Miracle-dz/UniFAR-FTUs huggingface dataset:
Addressing diabetes mellitus as part of the strategy for ending TB

As we enter the new era of Sustainable Development Goals, the international community has committed to ending the TB epidemic by 2030 through implementation of an ambitious strategy to reduce TB-incidence and TB-related mortality and avoiding catastrophic costs for TB-affected families. Diabetes mellitus (DM) triples the risk of TB and increases the probability of adverse TB treatment outcomes such as failure, death and recurrent TB. The rapidly escalating global epidemic of DM means that DM needs to be addressed if TB-related milestones and targets are to be achieved. WHO and the International Union Against Tuberculosis and Lung Disease's Collaborative Framework for Care and Control of Tuberculosis and Diabetes, launched in 2011, provides a template to guide policy makers and implementers to combat the epidemics of both diseases. However, more evidence is required to answer important questions about bi-directional screening, optimal ways of delivering treatment, integration of DM and TB services, and infection control. This should in turn contribute to better and earlier TB case detection, and improved TB treatment outcomes and prevention. DM and TB collaborative care can also help guide the development of a more effective and integrated public health approach for managing non-communicable diseases.
The Linked Sensor Middleware — Connecting the real world and the Semantic Web

Sensing devices are becoming the source of a large portion of the Web data. To facilitate the integration of sensed data with data from other sources, both sensor stream sources and data are being enriched with semantic descriptions, creating Linked Stream Data. Despite its enormous potential, little has been done to explore Linked Stream Data. One of the main characteristics of such data is its “live” nature, which prohibits existing Linked Data technologies to be applied directly. Moreover, there is currently a lack of tools to facilitate publishing Linked Stream Data and making it available to other applications. To address these issues we have developed the Linked Stream Middleware (LSM), a platform that brings together the live real world sensed data and the Semantic Web. A LSM deployment is available at http://lsm.deri. ie/. It provides many functionalities such as: i) wrappers for real time data collection and publishing; ii) a web interface for data annotation and visualisation; and iii) a SPARQL endpoint for querying unified Linked Stream Data and Linked Data. In this paper we describe the system architecture behind LSM, provide details how Linked Stream Data is generated, and demonstrate the benefits of the platform by showcasing its interface.
Inner Speech during Silent Reading Reflects the Reader's Regional Accent

While reading silently, we often have the subjective experience of inner speech. However, there is currently little evidence regarding whether this inner voice resembles our own voice while we are speaking out loud. To investigate this issue, we compared reading behaviour of Northern and Southern English participants who have differing pronunciations for words like ‘glass’, in which the vowel duration is short in a Northern accent and long in a Southern accent. Participants' eye movements were monitored while they silently read limericks in which the end words of the first two lines (e.g., glass/class) would be pronounced differently by Northern and Southern participants. The final word of the limerick (e.g., mass/sparse) then either did or did not rhyme, depending on the reader's accent. Results showed disruption to eye movement behaviour when the final word did not rhyme, determined by the reader's accent, suggesting that inner speech resembles our own voice.
LONG-TERM RESULTS OF PHOTODYNAMIC THERAPY FOR SUBFOVEAL CHOROIDAL NEOVASCULARIZATION WITH PATHOLOGIC MYOPIA

Purpose: The purpose of our study was to determine the long-term visual and anatomic outcomes of photodynamic therapy in patients affected with choroidal neovascularization secondary to pathologic myopia. Methods: We retrospectively evaluated 43 eyes of 43 patients. Patients with pathologic myopia were included if they had received photodynamic therapy for choroidal neovascularization involving the center of the avascular foveal zone and if they had a follow-up of at least 5 years. We included only the cases for which both of the examiners of the FAs were in agreement concerning the subfoveal localization of choroidal neovascularization. Patients treated with other therapies such as anti–vascular endothelial growth factor or steroids in the study eye were excluded. Visual acuity was measured using Early Treatment Diabetic Retinopathy Study charts. Anatomic outcome measures were the lesion size expressed as the greatest linear diameter and the chorioretinal atrophy that developed around the regressed choroidal neovascularization. Results: Average visual acuity was stable during the first year, tended to be worse at 2 years, whereas it was significantly worse at 3 years and afterward, reaching a loss of nearly 3 lines at 7 years. We found that neither the number of photodynamic therapy treatments nor baseline photodynamic therapy spot size influenced change of visual acuity during follow-up. Chorioretinal atrophy around choroidal neovascularization was detected in 83% of patients at the 5-year follow-up visit. Conclusion: The results showed that visual acuity decreased significantly after a long follow-up period mainly because of the development of chorioretinal atrophy.
Range bagging: a new method for ecological niche modelling from presence-only data

The ecological niche is the set of environments in which a population of a species can persist without introduction of individuals from other locations. A good mathematical or computational representation of the niche is a prerequisite to addressing many questions in ecology, biogeography, evolutionary biology and conservation. A particularly challenging question for ecological niche modelling is the problem of presence-only modelling. That is, can an ecological niche be identified from records drawn only from the set of niche environments without records from non-niche environments for comparison? Here, I introduce a new method for ecological niche modelling from presence-only data called range bagging. Range bagging draws on the concept of a species' environmental range, but was inspired by the empirical performance of ensemble learning algorithms in other areas of ecological research. This paper extends the concept of environmental range to multiple dimensions and shows that range bagging is computationally feasible even when the number of environmental dimensions is large. The target of the range bagging base learner is an environmental tolerance of the species in a projection of its niche and is therefore an ecologically interpretable property of a species' biological requirements. The computational complexity of range bagging is linear in the number of examples, which compares favourably with the main alternative, Qhull. In conclusion, range bagging appears to be a reasonable choice for niche modelling in applications in which a presence-only method is desired and may provide a solution to problems in other disciplines where one-class classification is required, such as outlier detection and concept learning.
Cyclooxygenase enzyme expression and E series prostaglandin receptor signalling are enhanced in heavy menstruation.

BACKGROUND Although the mechanisms underlying the causes of heavy menstrual blood loss (MBL) remain to be elucidated, prostaglandins have been previously implicated. This study was initiated to elucidate a pattern of expression of the various components of the cyclooxygenase (COX)-prostaglandin signalling pathways present in the endometrium of women with normal and heavy MBLs. METHODS Endometrial biopsies were collected at different stages of the menstrual cycle from women who underwent measurement of MBL. Tissue was divided for either examination of gene expression by quantitative RT-PCR analysis or in vitro culture experimentation. RESULTS Analysis of gene expression demonstrated a significant elevation in expression of COX-1 and COX-2 mRNA in endometrium obtained from women with heavy MBL when compared with endometrium obtained from women with normal MBL. Tissue culture with PGE(2) stimulation caused a significantly elevated production of cyclic AMP (cAMP) by endometrium of women with heavy MBL when compared with normal MBL. Expression of phosphodiesterase 4B, an enzyme involved in cAMP breakdown, was reduced in these same endometrial samples obtained from women with heavy MBL. CONCLUSIONS These data identify the E series prostaglandin receptors and their signalling pathways as potential therapeutic targets in the treatment of heavy menstruation.
Wireless Sensor Networks for Networked Manufacturing Systems

With the continuing trend towards globalization and focusing on high value with low volume, the manufacturing system architecture is evolving from traditional centralised model to the distributed model and to the recent networked model. In the modern manufacturing environment, the manufacturing systems are in networked framework via a variety of networking communication systems integrating the heterogeneous collections of manufacturing equipment, devices and real-time information. Such networked manufacturing system monitors and controls with the clear objective of maximizing the Quality of Service (QoS) provided by the prevailing manufacturing resources and to achieve near zero down time operations. For such networked framework for manufacturing and execution, the key issue is how to sustain networked manufacturing operations’ capability in providing robust, zerobreakdown performance with various uncertainties (e.g., machine breakdown, device malfunction, sensor failure, communication delay, and data loss). The challenge therefore lies in the identification, characterization and generalization, and development of technologies to minimize their adverse impact on system performance and serviceability. Hence from the aspect of system availability, substantial research efforts have devoted to the prognosis of equipment condition. The objective is to prolong the useful life of critical manufacturing elements by estimating the life span of components, devices and equipment. This kind of technology is widely utilized for maintenance operations with the help of the advancement of sensor and sensor fusion techniques. From the perspective of manufacturing control, the machine health information is able to reflect the prevailing health status of the equipment and influence the control decision for networked manufacturing systems. The supervisory controllers are able to take proactive measures to ensure the continual operation by executing the fall back strategies. However from the aspect of system performance, considering the networked manufacturing systems that are connected through heterogeneous networks, hence, the decision making process is distributed to the individual control agents based on the common global goal. The collaborative decision ensures to make best choice from the consideration for all possible options. Various network models can be applied for such networked manufacturing system, particularly the wireless communication for sensory information fusion. Though such 7
Pythia: A System for Online Topic Discovery of Social Media Posts

Social media constitute nowadays one of the most common communication mediums. Millions of users exploit them daily to share information with their community in the network via messages, referred as posts. The massive volume of information shared is extremely diverse and covers a vast spectrum of topics and interests. Automatically identifying the topics of the posts is of particular interest as this can assist in a variety of applications, such as event detection, trends discovery, expert finding etc. However, designing an automated system that requires no human agent participation to identify the topics covered in posts published in Online Social Networks (OSNs) presents manifold challenges. First, posts are unstructured and commonly short, limited to just a few characters. This prevents existing classification schemes to be directly applied in such cases, due to sparseness of the text. Second, new information emerges constantly, hence building a learning corpus from past posts may fail to capture the ever evolving information emerging in OSNs. To overcome the aforementioned limitations we have designed Pythia, an automated system for short text classification that exploits the Wikipedia structure and articles to identify the topics of the posts. The topic discovery is performed in two phases. In the first step, the system exploits Wikipedia categories and articles of the corresponding categories to build the training corpus for the suppervised learning. In the second step, the text of a given post is augmented using a text enrichment mechanism that extends the post with relevant Wikipedia articles. After the initial steps are performed, we deploy k-NN classifier to determine the topic(s) covered in the original post.
Multi-fault Diagnosis in Dynamic Systems

In this paper, we address the problem of diagnosing multiple faults in dynamically changing systems. Currently used popular techniques such as codebook and active probing suffer from limitations imposed by their ”static”, non-temporal nature, and single-fault assumptions. We propose a very simple, linear-time multifault scheme, capable of tracking system changes and diagnosing multiple faults much more accurately than previously used approaches. We provide empirical results demonstrating the advantages of our approach and analyze the effect of test set quality on the diagnostic accuracy.
Multiagent Coordination Using a Distributed Combinatorial Auction

C AUCTIONS are a great way to represent and solve distributed allocation problems. Unfortunately, most of the winner determination solutions that exists are centralized. They require all agents to send their bids to a centralized auctioneer who then determines the winners. The PAUSE auction, in contrast, is an increasing-price combinatorial auction in which the problem of winner determination is naturally distributed amongst the bidders. We present PAUSEBID, a bidding algorithm for agents in a PAUSE auction which always returns the bid that maximizes the bidder’s utility. Our test results show that a system where all agents use PAUSEBID finds the revenue-maximizing solution at least 95% of the time. Run time, as expected since this is an NP-complete problem, remains exponential on the number of items. 1. Bidding in the PAUSE Auction A PAUSE AUCTION for m items has m stages. Stage 1 consists of having simultaneous ascending price open-cry auctions for each individual item. During this stage the bidders can only place individual bids on items. At the end of this stage we know what is the highest bid for each individual item and who placed that bid. In each successive stage k = 2,3, . ,m we hold an ascending price auction where the bidders must submit sets of bids that cover all goods but each one of the bids must be for k goods or less. The bidders are allowed to use bids that other agents have placed in previous rounds when placing their bid, thus allowing them to find better solutions. Also, any new bidset has to have a sum of bid prices which is bigger than the currently winning bidset. That is, revenue must increase monotonically. Formally, let each bid b be composed of bitems which is the set of items the bid is over, bvalue the value or price of the bid, and bagent the agent that placed the bid. The agents maintain a set B of the current best bids, one for each set of items of size≤ k. At any point in the auction, after the first round, there will also be a set W ⊆ B of currently winning bids. This is the set of bids that currently maximizes the revenue, where the revenue of W is given by r(W ) = ∑ b∈W bvalue. (1) Agent i’s value function is given by vi : S→R where S is a subset of the items. Given an agent’s value function and the current set of winning bids W we can calculate the agent’s utility from W as ui(W ) = ∑ b∈W |bagent=i vi(b)−b. (2) Given that W is the current set of winning bids, agent i must find a g∗ such that r(g∗)≥ r(W )+ e and g∗ = argmax g⊆2B ui(g), (3) where each g is a set of bids all taken from B and g covers all items. The goal of the PAUSEBID algorithm is to find this g∗.
Bitter Taste Receptor Polymorphisms and Human Aging

Several studies have shown that genetic factors account for 25% of the variation in human life span. On the basis of published molecular, genetic and epidemiological data, we hypothesized that genetic polymorphisms of taste receptors, which modulate food preferences but are also expressed in a number of organs and regulate food absorption processing and metabolism, could modulate the aging process. Using a tagging approach, we investigated the possible associations between longevity and the common genetic variation at the three bitter taste receptor gene clusters on chromosomes 5, 7 and 12 in a population of 941 individuals ranging in age from 20 to 106 years from the South of Italy. We found that one polymorphism, rs978739, situated 212 bp upstream of the TAS2R16 gene, shows a statistically significant association (p = 0.001) with longevity. In particular, the frequency of A/A homozygotes increases gradually from 35% in subjects aged 20 to 70 up to 55% in centenarians. These data provide suggestive evidence on the possible correlation between human longevity and taste genetics.
ΣΔ Modulator with op-amp gain compensation for nanometer CMOS technologies

A gain compensated op-amp for discrete-time ΣΔ modulators is described. The method greatly reduces the integrator's phase error caused by low DC gain on amplifiers. The scheme uses an additional unity gain buffer to correct the error caused by gains as low as 20 dB, thus enabling high-performance ΣΔ modulators in nanometer-scale CMOS technologies. Design strategies for op-amps and buffer designed with a 65 nm technology to be used with the method are considered. The effectiveness of the approach is verified with a second-order ΣΔ modulator simulated at behavioral level with MATLAB and Verilog-A descriptions. The low sensitivity to buffer gain's variations is also verified.
Investigation of spatial density of public and business objects in the largest city with help of geoinformation technologies

The article reveals the study of spatial distribution of the density of public and business objects with the use of geoinformation technologies. The source of the data was data from the open geoinformation project OpenStreetMap. Earlier, we showed that for the radial component of the density of public and business facilities. This paper is a continuation of the previous one. The angular distribution of density of public and business objects is studied by example of the largest city - Ekaterinburg. Spatial density has "tails" that characterize the predominant directions of the city development. At the same time, the average spatial configuration for the average density distribution shows the radial-ring structure for urban planning. The obtained results are interpreted within the framework of the "frame-fabric".
Long‐Term Trend of the Tropical Pacific Trade Winds Under Global Warming and Its Causes

The recent intensification of trade winds over the tropical Pacific is the strongest ever observed in the past hundred years. This strengthening trend is of great interest in recent research, but the causes are still unclear. Using two relatively long‐term surface wind data sets, the present research shows that there is an overall strengthening trend of the trades in the western equatorial Pacific and an overall weakening trend in the eastern equatorial Pacific. This long‐term trend pattern can be primarily attributed to the cold tongue mode (CTM) rather than to the impact of El Niño–Southern Oscillation (ENSO), El Niño Modoki, or Interdecadal Pacific Oscillation (IPO). The CTM, the second empirical orthogonal function mode of the sea surface temperature anomalies (SSTA) in the tropical Pacific, represents a strong long‐term trend of tropical Pacific background state under global warming. According to the Gill‐Matsuno theory, the easterly winds over the western equatorial Pacific are induced by the equatorial Pacific cooling and warming SSTA associated with the CTM, while the westerly winds over the eastern equatorial Pacific is primarily due to the eastern equatorial Pacific cooling SSTA associated with the CTM. Ultimately, an alternative explanation of past and future changes of the trades is expected to lead to improved understanding of the global climatic impacts of the enhanced trades in tropical Pacific under global warming.
GRIDS - AN ARCHITECTURE FOR MANAGING VERY LARGE ORTHOIMAGE MOSAICS IN A DATABASE FRAMEWORK

This paper presents the investigation and implementation of concepts for the efficient management of very large raster and orthoimage mosaics in a database framework. The paper first identifies and discusses the key requirements of a data management solution for orthoimage mosaics. These requirements include efficient support for spatial partitioning, spatial partition indexing and access, multi-resolution support, georeferencing, storage management and mass storage support. The paper then presents the architecture of the prototype spatial raster management system GrIdS. GrIdS is based on a 'spatial raster middleware' approach which allows typical GIS database engines, e.g. Oracle, to be extended with a spatial raster management capability. Key features of the architecture include a tile-based spatial partitioning solution and a spatial access and query concept using a modified Morton code-based indexing mechanism. The presented multi-resolution concept for raster mosaics represents a novel approach. It uses a virtual resolution pyramid of constant-dimension tiles, combining the resolution access with the spatial access through a single spatial coding scheme. The paper also presents a series of tests and results. These results demonstrate that orthoimages and very large orthoimage mosaics can efficiently be managed with state-of-art relational DBMS technology. The paper concludes with an outlook on important DBMS trends as well as on ongoing and future investigations.
Using Coarse State Space Abstractions to Detect Mutex Pairs

A mutex pair in a state space is a pair of assignments of values to state variables that does not occur in any reachable state. Detecting mutex pairs is a problem that has been addressed frequently in the planning literature. In this paper, we present the Coarse Abstraction (CA) method, a new efficient method for detecting mutex pairs in state spaces represented with multi-valued variables. CA detects mutex pairs based on exhaustive search in a collection of very small abstract state spaces. While in general CA may miss some mutex pairs, we provide a formal guarantee that CA finds all mutex pairs under a simple and quite natural condition. Using this formal guarantee, we prove that these properties hold for a range of common benchmark domains. We also show that CA can find all mutex pairs even if the formal guarantee is not satisfied. Finally, we show that CA’s effectiveness depends on how the domain is represented, and that it can fail to find mutex pairs in some domains and representations.
Stochastic stability of an attitude estimation algorithm on SO(3)

We consider the impact of noise on a modification of a recently developed attitude estimation algorithm which is formulated directly as a rotation matrix tracking problem on SO(3). By means of a stochastic Lyapunov analysis we derive several results. Firstly in the presence of noise the estimation algorithm no longer converges. Rather it fluctuates in the vicinity of the true rotation matrix and angular velocity bias vector. We compute the magnitude of these fluctuations as a function of noise variance and show how they influence the choice of algorithm gains.