Miracle-dz/UniFAR-FTUs huggingface dataset:
Best of many worlds: Robust model selection for online supervised learning

We introduce algorithms for online, full-information prediction that are competitive with contextual tree experts of unknown complexity, in both probabilistic and adversarial settings. We show that by incorporating a probabilistic framework of structural risk minimization into existing adaptive algorithms, we can robustly learn not only the presence of stochastic structure when it exists (leading to constant as opposed to $\mathcal{O}(\sqrt{T})$ regret), but also the correct model order. We thus obtain regret bounds that are competitive with the regret of an optimal algorithm that possesses strong side information about both the complexity of the optimal contextual tree expert and whether the process generating the data is stochastic or adversarial. These are the first constructive guarantees on simultaneous adaptivity to the model and the presence of stochasticity.
An Inter-domain Study for Arousal Recognition from Physiological Signals

Arousal recognition from physiological signals is a task with many challenge remaining, especially when performed in several different domains. However, the need for emotional intelligent machines increases day by day, starting with timely detection and improved management of mental disorders in mobile health, all the way to enhancing user experience in human-computer interaction (HCI). One of the open research questions, which we analyze in this paper, is which machine-learning (ML) methods and which input is most suitable for arousal recognition. We present an inter-domain study for arousal recognition on six different datasets. The datasets are processed and translated into a common spectro-temporal space of R-R intervals and Galvanic Skin Response (GSR) data, from which features are extracted and fed into ML algorithms. We present a comparison between dataset-specific models, “flat” models build on the overall data, and a novel stacking scheme, developed to utilize knowledge from all six datasets. When one model is built for each dataset, it turns out that whether the R-R, GSR, or merged features yield the best results is domain (dataset) dependent. When all datasets are merged into one and used to train and evaluate the models, the stacking scheme improved upon the results of the “flat” models.
Interactive comment on “Greenland Ice Sheet influence on Last Interglacial climate: global sensitivity studies performed with an atmosphere–ocean general circulation model” by M. Pfeiffer and G. Lohmann

Considering our results only for the Greenland region, we find that in one of the experiments with a reduced GIS (LIG-1300m-alb) there is a strong warming over Greenland in both summer and winter seasons. Merz et al. (2014a) describe results that on the other hand show a more mixed signal, with positive temperature anomalies being also accompanied by cooling. A comparison of our results to the study by Merz et al. (2014a) will be included in the revised version of the manuscript.
A classification method of liver tumors based on temporal change of Hounsfield unit in CT images

We present an automatic diagnosis method of liver cancer by using sequential images with contrast material of dynamic CT. Our method identifies and classifies liver tumors by extracting temporal change of CT values [Hounsfield Unit(HU)] of tumors from four kinds of CT images (i.e. plain CT, early phase, portal phase, late phase of dynamic CT images) in addition to morphological features of tumors. Automatic diagnosis of liver tumors is very difficult, because contrast of liver tumors is very small compared with liver background, shapes of tumors are diverse, and extraction of temporal change of CT values is very difficult due to morphological and contrast complexity of temporal change of tumor segments. Our method extracts temporal change of CT values of objects by mapping segments of same objects in different CT phase based on overlap ratio and position adjustment. We also implemented a graphical user interface for searching such images from an image database that include tumors similar to an image given as a search condition with respect to features of morphorogical and temporal change of contrast.
Ocean acidification stimulates particulate organic carbon accumulation in two Antarctic diatom species under moderate and high natural solar radiation

Impacts of rising atmospheric CO2 concentrations and increased daily irradiances from enhanced surface water stratification on phytoplankton physiology in the coastal Southern Ocean remain still unclear. Therefore, in the two Antarctic diatoms Fragilariopsis curta and Odontella weissflogii, the effects of moderate and high natural solar radiation combined with either ambient or future pCO2 on cellular particulate organic carbon (POC) contents and photophysiology were investigated. Results showed that increasing CO2 concentrations had greater impacts on diatom physiology than exposure to increasing solar radiation. Irrespective of the applied solar radiation regime, cellular POC quotas increased with future pCO2 in both diatoms. Lowered maximum quantum yields of photochemistry in PSII (Fv/Fm) indicated a higher photosensitivity under these conditions, being counteracted by increased cellular concentrations of functional photosynthetic reaction centers. Overall, our results suggest that both bloom‐forming Antarctic coastal diatoms might increase carbon contents under future pCO2 conditions despite reduced physiological fitness. This indicates a higher potential for primary productivity by the two diatom species with important implications for the CO2 sequestration potential of diatom communities in the future coastal Southern Ocean.
miR172 downregulates the translation of cleistogamy 1 in barley

Background and Aims Floret opening in barley is induced by the swelling of the lodicule, a trait under the control of the cleistogamy1 (cly1) gene. The product of cly1 is a member of the APETALA2 (AP2) transcription factor family, which inhibits lodicule development. A sequence polymorphism at the miR172 target site within cly1 has been associated with variation in lodicule development and hence with the cleistogamous phenotype. It was unclear whether miR172 actually functions in cly1 regulation and, if it does, which miR172 gene contributes to cleistogamy. It was also interesting to explore whether miR172-mediated cly1 regulation occurs at transcriptional level or at translational level. Methods Deep sequencing of small RNA identified the miR172 sequences expressed in barley immature spikes. miR172 genes were confirmed by computational and expression analysis. miR172 and cly1 expression profiles were determined by in situ hybridization and quantitative expression analysis. Immunoblot analysis provided the CLY1 protein quantifications. Definitive evidence of the role of miR172 in cleistogamy was provided by a transposon Ds-induced mutant of Hv-miR172a. Key Results A small RNA analysis of the immature barley spike revealed three isomers, miR172a, b and c, of which miR172a was the most abundant. In situ hybridization analysis showed that miR172 and cly1 co-localize in the lodicule primordium, suggesting that these two molecules potentially interact with one another. Immunoblot analysis showed that the sequence polymorphism at the miR172 target site within cly1 reduced the abundance of the CLY1 protein, but not that of its transcript. In a Ds-induced mutant of Hv-miR172a, which generates no mature miR172a, the lodicules fail to grow, resulting in a very small lodicule. Conclusions Direct evidence is presented to show that miR172a acts to reduce the abundance of the CLY1 protein, which enables open flowering in barley.
Combining Open IE and Distant Supervision for KBP Slot Filling

The University of Washington participated in English Slot Filling for TAC-KBP 2014 with a system that combines its 2013 OPENIE-KBP system (Soderland et al., 2013) with the MULTIR extractor (Hoffmann et al., 2011), which uses distant supervision from Freebase. Since OPENIE-KBP is identical to our KBP 2013 system, this lets us quantify how this year’s queries are more difficult than last year’s. OPENIE-KBP gives high precision at moderate recall – we analyze the limitations of recall to an extractor based on Open IE. Our MULTIR-KBP extractor added to the recall in a combined system, but lowered the precision. We analyze the reasons for low precision with distant supervision.
Animal Models for Coffin-Lowry Syndrome: RSK2 and Nervous System Dysfunction

Loss of function mutations in the rsk2 gene cause Coffin-Lowry syndrome (CLS), which is associated with multiple symptoms including severe mental disabilities. Despite the characterization of ribosomal S6 kinase 2 (RSK2) as a protein kinase acting as a downstream effector of the well characterized ERK MAP-kinase signaling pathway, it turns out to be a challenging task to link RSK2 to specific neuronal processes dysregulated in case of mutation. Animal models such as mouse and Drosophila combine advanced genetic manipulation tools with in vivo imaging techniques, high-resolution connectome analysis and a variety of behavioral assays, thereby allowing for an in-depth analysis for gene functions in the nervous system. Although modeling mental disability in animal systems has limitations because of the complexity of phenotypes, the influence of genetic variation and species-specific characteristics at the neural circuit and behavioral level, some common aspects of RSK2 function in the nervous system have emerged, which will be presented. Only with this knowledge our understanding of the pathophysiology of CLS can be improved, which might open the door for development of potential intervention strategies.
4‐Oxo‐β‐apo‐13‐carotenone from the Cyanobacterium Anabaena cylindrica PCC 7122

Apocarotenoids are widely distributed among living organisms (bacteria, fungi, algae, plants and even animals) and have been associated with several signaling functions. These compounds are generated by the activity of carotenoid cleavage dioxygenases (CCDs), whose diversity greatly contributes to the large number of apocarotenoids that have been described so far. It is nevertheless expected that a considerable diversity of these molecules is yet to be discovered. In this work, we describe the isolation and structural elucidation of the apocarotenoid 4‐oxo‐β‐apo‐13‐carotenone from the cultured freshwater cyanobacterium Anabaena cylindrica PCC 7122, corresponding to the first report of this compound from natural sources.
A Common Framework for Interactive Texture Transfer

In this paper, we present a general-purpose solution to interactive texture transfer problems that better preserves both local structure and visual richness. It is challenging due to the diversity of tasks and the simplicity of required user guidance. The core idea of our common framework is to use multiple custom channels to dynamically guide the synthesis process. For interactivity, users can control the spatial distribution of stylized textures via semantic channels. The structure guidance, acquired by two stages of automatic extraction and propagation of structure information, provides a prior for initialization and preserves the salient structure by searching the nearest neighbor fields (NNF) with structure coherence. Meanwhile, texture coherence is also exploited to maintain similar style with the source image. In addition, we leverage an improved PatchMatch with extended NNF and matrix operations to obtain transformable source patches with richer geometric information at high speed. We demonstrate the effectiveness and superiority of our method on a variety of scenes through extensive comparisons with state-of-the-art algorithms.
HyTasker: Hybrid Task Allocation in Mobile Crowd Sensing

Task allocation is a major challenge in Mobile Crowd Sensing (MCS). While previous task allocation approaches follow either the opportunistic or participatory mode, this paper proposes to integrate these two complementary modes in a two-phased hybrid framework called HyTasker. In the offline phase, a group of workers (called opportunistic workers) are selected, and they complete MCS tasks during their daily routines (i.e., opportunistic mode). In the online phase, we assign another set of workers (called participatory workers) and require them to move specifically to perform tasks that are not completed by the opportunistic workers (i.e., participatory mode). Instead of considering these two phases separately, HyTasker jointly optimizes them with a total incentive budget constraint. In particular, when selecting opportunistic workers in the offline phase of HyTasker, we propose a novel algorithm that simultaneously considers the predicted task assignment for the participatory workers, in which the density and mobility of participatory workers are taken into account. Experiments on two real-world mobility datasets demonstrate that HyTasker outperforms other methods with more completed tasks under the same budget constraint.
Task Allocation in Mobile Crowd Sensing: State-of-the-Art and Future Opportunities

Mobile crowd sensing (MCS) is the special case of crowdsourcing, which leverages the smartphones with various embedded sensors and user’s mobility to sense diverse phenomenon in a city. Task allocation is a fundamental research issue in MCS, which is crucial for the efficiency and effectiveness of MCS applications. In this paper, we specifically focus on the task allocation in MCS systems. We first present the unique features of MCS allocation compared to generic crowdsourcing, and then provide a comprehensive review for diversifying problem formulation and allocation algorithms together with future research opportunities.
Acute Responses to Forearm Compression of Blood Lactate Accumulation, Heart Rate, Perceived Exertion, and Muscle Pain in Elite Climbers

Objectives: To evaluate the immediate responses to forearm compression of blood lactate concentration, heart rate, perceived exertion and local forearm muscle pain during severe climbing in elite climbers. Method: Seven elite climbers (18 ± 2 years; 164 ± 5 cm; 57.8 ± 5.3 kg) performed 3 × 3 climbing bouts with maximal intensity on a distinct 8 m boulder wall (lead grade: 7a–8b) in a single blinded, placebo-controlled cross-over design, wearing either forearm sleeves with compression (verum-compression) or placebo forearm sleeves with no compression (falsum-compression). Each climber’s heart rate was recorded during and capillary blood lactate concentration, perceived exertion and forearm muscle pain were assessed directly after climbing. Result: Heart rate (p = 0.45, ηp2 = 0.12), blood lactate concentrations (p = 0.44, ηp2 = 0.10), perceived exertion levels (p = 0.51, ηp2 = 0.08) and pain perception (p = 0.67, ηp2 = 0.03) were not affected by forearm compression. No condition × time interaction effect (compression × time) occurred for heart rate (p = 0.66, ηp2 = 0.04), blood lactate concentration (p = 0.70, ηp2 = 0.02), perceived exertion (p = 0.20, ηp2 = 0.26) and pain perception (p = 0.62, ηp2 = 0.04). Conclusion: In elite climbers performing severe climbing bouts, sleeves with forearm compression do not alter blood lactate concentration, heart rate, perceived exertion and local forearm muscle pain.
Computable Variants of AIXI which are More Powerful than AIXItl

Abstract This paper presents Unlimited Computable AI, or UCAI, that is a family of computable variants of AIXI. UCAI is more powerful than AIXItl, which is a conventional family of computable variants of AIXI, in the following ways: 1) UCAI supports models of terminating computation, including typed lambda calculi, while AIXItl only supports Turing machine with timeout ˜t, which can be simulated by typed lambda calculi for any ˜t; 2) unlike UCAI, AIXItl limits the program length to some ˜l .
Inductance Evaluation and Sensorless Control of a Concentrated Winding PM Vernier Machine

Due to the advantages of high torque density and simple mechanical structure, permanent magnet vernier (PMV) machines have attracted more and more research interests. In this paper, the inductance nonlinearity of an advanced concentrated winding PMV machine is investigated with consideration of both magnetic saturation and cross-coupling saturation under different d-axis and q-axis current loading. Then, the mathematical model with a variable inductance matrix of the PMV machine is established through incorporation of the finite-element analysis and the surface fitting method. Further, a back electromotive force based sensorless control method is developed for this PMV machine model with design of a current-dependent state observer. Based on the sensorless algorithm, the influence of inductance variation on rotor position estimation performance is then quantitatively evaluated. Simulation results show that the PMV machine can be well controlled for steady- and dynamic-state operation, and the position estimation error is effectively decreased. Finally, the proposed sensorless control algorithm is validated through experimental tests of the PMV prototype machine.
Mitigation of DC and Harmonic Currents Generated by Voltage Measurement Errors and Grid Voltage Distortions in Transformerless Grid-Connected Inverters

The dc offset and scaling errors in the voltage measurements cause the injection of undesired dc and harmonic currents into the three-phase output currents of the grid-connected inverter. This study proposes an enhanced current control scheme to eliminate the dc and harmonic currents caused by voltage distortion and voltage measurement error in three-phase grid-connected inverters. The proposed current controller is designed in the synchronous (<italic>d-q </italic>) reference frame and composed of a proportional resonant (PR) controller and a repetitive controller (RC). The role of the RC is to regulate the grid current follow the reference value as well as compensate all <inline-formula><tex-math notation="LaTeX">$6{\rm{n}}\omega _{{\rm{s}}}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$(6{\rm{n}}\pm 2)\omega_{{\rm{s}}}\,(n= 1,\,2,\,3,\ldots)$</tex-math> </inline-formula> harmonic components caused by distorted grid voltage and scaling errors. Meanwhile, the PR controller helps to compensate the dc current generated by dc offset measurement errors to guarantee that the three-phase grid currents are balanced and sinusoidal with extremely low dc component. Since the RC employed in the proposed current controller reduces to time delay by four times compared to the conventional RC, the proposed control system ensures good steady-state performance of the grid current without deteriorating its fast dynamic response. The effectiveness of the suggested solution is verified by various experimental tests.
Resveratrol Promotes Nerve Regeneration via Activation of p300 Acetyltransferase-Mediated VEGF Signaling in a Rat Model of Sciatic Nerve Crush Injury

Peripheral nerve injuries are generally associated with incomplete restoration of motor function. The slow rate of nerve regeneration after injury may account for this. Although many benefits of resveratrol have been shown in the nervous system, it is not clear whether resveratrol could promote fast nerve regeneration and motor repair after peripheral nerve injury. This study showed that the motor deficits caused by sciatic nerve crush injury were alleviated by daily systematic resveratrol treatment within 10 days. Resveratrol increased the number of axons in the distal part of the injured nerve, indicating enhanced nerve regeneration. In the affected ventral spinal cord, resveratrol enhanced the expression of several vascular endothelial growth factor family proteins (VEGFs) and increased the phosphorylation of p300 through Akt signaling, indicating activation of p300 acetyltransferase. Inactivation of p300 acetyltransferase reversed the resveratrol-induced expression of VEGFs and motor repair in rats that had undergone sciatic nerve crush injury. The above results indicated that daily systematic resveratrol treatment promoted nerve regeneration and led to rapid motor repair. Resveratrol activated p300 acetyltransferase-mediated VEGF signaling in the affected ventral spinal cord, which may have thus contributed to the acceleration of nerve regeneration and motor repair.
Coordinated Frequency Control Strategy for an Islanded Microgrid With Demand Side Management Capability

This paper presents a novel coordinated frequency control (CFC) scheme with demand side management capability for an islanded microgrid. The proposed CFC scheme is a communication-free coordination among fast responding devices: thermostatically controlled loads (TCLs), photovoltaic power systems, battery energy storage systems, and a slow responding diesel generator (DZ). The fast responding devices are deployed to achieve a swift frequency regulation in transient state. In steady state, these devices are returned to their normal operating condition by changing loading conditions of the DZ without employing interdevice communication. The proposed control strategy not only achieves frequency regulation in adherence to IEEE Standard 1547, but also maintains customers’ quality of service while manipulating TCLs for frequency regulation. A comprehensive study of the proposed CFC scheme is carried out on a modified IEEE 13-bus balanced industrial distribution network using MATLAB/Simulink. In addition, real-time performances of the CFC scheme have been validated experimentally using OPAL-RT simulator, and a well-programmed TMS320F28335 microcontroller. Both the simulation and experimental results demonstrate effective performance of the proposed CFC in achieving efficient frequency regulation.
SAIL (UNIST) team Participation in KBP 2016 Cold-Start Slot filling

Building a Knowledge Base (KB) from unstructured text is one of challenges in natural language processing. From 2009, National Institute of Standards and Technology (NIST) has been annually opening challenge, Knowledge Base Population (KBP)1, for this work. In this paper, we focus on automatic knowledge base population by Cold Start Slot Filling (Cold Start SF)2 which is a kind of NIST KBP. We will use Distant Supervision (DS), widely used to this problem, to extract feature from unstructured text and map sentence to feature space. We also use neural network to extend representation power of feature. Some cases, we can not find the answer using DS. In this case, we use bidirectional Long ShortTerm Memory (LSTM) to find the answer.
Changes in Blood Pressure After the 2016 United States Presidential Election. Analyses in Response to "The Association of Posttraumatic Stress Disorder With Clinic and Ambulatory Blood Pressure in Healthy Adults" by Edmondson et al.

With the recent spate of studies looking into the effect of socioeconomics and health, I wanted to share some interesting findings we found incidentally as a part of a larger blood pressure study that add evidence to the findings of Edmondson et al. on the relationship between posttraumatic stress disorder (PTSD) and elevated blood pressure (BP) (1). Their study found that the presence of PTSDwas associated with a 3to 4-point increase in systolic blood pressure in clinic and ambulatory settings. The current thought is that those with elevated stress levels, like those with PTSD, are prone to experience events more that provoke anxiety, and the cumulative effect of these leads to an overall increase in BP. This mechanism should be consistent with high perceived stress as it is with PTSD. In support of this finding, during the fall of 2016, we evaluated effects of yogic breathing exercises on BP in a 3-arm randomized controlled trial. Data collection of this study coincidentally overlapped with the US presidential election. Blood pressures were measured using uniform validated BP monitors in examination rooms according to standard clinic protocols. Trained research assistants and physicians took 2 BPs 5 minutes apart, of which only the second was used for analysis. Blood pressures were taken once weekly for 6 weeks and at 1 and 3 months after intervention. A post hoc survey was created based on the American Psychological