Miracle-dz/UniFAR-FTUs huggingface dataset:
Specific receptor detection by a functional keratinocyte growth factor- immunoglobulin chimera

Fibroblast growth factor receptors (FGFRs) are encoded by at least four distinct highly conserved genes, and alternative splicing generates multiple gene products. The close relationship among different FGFRs has greatly increased the difficulty in generating specific immunochemical probes. As an alternative strategy, we constructed a fusion protein comprising keratinocyte growth factor (KGF) and an IgG1 Fc domain (HFc). The chimeric molecule was efficiently secreted from transfectants as a disulfide-linked dimer that bound KGFRs with high affinity. Moreover, the KGF-HFc, like native KGF, induced DNA synthesis by epithelial cells implying normal functional receptor activation. Because it retained the convenient detection properties of an immunoglobulin, it was possible to use the KGF-HFc in ligand-mediated histochemical analysis of KGFRs. Flow cytometry revealed KGF-HFc chimera detection of the KGFR, an alternative FGFR2 product, but not FGFR1 (flg) or FGFR2 (bek). Histochemical analysis of normal skin demonstrated the specific localization of KGFRs within the spinous layer, a zone of epithelial cell differentiation. KGFRs were also localized to epithelial cells within a specific region of the hair follicle, and they were not detectable in cells of the sweat gland. Tissue sections of soft palate and tonsil, two examples of nonkeratinizing epithelium, revealed staining of stratum spinosum and some staining of the basal cell layer as well. Neither salivary gland epithelium nor lymphoid cells were positive. The ciliated epithelium of the trachea exhibited KGFR expression in intermediate and basal cell layers. In striking contrast to the normal pattern of staining in the adjacent epithelium, a squamous cell carcinoma of skin lacked detectable KGFRs. Our present findings suggest that growth factor-Ig fusion proteins may be generally applicable in ligand-mediated histochemical detection and localization of growth factor receptors.
Monitoring Requirements Evolution using Views

This paper describes a research project concentrating on improving requirements management. We started this research by identifying the problems companies face with respect to requirements engineering in general, and requirements management in particular. We learned that monitoring requirements satisfaction is a major problem in practice. Requirements change continuously, making the trace-ability of requirements hard and the monitoring of requirements unreliable. As a solution, we developed a framework (requirements engineering system (RES)) that structures the process of requirements evolution, and a methodology that improves the traceability and monitoring of requirements. This methodology covers most of the processes defined in RES. We will implement the methodology in a tool, called ReqAnalyst. It uses latent semantic index (LSI), an information retrieval technique, to recover the traceability links between the requirements and other work products. This traceability information will be used to generate 'requirements views' that help monitoring the requirements. We will apply the methodology in several case studies
Modular Hyperthermostable Bacterial Endo-β-1,4-Mannanase: Molecular Shape, Flexibility and Temperature-Dependent Conformational Changes

Endo-β-1,4-mannanase from Thermotoga petrophila (TpMan) is a hyperthermostable enzyme that catalyzes the hydrolysis of β-1,4-mannoside linkages in various mannan-containing polysaccharides. A recent study reported that TpMan is composed of a GH5 catalytic domain joined by a linker to a carbohydrate-binding domain. However, at this moment, there is no three-dimensional structure determined for TpMan. Little is known about the conformation of the TpMan as well as the role of the length and flexibility of the linker on the spatial arrangement of the constitutive domains. In this study, we report the first structural characterization of the entire TpMan by small-angle X-ray scattering combined with the three-dimensional structures of the individual domains in order to shed light on the low-resolution model, overall dimensions, and flexibility of this modular enzyme at different temperatures. The results are consistent with a linker with a compact structure and that occupies a small volume with respect to its large number of amino acids. Furthermore, at 20°C the results are consistent with a model where TpMan is a molecule composed of three distinct domains and that presents some level of molecular flexibility in solution. Even though the full enzyme has some degree of molecular flexibility, there might be a preferable conformation, which could be described by the rigid-body modeling procedure. Finally, the results indicate that TpMan undergoes a temperature-driven transition between conformational states without a significant disruption of its secondary structure. Our results suggest that the linker can optimize the geometry between the other two domains with respect to the substrate at high temperatures. These studies should provide a useful basis for future biophysical studies of entire TpMan.
In Advances in Neural Information Processing Systems 12 Learning Factored Representations for Partially Observable Markov Decision Processes

The problem of reinforcement learning in a non-Markov environment is explored using a dynamic Bayesian network, where conditional independence assumptions between random variables are compactly represented by network parameters. The parameters are learned on-line, and approximations are used to perform inference and to compute the optimal value function. The relative effects of inference and value function approximations on the quality of the final policy are investigated, by learning to solve a moderately difficult driving task. The two value function approximations , linear and quadratic, were found to perform similarly, but the quadratic model was more sensitive to initialization. Both performed below the level of human performance on the task. The dynamic Bayesian network performed comparably to a model using a localist hidden state representation, while requiring exponentially fewer parameters.
Federating Traders: An ODP Adventure

In this paper we propose a model of decentralized federation of traders. Each component trader manages its own set of federated traders. A federation contract is used to document the agreement between two federating traders. The importer's portion of the federation contract forms an import contract that states the service types available in the remote trader. The exporter's portion of the federation contract forms the corresponding export contract that states the extent of allowed access of a remote trader to the local trader's database. The contracts also contain mapping functions for requests and results, to be expressed in a canonical form for communication between traders. There are two protocols: one for a user with its trader and another for a trader with another trader in the federation. A user has access only to the protocols of its local trader. We present our model using the ve viewpoints of ODP, and demonstrate the need to recursively apply the ve viewpoints to engineering mechanisms of a system. We learn that there is a need for a third-party security mechanism and a separate type management function in ODP. We also discover that transparency does not imply secrecy. Finally, our experience con rms that while separation and location can be made transparent, autonomy and incremental change cannot be made completely transparent in an Open Distributed Processing environment. Keyword Codes: C.2. 0; C.2. 4
Multi-view face alignment guided by several facial feature points

This paper proposes an improved algorithm for ASM addressing at face alignment with pose variation conquering local obstruction. To providing good initialization of ASM for reliable searching starting-point and faster convergence, an affine transform insensitive initialization algorithm (ATIIA) is employed after several facial feature points are extracted by SDAM searching. Landmarks of ASM are sampled with special strategy to sufficiently describe gray-level information surrounding them. Special searching strategy is also provided for ASM so that problem of local obstruction can be solved. For multi-view face alignment, view-based ASMs are trained respectively for 5 face pose based on CMU-PIE database. The exciting experiment results are shown proving that this method is robust and not susceptible to various factors such as the scale of image, the rotation of head, the local obstruction and so on.
Dietary fat and protein in relation to risk of non-Hodgkin's lymphoma among women.

BACKGROUND Non-Hodgkin's lymphoma occurs more frequently in individuals with suppressed immune status, and some types of dietary fat and protein have been associated with decreased immune responses. In this study, we examined the intake of specific types of dietary fat and protein in relation to the risk of non-Hodgkin's lymphoma. METHODS We documented 199 incident cases of non-Hodgkin's lymphoma in a cohort of 88 410 women, who were enrolled in the Nurses' Health Study and were aged 34-60 years in 1980, during 14 years of follow-up. Relative risks of the disease and 95% confidence intervals (95% CIs) were calculated. All P values are two-sided and were considered to be statistically significant for P<. 05. RESULTS Intake of saturated fat was associated with an increase in risk that was not statistically significant; the multivariate relative risk for the highest versus the lowest quintiles of intake was 1.4 (95% CI = 0.7-3.0; P for trend =.42). Intake of beef, pork, or lamb as a main dish was associated with a statistically significantly increased risk of non-Hodgkin's lymphoma; the multivariate relative risk for consumption of these meats at least once per day as compared with less than once per week was 2.2 (95% CI = 1.1-4.4; P for trend =.002). Higher intake of trans unsaturated fat was also statistically significantly associated with an increased risk of the disease; the multivariate relative risk for the highest versus the lowest quintiles was 2.4 (95% CI = 1.3-4.6; P for trend =.01). Higher intake of red meat cooked by broiling or barbecuing-but not by roasting, pan-frying, or boiling or stewing-was associated with an increase in risk that was not statistically significant. CONCLUSIONS Greater dietary intake of certain meats and fats was associated with a higher risk of non-Hodgkin's lymphoma. These relationships and their potential mechanisms deserve further examination.
The Linguistic Structure of Discourse

In order to provide a principled foundation for the study of discourse, in this paper we propose answers to three basic questions: What are the atomic units of discourse? What kind of structures can be built from the elementary units? How do we interpret the resulting structures semantically? Inferences and the correct interpretation of deixis and anaphors in discourse depend upon both structural and semantic accessibility relations. Structurally, we argue, discourse is context free and accessibility is determined by the coordination and subordination relations specified by the model of discourse presented here. Semantically, accessibility is controlled by relations among a number of modal contexts (interaction, speech event, genre unit, modality, polarity, and point of view) which determine the discourse world relative to which each primitive discourse unit is interpreted. To demonstrate the validity of our approach, the linguistic discourse model developed here is applied to a problem concerning the distribution of a discourse particle in Mocho and to various problems of discourse interpretation.
Effects of Individual Differences on Knowledge and Wisdom of Society: A Social Modeling Approach

Categorically organized knowledge is the main vehicle in high-level cognitive processes. The previous empirical and theoretical studies on categorization paid almost exclusive attention to how individuals learn categorical knowledge. In the real world, however, people acquire knowledge not only through individual learning, but also through interacting with others. In the present study, using computational modeling, we explored how social interactions would produce unique dynamics of knowledge acquisition that cannot be examined by studies on micro level processes. The results of simulation studies showed that when there were several clusters of individuals in a society where individuals held different beliefs about what constitutes ”good” knowledge, then the society as a whole formed Pareto-optimal knowledge. That is, there was no cluster of knowledge that was simultaneously worse in two important aspects of knowledge (i.e., accuracy and simplicity) as compared with those of other clusters in a mature society.
The Effects of Dementia Prevention Program on Cognition, Depression, Self-esteem and Quality of life in the Elderly with Mild Cognitive Disorder

Purpose: This study was conducted to develop and evaluate a dementia prevention intervention program for the elderly with mild cognitive disorder. Methods: The study was nonequivalent control group pretest-posttest design. The subjects of the study were a total of 68 elderly who ranged from 21 to 24 of total scores of K-MMSE, aged over 65, in home. The program consisted of music therapy, humor therapy, art therapy, dancing therapy, recreation, and health education to enhance brain function. The program was applied to the experimental group twice a week, ninety minutes per session for eight weeks. The data were analysed by using chi-square test and t-test. Results: The variables measured in the experimental group and the control group before the intervention were not significantly different in the homogeneity test. The dementia prevention program improved the cognition(t=9.243, p<.001), self-esteem(t=.4.336, p<.001), quality of life(t=8.375, p<.001) and reduced depression(t=-3.913, p<.001). Conclusion: These findings confirmed that the dementia prevention program made a contribution to improving cognitive function, self-esteem, and quality of life and also to reduce depression in the elderly with mild cognition disorder. Therefore, it is recommended that this program could be used in clinical practice as an effective nursing intervention for the elderly with mild cognitive disorder.
A study on the impact of global software development in packaged software release planning

: Today’s globalization of software development has its advantages, but also its drawbacks. Software project managers often lead the production of new software versions and their release on the market. This paper analyses the main challenges faced by software product managers in release planning with regard to the adoption of Global Software Development (GSD) practices for developing packaged software. To achieve this objective, two qualitative techniques are used in this study, namely, Focus Group and Delphi Study. The experiment produced two lists, ranking challenges in software release planning. One list was made considering the adoption of GSD practices and the other did not take into account the adoption of these practices. Results show that there are some, apparently solved, challenges for packaged software release planning like “Project monitoring & control” or “Quality management” that become crucial when facing GSD scenarios, while there are other important challenges in traditional software release planning such as “Requirements prioritisation” and “Stakeholders Management” that apparently do not add extra pressure in GSD environments. In sum, GSD is found to be highly influenced by issues concerning personnel and human resources management.
Cooperation without Reputation: Experimental Evidence from Prisoner's Dilemma Games

Abstract This paper investigates cooperative play in prisoner's dilemma games by designing an experiment to evaluate the ability of two leading theories of observed cooperation: reputation building and altruism. We analyze both one-shot and finitely repeated games to gauge the importance of these theories. We conclude that neither altruism nor reputation building alone can explain our observations. The reputation model is inconsistent with play in both one-shots and finitely repeated games while the model with altruism is unable to explain observed play in the finitely repeated games. Journal of Economic Literature Classification Numbers: C72, C92.
Real-time multi-person tracking with detector assisted structure propagation

Classical tracking-by-detection approaches require a robust object detector that needs to be executed in each frame. However the detector is typically the most computationally expensive component, especially if more than one object class needs to be detected. In this paper we investigate how the usage of the object detector can be reduced by using stereo range data for following detected objects over time. To this end we propose a hybrid tracking framework consisting of a stereo based ICP (Iterative Closest Point) tracker and a high-level multi-hypothesis tracker. Initiated by a detector response, the ICP tracker follows individual pedestrians over time using just the raw depth information. Its output is then fed into the high-level tracker that is responsible for solving long-term data association and occlusion handling. In addition, we propose to constrain the detector to run only on some small regions of interest (ROIs) that are extracted from a 3D depth based occupancy map of the scene. The ROIs are tracked over time and only newly appearing ROIs are evaluated by the detector. We present experiments on real stereo sequences recorded from a moving camera setup in urban scenarios and show that our proposed approach achieves state of the art performance.
Access to intra-arterial therapies for acute ischemic stroke: an analysis of the US population.

BACKGROUND AND PURPOSE Intra-arterial therapies for ischemic stroke offer promise as a means to extend the time window for acute treatment. The purpose of this study was to identify the percentage of the US population with potential access to interventional neuroradiologic expertise within 6 hours of the onset of stroke symptoms. METHODS Hospital locations of interventional neuroradiologists were identified from the 2002 roster of the American Society of Interventional and Therapeutic Neuroradiology. Data for populations in surrounding regions were extracted from US Census 2001 data by zip code. Standard transport speeds for emergency medical services were used in our estimates of the population living within a 5-hour transport time, which was a 6-hour treatment window less a 1-hour door-to-needle time, resulting in a 200-mile radius. A 2-hour transport time, or 3-hour treatment window, reflected a 65-mile radius. RESULTS A total of 385 interventional neuroradiologists were identified, practicing in 45 states. With a 200-mile radius, 99% of the total US population had access to neurointerventional treatment within 6 hours of symptom onset. With a 65-mile radius, 82% of the population had access within 3 hours of symptom onset. Alaska and the Mid-Northwest region covering Idaho, Wyoming, North Dakota, and South Dakota had limited coverage. CONCLUSION Most of the US population has access to interventional neuroradiologic expertise for acute stroke therapy. These data suggest that interventional therapies that extend the time window for treating acute ischemic stroke could have a major effect on public health and merit further research development and investment.
MMASS: an optimized array-based method for assessing CpG island methylation

We describe an optimized microarray method for identifying genome-wide CpG island methylation called microarray-based methylation assessment of single samples (MMASS) which directly compares methylated to unmethylated sequences within a single sample. To improve previous methods we used bioinformatic analysis to predict an optimized combination of methylation-sensitive enzymes that had the highest utility for CpG-island probes and different methods to produce unmethylated representations of test DNA for more sensitive detection of differential methylation by hybridization. Subtraction or methylation-dependent digestion with McrBC was used with optimized (MMASS-v2) or previously described (MMASS-v1, MMASS-sub) methylation-sensitive enzyme combinations and compared with a published McrBC method. Comparison was performed using DNA from the cell line HCT116. We show that the distribution of methylation microarray data is inherently skewed and requires exogenous spiked controls for normalization and that analysis of digestion of methylated and unmethylated control sequences together with linear fit models of replicate data showed superior statistical power for the MMASS-v2 method. Comparison with previous methylation data for HCT116 and validation of CpG islands from PXMP4, SFRP2, DCC, RARB and TSEN2 confirmed the accuracy of MMASS-v2 results. The MMASS-v2 method offers improved sensitivity and statistical power for high-throughput microarray identification of differential methylation.
To Boldly Go : an occam-π Adventure

Future systems will be too complex to design and implement explicitly. Instead, we will have to learn to engineer complex behaviours indirectly: through the discovery and application of local rules of behaviour, applied to simple process components, from which desired behaviours predictably emerge through dynamic interactions between massive numbers of instances. This talk considers such indirect engineering of emergence using a processoriented architecture. Different varieties of behaviour may emerge within a single application, with interactions between them provoking ever-richer patterns – almost social systems. We will illustrate with a study based on Reynolds' boids: emergent behaviours include flocking (of course), directional migration (with waves), fear and panic (of hawks), orbiting (points of interest), feeding frenzy (when in a large enough flock), turbulent flow and maze solving. With this kind of engineering, a new problem shows up: the suppression of the emergence of undesired behaviours. The panic reaction within a flock to the sudden appearance of a hawk is a case in point. With our present rules, the flock loses cohesion and scatters too quickly, making individuals more vulnerable. What are the rules that will make the flock turn almost-as-one and maintain most of its cohesion? There are only the boids to which these rules may apply (there being, of course, no design or programming entity corresponding to a flock). More importantly, how do we set about finding such rules in the first place? Something else that can emerge from emergent engineering are unexpected relationships between quite different domains of study (e.g. bird migration, gas dynamics and maze solving). These relationships may not have been noticed before, as the low-level agents generating the emergent behaviours appear quite unrelated. There is also the potential to discover completely new domains of interest from such studies. Our architecture and models are written in occam-π, whose processes are sufficiently lightweight to enable a sufficiently large mass to run and be interacted with for real-time experiments on emergent behaviour. This work is in collaboration with the Software Engineering Institute (at CMU) and is part of the CoSMoS project (at the Universities of Kent and York in the UK).