University of Louisiana at Lafayette

Due to object detection's close relationship with video analysis and image understanding, it has attracted much research attention in recent years. Traditional object detection methods are built on handcrafted features and shallow trainable architectures. Their performance easily stagnates by constructing complex ensembles that combine multiple low-level image features with high-level context from object detectors and scene classifiers. With the rapid development in deep learning, more powerful tools, which are able to learn semantic, high-level, deeper features, are introduced to address the problems existing in traditional architectures. These models behave differently in network architecture, training strategy, and optimization function. In this paper, we provide a review of deep learning-based object detection frameworks. Our review begins with a brief introduction on the history of deep learning and its representative tool, namely, the convolutional neural network. Then, we focus on typical generic object detection architectures along with some modifications and useful tricks to improve detection performance further. As distinct specific detection tasks exhibit different characteristics, we also briefly survey several specific tasks, including salient object detection, face detection, and pedestrian detection. Experimental analyses are also provided to compare various methods and draw some meaningful conclusions. Finally, several promising directions and tasks are provided to serve as guidelines for future work in both object detection and relevant neural network-based learning systems.

This revision of the classification of unicellular eukaryotes updates that of Levine et al. (1980) for the protozoa and expands it to include other protists. Whereas the previous revision was primarily to incorporate the results of ultrastructural studies, this revision incorporates results from both ultrastructural research since 1980 and molecular phylogenetic studies. We propose a scheme that is based on nameless ranked systematics. The vocabulary of the taxonomy is updated, particularly to clarify the naming of groups that have been repositioned. We recognize six clusters of eukaryotes that may represent the basic groupings similar to traditional "kingdoms." The multicellular lineages emerged from within monophyletic protist lineages: animals and fungi from Opisthokonta, plants from Archaeplastida, and brown algae from Stramenopiles.

Adsorption for water and wastewater treatment has been the subject of many research in the scientific community, focusing mainly on either equilibrium or kinetic studies. Adsorption kinetics are commonly modeled using pseudo-first and pseudo-second order rate laws. Analyses of published works in the past two decades indicated that the pseudo-second order is considered to be the superior model as it can represent many adsorption systems. However, critical assessment of modeling techniques and practices suggests that its superiority could be a consequence of currently acceptable modeling norms which tend to favor the pseudo-second order model. The partiality was due to several modeling pitfalls that are often neglected. In addition, commonly used model validation tools are often used haphazardly and redundantly. As such, they cannot sufficiently provide any kind of certainty on the validity of a model. To eliminate modeling biasness, a new validation method was proposed and was then employed to re-examine previously published adsorption kinetic data.

Over the last quarter century, the dominant tendency in comparative cognitive psychology has been to emphasize the similarities between human and nonhuman minds and to downplay the differences as "one of degree and not of kind" (Darwin 1871). In the present target article, we argue that Darwin was mistaken: the profound biological continuity between human and nonhuman animals masks an equally profound discontinuity between human and nonhuman minds. To wit, there is a significant discontinuity in the degree to which human and nonhuman animals are able to approximate the higher-order, systematic, relational capabilities of a physical symbol system (PSS) (Newell 1980). We show that this symbolic-relational discontinuity pervades nearly every domain of cognition and runs much deeper than even the spectacular scaffolding provided by language or culture alone can explain. We propose a representational-level specification as to where human and nonhuman animals' abilities to approximate a PSS are similar and where they differ. We conclude by suggesting that recent symbolic-connectionist models of cognition shed new light on the mechanisms that underlie the gap between human and nonhuman minds.

The freshwater and marine fish faunas of South America are the most diverse on Earth, with current species richness estimates standing above 9100 species. In addition, over the last decade at least 100 species were described every year. There are currently about 5160 freshwater fish species, and the estimate for the freshwater fish fauna alone points to a final diversity between 8000 and 9000 species. South America also has c. 4000 species of marine fishes. The mega-diverse fish faunas of South America evolved over a period of >100 million years, with most lineages tracing origins to Gondwana and the adjacent Tethys Sea. This high diversity was in part maintained by escaping the mass extinctions and biotic turnovers associated with Cenozoic climate cooling, the formation of boreal and temperate zones at high latitudes and aridification in many places at equatorial latitudes. The fresh waters of the continent are divided into 13 basin complexes, large basins consolidated as a single unit plus historically connected adjacent coastal drainages, and smaller coastal basins grouped together on the basis of biogeographic criteria. Species diversity, endemism, noteworthy groups and state of knowledge of each basin complex are described. Marine habitats around South America, both coastal and oceanic, are also described in terms of fish diversity, endemism and state of knowledge. Because of extensive land use changes, hydroelectric damming, water divergence for irrigation, urbanization, sedimentation and overfishing 4-10% of all fish species in South America face some degree of extinction risk, mainly due to habitat loss and degradation. These figures suggest that the conservation status of South American freshwater fish faunas is better than in most other regions of the world, but the marine fishes are as threatened as elsewhere. Conserving the remarkable aquatic habitats and fishes of South America is a growing challenge in face of the rapid anthropogenic changes of the 21st century, and deserves attention from conservationists and policy makers.

After decades of effort by some of our brightest human and non-human minds, there is still little consensus on whether or not non-human animals understand anything about the unobservable mental states of other animals or even what it would mean for a non-verbal animal to understand the concept of a 'mental state'. In the present paper, we confront four related and contentious questions head-on: (i) What exactly would it mean for a non-verbal organism to have an 'understanding' or a 'representation' of another animal's mental state? (ii) What should (and should not) count as compelling empirical evidence that a non-verbal cognitive agent has a system for understanding or forming representations about mental states in a functionally adaptive manner? (iii) Why have the kind of experimental protocols that are currently in vogue failed to produce compelling evidence that non-human animals possess anything even remotely resembling a theory of mind? (iv) What kind of experiments could, at least in principle, provide compelling evidence for such a system in a non-verbal organism?

Although differences in sampling intensity can bias comparisons of allelic richness (A) among populations, investigators often fail to correct estimates of A for differences in sample size. Methods that standardize A on the basis of the size of the smallest number of samples in a comparison are preferable to other approaches. Rarefaction and repeated random subsampling provide unbiased estimates of A with the greatest precision and thus provide greatest statistical power to detect differences in variation. Less promising approaches, in terms of bias or precision, include single random subsampling, eliminating very small samples, using sample size as a covariate or extrapolating estimates obtained from small samples to a larger number of individuals.

Abstract Ferns are the closest sister group to all seed plants, yet little is known about their genomes other than that they are generally colossal. Here, we report on the genomes of Azolla filiculoides and Salvinia cucullata (Salviniales) and present evidence for episodic whole-genome duplication in ferns—one at the base of ‘core leptosporangiates’ and one specific to Azolla . One fern-specific gene that we identified, recently shown to confer high insect resistance, seems to have been derived from bacteria through horizontal gene transfer. Azolla coexists in a unique symbiosis with N 2 -fixing cyanobacteria, and we demonstrate a clear pattern of cospeciation between the two partners. Furthermore, the Azolla genome lacks genes that are common to arbuscular mycorrhizal and root nodule symbioses, and we identify several putative transporter genes specific to Azolla –cyanobacterial symbiosis. These genomic resources will help in exploring the biotechnological potential of Azolla and address fundamental questions in the evolution of plant life.

The goal of the present study was to determine whether the architectonic criteria used to identify the core region in macaque monkeys (Macaca mulatta, M. nemestrina) could be used to identify a homologous region in chimpanzees (Pan troglodytes) and humans (Homo sapiens). Current models of auditory cortical organization in primates describe a centrally located core region containing two or three subdivisions including the primary auditory area (AI), a surrounding belt of cortex with perhaps seven divisions, and a lateral parabelt region comprised of at least two fields. In monkeys the core region can be identified on the basis of specific anatomical and physiological features. In this study, the core was identified from serial sets of adjacent sections processed for cytoarchitecture, myeloarchitecture, acetylcholinesterase, and cytochrome oxidase. Qualitative and quantitative criteria were used to identify the borders of the core region in individual sections. Serial reconstructions of each brain were made showing the location of the core with respect to gross anatomical landmarks. The position of the core with respect to major sulci and gyri in the superior temporal region varied most in the chimpanzee and human specimens. Although the architectonic appearance of the core areas did vary in certain respects across taxonomic groups, the numerous similarities made it possible to identify unambiguously a homologous cortical region in macaques, chimpanzees, and humans.

A performance analysis of 1-bit full-adder cell is presented. The adder cell is anatomized into smaller modules. The modules are studied and evaluated extensively. Several designs of each of them are developed, prototyped, simulated and analyzed. Twenty different 1-bit full-adder cells are constructed (most of them are novel circuits) by connecting combinations of different designs of these modules. Each of these cells exhibits different power consumption, speed, area, and driving capability figures. Two realistic circuit structures that include adder cells are used for simulation. A library of full-adder cells is developed and presented to the circuit designers to pick the full-adder cell that satisfies their specific applications.

Epilepsy is one of the world's most common neurological diseases. Early prediction of the incoming seizures has a great influence on epileptic patients' life. In this paper, a novel patient-specific seizure prediction technique based on deep learning and applied to long-term scalp electroencephalogram (EEG) recordings is proposed. The goal is to accurately detect the preictal brain state and differentiate it from the prevailing interictal state as early as possible and make it suitable for real time. The features extraction and classification processes are combined into a single automated system. Raw EEG signal without any preprocessing is considered as the input to the system which further reduces the computations. Four deep learning models are proposed to extract the most discriminative features which enhance the classification accuracy and prediction time. The proposed approach takes advantage of the convolutional neural network in extracting the significant spatial features from different scalp positions and the recurrent neural network in expecting the incidence of seizures earlier than the current methods. A semi-supervised approach based on transfer learning technique is introduced to improve the optimization problem. A channel selection algorithm is proposed to select the most relevant EEG channels which makes the proposed system good candidate for real-time usage. An effective test method is utilized to ensure robustness. The achieved highest accuracy of 99.6% and lowest false alarm rate of 0.004 h <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-</sup> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> along with very early seizure prediction time of 1 h make the proposed method the most efficient among the state of the art.

Concepts and theory for the design and application of terrestrial reserves is based on our understanding of environmental, ecological, and evolutionary processes responsible for biological diversity and sustainability of terrestrial ecosystems and how humans have influenced these processes. How well this terrestrial-based theory can be applied toward the design and application of reserves in the coastal marine environment depends, in part, on the degree of similarity between these systems. Several marked differences in ecological and evolutionary processes exist between marine and terrestrial ecosystems as ramifications of fundamental differences in their physical environments (i.e., the relative prevalence of air and water) and contemporary patterns of human impacts. Most notably, the great extent and rate of dispersal of nutrients, materials, holoplanktonic organisms, and reproductive propagules of benthic organisms expand scales of connectivity among nearshore communities and ecosystems. Consequently, the “openness” of marine populations, communities, and ecosystems probably has marked influences on their spatial, genetic, and trophic structures and dynamics in ways experienced by only some terrestrial species. Such differences appear to be particularly significant for the kinds of organisms most exploited and targeted for protection in coastal marine ecosystems (fishes and macroinvertebrates). These and other differences imply some unique design criteria and application of reserves in the marine environment. In explaining the implications of these differences for marine reserve design and application, we identify many of the environmental and ecological processes and design criteria necessary for consideration in the development of the analytical approaches developed elsewhere in this Special Issue.

Theoretical analyses and experimental studies of synthesized assemblages indicate that under particular circumstances species diversity can enhance community productivity through niche complementarity. It remains unclear whether this process has important effects in mature natural ecosystems where competitive feedbacks and complex environmental influences affect diversity-productivity relationships. In this study, we evaluated diversity-productivity relationships while statistically controlling for environmental influences in 12 natural grassland ecosystems. Because diversity-productivity relationships are conspicuously nonlinear, we developed a nonlinear structural equation modeling (SEM) methodology to separate the effects of diversity on productivity from the effects of productivity on diversity. Meta-analysis was used to summarize the SEM findings across studies. While competitive effects were readily detected, enhancement of production by diversity was not. These results suggest that the influence of small-scale diversity on productivity in mature natural systems is a weak force, both in absolute terms and relative to the effects of other controls on productivity.

The construction of a crossed cube which has many of the properties of the hypercube, but has diameter only about half as large, is discussed. This network is self-routing, in the sense that there is a simple distributed routing algorithm which guarantees optimal paths between any pair of vertices. This fact, together with other properties such as regularity, symmetry, high connectivity, and a simple recursive structure, suggests that the crossed cube may be an attractive alternative to the ordinary hypercube for massively parallel architectures, SIMD algorithms, which utilize the architecture are developed, and it is shown that the CQ/sub n/ architecture can profitably emulate the ordinary hypercube. It is also shown that addition of simple switches can improve the capabilities of the system significantly. For instance, the dynamic reconfiguration capability allows hypercube algorithms to be executed on the proposed architecture. The use of these switches also improves the embedding properties of the system.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

We present a new design for a 1-b full adder featuring hybrid-CMOS design style. The quest to achieve a good-drivability, noise-robustness, and low-energy operations for deep submicrometer guided our research to explore hybrid-CMOS style design. Hybrid-CMOS design style utilizes various CMOS logic style circuits to build new full adders with desired performance. This provides the designer a higher degree of design freedom to target a wide range of applications, thus significantly reducing design efforts. We also classify hybrid-CMOS full adders into three broad categories based upon their structure. Using this categorization, many full-adder designs can be conceived. We will present a new full-adder design belonging to one of the proposed categories. The new full adder is based on a novel xor-xnor circuit that generates xor and xnor full-swing outputs simultaneously. This circuit outperforms its counterparts showing 5%-37% improvement in the power-delay product (PDP). A novel hybrid-CMOS output stage that exploits the simultaneous xor-xnor signals is also proposed. This output stage provides good driving capability enabling cascading of adders without the need of buffer insertion between cascaded stages. There is approximately a 40% reduction in PDP when compared to its best counterpart. During our experimentations, we found out that many of the previously reported adders suffered from the problems of low swing and high noise when operated at low supply voltages. The proposed full adder is energy efficient and outperforms several standard full adders without trading off driving capability and reliability. The new full-adder circuit successfully operates at low voltages with excellent signal integrity and driving capability. To evaluate the performance of the new full adder in a real circuit, we embedded it in a 4- and 8-b, 4-operand carry-save array adder with final carry-propagate adder. The new adder displayed better performance as compared to the standard full adders

MOTIVATION: The BioTIME database contains raw data on species identities and abundances in ecological assemblages through time. These data enable users to calculate temporal trends in biodiversity within and amongst assemblages using a broad range of metrics. BioTIME is being developed as a community-led open-source database of biodiversity time series. Our goal is to accelerate and facilitate quantitative analysis of temporal patterns of biodiversity in the Anthropocene. MAIN TYPES OF VARIABLES INCLUDED: The database contains 8,777,413 species abundance records, from assemblages consistently sampled for a minimum of 2 years, which need not necessarily be consecutive. In addition, the database contains metadata relating to sampling methodology and contextual information about each record. SPATIAL LOCATION AND GRAIN: ). TIME PERIOD AND GRAIN: BioTIME records span from 1874 to 2016. The minimal temporal grain across all datasets in BioTIME is a year. MAJOR TAXA AND LEVEL OF MEASUREMENT: BioTIME includes data from 44,440 species across the plant and animal kingdoms, ranging from plants, plankton and terrestrial invertebrates to small and large vertebrates. SOFTWARE FORMAT: .csv and .SQL.

In the area of applied statistics, scientists use statistical distributions to model a wide range of practical problems, from modeling the size grade distribution of onions to modeling global positioning data. To apply these probability models successfully, practitioners and researchers must have a thorough understanding of the theory as well as a

Geographic changes in species distributions toward traditionally cooler climes is one hypothesized indicator of recent global climate change. We examined distribution data on 56 bird species. If global warming is affecting species distributions across the temperate northern hemisphere, these data should show the same northward range expansions of birds that have been reported for Great Britain. Because a northward shift of distributions might be due to multidirectional range expansions for multiple species, we also examined the possibility that birds with northern distributions may be expanding their ranges southward. There was no southward expansion of birds with a northern distribution, indicating that there is no evidence of overall range expansion of insectivorous and granivorous birds in North America. As predicted, the northern limit of birds with a southern distribution showed a significant shift northward (2.35 km/year). This northward shift is similar to that observed in previous work conducted in Great Britain: the widespread nature of this shift in species distributions over two distinct geographical regions and its coincidence with a period of global warming suggests a connection with global climate change.

We describe here the synthesis of a novel magnetic drug-targeting carrier characterized by a core-shell structure. The core-shell carrier combines the advantages of a magnetic core and the stimuli-responsive property of the thermosensitive biodegradable polymer shell (e.g., an on-off mechanism responsive to external temperature change). The composite nanoparticles are approximately 8 nm in diameter with approximately 3 nm shell. The lower critical solution temperature (LCST) is approximately 38 degrees C as determined by UV-vis absorption spectroscopy. The carrier is composed of cross-linked dextran grafted with a poly(N-isopropylacrylamide-co-N,N-dimethylacrylamide) [dextran-g-poly(NIPAAm-co-DMAAm)] shell and superparamagnetic Fe3O4 core. Fourier transform infrared spectroscopy (FTIR) confirmed the composition of the carrier. The synthesized magnetic carrier system has potential applications in magnetic drug-targeting delivery and magnetic resonance imaging.

Systema Naturae includes representatives of every major lineage of the animal phylum Cnidaria. However, Linnaeus did not classify the members of the phylum as is now done, and the diversity of the group is not well represented. We contrast the Linnaean perspective on cnidarian diversity with the modern, phylogenetic perspective. For each order, we detail diversity at the family level, providing phylogenetic context where possible.