Miracle-dz/UniFAR-FTUs huggingface dataset:
Phylogeography of Tetrancistrum nebulosi (Monogenea, Dactylogyridae) on the host of mottled spinefoot (Siganus fuscescens) in the South China Sea, inferred from mitochondrial COI and ND2 genes

Abstract To examine the phylogeographical pattern of Tetrancistrum nebulosi (Monogenea, Dactylogyridae) in the South China Sea, fragments of mitochondrial cytochrome c oxidase subunit I and NADH dehydrogenase subunit 2 genes were obtained for 220 individuals collected from 8 localities along the southeast coast of China and 1 locality in Terengganu, Malaysia. Based on these two genes, two and three distinct clades with geographic signals were revealed on the phylogenetic trees respectively. The divergence between these clades was estimated to occur in the late Pleistocene. Analysis of molecular variance and pairwise FST suggested a high rate of gene flow among individuals sampled from the Chinese coast, but with obvious genetic differentiation from the Malaysian population. Mismatch distribution and neutrality tests indicated that the T. nebulosi population experienced expansion in Pleistocene low sea level periods. Vicariance was considered to account for the genetic divergence between Chinese and Malaysian populations, while sea level fluctuations and mainland-island connections during glacial cycles were associated with the slight genetic divergence between the populations along the mainland coast of China and those off Sanya. On the contrary, oceanographic circulations and host migration could lead to genetic homogeneity of populations distributed along the mainland coast of China.
A 4-Transistor nMOS-Only Logic-Compatible Gain-Cell Embedded DRAM With Over 1.6-ms Retention Time at 700 mV in 28-nm FD-SOI

Gain-cell embedded DRAM (GC-eDRAM) is a possible alternative to traditional static random access memories (SRAM). While GC-eDRAM provides high-density, low-leakage, low-voltage, and inherent2-ported operation, its limited retention time requires periodic, power-hungry refresh cycles. This drawback is further aggravated at scaled technologies, where increased subthreshold leakage currents and decreased in-cell storage capacitances result in faster data integrity deterioration. Therefore, integration of GC-eDRAM within modern systems is often considered to be limited to mature process technologies, where these phenomena are less detrimental. In this paper, we present for the first time a fully functional GC-eDRAM array, implemented and fabricated in a 28-nm process node. The 8-kb array is based on a novel, 2-ported, 4-transistor NMOS-only bitcell with internal feedback to provide efficient operation in the target 28-nm FD-SOI technology. The fabricated memory macro achieves more than 1.6-ms data retention time at 27 °C, which is $30\times $ longer than conventional gain-cell topologies when applied to this technology. The described 4-transistor dual-port nMOS array utilizes over 70% of the total memory macro area, while retaining almost 30% lower cell area than a single-ported 6T SRAM in the same technology.
Similar Cerebral Motor Plans for Real and Virtual Actions

A simple movement, such as pressing a button, can acquire different meanings by producing different consequences, such as starting an elevator or switching a TV channel. We evaluated whether the brain activity preceding a simple action is modulated by the expected consequences of the action itself. To further this aim, the motor-related cortical potentials were compared during two key-press actions that were identical from the kinematics point of view but different in both meaning and consequences. In one case (virtual grasp), the key-press started a video clip showing a hand moving toward a cup and grasping it; in the other case, the key-press did not produce any consequence (key-press). A third condition (real grasp) was also compared, in which subjects actually grasped the cup, producing the same action presented in the video clip. Data were collected from fifteen subjects. The results showed that motor preparation for virtual grasp (starting 3 s before the movement onset) was different from that of the key-press and similar to the real grasp preparation–as if subjects had to grasp the cup in person. In particular, both virtual and real grasp presented a posterior parietal negativity preceding activity in motor and pre-motor areas. In summary, this finding supports the hypothesis that motor preparation is affected by the meaning of the action, even when the action is only virtual.
Determining Signalling Nodes for Apoptosis by a Genetic High-Throughput Screen

Background With the ever-increasing information emerging from the various sequencing and gene annotation projects, there is an urgent need to elucidate the cellular functions of the newly discovered genes. The genetically regulated cell suicide of apoptosis is especially suitable for such endeavours as it is governed by a vast number of factors. Methodology/Principal Findings We have set up a high-throughput screen in 96-well microtiter plates for genes that induce apoptosis upon their individual transfection into human cells. Upon screening approximately 100,000 cDNA clones we determined 74 genes that initiate this cellular suicide programme. A thorough bioinformatics analysis of these genes revealed that 91% are novel apoptosis regulators. Careful sequence analysis and functional annotation showed that the apoptosis factors exhibit a distinct functional distribution that distinguishes the cell death process from other signalling pathways. While only a minority of classic signal transducers were determined, a substantial number of the genes fall into the transporter- and enzyme-category. The apoptosis factors are distributed throughout all cellular organelles and many signalling circuits, but one distinct signalling pathway connects at least some of the isolated genes. Comparisons with microarray data suggest that several genes are dysregulated in specific types of cancers and degenerative diseases. Conclusions/Significance Many unknown genes for cell death were revealed through our screen, supporting the enormous complexity of cell death regulation. Our results will serve as a repository for other researchers working with genomics data related to apoptosis or for those seeking to reveal novel signalling pathways for cell suicide.
Expression Profiling of Human Genetic and Protein Interaction Networks in Type 1 Diabetes

Proteins contributing to a complex disease are often members of the same functional pathways. Elucidation of such pathways may provide increased knowledge about functional mechanisms underlying disease. By combining genetic interactions in Type 1 Diabetes (T1D) with protein interaction data we have previously identified sets of genes, likely to represent distinct cellular pathways involved in T1D risk. Here we evaluate the candidate genes involved in these putative interaction networks not only at the single gene level, but also in the context of the networks of which they form an integral part. mRNA expression levels for each gene were evaluated and profiling was performed by measuring and comparing constitutive expression in human islets versus cytokine-stimulated expression levels, and for lymphocytes by comparing expression levels among controls and T1D individuals. We identified differential regulation of several genes. In one of the networks four out of nine genes showed significant down regulation in human pancreatic islets after cytokine exposure supporting our prediction that the interaction network as a whole is a risk factor. In addition, we measured the enrichment of T1D associated SNPs in each of the four interaction networks to evaluate evidence of significant association at network level. This method provided additional support, in an independent data set, that two of the interaction networks could be involved in T1D and highlights the following processes as risk factors: oxidative stress, regulation of transcription and apoptosis. To understand biological systems, integration of genetic and functional information is necessary, and the current study has used this approach to improve understanding of T1D and the underlying biological mechanisms.
Steady‐state analysis of a novel ZVT interleaved boost converter

In this paper, a novel soft‐switched interleaved boost converter composed of two‐cell boost conversion units and an auxiliary circuit is proposed and investigated. The proposed auxiliary circuit is implemented using only one auxiliary switch and a minimum number of passive components without an effective increase in the cost and the complexity of the converter. The main advantage of this auxiliary circuit is that it not only provides zero‐voltage‐transition (ZVT) for the main switches but also provides soft switching for the auxiliary switch and diodes. Though all semiconductor devices operate under soft switching, they do not have any additional voltage and current stresses. The proposed converter operates successfully in soft‐switching operation mode for a wide range of input voltage level and the load. In addition, it has advantages such as fewer structure complications, lower cost and ease of control. Since the two‐cell interleaved boost units are identical, operational analysis and design for the converter module become quite simple. In this study, the detailed steady‐state theoretical analysis of the proposed converter is presented, which is verified exactly by simulation and experiments carried out on a prototype of a 120 W and 50 kHz/cell interleaved boost converter. The practical results confirm the results obtained from theoretical analysis. Copyright © 2010 John Wiley & Sons, Ltd.
Transcriptional fidelities of human mitochondrial POLRMT, yeast mitochondrial Rpo41, and phage T7 single-subunit RNA polymerases

Single-subunit RNA polymerases (RNAPs) are present in phage T7 and in mitochondria of all eukaryotes. This RNAP class plays important roles in biotechnology and cellular energy production, but we know little about its fidelity and error rates. Herein, we report the error rates of three single-subunit RNAPs measured from the catalytic efficiencies of correct and all possible incorrect nucleotides. The average error rates of T7 RNAP (2 × 10−6), yeast mitochondrial Rpo41 (6 × 10−6), and human mitochondrial POLRMT (RNA polymerase mitochondrial) (2 × 10−5) indicate high accuracy/fidelity of RNA synthesis resembling those of replicative DNA polymerases. All three RNAPs exhibit a distinctly high propensity for GTP misincorporation opposite dT, predicting frequent A→G errors in RNA with rates of ∼10−4. The A→C, G→A, A→U, C→U, G→U, U→C, and U→G errors mostly due to pyrimidine–purine mismatches were relatively frequent (10−5–10−6), whereas C→G, U→A, G→C, and C→A errors from purine–purine and pyrimidine–pyrimidine mismatches were rare (10−7–10−10). POLRMT also shows a high C→A error rate on 8-oxo-dG templates (∼10−4). Strikingly, POLRMT shows a high mutagenic bypass rate, which is exacerbated by TEFM (transcription elongation factor mitochondrial). The lifetime of POLRMT on terminally mismatched elongation substrate is increased in the presence of TEFM, which allows POLRMT to efficiently bypass the error and continue with transcription. This investigation of nucleotide selectivity on normal and oxidatively damaged DNA by three single-subunit RNAPs provides the basic information to understand the error rates in mitochondria and, in the case of T7 RNAP, to assess the quality of in vitro transcribed RNAs.
An encapsulated authentication logic for reasoning about key distribution protocols

Authentication and secrecy properties are proved by very different methods: the former by local reasoning, leading to matching knowledge of all principals about the order of their actions, the latter by global reasoning towards the impossibility of knowledge of some data. Hence, proofs conceptually decompose in two parts, each encapsulating the other as an assumption. From this observation, we develop a simple logic of authentication that encapsulates secrecy requirements as assumptions. We apply it within the derivational framework to derive a large class of key distribution protocols based on the authentication properties of their components.
Basin-scale availability of salmonid spawning gravel as influenced by channel type and hydraulic roughness in mountain catchments

A general framework is presented for examining the effects of channel type and associated hydraulic roughness on salmonid spawning-gravel availability in mountain catchments. Digital elevation models are coupled with grain-size predictions to provide basin-scale assessments of the potential extent and spatial pattern of spawning gravels. To demonstrate both the model and the significance of hydraulic roughness, we present a scenario for optimizing the spatial extent of spawning gravels as a function of channel type in Pacific Northwest catchments. Predictions indicate that hydraulic roughness could control more than 65% of the potential available spawning habitat at our study sites. Results further indicate that bar roughness can be important for maintaining spawning gravels in lower mainstem reaches, while wood roughness may be required for spawning-gravel maintenance in steeper, upper mainstem channels. Our analysis indicates that wood loss and consequent textural coarsening could deplete up to one third of the potentially usable spawning area at our study sites.
A combined all-digital PLL-buck slack regulation system with autonomous CCM/DCM transition control and 82% average voltage-margin reduction in a 0.6-to-1.0V cortex-M0 processor

Integrated Voltage Regulation (IVR) using buck converters enables efficient, fine-grained supply-voltage control in modern SoC domains [1]. However, existing IVR implementations face several challenges. As voltage domains continue to shrink, reduced per-domain decoupling capacitance requires rapid IVR transient response, leading to unfavorable efficiency and supply droop margin trade-offs. Additionally, digital domains exhibit a wide load current (Iload) range, requiring capabilities for autonomous transition between Continuous Conduction Mode (CCM) and Discontinuous Conduction Mode (DCM). All-digital IVR solutions are particularly desirable for ease of integration in SoCs.
Cloning and expression of coxsakievirus B3 viral protein-1 in E. coli.

BACKGROUND Viral protein-1 (VP1) is a major capsid protein of Coxsakievirus B3 (CVB3) that plays an important role in directing viruses towards permissive cells and acts as a main antigenic site of the virus in eliciting of host immune response, hence it seems VP1 can be considered as a vaccine candidate against CVB3 infection. In this study, cDNA of VP1 was prepared, cloned into pET expression vector and the recombinant protein (VP1) was over expressed in E. coli. METHODS The viruses were grown in suspension cultures of Vero cells with an input virus multiplicity of 10-50 plaque-forming units/cell. After observing complete cytopathic effect, the total RNA (cells and virus) was prepared for RT-PCR and by using specific primers, VP1 cDNA was amplified and ligated into pET vectors (32 a and 28 a). The recombinant vector was transferred into competent E. coli (BL-21) and after selection of proper colony, which carried correct cDNA within the vector; cells were cultured and induced with isopropyl B-D-thiogalactopyranoside, in order to express protein (VP1). The cultures were tested for presence of VP1 by SDS-PAGE and Western-Blotting analysis. RESULTS Molecular techniques such as PCR which showed exact defined size of the VP1 (819 bp), restriction digestion and finally immunoblot analysis of over expressed protein; all confirmed the correct cloning and expression of VP1 in this research. CONCLUSION In this research, full length of VP1 as major capsid protein of CVB3 was over expressed in E. coli which, can be used for further studies, including neutralizing antibody production against CVB3.
Hyperbolic metamaterials-based plasmonic biosensor for fluid biopsy with single molecule sensitivity

Plasmonic sensors are one of the most powerful optical biosensors, which can be used for the detection of small numbers of molecules at ultra-low concentrations. However, the detection of dilute analytes of low molecular weight (<500 Da) is still a challenging task using currently available plasmonic biosensors. Here, we demonstrate the detection of both lower and heavier molecular weight biomolecules close to single molecule level using a novel plasmonic biosensor platform based on hyperbolic metamaterials. We show experimentally the extraordinary spectral and angular sensitivities of the biosensor platform, from visible to near infrared (NIR) wavelengths, by exciting the bulk plasmon polaritons associated with hyperbolic metamaterials.
DAP: LSTM-CRF Auto-encoder

The LSTM-CRF is a hybrid graphical model which achieves state-of-the-art performance in supervised sequence labeling tasks. Collecting labeled data consumes lots of human resources and time. Thus, we want to improve the performance of LSTM-CRF by semi-supervised learning. Typically, people use pre-trained word representation to initialize models embedding layer from unlabeled data. However, these word representations are model-agnostic, which means they were trained without knowledge of the LSTM-CRFs structure. Thus, we introduce auto-encoder training for the LSTM-CRF to tune the models parameters by adding a decoder after the CRF. We compare the performance of these two meth-ods and ﬁnd that while the auto-encoder can improve performance in some situation, the model-agnostic approach achieves more universal improvement. We also how to use mini-batches in LSTM-CRF.
TSTE: A Time-variant Stochastic Trust Evaluation Model in Social Networks

Building appropriate trust evaluation models is an important research issue for security guarantee in social networks. Most of the existing works usually consider the trust values at the current time slot, and model trust as the stochastic variable. However, in fact, trust evolves over time, and trust is a stochastic process. In this paper, we propose a novel time-variant stochastic trust evaluation (TSTE) model, which models trust over time and captures trust evolution by a stochastic process. Based on the proposed model, we derive the time-variant bound of untrustworthy probability, which provides stochastic trust guarantee. On one hand, the time-variant trust level of each node can be measured by our model. Meanwhile, by tolerating nodes with relatively poor performance, our model can effectively improve the node resource utilization rate. Numerical simulations are conducted to verify the accuracy and consistency of the analytical bounds on distinguishing misbehaved nodes from normal ones. Moreover, simulation results on social network dataset show the tradeoff between trust level and resource utilization rate, and verify that the successful transmission rate can be improved by our model.
Harnessing the Potential of Biomaterials for Brain Repair after Stroke

Stroke is a devastating disease for which no clinical treatment exists to regenerate lost tissue. Strategies for brain repair in animal models of stroke include the delivery of drug or cell-based therapeutics; however, the complex anatomy and functional organization of the brain presents many challenges. Biomaterials may alleviate some of these challenges by providing a scaffold, localizing the therapy to the site of action, and/or modulating cues to brain cells. Here, the challenges associated with delivery of therapeutics to the brain and the biomaterial strategies used to overcome these challenges are described. For example, innovative hydrogel delivery systems have been designed to provide sustained trophic factor delivery for endogenous repair and to support transplanted cell survival and integration. Novel treatments, such as electrical stimulation of transplanted cells and the delivery of factors for the direct reprogramming of astrocytes into neurons, may be further enhanced by biomaterial delivery systems. Ultimately, improved clinical translation will be achieved by combining clinically relevant therapies with biomaterials strategies.
NTCIR-12 MOBILECLICK: Sense-based Ranking and Summarization of English Queries

NTCIR-12 MobileClick task has been designed to rank and summarize English queries. The primary aim of this task was to develop a system which is capable of minimizing interaction between the human users and mobile phones while extracting relevant data with respect to given queries. Organizers provided the data represented as information units (iUnits). Each of the iUnits describes a pertinent query associated with other information like type or category, relevance, sense and knowledge-based relations [1] [2] [4]. The task is divided into two sub-tasks namely ranking and summarization. The ranking sub-task focuses on identifying the important iUnits related to a query. In the summarization sub-task, the output has to be designed as a two-layered model where the first layer will identify the important iUnits and the second layer will compile those important iUnits and generate a summarized output for the query. In this present task, we have employed several sentiment lexicons like SentiWordNet 1 , SenticNet 2 etc. with tabulation based approaches to identify the important query-based iUnits for ranking and summarization. Our sense-based system has achieved a score of 0.8859 mean Q-measure for ranking and score of 11.7033 mean M-measure for summarization tasks, respectively.
Temporal metastates are associated with differential patterns of time-resolved connectivity, network topology, and attention

Significance The brain is an inherently dynamic organ; however, the manner in which the brain changes over longitudinal time remains poorly understood. An understanding of these dynamic mechanisms is critical for understanding normal childhood development and aging as well as neurological and psychiatric disease states. Here, we leverage data collected in a single individual over the course of 2 y to investigate changes in brain organization over time. In doing so, we show intermittent fluctuations in brain network configuration that were associated with separable patterns of time-resolved interactions between neural regions. The states also directly relate to alterations in whole-brain information processing and self-reported attention. In addition, the patterns that we observed were replicated in a separate longitudinal dataset. Little is currently known about the coordination of neural activity over longitudinal timescales and how these changes relate to behavior. To investigate this issue, we used resting-state fMRI data from a single individual to identify the presence of two distinct temporal states that fluctuated over the course of 18 mo. These temporal states were associated with distinct patterns of time-resolved blood oxygen level dependent (BOLD) connectivity within individual scanning sessions and also related to significant alterations in global efficiency of brain connectivity as well as differences in self-reported attention. These patterns were replicated in a separate longitudinal dataset, providing additional supportive evidence for the presence of fluctuations in functional network topology over time. Together, our results underscore the importance of longitudinal phenotyping in cognitive neuroscience.