Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional programming languages in computing clouds : practical and theoretical explorations

Cloud platforms must integrate three pillars: messaging, coordination of workers and data. This research investigates whether functional programming languages have any special merit when it comes to the implementation of cloud computing platforms. This thesis presents the lightweight message queue CMQ and the DSL CWMWL for the coordination of workers that we use as artefact to proof or disproof the special merit of functional programming languages in computing clouds. We have detailed the design and implementation with the broad aim to match the notions and the requirements of computing clouds. Our approach to evaluate these aims is based on evaluation criteria that are based on a series of comprehensive rationales and specifics that allow the FPL Haskell to be thoroughly analysed. We find that Haskell is excellent for use cases that do not require the distribution of the application across the boundaries of (physical or virtual) systems, but not appropriate as a whole for the development of distributed cloud based workloads that require communication with the far side and coordination of decoupled workloads. However, Haskell may be able to qualify as a suitable vehicle in the future with future developments of formal mechanisms that embrace non-determinism in the underlying distributed environments leading to applications that are anti-fragile rather than applications that insist on strict determinism that can only be guaranteed on the local system or via slow blocking communication mechanisms.
Nicotine Treatment Alters NF-κB Expression in Human Cytomegalovirus-Infected ARPE-19 Cells

Purpose: To test if nicotine counteracts the dampening effect of human cytomegalovirus (HCMV) infection of NF-κB in retinal pigment epithelial (RPE) cells, thereby increasing the permissiveness of RPE cells for HCMV replication. Methods: Human ARPE-19 cells were transfected with NF-κB luciferase DNA, inoculated with HCMV at 24 hr post-transfection, and maintained in the absence or presence of a physiologic dose of nicotine at 1 hr prior to HCMV inoculation. Results: Whereas HCMV-infected ARPE-19 cells without nicotine treatment showed a dramatic decrease in NF-κB levels, nicotine treatment reduced this decrease but did not abolish it completely. Nicotine treatment of uninfected ARPE-19 cells had no effect on baseline NF-κB levels. Conclusions: Treatment of HCMV-infected ARPE-19 cells with nicotine at a physiologic dose dampened the downregulation of NF-κB observed in HCMV-infected ARPE-19 cells without nicotine treatment. We conclude that nicotine can serve as a cofactor to stimulate productive, lytic replication of HCMV.
Hierarchical causality explorer: making complemental use of 3D/2D visualizations

Hierarchical causality relationships reside ubiquitously in the reality. Since the relationships take intricate forms with two kinds of links - hierarchical abstraction and causal association, there exists no single visualization style that allows the user to comprehend them effectively. This paper introduces a novel information visualization framework which can change existing 3D and 2D display styles interactively according to the user's visual analysis demands. The two visualization styles play a complementary role, and the change in the style relies on morphing so as to maintain the user's cognitive map. Based on this framework, we have developed a general-purpose prototype system, which provides the user with an enriched set of functions not only for supporting fundamental information seeking, but bridging analytic gaps to accomplishing high-level analytic tasks such as knowledge discovery and decision making. The effectiveness of the system is illustrated with an application to the analysis of a nuclear-hazard cover-up problem.
Person identification system using feature level fusion of multi-biometrics

The use of unimodal biometric system is very low because of physiological defects, modes of user and their environment. Some of those drawbacks are alleviated by providing same identity for multiple evidences. Here a multimodal biometric system is proposed based on LBP, PCA and probabilistic neural network (PNN). In proposed method LBP extracted the Face features from face images and those features are given as input to PCA that generates Face Feature Vector with reduced Dimensions. Finger features are extracted from Fingerprint images using LBP and those features are given as input to PCA that generates Finger Feature Vector with reduced Dimensions. Using LBP, the distinct textual features of face and fingerprint are extracted. Weighted Summation Fusion method is used to combine these unimodal features. A probabilistic neural network is used as Classifier. An average recognition rate of 97.5% achieved with proposed method. Proposed method show that the proposed algorithm requires low computational cost.
Inference with Recursive Rules

Recursive rules, such as "Your parents' ancestors are your ancestors", although very useful for theorem proving, natural language understanding, questions-answering and information retrieval systems, present problems for many such systems, either causing infinite loops or requiring that arbitrarily many copies of them be made. We have written an inference system that can use recursive rules without either of these problems. The solution appeared automatically from a technique designed to avoid redundant work. A recursive rule causes a cycle to be built in an AND/OR graph of active processes. Each pass of data through the cycle resulting in another answer. Cycling stops as soon as either the desired answer is produced, no more answers can be produced, or resource bounds are exceeded.
Spatial Modelling and Mapping of Socio-Demographic Determinants ofInfant Mortality in Kenya

This paper addresses the problem of monitoring the infant and child mortality from point referenced data. Indicators of the determinants of child survival based on Mosley and Chen framework are derived and used to model the spatial distribution of infant mortality. Spatial generalised linear model which assumes a Bernoulli distribution to model the indicator determinants of child survival. A smooth map of the predicted values at both sampled and the un sampled is produced. We find evidence of spatial autocorrelation in the data and the smooth map indicates the hot spot of infant mortality where more resources are needed to attain the millennium development goal four.
Color matches of patients with retinitis pigmentosa.

The color matches of 46 retinitis pigmentosa (RP) patients were found to differ significantly from those of 55 unaffected observers. The color matches of group I (trichromatic) RP observers were more protanomalous (i.e., required a greater red/green mixture ratio) than those of unaffected observers. The matches of group II (dichromatic) RP observers were more protanopic (i.e., required less yellow to match the red primary) than those of the group II unaffected observers. In view of current evidence, this difference can be attributed to reductions in the pigment optical density of cone photoreceptors in eyes of RP patients.
Service Oriented Cooperation among Trustworthy Peers

Various types of applications make access to objects distributed in peer-to-peer (P2P) overlay networks. Even if the locations of target objects are discovered by some look-up algorithm such as flooding and distributed hash table (DHT), applications cannot manipulate the target objects without access rights. It is critical to perceive which peer can manipulate an object in which method, i.e. only a peer authorized with an access right is allowed to manipulate an object. Hence, an application has to find peers which can manipulate a target object rather than detect the location of the target object. Due to the scalability, variety, and autonomy of peers, it is difficult, may be impossible to maintain a centralized directory showing in which peer each object is distributed. An acquaintance peer of a peer p is a peer whose service the peer p knows and with which the peer p can directly communicate. We discuss types of acquaintance relations of peers with respect to what objects each peer holds, is allowed to manipulate, and can grant access rights on. Acquaintance peers of a peer may notify the peer of different information on target peers due to communication and propagation delay. Here, it is critical to discuss how much a peer trusts each acquaintance peer. We first define the satisfiability of an acquaintance peer, i.e. how much a peer is satisfied by issuing an access request to the acquaintance peer. For example, if a peer p locally manipulates a target object o and obtains a response, p is mostly satisfied. On the other hand, if the peer p has to ask another peer to manipulate the object o, the peer p is less satisfied. We define the trustworthiness and ranking factor of an acquaintance peer obtained by accumulating the satisfiability of each interaction with the acquaintance peer. Differently from traditional reputation concepts, trustworthiness information only from trustworthy acquaintance peers can be used to obtain the ranking factor. The trustworthiness of an acquaintance peer shows how much a peer can trusts the acquaintance peer while the ranking factor of an acquaintance peer shows how much the acquaintance peer is trusted by other trustworthy acquaintance peers. Then, we evaluate the trustworthiness and ranking factor in presence of faulty peers.
Red blood cell-mimicking synthetic biomaterial particles

Biomaterials form the basis of current and future biomedical technologies. They are routinely used to design therapeutic carriers, such as nanoparticles, for applications in drug delivery. Current strategies for synthesizing drug delivery carriers are based either on discovery of materials or development of fabrication methods. While synthetic carriers have brought upon numerous advances in drug delivery, they fail to match the sophistication exhibited by innate biological entities. In particular, red blood cells (RBCs), the most ubiquitous cell type in the human blood, constitute highly specialized entities with unique shape, size, mechanical flexibility, and material composition, all of which are optimized for extraordinary biological performance. Inspired by this natural example, we synthesized particles that mimic the key structural and functional features of RBCs. Similar to their natural counterparts, RBC-mimicking particles described here possess the ability to carry oxygen and flow through capillaries smaller than their own diameter. Further, they can also encapsulate drugs and imaging agents. These particles provide a paradigm for the design of drug delivery and imaging carriers, because they combine the functionality of natural RBCs with the broad applicability and versatility of synthetic drug delivery particles.
Two-Level Hierarchical Alignment for Semi-Coupled HMM-Based Audiovisual Emotion Recognition With Temporal Course

A complete emotional expression typically contains a complex temporal course in face-to-face natural conversation. To address this problem, a bimodal hidden Markov model (HMM)-based emotion recognition scheme, constructed in terms of sub-emotional states, which are defined to represent temporal phases of onset, apex, and offset, is adopted to model the temporal course of an emotional expression for audio and visual signal streams. A two-level hierarchical alignment mechanism is proposed to align the relationship within and between the temporal phases in the audio and visual HMM sequences at the model and state levels in a proposed semi-coupled hidden Markov model (SC-HMM). Furthermore, by integrating a sub-emotion language model, which considers the temporal transition between sub-emotional states, the proposed two-level hierarchical alignment-based SC-HMM (2H-SC-HMM) can provide a constraint on allowable temporal structures to determine an optimal emotional state. Experimental results show that the proposed approach can yield satisfactory results in both the posed MHMC and the naturalistic SEMAINE databases, and shows that modeling the complex temporal structure is useful to improve the emotion recognition performance, especially for the naturalistic database (i.e., natural conversation). The experimental results also confirm that the proposed 2H-SC-HMM can achieve an acceptable performance for the systems with sparse training data or noisy conditions.
18F-Fluoromisonidazole Kinetic Modeling for Characterization of Tumor Perfusion and Hypoxia in Response to Antiangiogenic Therapy

Multiparametric imaging of tumor perfusion and hypoxia with dynamic 18F-fluoromisonidazole (18F-FMISO) PET may allow for an improved response assessment to antiangiogenic therapies. Cediranib (AZD2171) is a potent inhibitor of tyrosine kinase activity associated with vascular endothelial growth factor receptors 1, 2, and 3, currently in phase II/III clinical trials. Serial dynamic 18F-FMISO PET was performed to investigate changes in tumor biomarkers of perfusion and hypoxia after cediranib treatment. Methods: Twenty-one rats bearing HT29 colorectal xenograft tumors were randomized into a vehicle-treated control group (0.5% methylcellulose daily for 2 d [5 rats] or 7 d [4 rats]) and a cediranib-treated test group (3 mg/kg daily for 2 or 7 d; 6 rats in both groups). All rats were imaged before and after treatment, using a 90-min dynamic PET acquisition after administration of 42.1 ± 3.9 MBq of 18F-FMISO by tail vein injection. Tumor volumes were delineated manually, and the input function was image-derived (abdominal aorta). Kinetic modeling was performed using an irreversible 1-plasma 2-tissue compartmental model to estimate the kinetic rate constants K1, K1/k2, and k3—surrogates for perfusion, 18F-FMISO distribution volume, and hypoxia-mediated entrapment, respectively. Tumor-to-blood ratios (TBRs) were calculated on the last dynamic frame (80–90 min). Tumors were assessed ex vivo by digital autoradiography and immunofluorescence for microscopic visualization of perfusion (pimonidazole) and hypoxia (Hoechst 33342). Results: Cediranib treatment resulted in significant reduction of mean voxelwise 18F-FMISO TBR, K1, and K1/k2 in both the 2-d and the 7-d groups (P < 0.05). The k3 parameter was increased in both groups but reached significance only in the 2-d group. In the vehicle-treated groups, no significant change in TBR, K1, K1/k2, or k3 was observed (P > 0.2). Ex vivo tumor analysis confirmed the presence of hypoxic tumor regions that nevertheless exhibited relatively lower 18F-FMISO uptake. Conclusion: 18F-FMISO kinetic modeling reveals a more detailed response to antiangiogenic treatment than a single static image is able to reveal. The reduced mean K1 reflects a reduction in tumor vascular perfusion, whereas the increased k3 reflects a rise in hypoxia-mediated entrapment of the radiotracer. However, if only late static images are analyzed, the observed reduction in 18F-FMISO uptake after treatment with cediranib may be mistakenly interpreted as a global decrease, rather than an increase, in tumor hypoxia. These findings support the use of 18F-FMISO kinetic modeling to more accurately characterize the response to treatments that have a direct effect on tumor vascularization and perfusion.
Protein Disorder Prediction using Information Theory Measures on the Distribution of the Dihedral Torsion Angles from Ramachandran Plots

This paper addresses the problem of order/disorder prediction in protein sequences from alignment free methods. The proposed approach is based on a set of 11 information theory measures estimated from the distribution of the dihedral torsion angles in the amino acid chain. The aim is to characterize the energetically allowed regions for amino acids in the protein structures, as a way of measuring the rigidity/flexibility of every amino acid in the chain, and the effect of such rigidity on the disorder propensity. The features are estimated from empirical Ramachandran Plots obtained using the Protein Geometry Database. The proposed features are used in conjunction with well-established features in the state of the art for disorder prediction. The classification is performed using two different strategies: one based on conventional supervised methods and the other one based on structural learning. The performance is evaluated in terms of AUC (Area Under the ROC Curve), and three suitable performance metrics for unbalanced classification problems. The results show that the proposed scheme using conventional supervised methods is able to achieve results similar than well-known alignment free methods for disorder prediction. Moreover, the scheme based on structural learning outperforms the results obtained for all the methods evaluated, including three alignment-based methods.
Parental attributions of controllability as a moderator of the relationship between developmental disability and behaviour problems.

BACKGROUND Children with developmental disabilities present behaviour problems to a greater extent than do typically developing children. Psychosocial models of child development suggest that parental attributions of child and adult controllability could moderate this relationship between child disability status and behaviour. METHODS The influence of parental attributions of adult and child controllability on the relationship between problem behaviours and disability was explored in mothers of children with developmental disabilities (DD) (N = 20) with a mean age of 9 years 3 months (SD 24.6 months), and in mothers of typically developing (TD) children (N = 26) with a mean age of 9 years 4 months (standard deviation 23.7 months). The DD group comprised 11 children with autistic spectrum disorders or other communication impairments, three children with Down Syndrome, one with cerebral palsy, one with attentional problems, and four with specific or complex developmental problems. Child behaviour was measured by the Child Behaviour Checklist. Parental attributions were measured using a modified version of the Parent Attribution Test and mothers were divided into higher and lower controllability groups on the basis of their responses on this test. RESULTS Multivariate analysis of variance found significant group × adult controllability interaction effects for 'aggressive behaviour', 'rule-breaking behaviour', as well as borderline significant effects for 'social problems' and 'other problems'. Simple effects analysis suggested that when mothers had lower attributions of adult controllability, there were indeed significantly more problem behaviours in the DD group, but when mothers had attributions of higher adult controllability there was no longer any significant difference in problematic behaviour between the two groups. CONCLUSIONS Parental attributions of controllability may moderate the well-established effect of disability on problem behaviour. Implications for parent intervention programmes are discussed.
The lethal dose of total-body X-ray irradiation in swine.

The Development of the atomic bomb has stimulated great interest in the study of ionizing radiation injury to living tissue. A large field experiment, designed to determine both physical and biological effects of the release of atomic energy, was successfully carried out by Joint Task Force One in Operation Crossroads in the summer of 1946 (1, 2). It is desirable to produce comparable ionizing radiation lesions in laboratory experiments not only to allow correlation with and better understanding of the data obtained at Bikini, but also to serve as a basis for future studies of ionizing radiation injuries. Previous work has largely concerned smaller forms. Some interest lies in studying larger animals, such as swine, not only from the standpoint of greater tissue masses and the increasing significance of depth dosage, but also because of a possible doser relation to the radiosensitivity of man. Groups of swine were given known amounts of total body irradiation with hard x-rays emanating from an industrial .
Concurrent Validity of the Zeno Walkway for Measuring Spatiotemporal Gait Parameters in Older Adults

Background and Purpose: Previous studies have shown that older adults at high fall risk exhibit altered spatiotemporal gait parameters such as lesser gait speed, shorter step length, and greater step width compared with their healthy counterparts. Measurement of these gait parameters for older adults can play a pivotal role in clinical evaluation. While the GAITRite walkway has been previously validated and used extensively for research purposes, the Zeno walkway validity has not been established. Although both walkways use pressure sensor–based technology, comparison of the spatiotemporal gait measurements between the systems for older adults is unknown. Our purpose was to determine the concurrent validity of the Zeno walkway with the gold-standard GAITRite walkway among healthy older adults and those at high fall risk using a cross-sectional study design. Methods: Thirty healthy older adults and 17 older adults at high fall risk performed 5 walking trials barefoot on a 16´ × 4´ Zeno walkway and a 14´ × 2´ GAITRite walkway in a quasi-randomized order. Testing on the Zeno walkway was performed in a continuous manner while testing on the GAITRite walkway was performed using 5 discrete trials. Walking trials were done at self-selected comfortable and fast pace conditions. Data from the Zeno walkway were processed using the PKMAS software. Data from the GAITRite were processed using the GAITRite software. For each group and condition, spatiotemporal gait parameters common to both walkways' footfall processing software were compared using a Wilcoxon signed rank test. Concurrent validity was estimated using intraclass correlation coefficient (ICC(2,5)) and Bland-Altman plots. Results and Discussion: Both groups had significantly greater stride width on the GAITRite walkway during both conditions. During the fast pace condition, both groups walked with greater gait speed, cadence, and stride velocity, lesser step time, stance time, and double-support time, greater percentage of gait cycle spent in single-support phase, and lesser percentage of gait cycle spent in double-support phase on the GAITRite walkway. Differences observed could be attributed to surface textures, software used to process the footfalls, dimensions of the walkways, or the continuous versus discrete protocols used in the current study. The ranges of ICC(2,5) values for healthy older adults and adults at high fall risk walking at a comfortable pace were 0.449 to 0.918 and 0.854 to 0.969 and at a fast pace were 0.784 to 0.964 and 0.850 to 0.976, respectively. These values imply that the concurrent validity was moderate for most temporal parameters when healthy older adults walked at comfortable pace and excellent otherwise. Overall, the concurrent validity between both walkways was acceptable. Conclusion: Concurrent validity for spatiotemporal parameters between the GAITRite walkway and the Zeno walkway was moderate to excellent for older adults dependent on the specific parameter (spatial vs temporal), population (healthy or fall risk), and walking pace (comfortable or fast).
Asymptotic Stability of the Golden-Section Control Law for Multi-Input and Multi-Output Linear Systems

This paper is concerned with the problem of the asymptotic stability of the characteristic model-based golden-section control law for multi-input and multi-output linear systems. First, by choosing a set of polynomial matrices of the objective function of the generalized least-square control, we prove that the control law of the generalized least square can become the characteristic model-based golden-section control law. Then, based on both the stability result of the generalized least-square control system and the stability theory of matrix polynomial, the asymptotic stability of the closed loop system for the characteristic model under the control of the golden-section control law is proved for minimum phase system.