Miracle-dz/UniFAR-FTUs huggingface dataset:
Should I stay or should I go? Individual movement decisions during group departures in red-fronted lemurs

Collective movements are essential for maintaining group cohesion. However, group members can have different optimal departure times, depending on individual, social and contextual factors whose relative importance remains poorly known. We, therefore, studied collective departures in four groups of red-fronted lemurs (Eulemur rufifrons) in Kirindy Forest, Madagascar, to investigate the influence of an individual's age, sex, their affiliative relationships and their proximity to other group members at the time of departure on their individual departure decision. We recorded behavioural and spatial data on individual departures during 167 group movements and conducted group scans (181–279 per group) to assess affiliative relationships. All factors influenced individual departures. Both affiliation and proximity determined a mimetic joining process in which dyads with stronger affiliative bonds departed in closer succession, and individuals followed the initiator and predecessors more quickly when they were in closer proximity at departure. While the influence of affiliation is common, the effect of inter-individual distance has rarely been considered in groups with heterogeneous social relationships. Although local rules influenced joining, the overall movement pattern was mainly determined by individual traits: juveniles took protected central positions, while females made up the van and males brought up the rear. Individual needs, expressed in the departure order, to an extent overruled the effect of affiliation. These results highlight the importance of considering individual, social and contextual factors collectively in the study of collective movements.
Water-saving Rice Production Technologies in Krishna Western Delta Command of Andhra Pradesh – An Economic Analysis

The economic analysis of water-saving rice production technologies, viz. system of rice intensification (SRI), semi-dry and rotational irrigation vis-a-vis farmers’ practice has been carried out based on the study executed in Modukuru pilot area of Guntur district of Andhra Pradesh. Among the three water-saving rice production technologies analyzed, the total cost of cultivation has been recorded highest in SRI (Rs 58645/ha), followed by rotational (Rs 47140/ha) and semi-dry (Rs 39321/ha). But, the per hectare yield has been found highest in SRI (6.85 t), followed by semi-dry (6.66 t) and rotational (6.2 t), inferring that all the three technologies have recorded higher yields over farmers’ practice of 5.5 t/ha. However, the net returns and B-C ratio are maximum in semi-dry (Rs 43,484/ha; 1.11), followed by rotational (Rs 30,085; 0.64) and SRI (Rs 26,466/ha; 0.45) methods. Similarly, the water-use efficiency has been found highest in SRI (8.53 kg/ ha-mm), followed by semi-dry (8.02 kg/ha-mm) and rotational (7.33 kg/ ha-mm) methods, while the water-use efficiency benefit (Rs/ha-mm) has been recorded maximum in semi-dry (52.39), followed by SRI (42.08) and rotational (35.56) methods. With the initiation of Andhra Pradesh Water Management Project, Bapatla, the area under semi-dry rice cultivation has been found increasing over a period of four years, from 0.6 ha in 2004-2005 to 22 ha in 2007 -2008.
Computer-Program Model for Predicting Horizontally and Vertically Polarized VLF Atmospheric Radio Noise at Elevated Receivers

Abstract : A computer program has been developed that can predict horizontally and vertically polarized atmospheric radio noise at any altitude or location in the earth-ionosphere waveguide in the very-low-frequency (VLF) range from 10 to 30 kHz. The new program, HORNS, uses the outputs of two previously written programs, COMPWR and NOISLAN, which predict the vertical electric noise field at the ground. The HORNS program computes all the field components at any altitude using the vertical electric field at the earth's surface as a basis. Predicted values from several versions of the new model have been compared with presently available data. The results are encouraging, but more data are needed to test the model.
CW high power 1.24 /spl mu/m and 1.48 /spl mu/m Raman lasers based on low loss phosphosilicate fibre

The authors propose a new simple configuration for 1.24 and 1.48 /spl mu/m Raman fibre lasers which are promising pumping sources for 1.31 /spl mu/m Raman amplifiers and Er-doped fibre amplifiers, respectively. Efficient resonant conversion of CW 1.06 /spl mu/m radiation to the first (1.24 /spl mu/m) and second (1.48 /spl mu/m) Raman Stokes in a phosphosilicate fibre is demonstrated for the first time.
Differentiation of Crystal Cells, Gravity-Sensing Cells in the Placozoan Trichoplax adhaerens

Trichoplax adhaerens are simple animals with no nervous system, muscles or body axis. Nevertheless, Trichoplax demonstrate complex behaviors, including responses to the direction of the gravity vector. They have only six somatic cell types, and one of them, crystal cells, has been implicated in gravity reception. Multiple crystal cells are scattered near the rim of the pancake-shaped animal; each contains a cup-shaped nucleus and an intracellular crystal, which aligns its position according to the gravity force. Little is known about the development of any cell type in Trichoplax, which, in the laboratory, propagate exclusively by binary fission. Electron and light microscopy were used to investigate the stages by which crystal cells develop their mature phenotypes and distributions. Nascent crystal cells, identified by their possession of a small crystal, were located farther from the rim than mature crystal cells, indicating that crystal cells undergo displacement during maturation. They were elongated in shape and their nucleus was rounded. The crystal develops inside a vacuole flanked by multiple mitochondria, which, perhaps, supply molecules needed for the biomineralization process underlying crystal formation. This research sheds light on the development of unique cells with internal biomineralization and poses questions for further research.
Skid-to-turn missile autopilot design using scheduled eigenstructure assignment technique

Abstract This paper presents an application of adaptive control techniques to the design of skid-to-turn missile autopilot. The involved simplified adaptive controller is developed by combining gain scheduling approach with the eigenstructure assignment control design. A linear interpolation method is proposed to generate linear parameter-varying controller from a finite set of linear time-invariant controllers. Results of simulations are reported to demonstrate the performance, stability, and robustness of the considered autopilot.
Machine Learning Mini Batch K-means and Business Intelligence Utilization for Credit Card Customer Segmentation

An effective marketing strategy is a method to identify the customers well. One of the methods is by performing a customer segmentation. This study provided an illustration of customer segmentation based on the RFM (Recency, Frequency, Monetary) analysis using a machine learning clustering that can be combined with customer segmentation based on demography, geography, and customer habit through data warehouse-based business intelligence. The purpose of classifying the customers based on the RFM and machine learning clustering analyses was to make a customer level. Meanwhile, customer segmentation based on demography, geography, and behavior was to classify the customers with the same characteristics. The combination of both provided a better analysis result in understanding customers. This study also showed a result that minibatch kmeans was the machine learning model with the rapid performance in clustering 3-dimension data, namely recency, frequency, and monetary. Keywords—Customer segmentation; machine learning; business intelligence; data warehouse
Urban Road Pricing: Modeling Public Acceptance

Acceptability is considered the most important barrier in establishing a congestion pricing scheme. Using data from an extensive questionnaire survey conducted in the central area of Athens, Greece, in 2008, this paper examines attitudes toward traffic congestion, choice of travel mode, and revenue allocation, which can influence the acceptability of congestion pricing. Since one of the major goals of congestion pricing is to discourage personal automobile use, we also examine the choice of mode following the implementation of a congestion pricing system. Further, we developed a multivariate probit model to investigate the factors that influence public perception regarding the effectiveness of six traffic-management measures. Results from this study can assist in better understanding the factors that affect public acceptance of congestion pricing in urban areas.
Evaluating Deep and Statistical Machine Learning Models in the Classification of Breast Cancer from Digital Mammograms

—The application of artificial intelligence techniques in computer aided detection and diagnosis problems has been among the most promising areas with interest from the scientific community and healthcare industry. Recently, deep learning has become the prime tool for such application with many studies focusing on developing variants that optimize diagnostic performance. Despite the widely accepted success of this class of techniques in this application by the scientific community, it is not prudent to consider it as the only tool available for such purpose. In particular, statistical machine learning offers a variety of techniques that can also be applied at a much lower computational cost. Unfortunately, the results from both strategies cannot be directly compared due to the differences in experimental setups and datasets used in available research studies. Therefore, we focus in this study on this direct comparison using the same dataset and similar data preprocessing as the input to both. We compare statistical machine learning to deep learning in the context of computer-aided detection of breast cancer from mammographic images. The results are compared using diagnostic performance metrics and suggest that simpler statistical machine learning techniques may provide better performance with simpler architectures that allow explanation of results.
Network Relationships in Knowledge Based Service Firms: Variance in Terms of Firm Size

Networks are critical in the growth of knowledge intensive business services (KIBS) and include networks with service providers, suppliers, competitors, customers and investors. The research evaluates the variance of network relationships in terms of firm size and involved cross sectional survey of KIBS firms in India. Firms were classified into four groups in terms of number of employees: up to 100; 101 to 1000; 1001 to 10,000; and with above 10,000 employees. The study finds there is a significant difference in network relationships with customers and investors for firms with above 10000 employees as compared to firms with upto 100 employees. At the same time no difference across firms of different sizes is found in terms of network relationships with suppliers and competitors. The study also finds that as a firm crosses the threshold of 100 employees, network relationships across different groups do not have differences that are significant.
Effect of Captive Stores on Internal Weapons Bay Floor Pressure Distributions

T HE new generation of stores to be used on the F-22 and joint strike fighter (JSF) are designed as efficiently packaged, small, highly lethal minimissiles. Because of their lighter weights and smaller moments of inertia, these small smart bombs (SSB) are more easily perturbed by flowfield effects than heavier stores carried externally in older aircraft. This can result in unsafe separations and targeting inaccuracies. For this reason, the majority of studies on internal weapons bays are focused on the stores’ separation problem. A recent investigation on wind-tunnel and flight-test comparisons is given by Grove et al. [1]. However, aircraft weapons bays exposed to high subsonic or supersonic flows are subjected to an intense aeroacoustic field inside the bay. TheM219 cavity [2] is often used as a test case for computational fluid dynamic (CFD) and wind-tunnel test comparisons. For a length-to-depth ratio of 5, Lee et al. [3] measured the frequency of the pressure oscillations on the cavity floor. The frequency for the first three modes at a Mach number of M 1:11when scaled to a typical weapons bay of 13 ft length gives values for f1 23 Hz, f2 56 Hz, and f3 90 Hz, respectively. The large pressure oscillations at these low frequencies can lead to structural fatigue of theweapons bay walls and damages to the stores and electronic equipment. Data on the effect of small stores typical of the dimensions of the SSB on the unsteady pressure inside aweapons bay are lacking. This paper presents some preliminary results on the floor pressure measurements of a generic weapons bay for small stores at forwardand aft-release positions. The perturbations introduced by the stores are found to cause significant changes in the acoustic wave intensities inside the M219 cavity.
Taxonomy of outsourcing decision models

This article proposes a taxonomy of outsourcing decision models. The proposed taxonomy may assist practitioners in their decision-making and researchers in the identification, evaluation and classification of decision models. Further, this article also provides an overview and evaluation of existing outsourcing decision models, and assesses them for their applicability to the outsourcing decision process. In particular, this article finds that the outsourcing decision models proposed in the literature have limitations in their applicability to the outsourcing decision process.
House and Senate

In the new Third Edition, Ross Baker once again uses his unique approach interviews with senators who were formerly members of the House, as well as with journalists, lobbyists, and staff members to paint a clear and colorful portrait of the two houses, which remain distinct, and often antagonistic, partners. House and Senate allows students to peek into the hidden corners of Capitol Hill and offers a fascinating insider s view of the two chambers. "
Bernoulli Equation in the Mitral Valve of Heart

Background: The mechanics of the mitral valve leaflet as a nonlinear, inelastic and anisotropic soft tissue results from an integrated response of many mathematical/physical indexes’ that illustrate the tissue. Objectives: The objective of this paper is to study and give an algorithm for the mechanisms of mitral valve of the heart based on mathematical techniques and Bernoulli’s equation. Methods and Results: Utilizing mathematical techniques and Bernoulli’s equation, we can make a geometrical modeling of the mitral valve leaflets and give available and valuable clinical benefit information of the Mitral valve behaviors for physician. Echocardiography was performed on healthy volunteers. Data evaluated included: velocity (radial, longitudinal, rotational and vector point), displacement (longitudinal and rotational), strain rate (longitudinal and circumferential) and strain (radial, longitudinal and circumferential) of all leaflet segments. Using these data, force vectors of myocardial samples and a new formula that was provided by Bernoulli equation, we were able to see what’s happening around the mitral valve of heart. All data were estimated/run by MATLAB software.
Effects of Arachidonic Acid Metabolites on Cardiovascular Health and Disease

Arachidonic acid (AA) is an essential fatty acid that is released by phospholipids in cell membranes and metabolized by cyclooxygenase (COX), cytochrome P450 (CYP) enzymes, and lipid oxygenase (LOX) pathways to regulate complex cardiovascular function under physiological and pathological conditions. Various AA metabolites include prostaglandins, prostacyclin, thromboxanes, hydroxyeicosatetraenoic acids, leukotrienes, lipoxins, and epoxyeicosatrienoic acids. The AA metabolites play important and differential roles in the modulation of vascular tone, and cardiovascular complications including atherosclerosis, hypertension, and myocardial infarction upon actions to different receptors and vascular beds. This article reviews the roles of AA metabolism in cardiovascular health and disease as well as their potential therapeutic implication.
The Influence of Selected Meteorological Factors on the Prevalence and Course of Stroke

Background: The objective of this study was to evaluate the impact of weather factors on stroke parameters. Methods: This retrospective study analyzed the records of stroke patients concerning the influence of meteorological conditions and moon phases on stroke parameters. Results: The study group consisted of 402 patients aged between 20 and 102; women constituted 49.8% of the subjects. Ischaemic stroke was diagnosed in 90.5% of patients and hemorrhagic stroke was diagnosed in 9.5% of patients. The highest number of hospitalizations due to stroke was observed in January (48 events); the lowest number was observed in July (23 events). There was no statistically significant correlation between the meteorological parameters on the day of onset and the preceding day of stroke and the neurological status (NIHSS) of patients. Mean air temperature on the day of stroke and the day preceding stroke was significantly lower in the group of patients discharged with a very good functional status (≤2 points in modified Rankin scale (mRS)) compared to the patients with a bad functional status (>2 points in mRS); respectively: 7.98 ± 8.01 vs. 9.63 ± 7.78; p = 0.041 and 8.13 ± 7.72 vs. 9.70 ± 7.50; p = 0.048). Humidity above 75% on the day of stroke was found to be a factor for excellent functional state (RR 1.61; p = 0.016). The total anterior circulation infarcts (in comparison with stroke in the other localization) were more frequent (70%) during a third quarter moon (p = 0.011). The following parameters had a significant influence on the number of stroke cases in relation to autumn having the lowest number of onsets: mean temperature (OR 1.019 95% CI 1.014–1.024, p < 0.000), humidity (OR 1.028, CI 1.023–1.034, p < 0.0001), wind speed (OR 0.923, 95% CI 0.909–0.937, p < 0.0001), insolation (OR 0.885, 95% CI 0.869–0.902, p < 0.0001), precipitation (OR 0.914, 95% CI 0.884–0.946, p < 0.0001). Conclusion: Air humidity and air temperature on the day of stroke onset as well as air temperature on the day preceding stroke are important for the functional status of patients in the acute disease period. A combination of the following meteorological parameters: lowered mean temperature and low sunshine, high humidity and high wind speed all increase the risk of stroke during the winter period. High humidity combined with high precipitation, low wind speed and low sunshine in the autumn period are associated with the lowest stroke incidence risk. A possible relationship between phases of the moon and the incidence requires further investigation.
Damage detection in aircraft structures using dynamically measured static flexibility matrices

Two methods for detecting the location of structural damage in an aircraft fuselage using modal test data are presented. Both methods use the dynamically measured static flexibility matrix, which is assembled from a combination of measured modal vectors, frequencies, and driving point residual flexibilities. As a consequence, neither method requires a mode-to-mode correlation, and both avoid tedious modal discrimination and selection. The first method detects damage as a softening in the point flexibility components, which are the diagonal entries in the flexibility matrix. The second method detects damage from the disassembled elemental stiffnesses as determined using a presumed connectivity. Vibration data from a laser vibrometer is used to measure the modal mechanics of a DC9 aircraft fuselage before and after induced weakening in a longitudinal stringer. Both methods are shown to detect the location of the damage, primarily because the normal stiffness of the reinforced shell of the fuselage is localized to a few square centimeters.
Geosynchronous satellite maneuver detection and orbit recovery using ground based optical tracking

Geosynchronous satellite orbit maintenance is a very important issue. Satellites maneuver frequently requiring the ability to detect unknown maneuvers for target satellites and quickly recover an accurate orbit. This study uses angles only ground based optical tracking to detect maneuvers and recover orbits for geosynchronous satellites. Using the Analytical Graphics Inc. Orbit Determination Tool Kit sequential estimation software, a sequential estimation filter was "tuned" and validated in various ways. Then, a parametric study of maneuver size and time required to detect a maneuver was done via simulation. Simulated maneuvers ranging fiom Av's of 0.01 m/s to 1.0 m/s are discussed. Also examined are multiple methods to recover the orbit after such maneuvers are detected. Orbits are recovered for simulated maneuvers and for a real data case of unknown maneuver size. This work is important towards developing more automatic methods of detecting maneuvers for a large population of active geosynchronous satellites. Specific contributions made by this thesis include the following: the process and results of "tuning" of the sequential filter for a geosynchronous satellite using high accuracy ground based optical tracking data, the methods of orbit and covariance validation including an orbit overlap analysis and a statistical method using measurements, a parametric study for maneuver detection, and exploring methods for recovering post maneuver orbits quickly and accurately. With the tuned filter and optical tracking, simulations showed that a Av of 1.0 m/s could be detected as soon as 15 minutes after the maneuver, a Av of 0.1 rn/s could be discernible within 6 hours and easily detected by 12 hours, and a Av of 0.01 m/s took fiom 12 to 24 hours to detect with confidence. The best demonstrated means for post-maneuver orbit recovery utilized a method of estimating the approximate maneuver time using the pre-maneuver filter orbit and an approximate post maneuver orbit followed by the "sprinkling" of a number of maneuvers over that period with Av's of 0 d s but with finite covariances, and then filtering through that period. Thesis Supervisor: Dr. Richard I. Abbot Title: Technical Staff, the MIT Lincoln Laboratory Thesis Supervisor: Dr. Jayant Sharma Title: Technical Staff, the MIT Lincoln Laboratory Thesis Supervisor: Dr. Jeffrey A. Hoffman Title: Professor of Aerospace Engineering
Regular Wave Measurements on a Submerged Semicircular Breakwater

The submerged semicircular breakwater (SBW) is mainly adopted to prevent beach erosion and to reduce the incident wave energy on its leeside, if it is used in front of a vertical breakwater. In addition, it facilitates the premature wave breaking, which in turn causes the reduction in wave energy. The dynamic pressures and forces exerted on the submerged SBW with 7%, 11 %, and 17% of the exposed surface area with perforations on its seaside due to regular waves were measured. The hydrodynamic characteristics such as variations in the dimensionless pressures and forces, reflection and transmission coefficients on the semicircular caisson as a function of scattering parameter for three different water depths are presented and an optimum depth of submergence is arrived. The results on the above stated variables for seaside perforated SBWs are compared with the results of an impermeable SBW to study the effect of perforations.