Miracle-dz/UniFAR-FTUs huggingface dataset:
Meta-Learning with Sparse Experience Replay for Lifelong Language Learning

Lifelong learning requires models that can continuously learn from sequential streams of data without suffering catastrophic forgetting due to shifts in data distributions. Deep learning models have thrived in the non-sequential learning paradigm; however, when used to learn a sequence of tasks, they fail to retain past knowledge and learn incrementally. We propose a novel approach to lifelong learning of language tasks based on meta-learning with sparse experience replay that directly optimizes to prevent forgetting. We show that under the realistic setting of performing a single pass on a stream of tasks and without any task identifiers, our method obtains state-of-the-art results on lifelong text classification and relation extraction. We analyze the effectiveness of our approach and further demonstrate its low computational and space complexity.
Super connectivity of lexicographic product graphs

For a graph $G$, $k(G)$ denotes its connectivity. A graph is super connected if every minimum vertex-cut isolates a vertex. Also $k_{1}$-connectivity of a connected graph is the minimum number of vertices whose deletion gives a disconnected graph without isolated vertices. This paper provides bounds for the super connectivity and $k_{1}$-connectivity of the lexicographic product of two graphs.
Coherent noise cancellation in optomechanical system with double optical modes

A quantum metrology protocol for continuous force sensing is developed beyond the quantum standard limit on performing a coherent quantum noise cancellation (CQNC) strategy in an optomechanical system, that consists of two optical modes with non-identical frequencies and a mechanical mode. In particular, an ultrasensitive susceptibility around the mechanical-mode frequency is solely achieved with driving the higher-frequency optical mode and probing the lower-frequency one. More importantly, this asymmetrical and unique treatment allows the ancillary optical mode to constitute an effective coherent channel for implementing the CQNC strategy, when the ancillary mode is set to be near-resonant with the probe mode to avoid the disturbance from the driven mode. The ancillary mode then acts as a negative-frequency mechanical oscillator to offset the backaction noise arising from both radiation-pressure and driving. Under the condition of strong driving and strong coupling, the measurement sensitivity as well as the signal-to-noise ratio in our optomechanical-sensing scheme is therefore found to be significantly enhanced by about two orders in magnitude, comparing to that without noise cancellation. In addition, our scheme can be practiced in a tripartite optomechanical setup with a membrane in the middle and a twisted-cavity-based weak-torque detector.
Uncovering edge plasma dynamics via deep learning from partial observations

One of the most intensely studied aspects of magnetic confinement fusion is edge plasma behaviour, which is critical to reactor performance and operation. Drift-reduced Braginskii two-fluid theory has for decades been widely used to model edge plasmas with varying success. This Letter demonstrates that physics-informed neural networks can accurately learn turbulent field dynamics consistent with the two-fluid theory from just partial observations of a synthetic plasma's electron density and temperature for plasma diagnosis and model validation in challenging thermonuclear environments.
Finite Group Equivariant Neural Networks for Games

Games such as go, chess and checkers have multiple equivalent game states, i.e. multiple board positions where symmetrical and opposite moves should be made. These equivalences are not exploited by current state of the art neural agents which instead must relearn similar information, thereby wasting computing time. Group equivariant CNNs in existing work create networks which can exploit symmetries to improve learning, however, they lack the expressiveness to correctly reflect the move embeddings necessary for games. We introduce Finite Group Neural Networks (FGNNs), a method for creating agents with an innate understanding of these board positions. FGNNs are shown to improve the performance of networks playing checkers (draughts), and can be easily adapted to other games and learning problems. Additionally, FGNNs can be created from existing network architectures. These include, for the first time, those with skip connections and arbitrary layer types. We demonstrate that an equivariant version of U-Net (FGNN-U-Net) outperforms the unmodified network in image segmentation.
Improving Coreference Resolution by Leveraging Entity-Centric Features with Graph Neural Networks and Second-order Inference

One of the major challenges in coreference resolution is how to make use of entity-level features defined over clusters of mentions rather than mention pairs. However, coreferent mentions usually spread far apart in an entire text, which makes it extremely difficult to incorporate entity-level features. We propose a graph neural network-based coreference resolution method that can capture the entity-centric information by encouraging the sharing of features across all mentions that probably refer to the same real-world entity. Mentions are linked to each other via the edges modeling how likely two linked mentions point to the same entity. Modeling by such graphs, the features between mentions can be shared by message passing operations in an entity-centric manner. A global inference algorithm up to second-order features is also presented to optimally cluster mentions into consistent groups. Experimental results show our graph neural network-based method combing with the second-order decoding algorithm (named GNNCR) achieved close to state-of-the-art performance on the English CoNLL-2012 Shared Task dataset.
A dataset and classification model for Malay, Hindi, Tamil and Chinese music

In this paper we present a new dataset, with musical excepts from the three main ethnic groups in Singapore: Chinese, Malay and Indian (both Hindi and Tamil). We use this new dataset to train different classification models to distinguish the origin of the music in terms of these ethnic groups. The classification models were optimized by exploring the use of different musical features as the input. Both high level features, i.e., musically meaningful features, as well as low level features, i.e., spectrogram based features, were extracted from the audio files so as to optimize the performance of the different classification models.
A Novel Sinorhizobium meliloti Operon Encodes an α-Glucosidase and a Periplasmic-Binding-Protein-Dependent Transport System for α-Glucosides

ABSTRACT The most abundant carbon source transported into legume root nodules is photosynthetically produced sucrose, yet the importance of its metabolism by rhizobia in planta is not yet known. To identify genes involved in sucrose uptake and hydrolysis, we screened aSinorhizobium meliloti genomic library and discovered a segment of S. meliloti DNA which allows Ralstonia eutropha to grow on the α-glucosides sucrose, maltose, and trehalose. Tn5 mutagenesis localized the required genes to a 6.8-kb region containing five open reading frames which were namedagl, for α-glucoside utilization. Four of these (aglE, aglF, aglG, andaglK) appear to encode a periplasmic-binding-protein-dependent sugar transport system, and one (aglA) appears to encode an α-glucosidase with homology to family 13 of glycosyl hydrolases. Cosmid-borne agl genes permit uptake of radiolabeled sucrose into R. eutrophacells. Analysis of the properties of agl mutants suggests that S. meliloti possesses at least one additional α-glucosidase as well as a lower-affinity transport system for α-glucosides. It is possible that the Fix+ phenotype ofagl mutants on alfalfa is due to these additional functions. Loci found by DNA sequencing to be adjacent toaglEFGAK include a probable regulatory gene (aglR), zwf and edd, which encode the first two enzymes of the Entner-Doudoroff pathway, pgl, which shows homology to a gene encoding a putative phosphogluconolactonase, and a novel Rhizobium-specific repeat element.
AN INVESTIGATION TOWARDS DEVELOPING A MOLECULAR APPROACH TO IMPROVE THE EFFICIENCY OF COCONUT BREEDING BY RAPD-MARKER ASSISTED SELECTION

Tall, dwarf green and San Ramon are three phenotypically distinct forms of coconut, currently used for production of hybrid seeds in Sri Lanka. Development of molecular markers for further improvement of important economic traits of these hybrids was thought important due to various constraints faced by conventional breeders. Sixty random primers (OPERON) were used for generation of RAPD profiles using DNA from 3 individuals of each form. All the sixty primers except one (OPC3) yielded RAPD-PCR products with coconut DNA. They generated a total of 326 consistently amplified bands of which 54 distinguished tall, dwarf green and San Ramon. Among RAPDs detected 16 and 8 were specific to tall and dwarf respectively, 18 distinguished dwarf and San Ramon from tall, 9 distinguished tall and San Ramon from dwarf and 3 distinguished tall and dwarf green from San Ramon. It is expected to study the segregation of these markers in F2 populations derived from tall x dwarf green and tall x San Ramon F1 palms.
Parent-Offspring Interactions and Feeding Chases in the Chinstrap Penguin Pygoscelis antarctica

Feeding interactions between parents and chicks in pygoscelid penguins frequently lead to "chases. " In a field experiment with Chinstrap penguins (Pygoscelis antarctica) on Deception Island, we showed that chases are almost nonexistent when a parent is met by only one of their chicks (the other was temporarily removed). Also, chasing intensity in the two-chick situation decreased after chick separation, whereas the rate of feedings increased. The initiation of chases could be due to the need of separating the two chicks before feeding them in order to increase feeding efficiency or, alternatively, be a reaction of the parent to the harassment from two begging, competing chicks.
Representing Temporal Dependencies in Smart Home Activity Recognition for Health Monitoring

Long term health conditions, such as fall risk, are traditionally diagnosed through testing performed in hospital environments. Smart Homes offer the opportunity to perform continuous, long-term behavioural and vitals monitoring of residents, which may be employed to aid diagnosis and management of chronic conditions without placing additional strain on health services. A profile of the resident’s behaviour can be produced from sensor data, and then compared over time. Activity Recognition is a primary challenge for profile generation, however many of the approaches adopted fail to take full advantage of the inherent temporal dependencies that exist in the activities taking place. Long Short Term Memory (LSTM) is a form of recurrent neural network that uses previously learned examples to inform classification decisions. In this paper we present a variety of approaches to human activity recognition using LSTMs which consider the temporal dependencies present in the sensor data in order to produce richer representations and improved classification accuracy. The LSTM approaches are compared to the performance of a selection of baseline classification algorithms on several real world datasets. In general, it was found that accuracy in LSTMs improved as additional temporal information was presented to the classifier.
Spatial tick bite exposure and associated risk factors in Scandinavia

ABSTRACT Tick-borne diseases are emerging and re-emerging threats causing public health concerns in Europe and North America. Prevention and control requires understanding of human exposure and behaviour. The aim was to measure exposure to tick bites across Scandinavia, its spatial distribution and the associated risk factors. Methods We sent a web-based survey to a randomly chosen population and analysed answers by Principal Component Analysis and Chi-Square. Individual responses were aggregated at the municipality level to assess the spatial distribution of bites. Results Nearly 60% of adults reported bites at low levels (1-5 bites); however, the majority were not in their resident municipality. We found two spatial profiles: In their home municipalities, people were most often bitten in less, but not the least, urbanized areas. When visiting other municipalities, people were most frequently bitten in peri-urban areas. Running/walking in the forest, gardening, and paddling/rowing were activities most strongly associated with bites. Conclusion Tick bites affect the entire Scandinavian population, with a higher risk in Sweden compared to Denmark and Norway. The frequency of observation of ticks in the environment or on pets might be used as a proxy for the actual risk of exposure to tick bites. Our results indicates that urban-dwelling outdoor enthusiasts and inhabitants of rural areas must be equally targeted for prevention campaigns.
Correlation between +1923C/T polymorphism in IL-13 gene and asthma and its impact on total plasm IgE levels

Objective: To investigate the correlation between +1923C/T polymorphism in IL-13 gene intron and its impact on total plasm IgE levels. Methods: +1923C/T polymorphism in IL-13 gene and total plasm IgE levels in asthma and control groups were detected by polymerase chain reaction/restriction fragment length polymorphism (PCR/RFLP) and ELISA,respectively. Results: There were significant differences in C and T allele frequencies at +1923 locus (χ 2=9.30, P0.01), and in genetype distribution such as CC,CT and TT (χ 2=9.92, P0.01)between two groups . Allele T was associated with asthma, [OR (T/C) =1.87, 95% CI =1.25～2.80,P0.01]. The total plasm IgE levels in T allele carriers and in asthma group were higher than those in another allele carriers and in control group,respectively.Conclusion:+1923 polymorphism in IL-13 gene could be an important candidate gene for asthma.Allele T is associated with asthma,which increases the total plasm IgE levels via enhancing IL-13 gene expression.
The impact of affect on memory of advertising

The impact of affect on memory has been considered by both advertising and neuroscience research. As part of testing a MAC (Memory superset of Affect superset of Cognition) model of the intermediate effects of advertising, four hypotheses were developed: ads with higher affective content would have higher recognition and recall, and subjects treated with beta-blockers (Propranolol), which interact with those brain regions known to mediate affect, would have lower recognition and recall than those treated with placebos. The hypotheses are tested and broadly supported. This exploratory research, taken in conjunction with previous work, indicates some ways in which affect enhances advertising effectiveness. We conclude with directions for further research and testing the MAC model.
Tripogon loliiformis elicits a rapid physiological and structural response to dehydration for desiccation tolerance.

Resurrection plants can withstand extreme dehydration to an air-dry state and then recover upon receiving water. Tripogon loliiformis (F.Muell.) C.E. Hubb. is a largely uncharacterised native Australian desiccation-tolerant grass that resurrects from the desiccated state within 72h. Using a combination of structural and physiological techniques the structural and physiological features that enable T. loliiformis to tolerate desiccation were investigated. These features include: (i) a myriad of structural changes such as leaf folding, cell wall folding and vacuole fragmentation that mitigate desiccation stress, (ii) potential role of sclerenchymatous tissue within leaf folding and radiation protection, (iii) retention of ~70% chlorophyll in the desiccated state, (iv) early response of photosynthesis to dehydration by 50% reduction and ceasing completely at 80 and 70% relative water content, respectively, (v) a sharp increase in electrolyte leakage during dehydration, and (vi) confirmation of membrane integrity throughout desiccation and rehydration. Taken together, these results demonstrate that T. loliiformis implements a range of structural and physiological mechanisms that minimise mechanical, oxidative and irradiation stress. These results provide powerful insights into tolerance mechanisms for potential utilisation in the enhancement of stress-tolerance in crop plants.
Preparation and Quality Evaluation of Curcumin Liposomes Modified with Vitamin A

Curcumin liposomes modified with vitamin A were prepared by reverse-phase evaporation vesicles.Orthogonal test was adopted to optimize the formulation with encapsulation efficiency and binding rate as the evaluation parameters.Encapsulation efficiency,binding rate,particle size and in vitro release were investigated.The ratio of the liposomes of less than 1.58 μm was 57%. The encapsulation efficiency and vitamin A binding rate of curcumin liposomes modified with vitamin A were 89.3% and 61.3%.
The panic‐agoraphobic spectrum

Categorical classifications of mental disorders do not take into account the subthreshold, atypical and often enduring symptoms that accompany the core manifestations of full‐blown mental disorders. However, this often neglected spectrum of symptoms may be as distressing and debilitating as the full‐blown disorder and may have unrecognized importance in treatment selection and response. To this end, a spectrum approach to mental disorders, such as bipolar, obsessive‐compulsive, eating, and panic disorder has been developed, which has been extensively used and proven effective in clinical practice. The need for a systematic identification and assessment of a broad array of symptoms and behavioural features led, as a first step, to the conceptualization of the panic‐agoraphobic spectrum model and to the development of a structured interview (SCI‐PAS). This model has been constructed by identifying different psychopathological and clinical domains incorporating and extending Panic Disorder as described in DSM‐IV. The rationale, clinical usefulness, and heuristic significance of the panic‐agoraphobic spectrum model will be discussed. Copyright © 1999 John Wiley & Sons, Ltd.
change the predatory functional response type? Experiments and simulations in an acarine predator-prey system

In multipatch landscapes, understanding the role of patch number and connectivity is key for the conserva- tion of species under processes such as predation. The functional response is the most basic form of the predator-prey interaction. Two common response types exist: a decelerating curvilinear increase in prey consumption with prey den- sity to a plateau (type II) and a sigmoidal-shaped curve (type III). Type II responses have been observed for a variety of predators, though only type III responses allow long-term persistence and are demographically stabilizing. We tested the hypothesis that the functional response type can change from a type II to a type III with increasing patch number and (or) decreasing connectivity. The predatory mite Amblyseius fallacis (Garman, 1948) has previously been shown to have a type II response when feeding on Panonychus ulmi (Koch, 1839). We examined this predator-prey interaction using experiments that varied in patch number, and simulations that varied in both patch number and connectivity. In no experimental or simulation trial did altering patch number or connectivity change the predator's functional re- sponse from type II to type III, even with an 80-fold decrease in patch connectivity. How do predators with this demo- graphically destabilizing functional response persist? Hypotheses regarding metapopulations and alternative prey are discussed.
Emergence of Multilingualism in Population based Referential Games

The ability of agents to learn to communicate by interaction has been studied through emergent communication tasks. Inspired by previous work in this domain, we extend the referential game setup to a population of spatially distributed agents. In such a setting, our experiments reveal that multiple languages can emerge in the population and some agents develop multilingual traits. Further, an action-advising framework is proposed for improving sample efﬁciency in the learning process.
Mapping Chinese Rice Suitability to Climate Change

Climate change has the potential to affect Chinese rice production; however, the rice crop could become more suitable to new climatic conditions because of benefits derived from new agricultural technologies. In this paper, a county-level dataset and crop model were used to analyze actual rice yield suitability by measuring the yield gap and yield stability from 1980 to 2011 in 1561 counties of China. The results showed that the national yield gap between the actual and potential yields was approximately 23.0%, which is close to the threshold for profitable planting. However, a number of counties in the northeastern and southwestern regions showed a 30 to 50% yield gap, which indicates a relatively lower suitability of the rice. The rice yield stability results indicated that the actual stability has exceeded the potential stability in most of the counties of China, thus indicating a high level of suitability. Temporally, a decreasing trend was observed for both the yield gap and stability, suggesting that the suitability of rice in China has improved, which might be associated with the development of agricultural technology. The only noteworthy locations presenting a high yield gap and yield instability were several counties in the northeastern region. Since the northeastern region accounts for a significant proportion of China's rice production, further investigations should be conducted to identify the underlying causes of the yield gaps and determine methods of increasing the yield stability. The implementation of more suitable agricultural technology in the area is also suggested to improve the rice suitability in the region.
Chemical Validation of Mycobacterium tuberculosis Phosphopantetheine Adenylyltransferase Using Fragment Linking and CRISPR Interference

The coenzyme A (CoA) biosynthesis pathway has attracted attention as a potential target for much-needed novel antimicrobial drugs, including for the treatment of tuberculosis (TB), the lethal disease caused by Mycobacterium tuberculosis (Mtb). Seeking to identify the first inhibitors of Mtb phosphopantetheine adenylyltransferase (MtbPPAT), the enzyme that catalyses the penultimate step in CoA biosynthesis, we performed a fragment screen. In doing so, we discovered three series of fragments that occupy distinct regions of the MtbPPAT active site, presenting a unique opportunity for fragment linking. Here we show how, guided by X-ray crystal structures, we could link weakly-binding fragments to produce an active site binder with a KD < 20 μM and on-target anti-Mtb activity, as demonstrated using CRISPR interference. This study represents a big step toward validating MtbPPAT as a potential drug target and designing a MtbPPAT-targeting anti-TB drug.