Miracle-dz/UniFAR-FTUs huggingface dataset:
The Ecology and Feeding Habits of the Arboreal Trap-Jawed Ant Daceton armigerum

Here we show that Daceton armigerum, an arboreal myrmicine ant whose workers are equipped with hypertrophied trap-jaw mandibles, is characterized by a set of unexpected biological traits including colony size, aggressiveness, trophobiosis and hunting behavior. The size of one colony has been evaluated at ca. 952,000 individuals. Intra- and interspecific aggressiveness were tested and an equiprobable null model used to show how D. armigerum colonies react vis-à-vis other arboreal ant species with large colonies; it happens that D. armigerum can share trees with certain of these species. As they hunt by sight, workers occupy their hunting areas only during the daytime, but stay on chemical trails between nests at night so that the center of their home range is occupied 24 hours a day. Workers tend different Hemiptera taxa (i.e., Coccidae, Pseudococcidae, Membracidae and Aethalionidae). Through group-hunting, short-range recruitment and spread-eagling prey, workers can capture a wide range of prey (up to 94.12 times the mean weight of foraging workers).
Design and research of a novel caudal-fin propulsion mechanism with two degrees of freedom

In order to avoid the reciprocating reversal of the motor in the propulsion mechanism leading to the lower electric drive efficiency, and realize the various functions of the caudal fins. This article presents a novel caudal-fin propulsion mechanism with 2-DOF for bionic robotic fish. The robotic fish based on the propulsion mechanism could achieve straight swimming, flexible turning, floating and diving movement without the other auxiliary devices. Firstly, mechanism design will be mentioned in detail. Then, kinematics principle and control strategies of the robotic fish are established on base of motion simulation. In addition, experiments of straight swimming and turning were carried out with unmanned aerial photography in outdoor pond. The results show that robotic fish used the 2-DOF caudal-fin propulsion mechanism could achieve various basic swimming action with its caudal fins, which provides a new reference method for the design of robotic fish.
Binary Matrix Completion Using Unobserved Entries

A matrix completion problem, which aims to recover a complete matrix from its partial observations, is one of the important problems in the machine learning field and has been studied actively. However, there is a discrepancy between the mainstream problem setting, which assumes continuous-valued observations, and some practical applications such as recommendation systems and SNS link predictions where observations take discrete or even binary values. To cope with this problem, Davenport et al. (2014) proposed a binary matrix completion (BMC) problem, where observations are quantized into binary values. Hsieh et al. (2015) proposed a PU (Positive and Unlabeled) matrix completion problem, which is an extension of the BMC problem. This problem targets the setting where we cannot observe negative values, such as SNS link predictions. In the construction of their method for this setting, they introduced a methodology of the classification problem, regarding each matrix entry as a sample. Their risk, which defines losses over unobserved entries as well, indicates the possibility of the use of unobserved entries. In this paper, motivated by a semi-supervised classification method recently proposed by Sakai et al. (2017), we develop a method for the BMC problem which can use all of positive, negative, and unobserved entries, by combining the risks of Davenport et al. (2014) and Hsieh et al. (2015). To the best of our knowledge, this is the first BMC method which exploits all kinds of matrix entries. We experimentally show that an appropriate mixture of risks improves the performance.
The Association between Air Pollution and Population Health Risk for Respiratory Infection: A Case Study of Shenzhen, China

Nowadays, most of the research on air pollution and its adverse effects on public health in China has focused on megacities and heavily-polluted regions. Fewer studies have focused on cities that are slightly polluted. Shenzhen used to have a favorable air environment, but its air quality has deteriorated gradually as a result of development in recent years. So far, no systematic investigations have been conducted on the adverse effects of air pollution on public health in Shenzhen. This research has applied a time series analysis model to study the possible association between different types of air pollution and respiratory hospital admission in Shenzhen in 2013. Respiratory hospital admission was divided into two categories for comparison analysis among various population groups: acute upper respiratory infection and acute lower respiratory infection. The results showed that short-term exposure to ambient air pollution was significantly associated with acute respiratory infection hospital admission in Shenzhen in 2013. Children under 14 years old were the main susceptible population of acute respiratory infection due to air pollution. PM10, PM2.5 and NO2 were the primary air pollutants threatening respiratory health in Shenzhen. Though air pollution level is generally relatively low in Shenzhen, it will benefit public health to control the pollution of particulate matter as well as other gaseous pollutants.
Gr upSM Inverse Mapping of BOLD fMRI : 4 D Magnetic Susceptibility ( χ ) Tomography

Background: A brain magnetic state (in terms of magnetic susceptibility distribution χ) can be detected by T2*-weighted MRI (T2*MRI) undergoing a cascade of data transformations. The MRI transformations cause distortions (or spatial morphing), which may be undone by solving the inverse imaging or mapping problem. Upon having a dataset acquired from Blood Oxygenation Level-Dependent (BOLD) functional MRI, we can reconstruct the dynamic brain χ source by inverse mapping called 4D χ tomography. This chapter is to address the imaging and inverse imaging aspects of BOLD fMRI from the perspective of data mapping. Methods: T2*MRI is described by a mathematical mapping from a real-valued continuous χ source to a complex-valued discrete T2* image, of which the T2* magnitude imaging implements a mapping from a set of real numbers (R = (-∞, ∞)) to a set of nonnegative numbers (R+ = [0, ∞)) that is irreversible; whereas the T2* phase imaging (with unwrapped phase) is a mapping of R → R that is reversible. A 3D χ map is reconstructed from a 3D T2* phase image by a Computed Inverse MRI (CIMRI) method. The dynamic 4D χ source is reconstructed by 4D χ tomography, implementing a spatiotemporal inverse mapping of BOLD fMRI. Zikuan Chen1,2* 1Zinv LLC, Albuquerque, NM 87108, USA 2The Mind Research Network, Albuquerque, NM 87106, USA *Corresponding author: Zikuan Chen, The Mind Research Network, Albuquerque, NM 87106, USA, Email: zchen@mrn.org Published Date: June 30, 2016
Piezoelectric electrospun nanofibrous energy harvesting devices: Influence of the electrodes position and finite variation of dimensions

Having control on the specific area of power harvesting devices is the main controllable parameter in their fabrication. Hence, in this paper, at first a piezoelectric nanofiber is made with different dimensions and all kinds of function tests including X-ray diffraction, Fourier transform infrared spectroscopy, differential scanning calorimetry are implemented thereon. After ensuring accurate …… responses from the device, some kinds of forces like concentration impact and distributed impact and tension creation by applying bending force are applied on the fabricated device in the laboratory. To assess the effect of electrode position, electrodes were placed in five modes within the samples and the output voltage was recorded with regard to applied forces type. The results indicated that an increase in specific area of nanofibrous mats in devices absolutely resulted in an increase in electric output, but the electric output reduced consequently when it normalized to the specific area of nanofibrous mats. These results imply promising approaches, as an enhanced efficiency energy-scavenging interface, for designing and fabricating various wearable self-powered electrical devices and systems.
SSI for Disabled Immigrants: Why Do Ethnic Networks Matter?

Immigrants residing among many people who share their ethnic background are especially likely to receive Supplemental Security Income (SSI) for a disability when they belong to high SSI take-up immigrant groups. After showing that this relationship cannot be fully explained by differences in health, we consider the likely sources of these network effects by separately examining their role in the decision to apply for SSI and, conditional on applying, their role in determining who ultimately receives benefits. Our results suggest that networks may increase the probability of applying for SSI despite minor disabilities, but it is unlikely that network effects are driven by egregious lies on applications.
Effects of Patch-Size on Populations of Intertidal Limpets, Siphonaria spp., in a Linear Landscape

Organisms with different life-histories and abilities to disperse often utilise habitat patches in different ways. We investigated the influence of the size of patches of rock (separated by stretches of sand) on the density of pulmonate limpets (Siphonaria spp.) along 1500 km of the linear landscape of the South African coastline. We compared the influence of patch-size on two congeneric species with different modes of development, S. serrata a direct developer, and S. concinna a planktonic developer. We tested the spatial and temporal consistency of the effects of patch-size by sampling 7 independent regions spanning the distributional range of both species of limpets, and by sampling one region at monthly intervals for 1 year. Within each region or month, 4 small patches (<20 m in length) interspersed with the 4 large patches (>60 m in length) were sampled. Across the entire geographic range and throughout the year, there were more of both species of limpets in large patches than in small patches. In most regions, there was greater variability in large patches than small patches. Variability within patches in a single region was similar throughout the year, with greater variability of both species in large than in small patches. We found little influence of the mode of development on the response of limpets to patch-size. Our findings highlight the importance of understanding patterns of distribution of species with respect to habitat heterogeneity in linear landscapes, and contradict the idea that organism mobility at an early ontogenetic stage directly affects habitat use.
Material Optimization in Transverse Electromagnetic Scattering Applications

A class of algorithms for the solution of discrete material optimization problems in electromagnetic applications is discussed. The idea behind the algorithm is similar to that of the sequential programming. However, in each major iteration a model is established on the basis of an appropriately parametrized material tensor. The resulting nonlinear parametrization is treated on the level of the subproblem, for which globally optimal solutions can be computed due to the block separability of the model. Although global optimization of nonconvex design problems is generally prohibitive, a well chosen combination of analytic solutions along with standard global optimization techniques leads to a very efficient algorithm for most relevant material parametrizations. A global convergence result for the overall algorithm is established. The effectiveness of the approach in terms of both computation time and solution quality is demonstrated by numerical examples based on a two-dimensional Helmholtz equation, inclu.
A Multiscale Latent Dirichlet Allocation Model for Object-Oriented Clustering of VHR Panchromatic Satellite Images

A novel model is presented to address the problem of semantic clustering of geo-objects in very high resolution panchromatic satellite images. The proposed model combines a probabilistic topic model with a multiscale image representation into an automatic framework by embedding both document and scale selections. The probabilistic topic model is used to characterize the statistical distributions of both intraclass appearance and inter-class coherence of geo-objects within documents, i.e., squared sub-images. Because the bag-of-words assumption involved in the probabilistic topic models does not consider the spatial coherence between topic labels, the multiscale image representation is designed to provide a self-adaptive spatial regularization for various geo-object categories. By introducing scale and document selections, the automatic framework integrates the probabilistic topic model and the multiscale image representation to ensure that words on a site should be allocated the same topic label no matter what documents they reside in. Consequently, unlike the traditional method of applying topic models for analyzing satellite images, the process of explicitly generating a set of documents before modeling and then combining multiple labels for a word on a given site is unnecessary. Gibbs sampling is adopted for parameter estimation and image clustering. Extensive experimental evaluations are designed to first analyze the effect of parameters in the proposed model and then compare the results of our model with those of some state-of-the-art methods for three different types of images. The results indicate that the proposed algorithm consistently outperforms these exiting state-of-the-art methods in all of the experiments.
Detection and Tracking of NY-ESO-1-Specific CD8+ T Cells by High-Throughput T Cell Receptor β (TCRB) Gene Rearrangements Sequencing in a Peptide-Vaccinated Patient

Comprehensive immunological evaluation is crucial for monitoring patients undergoing antigen-specific cancer immunotherapy. The identification and quantification of T cell responses is most important for the further development of such therapies. Using well-characterized clinical samples from a high responder patient (TK-f01) in an NY-ESO-1f peptide vaccine study, we performed high-throughput T cell receptor β-chain (TCRB) gene next generation sequencing (NGS) to monitor the frequency of NY-ESO-1-specific CD8+ T cells. We compared these results with those of conventional immunological assays, such as IFN-γ capture, tetramer binding and limiting dilution clonality assays. We sequenced human TCRB complementarity-determining region 3 (CDR3) rearrangements of two NY-ESO-1f-specific CD8+ T cell clones, 6-8L and 2F6, as well as PBMCs over the course of peptide vaccination. Clone 6-8L possessed the TCRB CDR3 gene TCRBV11-03*01 and BJ02-01*01 with amino acid sequence CASSLRGNEQFF, whereas 2F6 possessed TCRBV05-08*01 and BJ02-04*01 (CASSLVGTNIQYF). Using these two sequences as models, we evaluated the frequency of NY-ESO-1-specific CD8+ T cells in PBMCs ex vivo. The 6-8L CDR3 sequence was the second most frequent in PBMC and was present at high frequency (0.7133%) even prior to vaccination, and sustained over the course of vaccination. Despite a marked expansion of NY-ESO-1-specific CD8+ T cells detected from the first through 6th vaccination by tetramer staining and IFN-γ capture assays, as evaluated by CDR3 sequencing the frequency did not increase with increasing rounds of peptide vaccination. By clonal analysis using 12 day in vitro stimulation, the frequency of B*52:01-restricted NY-ESO-1f peptide-specific CD8+ T cells in PBMCs was estimated as only 0.0023%, far below the 0.7133% by NGS sequencing. Thus, assays requiring in vitro stimulation might be underestimating the frequency of clones with lower proliferation potential. High-throughput TCRB sequencing using NGS can potentially better estimate the actual frequency of antigen-specific T cells and thus provide more accurate patient monitoring.
A Blind Spot in Research on Foreign Language Effects in Judgment and Decision-Making

One of the most fascinating topics of current investigation in the literature on judgment and decision-making concerns the exploration of foreign language effects (henceforth, FLE). Specifically, recent research suggests that presenting information in a foreign language helps reasoners make better choices. However, this piece aims at making scholars aware of a blind spot in this stream of research. In particular, research on FLE has imported only one view of judgment and decision-making, in which the heuristics that people use are seen as conducive to biases and, in turn, to costly mistakes. But heuristics are not necessarily a liability, and this article indicates two routes to push forward research on FLE in judgment and decision-making. First, research on FLE should be expanded to explore also classes of fast and frugal heuristics, which have been shown to lead to accurate predictions in several contexts characterized by uncertainty. Second, research on FLE should be open to challenge the interpretations given to previous FLE findings, since alternative accounts are plausible and not ruled out by evidence.
Utility-Based Mechanism for Structural Self-Organization in Service-Oriented MAS

Structural relations established among agents influence the performance of decentralized service discovery process in multiagent systems. Moreover, distributed systems should be able to adapt their structural relations to changes in environmental conditions. In this article, we present a service-oriented multiagent systems, where agents initially self-organize their structural relations based on the similarity of their services. During the service discovery process, agents integrate a mechanism that facilitates the self-organization of their structural relations to adapt the structure of the system to the service demand. This mechanism facilitates the task of decentralized service discovery and improves its performance. Each agent has local knowledge about its direct neighbors and the queries received during discovery processes. With this information, an agent is able to analyze its structural relations and decide when it is more appropriate to modify its direct neighbors and select the most suitable acquaintances to replace them. The experimental evaluation shows how this self-organization mechanism improves the overall performance of the service discovery process in the system when the service demand changes.
Hydroxyapatite-Poly(Vinyl Alcohol)-Sodium Alginate Porous Hydrogels with Poly(Vinyl Alcohol) Surface Layer Used for Articular Cartilage Repair

The double-layered PVA/nanohydroxyapatite (nHA)-poly (vinyl alcohol)(PVA)-sodium alginate (SA) porous composite scaffolds used as synthetic articular cartilage were prepared by the freeze-thawing method, gas foaming method and crosslink method of Ca2+ ion, i.e., upper PVA layer for the cartilage substitute and underlying SA30 porous hydrogels for bone bonding. The microstructure and morphology of composite hydrogels were characterized using scanning electronic microscopy (SEM). It had high porosity and uniform pores. The content of HA in SA30 matrix were tested by Energy-dispersive X-ray spectroscopy (EDS). The biological properties of the composite hydrogels had been evaluated by co-culture and MTT. All results indicate that the PVA/SA30 hydrogels has good potential for repairing or replacing articular cartilage.
A 2.5μW 0.0067mm2 automatic back-biasing compensation unit achieving 50% leakage reduction in FDSOI 28nm over 0.35-to-1V VDD range

Worst-case design and post-silicon tuning are well established digital design practices reducing timing violations in presence of process, temperature, aging and voltage variations, but they suffer from extra power consumption due to overdesign [1]. Adaptive voltage scaling (AVS) [2] and body bias modulation [1] are well-known strategies to dynamically ensure that the digital core can operate at a targeted frequency, even in the presence of delay degradation due to variations. In a multiple voltage islands context, AVS requires many integrated supply generators, such as switched capacitor converters that need to be controlled accurately. Also, for fine-grained compensation, level shifters are required, impacting circuit performance. As FDSOI technology offers the ability to adjust transistor speed through high sensitivity (85mV/VBB) VTH tuning by acting on buried Nwell (NW) and Pwell (PW) voltages, back-biasing generators have been investigated [3-5]. However, they require an external controller to reach the optimal Back Bias (BB) voltages (no self-adjustment) ([3-4] and [5]), imposing a non-negligible area overhead for a sub-mm2 digital core having a narrow compensation range limited to 0.35–0.45V VDD. We therefore propose a variation-aware BB compensation unit (BBC), which dynamically self-adjusts the N- and PMOS transistors' BB voltages to maintain the target frequency with low-latency tuning (100μs) across a wide range of supply voltage (0.35–1V) and temperature (−40–125°C). The low reported area of 0.0067mm2 makes it affordable for a small digital core area (0.1–2mm2). Requiring only a reference frequency signal FTGT, the self-operating BBC exhibits 2. 5μW quiescent current without any external components. Compared to a worst-case design strategy, the BBC unit brings up to 50% leakage reduction @0.45VDD, 120°C and reduces the energy per cycle up to 32% compared to worst-case design. By providing continuous BB voltage adjustment (continuous VTH tuning), the target frequency is maintained within ±3.5% accuracy.
The “Double Whammy”: Women's Experiences of Weight Gain After Diagnosis and Treatment for Schizophrenia Spectrum Disorders

Abstract High levels of lifestyle risk factors compound medication side effects, resulting in high rates of obesity among people with schizophrenia spectrum disorders (SSDs). Obesity and related comorbidities increase the levels of disability and disadvantage in this population. Little research has explored the lived experiences in relation to this issue, and less has considered the experiences of women. Our aim in this study was to understand the experiences of women who gained weight after their diagnosis and treatment for SSDs. We carried out up to three in-depth qualitative interviews with 11 women over 2 years. Data were analyzed using constructivist grounded theory procedures. The women described a “double whammy”–like experience whereby weight gain and obesity came with their diagnosis and treatment of an SSD and brought with it additional challenges. The double whammy parallels the co-occurrence of mental illness and substance misuse. Implications of these parallels for service provision are discussed.
Development of Dipicolylamine-Modified Cyclodextrins for the Design of Selective Guest-Responsive Receptors for ATP

The construction of supramolecular recognition systems based on specific host–guest interactions has been studied in order to design selective chemical sensors. In this study, guest-responsive receptors for ATP have been designed with cyclodextrins (CyDs) as a basic prototype of the turn-on type fluorescent indicator. We synthesized dipicolylamine (DPA)-modified CyD–Cu2+ complexes (Cu·1α, Cu·1β, and Cu·1γ), and evaluated their recognition capabilities toward phosphoric acid derivatives in water. The UV-Vis absorption and fluorescence spectra revealed that Cu·1β selectively recognized ATP over other organic and inorganic phosphates, and that β-CyD had the most suitable cavity size for complexation with ATP. The 1D and 2D NMR analyses suggested that the ATP recognition was based on the host–guest interaction between the adenine moiety of ATP and the CyD cavity, as well as the recognition of phosphoric moieties by the Cu2+–DPA complex site. The specific interactions between the CyD cavity and the nucleobases enabled us to distinguish ATP from other nucleoside triphosphates, such as guanosine triphosphate (GTP), uridine triphosphate (UTP), and cytidine triphosphate (CTP). This study clarified the basic mechanisms of molecular recognition by modified CyDs, and suggested the potential for further application of CyDs in the design of highly selective supramolecular recognition systems for certain molecular targets in water.