Miracle-dz/UniFAR-FTUs huggingface dataset:
An examination of how households share and coordinate the completion of errands

People often complete tasks and to-dos not only for themselves but also for others in their household. In this work, we examine how household members share and accomplish errands both individually and together. We conducted a three-week diary study with eight households to understand the types of errands that family members and roommates share with each other. We explore their motivations for offering and requesting help to complete their errands and the variety of methods for doing so. Our findings reveal when participants sometimes face challenges completing their errands, and how household members request and receive help. We learned that the cooperative performance of errands is typically dependent on household members' location, availability, and capability. Using these findings, we discuss design opportunities for cooperative errands sharing systems that can assist households.
N$^3$LARS: Minimum Redundancy Maximum Relevance Feature Selection for Large and High-dimensional Data

We propose a feature selection method that finds non-redundant features from a large and high-dimensional data in nonlinear way. Specifically, we propose a nonlinear extension of the non-negative least-angle regression (LARS) called N${}^3$LARS, where the similarity between input and output is measured through the normalized version of the Hilbert-Schmidt Independence Criterion (HSIC). An advantage of N${}^3$LARS is that it can easily incorporate with map-reduce frameworks such as Hadoop and Spark. Thus, with the help of distributed computing, a set of features can be efficiently selected from a large and high-dimensional data. Moreover, N${}^3$LARS is a convex method and can find a global optimum solution. The effectiveness of the proposed method is first demonstrated through feature selection experiments for classification and regression with small and high-dimensional datasets. Finally, we evaluate our proposed method over a large and high-dimensional biology dataset.
Recommending Accounts to Twitter Users

Introduction Twitter is a service that allows users to post short messages (140 characters) to their profile page. It also allows users to "follow" other users whereby a user can see updates from the users he follows on his twitter page. People usually follow friends (people they know in real life) or accounts whose updates they find interesting. Today, Twitter has more than 100M users and more than 190 M visitors monthly. Therefore, it is not easy to find interesting accounts to follow.The objective of this paper is to recommend accounts to users that they might find interesting
Should age be a factor to change from a level II to a level I trauma activation?

BACKGROUND Elderly trauma patients have a higher incidence of medical comorbidities when compared with their younger cohorts. Currently, the minimally accepted criteria established by the Committee on Trauma for the highest level of trauma activation (Level I) does not include age as a factor. Should patients older than 60 years with multiple injuries and/or a significant mechanism of injury be considered as part of the criteria for Level I activation? Would these patients benefit from a higher level of activation? METHODS The National Trauma Data Bank was queried for the period of January 1, 1999, to December 31, 2008, for all trauma patients and associated injury severity score (ISS). The data abstracted were based on age and ISS. RESULTS The National Trauma Data Bank contained 802,211 trauma patients. Seventy-nine percent were younger than 60 years, and 21% were older than 60 years. Our analysis shows that in all levels of injury, patients older than 60 years have an increased risk for morbidity and mortality. We found a threefold increase in morbidity and a fivefold increase in mortality among the older (age >60 years) population with a minor ISS. Elderly patients with a major ISS demonstrated a twofold increase in morbidity and a fourfold increase in mortality. CONCLUSION Patients with an ISS between 0 and 15 are often triaged to Level II activation. Our data would suggest that patients older than 60 years should be a criterion for the highest level of trauma activation.
In Vitro Reconstitution of Light-harvesting Complexes of Plants and Green Algae

In plants and green algae, light is captured by the light-harvesting complexes (LHCs), a family of integral membrane proteins that coordinate chlorophylls and carotenoids. In vivo, these proteins are folded with pigments to form complexes which are inserted in the thylakoid membrane of the chloroplast. The high similarity in the chemical and physical properties of the members of the family, together with the fact that they can easily lose pigments during isolation, makes their purification in a native state challenging. An alternative approach to obtain homogeneous preparations of LHCs was developed by Plumley and Schmidt in 19871, who showed that it was possible to reconstitute these complexes in vitro starting from purified pigments and unfolded apoproteins, resulting in complexes with properties very similar to that of native complexes. This opened the way to the use of bacterial expressed recombinant proteins for in vitro reconstitution. The reconstitution method is powerful for various reasons: (1) pure preparations of individual complexes can be obtained, (2) pigment composition can be controlled to assess their contribution to structure and function, (3) recombinant proteins can be mutated to study the functional role of the individual residues (e.g., pigment binding sites) or protein domain (e.g., protein-protein interaction, folding). This method has been optimized in several laboratories and applied to most of the light-harvesting complexes. The protocol described here details the method of reconstituting light-harvesting complexes in vitro currently used in our laboratory,and examples describing applications of the method are provided.
An improved multiphysics modelling approach for dielectrophoresis-based cell separation

This article presents a new multiphysics modelling approach for cell manipulation by dielectrophoresis. This approach is proposed to model and predict the behavior of particles injected into a microchannel due to the application of an electrical field. The objective of this model is to better characterize microelectronic circuits dedicated to design and implement hybrid systems such as lab-on-chips integrating microelectronics and microfluidic structures. The proposed model allows to determine the required configuration of microelectronic circuits and needed control signals to generate. This model applies primarily to applications using dielectrophoresis cell separation in a microchannel. Then, by using the proposed model, the cell behaviour can be predicted using an advanced multiphysics simulation methode.
Application Research based on Artificial Fish-swarm Neural Network in Sintering Process

Sinter tumbler strength is an important parameter in the sintering process, and has an important influence on the performance of finished sinter. Artificial fish swarm algorithm have good ability to acquire the global performance, the neural network has strong nonlinear ability and local optimization performance,; AFSA+BP algorithm combined with artificial fish swarm algorithm and BP algorithm, realizes the complementary artificial fish swarm algorithm global search capability and BP algorithm's local optimization combination of performance, an artificial fish swarm neural results show that the network combination algorithm, it is shown that comparing with the traditional BP neural network forecasting method，the presented forecasting method has better adaptive ability and can give better forecasting results.The artificial fish—swarm algorithm network is trained and checked with the actual production data．this algorithm has strong generalization capability, predictive accuracy improved significantly, and speed up the convergence rate, provides an effective method for strength prediction. Which be used for off-line learning and prediction, a good basis for the online application.
Intra-Clustering: Accelerating On-chip Communication for Data Parallel Architectures

Modern computation workloads contain abundant Data Level Parallelism (DLP), which requires specialized data parallel architectures, such as Graphics Processing Units (GPUs). With parallel programming models, such as CUDA and OpenCL, GPUs are easily to be programmed for non-graphics applications, and therefore become a cost effective approach for data parallel architectures. The large quantity of available parallelism places a heavy stress on the memory system as the limited number of pins confines the number of memory controllers on the chip. This creates a potential bottleneck for performance scalability of the GPUs. To accelerate communication with the memory system, we propose the Intra-Clustering on-chip network for data parallel architectures, which is built upon a traditional two-dimensional electrical mesh network with memory controllers connected through a nanophotonic ring and compute cores grouped into different clusters. Our evaluations with CUDA benchmarks show that the Intra-Clustering architecture can improve communication delay by an average of 17% (up to 32%) and IPC by an average of 5% (up to 11.5%).
Medial Preoptic Regulation of the Ventral Tegmental Area Related to the Control of Sociosexual Behaviors

Visual Abstract During sociosexual encounters, different brain mechanisms interact to orchestrate information about the salience of external stimuli along with the current physiological and environmental conditions in order to process these in an optimal manner. One candidate neural system involves the potential interplay between the medial preoptic nucleus (POM) and mesolimbic reward circuitry. We present here evidence indicating that projections originating from the POM play a modulatory role on the mesolimbic reward circuitry related to male sexual behavior in Japanese quail (Coturnix japonica). First, we used an asymmetrical inactivation strategy where POM and ventral tegmental area (VTA) were unilaterally inactivated via the GABAA agonist muscimol, either in an ipsilateral or contralateral fashion. Ipsilateral injections of muscimol had negligible effects on both appetitive and consummatory sexual behaviors. In contrast, contralateral injections significantly impaired appetitive sexual behaviors but had no clear effect on consummatory sexual behaviors. Next, we labeled cells projecting from the POM to the VTA by stereotaxic injection into VTA of the retrograde tracer biotinylated dextran amine (BDA). Two weeks later, brains from males who had been allowed to interact freely with a female (15 min) or kept as controls were collected and fixed for double immunohistochemical labeling of BDA and the immediate early gene Fos. More retrogradely labeled BDA cells in POM expressed Fos after sociosexual interactions than in control conditions. Overall, these findings provide novel evidence for the interplay between POM and VTA in the modulation of appetitive but not consummatory sexual behaviors. Schematic representation of the putative role of the projection from the medial POM to the VTA in the regulation of appetitive and consummatory sexual behaviors. Unilateral inactivation of POM and VTA on (1) ipsilateral sides has negligible effects on both aspects of sexual behaviors, whereas (2) contralateral inactivation disrupts appetitive sexual behaviors.
Comparametric image compositing: Computationally efficient high dynamic range imaging

We propose a novel computational method for compositing low-dynamic-range (LDR) images into an high-dynamic-range (HDR) image by the use of a comparametric camera response function (CCRF), which is the response of a virtual HDR camera to multiple inputs. We demonstrate the use of this method with a simple probabilistic joint estimation model, that accounts for Gaussian noise, using iterative non-linear optimization to compute the CCRF. We achieve a speedup of ≈2500×, relative to direct calculation using the probabilistic model. This method can be implemented as a multidimensional lookup table, and enables realtime HDR video with any camera response function model, and any compositing algorithm based on pixel value and exposure.
Evaluation of antioxidant activity of Ruta graveolens L. extract on inhibition of lipid peroxidation and DPPH radicals and the effects of some external factors on plant extract's potency.

The antioxidant properties of Ruta graveolens L. were evaluated by two different methods; free radical scavenging using DPPH and inhibition of lipid peroxidation by the ferric thiocyanate method. The IC50 value of the methanol extract in DPPH inhibition was 200.5 μg/mL which was acceptable in comparison with BHT (41.8 μg/mL). In thiocyanate method, the plant extract demonstrated activity as much as BHT in prevention of lipid peroxidation. Increasing the temperature during extraction, significantly decreased the extract power in inhibition of DPPH radicals. The storage time and temperature had no effect on lipid peroxidation inhibition.
Design of Chinese Text Categorization Classifier Based on Attribute Bagging

In order to improve the precise rate and recall rate of Chinese text classifier, an improved bagging algorithm – attribute bagging is used in this paper. Document is represented by vector space model and Information Gain is used to do the feature selection. Re-sampling attributes is used to get multiple training sets and the kNN is selected as the individual classifier. The classification result is attained by voting. Experiments show that the attribute bagging gets lower errors and better performance than bagging and kNN in Chinese text categorization.
Item pricing for revenue maximization

In this note we report recent results on item pricing for revenue maximization in the presence of buyers with complex, unknown preferences. We focus on two important classes of settings: buyers with general valuations for the case of items in unlimited supply, and buyers with subadditive valuations for the case of items in limited supply.
Pairs Trading: Performance of a Relative Value Arbitrage Rule

We test a Wall Street investment strategy known as "pairs trading" with daily data over the period 1962 through 1997. Stocks are matched into pairs according to minimum distance in historical normalized price space. We test the profitability of several trading rules with six-month trading periods over the 1962-1997 period, and find average annualized excess returns of up to 12 percent for a number of self-financing portfolios of top pairs. Part of these profits may be due to market microstructure effects. Nevertheless, our historical trading profits exceed a conservative estimate of transaction costs through most of the period. We bootstrap random pairs in order to distinguish pairs trading from pure mean-reversion strategies. The bootstrap results suggest that the ? pairs? effect differs from previously documented mean reversion profits.
Cerebral Ischemia and Seizures Induce Tyrosine Phosphorylation of PYK2 in Neurons and Microglial Cells

The nonreceptor tyrosine kinase PYK2 represents a stress-sensitive mediator of c-Jun N-terminal kinase and p38 mitogen-activated protein kinase (MAPK) signaling pathways in many cell types. In the present study, we assessed the tyrosine phosphorylation of PYK2 under normal and pathological conditions in the CNS. We generated a polyclonal antibody that selectively recognizes tyrosine-phosphorylated PYK2 at its major autophosphorylation site. By using this antibody, we demonstrate that the phosphorylation profile of PYK2 after focal cerebral ischemia is biphasic. The first phase occurs within 1 hr, when most of the phospho-PYK2 immunoreactivity was observed in cortical neurons, whereas 24–72 hr after ischemia, a striking induction of phospho-PYK2 immunoreactivity was evident in microglia around the necrotic infarcted area. Double-immunostaining analysis using both anti-phospho-PYK2 antibody and antibody against the double-phosphorylated active form of p38MAPK revealed that the two phosphorylated protein kinases exhibit strikingly similar distribution patterns after ischemia. A short time after ischemia, phosphorylation of p38MAPK was evident in the cortical neurons as demonstrated by both immunohistochemistry and immunoblotting analysis, whereas 24–72 hr after ischemia, phospho-p38MAPK was found in activated microglia and colocalized with phospho-PYK2. In contrast to cortical neurons, basal phospho-PYK2 immunoreactivity was observed in hippocampal pyramidal neurons, which was markedly decreased after kainate acid-induced status epilepticus. However, 24 hr after the epileptic onset, a pronounced upregulation of PYK2 and phospho-PYK2 immunoreactivities was evident in microglial cells, as demonstrated by double-immunostaining with the microglial marker OX42. These results provide, for the first time, in situ localization of tyrosine-phosphorylated PYK2 in neuronal stress pathways in the adult rat brain and are consistent with the role of PYK2 as an upstream regulator of p38MAPK signaling cascades in response to stress signals.
Characterization of approximate plane symmetries for 3D fuzzy objects

We are interested in ﬁnding and characterizing the symmetry planes of fuzzy objects in 3D space. We introduce ﬁrst a fuzzy symmetry measure which deﬁnes an object symmetry degree with respect to a given plane. It is computed by measuring the similarity between the original object and its reﬂection. The choice of an appropriate measure of comparison is based on the desired properties. In a second part, a method for ﬁnding the best symmetry planes of fuzzy objects is proposed. We then apply these results to the representation of directional relationships.
Submodular volume simplex analysis: A greedy algorithm for hyperspectral unmixng

The hyperspectral unmixing problem can be formulated as a combinatorial optimization which selects the spectral vectors that maximize the volume of a simplex, with the assumptions that the dataset contain pure pixels and the mixture is linear. Submodularity presents an intuitive diminishing returns property which arises naturally in discrete and combinatorial optimization problems. Submodular functions enable the application of fast, greedy algorithms which possess near optimal approximation guarantees. This paper proposes a submodular greedy-based approach for solving the spectral unmixing problem by modifying the objective function to become a non-decreasing submodular function. Theoretical and experimental results are presented to demonstrate the feasibility of the method.
Robust speech separation using time-frequency masking

A multi-microphone time-frequency speech masking technique is proposed. This technique utilizes both the time-frequency magnitude and phase information in order to estimate the signal-to-noise ratio (SNR) maximizing masking coefficients for each time-frequency block given that the direction (or alternatively, the time-delay of arrival) of the speaker of interest is known. Using this masking algorithm, speech features (such as formants) from the direction of interest are preserved while features from other directions are severely degraded. Digit recognition experiments indicate that the proposed technique can result in a substantial increase in the digit recognition accuracy rate. At 0 dB, for example, the proposed technique results in a digit recognition accuracy rate improvement of 26% over the single microphone case and an improvement of 12% over the two microphone superdirective beamforming case.
One-year prevalence of migraine in Spain: A nationwide population-based survey

Aim: The purpose of the study was to estimate the one-year prevalence of migraine among a population-based sample of Spanish adults. Method: Men and women aged 18−65 years were selected at random according to quotas for age, sex, size of habitat (<10,000 inhabitants, 10,001−50,000 inhabitants, 50,001−200,000 inhabitants and >200,000 inhabitants) and residence proportional to the population size of the geographical location. A random-digit-dial, computer-assisted telephone interview (CATI) survey was conducted between April and July 2006. The 2004 International Headache Society operational diagnostic criteria were applied. Results: From a total of 70,692 telephone calls and 26,255 (31.7%) valid contacts, 5,668 (21.6%) respondents completed the CATI survey. A total of 476 subjects (8.4%, 95% confidence interval [CI] 7.7−9.1%) with strict migraine and 236 with probable migraine (4.2%, 95% CI 3.7−4.7%) were recorded. The 1-year prevalence of total migraine (N = 712) was 12.6% (95% CI 11.6−13.6) (17.2% in females, 8.0% in males). The prevalence rates showed significant geographic variations, from 7.6% in Navarra to 18% in the Canary Islands. One-half of the subjects had migraine with aura. One-third of subjects were never diagnosed for migraine. Conclusions: The one-year prevalence of migraine in Spain is 12.6%, with a prevalence of migraine with and without aura of 8.4% and probable migraine of 4.2%. These findings add data to the current understanding of migraine.
Stochastic Volatility, Takeover Threats and Defensive Payout Strategy

This paper proposes a dynamic model of the growth firm facing takeover threats stochastically. The formal analysis here focuses on the defensive payout strategy of value-maximizing management under the circumstances of random stock market valuation errors, and the bidders' perceived synergistic gains. By borrowing the concept of "hazard rate" from reliability theory, The model sheds light on takeover activities and the observed defensive payout phenomenon in the financial markets. It also yields novel testable implications concerning the impact of anti-takeover costs on the target firm's value over time
Analysis and Presentation of Distributed Sensor Data for Network Intrusion Detection

Distributed network intrusion detection systems which incorporate tens, hundreds, even thousands, of sensors are becoming increasing popular. Managing and presenting the information from these sensors is becoming an increasingly difficult task. The paper explores the use of Conversation Exchange Dynamics (CED) to integrate and display sensor information from multiple nodes. We present an experimental setup consisting of multiple sensors reporting individual findings to a central server for aggregated analysis. Different scenarios of network attacks and intrusions were planned to investigate the effectiveness of the distributed system. The network attacks were taken from the M.I. T Lincoln Lab 1999 Data Sets. The distributed system was subjected to different combinations of network attacks in various parts of the network. The results were then analyzed to understand the behavior of the distributed system in response to the different attacks. In general, the distributed system detected all attacks under each scenario. Some surprising observations also indicated attack responses occurring in unanticipated scenarios.
Reaching consensus on a connected graph

We study a simple random process by means of which vertices of a connected graph can reach a mutual decision only through pairwise interactions with their neighbours. We compute probabilities that a certain option gets chosen and prove that these, surprisingly, do not depend on the network structure between the nodes. In some cases we are able show that the expected waiting time until the decision has been made is the shortest for the complete graph, and we consider also which graphs give the longest waiting time for $p=0$, proving an upper bound and giving a family of graphs which achieve this within a lower-order error term. This bound involves results on a variant of the coupon collector's problem. In order to obtain the formula for the mean of the waiting time we also study a version of the classical gambler's ruin process with delays. We obtain explicit expressions for the expected time until absorption and also prove that this monotonically increases with the parameter $p\in[0,1/2]$ in case of symmetric delays.