Miracle-dz/UniFAR-FTUs huggingface dataset:
Sensor Stability of a Low-Cost Attitude Sensor Suitable for Micro Air Vehicles

This paper expands on previous work to introduce a high quality, but low cost attitude and heading reference system (AHRS), that is physically small, lightweight, and lowpower. Previous Work on the sensor has shown that for non-accelerating environments, this small low-cost sensor has a short term accuracy of approximately 4 ◦ in pitch, roll, and yaw. We extend the previous two-step non-linear calibration algorithm to account for non-orthogonality in the sensor axes, and also correlate the measured temperature of the sensor against the long term bias stability. Further bias stability is investigated using the Allan Variance, demonstrating that with temperature correction, the static attitude solution has approximately 1 2 the standard deviation as without temperature correction. When the data is averaged to a 1Hz data rate, the 24 hour standard deviations vary from 0.017 to 0.06 for pitch, roll, and yaw.
A modern analogue of the Pleistocene steppe‐tundra ecosystem in southern Siberia

Steppe‐tundra is considered to have been a dominant ecosystem across northern Eurasia during the Last Glacial Maximum. As the fossil record is insufficient for understanding the ecology of this vanished ecosystem, modern analogues have been sought, especially in Beringia. However, Beringian ecosystems are probably not the best analogues for more southern variants of the full‐glacial steppe‐tundra because they lack many plant and animal species of temperate steppes found in the full‐glacial fossil record from various areas of Europe and Siberia. We present new data on flora, land snails and mammals and characterize the ecology of a close modern analogue of the full‐glacial steppe‐tundra ecosystem in the southeastern Russian Altai Mountains, southern Siberia. The Altaian steppe‐tundra is a landscape mosaic of different habitat types including steppe, mesic and wet grasslands, shrubby tundra, riparian scrub, and patches of open woodland at moister sites. Habitat distribution, species diversity, primary productivity and nutrient content in plant biomass reflect precipitation patterns across a broader area and the topography‐dependent distribution of soil moisture across smaller landscape sections. Plant and snail species considered as glacial relicts occur in most habitats of the Altaian steppe‐tundra, but snails avoid the driest types of steppe. A diverse community of mammals, including many species typical of the full‐glacial ecosystems, also occurs there. Insights from the Altaian steppe‐tundra suggest that the full‐glacial steppe‐tundra was a heterogeneous mosaic of different habitats depending on landscape‐scale moisture gradients. Primary productivity of this habitat mosaic combined with shallow snow cover that facilitated winter grazing was sufficient to sustain rich communities of large herbivores.
Laser scan matching in polar coordinates with application to SLAM

This paper presents a novel method for 2D laser scan matching called polar scan matching (PSM). The method belongs to the family of point to point matching approaches. Our method avoids searching for point associations by simply matching points with the same bearing. This association rule enables the construction of an algorithm faster than the iterative closest point (ICP). Firstly the PSM approach is tested with simulated laser scans. Then the accuracy of our matching algorithm is evaluated from real laser scans from known relative positions to establish a ground truth. Furthermore, to demonstrate the practical usability of the new PSM approach, experimental results from a Kalman filter implementation of simultaneous localization and mapping (SLAM) are provided.
Estimation of ground water recharge at NCAM, Ilorin for improved irrigation management.

The recharge rate is a very important parameter required in the successful development of ground water resources, as often, it is this rate that can be safely abstracted as safe yield from wells and boreholes. Groundwater recharge was estimated for 2 wells located in areas representing the different land uses at NCAM using the water table fluctuation method. The yield from sites A and B were 0.02 – 0.2 m 3 /hr and 0.008 – 0.03 m 3 /hr respectively while the peak scheme water demand required for producing dry season vegetables for 0.5ha was obtained as 0.002 m 3 /s. Achieving better understanding of the mechanisms that control groundwater recharge is crucial towards improving groundwater management. INTRODUCTION Water is indispensable to all life on earth. Fresh water is constantly formed newly through a phenomenon known as hydrological cycle. Groundwater, on the other hand, is a replenishable resource widely distributed under the ground. It is free from pollution and can be developed with small capital cost in the least possible time (Raghunath, 1991). It allows the practice of intensive irrigation with possibilities of double or triple cropping, including commercial crops. In addition, supplemental irrigation during periods of deficient surface supply can be practiced thus making all year round farming possible. Rainfall is the principal source for replenishment of moisture in the soil water system and recharge of ground water.
Characterising the evolution of Himalayan debris covered glaciers.

The majority of the 20,000 glaciers found in the Himalaya are in a state of negative mass balance, and have been for decades. Broad spatial trends in ice mass loss have been identified by large scale geodetic mass balance studies, but regional averaging of mass loss data has masked catchment or glacier scale variability. This thesis has the broad aim of examining the catchment scale variability of ice mass loss, in order to identify factors that might promote, or inhibit, more substantial ice mass loss from the region in the future. Ice mass loss rates from Everest region glaciers were calculated using the geodetic approach, over the period 2000-2015, and compared depending on glacier terminus type. Lake-terminating glaciers were found to have lost 32% more ice mass than land-terminating glaciers, and maximum surface lowering rates of lake-terminating glaciers peaked at more than twice the rate of land-terminating counterparts. Glacier hypsometry was found to be contrasting at the catchment scale, and predicted accumulation area ratio (AARs) change in response to different RCP warming scenarios emphasises the importance of considering glacier area-altitude distribution in future ice loss estimates. A more detailed assessment of the evolving geometry, dynamics and ice loss rates of nine lake-terminating glaciers suggested two phases of glacier-lake interaction may exist. A phase of dynamic lake-terminating glacier retreat was evident where terminus proximal surface lowering rates were high (up to 3 m a-1), ice front retreat rates were steady or accelerating, and surface velocities increased (by up to 10 m a-1, between 1999 and 2015). Alternatively, a phase of retreat typified by surface lowering rates akin to land-terminating glaciers (~1 m a-1), where ice front retreat rates were steady or diminishing, and where surface velocity reduction occurred. The dynamic phase of ice loss observed on lake-terminating glaciers in the Everest region is not of the same magnitude as larger waterter-minating glaciers found in other glacierised regions, probably because of the topographic confinement of host glaciers and the dominance of resistive stresses, but the now populous nature of glacial lakes in the region means the potential for amplified future ice loss exists. The impact of long-term ice loss on the topographic characteristics of debris covered glacier surfaces was also examined. Ice cliff and supraglacial pond expansion was identified as the main driver of topographic change on slow flowing, land-terminating glaciers. A more pitted surface topography of greater relief developed on most glaciers, which has implications for the energy balance at the glacier surface, and for supraglacial hydrology. Overall, the results of this thesis emphasise the need to incorporate a range of glacier dynamics scenarios and melt processes into simulations of future ice loss in the Himalaya.
Study on the Preparation Process of Rice Bran Oil by the Ultrasonic Enzymatic Extraction

The influence of oil rate and quality of rice bran oil by enzymatic extraction ultrasonic assisted were studied through designed experiment. The optimum enzymatic hydrolysis conditions were determined by the way of the orthogonal test. The results showed: after lipase enzyme in the rice bran (40 mesh sieve) was killed by the hot steam, the solution compounding material liquid ratio was 1:5 (W/V), 60°C, power and time of ultrasonic treatment were 120 W and 55 min, cellulose 1.2%, protease 0.6% and amylase 0.3%, pH 4.5, temperature 55°C, enzyme hydrolysis 5.5 h, the oil rate would reach to 92.63%.
Reservoir characteristics in the Cretaceous volcanic rocks of Songliao Basin, China: A case of dynamics and evolution of the volcano-porosity and diagenesis

To explain the strong spatial heterogeneity of volcanic reservoirs porosity in the Songliao Basin and provide new ideas for predicting good volcanic reservoirs in other similar basins, the relationship between the pore evolution process and lithology of volcanic reservoirs has been described in this article. With the description and interpretation of core, thin section, scanning electron microscope, and the results of mercury injection experiment, this article clarifies the lithology, pore types, and pore structure features of the volcanic reservoirs in the Songliao Basin. The rocks of volcanic reservoirs in study area contain pyroclastic rock and volcanic lavas. The most common lithologies are rhyolite, volcanic breccia, and volcanic tuff. The pore size, morphology, and structure vary greatly between these three lithologies, the reason of which we think is the different volcanic eruption process as well as rock composition and its structure. The digenetic evolution of rhyolite includes gas dissipation of magmatic condensation; vesicles fulfilling by hydrothermal fluid; kaolinization and sericitization of feldspar phenocrysts; carbonation, devitrification, and recrystallization of felsic matrix; and finally, the dissolution of feldspar phenocrysts and felsic matrix. As for volcanic breccia, it usually go through the compaction, quartz and calcite filling the original pores between volcanic breccias, and dissolution of mineral debris together with tuff matrix. Similar with the rhyolite, volcanic tuff also undergoes the carbonation and kaolinization of felsic matrix, the dissolution of feldspar and felsic matrix, and compaction. Due to these comprehensive processes, a comprehensive analysis of volcanic rock lithology, which can indicate lithology distribution vertically and horizontally, is very necessary during volcanic reservoirs evaluation and prediction. These detailed analyses will help explorers to find potential reservoirs by distinguishing the diagenetic evolution and pore characteristic of volcanic reservoirs.
Using testing techniques to classify user interface designs

Number entry systems in medical devices such as infusion pumps are used to input drug doses that will be administered to patients. They are safety critical since if the drug dose is too high or too low, this may cause harm to patients. Previous work shows that number entry systems with the same hardware layout can have software that is implemented in different ways. This means that devices with the same hardware layout may lead to different results after the same keystrokes are pressed. Previous work also shows that choosing the best software implementation over the worst can reduce the likelihood of human error eight-fold in directional number entry systems. Determining whether a software implementation abides by the requirements is a time consuming task for regulatory bodies and hospital procurement departments. In this paper we show how software testing techniques can be used to classify various software implementations in order to determine whether the given number entry system satisfies specifications.
Prediction of Active Site Cleft Using Support Vector Machines

Computational tools are available today for the detection and delineation of the clefts and cavities in protein 3D structure and ranking them on the basis of probable binding site clefts. There is a need to improve the ranking of clefts and accuracy of predicting catalytic site clefts. Our results show that the distance of the clefts from protein centroid and sequence entropy of the lining residues, when used in conjunction with the volume, are valuable descriptors for predicting the catalytic site. We have applied the SVM approach for recognizing and ranking the active site clefts and tested its performance using different combinations of attributes. In both the ligand-bound and the unbound forms of structures, our method correctly predicts the active site clefts in 73% of cases at rank one. If we consider the results at rank 3 (i.e., the correct solution is among one of the top three solutions), the correctly predicted cases are 94% and 90% for the bound and the unbound forms of structures, respectively. Our approach improves the ranking of binding site clefts in comparison with CASTp and is comparable to other existing methods like Fpocket. Although the data set for training the SVM approach is rather small in size, the results are encouraging for the method to be used as complementary to other existing tools.
Prevalence of birth defects among infants of Gulf War veterans in Arkansas, Arizona, California, Georgia, Hawaii, and Iowa, 1989-1993.

BACKGROUND Epidemiologic studies of birth defects among infants of Gulf War veterans (GWV) have been limited to military hospitals, anomalies diagnosed among newborns, or self-reported data. This study was conducted to measure the prevalence of birth defects among infants of GWVs and nondeployed veterans (NDV) in states that conducted active case ascertainment of birth defects between 1989-93. METHODS Military records of 684,645 GWVs and 1,587,102 NDVs were electronically linked with 2,314,908 birth certficates from Arizona, Hawaii, Iowa, and selected counties of Arkansas, California, and Georgia; 11,961 GWV infants and 33,052 NDV infants were identified. Of these, 450 infants had mothers who served in the Gulf War, and 3966 had NDV mothers. RESULTS Infants conceived postwar to male GWVs had significantly higher prevalence of tricuspid valve insufficicieny (relative risk [RR], 2.7; 95% confidence interval [CI], 1.1-6.6; p = 0.039) and aortic valve stenosis (RR, 6.0; 95% CI, 1.2-31.0; p = 0.026) compared to infants conceived postwar to NDV males. Among infants of male GWVs, aortic valve stenosis (RR, 163; 95% CI, 0.09-294; p = 0.011) and renal agenesis or hypoplasia (RR, 16.3; 95% CI, 0.09-294; p = 0.011) were significantly higher among infants conceived postwar than prewar. Hypospadias was significantly higher among infant sons conceived postwar to GWV women compared to NDV women (RR, 6.3; 95% CI, 1.5-26.3; p = 0.015). CONCLUSION We observed a higher prevalence of tricuspid valve insufficiency, aortic valve stenosis, and renal agenesis or hypoplasia among infants conceived postwar to GWV men, and a higher prevalence of hypospadias among infants conceived postwar to female GWVs. We did not have the ability to determine if the excess was caused by inherited or environmental factors, or was due to chance because of myriad reasons, including multiple comparisons. Although the statistical power was sufficient to compare the combined birth defects prevalence, larger sample sizes were needed for less frequent individual component defects.
Epigenetic mechanisms in the development and maintenance of dopaminergic neurons

Mesodiencephalic dopaminergic (mdDA) neurons are located in the ventral mesodiencephalon and are involved in psychiatric disorders and severely affected in neurodegenerative diseases such as Parkinson’s disease. mdDA neuronal development has received much attention in the last 15 years and many transcription factors involved in mdDA specification have been discovered. More recently however, the impact of epigenetic regulation has come into focus, and it’s emerging that the processes of histone modification and DNA methylation form the basis of genetic switches that operate during mdDA development. Here, we review the epigenetic control of mdDA development, maturation and maintenance. As we highlight, epigenetic mechanisms play a pivotal role in all of these processes and the knowledge gathered from studying epigenetics in these contexts may aid our understanding of mdDA-related pathologies.
Using CHIRPS Dataset to Assess Wet and Dry Conditions along the Semiarid Central-Western Argentina

The Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset was conceived as a tool for monitoring drought and environmental change over land. Recent validation efforts along South America have assessed its suitability for reproducing the main spatial and temporal features of precipitation. Nevertheless, little has been done regarding the ability of CHIRPS for the assessment of wet and dry conditions, particularly in areas where in situ precipitation records are scarce. In this paper, we investigated the performance of CHIRPS for monitoring wet and dry events along the semiarid Central-Western Argentina. Using the Standardized Precipitation Index (SPI), we compared the CHIRPS database with records from 49 meteorological stations along the study area for the period 1987–2016. Results indicate that the CHIRPS dataset adequately reproduced the temporal variability of SPI on multiple timescales (1 month, 3 months, and 6 months), particularly in the region dominated by warm season precipitation. The large overestimation of the seasonal precipitation in the region dominated by cold season precipitation can introduce errors that are reflected in the performance of CHIRPS over the western portion of the domain. The frequency of wet and dry classes was accurately reproduced by CHIRPS on timescales larger than 1 month (SPI1), given the existence of a wet bias that produces an underestimation of the frequency of zero values. This bias is further translated to the evaluation of the SPI1 during the spatial and temporal assessment of historical dry (1998) and wet (2016) events, especially for the classification of extreme dry/wet months. The results from the evaluation indicate that CHIRPS is a suitable tool for assessing dry and wet conditions for timescales longer than 1 month and can support decision-making process within the hydrometeorological agencies over the region.
Proximity-Based Anomaly Detection Using Sparse Structure Learning

We consider the task of performing anomaly detection in highly noisy multivariate data. In many applications involving real-valued time-series data, such as physical sensor data and economic metrics, discovering changes and anomalies in the way variables depend on one another is of particular importance. Our goal is to robustly compute the “correlation anomaly” score of each variable by comparing the test data with reference data, even when some of the variables are highly correlated (and thus collinearity exists). To remove seeming dependencies introduced by noise, we focus on the most significant dependencies for each variable. We perform this “neighborhood selection” in an adaptive manner by fitting a sparse graphical Gaussian model. Instead of traditional covariance selection procedures, we solve this problem as maximum likelihood estimation of the precision matrix (inverse covariance matrix) under the L1 penalty. Then the anomaly score for each variable is computed by evaluating the distances between the fitted conditional distributions within the Markov blanket for that variable, for the (two) data sets to be compared. Using real-world data, we demonstrate that our matrix-based sparse structure learning approach successfully detects correlation anomalies under collinearities and heavy noise.
Dealing with Sparse Document and Topic Representations: Lab Report for CHiC 2012

We will report on the participation of GESIS at the first CHiC workshop (Cultural Heritage in CLEF). Being held for the first time, no prior experience with the new data set, a document dump of Europeana with ca. 23 million documents, exists. The most prominent issues that arose from pretests with this test collection were the very unspecific topics and sparse document representations. Only half of the topics (26/50) contained a description and the titles were usually short with just around two words. Therefore we focused on three different term suggestion and query expansion mechanisms to surpass the sparse topical description. We used two methods that build on concept extraction from Wikipedia and on a method that applied co-occurrence statistics on the available Europeana corpus. In the following paper we will present the approaches and preliminary results from their assessments.
SmartReflection: Efficient Introspection in Java

In the last few years the interest in reflection has grown and many modern programming languages/environments (e.g., Java and .NET) have provided the programmer with reflective mechanisms, i.e., with the ability of dynamically looking into (introspect) the structure of the code from the code itself. In spite of its evident usefulness, reflection has many detractors, who claim that it is too inecient to be used with real profit. In this work, we have investigated about the performance issue in the context of the Java reflection library and presented a dierent approach to the introspection in Java that improves its performances. The basic idea of the proposed approach consists of moving most of the overhead due to the dynamic introspection from run-time to compiletime. The eciency improvement has been proved by providing a new reflection library compliant ‐ that is, it provides exactly the same services ‐, with the standard Java reflection library based on the proposed approach. This paper is focused on speeding up the reification and the invocation of methods, i.e., on the class SmartMethod that replaces the class Method of the standard reflection library.
SoMap: Dynamic Clustering and Ranking of Geotagged Posts

This demo presents SoMap, a web-based platform that provides new scalable methods to aggregate, analyse and valorise large collections of heterogeneous social data in urban contexts. The platform relies on geotagged data extracted from social networks and microblogging applications such as Instagram, Flickr and Twitter and on Points Of Interest gathered from OpenStreetMap. It could be very insightful and interesting for data scientists and decision-makers. SoMap enables dynamic clustering of filtered social data in order to display it on a map in a combined form. The key components of this platform are the clustering module, which relies on a scalable algorithm described in this paper, and the ranking algorithm that combines the popularity of the posts, their location and their link to the points of interest found in the neighbourhood. The system further detects mobility patterns by identifying and aggregating trajectories for all the users. SoMap will be demonstrated through several examples that highlight all of its functionalities and reveal its effectiveness and usefulness.