Miracle-dz/UniFAR-FTUs huggingface dataset:
Beta diversity of aquatic invertebrates increases along an altitudinal gradient in a Neotropical mountain

Mountains harbor rich biodiversity and high levels of endemism, particularly due to changes in environmental conditions over short spatial distances, which affects species distribution and composition. Studies on mountain ecosystems are increasingly needed, as mountains are highly threatened despite providing ecosystem services, such as water supply for half of the human population. We aimed to understand the patterns and drivers of alpha and beta diversities of aquatic invertebrates in headwater streams along an altitudinal gradient in the second largest South American mountain range, the Espinhaço mountains. Headwater streams were selected at each 100 m of elevation along an altitudinal gradient ranging from 800 to 1400 m asl, where three substrate types per stream were sampled: leaf litter, gravel, and cobbles. Environmental variables were sampled to represent local riparian canopy cover, instream physical habitat, water quality, climatic data, and land use. Generalized linear models and mixed models were used to test relationships between altitude and the richness and abundance of invertebrates and to assess the influence of environmental variables on the same metrics. Patterns of spatial variation in aquatic invertebrate assemblages along the altitudinal gradient were assessed using multiplicative beta diversity partitioning. The richness and abundance of aquatic invertebrates decreased with increasing altitude, whereas beta diversity increased with increasing altitude. Significant differences in assemblage composition and in relative abundance of invertebrates were observed for both substrates and altitude. We thus show that the high regional beta diversity in aquatic ecosystems in the studied site is due to the high turnover among areas.
WORKINGS OF THE MELTING POT : SOCIAL NETWORKS AND THE EVOLUTION OF POPULATION ATTRIBUTES

This paper links the two nascent economic literatures on social networks and cultural assimilation by investigating the evolution of population attributes in a simple model where agents are influenced by their acquaintances. The main conclusion of the analysis is that attributes converge to a melting-pot equilibrium, where everyone is identical, provided the social network exhibits a sufficient degree of interconnectedness. When the model is extended to allow an expanding acquaintance set, convergence is guaranteed provided a weaker interconnectedness condition is satisfied, and convergence is rapid. If the intensity of interactions with acquaintances becomes endogenous, convergence (when it occurs) is slowed when agents prefer to interact with people like themselves and hastened when interaction with dissimilar agents is preferred. JEL Code: J00, J10. Jan K. Brueckner Department of Economics University of Illinois at Urbana-Champaign 1206 South Sixth St. Champaign, IL 61820 USA jbrueckn@uiuc.edu Oleg Smirnov Department of Geography University of Illinois at Urbana-Champaign 607 South Mathews Ave. Urbana, IL 61801 USA osmirnov@uiuc.edu Workings of the Melting Pot: Social Networks and the Evolution of Population Attributes
Effect of reduced rates of glyphosate and paraquat simulating drift on sorghum crop

Herbicide application for crop desiccation or weed control has been growing due to the expansion of the Brazilian agricultural frontier. This fact increases the risks of drift to susceptible crops grown in the vicinity areas; however, several questions are frequently raised about possible losses in grain yield of these crops due to herbicide drift. The objective of this work was to evaluate injuries caused by reduced rates of glyphosate and paraquat simulating drift and its effect on sorghum plant development and grain production. The study was carried out during the crop growing seasons of 1996/97 and 1997/98. The hybrid BR 700 was used in a randomized complete block design, with 12 treatments and four replications. The treatments were performed by the combination of two herbicides with five concentrations of simulated drift: 2, 4, 6, 8 and 12% of the recommended rates (1,440 g ha-1 of glyphosate and 400 g ha-1 of paraquat), and two check treatments without herbicide application for compressions. Leaf area and dry matter weight were not affected by drift, whereas plant height was reduced, especially by the highest herbicide reduced rate. The chlorophyll content was slightly affected in the growing season 1997/98, whereas the visual symptoms, in both growing seasons, resulted in higher percentage of injuries while concentration drift increased. The leaf damages observed were greater at the growing season 1996/97. Also in this growing season, the final stand was reduced by the highest glyphosate rate. As far as grain production is concerned, only the growing season 1996/97 presented yield reduction due to drift, when the highest rate of glyphosate resulted in the lowest grain weight. In the 1997/98 trial, there was no drift effect on the productivity characteristics probably due to climate factors. The sorghum plant is susceptible to the action of non-selective herbicides; reduced rates of glyphosate as well as paraquat, at 12% or lower of the recommended dosage may influence sorghum plant development and grain production, especially when the weather conditions are favorable to the action of these herbicides.
Robots for Cleaning Photovoltaic Panels: State of the Art and Future Prospects

The growing interest in use of renewable energy sources, such as photovoltaic energy systems, occurs due to the high cost of conventional energy sources and the environmental awareness linked to renewable sources. For photovoltaic panels efficient operation, it is necessary the system presents appropriate cleaning conditions to the dirt do not obstruct the solar radiation incidence. In this context, periodic cleaning of photovoltaic panels is an obvious necessity. This work aims to present a market survey and patent analysis on the use of robots to perform cleaning tasks on photovoltaic panels. For that, the Brazilian and international literature were consulted. As a result, it was noted the existence of different solutions for cleaning photovoltaic panels, all with positive and negative aspects in practical terms. With this study it was also possible to map the technology of robotics for cleaning photovoltaic panels.
Summary Growth requirements and expression of LDL receptor and HMG-CoA reductase in Hep G 2 hepatoblastoma cells cultured in a chemically defined medium

Mammalian cells acquire cholesterol either from de novo synthesis from acetyl-CoA or from plasma lipoproteins by receptor-mediated endocytosis (reviewed by Goldstein and Brown, 1990). The receptor responsible for the uptake of plasma low density lipoprotein (LDL) is a membrane glycoprotein which binds the lipoprotein in the presence of Ca2+ and promotes the internalization and degradation within the lysosomal compartment (Brown and Goldstein, 1986). The expression of the LDL receptor is highest in tissues which utilize cholesterol as a substrate for the synthesis of steroid hormones (adrenal glands, ovary and testis) or bile acids (liver parenchymal cells) and thus appears to be controlled in a tissue-specific manner (Spady et al., 1983). When expressed on the basis of weight of the organ the liver is by far the most important tissue for clearance of plasma LDL, accounting for more than 70% of the total uptake (Spady et al., 1983), and thus appears to have a major role in determining the plasma cholesterol level. The importance of the liver in controlling the plasma cholesterol is demonstrated by the observation that transplantation of a liver into a homozygous familial hypercholesterolemic patient resulted in a reduction of her plasma cholesterol level from 1079 mg/dl to 302 mg/dl (Bilheimer et al., 1984). The basis for the regulation of the LDL receptor in hepatocytes is not completely understood. Experiments in vivo indicate that the primary response which takes place following changes in cholesterol supply is a change in de novo cholesterol synthesis and that LDL receptor activity varies only if the changes in the rate of cholesterol synthesis are inadequate to meet the new demands (Spady et al., 1985). Yet, studies with cells in culture indicate that in at least some conditions the HMG-CoA (3-hydroxy-3-methylglutaryl coenzyme A) reductase and LDL receptor are regulated in a co-ordinate fashion (Brown and Goldstein, 1986). This conclusion has been strengthened by the observation that the 5′ flanking regions of the HMG-CoA reductase and 531 Journal of Cell Science 103, 531-539 (1992) Printed in Great Britain © The Company of Biologists Limited 1992
Compressed Sensing for Diffusion MRI of the Mouse Brain: A Trade-off of Spatial and Directional Information

Compressed Sensing for Diffusion MRI of the Mouse Brain: A Trade-off of Spatial and Directional Information Anthony Albert Salerno Master of Science Department of Medical Biophysics University of Toronto 2018 Diffusion Magnetic Resonance Imaging (MRI) uses loss of signal coherence caused by movement of water molecules to determine how water diffuses in tissue. These scans are known to take a significant amount of time owing to the repeated acquisition of images, each measuring diffusion for a particular direction and weighting. Emerging methods based on collection of increasingly large numbers of diffusion directions and/or weightings promise to provide a more detailed characterization of brain microstructure than previously possible. However, because the time required for these methods can render them impractical, I present a method of acquiring and reconstructing diffusion MRI data based on Compressed Sensing (CS) that enables flexible trade-off between spatial sampling and diffusion direction/weighting sampling. This method enables the collection of more diffusion data in a given scan time at the cost of extended reconstruction time.
The high-performance work system and commitment of the Portuguese Navy personnel

ABSTRACT This study evaluates the relationship between the high-performance work system (HPWS) as perceived by the Portuguese Navy military and their affective (AC), normative (NC), and continuance commitment (CC). The sample is representative and composed of 1,003 individuals (officers, warrant/petty officers, and seamen—as a reference, these last two categories are called ratings in the British Royal Navy, and enlisted in the United States Navy) from different naval units. A structural models analysis was carried out, and the results showed, as expected, that the perception of an HPWS was positively related to the commitment of the military personnel, in both its affective and normative dimensions. Nevertheless, contrary to our expectations, we also observed that the perception of an HPWS was positively related to the continuance commitment as well. On the other hand, we examined the moderator role played by the professional category—the relationship between the perception of the HPWS and the AC was stronger in commissioned officers and seamen than in warrant and petty officers—and by the contractual relationship. In the latter, the relationship between the HPWS and the AC and the CC was stronger in the individuals having a fixed-term contract than in those with a permanent position. The theoretical and practical implications of these results will be discussed.
Development and validation of the Work Environment Complexity Scale for leaders

Purpose The purpose of this paper is to develop and validate a Work Environment Complexity (WEC) Scale for leaders. Design/methodology/approach The paper uses both cross-sectional and longitudinal data, gathered in the course of major organisational restructuring, using samples from employees (n=305) and leaders (n=120) in two health care organisations. Findings The research developed and validated a scale of WEC for leaders with two factors: frequent change and events, and uncertain work demands. Comparisons between samples suggest diverging employee and leadership representations of WEC. Practical implications Being the first scale to measure the comprehensive construct of WEC, a foundation is laid to measure the amount of complexity in a leader’s work and the functioning of leaders with regards to WEC. Originality/value This paper contributes to leadership research and practice by clarifying the construct of WEC for leaders empirically and validating a bidimensional scale of WEC.
(ANURA, BUFONIDAE)

─ Herein, we describe the distribution, call, diet, and niche model of Osornophryne percrassa. This species has been recorded at 23 locations of Colombia, 14 of which are reported in this work. In addition, we reported the first record for the Department of Valle del Cauca, southern Colombia. Based on the points of occurrence, we estimated the potential geographic distribution of this species through the maximum entropy algorithm, and the model prediction showed a good performance. The model shows that The Cordillera Central provides the higher habitat availability for the species occurrence, with no geographical barriers that hinder the spread of the species. We analyzed the stomach contents of 14 females. We identified 73 Arthropoda prey and nine Nematoda prey. Coleopterans and isopods were numerically and volumetrically the more important prey, respectively. We found a positive and significant correlation between snout-vent length (SVL) and head width (HW). Our data indicate that the species is a generalist/opportunistic feeder with a sit-and-wait strategy for obtaining prey. We described the vocal repertoire (advertisement and courtship calls) based on 23 advertisement calls and 11 courtship calls from a male. The advertisement call consists of 8–10 Peep notes whereas the courtship call consists of 6–9 Peep notes. The advertisement calls of O. guacamayo were similar in temporal and structural characteristics to those of O. percrassa. This is the first description of the courtship calls not only for O. percrassa but also for the genus.
New Variants of Newton's Method for Nonlinear Unconstrained Optimization Problems

In this paper, we propose new variants of Newton’s method based on quadrature formula and power mean for solving nonlinear unconstrained optimization problems. It is proved that the order of convergence of the proposed family is three. Numerical comparisons are made to show the performance of the presented methods. Furthermore, numerical experiments demonstrate that the logarithmic mean Newton’s method outperform the classical Newton’s and other variants of Newton’s method. MSC: 65H05.
Mixed Bernstein-Bézier Construction from Unstructured Mesh for Higher-order Finite Element Analysis of Plates and Shells

Bernstein polynomials possess several e cient and stable algorithms and have been widely used in engineering elds such as CAGD, computer graphics, and nite element analysis. In this paper, a mixed Bernstein basis function based higher-order nite element method is developed from a geometric view for the analysis and simulation of plate and shell structures represented by unstructured triangular and quadrilateral mesh. Triangular Bernstein-Bézier patches and tensor-product Bézier patches are constructed in a simple and intuitive way over triangular and quadrilateral elements, respectively. The hand pre nements can be easily implemented on the constructed mixed Bernstein-Bézier patches. Reissner-Mindlin theory is employed to deduce the governing equations and sti ness matrices of plates and shells. Several numerical examples including classical benchmark problems and engineering applications are studied to validate the accuracy, robustness, and convergence of the presented Bernstein-Bézier nite element method.
Advances in population ecology and species interactions in mammals

The study of mammals has promoted the development and testing of many ideas in contemporary ecology. Here we address recent developments in foraging and habitat selection, source–sink dynamics, competition (both within and between species), population cycles, predation (including apparent competition), mutualism, and biological invasions. Because mammals are appealing to the public, ecological insight gleaned from the study of mammals has disproportionate potential in educating the public about ecological principles and their application to wise management. Mammals have been central to many computational and statistical developments in recent years, including refinements to traditional approaches and metrics (e.g., capture-recapture) as well as advancements of novel and developing fields (e.g., spatial capture-recapture, occupancy modeling, integrated population models). The study of mammals also poses challenges in terms of fully characterizing dynamics in natural conditions. Ongoing climate change threatens to affect global ecosystems, and mammals provide visible and charismatic subjects for research on local and regional effects of such change as well as predictive modeling of the long-term effects on ecosystem function and stability. Although much remains to be done, the population ecology of mammals continues to be a vibrant and rapidly developing field. We anticipate that the next quarter century will prove as exciting and productive for the study of mammals as has the recent one.
Readability Analysis Based on Cognitive Assessment Using Physiological Sensing

For a given individual, the readability of a content determines the amount of cognitive load experienced during the reading. Among many physiological parameters, the brain signals provide direct information about the cognitive load. In this paper, for a silent reading scenario, electroencephalogram (EEG) signal and pupillary response are used to address both global and localized analysis of a content. The global analysis is done using the EEG data collected from a target group of readers on whether the overall content is easy or difficult to understand. The entropy analysis of left temporal brain signals is found to grossly differentiate the texts. Detailed analysis is done using the pupil dilation to localize certain difficult segments in the content. The oscillatory behavior of the pupil dilation reveals detailed characteristics of the effect of the texts on each individual. To carry out the experiment, two types (easy and difficult) of textual contents are considered which are calibrated using standard natural language processing parameters. The proposed work presents a methodology for global and detailed analysis of a content which helps in preparing the reading materials. Furthermore, the methodology provides the insights into the reading characteristics of the individuals.
VIEWPOINT The Calisthenics of Surface

I t has long been a chemist’s dream to catch a chemical reaction in the act. In a chemical reaction, reactant atoms or molecules pass over energy barriers, through transition states, and eventually convert into new chemical products. Chemists would like to observe and interfere with this process in mid-course and thereby control its outcome. The development of lasers that produce pulses of light just a few femtoseconds long has allowed researchers to initiate and track chemical reactions in the gas phase. Typically, one femtosecond pulse initiates the reaction through excitation of the reactant to a new electronic state, which drives the reactant’s nuclear motion. Another pulse, time-delayed from the first, then monitors the nuclear motion as the excited reactant decays or a new product forms. This approach gave rise to the field of femtochemistry and earned Ahmed Zewail (1946–2016) the 1999 Nobel Prize in Chemistry [1].
DeepAttest: An End-to-End Attestation Framework for Deep Neural Networks

Emerging hardware architectures for Deep Neural Networks (DNNs) are being commercialized and considered as the hardware- level Intellectual Property (IP) of the device providers. However, these intelligent devices might be abused and such vulnerability has not been identified. The unregulated usage of intelligent platforms and the lack of hardware-bounded IP protection impair the commercial advantage of the device provider and prohibit reliable technology transfer. Our goal is to design a systematic methodology that provides hardware-level IP protection and usage control for DNN applications on various platforms. To address the IP concern, we present DeepAttest, the first on-device DNN attestation method that certifies the legitimacy of the DNN program mapped to the device. DeepAttest works by designing a device-specific fingerprint which is encoded in the weights of the DNN deployed on the target platform. The embedded fingerprint (FP) is later extracted with the support of the Trusted Execution Environment (TEE). The existence of the pre-defined FP is used as the attestation criterion to determine whether the queried DNN is authenticated. Our attestation framework ensures that only authorized DNN programs yield the matching FP and are allowed for inference on the target device. DeepAttest provisions the device provider with a practical solution to limit the application usage of her manufactured hardware and prevents unauthorized or tampered DNNs from execution. We take an Algorithm/Software/Hardware co-design approach to optimize DeepAttest's overhead in terms of latency and energy consumption. To facilitate the deployment, we provide a high-level API of DeepAttest that can be seamlessly integrated into existing deep learning frameworks and TEEs for hardware-level IP protection and usage control. Extensive experiments corroborate the fidelity, reliability, security, and efficiency of DeepAttest on various DNN benchmarks and TEE-supported platforms.
Benefits of adaptive lessons for pre-class preparation in a flipped numerical methods course

ABSTRACT A challenge with flipped instruction is the pre-class preparation, where students independently learn fundamental content outside the classroom. For this pre-class learning, instructors typically assign videos with quizzes. However, this approach is the same for all and does not address differential needs. In a prior National Science Foundation (NSF) study with three schools, differences in the outcomes for blended versus flipped instruction in a numerical method course were not statistically significant, and the effect sizes were small. To diversify pre-class preparation and potentially improve outcomes in the flipped classroom, the instructor developed lessons using an adaptive platform via a new NSF grant. The adaptive platform provides personalized, flexible learning with multiple resources, including videos, text, quizzes, and simulations, with different paths depending on a student's progress. Adaptive lessons were implemented during two semesters in a flipped classroom, and the results were compared to (1) flipped instruction without adaptive lessons and (2) blended instruction. The comparisons consisted of direct assessments (i.e. exams) and student evaluations via survey. Analysis was done collectively for students and for several demographic groups. Based on direct and indirect measures, the flipped classroom with adaptive learning may be the preferred method for this and other STEM courses.
OXYGEN UPTAKE UTILISING DIFFERENT TREADMILL PROTOCOLS

The study compared five treadmill protocols (four utilising a motorised, and one a non-motorised, treadmill) on maximum oxygen uptake. The five male and five female subjects, all actively engaged in training, were assigned the tests in random order. Statistical analysis revealed no significant differences between the five protocols for maximal oxygen uptake, maximum ventilation, maximum heart rate and blood lactate inflection point, relative to maximal oxygen uptake. Significant differences were observed between the 3' protocol with incline increments of 1.5% and all other protocols on time to exhaustion (p = < 0.01) and maximum blood lactate levels (H LA, p = < 0.05). The results indicate that the protocols used in this study did not significantly influence the maximum oxygen uptake attained.