Miracle-dz/UniFAR-FTUs huggingface dataset:
Faster Dynamic Controllability Checking for Simple Temporal Networks with Uncertainty

Simple Temporal Networks (STNs) are a well-studied model for representing and reasoning about time. An STN comprises a set of real-valued variables called time-points, together with a set of binary constraints, each of the form Y ≤ X + w . The problem of ﬁnding a feasible schedule (i.e., an assignment of real numbers to time-points such that all of the constraints are satisﬁed) is equivalent to the Single Source Shortest Path problem (SSSP) in the STN graph. Simple Temporal Networks with Uncertainty (STNUs) augment STNs to include contingent links that can be used, for example, to represent actions with uncertain durations. The duration of a contingent link is not controlled by the planner, but is instead controlled by a (possibly adversarial) environment. Each contingent link has the form, h A, ‘, u, C i , where 0 < ‘ ≤ u < ∞ . Once the planner executes the activation time-point A , the environment must execute the contingent time-point C at some time A +∆, where ∆ ∈ [ ‘, u ]. Crucially, the planner does not know the value of ∆ in advance, but only discovers it when C executes. An STNU is dynamically controllable (DC) if there is a strategy that the planner can use to execute all of the non-contingent time-points, such that all of the constraints are guaranteed to be satisﬁed no matter which durations the environment chooses for the contingent links. The strategy can be dynamic in that it can react in real time to the contingent durations it observes. Recently, an upper bound of O ( N 3 ) was given for the DC-checking problem for STNUs, where N is the number of time-points. This paper introduces a new algorithm, called the RUL − algorithm, for solving the
Temporal Cross-Media Retrieval with Soft-Smoothing

Multimedia information have strong temporal correlations that shape the way modalities co-occur over time. In this paper we study the dynamic nature of multimedia and social-media information, where the temporal dimension emerges as a strong source of evidence for learning the temporal correlations across visual and textual modalities. So far, cross-media retrieval models, explored the correlations between different modalities (e.g. text and image) to learn a common subspace, in which semantically similar instances lie in the same neighbourhood. Building on such knowledge, we propose a novel temporal cross-media neural architecture, that departs from standard cross-media methods, by explicitly accounting for the temporal dimension through temporal subspace learning. The model is softly-constrained with temporal and inter-modality constraints that guide the new subspace learning task by favouring temporal correlations between semantically similar and temporally close instances. Experiments on three distinct datasets show that accounting for time turns out to be important for cross-media retrieval. Namely, the proposed method outperforms a set of baselines on the task of temporal cross-media retrieval, demonstrating its effectiveness for performing temporal subspace learning.
LIRS: Enabling efficient machine learning on NVM-based storage via a lightweight implementation of random shuffling

Machine learning algorithms, such as Support Vector Machine (SVM) and Deep Neural Network (DNN), have gained a lot of interests recently. When training a machine learning algorithm, randomly shuffle all the training data can improve the testing accuracy and boost the convergence rate. Nevertheless, realizing training data random shuffling in a real system is not a straightforward process due to the slow random accesses in hard disk drive (HDD). To avoid frequent random disk access, the effect of random shuffling is often limited in existing approaches. With the emerging non-volatile memory-based storage device, such as Intel Optane SSD, which provides fast random accesses, we propose a lightweight implementation of random shuffling (LIRS) to randomly shuffle the indexes of the entire training dataset, and the selected training instances are directly accessed from the storage and packed into batches. Experimental results show that LIRS can reduce the total training time of SVM and DNN by 49.9% and 43.5% on average, and improve the final testing accuracy on DNN by 1.01%.
Temporal Sampling Implications for Crowd Sourced Population Estimations from Social Media

Understanding the movements of a population throughout the 24-hour day is critical when directing disaster response in an urban area. An emergency situation can develop rapidly, and understanding the expected locations of groups of people is required for the success of first responders. Recent advances in modern consumer technologies have facilitated the generation, sharing and mining of an extensive amount of volunteered geographic information. Users leverage inexpensive smart devices, pervasive Internet connections and social media services to provide data about geospatial locations. Using an enterprise system, it is possible to aggregate this freely available, geospatially enabled data and create a population estimation with high spatiotemporal resolution, via a heat map. This investigation explores the effects of different temporal sampling periods when creating such estimations. Time periods are selected, estimations are generated for several large urban areas in the western United States, and comparisons of the results are shown/discussed.
Optimization of Biodiesel Production over Chicken Eggshell-Derived CaO Catalyst in a Continuous Centrifugal Contactor Separator

Solid calcium oxide (CaO) catalyst was prepared via the calcination of chicken eggshells as an environmentally friendly waste resource and incorporated in a continuous centrifugal contactor separator (CCCS) for intensified biodiesel synthesis. Biodiesel or fatty acid methyl esters (FAME) were produced via the transesterification of sunflower oil (containing 5 wt % tetrahydrofuran as a cosolvent) with methanol under 60 °C and separated from the glycerol and catalyst phases continuously in the CCCS. The influence of reaction parameters on biodiesel production was well modeled by response surface methodology. At an oil flow rate of 9 mL/min, an alcohol to oil molar ratio of 11:1, and a weight hourly space time (defined as the catalyst weight over the oil mass flow rate) of 0.050 h, an optimized FAME yield of 83.2% with a productivity of 638 kgFAME/(m3reactor·h) was achieved. CaO catalyst was reused without significant activity loss for at least four cycles.
Social Triangulation: A new method to identify local citizens using social media and their local information curation behaviors

Local citizens can use social media such as Twitter to share and receive critical information before, during, and after emergencies. However, standard methods of identifying local citizens on Twitter discover only a small proportion of local users in a geographic area. To better identify local citizens and their social media sources for local information, we explore the information infrastructure of a local community that is constituted prior to emergencies through the everyday social network curation of local citizens. We hypothesize that investigating social network ties among local organizations and their followers may be key to identifying local citizens and understanding their local information seeking behaviors. We describe Social Triangulation as a method to identify local citizens vis-à-vis the local organizations they follow on Twitter, and evaluate our hypothesis by analyzing users’ profile location information. Lastly, we discuss how Social Triangulation might support community preparedness by informing emergency communications planning.
First Look at Control-IQ: A New-Generation Automated Insulin Delivery System

OBJECTIVE To pilot test a new closed-loop control technology to validate it for a further large clinical trial. RESEARCH DESIGN AND METHODS The t:slim X2 insulin pump with Control-IQ Technology (Tandem Diabetes Care) includes a Dexcom G6 sensor and a closed-loop algorithm implemented in the pump that 1) automates insulin correction boluses, 2) has a dedicated hypoglycemia safety system, and 3) gradually intensifies control overnight, aiming for blood glucose levels of approximately 100–120 mg/dL every morning. RESULTS Five patients with type 1 diabetes (mean age 52.8 years, 2/3 male/female, mean A1C 6.5%) used Control-IQ in an outpatient setting (hotel) for approximately 37 h. During the closed loop, mean glucose was 129 mg/dL (135/121 mg/dL during the day/night), time within target range 70–180 mg/dL was 87% (82%/94% during the day/night), and time <60 mg/dL was 1.1% (2.0%/0.0% during the day/night). CONCLUSIONS Following this pilot trial, Control-IQ was deployed in several studies, including the large-scale National Institutes of Health International Diabetes Closed-Loop (iDCL) Trial.
Past-year relational victimization is associated with a blunted neural response to rewards in emerging adults

Abstract Anhedonia is associated with multiple forms of psychopathology, yet relatively, little is known about how anhedonia develops. Emerging evidence suggests that anhedonia is the result of interactions between life stress and the brain’s reward systems, and that social stress, in particular, may drive these processes. One potent form of social stress is peer victimization, but very little research has focused on peer victimization beyond adolescence, and even less has examined the associations between peer victimization and neural response to rewards. The present study sought to identify associations between past-year history of peer victimization and neural response to rewards in emerging adults (N = 61). Relational and physical forms of victimization were assessed separately since these distinct types of social stress have different trajectories across development and different associations with psychopathology. Reward sensitivity was indexed with the event-related potential component known as the reward positivity, which was elicited using a forced-choice monetary reward guessing task. Results demonstrated that past-year relational, but not physical, victimization was associated with a blunted neural response to rewards. These findings provide insight into one potential mechanism in the etiology of anhedonia, which may, in turn, help us to better identify pathways to multiple psychopathologies.
Inositol 1,4,5-trisphosphate receptor type2-independent Ca2+ release from the endoplasmic reticulum in astrocytes

Accumulating evidence indicates that astrocytes are actively involved in the physiological and pathophysiological functions of the brain. Intracellular Ca2+ signaling, especially Ca2+ release from the endoplasmic reticulum (ER), is considered to be crucial for the regulation of astrocytic functions. Mice with genetic deletion of inositol 1,4,5-trisphosphate receptor type 2 (IP3R2) are reportedly devoid of astrocytic Ca2+ signaling, and thus widely used to explore the roles of Ca2+ signaling in astrocytic functions. While functional deficits in IP3R2-knockout (KO) mice have been found in some reports, no functional deficit was observed in others. Thus, there remains a controversy regarding the functional significance of astrocytic Ca2+ signaling. To address this controversy, we re-evaluated the assumption that Ca2+ release from the ER is abolished in IP3R2-KO astrocytes using a highly sensitive imaging technique. We expressed the ER luminal Ca2+ indicator G-CEPIA1er in cortical and hippocampal astrocytes to directly visualize spontaneous and stimulus-induced Ca2+ release from the ER. We found attenuated but significant Ca2+ release in response to application of norepinephrine to IP3R2-KO astrocytes. This IP3R2-independent Ca2+ release induced only minimal cytosolic Ca2+ transients but induced robust Ca2+ increases in mitochondria that are frequently in close contact with the ER. These results indicate that ER Ca2+ release is retained and is sufficient to increase the Ca2+ concentration in close proximity to the ER in IP3R2-KO astrocytes.
Covariate selection strategies for causal inference: Classification and comparison

When causal effects are to be estimated from observational data, we have to adjust for confounding. A central aim of covariate selection for causal inference is therefore to determine a set that is sufficient for confounding adjustment, but other aims such as efficiency or robustness can be important as well. In this paper, we review six general approaches to covariate selection that differ in the targeted type of adjustment set. We discuss and illustrate their advantages and disadvantages using causal diagrams. Moreover, the approaches and different ways of implementing them are compared empirically in an extensive simulation study. We conclude that there are considerable differences between the approaches but none of them is uniformly best, with performance depending on the chosen adjustment method as well as the true confounding structure. Any prior structural knowledge on the causal relations is helpful to choose the most appropriate method.
Performance enhancement of approximated model based near-field sources localisation techniques

Most of the existing near-field sources localisation methods are based on an approximated model. Making use of such an approximation brings degradation in the estimation accuracy. In this study, the authors propose a correction method to mitigate this problem and improve the estimation performance of the approximated model based methods. Simulation results show that the proposed technique can significantly improve the performance of the classical approximated model based near-field sources localisation methods.
Genome-wide mapping reveals conserved and diverged R-loop activities in the unusual genetic landscape of the African trypanosome genome

R-loops are stable RNA-DNA hybrids that have been implicated in transcription initiation and termination, as well as in telomere homeostasis, chromatin formation, and genome replication and instability. RNA Polymerase (Pol) II transcription in the protozoan parasite Trypanosoma brucei is highly unusual: virtually all genes are co-transcribed from multigene transcription units, with mRNAs generated by linked trans-splicing and polyadenylation, and transcription initiation sites display no conserved promoter motifs. Here, we describe the genome-wide distribution of R-loops in wild type mammal-infective T. brucei and in mutants lacking RNase H1, revealing both conserved and diverged functions. Conserved localisation was found at centromeres, rRNA genes and retrotransposon-associated genes. RNA Pol II transcription initiation sites also displayed R-loops, suggesting a broadly conserved role despite the lack of promoter conservation or transcription initiation regulation. However, the most abundant sites of R-loop enrichment were within the intergenic regions of the multigene transcription units, where the hybrids coincide with sites of polyadenylation and nucleosome-depletion. Thus, instead of functioning in transcription termination, most T. brucei R-loops act in a novel role, promoting RNA Pol II movement or mRNA processing. Finally, we show there is little evidence for correlation between R-loop localisation and mapped sites of DNA replication initiation.
Unsupervised feature learning via prior information-based similarity metric learning for face verification

: Here, an efficient framework is developed to address the problem of unconstrained face verification. In particular, an unsupervised feature learning method for face image representation and a novel similarity metric model are discussed. First, the authors propose an unsupervised feature learning method with sparse auto-encoder (SAE) based on local descriptor (SAELD). A set of filter operators are learned based on SAE model from local patches, and face descriptors are extracted by applying the set of filter operators to convolve images. This can address the face discriminative representation issue of unconstrained face verification. Then pairwise SAELD descriptors are projected into the weighted subspace. Furthermore, a prior information-based similarity metric learning model is presented, in which the metric matrix is learned by enforcing a regularisation term based on the prior similar and discriminative information. This idea can improve the robustness to intra-personal variations and discrimination to inter-personal variations. Experimental results show that the proposed method has competitive performance compared with several state-of-the-art methods on challenging labelled faces in the wild data set.
A gaze-Independent audiovisual brain-Computer Interface and its Application in Awareness Detection

Awareness detection in patients with DOC is a challenging task, which is commonly addressed through behavioral observation scales. In this study, we proposed a gaze-independent audiovisual brain computer interface (BCI) for patients with disorders of consciousness (DOC). Semantically congruent and incongruent audiovisual number stimuli were presented one by one to evoke event-related potential (ERP) components. Subjects were instructed to selectively attend to the congruent audiovisual stimuli (target) whereas ignoring the incongruent audiovisual stimuli (nontarget). Ten healthy subjects first participated in the experiment to evaluate the system. The results demonstrated the audiovisual BCI system outperformed the corresponding auditory-only and visualonly systems. Multiple ERP components including the P300, N400 and LPC were observed in the audiovisual condition, which enhanced the discriminability between the brain responses for target and nontarget stimuli. This system was then applied to detect the awareness in eight patients with DOC. The results demonstrated the command following as well as number recognition in three of the eight patients. Therefore, this gaze-independent audiovisual BCI system might be used as a supportive bedside tool for awareness detection in patients with DOC.
Improving Neural Text Simplification Model with Simplified Corpora

Text simplification (TS) can be viewed as monolingual translation task, translating between text variations within a single language. Recent neural TS models draw on insights from neural machine translation to learn lexical simplification and content reduction using encoder-decoder model. But different from neural machine translation, we cannot obtain enough ordinary and simplified sentence pairs for TS, which are expensive and time-consuming to build. Target-side simplified sentences plays an important role in boosting fluency for statistical TS, and we investigate the use of simplified sentences to train, with no changes to the network architecture. We propose to pair simple training sentence with a synthetic ordinary sentence via back-translation, and treating this synthetic data as additional training data. We train encoder-decoder model using synthetic sentence pairs and original sentence pairs, which can obtain substantial improvements on the available WikiLarge data and WikiSmall data compared with the state-of-the-art methods.
The Role of Rayleigh-Wood Anomalies and Surface Plasmons in Optical Enhancement for Nano-Gratings

We propose and report on the design of a 1-D metallo-dielectric nano-grating on a GaAs substrate. We numerically study the impact of grating period, slit and wire widths, and irradiating angle of incidence on the optical response. The optimal wire width, w = 160 nm, was chosen based on previous results from investigations into the influence of wire width and nano-slit dimensions on optical and electrical enhancements in metal-semiconductor-metal photodetectors. In this present project, resonant absorption and reflection modes were observed while varying the wire and nano-slit widths to study the unique optical modes generated by Rayleigh-Wood anomalies and surface plasmon polaritons. We observed sharp and diffuse changes in optical response to these anomalies, which may potentially be useful in applications such as photo-sensing and photodetectors. Additionally, we found that varying the slit width produced sharper, more intense anomalies in the optical spectrum than varying the wire width.
NG2 expression in NG2 glia is regulated by binding of SoxE and bHLH transcription factors to a Cspg4 intronic enhancer

NG2 is a type 1 integral membrane glycoprotein encoded by the Cspg4 gene. It is expressed on glial progenitor cells known as NG2 glial cells or oligodendrocyte precursor cells that exist widely throughout the developing and mature central nervous system and vascular mural cells but not on mature oligodendrocytes, astrocytes, microglia, neurons, or neural stem cells. Hence NG2 is widely used as a marker for NG2 glia in the rodent and human. The regulatory elements of the mouse Cspg4 gene and its flanking sequences have been used successfully to target reporter and Cre recombinase to NG2 glia in transgenic mice when used in a large 200 kb bacterial artificial chromosome cassette containing the 38 kb Cspg4 gene in the center. Despite the tightly regulated cell type‐ and stage‐specific expression of NG2 in the brain and spinal cord, the mechanisms that regulate its transcription have remained unknown. Here, we describe a 1.45 kb intronic enhancer of the mouse Cspg4 gene that directed transcription of EGFP reporter to NG2 glia but not to pericytes in vitro and in transgenic mice. The 1.45 kb enhancer contained binding sites for SoxE and basic helix–loop–helix transcription factors, and its enhancer activity was augmented cooperatively by these factors, whose respective binding elements were found in close proximity to each other. Mutations in these binding elements abrogated the enhancer activity when tested in the postnatal mouse brain.
2-Mercaptobenzimidazole Schiff Bases: Design, Synthesis, Antimicrobial Studies and Anticancer Activity on HCT-116 Cell Line.

BACKGROUND Increased rate of mortality due to the development of resistance to currently available antimicrobial and anticancer agents initiated the need to develop new chemical entities for the treatment of microbial infections and cancer. OBJECTIVE The present study was aimed to synthesize and evaluate antimicrobial and anticancer activities of Schiff bases of 2-mercaptobenzimidazole. METHOD The Schiff bases of 2-mercaptobenzimidazole was synthesized from 4-(2-(1H-benzo[d]imidazol-2-ylthio)acetamido)benzohydrazide. The synthesized compounds were evaluated for antimicrobial and anticancer activities by tube dilution method and sulforhodamine-B (SRB) assay respectively. RESULTS Compounds 8 (MICpa, an = 2.41, 1.20 µM/ml), 10 (MICse, sa = 2.50 µM/ml), 20 (MICec = 2.34 µM/ml) and 25 (MICca = 1.46 µM/ml) showed significant antimicrobial activity against tested bacterial and fungal strains and compounds 20 (IC50 = 8 µg/ml) and 23 (IC50 = 7 µg/ml) exhibited significant anticancer activity. CONCLUSION In general, the synthesized derivatives exhibited moderate antimicrobial and anticancer activity. Compounds 8 and 25 having high antifungal potential among the synthesized compounds may be taken as lead compound for the development of novel antifungal agents.