Miracle-dz/UniFAR-FTUs huggingface dataset:
Chaos-guided Input Structuring for Improved Learning in Recurrent Neural Networks

Anatomical studies demonstrate that brain reformats input information to generate reliable responses for performing computations. However, it remains unclear how neural circuits encode complex spatio-temporal patterns. We show that neural dynamics are strongly influenced by the phase alignment between the input and the spontaneous chaotic activity. Input structuring along the dominant chaotic projections causes the chaotic trajectories to become stable channels (or attractors), hence, improving the computational capability of a recurrent network. Using mean field analysis, we derive the impact of input structuring on the overall stability of attractors formed. Our results indicate that input alignment determines the extent of intrinsic noise suppression and hence, alters the attractor state stability, thereby controlling the network's inference ability.
Epidemic characteristics of hand, foot, and mouth disease in Shanghai from 2009 to 2010: Enterovirus 71 subgenotype C4 as the primary causative agent and a high incidence of mixed infections with coxsackievirus A16

Abstract Background: Enterovirus 71 (EV71) has been the main causative agent of hand, foot, and mouth disease (HFMD) outbreaks in recent years. A significant increase in the number of HFMD cases in China over the last 3 y has made the public prevention and therapy of this disease a critical issue. Methods: A total of 3208 HFMD patients in Shanghai during the period 2009 to 2010 were analyzed; 437 clinical specimens were collected for the determination of causative pathogens. Eight of the isolated EV71 strains were sequenced and phylogenetically analyzed. Results: The widespread outbreak of HFMD in Shanghai was caused predominantly by EV71 (86.5%), and in part by coxsackievirus A16 (CA16) (6.9%). The high incidence of mixed infections with EV71 and CA16 (17.6% of the total CA16-infected cases) has never before been observed in China. Most HFMD patients (76.9%) were aged 1–4 y. Boys showed a higher HFMD prevalence rate (65.3%) than girls (34.7%). Phylogenetic analysis on the basis of the VP1 gene and the complete genome sequences revealed that the EV71 strains that circulated in Shanghai belonged to the C4 subgenotype. Conclusions: EV71 subgenotype C4 was the major causative agent of the HFMD outbreak in Shanghai. A high incidence of mixed infections with EV71 and CA16 was also observed.
Dynamic Expression Changes in the Transcriptome of the Prefrontal Cortex after Repeated Exposure to Cocaine in Mice

Prefrontal cortex (PFC)-dependent functions, such as executive function, explicit learning, and memory, are negatively affected in cocaine abusers and experimental animal models of cocaine treatment. However, its molecular mechanisms are less understood. In the present study, we performed transcriptome profiling of the dynamic changes in the PFC after repeated cocaine administration in mice. We found 463, 14, and 535 differentially expressed genes (DEGs) at 2 h, 24 h, and 7 days, respectively, after the withdrawal of chronic cocaine treatment. Time-series correlation analysis identified 5 clusters of statistically significant expression patterns. The expression levels of DEGs in Clusters 1 and 5 exhibited a gradual or fluctuant decrease, Cluster 2 exhibited an initial increase followed by a decrease or return to the baseline level, and Clusters 3 and 4 exhibited a fluctuant increase in the expression of DEGs. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that genes related to oxidative phosphorylation, ribosomes, and neurodegenerative disorder were enriched in Cluster 1; genes related to the mitogen activated protein kinase (MAPK), transforming growth factor (TGF)-β, insulin signaling, and circadian pathways were enriched in Cluster 2; genes related to plasticity-related pathways were enriched in Clusters 3 and 4; and genes related to the proteasome were enriched in Cluster 5. Our results suggest that maladaptive neural plasticity associated with psychostimulant dependence may be an ongoing degenerative process with dynamic changes in the gene network at different stages of withdrawal. Furthermore, it could be helpful to develop new therapeutic approaches according to different periods of abstinence.
The effectiveness of deduplication on virtual machine disk images

Virtualization is becoming widely deployed in servers to efficiently provide many logically separate execution environments while reducing the need for physical servers. While this approach saves physical CPU resources, it still consumes large amounts of storage because each virtual machine (VM) instance requires its own multi-gigabyte disk image. Moreover, existing systems do not support ad hoc block sharing between disk images, instead relying on techniques such as overlays to build multiple VMs from a single "base" image. Instead, we propose the use of deduplication to both reduce the total storage required for VM disk images and increase the ability of VMs to share disk blocks. To test the effectiveness of deduplication, we conducted extensive evaluations on different sets of virtual machine disk images with different chunking strategies. Our experiments found that the amount of stored data grows very slowly after the first few virtual disk images if only the locale or software configuration is changed, with the rate of compression suffering when different versions of an operating system or different operating systems are included. We also show that fixed-length chunks work well, achieving nearly the same compression rate as variable-length chunks. Finally, we show that simply identifying zero-filled blocks, even in ready-to-use virtual machine disk images available online, can provide significant savings in storage.
Formal Development of Path Discovery in AODV Routing Protocol using Event-B

In this paper, we present a formal model for path discovery process of the AODV protocol using Event-B. The model have been developed and checked using the RODIN tool which provides an integrated framework for development of Event-B models. Event-B technique uses a notion of refinement to specify the mathematical models of distributed systems in an incremental manner. The specifications of the system have been checked for consistency and satisfy the behavioural properties of the system expressed as invariants. All the proof obligations were discharged automatically by the RODIN tool.
GAN Q UALITY I NDEX ( GQI ) BY GAN-INDUCED C LASSIFIER

We propose an objective measure, called GAN Quality Index (GQI), to evaluate GANs. The idea is to train a GAN-induced classifier from the GAN generated data and use its accuracy on a real test set as a metric to measure how well the GAN model distribution matches the real data distribution. Unlike most existing quantitative measurements of GANs, which only reflect partial characteristics of generation distribution, the accuracy of the GAN-induced classifier can be used to derive a simple yet sufficient index to measure how well the generation distribution matches the true data distribution. We demonstrate the effectiveness of GQI on CIFAR-100, Flower-102, and MS-Celeb-1M which contains 10,000 classes.
Transcript-Specific Associations of SLC12A5 (KCC2) in Human Prefrontal Cortex with Development, Schizophrenia, and Affective Disorders

The neuron-specific K+-Cl− cotransporter SLC12A5, also known as KCC2, helps mediate the electrophysiological effects of GABA. The pattern of KCC2 expression during early brain development suggests that its upregulation drives the postsynaptic switch of GABA from excitation to inhibition. We previously found decreased expression of full-length KCC2 in the postmortem hippocampus of patients with schizophrenia, but not in the dorsolateral prefrontal cortex (DLPFC). Using PCR and rapid amplification of cDNA ends, we discovered several previously unrecognized alternative KCC2 transcripts in both human adult and fetal brain in addition to the previously identified full-length (NM_020708.3) and truncated (AK098371) transcripts. We measured the expression levels of four relatively abundant truncated splice variants, including three novel transcripts (ΔEXON6, EXON2B, and EXON6B) and one previously described transcript (AK098371), in a large human cohort of nonpsychiatric controls across the lifespan, and in patients with schizophrenia and affective disorders. In SH-SY5Y cell lines, these transcripts were translated into proteins and expressed at their predicted sizes. Expression of the EXON6B transcript is increased in the DLPFC of patients with schizophrenia (p = 0.03) but decreased in patients with major depression (p = 0.04). The expression of AK098371 is associated with a GAD1 single nucleotide polymorphism (rs3749034) that previously has been associated with GAD67 expression and risk for schizophrenia. Our data confirm the developmental regulation of KCC2 expression, and provide evidence that KCC2 transcripts are differentially expressed in schizophrenia and affective disorders. Alternate transcripts from KCC2 may participate in the abnormal GABA signaling in the DLPFC associated with schizophrenia.
Application of Nanoparticle Tracking Analysis (NTA) in Aqueous Solutions of TiO2

The study of nanoparticles involves a new field of research in various areas of technology, whose production and use have been recognized as multiple benefits to the society. However, the uncontrolled emission to the environment of nanoparticles is growing exponentially over the last decade. Thus, knowledge of the influence of nanoparticles and how they can modify the ecosystem is extremely importantand demand specific studies. Therefore, it is of fundamental importance to increase the knowledge of the interactions and transport of nanoparticles in soil, in particular this research will study the TiO2 nanoparticles (TiNPs). Aiming to improve such knowledge, this paper addressed tests on columns with soil collected in the landfill Volta Redonda located in the state of Rio de Janeiro, Brazil. Aliquots of TiO2-nanoparticle suspensions in soil were collected periodically after their preparation, and analyzed the aggregate of particles distribution and Ti concentration. Experimental results suggest that the higher stability of TiO2 suspensions resulted in a higher mobility of TiO2 through soil layers with lower retention rate.
Wavelet compression of parametrically coherent mesh sequences

We introduce an efficient compression method for animated sequences of irregular meshes of the same connectivity. Our approach is to transform the original input meshes with an anisotropic wavelet transform running on top of a progressive mesh hierarchy, and progressively encode the resulting wavelet details. For temporally coherent mesh sequences we get additional improvement by encoding the differences of the wavelet coefficients. The resulting compression scheme is scalable, efficient, and significantly improves upon the current state of the art for the animated mesh compression.
Protective Effects of L-902,688, a Prostanoid EP4 Receptor Agonist, against Acute Blood-Brain Barrier Damage in Experimental Ischemic Stroke

Ischemic stroke occurs when a clot forms in the brain vasculature that starves downstream tissue of oxygen and nutrients resulting in cell death. The tissue immediately downstream of the blockage, the core, dies within minutes, but the surrounding tissue, the penumbra is potentially salvageable. Prostaglandin E2 binds to four different G-protein coupled membrane receptors EP1–EP4 mediating different and sometimes opposing responses. Pharmacological activation of the EP4 receptor has already been established as neuroprotective in stroke, but the mechanism(s) of protection are not well-characterized. In this study, we hypothesized that EP4 receptor activation reduces ischemic brain injury by reducing matrix metalloproteinase (MMP)-3/-9 production and blood-brain barrier (BBB) damage. Rats underwent transient ischemic stroke for 90 min. Animals received an intravenous injection of either the vehicle or L-902,688, a highly specific EP4 agonist, at the onset of reperfusion. Brain tissue was harvested at 24 h. We established a dose-response curve and used the optimal dose that resulted in the greatest infarct reduction to analyze BBB integrity compared to vehicle-treated rats. The presence of IgG, a blood protein, in the brain parenchyma is a marker of BBB damage, and L-902,688 (1 mg/kg; i.v.) dramatically reduced IgG extravasation (P < 0.05). Consistent with these data, we assessed zona occludens-1 and occludin, tight junction proteins integral to the maintenance of the BBB, and found reduced degradation with L-902,688 administration. With immunoblotting, qRT-PCR, and/or a fluorescence resonance energy transfer (FRET)-based activity assay, we next measured MMP-3/-9 since they are key effectors of BBB breakdown in stroke. In the cerebral cortex, not only was MMP-3 activity significantly decreased (P < 0.05), but L-902,688 treatment also reduced MMP-9 mRNA, protein, and enzymatic activity (P < 0.001). In addition, post-ischemic administration of the EP4 agonist significantly reduced pro-inflammatory cytokines IL-1β (P < 0.05) and IL-6 (P < 0.01) in the ischemic cerebral cortex. Most importantly, one injection of L-902,688 (1 mg/kg; i.v) at the onset of reperfusion significantly reduces neurological deficits up to 3 weeks later (P < 0.05). Our data show for the first time that pharmacological activation of EP4 with L-902,688 is neuroprotective in ischemic stroke by reducing MMP-3/-9 and BBB damage.
Microstructure and magnetorheological properties of the thermoplastic magnetorheological elastomer composites containing modified carbonyl iron particles and poly(styrene-b-ethylene-ethylenepropylene-b-styrene) matrix

Novel isotropic and anisotropic thermoplastic magnetorheological elastomers (MRE) were prepared by melt blending titanated coupling agent modified carbonyl iron (CI) particles with poly(styrene-b-ethylene-ethylene–propylene-b-styrene) (SEEPS) matrix in the absence and presence of a magnetic field, and the microstructure and magnetorheological properties of these SEEPS-based MRE were investigated in detail. The particle surface modification improves the dispersion of the particles in the matrix and remarkably softens the CI/SEEPS composites, thus significantly enhancing the MR effect and improving the processability of these SEEPS-based MRE. A microstructural model was proposed to describe the interfacial compatibility mechanism that occurred in the CI/SEEPS composites after titanate coupling agent modification, and validity of this model was also demonstrated through adsorption tests of unmodified and surface-modified CI particles.
Characterization of C-PDMS electrodes for electrokinetic applications in microfluidic systems

This paper reports on the integration of thick carbon-polydimethylsiloxane (C-PDMS) electrodes in microfluidic systems for electrokinetic operations. The C-PDMS material, obtained by mixing carbon nanopowder and PDMS, preserves PDMS processing properties such as O2 plasma activation and soft-lithography patternability in thick or 3D electrodes. Conductivity in the order of 10 S m−1 was reached for a carbon concentration of 25 wt%. To evaluate the adhesion between PDMS and C-PDMS, we prepared bi-material strips and carried out a manual pull test. The cohesion and robustness of C-PDMS were also evaluated by applying a large range of electric field conditions from dc to ac (300 kHz). No damage to the electrodes or release of carbon was noticed. The use of such a material for electrokinetic manipulation was validated on polystyrene particles and cells. Here, we demonstrate that C-PDMS seems to be a valuable technological solution for electrokinetic in microfluidic and particularly for biological applications such as cell electrofusion, lysis and trapping, which are favored by uniform lateral electric fields across the microchannel section.
Center-of-Mass-Based Grasp Pose Adaptation Using 3D Range and Force/Torque Sensing

Lifting objects, whose mass may produce high wrist torques that exceed the hardware strength limits, could lead to unstable grasps or serious robot damage. This work introduces a new Center-of-Mass (CoM)-based grasp pose adaptation method, for picking up objects using a combination of exteroceptive 3D perception and proprioceptive force/torque sensor feedback. The method works in two iterative stages to provide reliable and wrist torque efficient grasps. Initially, a geometric object CoM is estimated from the input range data. In the first stage, a set of hand-size handle grasps are localized on the object and the closest to its CoM is selected for grasping. In the second stage, the object is lifted using a single arm, while the force and torque readings from the sensor on the wrist are monitored. Based on these readings, a displacement to the new CoM estimation is calculated. The object is released and the process is repeated until the wrist torque effort is minimized. The advantage of our method is the blending of both exteroceptive (3D range) and proprioceptive (force/torque) sensing for finding the grasp location that minimizes the wrist effort, potentially improving the reliability of the grasping and the subsequent manipulation task. We experimentally validate the proposed method by executing a number of tests on a set of objects that include handles, using the humanoid robot WALK-MAN.
A Dataset To Evaluate The Representations Learned By Video Prediction Models

We present a parameterized synthetic dataset called Moving Symbols to support the objective study of video prediction networks. Using several instantiations of the dataset in which variation is explicitly controlled, we highlight issues in an existing state-of-the-art approach and propose the use of a performance metric with greater semantic meaning to improve experimental interpretability. Our dataset provides canonical test cases that will help the community better understand, and eventually improve, the representations learned by such networks in the future. Code is available at this https URL .
OFDM Visible Light Wireless Communication Based on White LEDs

White LEDs are set to penetrate many areas of everyday life. An interesting property of these devices (in addition to their lightening capabilities) is that they can be utilised for data transmission. In the past, primarily OOK (on-off keying) has been used for digital data modulation of such devices. OOK imposes limitations on the achievable data rates. Therefore, in this paper OFDM is considered in combination with higher order modulation schemes. A hardware demonstrator with an entire link chain (transmitter and receiver) is developed and measured BER (bit error ratio) results are reported. The system uses pilot sub-carriers to correct frequency synchronisation errors, training sequences for channel estimation and time synchronisation routines. Forward error correction (FEC) coding is used. It is shown that for COFDM (coded OFDM) with QPSK (quadrature phase shift keying) modulation and a single LED, a BER of 2 times 10-5 is achieved for a distance of 90 cm between transmitter and receiver.
Mining high utility itemsets without candidate generation

High utility itemsets refer to the sets of items with high utility like profit in a database, and efficient mining of high utility itemsets plays a crucial role in many real-life applications and is an important research issue in data mining area. To identify high utility itemsets, most existing algorithms first generate candidate itemsets by overestimating their utilities, and subsequently compute the exact utilities of these candidates. These algorithms incur the problem that a very large number of candidates are generated, but most of the candidates are found out to be not high utility after their exact utilities are computed. In this paper, we propose an algorithm, called HUI-Miner (High Utility Itemset Miner), for high utility itemset mining. HUI-Miner uses a novel structure, called utility-list, to store both the utility information about an itemset and the heuristic information for pruning the search space of HUI-Miner. By avoiding the costly generation and utility computation of numerous candidate itemsets, HUI-Miner can efficiently mine high utility itemsets from the utility-lists constructed from a mined database. We compared HUI-Miner with the state-of-the-art algorithms on various databases, and experimental results show that HUI-Miner outperforms these algorithms in terms of both running time and memory consumption.
IFELONG L EARNING WITH D YNAMICALLY E XPANDABLE N ETWORKS

We propose a novel deep network architecture for lifelong learning which we refer to as Dynamically Expandable Network (DEN), that can dynamically decide its network capacity as it trains on a sequence of tasks, to learn a compact overlapping knowledge sharing structure among tasks. DEN is efficiently trained in an online manner by performing selective retraining, dynamically expands network capacity upon arrival of each task with only the necessary number of units, and effectively prevents semantic drift by splitting/duplicating units and timestamping them. We validate DEN on multiple public datasets under lifelong learning scenarios, on which it not only significantly outperforms existing lifelong learning methods for deep networks, but also achieves the same level of performance as the batch counterparts with substantially fewer number of parameters. Further, the obtained network fine-tuned on all tasks obtained significantly better performance over the batch models, which shows that it can be used to estimate the optimal network structure even when all tasks are available in the first place.
Plant, soil and microbial controls on grassland diversity restoration: a long‐term, multi‐site mesocosm experiment

1. The success of grassland biodiversity restoration schemes is determined by many factors; as such their outcomes can be unpredictable. There is a need for improved understanding of the relative importance of belowground factors to restoration success, such as contrasting soil type and management intensities, as well as plant community composition and order of assembly. 2. We carried out an eight-year mesocosm experiment across three locations in the UK to explore the relative and interactive roles of various aboveground and belowground factors in the establishment of target species, to determine general constraints on grassland restoration. Each location had a series of mesocosms with contrasting soil types and management status, which were initially sown with six grasses typical of species-poor grasslands targeted for restoration. 3. Over five years, sets of plant species were added, to test how different vegetation treatments, including early-coloniser species and the hemiparasite Rhinanthus minor, and soil type and management, influenced the establishment of target plant species and community diversity. 4. The addition of early-coloniser species to model grasslands suppressed the establishment of target species, indicating a strong priority effect. Soil type was also an important factor, but effects varied considerably across locations. In the absence of early-coloniser species, low soil nutrient availability improved establishment of target species across locations, although R. minor had no beneficial effect. 5. Synthesis and applications. Our long-term, multi-site study indicates that successful restoration of species rich grassland is dependent primarily on priority effects, especially in the form of early-coloniser species that suppress establishment of slow-growing target species. We also show that priority effects vary with soil conditions, being stronger in clay than sandy soils, and on soils of high nutrient availability. As such, our work emphasises the importance of considering priority effects and local soil conditions in developing management strategies for restoring plant species diversity in grassland.