In Washington, the first fly was detected on 23 May 1988, with an average first detection time of 1 June in the three site-years. On a degree-day (DD) scale (lower threshold of 5°C and no upper threshold), detection of the first fly averaged 573 ± 19.0 DD (x ± SEM) in Utah and 592 ± 42.1 DD in Washington. A degree-day model using the combined data for Utah and Washington consistently predicted emergence for all but one Utah site without synchronization of the model based on capture of the first fly.
Examining the Relationships between Empathy, Mood, and Facial Mimicry

Facial mimicry is an automatic process that may occur as we see facial expression and respond congruently with a similar expression (van Baaren, Fockenberg, Holland, Janssen, & van Knippenberg, 2006). Empathy is the capacity to take on and understand another’s emotions (Hojat et al., 2002). While positive relationships between mimicry and empathy have been previously established, less is known regarding the interrelations among state affect, empathy, and facial mimicry. The present study examined these relationships in a single sample. While positive relationships were found between empathy and state affect, empathy and state affect did not have an effect on facial mimicry.
iTreePack: Protein Complex Side-Chain Packing by Dual Decomposition

Protein side-chain packing is a critical component in obtaining the 3D coordinates of a structure and drug discovery. Single-domain protein side-chain packing has been thoroughly studied. A major challenge in generalizing these methods to protein complexes is that they, unlike monomers, often have very large treewidth, and thus algorithms such as TreePack cannot be directly applied. To address this issue, SCWRL4 treats the complex effectively as a monomer, heuristically excluding weak interactions to decrease treewidth; as a result, SCWRL4 generates poor packings on protein interfaces. To date, few side-chain packing methods exist that are specifically designed for protein complexes. In this paper, we introduce a method, iTreePack, which solves the side-chain packing problem for complexes by using a novel combination of dual decomposition and tree decomposition. In particular, iTreePack overcomes the problem of large treewidth by decomposing a protein complex into smaller subgraphs and novelly reformulating the complex side-chain packing problem as a dual relaxation problem; this allows us to solve the side-chain packing of each small subgraph separately using tree-decomposition. A projected subgradient algorithm is applied to enforcing the consistency among the side-chain packings of all the small subgraphs. Computational results demonstrate that our iTreePack program outperforms SCWRL4 on protein complexes. In particular, iTreePack places side-chain atoms much more accurately on very large complexes, which constitute a significant portion of protein-protein interactions. Moreover, the advantage of iTreePack over SCWRL4 increases with respect to the treewidth of a complex. Even for monomeric proteins, iTreePack is much more efficient than SCWRL and slightly more accurate.
Experience-based guidelines for effective and efficient data extraction in systematic reviews in software engineering

To systematically collect evidence and to structure a given area in software engineering (SE), Systematic Literature Reviews (SLR) and Systematic Mapping (SM) studies have become common. Data extraction is one of the main phases (activities) when conducting an SM or an SLR, whose objective is to extract required data from the primary studies and to accurately record the information researchers need to answer the questions of the SM/SLR study. Based on experience in a large number of SM/SLR studies, we and many other researchers have found the data extraction in SLRs to be time consuming and error-prone, thus raising the real need for heuristics and guidelines for effective and efficient data extraction in these studies, especially to be learnt by junior and young researchers. As a 'guideline' paper, this paper contributes a synthesized list of challenges usually faced during SLRs' data extraction phase and the corresponding solutions (guidelines). For our synthesis, we consider two data sources: (1) the pool of 16 SLR studies in which the authors have been involved in, as well as (2) a review of challenges and guidelines in the existing literature. Our experience in utilizing the presented guidelines in the near past have helped our junior colleagues to conduct data extractions more effectively and efficiently.
Forecasting Ad-Impressions on Online Retail Websites using Non-homogeneous Hawkes Processes

Promotional listing of products or advertisements is a major source of revenue for online retail companies. These advertisements are often sold in the guaranteed delivery market, serving of which critically depends on the ability to predict supply or potential impressions from a target segment of users. In this paper, we study the problem of predicting user visits or potential ad-impressions to online retail websites, based on historical time-stamps. We explore the time-series and temporal point process models. We find that a successful model must encompass three properties of the data: (1) temporally non-homgeneous rates, (2) self excitation and (3) handling special events. We propose a novel non-homogeneous Hawkes process based model for the same, and new algorithm for fitting this model without overfitting the self-excitation part. We validate the proposed model and algorithm using mulitple large scale ad-serving dataset from a top online retail company in India.
A Power Provision and Capping Architecture for Large Scale Systems

The rapid growth of large scale computing systems imposes a grave challenge to their power management, where power provision and capping is essential. In this paper, we propose a new architecture of power provision and capping to control the power consumption of large scale clusters. In this architecture, performance sensitive computation units are distinguished from those having less impact on system performance. A subset of units is monitored and their operation states are controlled in order to maintain whole system's total power consumption under budget. Two policies are designed and implemented to select the target subset of nodes for power regulation. One policy is state-based, which chooses nodes running the most power consuming job for power regulation. The other is change-based, which chooses those nodes that runs a job whose power consumption increases most rapidly among all jobs. Experiments have been conducted on the Tianhe-1A supercomputer system to evaluate the effectiveness of these power capping solutions. The experiments demonstrated that the new architecture can ensure power usage safety with only a negligible decline of performance, which is only about 2%.
Extraction Based Multi Document Summarization using Single Document Summary Cluster

Multi document summarization has very great impact among research community, ever since the growth of online information and availability. Selecting most important sentences from such huge repository of data is quiet tricky and challenging task. While multi document poses some additional overhead in sentence selection, generating summaries for each individual documents and merging the sentences in a coherent order would greater strength. The proposed approach was competitively better as compared to state of MEAD summarizer at focused compression ratios. This paper focus on three different studies namely i. To find the performance of multi document summarizer from single document cluster (using MEAD) ii. Comparison of our approach with MEAD performance for the dataset considered iii. To extract sentences for multi document summarization at 30% compression rate to obtain 100% efficiency using 7-point summary sheet. Investigation carried out from an average of 22 documents shows that our system is promising.
Influence of motor unit firing patterns on evaluation of muscle activities by Karhunen-Loève expansion

In fields such as rehabilitation and sports science, it is important to evaluate the state of muscle fatigue exactly in order to realize the maximum training effect while avoiding damage due to overtraining. Since the surface EMG is noninvasive and measurement is easy, the EMG evaluation parameters calculated from EMG are widely used for evaluation. It should be noted, however, that the behavior of the evaluation parameters is similar in true muscle fatigue and in cases where muscle fatigue is simulated by intentionally decreasing the muscle tension. This makes discrimination of the two cases difficult. To recognize the difference between the states of muscle activity, the authors proposed a method in which the time series of the EMG evaluation parameters is represented by a Karhunen–Loeve (KL) expansion, but the physiological condition which is expressed by the result of KL expansion analysis has not been sufficiently investigated. This study uses a surface EMG simulation model in which the firing pattern of the motor units (MU) can be varied flexibly, and attempts to clarify how the MU firing pattern affects the results of analysis by KL expansion. It is found that the same analytical results as for the state of muscle fatigue can be obtained by considering the fluctuation of the firing probability in multiple MU and the accompanying intermittent MU recruitment. © 2003 Wiley Periodicals, Inc. Syst Comp Jpn, 34(12): 45–55, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10326
3D Porous Architecture of Stacks of β-TCP Granules Compared with That of Trabecular Bone: A microCT, Vector Analysis, and Compression Study

The 3D arrangement of porous granular biomaterials usable to fill bone defects has received little study. Granular biomaterials occupy 3D space when packed together in a manner that creates a porosity suitable for the invasion of vascular and bone cells. Granules of beta-tricalcium phosphate (β-TCP) were prepared with either 12.5 or 25 g of β-TCP powder in the same volume of slurry. When the granules were placed in a test tube, this produced 3D stacks with a high (HP) or low porosity (LP), respectively. Stacks of granules mimic the filling of a bone defect by a surgeon. The aim of this study was to compare the porosity of stacks of β-TCP granules with that of cores of trabecular bone. Biomechanical compression tests were done on the granules stacks. Bone cylinders were prepared from calf tibia plateau, constituted high-density (HD) blocks. Low-density (LD) blocks were harvested from aged cadaver tibias. Microcomputed tomography was used on the β-TCP granule stacks and the trabecular bone cores to determine porosity and specific surface. A vector-projection algorithm was used to image porosity employing a frontal plane image, which was constructed line by line from all images of a microCT stack. Stacks of HP granules had porosity (75.3 ± 0.4%) and fractal lacunarity (0.043 ± 0.007) intermediate between that of HD (respectively 69.1 ± 6.4%, p < 0.05 and 0.087 ± 0.045, p < 0.05) and LD bones (respectively 88.8 ± 1.57% and 0.037 ± 0.014), but exhibited a higher surface density (5.56 ± 0.11 mm2/mm3 vs. 2.06 ± 0.26 for LD, p < 0.05). LP granular arrangements created large pores coexisting with dense areas of material. Frontal plane analysis evidenced a more regular arrangement of β-TCP granules than bone trabecule. Stacks of HP granules represent a scaffold that resembles trabecular bone in its porous microarchitecture.