Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating maximum performance: effects of intraindividual variation

SUMMARY Researchers often estimate the performance capabilities of animals using a small number of trials per individual. This procedure inevitably underestimates maximum performance, but few studies have examined the magnitude of this effect. In this study we explored the effects of intraindividual variation and individual sample size on the estimation of locomotor performance parameters. We measured sprint speed of the lizard Sceloporus occidentalis at two temperatures (20°C and 35°C), obtaining 20 measurements per individual. Speed did not vary temporally, indicating no training or fatigue effects. About 50% of the overall variation in speed at each temperature was due to intraindividual variation. While speed was repeatable, repeatability decreased slightly with increasing separation between trials. Speeds at 20°C and 35°C were positively correlated, indicating repeatability across temperatures as well. We performed statistical sampling experiments in which we randomly drew a subset of each individual's full set of 20 trials. As expected, the sample's maximum speed increased with the number of trials per individual; for example, five trials yielded an estimate averaging 89% of the true maximum. The number of trials also influenced the sample correlation between mean speeds at 20°C and 35°C; for example, five trials yielded a correlation coefficient averaging 90% of the true correlation. Therefore, intraindividual variation caused underestimation of maximal speed and the correlation between speeds across temperatures. These biases declined as the number of trials per individual increased, and depended on the magnitude of intraindividual variation, as illustrated by running sampling experiments that used modified data sets.
Integration of Plug-In Hybrid Electric Vehicles into energy networks

Electrification of substantial percentages of individual transportation through Plug-In Hybrid Electric Vehicles (PHEVs) will lead to an integration of power and transport systems. This, in turn, will impose an additional demand on today's power system, potentially stressing hazardous for some pieces of equipment. Smart management schemes, investigated in this paper, can alleviate possible congestion issues in power systems by intelligently distributing available energy among connected PHEVs, modelled as agents with individual parameters and goals. The management scheme is integrated in aggregation entities, clustering PHEVs in various urban areas. Network impacts resulting from the smart management scheme will be studied based on power flow calculations. The analysis will give implications for PHEV integration schemes as well as tentative ideas of possible repercussions on hybrid power systems and how to counteract.
Analysis and Empirical Research on the Long-Memory Property of Exchange Rate Time Series

This paper applies the Rescaled Range Analysis(R/S), Log Period-gram Estimation(GPH) and Gaussian Semi-parametric Estimation(GSP) on eighteen time series, including daily, weekly and monthly of six exchange rates. The results tell us there does be the "Long-Memory" in exchange rates. It doesn't only help us for knowing exchange rates better with ARFIMA, but also for forecasting and National Bank's intervening.
A Novel Dual Iterative  $Q$-Learning Method for Optimal Battery Management in Smart Residential Environments

In this paper, a novel iterative Q-learning method called “dual iterative Q-learning algorithm” is developed to solve the optimal battery management and control problem in smart residential environments. In the developed algorithm, two iterations are introduced, which are internal and external iterations, where internal iteration minimizes the total cost of power loads in each period, and the external iteration makes the iterative Q-function converge to the optimum. Based on the dual iterative Q-learning algorithm, the convergence property of the iterative Q-learning method for the optimal battery management and control problem is proven for the first time, which guarantees that both the iterative Q-function and the iterative control law reach the optimum. Implementing the algorithm by neural networks, numerical results and comparisons are given to illustrate the performance of the developed algorithm.
Combining Ethnography and Case Study Research Designs in Studying Forestry Co-Management Approaches

The paper discusses how a combination of ethnographic and case study research designs can be appropriate in studying forestry co-management approaches and gives a step per step explanation of the methods that can be used for collecting data, ethical considerations, data analysis and selection of the interviewees in a combined ethnographic and case study research designs scenario to study forestry co-management approaches. It further shows how a researcher can take various decisions during field work when using the ethnographic and case study research designs scenarios to study forest co-management approaches in order to obtain as credible results as possible. It is concluded in the paper that a combination of ethnographic and case study research designs are suitable for studying forest co-management approaches. However, despite the widely acknowledged potential inherent in the ethnographic design, there is still hesitation in adopting and accepting ethnography as a mode of studying forest co-management approaches most properly because of the time required to study forestry co-management approaches.
Deep Learning in Semantic Kernel Spaces

Kernel methods enable the direct usage of structured representations of textual data during language learning and inference tasks. Expressive kernels, such as Tree Kernels, achieve excellent performance in NLP. On the other side, deep neural networks have been demonstrated effective in automatically learning feature representations during training. However, their input is tensor data, i.e., they can not manage rich structured information. In this paper, we show that expressive kernels and deep neural networks can be combined in a common framework in order to (i) explicitly model structured information and (ii) learn non-linear decision functions. We show that the input layer of a deep architecture can be pre-trained through the application of the Nystrom low-rank approximation of kernel spaces. The resulting “kernelized” neural network achieves state-of-the-art accuracy in three different tasks.
An adaptive method for mining frequent itemsets efficiently: An improved header tree method

Data mining has become an important field and has been applied extensively across many different areas. Mining frequent itemsets from a transaction database is crucial for mining association rules. FP-growth algorithm has been widely used for frequent pattern mining and it is one of the most important algorithm proposed to efficiently mine association rules because it can dramatically improve the performance compared to the Apriori algorithm. Many investigations have proved that FP-growth method outperforms the method of Apriori-like candidate generation. The performance of the FP-growth method depends on many factors; the data structures, recursive creation of pattern trees, searching, sorting, insertion and many more. In all of the algorithms which are using fp-tree, a header table is used with sorted items. Header table is an important data structure in the mining process. The main datastructure (frequent trees) is created with the use of the header table. In this paper we suggest a new Binary Search Header Three (BSHT) and an Improved Header Tree mining (IHT-growth) to improve the performance of the frequent pattern mining. Experimental results show that the mining with BSHT is efficient for frequent pattern mining.
Analysis of genetic diversity among high sucrose genotypes of sugarcane (Saccharum spp.) derived from CoC 671 using sugarcane specific microsatellite markers.

Sugarcane breeders target genetic improvement for sucrose content using conventional and molecular approaches in order to produce more sugar per unit area. The sucrose rich clone viz. CoC 671 is a widely used parent in juice quality improvement programmes. The present study is carried out using twenty eight derivatives of CoC 671 bred through crossing as male parent, as female parent, selfing, through somaclonal variation and induced mutagenesis. The clones were evaluated based on 30 sugarcane specific STMS markers in order to identify more diverse types to be used as parents and to compare the efficiency of different breeding methods to generate more variability for imparting selection. Genetic diversity was estimated using Dice, Jaccard's and Simple Matching coefficient methods. STMS markers were found to be suited to detect genetic differences among the clones of common descent as supported by the lower similarity index values. Mean genetic similarity among the somaclones (SI value = 0.72), mutants (SI value = 0.81), clones derived from CoC 671 as a female (SI value = 0.73) parent and male parent (SI value = 0.70) clearly showed that the clones with CoC 671 as the male parent were more diverse and indicated the role of male parent in creating a more segregating population than when used as female parent. Tissue culture based selection through somaclonal variation and induced mutations were less efficient in creating variability than the conventional methods. More diverse clones and combinations were identified to be used in hybridization for sucrose improvement in sugarcane.
Silver lining in winning silver: an exploratory study of supporters’ reactions and coping on the social media towards Lee Chong Wei’s London Olympics defeat

Abstract The experience of loss is prevalent in all sports, but research into the phenomenon is scarce. Comments related to two YouTube videos which featured interviews with Malaysian badminton player Lee Chong Wei after his narrow final defeat to Lin Dan in the 2012 London Olympics were analysed in an exploratory attempt to understand supporters’ reactions and coping with the loss on social media. Content analysis of supporters’ collective reactions suggests that most of Lee’s supporters who posted comments were able to find a ‘silver lining in the cloud’ despite this loss, i.e. signs of coping were prevalent. The following seven categories were identified: (a) providing rationalizations, (b) offering solace, (c) expressing emotion, (d) showing respect, (e) displaying solidarity, (f) injecting humour, and (g) being negative. Insights from this study based on reactions on social media offer a fresh perspective for understanding supporters’ coping strategies in response to sport losses which could serve as a catalyst for future understanding of sport losses in sport psychology.
Using Rasch measurement to validate an instrument for measuring the quality of classroom teaching in secondary chemistry lessons

This study intends to develop a standardized instrument for measuring classroom teaching and learning in secondary chemistry lessons. Based on previous studies and interviews with expert teachers, the progression of five quality levels was constructed hypothetically to represent the quality of chemistry lessons in Chinese secondary schools. The measurement instrument was revised from the Evaluation Scale of Effectiveness of Primitive System of Classroom Teaching (ESEPrSCT). 90 videotaped chemistry lessons were collected and measured to validate the instrument in the pilot and field stage. By means of Rasch modeling, the instrument consisting of 18 items with five response categories was finally validated in this study. The results provide the validity and reliability evidence for using this measurement instrument to assess the quality of chemistry lessons.
Cultural fit and life satisfaction: Endorsement of cultural values predicts life satisfaction only in collectivistic societies

The current research examined the eff ct of cultural fit, or the congruence between values that individuals endorse and values that are normative in their culture, as a predictor of life satisfaction. In a large international data set drawn from the World Values Survey (Study 1), the effect of cultural fit was found in collectivistic societies but not in individualistic societies. While the endorsement of collectivistic values was predictive of life satisfaction in collectivistic societies, the reverse effect in individualistic societies, the endorsement of individualistic values predicting well-being, was not found. Study 2 examined these effects with a more comprehensive set of individualistic and collectivistic values administered to Chinese and Western participants. Findings replicated those in Study 1 in that the effect of cultural fit was observed only among Chinese participants. The asymmetric pattern of the results may reflect diverging ways of approaching culturally valued goals.
Transcranial Magnetic Stimulation of the Prefrontal Cortex in Awake Nonhuman Primates Evokes a Polysynaptic Neck Muscle Response That Reflects Oculomotor Activity at the Time of Stimulation

Transcranial magnetic stimulation (TMS) has emerged as an important technique in cognitive neuroscience, permitting causal inferences about the contribution of a given brain area to behavior. Despite widespread use, exactly how TMS influences neural activity throughout an interconnected network, and how such influences ultimately change behavior, remain unclear. The oculomotor system of nonhuman primates (NHPs) offers a potential animal model to bridge this gap. Here, based on results suggesting that neck muscle activity provides a sensitive indicator of oculomotor activation, we show that single pulses of TMS over the frontal eye fields (FEFs) in awake NHPs evoked rapid (within ∼25 ms) and fairly consistent (∼50–75% of all trials) expression of a contralateral head-turning synergy. This neck muscle response resembled that evoked by subsaccadic electrical microstimulation of the FEF. Systematic variation in TMS location revealed that this response could also be evoked from the dorsolateral prefrontal cortex (dlPFC). Combining TMS with an oculomotor task revealed state dependency, with TMS evoking larger neck muscle responses when the stimulated area was actively engaged. Together, these results advance the suitability of the NHP oculomotor system as an animal model for TMS. The polysynaptic neck muscle response evoked by TMS of the prefrontal cortex is a quantifiable trial-by-trial reflection of oculomotor activation, comparable to the monosynaptic motor-evoked potential evoked by TMS of primary motor cortex. Our results also speak to a role for both the FEF and dlPFC in head orienting, presumably via subcortical connections with the superior colliculus.
Continuity in the Lives of Elder Catholic Women Religious

Data from life review interviews with thirty-nine elder Catholic women religious (68–98) show these women's lives do not conform to a sequential pattern of late life developmental stages. Their lives can best be understood in terms of continuous themes throughout individual lives. The majority of the women reach ego integrity in young old age and continue to reestablish this by adhering to themes in their life stories. Themes serve as a framework of the self. The main themes of the participants are: faith, family, education, friends, community, caring for others, and prayer. Communal aspects of religious life support the women in their continuous development of identity. Generativity is evidenced in their lives as an ongoing component of self-identity. These data show the continuous process of establishing ego integrity throughout late life. The life review data can best be explained using the continuity theory of identity development.
The role of perceived stress and coping styles in development of prenatal anxiety

Prethodna istraživanja su pokazala da je predporođajna anksioznost rizicni faktor za razvoj afektivnih poremecaja nakon poroda, a može imati utjecaja i na razvoj fetusa. Cilj ovog istraživanja bio je ispitati ulogu percipiranog stresa i stilova suocavanja u nastanku predporođajne anksioznosti. Obuhvacen je uzorak od 149 trudnica u posljednjem tromjesecju trudnoce koje su popunile Ljestvicu percipiranog stresa, revidirani Upitnik suocavanja sa stresom te Upitnik anksioznosti kao stanja i osobine licnosti. Regresijska analiza je pokazala da su anksioznost kao osobina licnosti, dob, komplikacije u trudnoci te razina percipiranog stresa znacajni prediktori anksioznosti. S obzirom na povisen rizik za razvoj poslijeporođajne depresije kod anksioznih trudnica te moguc negativni utjecaj na dijete, naglasava se važnost adekvatnih intervencijskih postupaka u trudnoci.
Positron Emission Tomography Imaging of Risperidone Augmentation in Serotonin Reuptake Inhibitor-Refractory Patients

We studied 15 nondepressed patients with obsessive-compulsive disorder (OCD) who were nonresponders to serotonin reuptake inhibitors with an additive trial of risperidone. Positron emission tomography with 18F-deoxyglucose and magnetic resonance imaging was obtained at baseline and following 8 weeks of either risperidone or placebo in a double-blind parallel group design. Risperidone treatment was associated with significant increases in relative metabolic rate in the striatum, cingulate gyrus, the prefrontal cortex, especially in the orbital region, and the thalamus. Four of 9 patients who received risperidone showed clinical improvement (CGI score of 1 or 2 at 8 weeks) while none of the 6 patients who received placebo showed improvement. Patients with low relative metabolic rates in the striatum and high relative metabolic rates in the anterior cingulate gyrus were more likely to show a clinical response. These metabolic predictors of clinical response are consistent with earlier PET studies showing similar prediction when either neuroleptics or serotonin reuptake inhibitor treatments are administered individually. Our results are consistent with a frontostriatal circuit change related to both dopaminergic and serotonergic systems and with the presence of psychopharmacological subtypes within OCD.
Adaptive subcarrier and power allocation for multiuser OFDM in wireless environments – A Survey

The surge in demand for methods to transmit large amounts of data over wireless channel has led to recent interest in orthogonal frequency division multiplexing (OFDM). The time dispersive and frequency-selective nature of the wireless channel, causes intersymbol interference (ISI) and fading to be a serious impediment in wireless communication. OFDM has shown to be effective at combating frequency-selective fading, by dividing the channel into subcarriers much narrower than the channel coherent bandwidth, which reduces a frequency-selective fading channel into a set of flat fading subcarriers. The use of cyclic prefixes in OFDM has also been effective at addressing ISI. The effectiveness of OFDM has prompted more research in applying it in multiuser environments. In a single-user OFDM system, the transmit power for each subcarrier can be adapted to maximize data rate using the water-filling algorithm [1]. In multiuser environments, the situation becomes more complicated, as each user will likely have a different multipath fading profile, due to the users not being in the same location. Thus, it is likely that while one subcarrier may be in deep fade for a particular user, it may be in good condition for another user due to temporal and spatial diversity in user locations. Thus, this effect can be exploited to further enhance system performance. By dynamically allocating different subcarriers and transmit power to users, this scheme can enhance system performance beyond a fixed-power, fixed-subcarrier scheme. Furthermore, OFDM is typically used as a physical layer modulation scheme, on top of which a MAC scheme, such as TDMA, CDMA, or FDMA is used. By allocating different subcarriers to different users, this approach can also be viewed as a MAC scheme, where the entire set of subcarriers are shared between different users. We can denote this scheme as orthogonal frequency division multiple access (OFDMA). Several papers have investigated the problem of dynamic transmit power adaptation for multiuser OFDM in wireless environments. Different parameters can be optimized, whether it is data rate, or power efficiency. In [2], the authors attempted to minimize transmit power subject to a particular performance constraint, and then compare its performance with other MAC schemes. In [3], the authors studied the dual problem, in which capacity was maximized subject to a particular power and rate traffic constraint. A similar problem was studied in [4], in which capacity was maximized subject to power constraints, but a formal proof was developed to support the empirical approach taken by authors in [2]. Several other papers attempted to apply in real-world settings, including 802.11 wireless LAN [5]. In this paper, I shall attempt to survey and analyze the above papers, as well as analyze the general approach of dynamic power and subcarrier allocation for wireless multiuser OFDM.
Role of nitric oxide in lung injury associated with experimental acute pancreatitis

This study evaluated the effect of varying the synthesis of nitric oxide with sodium nitroprusside or N‐nitro‐L‐arginine methyl ester (L‐NAME) in a pancreatitis‐lung injury model. Rats (n = 45) were randomized to control or caerulein‐induced pancreatitis groups, treated with saline, sodium nitroprusside (0·4 μg/kg) or L‐NAME (10 mg/kg). Myeloperoxidase activity was used as a measure of neutrophil infiltration. Wet to dry (W:D) lung weight and bronchoalveolar lavage (BAL) protein concentrations were used to assess vascular leakage. Pancreatitis was shown to induce pulmonary neutrophil influx: mean(s.e.m.) myeloperoxidase activity 6·79(0·5) units/g in caerulein‐treated animals versus 2·08(0·5) units/g in controls (P < 0·001). Animals with pancreatitis showed increased microvascular leakage compared with controls (mean(s.e.m.) W:D lung weight 7·01(0·5) versus 2·85(0·2), P < 0·001; BAL protein concentration 2539(222) versus 347(32) μg/ml, P < 0·001). Compared with the saline‐treated pancreatitis group, these changes were reduced by sodium nitroprusside (mean(s.e.m.) myeloperoxidase activity to 2·5(0·4) units/g, P < 0·001; W:D lung weight to 3·8(0·37), P < 0·001; BAL protein concentration 1389(182) μg/ml, P < 0·05). L‐NAME exacerbated the pancreatitis‐induced pulmonary oedema (W:D lung weight increased to 11·96(0·6), P < 0·001), protein leakage (BAL protein concentration rose to 3707(309) μg/ml, P < 0·05) and neutrophil infiltration (myeloperoxidase activity increased to 9·01(0·3) units/g, P < 0·05). These data suggest that, in vivo, nitric oxide inhibits pancreatitis‐induced lung injury, possibly in part by inhibiting pulmonary neutrophil influx.
FPGA-based Acceleration of Deep Neural Networks Using High Level Method

Deep neural network (DNN) is becoming more and more applied in data center applications such as speech recognition, image search, etc. However, the training in DNN is very time-consuming because of its deep structure. This paper presents FPGA-based acceleration of deep neural networks using a high level method and proposes a parallel optimizing strategy using the Kintex-7 FPGA board's features. Experimental results show that it can increase the utilization of FPGA computation units with low mini-batch size and reduce the transfer cost effectively. The optimized algorithm achieves up to 17.65x higher performance than CPU.
On the Predictability of Human Contacts: Influence Factors and the Strength of Stronger Ties

While the analysis of online social networks is a prominent research topic, offline real-world networks are still not covered extensively. However, their analysis can provide important insights into human behavior. In this paper, we analyze influence factors for link prediction in human contact networks. Specifically, we consider the prediction of new links, and extend it to the analysis of recurring links. Furthermore, we consider the impact of stronger ties for the prediction. The results and insights of the analysis are a first step onto predictability applications for human contact networks.