Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship between Oil, Exchange Rates, and Commodity Prices

Exchange rates have long been thought to have an important impact on the export and import of goods and services, and, thus, exchange rates are expected to influence the price of those products that are traded. At the same time, energy impacts commodity production in some very important ways. The use of chemical and petroleum derived inputs has increased in agriculture over time; the prices of these critical inputs, then, would be expected to alter supply, and, therefore, the prices of commodities using these inputs. Also, agricultural commodities have been increasingly used to produce energy, thereby leading to an expectation of a linkage between energy and commodity markets. In this paper, we examine the price relationship through time of the primary agricultural commodities, exchange rates, and oil prices. Using overlapping time periods, we examine the cointegration relationship between prices to determine changes in the strength of the linkage between markets through time. In general, we find that commodity prices are linked to oil for corn, cotton, and soybeans, but not for wheat, and that exchange rates do play a role in the linkage of prices over time.
Increasing the efficiency of a hybrid polymer photovoltaic cell with polymer nanofiber complexes of varied thickness

The purpose of this investigation is to increase the power output of a specific polymer when utilized in a photovoltaic cell. Fossil fuels are an efficient and reliable source of energy, but they are detrimental to the environment, producing pollutants and greenhouse gases. [1] Also, the supply of fossil fuels is quickly diminishing. According to Kaufman,[2] at the rate fossil fuels are currently consumed, the supply will be exhausted within fifty years. Assuming that this statement is true, there is significant need for a new source of energy that will last a long time, be safe, clean, and easy to produce.
Real-time informed path sampling for motion planning search

Mobile robot motions often originate from an uninformed path-sampling process such as random or low-dispersion sampling. We demonstrate an alternative approach to path sampling that closes the loop on the expensive collision-testing process. Although all necessary information for collision testing a path is known to the planner, that information is typically stored in a relatively unavailable form in a costmap or obstacle map. By summarizing the most salient data in a more accessible form, our process delivers a denser sampling of the free path space per unit time than open-loop sampling techniques. We obtain this result by probabilistically modeling—in real time and with minimal information—the locations of obstacles and free space, based on collision-test results. We present CALM, the combined adaptive locality model, along with an algorithm to bias path sampling based on the model’s predictions. We provide experimental results in simulation for motion planning on mobile robots, demonstrating up to a 330% increase in paths surviving collision test.
Power efficient Spiking Neural Network Classifier based on memristive crossbar network for spike sorting application

In this paper authors have presented a power efficient scheme for implementing a spike sorting module. Spike sorting is an important application in the field of neural signal acquisition for implantable biomedical systems whose function is to map the Neural-spikes (N-spikes) correctly to the neurons from which it originates. The accurate classification is a pre-requisite for the succeeding systems needed in Brain-Machine-Interfaces (BMIs) to give better performance. The primary design constraint to be satisfied for the spike sorter module is low power with good accuracy. There lies a trade-off in terms of power consumption between the on-chip and off-chip training of the N-spike features. In the former case care has to be taken to make the computational units power efficient whereas in the later the data rate of wireless transmission should be minimized to reduce the power consumption due to the transceivers. In this work a 2-step shared training scheme involving a K-means sorter and a Spiking Neural Network (SNN) is elaborated for on-chip training and classification. Also, a low power SNN classifier scheme using memristive crossbar type architecture is compared with a fully digital implementation. The advantage of the former classifier is that it is power efficient while providing comparable accuracy as that of the digital implementation due to the robustness of the SNN training algorithm which has a good tolerance for variation in memristance.
Deep-learnt classification of light curves

Astronomy light curves are sparse, gappy, and heteroscedastic. As a result standard time series methods regularly used for financial and similar datasets are of little help and astronomers are usually left to their own instruments and techniques to classify light curves. A common approach is to derive statistical features from the time series and to use machine learning methods, generally supervised, to separate objects into a few of the standard classes. In this work, we transform the time series to two-dimensional light curve representations in order to classify them using modern deep learning techniques. In particular, we show that convolutional neural networks based classifiers work well for broad characterization and classification. We use labeled datasets of periodic variables from CRTS survey and show how this opens doors for a quick classification of diverse classes with several possible exciting extensions.
Sediment Contaminants and Infauna Associated with Recreational Boating Structures in a Multi-Use Marine Park

Multi-use marine parks achieve conservation through spatial management of activities. Zoning of marine parks in New South Wales, Australia, includes high conservation areas and special purpose zones (SPZ) where maritime activities are concentrated. Although such measures geographically constrain anthropogenic impacts, we have limited understanding of potential ecological effects. We assessed sediment communities and contaminants adjacent to boating infrastructure (boat ramps, jetties and a marina) in a SPZ from the Clyde Estuary in Batemans Marine Park. Metal concentrations and fines content were elevated at boating structures compared to reference sites. Species richness was higher at sites with boating structures, where capitellid polychaetes and nematodes dominated the communities. Changes associated with boating structures were localised and did not extend beyond breakwalls or to reference sites outside the SPZ. The study highlights the benefits of appropriate zoning in a multi-use marine park and the potential to minimise stress on pristine areas through the application of spatial management.
Moral Reputation: An Evolutionary and Cognitive Perspective

From an evolutionary point of view, the function of moral behaviour may be to secure a good reputation as a co-operator. The best way to do so may be to obey genuine moral motivations. Still, one's moral reputation maybe something too important to be entrusted just to one's moral sense. A robust concern for one's reputation is likely to have evolved too. Here we explore some of the complex relationships between morality and reputation both from an evolutionary and a cognitive point of view. People may behave morally because they intrinsically value doing so—a genuine moral reason—or in order to gain the approval of others—an instrumental reason. Both moral and reputational concerns are commonly involved in moral behaviour and cannot be pried apart without understanding their intricate relationships. Here we aim at contributing to such an understanding by investigating the role, content, and mechanisms of moral reputation. 1. Function and Motivation of Moral Behaviour
Functional characterization of a chr13q22.1 pancreatic cancer risk locus reveals long-range interaction and allele-specific effects on DIS3 expression.

Genome-wide association studies (GWAS) have identified multiple common susceptibility loci for pancreatic cancer. Here we report fine-mapping and functional analysis of one such locus residing in a 610 kb gene desert on chr13q22.1 (marked by rs9543325). The closest candidate genes, KLF5, KLF12, PIBF1, DIS3 and BORA, range in distance from 265-586 kb. Sequencing three sub-regions containing the top ranked SNPs by imputation P-value revealed a 30 bp insertion/deletion (indel) variant that was significantly associated with pancreatic cancer risk (rs386772267, P = 2.30 × 10-11, OR = 1.22, 95% CI 1.15-1.28) and highly correlated to rs9543325 (r2 = 0.97 in the 1000 Genomes EUR population). This indel was the most significant cis-eQTL variant in a set of 222 histologically normal pancreatic tissue samples (β = 0.26, P = 0.004), with the insertion (risk-increasing) allele associated with reduced DIS3 expression. DIS3 encodes a catalytic subunit of the nuclear RNA exosome complex that mediates RNA processing and decay, and is mutated in several cancers. Chromosome conformation capture revealed a long range (570 kb) physical interaction between a sub-region of the risk locus, containing rs386772267, and a region ∼6 kb upstream of DIS3 Finally, repressor regulatory activity and allele-specific protein binding by transcription factors of the TCF/LEF family were observed for the risk-increasing allele of rs386772267, indicating that expression regulation at this risk locus may be influenced by the Wnt signaling pathway. In conclusion, we have identified a putative functional indel variant at chr13q22.1 that associates with decreased DIS3 expression in carriers of pancreatic cancer risk-increasing alleles, and could therefore affect nuclear RNA processing and/or decay.
Lack of effect of dietary conjugated linoleic acids naturally incorporated into butter on the lipid profile and body composition of overweight and obese men.

BACKGROUND Dietary conjugated linoleic acid (CLA) is known to reduce atherosclerosis, plasma total and LDL-cholesterol concentrations, and body fat accumulation in several animal species. Of the few studies that investigated the effects of CLA supplementation in humans, all used commercially formulated oral supplements made from a mixture of CLA isomers. OBJECTIVE We compared the effects on plasma lipoproteins and body composition of the consumption of a modified butter naturally enriched with CLA (CLA-B: 4.22 g CLA/100 g butter fat) by the addition of sunflower oil to the diet of dairy cows with the consumption of a control butter (CON-B) that was low in CLA (0.38 g CLA/100 g butter fat). DESIGN In a crossover design study including an 8-wk washout period, 16 men [x +/- SD age: 36.6 +/- 12.4 y; body mass index (in kg/m2): 31.2 +/- 4.4] were fed each of the 2 experimental isoenergetic diets, providing 15% of energy as protein, 45% as carbohydrates, and 40% as lipids, of which >60% was derived from experimental fats, for 4 wk. RESULTS Consumption of the CLA-B diet induced a significantly (P < 0.05) smaller reduction in plasma total cholesterol and in the ratio of total to HDL cholesterol (-0.02 mmol/L and -0.00, respectively) than did consumption of the CON-B diet (-0.26 mmol/L and-0.34, respectively). Abdominal adipose tissue area measured by computed tomography showed no difference in accumulation of either visceral or subcutaneous adipose tissue after the 2 experimental diets. CONCLUSION These results suggest that a 10-fold CLA enrichment of butter fat does not induce beneficial metabolic effects in overweight or obese men.
Quality of Care for Work-Associated Carpal Tunnel Syndrome

Objective: To evaluate the quality of care provided to individuals with workers’ compensation claims related to Carpal tunnel syndrome (CTS) and identify patient characteristics associated with receiving better care. Methods: We recruited subjects with new claims for CTS from 30 occupational clinics affiliated with Kaiser Permanente Northern California. We applied 45 process-oriented quality measures to 477 subjects’ medical records, and performed multivariate logistic regression to identify patient characteristics associated with quality. Results: Overall, 81.6% of care adhered to recommended standards. Certain tasks related to assessing and managing activity were underused. Patients with classic/probable Katz diagrams, positive electrodiagnostic tests, and higher incomes received better care. However, age, sex, and race/ethnicity were not associated with quality. Conclusions: Care processes for work-associated CTS frequently adhered to quality measures. Clinical factors were more strongly associated with quality than demographic and socioeconomic ones.
A QoS Optimization Approach in Cognitive Body Area Networks for Healthcare Applications

Wireless body area networks are increasingly featuring cognitive capabilities. This work deals with the emerging concept of cognitive body area networks. In particular, the paper addresses two important issues, namely spectrum sharing and interferences. We propose methods for channel and power allocation. The former builds upon a reinforcement learning mechanism, whereas the latter is based on convex optimization. Furthermore, we also propose a mathematical channel model for off-body communication links in line with the IEEE 802.15. 6 standard. Simulation results for a nursing home scenario show that the proposed approach yields the best performance in terms of throughput and QoS for dynamic environments. For example, in a highly demanding scenario our approach can provide throughput up to 7 Mbps, while giving an average of 97.2% of time QoS satisfaction in terms of throughput. Simulation results also show that the power optimization algorithm enables reducing transmission power by approximately 4.5 dBm, thereby sensibly and significantly reducing interference.
FPGA based offline 3D UAV local path planner using evolutionary algorithms for unknown environments

This paper presents an FPGA based synthesizable offline UAV local path planner implementation using Evolutionary Algorithms for 3D unknown environments. A Genetic Algorithm is selected as the path planning algorithm and all units of it are executed on a single FPGA board. In this study, Nexys 4 Artix-7 FPGA board is selected as the target device and Xilinx Vivado 2015.4 software is used for synthesis and analysis of HDL design. Local path planner is designed in a way that it has two flight modes: free elevation flight mode and fixed elevation flight mode. Designed FPGA based local path planner which has 74 MHz operating frequency and 62% logic slice utilization is tested into two different unknown environments generated by a LIDAR sensor. Results show that both GAs are efficient path planning algorithms for UAV applications and FPGAs are very suitable platforms for flight planning periphery.
The Effect of Speech Repetition Rate on Neural Activation in Healthy Adults: Implications for Treatment of Aphasia and Other Fluency Disorders

Functional imaging studies have provided insight into the effect of rate on production of syllables, pseudowords, and naturalistic speech, but the influence of rate on repetition of commonly-used words/phrases suitable for therapeutic use merits closer examination. Aim: To identify speech-motor regions responsive to rate and test the hypothesis that those regions would provide greater support as rates increase, we used an overt speech repetition task and functional magnetic resonance imaging (fMRI) to capture rate-modulated activation within speech-motor regions and determine whether modulations occur linearly and/or show hemispheric preference. Methods: Twelve healthy, right-handed adults participated in an fMRI task requiring overt repetition of commonly-used words/phrases at rates of 1, 2, and 3 syllables/second (syll./sec.). Results: Across all rates, bilateral activation was found both in ventral portions of primary sensorimotor cortex and middle and superior temporal regions. A repeated measures analysis of variance with pairwise comparisons revealed an overall difference between rates in temporal lobe regions of interest (ROIs) bilaterally (p < 0.001); all six comparisons reached significance (p < 0.05). Five of the six were highly significant (p < 0.008), while the left-hemisphere 2- vs. 3-syll. /sec. comparison, though still significant, was less robust (p = 0.037). Temporal ROI mean beta-values increased linearly across the three rates bilaterally. Significant rate effects observed in the temporal lobes were slightly more pronounced in the right-hemisphere. No significant overall rate differences were seen in sensorimotor ROIs, nor was there a clear hemispheric effect. Conclusion: Linear effects in superior temporal ROIs suggest that sensory feedback corresponds directly to task demands. The lesser degree of significance in left-hemisphere activation at the faster, closer-to-normal rate may represent an increase in neural efficiency (and therefore, decreased demand) when the task so closely approximates a highly-practiced function. The presence of significant bilateral activation during overt repetition of words/phrases at all three rates suggests that repetition-based speech production may draw support from either or both hemispheres. This bihemispheric redundancy in regions associated with speech-motor control and their sensitivity to changes in rate may play an important role in interventions for nonfluent aphasia and other fluency disorders, particularly when right-hemisphere structures are the sole remaining pathway for production of meaningful speech.
3D perceptual shape feature-based body parts classification and pose estimation

Human body motion and gesture analysis has been boosted by the latest developments of 3D cameras and the high demands of emerging applications. Body parts classification and pose estimation are essential for the human body tracking and motion recognition. In this poster, we present a 3D perceptual shape feature-based approach for efficient body parts classification and pose estimation. The contribution of this work is twofold: 1) by utilizing 3D image features and kinematic constraints, the classification task can be efficiently performed without huge training data and costly learning process; 2) by applying the classification results, complexity of body pose estimation can be significantly reduced. Experimental results demonstrate the system performance, and exhibit the potential for complex body pose estimation and tracking.
Association of rs2279744 and rs117039649 promoter polymorphism with the risk of gynecological cancer

Background: Increasing evidence has suggested that rs2279744 is associated with rs117039649 polymorphism, which can increase the risk of gynecological cancers, including cervical, ovarian, breast, and endometrial cancer. The results are inconsistent so that we performed a meta-analysis of current literature to clarify the impacts of these polymorphisms on gynecological cancer. Methods: Eligible articles were identified through an exhaustive search of relevant databases including PubMed, Embase, Web of science, Springer Link, Chinese National Knowledge Infrastructure (CNKI), and Weipu database for the period up to July 2016. Data about the association between single nucleotide polymorphisms (SNPs) and cancer risk were refined from the selected articles as well as other information about cases and controls, and all of them were extracted by 2 independent researchers and pooled odds ratio with 95% confidence interval was calculated. Results: This analysis included 24 articles, 27 case–control studies of rs2279744 polymorphism and 3 case–control studies of rs117039649 polymorphism. Significant association with the risk of gynecological cancer was observed for both SNPs. Subgroup analysis by ethnicity and cancer type (cervical, ovarian, breast, and endometrial) also showed a positive relationship between rs2279744 polymorphism and gynecological cancer risk in Caucasian; and there was also a notable association between rs2279744 polymorphism and cervical cancer. Conclusions: We found that rs2279744 (SNP309) and rs117039649 (SNP285) were both associated with the risk of gynecological cancers. Subgroup analysis showed that rs2279744 (SNP309) was associated with the risk of gynecological cancers in Caucasian and Asian according to the ethnicity and cancer type, especially for endometrial cancer.
A novel mouse model with impaired dynein / dynactin function develops amyotrophic lateral sclerosis ( ALS )-like features in motor neurons and improves lifespan in SOD 1-ALS mice

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative condition characterized by progressive motor neuron degeneration and muscle paralysis. Genetic evidence from man and mouse has indicated that mutations in the dynein/dynactin motor complex are correlated with motor neuron degeneration. In this study, we have generated transgenic mice with neuron-specific expression of Bicaudal D2 N-terminus (BICD2-N) to chronically impair dynein/dynactin function. Motor neurons expressing BICD2-N showed accumulation of dynein and dynactin in the cell body, Golgi fragmentation and several signs of impaired retrograde trafficking: the appearance of giant neurofilament swellings in the proximal axon, reduced retrograde labelling by tracer injected in the muscle and delayed expression of the injury transcription factor ATF3 after axon transection. Despite these abnormalities, BICD2-N mice did not develop signs of motor neuron degeneration and motor abnormalities. Interestingly, the BICD2-N transgene increased lifespan in ‘low copy’ SOD1G93A ALS transgenic mice. Our findings indicate that impaired dynein/dynactin function can explain several pathological features observed in ALS patients, but may be beneficial in some forms of ALS.
Effect of local anaesthetic volume (20 vs 5 ml) on the efficacy and respiratory consequences of ultrasound-guided interscalene brachial plexus block.

BACKGROUND Interscalene brachial plexus block (ISBPB) is an effective nerve block for shoulder surgery. However, a 100% incidence of phrenic nerve palsy limits the application of ISBPB for patients with limited pulmonary reserve. We examined the incidence of phrenic nerve palsy with a low-volume ISBPB compared with a standard-volume technique both guided by ultrasound. METHODS Forty patients undergoing shoulder surgery were randomized to receive an ultrasound-guided ISBPB of either 5 or 20 ml ropivacaine 0.5%. General anaesthesia was standardized. Both groups were assessed for respiratory function by sonographic diaphragmatic assessment and spirometry before and after receiving ISBPB, and after surgery. Motor and sensory block, pain, sleep quality, and analgesic consumption were additional outcomes. Statistical comparison of continuous variables was analysed using one-way analysis of variance and Student's t-test. Non-continuous variables were analysed using chi(2) tests. Statistical significance was assumed at P<0.05. RESULTS The incidence of diaphragmatic paralysis was significantly lower in the low-volume group compared with the standard-volume group (45% vs 100%). Reduction in forced expiratory volume in 1 s, forced vital capacity, and peak expiratory flow at 30 min after the block was also significantly less in the low-volume group. In addition, there was a significantly greater decrease in postoperative oxygen saturation in the standard-volume group (-5.85 vs -1.50, P=0.004) after surgery. There were no significant differences in pain scores, sleep quality, and total morphine consumption up to 24 h after surgery. CONCLUSIONS The use of low-volume ultrasound-guided ISBPB is associated with fewer respiratory and other complications with no change in postoperative analgesia compared with the standard-volume technique.