Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel algorithm for estimation of Twitter users location using public available information

Abstract Social media networks are an attractive and hot research area in the big data community because of their numerous active users. One of the most widely studied topics in social networks is the prediction from the public available data. Recently, researchers have successfully predicted many statistical and human properties from social media networks using different machine learning algorithms. In this paper, a new efficient and accurate algorithm is proposed to predict the country location of a Twitter user using his or her public information only. The proposed algorithm employs the public information of the Twitter user and that of his or her followers and friends to predict his or her location without using GPS data. A convenient data set of Twitter users is gathered and used to test our proposed algorithm using KNIME software. The proposed algorithm is compared with other state-of-the-art algorithms, and results showed that our proposed algorithm significantly outperforms other location detection algorithms by using Twitter users from different countries.
Ecohydraulics needs to embrace ecology and sound science, and to avoid mathematical artefacts

We respond to comments on our review of the role of ecology in much of the ecohydraulics literature. Unfortunately, the commentators have attempted largely to defend the status quo without addressing the identified ecological weaknesses, and they have fallen into some philosophical and logical traps that commonly occur when researchers carry out multiple statistical tests. We maintain that many researchers routinely make incorrect assumptions about abundance–environment relationships, with the consequence that many inferences, predictions, models and management tools based on these relationships are logically flawed. The commentators' attempts to dismiss suggestions of potentially fruitful areas of research in ecohydraulics are specious and out of step with the current literature. Copyright © 2010 John Wiley & Sons, Ltd.
Reducing spruce beetle Dendroctonus rufipennis (Kirby) (Coleoptera: Curculionidae) emergence for hibernation in central British Columbia by felling infested trees

Sanitation harvesting for the removal, processing and killing of spruce beetle in infested trees the year after attack is often only partially effective because a significant percentage of beetles emerge from standing trees in the autumn and drop down to the root collar to hibernate under the bark below the duff line. When trees are harvested, these beetles are left behind in stump root collars. We hypothesized that falling of spruce beetle‐infested standing trees, in the second summer (before pre‐hibernation emergence of beetles), can increase the window of opportunity for sanitation harvesting and extract more beetles from the forest. Thirty Engelmann spruce that had been successfully infested by spruce beetle on a 2‐year life cycle in 1995 were selected at each of two locations in the central interior of British Columbia in 1996. At each site, 10 replicates of three treatments were randomly applied. Ten spruce were felled from 29 May to 10 June (early treatment), 10 were felled on 8 August (late treatment) and the remaining 10 were left standing. In mid‐August, a pair of nylon screening emergence traps were attached to all trees to capture any immature adults emerging for hibernation. Emergence traps and underlying phloem were collected in late September to early October and revealed that 48–62% of immature adults emerged for hibernation from standing trees, whereas significantly fewer (7–17%) emerged from felled trees. We conclude that, if sanitation harvesting of 2‐year cycle spruce beetle‐infested spruce cannot occur until the second winter, pre‐harvest felling of these trees in the second year can reduce emergence for hibernation by 69–88% and allow the extraction of more beetles over a longer period.
Information Entropy and Cross Information Entropy Based Attacking Methods for Complex Networks

The security issue of complex networks has drawn signiﬁcant concerns recently and there exist many papers doing research works on how to improve the attacking eﬃciency. Behaviors of complex networks under intentional attacks guided by degree or betweenness centrality have been extensively studied, however, these attack strategies do not act well for the small-world network or the scale-free network. In this paper, we do research works on how diﬀerent attacking methods aﬀect the characteristics of complex networks. In our simulation tests, we remove nodes in three diﬀerent ways: ranking the information entropy of each node from high to low and deleting nodes according to the order, or ranking the cross information entropy of each node from high to low and deleting nodes according to the order, or deleting nodes randomly. With regard to the complex networks without node capacity, our evaluation criterion is based on the network attack eﬃciency, that is, the relative size of the giant connected subgraph of the network. Our understanding about damage attack may also shed light on eﬃcient solutions to protect real networks against damage attack.
Effect of Intake and Source of Protein on Laying Performance of Seven Strains under Single and Double Cage Housing

Abstract An experiment was conducted to compare the laying house performance of 7 strains of White Leghorns, housed at two different densities (1 and 2 birds per 8″ × 16″ cage) when fed 7 diets differing in protein and energy levels. The test started with 2366 pullets, and lasted for 336 days. Performance criteria were egg production, egg weight, body weight, feed consumption, mortality and egg quality. There were large real differences among strains in all performance traits. Compared to birds housed 1 per cage, those housed 2 in a cage laid 9% fewer eggs per hen housed, suffered 1.5 times as much mortality, gained 130 g. less weight from 20 to 64 weeks of age, consumed 3% more feed and required 8% more feed per unit weight of eggs produced, but eggs did not differ in size, specific gravity, albumin quality, shell shape or blood spots. Shells were slightly whiter at 225 days of age and rougher at 450 days of age in the 2 bird cages. Protein intake was the dietary factor most closely associated with large effects of diet on gains in body weight, egg production, egg size, feed conversion and albumin height. Average daily crude protein intake of 17 g. for the laying year appeared adequate and there were no significant strain differences in dietary effects. Strains differed markedly in voluntary nutrient intakes but not in sensitivity to the range of dietary protein and energy levels investigated. Housing birds at 2 versus 1 bird per cage reduced egg production and feed conversion significantly more at lower protein intake levels; its effects also differed appreciably among genetic stocks for feed consumption, egg weight and body weight but not for net efficiency of feed conversion.
Abaloparatide followed by alendronate in women ≥80 years with osteoporosis: post hoc analysis of ACTIVExtend

Supplemental Digital Content is available in the text Abstract Objective: Fracture risk increases with age, but few studies focus on persons ≥80 years. In the ACTIVE trial, treatment with abaloparatide for 18 months reduced osteoporotic fracture risk and increased bone mineral density. These effects were maintained with 24 months alendronate treatment in ACTIVExtend. We postulated that similar improvements in bone mineral density and safety would be demonstrated in women ≥80 years. Methods: Post hoc analyses of bone mineral density and fracture incidence in women with osteoporosis at high risk of fracture ≥80 years from ACTIVExtend. Results: In total, 56 women aged ≥80 years at ACTIVE baseline entered the ACTIVExtend study; 46 of these completed the study. Mean age was 83.3 years; other baseline characteristics were similar. At the end of ACTIVE, bone mineral density increased at all sites for abaloparatide versus placebo. Bone mineral density increased in parallel in both groups during alendronate therapy (19 to 43 months) in ACTIVExtend. At month 43, mean percent change in bone mineral density from baseline was 17.2% abaloparatide/alendronate versus 8.6% placebo/alendronate (P < 0.0001) at the lumbar spine, 5.3% abaloparatide/alendronate versus 3.0% placebo/alendronate (P = 0.024) at the total hip, and 4.6% abaloparatide/alendronate versus 3.1% placebo/alendronate (P = 0.044) at the femoral neck. Fracture incidence was low and did not differ significantly between groups. Sequential treatment with abaloparatide followed by alendronate was well tolerated; the proportion of participants reporting adverse events was similar between groups. Conclusions: Sequential treatment with abaloparatide followed by alendronate (43 months follow-up) in this small subgroup of ACTIVExtend participants suggests abaloparatide is well tolerated and effective in women aged ≥80 years. Video Summary:http://links.lww. com/MENO/A618.
Marker based estimates of between and within population kinships for the conservation of genetic diversity

Summary In this article coefficients of kinship between and within populations are proposed as a tool to assess genetic diversity for conservation of genetic variation. However, pedigree-based kinships are often not available, especially between populations. A method of estimation of kinship from genetic marker data was applied to simulated data from random breeding populations in order to study the suitability of this method for livestock conservation plans. Average coefficients of kinship between populations can be estimated with low Mean Square Error of Prediction, although a bias will occur from alleles that are alike in state in the founder population. The bias is similar for all populations, so the ranking of populations will not be affected. Possible ways of diminishing this bias are discussed. The estimation of kinships between individuals is imprecise unless the number of marker loci is large (> 200). However, it allows distinction between highly related animals (full sibs, half sibs and equivalent relations) and animals that are not directly related if about 30‐50 polymorphic marker genes are used. The markerbased estimates of kinship coefficients yielded higher correlations than genetic distance measures with pedigree-based kinships and thus to this measure of genetic diversity, although correlations were high overall. The relation between coefficients of kinship and genetic distances are discussed. Kinship-based diversity measures conserve the founder population allele frequencies, whereas genetic distances will conserve populations in which allele frequencies are the most different. Marker-based kinship estimates can be used for the selection of breeds and individuals as contributors to a genetic conservation programme.
Restriction Endonuclease-Based Assays for DNA Detection and Isothermal Exponential Signal Amplification

Application of restriction endonuclease (REase) enzymes for specific detection of nucleic acids provides for high assay specificity, convenience and low cost. A direct restriction assay format is based on the specific enzymatic cleavage of a target–probe hybrid that is accompanied with the release of a molecular marker into the solution, enabling target quantification. This format has the detection limit in nanomolar range. The assay sensitivity is improved drastically to the attomolar level by implementation of exponential signal amplification that is based on a cascade of self-perpetuating restriction endonuclease reactions. The cascade is started by action of an amplification “trigger”. The trigger is immobilized through a target-specific probe. Upon the target probe hybridization followed with specific cleavage, the trigger is released into the reaction solution. The solution is then added to the assay amplification stage, and the free trigger induces cleavage of amplification probes, thus starting the self-perpetuating cascade of REase-catalyzed events. Continuous cleavage of new amplification probes leads to the exponential release of new triggers and rapid exponential signal amplification. The proposed formats exemplify a valid isothermal alternative to qPCR with similar sensitivity achieved at a fraction of the associated costs, time and labor. Advantages and challenges of the approach are discussed.
A Novel Approach to Bacterial Expression and Purification of Myristoylated Forms of Neuronal Calcium Sensor Proteins

N-terminal myristoylation is a common co-and post-translational modification of numerous eukaryotic and viral proteins, which affects their interaction with lipids and partner proteins, thereby modulating various cellular processes. Among those are neuronal calcium sensor (NCS) proteins, mediating transduction of calcium signals in a wide range of regulatory cascades, including reception, neurotransmission, neuronal growth and survival. The details of NCSs functioning are of special interest due to their involvement in the progression of ophthalmological and neurodegenerative diseases and their role in cancer. The well-established procedures for preparation of native-like myristoylated forms of recombinant NCSs via their bacterial co-expression with N-myristoyl transferase from Saccharomyces cerevisiae often yield a mixture of the myristoylated and non-myristoylated forms. Here, we report a novel approach to preparation of several NCSs, including recoverin, GCAP1, GCAP2, neurocalcin δ and NCS-1, ensuring their nearly complete N-myristoylation. The optimized bacterial expression and myristoylation of the NCSs is followed by a set of procedures for separation of their myristoylated and non-myristoylated forms using a combination of hydrophobic interaction chromatography steps. We demonstrate that the refolded and further purified myristoylated NCS-1 maintains its Ca2+-binding ability and stability of tertiary structure. The developed approach is generally suited for preparation of other myristoylated proteins.
Using Smart Bracelets to Assess Heart Rate Among Students During Physical Education Lessons: Feasibility, Reliability, and Validity Study

Background An increasing number of wrist-worn wearables are being examined in the context of health care. However, studies of their use during physical education (PE) lessons remain scarce. Objective We aim to examine the reliability and validity of the Fizzo Smart Bracelet (Fizzo) in measuring heart rate (HR) in the laboratory and during PE lessons. Methods In Study 1, 11 healthy subjects (median age 22.0 years, IQR 3.75 years) twice completed a test that involved running on a treadmill at 6 km/h for 12 minutes and 12 km/h for 5 minutes. During the test, participants wore two Fizzo devices, one each on their left and right wrists, to measure their HR. At the same time, the Polar Team2 Pro (Polar), which is worn on the chest, was used as the standard. In Study 2, we went to 10 schools and measured the HR of 24 students (median age 14.0 years, IQR 2.0 years) during PE lessons. During the PE lessons, each student wore a Polar device on their chest and a Fizzo on their right wrist to measure HR data. At the end of the PE lessons, the students and their teachers completed a questionnaire where they assessed the feasibility of Fizzo. The measurements taken by the left wrist Fizzo and the right wrist Fizzo were compared to estimate reliability, while the Fizzo measurements were compared to the Polar measurements to estimate validity. To measure reliability, intraclass correlation coefficients (ICC), mean difference (MD), standard error of measurement (SEM), and mean absolute percentage errors (MAPE) were used. To measure validity, ICC, limits of agreement (LOA), and MAPE were calculated and Bland-Altman plots were constructed. Percentage values were used to estimate the feasibility of Fizzo. Results The Fizzo showed excellent reliability and validity in the laboratory and moderate validity in a PE lesson setting. In Study 1, reliability was excellent (ICC>0.97; MD<0.7; SEM<0.56; MAPE<1.45%). The validity as determined by comparing the left wrist Fizzo and right wrist Fizzo was excellent (ICC>0.98; MAPE<1.85%). Bland-Altman plots showed a strong correlation between left wrist Fizzo measurements (bias=0.48, LOA=–3.94 to 4.89 beats per minute) and right wrist Fizzo measurements (bias=0.56, LOA=–4.60 to 5.72 beats per minute). In Study 2, the validity of the Fizzo was lower compared to that found in Study 1 but still moderate (ICC>0.70; MAPE<9.0%). The Fizzo showed broader LOA in the Bland-Altman plots during the PE lessons (bias=–2.60, LOA=–38.89 to 33.69 beats per minute). Most participants considered the Fizzo very comfortable and easy to put on. All teachers thought the Fizzo was helpful. Conclusions When participants ran on a treadmill in the laboratory, both left and right wrist Fizzo measurements were accurate. The validity of the Fizzo was lower in PE lessons but still reached a moderate level. The Fizzo is feasible for use during PE lessons.
LC-MS and Spectrophotometric Approaches for Evaluation of Bioactive Compounds from Peru Cocoa By-Products for Commercial Applications

Peru is one of the main areas where there are large cocoa crops with special relevance to the economy of this country. In fact, cocoa is a major, economically important, international crop which has been linked to several benefits, such as anti-allergenic, anti-atherogenic, anti-inflammatory, anti-microbial, anti-oxidant, anti-thrombotic, cardioprotective and vasodilatory properties, relating to its bioactive compound content. However, in cocoa industrial processing, several residues or wastes, which are commonly discarded generating a negative impact on the environment, are produced in large amounts. Some of the cocoa by-products, which go underutilized, could be a good source of bioactive compounds with high utility for the development of innovative products in nutraceutical, medical or pharmaceutical industries. For this reason, the aim of this study is to qualitatively determine the phytochemical composition of husk and bean extracts from different cocoa-growing areas and processes from Peru by high performance liquid chromatography coupled to mass spectrometry. Furthermore, we aim to evaluate their phenolic and flavan-3-ol contents and antioxidant capacities for the purpose of highlighting the potential of cocoa by-products from these cultivars as functional ingredients. In total, 49 chemical compounds were detected in the analyzed extracts. Comparing both husks and beans, bean extracts were characterized by high content in flavonoids whereas husk extracts had a higher content of phenolic acids. The presence of these compounds together with the bioactivity results suggest that these matrices may be further studied for their revaluation in the development of high added-value products in nutraceutical, medical, and pharmaceutical industries.
Predicting personality from patterns of behavior collected with smartphones

Significance Smartphones are sensor-rich computers that can easily be used to collect extensive records of behaviors, posing serious threats to individuals’ privacy. This study examines the extent to which individuals’ personality dimensions (assessed at broad domain and narrow facet levels) can be predicted from six classes of behavior: 1) communication and social behavior, 2) music consumption, 3) app usage, 4) mobility, 5) overall phone activity, and 6) day- and night-time activity, in a large sample. The cross-validated results show which Big Five personality dimensions are predictable and which specific patterns of behavior are indicative of which dimensions, revealing communication and social behavior as most predictive overall. Our results highlight the benefits and dangers posed by the widespread collection of smartphone data. Smartphones enjoy high adoption rates around the globe. Rarely more than an arm’s length away, these sensor-rich devices can easily be repurposed to collect rich and extensive records of their users’ behaviors (e.g., location, communication, media consumption), posing serious threats to individual privacy. Here we examine the extent to which individuals’ Big Five personality dimensions can be predicted on the basis of six different classes of behavioral information collected via sensor and log data harvested from smartphones. Taking a machine-learning approach, we predict personality at broad domain (rmedian = 0.37) and narrow facet levels (rmedian = 0.40) based on behavioral data collected from 624 volunteers over 30 consecutive days (25,347,089 logging events). Our cross-validated results reveal that specific patterns in behaviors in the domains of 1) communication and social behavior, 2) music consumption, 3) app usage, 4) mobility, 5) overall phone activity, and 6) day- and night-time activity are distinctively predictive of the Big Five personality traits. The accuracy of these predictions is similar to that found for predictions based on digital footprints from social media platforms and demonstrates the possibility of obtaining information about individuals’ private traits from behavioral patterns passively collected from their smartphones. Overall, our results point to both the benefits (e.g., in research settings) and dangers (e.g., privacy implications, psychological targeting) presented by the widespread collection and modeling of behavioral data obtained from smartphones.
Simulation of an Autonomous Mobile Robot for LiDAR-Based In-Field Phenotyping and Navigation

The agriculture industry is in need of substantially increasing crop yield to meet growing global demand. Selective breeding programs can accelerate crop improvement but collecting phenotyping data is time- and labor-intensive because of the size of the research fields and the frequency of the work required. Automation could be a promising tool to address this phenotyping bottleneck. This paper presents a Robotic Operating System (ROS)-based mobile field robot that simultaneously navigates through occluded crop rows and performs various phenotyping tasks, such as measuring plant volume and canopy height using a 2D LiDAR in a nodding configuration. The efficacy of the proposed 2D LiDAR configuration for phenotyping is assessed in a high-fidelity simulated agricultural environment in the Gazebo simulator with an ROS-based control framework and compared with standard LiDAR configurations used in agriculture. Using the proposed nodding LiDAR configuration, a strategy for navigation through occluded crop rows is presented. The proposed LiDAR configuration achieved an estimation error of 6.6% and 4% for plot volume and canopy height, respectively, which was comparable to the commonly used LiDAR configurations. The hybrid strategy with GPS waypoint following and LiDAR-based navigation was used to navigate the robot through an agricultural crop field successfully with an root mean squared error of 0.0778 m which was 0.2% of the total traveled distance. The presented robot simulation framework in ROS and optimized LiDAR configuration helped to expedite the development of the agricultural robots, which ultimately will aid in overcoming the phenotyping bottleneck.