Miracle-dz/UniFAR-FTUs huggingface dataset:
Supervised learning in the brain

Experience shapes the functional organization of the brain, optimizing and customizing its properties for the individual and his or her environment. One way that experience shapes the constituent networks ofthe brain is through supervised learning. In supervised learning, information from one network of neurons acts as an instructive signal to influence the pattern of connectivity in another network. As a result, the instructed network learns to process information so that a particular goal or transformation specified by the instructive signal is achieved. In so doing, supervised learning establishes patterns of connectivity efficiently and with a precision that does not need to be and, often, cannot be encoded in the genome. Supervised learning contributes to the development and maintenance of a variety of brain functions. For example, sensorimotor networks that control goal-directed movements are calibrated by sensory feedback indicating the accuracy with which the movements are made. In a specific example that will be discussed at some length, a visual instructive signal, indicating the slip of images across the retinae, is used to calibrate the transformation of vestibular sensory information (indicating rotation of the head) into precise, compensatory movements of the eyes that stabilize the images on the retinae (Miles and Eighmy, 1980). Supervised learning can also control the representation of information in sensory networks. For example, in the development of binocular neurons in the optic tectum of the frog Xenopus, visually driven activity from the contralateral eye specifies the topography of the visual map originating from the ipsilateral eye (Gaze et al., 1970; Udin, 1985). In this example, which also will be discussed in detail, the activity from the contralateral eye provides an instructive signal that assures the mutual alignment of leftand right-eye receptive fields. It is likely that supervised learning also contributes to the establishment of networks that support certain cognitive skills, such as pattern recognition and language acquisition, although there is, as yet, no experimental confirmation of this proposition. This article discusses supervised learning as it might be implemented in the brain. Different kinds of instructive signals,
Weighted localization in Vehicular Ad Hoc Networks using vehicle-to-vehicle communication

Vehicular Ad Hoc Networks (VANETs) have attracted the interest of many researchers all over the world. With advances in technologies in wireless networks, vehicles will be able to communicate with each other and roadside units (RSU), to exchange road and traffic information. VANET and many other applications demand a real-time, accurate position of a vehicle; highlighting the importance of accurate localization. A number of methods and protocols have been proposed to fulfill this requirement, However, they have not attained high location accuracy required for VANET safety applications. We propose two new localization methods that assist vehicles in estimating their positions: 1) weighted localization (WL) using signal to interference-noise ratio (SINR) obtained from the exchange messages, and 2) weighted localization using SINR and distance between the neighboring vehicles (WLD). Our methods expand the concept of centroid localization (CL) by assigning a weight to each of the neighboring vehicles' coordinates, based on SINR values and the distance. We develop a simulation program to evaluate our methods against CL and relative span weighted localization (RWL). Our simulation results show that WLD demonstrates a better performance with less average location errors than CL and RWL in varying of densities.
Building Trust with Corporate Blogs

The personal relationships that companies once had with customers degenerated into the cold automaticity of datagathering with the widespread adoption of management information systems. By restoring a human face to a company’s self-presentation, blogging has been heralded as a paradigm shift in the way companies interact with customers. This study tests a model relating the content of an author's blog posts to readers' responses. It suggests that companies can use blogging to complement customer relationship management processes to the extent their customers exhibit an organic desire to commune by combining provocative informational content with expressions of benevolent intent. Such consumers respond well to these overtures, showing evidence of increased subject-matter involvement, liking and trust. The study also proposes a way to measure diversity of thought in reader comments to guard against being unduly swayed by a vocal minority.
Detecting and Ranking Conceptual Links between Texts Using a Knowledge Base

Recent research has explored the use of Knowledge Bases (KBs) to represent documents as subgraphs of a KB concept graph and define metrics to characterize semantic relatedness of documents in terms of properties of the document concept graphs. However, none of the studies so far have examined to what degree such metrics capture a user-perceived relatedness of documents. Considering the users' explanations of how pairs of documents are related, the aim is to identify concepts in a KB graph that express the same notion of document relatedness. Our algorithm generates paths through the KB graph that originate from the terms in two documents. KB concepts where these paths intersect capture the semantic relatedness of the two starting terms and therefore the two documents. We consider how such intersecting concepts relate to the concepts in the users' explanations. The higher the users' concepts appear in the ranked list of intersecting concepts, the better the method in capturing the users' notion of document relatedness. Our experiments show that our approach outperforms a simpler graph method that uses properties of the concept nodes alone.
Exploiting Quasi-reversible Structures in Markovian Process Algebra Models

Efficient product form solution is one of the major attractions of queueing networks for performance modelling purposes. These models rely on a form of interaction between nodes in a network which allows them to be solved in isolation, since they behave as if independent up to normalisation. Markovian process algebras (MPA) extend classical process algebras with information about the duration of actions but retain their compositional structure: a system is modelled as an interaction of components. The advantages of this compositional structure for model construction and model simplification have already been demonstrated. In this paper we exploit results from queueing networks to identify a restricted form of interaction between suitable MPA components which leads to a product form solution. Each component of the model may be solved separately and the compositional structure of an MPA consequently facilitates efficient solution for successively more complex models. This work uses the notion of quasi-reversibility in a Markov process setting to define the type of interaction between MPA components. This leads to a substantial class of MPA definitions that have product-form solutions which is more general than the usual queueing network-based class of Markov processes.
Human Motion Capture System Based on Distributed Wearable Sensing Technology

With the development of human-computer interaction technology, the multi-modal, natural interaction will become the primary way of interaction between human and computer. A supporting technology is that the computer must understand and capture the behavior characteristic of human, thus motion capture is proposed. Through motion capture technology, the computer can understand human action, and the user can send instructions and convey information to computer through the body, range, gestures and expressions. Therefore, the motion capture is one of the key technologies of new generation human-computer interaction. The current study of motion capture based on MEMS sensor is mainly for animation and film production, and the price is always very high. With sensor integration technology improve and sensor prices become low, there are some new system design needs. Based on pre-existing motion capture system, this paper tries to construct an inexpensive human motion capture system prototype using flexible architecture and distributed computing technology.
Cooperative Roles of SDF-1α and EGF Gradients on Tumor Cell Migration Revealed by a Robust 3D Microfluidic Model

Chemokine-mediated directed tumor cell migration within a three dimensional (3D) matrix, or chemoinvasion, is an important early step in cancer metastasis. Despite its clinical importance, it is largely unknown how cytokine and growth factor gradients within the tumor microenvironment regulate chemoinvasion. We studied tumor cell chemoinvasion in well-defined and stable chemical gradients using a robust 3D microfluidic model. We used CXCL12 (also known as SDF-1α) and epidermal growth factor (EGF), two well-known extracellular signaling molecules that co-exist in the tumor microenvironment (e.g. lymph nodes or intravasation sites), and a malignant breast tumor cell line, MDA-MB-231, embedded in type I collagen. When subjected to SDF-1α gradients alone, MDA-MB-231 cells migrated up the gradient, and the measured chemosensitivity (defined as the average cell velocity along the direction of the gradient) followed the ligand – receptor (SDF-1α – CXCR4) binding kinetics. On the other hand, when subjected to EGF gradients alone, tumor cells increased their overall motility, but without statistically significant chemotactic (directed) migration, in contrast to previous reports using 2D chemotaxis assays. Interestingly, we found that the chemoinvasive behavior to SDF-1α gradients was abrogated or even reversed in the presence of uniform concentrations of EGF; however, the presence of SDF-1α and EGF together modulated tumor cell motility cooperatively. These findings demonstrate the capabilities of our microfluidic model in re-creating complex microenvironments for cells, and the importance of cooperative roles of multiple cytokine and growth factor gradients in regulating cell migration in 3D environments.
General nucleic acid sequence design using implicit enumeration

The design of DNA and RNA sequences is an important area of research in fields such as gene microarrays, gene chips, medical diagnostic, and biomolecular computing. These nucleic acid molecules must satisfy several combinatorial, thermodynamic and secondary structure constraints, which aim to avoid undesired hybridizations and make the molecular experiment more reliable. In this paper, we formulate the DNA sequence design as a multiobjective optimization problem and solving it using implicit enumeration search approach. To heuristically search for good strand sets, our algorithm considers groups of solutions together. If any partial solution violates any constraint, all completion of this partial solution should be excluded from further consideration which accelerate the convergent of our algorithm. Finally, the performance of our algorithm is compared with other sequence design methods, and the results show that the implicit enumeration algorithm outperforms in DNA sequences quality, quantity and efficiency.
Standardisation of the adaptive multi-rate codec

European Telecommunication Standards Institute (ETSI) initiated a standardisation program in October 1997 to develop an Adaptive Multi-Rate (AMR) codec for GSM. After two competitive selection phases, ETSI chose in October 1998 a codec developed in collaboration between Ericsson, Nokia, and Siemens. The codec standard was finalised, characterised, and formally approved in ETSI during early 1999. The AMR codec provides the next step of speech quality improvement in GSM after the introduction of Enhanced Full-Rate (EFR) codec in 1996. AMR offers substantial improvement in error robustness by adapting speech and channel coding depending on channel conditions. By switching to operate in the GSM half-rate channel during good channel conditions, AMR provides also channel capacity gain over the EFR codec. In April 1999, the Third Generation Partnership Project (3GPP) adopted the AMR codec as the mandatory speech codec for the third generation WCDMA system.
Smoking at Diagnosis Is an Independent Prognostic Factor for Cancer-Specific Survival in Head and Neck Cancer: Findings from a Large, Population-Based Study

Background: Some studies suggest smoking may result in poorer clinical outcomes in head and neck cancer, but the evidence is heterogeneous and some of it is poor quality. In a large, population-based, study we investigated: (i) whether smoking at diagnosis is an independent prognostic factor for cancer-specific survival in head and neck cancer; and (ii) whether the association varies by site and treatment. Methods: Head and neck cancers (ICD10 C01-C14, and C30–32) diagnosed from 1994 to 2009 were abstracted from the National Cancer Registry Ireland, and classified by smoking status at diagnosis. Follow-up was for 5 years or until December 31, 2010. Multivariate Cox proportional hazards models were used to compare cancer-specific death rates in current, ex-, and never smokers. Subgroup analyses by site and treatment were conducted. Results: In total, 5,652 head and neck cancers were included. At diagnosis, 24% were never smokers, 20% ex-smokers, and 56% current smokers. Compared with never smokers, current smokers had a significantly raised death rate from cancer [multivariate HR, 1.36; 95% confidence interval (CI), 1.21–1.53]. The association was similar after restriction to squamous cell tumors. A significantly increased cancer-related death rate was seen for current smokers with oral cavity, pharyngeal, and laryngeal cancers. The association was stronger in surgically treated patients [HR, 1.49; 95% CI, 1.25–1.79; P(interaction) = 0.01]. Neither radiotherapy nor chemotherapy modified the effect of smoking. Conclusions: Patients with head and neck cancer who smoke at diagnosis have a significantly increased cancer death rate. Impact: Greater efforts are needed to encourage and support smoking cessation in those at risk of, and diagnosed with, head and neck cancer. Cancer Epidemiol Biomarkers Prev; 23(11); 2579–90. ©2014 AACR.
Cytokine and Leukocyte Profiling Reveal Pro-Inflammatory and Autoimmune Features in Frontotemporal Dementia Patients

The growing link between systemic environment and brain function opens the possibility that cellular communication and composition in blood are correlated with brain health. We tested this concept in frontotemporal dementia with novel, unbiased tools that measure hundreds of soluble signaling proteins or characterize the vast immune cell repertoire in blood. With these tools we discovered complementary abnormalities indicative of abnormal T cell populations and autoimmunity in frontotemporal dementia.
An Adaptive Block Pinning Cache for Reducing Network Traffic in Multi-core Architectures

With advent of new technologies there is exponential increase in multi-core processor (CMP) cache sizes accompanied by growing on-chip wire delays make it difficult to implement traditional caches with single, uniform access latency. Non-Uniform Cache Architecture (NUCA) designs have been proposed to address this issue. A NUCA partitions the complete cache memory into smaller multiple banks and allows banks near the processor cores to have lower access latencies than those further away, thus reducing the effects of the cache's internal wire delays. Traditionally, NUCA organizations have been classified as static (S-NUCA) and dynamic (D- NUCA). While in S-NUCA a data block is mapped to a unique bank in the NUCA cache, D-NUCA allows a data block to be mapped in multiple banks. In D-NUCA designs a data blocks can migrate towards the processor core that access them most frequently. This migration of data blocks will increase network traffic. The short life time of data blocks and low spatial locality in many applications results in eviction of block with few unused words. This effectively increases miss rate, and waste on chip network bandwidth. Unused word transfers also wastes a large fraction of on chip energy consumption.In this paper, we present an efficient and implementable cache design that eliminate unnecessary coherence traffic and match data movements to an applications spatial locality. It also presents one way to scale on-chip coherence with less costeffective techniques such as shared caches augmented to track cached copies, explicit eviction notification and hierarchal design. Based on our scalability analysis of this cache design we predict that this design consistently reduce miss rate and improve the fraction of data transmitted that is actually utilized by the application.
Seasonality Pattern of Suicides in the US – a Comparative Analysis of a Twitter Based Bad-mood Index and Committed Suicides

Is it possible that a general negative social climate exists, which, on the one hand, manifests itself in the number of suicides committed, and on the other hand, appears in the content of tweets posted on social media? In this paper, we are attempting to identify the seasonal and weekly patterns of suicide-related tweets and compare them with similar data that shows the ratios of committed suicides in the US. For this work we used the data stream freely provided by the online social networking site Twitter to collect geo-located tweets in the US. In order to calculate the negative mood Twitter–index three terms (words) were used related to suicide (suicide) and bad mood (depression, depressed). The raw daily occurrences of these three words were summarised and then divided by the number of all geo-located daily tweets in the US collected in the framework of the project. The weekly fluctuation of the temporal distribution of suicides and the ratio of bad mood messages on Twitter fit together well. Tweets show a deterioration of mood on Sundays more intensely; this tendency is more moderate in suicide data. Monthly data, however, are much more challenging to interpret, since the fluctuations show a completely opposite tendency than we expected. We present two possible explanation for this unexpected result.
The effect of visual metaphor on advertising response : an integrative framework

This thesis contributes toward the better understanding of the use and effect of visual metaphor in print advertising through an integrative framework. Two overall research questions are answered in this context. Firstly, why is visual metaphor in advertising such an important phenomenon that is worth further research? Secondly, how does visual metaphor engage the consumer and elicits favorable responses to different print advertisements? Two studies were conducted to answer these questions. Study one, a content analysis on 320 print advertisements answered the first overall research question. This study provided a comprehensive assessment of the use of visual metaphor in print advertising. Results showed that visual metaphor is strongly present in print advertising and that this presence shows an increasing trend over time. Study two answered the second overall research question through two experiments. The first experiment compared the effect of different types of visual metaphor on different consumer responses. Results from this experiment showed that replacement metaphor had the most positive effect on effectiveness of the ad. Furthermore, replacement metaphor together with fusion metaphor had the most positive effect on attitude toward the brand and purchase intention. Verbo-pictorial metaphor on the other hand scored the lowest with regards to its effect on the three aforementioned responses. The effect of replacement metaphor on effectiveness of the ad, attitude toward the brand and purchase intention was positively mediated through elaboration and subjective ad comprehension. Objective ad comprehension also positively mediated the effect of replacement metaphor but only on effectiveness of the ad and purchase intention. The same results applied to verbo-pictorial metaphor. However, the mediation effects in this case were negative. Findings, also uncovered that ads that compare two metaphorical objects which are conceptually similar particularly in terms of their functional characteristics are better comprehended. Therefore, a specific visual structure may vary in its effect and hence effectiveness depending on the nature and character of this conceptual similarity as perceived by consumers. The second experiment tested the moderating effect of ad viewing time on consumer response to visual metaphor in advertising. Results, however, did not support the hypothesis related to this moderating effect. Finally, comparing the content analysis and experimental findings provides valuable insights for advertising practitioners. Practitioners can better frame their advertisements and make more effective use of the different types of visual metaphor for this purpose. Therefore, this thesis has also important practical implications.
DOPAMINE - A tool for visualizing clinical properties of generic drugs

Visualization tools are becoming more important as ontologies increase in size and complexity. One example of a large ontology is the Drug Ontology developed at the Medical Informatics Group using GALEN classification techniques. It will provide a reference terminology for PRODIGY; a project providing computerized medicine prescribing guidelines for primary healthcare in the UK. While developing the Drug Ontology we have needed a customized visualization tool for authoring and checking ontology entries. The software tool (Drug Ontology Production And MaIntenance eNvironmEnt or DOPAMINE) provides a tabular summary of sets of ontology entries. DOPAMINE has improved the consistency and speed of authoring entries, and provided a means of highlighting, previously hard to detect, authoring errors. Although specific to the drug ontology, the techniques used could be generalized for other ontologies.
Research on quay crane scheduling problem by hybrid genetic algorithm

With the development of the global business and logisticspsila a container terminal (CT) system becomes more and more busy. Therefore, the available resources in the sea port get scarcer than before. In order to increase the operating efficiency of CT system, the resources planning problem has become a critical issue in the fields of operations research and logistics. In this paper, we introduce the berth allocation planning problem and formulate a mathematical model considered each berth for container ship with different number of quay cranes (QCs). In order to solve this quay crane scheduling in berth allocation planning problem, we also propose a hybrid genetic algorithm (HGA) approach with the priority-based encoding method. To demonstrate the effectiveness of proposed HGA approach, numerical experiment is carried out, and the best solution to the problem is obtained.