Miracle-dz/UniFAR-FTUs huggingface dataset:
Pulmonary hypertension associated with sarcoidosis: mechanisms, haemodynamics and prognosis

Background: Pulmonary hypertension (PH) is a rare complication of sarcoidosis, although it is not uncommon in advanced disease. Methods: A retrospective series of 22 sarcoidosis patients (16 men) of mean (SD) age 46 (13) years with PH was divided into two groups depending on the absence (stage 0: n = 2, stage II: n = 4, stage III: n = 1) or presence (n = 15) of radiographic pulmonary fibrosis at the time of PH diagnosis. Results: In both groups PH was moderate to severe and there was no response to acute vasodilator challenge. In non-fibrotic cases no other cause of PH was found, suggesting a specific sarcoidosis vasculopathy, although no histological specimens were available. In cases with fibrosis there was no correlation between haemodynamics and lung volumes or arterial oxygen tensions, suggesting other mechanisms for PH in addition to pulmonary destruction and hypoxaemia. These included extrinsic arterial compression by lymphadenopathies in three cases and histologically proven pulmonary veno-occlusive disease in the five patients who underwent lung transplantation. Ten patients received high doses of oral prednisone for PH (stage 0: n = 1, stage II: n = 4 and stage IV: n = 5); three patients without pulmonary fibrosis experienced a sustained haemodynamic response. Survival of the overall population was poor (59% at 5 years). Mortality was associated with NYHA functional class IV but not with haemodynamic parameters or with lung function. Conclusion: Two very different phenotypes of sarcoidosis combined with PH are observed depending on the presence or absence of pulmonary fibrosis. PH is a severe complication of sarcoidosis.
Detection of Malicious URLs by Correlating the Chains of Redirection in an Online Social Network ( Twitter )

Twitter is prone to malicious tweets containing URLs for spam, phishing, and malware distribution. Conventional Twitter spam detection schemes utilize account features such as the ratio of tweets containing URLs and the account creation date, or relation features in the Twitter graph. These detection schemes are ineffective against feature fabrications or consume much time and resources. Conventional suspicious URL detection schemes utilize several features including lexical features of URLs, URL redirection, HTML content, and dynamic behavior. However, evading techniques such as time-based evasion and crawler evasion exist. In this paper, we propose WARNINGBIRD, a suspicious URL detection system for Twitter. Our system investigates correlations of URL redirect chains extracted from several tweets. Because attackers have limited resources and usually reuse them, their URL redirect chains frequently share the same URLs. We develop methods to discover correlated URL redirect chains using the frequently shared URLs and to determine their suspiciousness. We collect numerous tweets from the Twitter public timeline and build a statistical classifier using them. Evaluation results show that our classifier accurately and efficiently detects suspicious URLs. We also present WARNINGBIRD as a near real-time system for classifying suspicious URLs in the Twitter stream.
Revisiting Boracay Island, the Philippines: an integrated coastal zone management perspective

Revisiting Boracay Island, the Philippines: An Integrated Coastal Zone Management Perspective by Thesa Saracanlao Rowan Tourism is one of the important industries in the world. Tourism can bring positive and negative economic, socio-cultural and environmental consequences at the destination level. Small island tourism destinations are often more susceptible to these various insular impacts due to its geographical scale and environmental fragility. In some destinations, impacts associated with tourism development were able to control by formal plans. There has been a move from sector-specific planning for tourism into an Integrated Coastal Zone Management (ICZM) for island tourism. However, other researchers argued that planning is not an effective measure to control tourism development. Hence, this research examines the effectiveness of a formal plan and ICZM in guiding development in a small island coastal zone area that is experiencing high tourism demand. This research explores whether or not the Boracay Island Master Development Plan (BIMDP), the first formal master plan for Boracay Island in the Philippines, manifests the components of ICZM. The research also aimed to find out if BIMDP was able to control the developments in the Island. The research results revealed that BIMDP did not manifest the components of ICZM. It also suggested that formal plans were not fully able to control tourism development in Boracay. This research discussed the different factors influencing the implementation of BIMDP and the reasons why ICZM failed to guide the development in the Island.
Stochastic simulation of daily precipitation, temperature, and solar radiation

Long samples of weather data are frequently needed to evaluate the long-term effects of proposed hydrologic changes. The evaluations are often undertaken using deterministic mathematical models that require daily weather data as input. Stochastic generation of the required weather data offers an attractive alternative to the use of observed weather records. This paper presents an approach that may be used to generate long samples of daily precipitation, maximum temperature, minimum temperature, and solar radiation. Precipitation is generated independently of the other variables by using a Markov chain-exponential model. The other three variables are generated by using a multivariate model with the means and standard deviations of the variables conditioned on the wet or dry status of the day as determined by the precipitation model. Daily weather samples that are generated with this approach preserve the seasonal and statistical characteristics of each variable and the interrelations among the four variables that exist in the observed data.
Amyloid-β oligomers: their production, toxicity and therapeutic inhibition

Despite extensive genetic and animal modelling data that support a central role for the amyloid beta-protein (A beta) in the genesis of Alzheimer's disease, the specific form(s) of A beta which causes injury to neurons in vivo has not been identified. In the present study, we examine the importance of soluble, pre-fibrillar assemblies of A beta as mediators of neurotoxicity. Specifically, we review the role of cell-derived SDS-stable oligomers, their blocking of hippocampal long-term potentiation in vivo and the finding that this blocking can be prevented by prior treatment of oligomer-producing cells with gamma-secretase inhibitors.
Natural head movement for HRI with a muscular-skeletal head and neck robot

This paper presents a study of the movements of a humanoid head-and-neck robot called Eddie. Eddie has a musculo-skeletal structure similar to that found in human necks enabling it to perform head movements that are comparable with human head movements. This study compares the movements of Eddie with those of a more conventional robotic neck structure and with those of a human head. Results show that Eddie's movements are perceived as significantly more natural and by trend more lifelike than the conventional head's. No differences were found with respect to the impression of human-likeness, consciousness, and elegance.
Big Data Analytics-Enhanced Cloud Computing: Challenges, Architectural Elements, and Future Directions

The emergence of cloud computing has made dynamic provisioning of elastic capacity to applications on-demand. Cloud data centers contain thousands of physical servers hosting orders of magnitude more virtual machines that can be allocated on demand to users in a pay-as-you-go model. However, not all systems are able to scale up by just adding more virtual machines. Therefore, it is essential, even for scalable systems, to project workloads in advance rather than using a purely reactive approach. Given the scale of modern cloud infrastructures generating real time monitoring information, along with all the information generated by operating systems and applications, this data poses the issues of volume, velocity, and variety that are addressed by Big Data approaches. In this paper, we investigate how utilization of Big Data analytics helps in enhancing the operation of cloud computing environments. We discuss diverse applications of Big Data analytics in clouds, open issues for enhancing cloud operations via Big Data analytics, and architecture for anomaly detection and prevention in clouds along with future research directions.
Resource Contracts for Java

Writing specifications about program behavior is hard. Writing specifications about non-functional effects such as resource usage is often even harder. If manually instrumenting the program is not an option, programmers have to rely on comment-based specification languages like JML to introduce ghost variables and other fairly abstract concepts that are complicated and hard to maintain. Even worse, most static analysis tools nowadays operate on bit- or bytecode and cannot process those type of specifications To address this problem, we propose a library-based specification formalism for time complexity in Java. The approach is inspired by the success of assertion libraries like CodeContracts and Guava. Our library provides a set of methods and enumerated types that allow the user to write complexity assertions in a 'human' readable form and without instrumenting the code. On the backend, we provide a bytecode rewriting tool that uses these assertions to automatically instrument the program with counter variables. The transformed program can then be checked via testing or off-the-shelf automated static analyzers
A modified concept of consciousness.

The long-standing assumption in the neurosciences that the subjective phenomena of conscious experiences do not exert any causal influence on the sequence of events in the physical brain process is directly challenged in this current view of the nature of mind and the mind-brain relationship. A theory of mind is suggested in which consciousness, interpreted to be a direct emergent property of cerebral activity, is conceived to be an integral component of the brain process that functions as an essential constituent of the action and exerts a directive holistic form of control over the flow pattern of cerebral excitation.
The stratification and water masses at Drake Passage

The waters at Drake Passage are known to be separated horizontally into four distinct zones of relatively small geostrophic shear by three fronts in which the shear and eastward flow are large. The two northern fronts, Subantarctic Front and Polar Front, that bound the Polar Frontal Zone comprise most of the transport of the Antarctic Circumpolar Current. Vertical sections of closely spaced (∼50 km) oceanographic stations made across Drake Passage in the summers of 1975 and 1976 produced quality measurements of temperature, salinity, oxygen, silicate, nitrate, and phosphate. Based on these data, a traditional description of characteristic distributions is presented. Good sampling resolution in the vertical allows maxima in hydrostatic stability to be traced laterally (approximately along isopycnals) between individual stations. Eleven strata of maximum stability are identified. Most vertically separate distinct water masses. The most pronounced stability stratum is associated with the seasonal pycnocline; north of the Polar Front, it separates the Subantarctic Surface Waters from Subantarctic Mode Water. To the south of the Polar Front the seasonal pycnocline is found slightly above the temperature minimum characteristic of the Antarctic Surface Waters in austral summer. This stability stratum extends northward near the base of the Subantarctic Mode Water. Another stability stratum extending across the entire passage forms the upper boundary for the Circumpolar Deep Water. South of the Polar Front, this stratum is at the base of the Antarctic Surface Water; to the north it is the lower boundary of the Antarctic Intermediate Water. Although Subantarctic Mode Water and Antarctic Intermediate Water are separated by a stability stratum north of the Polar Front, there is no such separation between Antarctic Intermediate Water and the temperature minimum of the Antarctic Surface Water south of the front. This suggests that Subantarctic Mode Water and Antarctic Intermediate Water are distinct and that the latter derives from the surface waters south of the Polar Front. At greater depths a horizontally discontinuous stratum is found between the Upper and Lower Circumpolar Deep Water. Two horizontally continuous stability strata are found near the base of the Circumpolar Deep Water, marking the transition to a high-silicate variety of denser deep water from the Southeast Pacific Basin. The densest water mass found is Weddell Sea Deep Water, which flows through a gap in the South Scotia Ridge and along the southern Scotia Sea to fill the trough in the southern Drake Passage. It is overlain by a laterally continuous stratum of relative maximum stability.
Effectiveness of strategic environmental assessment - the significance of learning

Learning, particularly transformative learning, is an established feature of environmental planning, management and assessment. Nevertheless, very often it loses its prominence both as a process and as a goal. This paper explores the extent to which strategic environmental assessment (SEA) can facilitate learning at an organisational and individual level, and ultimately, achieve effectiveness. It is based on the assumption that SEA effectiveness can be achieved if policy, programme and plan-making are oriented towards both the continuous improvement of decision-making and the associated implementation processes. Set within the context of the European SEA Directive, the learning dimension of SEA is explored in Germany, Italy and the UK. This is done through a framework for analysis based on a review of the organisational and individual learning literatures. The research indicates that, owing to their unique contextual and methodological influences, the three countries developed distinct approaches to SEA, with differences in the skills and knowledge needed to improve its learning outcomes. Based on the research findings, the paper identifies what further research is needed to improve SEA's learning outcomes and achieve more effective SEA practice.
A Framework for Dataset Benchmarking and Its Application to a New Movie Rating Dataset

Rating datasets are of paramount importance in recommender systems research. They serve as input for recommendation algorithms, as simulation data, or for evaluation purposes. In the past, public accessible rating datasets were not abundantly available, leaving researchers no choice but to work with old and static datasets like MovieLens and Netflix. More recently, however, emerging trends as social media and smartphones are found to provide rich data sources which can be turned into valuable research datasets. While dataset availability is growing, a structured way for introducing and comparing new datasets is currently still lacking. In this work, we propose a five-step framework to introduce and benchmark new datasets in the recommender systems domain. We illustrate our framework on a new movie rating dataset—called MovieTweetings—collected from Twitter. Following our framework, we detail the origin of the dataset, provide basic descriptive statistics, investigate external validity, report the results of a number of reproducible benchmarks, and conclude by discussing some interesting advantages and appropriate research use cases.
Prediction of petrophysical parameter logs using a multilayer backpropagation neural network

Abstract Quantitative petrophysical characterization is one of the principal tasks of a reservoir analyst and is generally affected by the methods used. For example, different theoretical and empirical formulas are in most cases restricted to the specific areas where they were developed. Prediction of continuous petrophysical parameters is often time consuming and complicated because of geological variability such as facies changes due to sedimentary and structural changes. In this work we propose a neural network approach which is used to predict quantitative petrophysical parameters from wireline logs of cored intervals. We then apply the knowledge learned during training to uncored intervals or other holes. Data from the Ocean Drilling Program and from two South American oilfield holes are used to test this technique. The results show a good match between the neural network-derived petrophysical parameter logs and the actual core measurements. Problematic petrophysical measurements can be identified by a mismatch between the responses.
Process Introspection: A Heterogeneous Checkpoint/Restart Mechanism Based on Automatic Code Modification

Process Introspection is a fundamentally new solution to the process checkpoint/restart problem suitable for use in high-performance heterogeneous distributed systems. A process checkpoint/restart mechanism for such an environment has the primary requirement that it must be platform-independent: process checkpoints produced on a computer system of one architecture or operating system platform must be restartable on a computer system of a different architecture or operating system platform. The central feature of the Process Introspection approach is automatic augmentation of program code to incorporate checkpoint and restart functionality. This program modification is performed at a platform-independent intermediate level of code representation, and preserves the original program semantics. This approach has attractive properties including portability, ease of use, customizability to application-specific requirements, and flexibility with respect to basic performance trade-offs. Our solution is novel in its true platform- and run-time system independence - no system support or non-portable code is required by our core mechanisms. Recent experimental results obtained using a prototype implementation of the Process Introspection system indicate the overheads introduced by the mechanisms are acceptable for computationally demanding applications.
La industria del cemento en Colombia

Este documento analiza el comportamiento de la industria del cemento en Colombia en las ultimas decadas. En particular, estudia la relacion que existe entre el precio y las cantidades producidas de cemento durante el periodo 1980 - 2006, asi como los determinantes del comportamiento de estas variables durante el periodo 1994 - 2006. Los resultados muestran que, como consecuencia de la crisis economica de finales de siglo pasado, la relacion de largo plazo entre precios y cantidades tuvo un fuerte desequilibrio, que se ha corregido parcialmente en los anos recientes. Ademas, se encuentra evidencia de una conducta estrategica en la fijacion del precio, de acuerdo al comportamiento de la demanda. Abstract This paper analyses the functioning of Colombia´s cement industry in the last decades. In particular, it explores the dynamic relation among real cement prices and output for period 1980 - 2006, and studies their determinants using data for the period 1994 - 2006. The evidence suggests that the severe recession of the late 1990s caused a disequilibrium in the long term relationship between prices and quantities, which has been partially corrected. In addition, results indicate a strategic behavior in price determination, depending on demand conditions.
Heart specific scoX knockdown induces p53 dependent apoptosis and cardiomyopathy

Cytochrome c oxidase or complex IV is the terminal component of the mitochondrial electron transport chain. It catalyses the transfer of electrons from reduced cytochrome c to molecular oxygen. Complex IV deficiency due to mutations in assembly factors is one of the most frequent defects of respiratory chain in humans. These pathologies are characterized by a very early age of onset and the display of different clinical presentations, as encephalopathy, cardiomyopathy, hepatic failure and leukodystrophy. SCO1 and SCO2 are two metallochaperones playing a key role in the formation of cooper centre CuA during complex IV assembly. Mutations in SCO1 cause hepato-encephalomyopathy although one case has been reported which also presents hypertrophic cardiomyopathy. Mutations in SCO2 cause hypertrophic cardiomyopathy and infantile encephalomyophathy and with but one exception, all patients harbour the E140K mutation. In this thesis, we have used Drosophila melanogaster as model system to investigate the genetic and molecular mechanisms that underlie the cardiomyopathy associated with SCO deficiency. The genetic network controlling cardiac specification and differentiation as well as many aspects of heart function are conserved from flies to mammals. Thus, Drosophila has become a powerful model system for the study and understanding of cardiac function and human cardiomyopathies. Furthermore, the recently established heart function assays in Drosophila make it possible to characterize how mitochondrial electron transport chain defects affect heart function. In Drosophila there is a single ortholog of mammalian Sco1 and 2, ScoX. Our findings demonstrate that cardiac-specific knockdown of ScoX causes dileted cardiomyopathy severely compromising heart function and structure. Cardiomyocytes undergo a metabolic switch from oxidative phosphorylation to glycolysis probably accompanied by lactic acidosis and therefore mimicking the clinical features found in patients with mutations in Sco1 and Sco2. The observed phenotype is result of dp53-dependent cell death activation. These results strongly suggest that dp53 is directly involved in cardiomyopathy development.
BIAS corrections in linear MMSE estimation with large filters

We investigate optimal bias corrections in the problem of linear minimum mean square error (LMMSE) estimation of a scalar parameter linearly described by a set of Gaussian multidimensional observations. The problem of finding the optimal scaling of a class of LMMSE filter implementations based on the sample covariance matrix (SCM) is addressed. By applying recent results from random matrix theory, the scaling factor minimizing the mean square error (MSE) and depending on both the unknown covariance matrix and its sample estimator is firstly asymptotically analyzed in terms of key scenario parameters, and finally estimated using the SCM. As a main result, a universal scaling factor minimizing the estimator MSE is obtained which dramatically outperforms the conventional LMMSE filter implementation. A Bayesian setting assuming random unknown parameters with known mean and variance is considered in this paper, but exactly the same methodology applies to the classical estimation setup considering deterministic parameters.
Anatomically realistic reference models of pregnant women for gestation ages of 13, 18, and 26 weeks

The safety of a human body exposed to radio-frequency (RF) electromagnetic fields (EMFs) has become important today. In recent times, conducting numerical dosimetry on the mother and the fetus during pregnancy has become a particularly important issue. This paper outlines the development of pregnant woman models that were adjusted to the reference values of physiological characteristics of maternal tissues in pregnant women for gestation ages of 13, 18, and 26 weeks The models are composed of voxels of 2 × 2 × 2 mm3, and there are 56 tissue types. The basic specific absorption rate (SAR) characteristics in the pregnant woman models for whole-body exposure to RF electromagnetic fields that were calculated using the finite-difference time-domain (FDTD) method are described here.