Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Basis of a Cognitive Complexity Metric

Relational complexity (RC) is a metric reflecting capacity limitation in relational processing. It plays a crucial role in higher cognitive processes and is an endophenotype for several disorders. However, the genetic underpinnings of complex relational processing have not been investigated. Using the classical twin model, we estimated the heritability of RC and genetic overlap with intelligence (IQ), reasoning, and working memory in a twin and sibling sample aged 15-29 years (N = 787). Further, in an exploratory search for genetic loci contributing to RC, we examined associated genetic markers and genes in our Discovery sample and selected loci for replication in four independent samples (ALSPAC, LBC1936, NTR, NCNG), followed by meta-analysis (N>6500) at the single marker level. Twin modelling showed RC is highly heritable (67%), has considerable genetic overlap with IQ (59%), and is a major component of genetic covariation between reasoning and working memory (72%). At the molecular level, we found preliminary support for four single-marker loci (one in the gene DGKB), and at a gene-based level for the NPS gene, having influence on cognition. These results indicate that genetic sources influencing relational processing are a key component of the genetic architecture of broader cognitive abilities. Further, they suggest a genetic cascade, whereby genetic factors influencing capacity limitation in relational processing have a flow-on effect to more complex cognitive traits, including reasoning and working memory, and ultimately, IQ.
Unexpected Population Distribution in a Microbial Mat Community: Sulfate-Reducing Bacteria Localized to the Highly Oxic Chemocline in Contrast to a Eukaryotic Preference for Anoxia

ABSTRACT The distribution and abundance of sulfate-reducing bacteria (SRB) and eukaryotes within the upper 4 mm of a hypersaline cyanobacterial mat community were characterized at high resolution with group-specific hybridization probes to quantify 16S rRNA extracted from 100-μm depth intervals. This revealed a preferential localization of SRB within the region defined by the oxygen chemocline. Among the different groups of SRB quantified, including members of the provisional families “Desulfovibrionaceae” and “Desulfobacteriaceae,” Desulfonema-like populations dominated and accounted for up to 30% of total rRNA extracted from certain depth intervals of the chemocline. These data suggest that recognized genera of SRB are not necessarily restricted by high levels of oxygen in this mat community and the possibility of significant sulfur cycling within the chemocline. In marked contrast, eukaryotic populations in this community demonstrated a preference for regions of anoxia.
Evolution of Electroencephalogram Signal Analysis Techniques during Anesthesia

Biosignal analysis is one of the most important topics that researchers have tried to develop during the last century to understand numerous human diseases. Electroencephalograms (EEGs) are one of the techniques which provides an electrical representation of biosignals that reflect changes in the activity of the human brain. Monitoring the levels of anesthesia is a very important subject, which has been proposed to avoid both patient awareness caused by inadequate dosage of anesthetic drugs and excessive use of anesthesia during surgery. This article reviews the bases of these techniques and their development within the last decades and provides a synopsis of the relevant methodologies and algorithms that are used to analyze EEG signals. In addition, it aims to present some of the physiological background of the EEG signal, developments in EEG signal processing, and the effective methods used to remove various types of noise. This review will hopefully increase efforts to develop methods that use EEG signals for determining and classifying the depth of anesthesia with a high data rate to produce a flexible and reliable detection device.
Hypoglycemic effect of Bromelia plumieri (E. Morren) L.B. Sm., leaves in STZ-NA-induced diabetic rats

This study confirms the hypoglycemic effects of two extracts obtained from the Bromelia plumieri (BP) plant in streptozotocin-nicotinamide-induced diabetic rats (STZ-NA). BP has been traditionally used in the municipality of Tlanchinol Hidalgo, Mexico, to treat type 2 diabetes. Two different BP extracts were prepared and tested. The first extract was a water extract (WE), similar to that traditionally used to make tea, and the second extract was an ethanol:water extract (EWE). The extracts (WE at 35 and 350 mg/kg, and EWE at 30 and 300 mg/kg) were tested in STZ-NA-induced diabetic rats to determine whether hypoglycemia occurred after oral administration of the extracts. Phytochemistry: Two different extracts were prepared, n-hexane and butanol, to determine the presence of alkaloids, terpenes and flavonoids. The extracts that were administered to the STZ-NA-induced diabetic rats produced a significant hypoglycemic effect as compared with the control group, similar to that achieved with glibenclamide. We also determined that flavonoids were the main components of BP leaves. The results presented here support the hypothesis that extracts obtained from this plant have hypoglycemic effects, which are in agreement with the traditional uses of this plant.
A Holistic Approach for Optimizing DSP Block Utilization of a CNN implementation on FPGA

Deep Neural Networks are becoming the de-facto standard models for image understanding, and more generally for computer vision tasks. As they involve highly parallelizable computations, Convolutional Neural Networks (CNNs) are well suited to current fine grain programmable logic devices. Thus, multiple CNN accelerators have been successfully implemented on Field-Programmable Gate Arrays (FPGAs). Unfortunately, FPGA resources such as logic elements or Digital Signal Processing (DSP) units remain limited. This work presents a holistic method relying on approximate computing and design space exploration to optimize the DSP block utilization of a CNN implementation on FPGA. This method was tested when implementing a reconfigurable Optical Character Recognition (OCR) convolutional neural network on an Altera Stratix V device and varying both data representation and CNN topology in order to find the best combination in terms of DSP block utilization and classification accuracy. This exploration generated dataflow architectures of 76 CNN topologies with 5 different fixed point representation. Most efficient implementation performs 883 classifications/sec at 256 × 256 resolution using 8 % of the available DSP blocks.
Climate-related changes in export production off the Pacific coast of Mexico during the last deglaciation

Climate-related changes in the ocean’s oxygen minimum zones A striking feature of abrupt climate change during the last glacial period is the correlation between temperature proxy records from Greenland ice cores and the intensity of the oxygen minimum zone (OMZ) in the eastern North Pacifi c Ocean (Ortiz et al., 2004) and the Arabian Sea (Altabet et al., 2002). Oxygen concentrations decreased during warm interstadial periods, much like conditions today, whereas oxygen concentrations were much greater during cold stadials and the Last Glacial Maximum. Intensifi cation of the OMZ is manifested in several proxies, including concentrations in sediments of organic carbon and of redox-sensitive trace elements, as well as in nitrogen isotope indicators of denitrifi cation. Various investigators have attributed these features to either 1) changes in the supply of oxygen associated with the ventilation of intermediate water mass, or 2) local changes in productivity, as a result of ocean-atmosphere reorganizations, such as is seen during El Niño events today in the eastern North Pacifi c. Whereas evidence for changes in the intensity of the OMZ is unequivocal, most sedimentary proxies cannot discriminate between the two proposed causes because the impact of low bottomwater oxygen concentrations on the composition of marine sediments (e.g., carbon concentration; trace metal enrichment) is generally indistinguishable from that of high biological productivity and associated organic rain rates.
An Ultra-Low-Power 24 GHz Low-Noise Amplifier Using 0.13 $\mu{\rm m}$  CMOS Technology

This study presents an ultra-low-power 24 GHz low-noise amplifier (LNA) using 0.13 μm CMOS technology. We propose of using the minimum noise measure (MMIN) as the guideline to determine the optimal bias and geometry of the transistors in the circuit. The power-constrained simultaneous noise and input matching (PCSNIM) technique is also employed for this design. With the proposed design approach, the LNA achieves a peak gain of 9.2 dB and a minimum NF of 3.7 dB under a supply voltage of 1 V. The associated power consumption is only 2.78 mW.
Developing smart commercial real estate: Technology-based self-service (TBSS) in commercial real estate facilities

Real estate companies are central actors in the development of a smart city. However, most industry participants are conservative and prefer to utilize established, often un-integrated, technologies rather than deploy newer technologies that would help achieve the goals of the smart city. To evaluate the potential of smart commercial real-estate (CRE) we studied a Swedish commercial real estate firm that has developed and deployed a technology-based self-service (TBSS) to help tenants reduce energy consumption. The study was grounded in the theoretical service-dominant (S-D) logic lexicon and our results suggest that for commercial real estate firms to successfully implement TBSS they need to enhance their competence in three areas: management of information technology, within-organization and business-to-business networking skills. Further, these areas are inter-related and successful deployment of TBSS requires improvement in all three areas.
Polytypic Functions Over Nested Datatypes

The theory and practice of polytypic programming is intimately connected with the initial algebra semantics of datatypes. This is both a blessing and a curse. It is a blessing because the underlying theory is beautiful and well developed. It is a curse because the initial algebra semantics is restricted to so-called regular datatypes. Recent work by R. Bird and L. Meertens [3] on the semantics of non-regular or nested datatypes suggests that an extension to general datatypes is not entirely straightforward. Here we propose an alternative that extends polytypism to arbitrary datatypes, including nested datatypes and mutually recursive datatypes. The central idea is to use rational trees over a suitable set of functor symbols as type arguments for polytypic functions. Besides covering a wider range of types the approach is also simpler and technically less involving than previous ones. We present several examples of polytypic functions, among others polytypic reduction and polytypic equality. The presentation assumes some background in functional and in polytypic programming. A basic knowledge of monads is required for some of the examples.
Preface: Improving seismic networks performances: from site selection to data integration (EGU2014 SM1.2/GI3.7 session)

The number and quality of seismic stations and networks in Europe continually improves, nevertheless there is always scope to optimize their performance. In this EGU2014 SM1.2/GI3.7 session we welcomed contributions from all aspects of seismic network installation, operation and management. This includes site selection; equipment testing and installation; planning and implementing com- munication paths; policies for redundancy in data acquisi- tion, processing and archiving; and integration of different datasets including GPS and OBS.
Gene Deletions by Ends-In Targeting in Drosophila melanogaster

Following the advent of a gene targeting technique in Drosophila, different methods have been developed to modify the Drosophila genome. The initial demonstration of gene targeting in flies used an ends-in method, which generates a duplication of the target locus. The duplicated locus can then be efficiently reduced to a single copy by generating a double-strand break between the duplicated segments. This method has been used to knock out target genes by introducing point mutations. A derivative of this method is reported here. By using different homologous regions for the targeting and reduction steps, a complete deletion of the target gene can be generated to produce a definitive null allele. The breakpoints of the deletion can be precisely controlled. Unlike ends-out targeting, this method does not leave exogenous sequence at the deleted locus. Three endogenous genes, Sir2, Sirt2, and p53 have been successfully deleted using this method.
Mitigating attacks against virtual coordinate based routing in wireless sensor networks

Virtual coordinate system (VCS) based routing provides a practical, efficient and scalable means for point-to-point routing in wireless sensor networks. Several VCS-based routing protocols have been proposed in the last few years, all assuming that nodes behave correctly. However, many applications require deploying sensor networks in adversarial environments, making VCS-based routing protocols vulnerable to numerous attacks. In this paper, we study the security of VCS-based routing protocols. We first identify novel attacks targeting the underlying virtual coordinate system. The attacks can be mounted with little resource, yet are epidemic in nature and highly destructive to system performance. We then propose lightweight defense mechanisms against each of the identified attacks. Finally, we evaluate experimentally the impact of the attacks and the effectiveness of our defense mechanisms using a well-known VCS-based routing protocol, BVR.
An integrative approach to predicting the functional effects of non-coding and coding sequence variation

Motivation: Technological advances have enabled the identification of an increasingly large spectrum of single nucleotide variants within the human genome, many of which may be associated with monogenic disease or complex traits. Here, we propose an integrative approach, named FATHMM-MKL, to predict the functional consequences of both coding and non-coding sequence variants. Our method utilizes various genomic annotations, which have recently become available, and learns to weight the significance of each component annotation source. Results: We show that our method outperforms current state-of-the-art algorithms, CADD and GWAVA, when predicting the functional consequences of non-coding variants. In addition, FATHMM-MKL is comparable to the best of these algorithms when predicting the impact of coding variants. The method includes a confidence measure to rank order predictions. Availability and implementation: The FATHMM-MKL webserver is available at: http://fathmm.biocompute. org.uk Contact: H.Shihab@bristol.ac. uk or Mark.Rogers@bristol.ac. uk or C.Campbell@bristol.ac. uk Supplementary information: Supplementary data are available at Bioinformatics online.
The development of CAR design for tumor CAR-T cell therapy

In recent years, the chimeric antigen receptor modified T cells (Chimeric antigen receptor T cells, CAR-T) immunotherapy has developed rapidly, which has been considered the most promising therapy. Efforts to enhance the efficacy of CAR-based anti-tumor therapy have been made, such as the improvement of structures of CAR-T cells, including the development of extracellular antigen recognition receptors, intracellular co-stimulatory molecules and the combination application of CARs and synthetic small molecules. In addition, effects on the function of the CAR-T cells that the space distance between the antigen binding domains and tumor targets and the length of the spacer domains have are also being investigated. Given the fast-moving nature of this field, it is necessary to make a summary of the development of CAR-T cells. In this review, we mainly focus on the present design strategies of CAR-T cells with the hope that they can provide insights to increase the anti-tumor efficacy and safety.
VPS29 Is Not an Active Metallo-Phosphatase but Is a Rigid Scaffold Required for Retromer Interaction with Accessory Proteins

VPS29 is a key component of the cargo-binding core complex of retromer, a protein assembly with diverse roles in transport of receptors within the endosomal system. VPS29 has a fold related to metal-binding phosphatases and mediates interactions between retromer and other regulatory proteins. In this study we examine the functional interactions of mammalian VPS29, using X-ray crystallography and NMR spectroscopy. We find that although VPS29 can coordinate metal ions Mn2+ and Zn2+ in both the putative active site and at other locations, the affinity for metals is low, and lack of activity in phosphatase assays using a putative peptide substrate support the conclusion that VPS29 is not a functional metalloenzyme. There is evidence that structural elements of VPS29 critical for binding the retromer subunit VPS35 may undergo both metal-dependent and independent conformational changes regulating complex formation, however studies using ITC and NMR residual dipolar coupling (RDC) measurements show that this is not the case. Finally, NMR chemical shift mapping indicates that VPS29 is able to associate with SNX1 via a conserved hydrophobic surface, but with a low affinity that suggests additional interactions will be required to stabilise the complex in vivo. Our conclusion is that VPS29 is a metal ion-independent, rigid scaffolding domain, which is essential but not sufficient for incorporation of retromer into functional endosomal transport assemblies.
Use of Market Data to Assess Bushmeat Hunting Sustainability in Equatorial Guinea

Abstract: Finding an adequate measure of hunting sustainability for tropical forests has proved difficult. Many researchers have used urban bushmeat market surveys as indicators of hunting volumes and composition, but no analysis has been done of the reliability of market data in reflecting village offtake. We used data from urban markets and the villages that supply these markets to examine changes in the volume and composition of traded bushmeat between the village and the market (trade filters) in Equatorial Guinea. We collected data with market surveys and hunter offtake diaries. The trade filters varied depending on village remoteness and the monopoly power of traders. In a village with limited market access, species that maximized trader profits were most likely to be traded. In a village with greater market access, species for which hunters gained the greatest income per carcass were more likely to be traded. The probability of particular species being sold to market also depended on the capture method and season. Larger, more vulnerable species were more likely to be supplied from less‐accessible catchments, whereas there was no effect of forest cover or human population density on probability of being sold. This suggests that the composition of bushmeat offtake in an area may be driven more by urban demand than the geographic characteristics of that area. In one market, traders may have reached the limit of their geographical exploitation range, and hunting pressure within that range may be increasing. Our results demonstrate that it is possible to model the trade filters that bias market data, which opens the way to developing more robust market‐based sustainability indices for the bushmeat trade.
Mapping Image-schemas and Translating Metaphors

In this paper we demonstrate that identifying the mappings between the source and target domains for a conceptual metaphor allows for both a greater understanding of the conceptual basis of metaphors, and more effective language translation. We first introduce and explain the Animal Metaphor to support our idea. We show that the Animal Metaphor exists in both English and Chinese, but that it maps different information from the source to the target domain. We then propose three principled steps to aid in the translation of metaphors from one language to another, using the animal metaphor as an example. Lastly, we summarize our findings and discuss future areas of research.
Precision Positioning of Hard Disk Drives Using Piezoelectric Actuators with Passive Damping

Positioning precision is crucial to today's increasingly high-speed, high-capacity, high data density, and miniaturized hard disk drives (HDDs). The demand for higher bandwidth servo systems that can quickly and precisely position the read/write head on a high track density becomes more pressing. Recently, the idea of applying dual-stage actuators to track servo systems has been studied. The push-pull piezoelectrically actuated devices have been developed as micro actuators for fine and fast positioning, while the voice coil motor functions as a large but coarse seeking. However, the current dual-stage actuator design uses piezoelectric patches only without passive damping. In this paper, we propose a dual-stage servo system using enhanced active-passive hybrid piezoelectric actuators. The proposed actuators improve the existing dual-stage actuators for higher precision and shock resistance, due to the incorporation of passive damping in the design. We aim to develop this hybrid servo system not only to increase speed of track seeking but also to improve precision of track following servos in HDDs. New piezoelectrically actuated suspensions with passive damping have been designed and fabricated. In order to evaluate positioning precision for the dual-stage servo systems, simulation and experiments are carried out to implement the active-passive hybrid suspension with enhanced piezoelectric actuators using a composite nonlinear feedback controller
An approximation algorithm for shortest path based on the hierarchy networks

It is a critical issue to compute the shortest paths between nodes in networks. Exact algorithms for shortest paths are usually inapplicable for large scale networks due to the high computational complexity. In this paper, we propose a novel algorithm that is applicable for large networks with high efficiency and accuracy. The basic idea of our algorithm is to iteratively construct higher level hierarchy networks by condensing the central nodes and their neighbors into super nodes until the scale of the top level network is very small. Then the algorithm approximates the distances of the shortest paths in the original network with the help of super nodes in the higher level hierarchy networks. The experiment results show that our algorithm achieves both good efficiency and high accuracy compared with other algorithms.
Dynamics of the Upper Oceanic Layers in Terms of Surface Quasigeostrophy Theory

In this study, the relation between the interior and the surface dynamics for nonlinear baroclinically unstable flows is examined using the concepts of potential vorticity. First, it is demonstrated that baroclinic unstable flows present the property that the potential vorticity mesoscale and submesoscale anomalies in the ocean interior are strongly correlated to the surface density anomalies. Then, using the invertibility of potential vorticity, the dynamics are decomposed in terms of a solution forced by the three-dimensional (3D) potential vorticity and a solution forced by the surface boundary condition in density. It is found that, in the upper oceanic layers, the balanced flow induced only by potential vorticity is strongly anticorrelated with that induced only by the surface density with a dominance of the latter. The major consequence is that the 3D balanced motions can be determined from only the surface density and the characteristics of the basin-scale stratification by solving an elliptic equation. These properties allow for the possibility to reconstruct the 3D balanced velocity field of the upper layers from just the knowledge of the surface density by using a simpler model, that is, an “effective” surface quasigeostrophic model. All these results are validated through the examination of a primitive equation simulation reproducing the dynamics of the Antarctic Circumpolar Current.