Miracle-dz/UniFAR-FTUs huggingface dataset:
Artemisinin Directly Targets Malarial Mitochondria through Its Specific Mitochondrial Activation

The biological mode of action of artemisinin, a potent antimalarial, has long been controversial. Previously we established a yeast model addressing its mechanism of action and found mitochondria the key in executing artemisinin's action. Here we present data showing that artemisinin directly acts on mitochondria and it inhibits malaria in a similar way as yeast. Specifically, artemisinin and its homologues exhibit correlated activities against malaria and yeast, with the peroxide bridge playing a key role for their inhibitory action in both organisms. In addition, we showed that artemisinins are distributed to malarial mitochondria and directly impair their functions when isolated mitochondria were tested. In efforts to explore how the action specificity of artemisinin is achieved, we found strikingly rapid and dramatic reactive oxygen species (ROS) production is induced with artemisinin in isolated yeast and malarial but not mammalian mitochondria, and ROS scavengers can ameliorate the effects of artemisinin. Deoxyartemisinin, which lacks an endoperoxide bridge, has no effect on membrane potential or ROS production in malarial mitochondria. OZ209, a distantly related antimalarial endoperoxide, also causes ROS production and depolarization in isolated malarial mitochondria. Finally, interference of mitochondrial electron transport chain (ETC) can alter the sensitivity of the parasite towards artemisinin. Addition of iron chelator desferrioxamine drastically reduces ETC activity as well as mitigates artemisinin-induced ROS production. Taken together, our results indicate that mitochondrion is an important direct target, if not the sole one, in the antimalarial action of artemisinins. We suggest that fundamental differences among mitochondria from different species delineate the action specificity of this class of drugs, and differing from many other drugs, the action specificity of artemisinins originates from their activation mechanism.
A Game Theoretic Model and Empirical Analysis of Spammer Strategies

Network security problems are deteriorating worldwide, and can potentially undermine the growth of the digital economy and imperil the multitude of innovations that have been a significant driver of economic growth as well as providing in- creased services to individuals, businesses, and governments. The emergence of botnets as a powerful force undermining security has raised new and important issues. In particu- lar, the difficulty of detection, elimination and prevention of botnets or spam caused thereof on an absolute scale us- ing computing technologies alone have focused attention on studying behavior patterns of botnets and spammers, to help devise better countermeasures. This paper has two ob- jectives; first to introduce a theoretical modeling approach to spammer behavior and derivation of the model, and sec- ond, to compare some of the derivations with data that has been collected from blocklist organizations. By making in- ferences about the blocklist rules, the spammer can strate- gize to maximize the amount of spam sent, and we find evidence of spammers using multiple strategies. The block- list can achieve reduction of spam by investigating longer history of a node's behavior instead of focusing on detection alone. While some of the derivations seem consistent with the data there is considerable room for modification and ex- tension of the modeling approach. The paper concludes with suggestion for the extension of the model.
Two Types of Planning in Language Generation

As our understanding of natural language generation has increased, a number of tasks have been separated from realization and put together under the heading "text planning". So far, however, no-one has enumerated the kinds of tasks a text planner should be able to do. This paper describes the principal lesson learned in combining a number of planning tasks in a planner-realizer: planning and realization should be interleaved, in a limited-commitment planning paradigm, to perform two types of planning: prescriptive and restrictive. Limited-commitment planning consists of both prescriptive (hierarchical expansion) planning and of restrictive planning (selecting from options with reference to the status of active goals). At present, existing text planners use prescriptive plans exclusively. However, a large class of planner tasks, especially those concerned with the pragmatic (non-literal) content of text such as style and slant, is most easily performed under restrictive planning. The kinds of tasks suited to each planning style are listed, and a program that uses both styles is described.
Phenology and dynamics of an African rainforest at Korup, Cameroon

In groves of ectomycorrhizal caesalpinaceous legumes in Korup, Cameroon, the most abundant of three co-dominant tree species, Microberlinia bisulcata, has had, and continues to show, very low recruitment. Replacement is likely to favour the two other guild members, Tetraberlinia bifoliolata nod T. morelitma. All three species produce large sufficient seedling banks. Microberlinia bisulcata attained the greatest tree sizes and had the most pronounced mast fruiting pattern (a 3-year cycle). Masting was associated with peaks in the previous dry-season radiation suggesting a requirement to accumulate carbon reserves before fruiting. More circumstantial evidence points to phosphorus supply as a co-controlling factor. The dominance of M. bisulcata is most likely due to a recently unique, natural historical event, an epoch of unusually dry years, which allowed its shade-intolerant ectomycorrhizal seedlings to outcompete other species. The putative fungal connections to parents appear to be of no advantage (possibly a disadvantage) to the seedlings under such mature adults. The composition of Korup is neither constant nor cycling but a fragment of change which might be reset by climatic fluctuations coincident with potential regeneration of a species also adapted to the low-phosphorus soils and strongly seasonal conditions of the site. Understanding the dynamic& of such an African forest requires a stochastic view over several centuries.
Experiments with real-world data: the acoustic-to-articulatory mapping problem

In this chapter, we apply our reconstruction algorithm to a version of the acoustic-to-articulatory mapping, a well-known mapping inversion problem of speech research. It is a complex, high-dimensional task that helps to further understand the performance of the algorithm. Before the description and discussion of the experimental results of section 10.2, we give some background of the problem and its significance for speech perception and automatic speech recognition (ASR) in section 10.1.
Immunosuppression with cyclophosphamide favors reinfection with recombinant Toxoplasma gondii strains

The aim of this study was to verify the effect of immunosuppression by cyclophosphamide (Cy) on susceptibility of BALB/c mice subjected to challenge with recombinant strains of Toxoplasma gondii. Animals were prime infected with the D8 (recombinant I/III) or the ME49 (type II) non-virulent strains, weekly immunosuppressed with Cy and challenged with the CH3 or EGS virulent strains (I/III). Parasites recovered from surviving mice were submitted to PCR-RFLP analysis to confirm co-infection. Prime-infection with the D8 strain conferred more protection against challenge with the CH3 and EGS strains when compared with ME49 prime infection. Cy treatment caused significant leukopenia in the infected mice, what probably favors reinfection after challenge. Reinfection was associated with increased levels of IgA. Otherwise, Cy-treated mice presented significantly lower IgA levels after challenge, suggesting involvement of this immunoglobulin on protection against reinfection. In conclusion, BALB/c mice susceptibility to reinfection by T. gondii is related to genetic differences among the strains used for primary and challenge infections. Alteration of the host’s immune integrity by Cy probably compromises the protection previously established by primary infection.
Winter Hydrology and NO3− Concentrations in a Forested Watershed: A Detailed Field Study in the Adirondack Mountains of New York 1

Abstract: More than 85% of NO3− losses from watersheds in the northeastern United States are exported during winter months (October 1 to May 30). Interannual variability in NO3− loads to individual streams is closely related to interannual climatic variations, particularly during the winter. The objective of our study was to understand how climatic and hydrogeological factors influence NO3− dynamics in small watersheds during the winter. Physical parameters including snow depth, soil temperature, stream discharge, and water table elevation were monitored during the 2007‐2008 winter in two small catchments in the Adirondack Mountains, New York State. Snowpack persisted from mid‐December to mid‐April, insulating soils such that only two isolated instances of soil frost were observed during the study period. NO3− export during a mid‐winter rain‐on‐snowmelt event comprised between 8 and 16% of the total stream NO3− load for the four‐month winter study period. This can be compared with the NO3− exported during the final spring melt, which comprised between 38 and 45% of the total four‐month winter NO3− load. Our findings indicate that minor melt events were detectable with changes in soil temperature, streamflow, groundwater level, and snow depth. But, based on loading, these events were relatively minor contributors to winter NO3− loss. A warmer climate and fluctuating snowpack may result in more major mid‐winter melt events and greater NO3− export to surface waters.
Automatic Classification of Time Series (ACTS): A new clustering method for remote sensing time series

Automatic classification methods have often been used as a first step for land cover mapping. The principle of such methods is to determine clusters of pixels with similar radiometric temporal behaviour based on their statistical properties. This allows a segmentation of the image into regions with similar radiometric properties. Most automatic classification of remote sensing data are based on the K-mean or dynamical clustering method. The latter method has two limitations. (i) It is necessary to fix the number of clusters, but this parameter is, in general, unknown. (ii) It is very slow and does not work correctly when the dimension of the problem and the number of samples become large which is typically the case for classification of remote sensing data at large scale. To avoid these limitations we have developed a new method called ACTS (Automatic Classification of Time Series), which is based on both hierarchical and dynamical clustering principles. First of all, the method is really 'automatic' since it determines, automatically, the number of clusters. Secondly, the method is very fast and does not show a degradation of the results with large dimensions or data sets. Application to synthetic data sets shows that in most cases ACTS is able to retrieve all the clusters of the image independently of the dimensions of the problem. Comparison of classifications based on actual global 8 km NDVI (Normalized Differential Vegetation Index) composites using both ACTS and a K-mean method show very similar results but the convergence for ACTS is 20 times faster than the K-mean method using '10-day' composites. The ability of ACTS to work with problems of large dimensions enables clustering of multi-year time series of NDVI. ACTS is here applied to the clustering of a 12-year time series of 10-day composites (1982-1993). The results show that the seasonal signal is dominant. The clusters are mainly representative of seasonal land cover regions. Moreover, the regions are more clearly delineated in comparison with the classification based on only one year of data. Such improved clustering can help avoid some confusion between biomes. Finally, ACTS is applied to 'deseasonalized' time series to investigate the interannual variability of the NDVI. The areas of higher variability are located in the tropical regions with a strong influence of El Nino events. A small positive trend in NDVI is visible in high latitudes. However, several problems linked to the quality of the data are clearly visible. For instance, the decrease of NDVI following the Pinatubo eruption in 1991 and the drift in calibration with the change from NOAA 9 to NOAA 11 in 1988 are visible in most of the regions. This unfortunately limits the possible interpretation of the signal and emphasizes the need to improve the preprocessing of AVHRR (Advanced Very High Resolution Radiometer) data for interannual variability applications.
Long term exposure to ambient air pollution and incidence of acute coronary events: prospective cohort study and meta-analysis in 11 European cohorts from the ESCAPE Project

Objectives To study the effect of long term exposure to airborne pollutants on the incidence of acute coronary events in 11 cohorts participating in the European Study of Cohorts for Air Pollution Effects (ESCAPE). Design Prospective cohort studies and meta-analysis of the results. Setting Cohorts in Finland, Sweden, Denmark, Germany, and Italy. Participants 100 166 people were enrolled from 1997 to 2007 and followed for an average of 11.5 years. Participants were free from previous coronary events at baseline. Main outcome measures Modelled concentrations of particulate matter <2.5 μm (PM2.5), 2.5-10 μm (PMcoarse), and <10 μm (PM10) in aerodynamic diameter, soot (PM2.5 absorbance), nitrogen oxides, and traffic exposure at the home address based on measurements of air pollution conducted in 2008-12. Cohort specific hazard ratios for incidence of acute coronary events (myocardial infarction and unstable angina) per fixed increments of the pollutants with adjustment for sociodemographic and lifestyle risk factors, and pooled random effects meta-analytic hazard ratios. Results 5157 participants experienced incident events. A 5 μg/m3 increase in estimated annual mean PM2.5 was associated with a 13% increased risk of coronary events (hazard ratio 1.13, 95% confidence interval 0.98 to 1.30), and a 10 μg/m3 increase in estimated annual mean PM10 was associated with a 12% increased risk of coronary events (1.12, 1.01 to 1.25) with no evidence of heterogeneity between cohorts. Positive associations were detected below the current annual European limit value of 25 μg/m3 for PM2.5 (1.18, 1.01 to 1.39, for 5 μg/m3 increase in PM2.5) and below 40 μg/m3 for PM10 (1.12, 1.00 to 1.27, for 10 μg/m3 increase in PM10). Positive but non-significant associations were found with other pollutants. Conclusions Long term exposure to particulate matter is associated with incidence of coronary events, and this association persists at levels of exposure below the current European limit values.
Changes in oceanic precipitation during the 1997–98 El Niño

The recent El Niño has been by most measures one of the most extreme, and there have been several papers on its thermal signature and associated wind field. There has also been wide coverage of the changes in terrestrial precipitation, with torrential rains in California and devastating fires in Borneo in response to the prolonged drought. Here we complete the picture by examining oceanic precipitation data derived from novel processing of dual‐frequency altimetry. An increased area of precipitation, with more frequent and slightly more intense rainfall, is found to mirror the expansion of the western warm pool.
Outcome and Predicting Factor Following Severe Traumatic Brain Injury: A Retrospective Cross-Sectional Study.

INTRODUCTION Severe traumatic brain injury (TBI) is a major and challenging problem in critical care medicine. AIM To assess the outcome and predicting factor following severe TBI. MATERIALS AND METHODS This is a retrospective and cross-sectional study. Data were collected from two sections; one section consisting of a questionnaire answered by the patients and other section from the patient records. The instruments used included the Glasgow Outcome Scale (GOS), SF-36 and the Hospital Anxiety and Depression Scale (HAD). RESULTS The mortality rate of the patients was 46.2%. The quality of life (QOL) of the patients in most dimension were impaired and (58%) of patients had unfavourable QOL. About (37.5%) of patients with anxiety and (27.5%) had a depression. A significant correlation was found between age, GCS arrival, length of ICU stay, mechanical ventilation, VAP & ARDS and pupil reactivity with QOL, GOS, HAD-A and HAD-D (p<0.05, p< 0.001). GCS arrival a predicate factor for QOL and GOS (p <0.001, OR: 1.75, 1.94 respectively); length of ICU stay a predicate factor for QOL and GOS (p <0.05, OR : 1.11, 1.28 respectively); mechanical ventilation a predicate factor for GOS (p <0.001, OR : 1.78); ventilation associated pneumonia (VAP) & acute respiratory distress syndrome (ARDS) and pupil reactivity a predicate factor for GOS (p <0.05, OR : 1.36; p<0.001, OR: 1.94 respectively). The GCS arrival and ICU stay a predicate factor for HAD-A (p<0.05, OR: 1.73, 1.38 respectively). CONCLUSION With respect to results advanced in pre hospital, medical and surgical care for the decrease in mortality rates of Head trauma (HT), the use of trauma triage tools and strict enforcement of traffic rules are necessary.
Dawn: Dependable Networking Framework for Multimedia-enabled Internet-of-Things

Developing reliable application for the Internet-of-Things (IoT) is challenging due to heterogenous sensors and the resource-constraints of IoT platforms. Multimedia sensors such as cameras and microphones require significant memory and bandwidth. Typically, multimedia content results in bursty traffic. It is shown in the literature that the bursty traffic degrades the performance of the network. Hence, the regulation of bursty transmission is important for achieving high reliability. In this paper, we propose Dawn, a dependable networking framework for time-synchronised IoT platforms, which uses application meta-data to derive bandwidth requirements and uses this information to optimally allocate bandwidth for the network. Dawn regulates the transmission of bursty traffic generated by multimedia sensors, while performing admission control for dynamically added sensors. Dawn guarantees end-to-end reliability for heterogenous IoT applications with minimal energy consumption. Our preliminary evaluation results show that dawn is dependable and provides 100% reliability for dynamic multimedia-enabled IoT applications while increasing the network lifetime by up to 4 years.
The 1982—83 El Niño: some of its consequences for Galápagos wildlife

The warm event, El Nino, that struck the eastern equatorial Pacific in 1982–83 was the strongest recorded in the last 100 years. Coastal people suffered floods, crop losses and failure of fish catches as the ocean waters grew warmer and the rainfall increased more than tenfold. Wildlife was affected in many different ways. The author has been working as a Naturalist Guide within the Galapagos National Park for the past three and a half years and he is particularly interested in the interactions of seabirds with their environment.
Unsupervised Feature Learning from Temporal Data

Current state-of-the-art classification and detection algorithms rely on supervised training. In this work we study unsupervised feature learning in the context of temporally coherent video data. We focus on feature learning from unlabeled video data, using the assumption that adjacent video frames contain semantically similar information. This assumption is exploited to train a convolutional pooling auto-encoder regularized by slowness and sparsity. We establish a connection between slow feature learning to metric learning and show that the trained encoder can be used to define a more temporally and semantically coherent metric.
Discontinuation of Antiplatelet Treatment and Risk of Recurrent Stroke and All-Cause Death: A Cohort Study

Background: We wished to examine the impact of antiplatelet drug discontinuation on recurrent stroke and all-cause mortality. Methods: We identified a cohort of incident ischaemic stroke patients in a Danish stroke registry, 2007-2011. Using population-based registries we assessed subjects' drug use and followed them up for stroke recurrence, or all-cause death. Person-time was classified by antiplatelet drug use into current use, recent use (≤150 days after last use), and non-use (>150 days after last use). Lipid-lowering drug (LLD) use was classified by the same rules. We used Cox proportional hazard models to calculate the adjusted hazard ratio (HR) and corresponding 95% confidence intervals (CIs) for the risk of recurrent stroke or death associated with discontinuation of antiplatelet or LLD drugs. Results: Among 4,670 stroke patients followed up for up a median of 1.5 years, 237 experienced a second stroke and 600 died. Compared with current antiplatelet drug use, both recent use (1.3 (0.8-2.0)), and non-use (1.3 (0.8-1.9)) were associated with increased recurrent stroke risk. The corresponding HRs of death were 1.9 (1.4-2.5) for recent and 1.8 (1.4-2.3) for non-use of antiplatelet drugs. Recent statin use was associated with markedly increased risk of death (2.1 (1.7-2.6)), and only marginally with recurrent stroke (1.2 (0.9-1.6)). Conclusions: Antiplatelet drug discontinuation may be associated with an increased recurrent stroke risk. Our results on death risk indicate that non-pharmacological biases, such as ‘sick stopper', may threaten the validity of this risk estimate.
Direct Measurement of Cognitive Load in Multimedia Learning

Cognitive load theory (CLT) is gaining increasing importance in the design and evaluation of instruction, both traditional and technology based. Although it is well understood as a theoretical construct, the measurement of cognitive load induced by instructional materials in general, and by multimedia instruction in particular, mainly relies on methods that are either indirect, subjective, or both. Integrating aspects of CLT, working memory research, and cognitive theories of multimedia learning, we describe the conceptual basis and practical implementation of a dual-task approach to the direct measurement of cognitive load in multimedia learning. This computer-based instrument provides a direct and objective measure that overcomes many of the shortcomings of other indirect and subjective methods that will enable researchers to validate empirically theoretical predictions of CLT.
Factors Limiting Industrial Adoption of Test Driven Development: A Systematic Review

Test driven development (TDD) is one of the basic practices of agile software development and both academia and practitioners claim that TDD, to a certain extent, improves the quality of the code produced by developers. However, recent results suggest that this practice is not followed to the extent preferred by industry. In order to pinpoint specific obstacles limiting its industrial adoption we have conducted a systematic literature review on empirical studies explicitly focusing on TDD as well as indirectly addressing TDD. Our review has identified seven limiting factors viz., increased development time, insufficient TDD experience/knowledge, lack of upfront design, domain and tool specific issues, lack of developer skill in writing test cases, insufficient adherence to TDD protocol, and legacy code. The results of this study is of special importance to the testing community, since it outlines the direction for further detailed scientific investigations as well as highlights the requirement of guidelines to overcome these limiting factors for successful industrial adoption of TDD.