Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Fitness and Performance of Diving using Machine Learning Algorithms

Various batteries of fitness tests are conducted to assess the fitness of divers. Testing and monitoring are conducted for the selection of divers based on their current fitness for future competitions. There is a paucity of data and knowledge of which fitness tests can be effective to predict fitness, performance, and selection of potential divers at national and international level competitions. Classical statistical methods could not identify the magnitude of the variable importance. Hence tree-based classifier Boruta algorithm was used to identify the most important features of the diving performance. Out of 19 variables, vertical jump, standing broad jump, sit & reach, shoulder flexibility, agility, pull-ups, maximum push-ups, maximum wall bar, handstand balance, age, height, and weight were more than 90% important for the diving performance. VO2max and static balance were 69% important while hyperextension and bridge flexibility were about 52% important. The ordinal forest and multi-ordinal logistic regression machine learning algorithms were used to develop models for predicting diving performance at national and international competitions. The diagnostic analysis was conducted to validate the model performances using unseen data. The predictive accuracy by multi-ordinal logistic regression with 6 variables was 52.1% (95% CI: 39.92%, 64.12%), which was poor as compared to the ordinal forest. Overall accuracy of the final ordinal forest, was 70.4% (95% confidence interval: 58.41%, 80.67%). The balanced accuracy was 68.5% and 82.8% for predicting the national and international performances respectively. Hence the ordinal forest is better for selecting high potential divers objectively at international competitions.
Virgin females compete for mates in the male lekking species Ceratitis capitata

Abstract. Aggressive behaviour occurring in intrasexual competition is an important trait for animal fitness. Although female intrasexual aggression is reported in several insect species, little is known about female competition and aggressive interactions in polygynous male lekking species. The interactions of female Mediterranean fruit flies, Ceratitis capitata (a male lekking species), with other females and mating pairs under laboratory conditions are investigated. Mature, unmated (virgin) females are aggressive against each other and against mating pairs, whereas immature females are not. Female aggression against other females decreases dramatically after mating; however, mated females maintain aggression against mating pairs. In addition, higher intrasexual aggression rates are observed for mature, virgin females than for virgin males of the same age. The results show that female aggressiveness is virginity related, suggesting female competition for mates. These findings have important implications for understanding the physiological aspects of a complex social behaviour such as aggression and should stimulate further research on female agonistic behaviour in male lekking mating systems.
Classification of Soybean Cultivars Based on Mitochondrial DNA Restriction Fragment Length Polymorphisms

Mitochondrial DNA restriction fragment length polymorphisms (RFLPs) are convenient markers for identifying cytoplasmic variation among plant cultivars. We have undertaken a systematic study to classify soybean [Glycine max (L.) Merr. ] germplasm into cytoplasmic groups based on RFLPs for several mitochondrial genes. This analysis substantially increases the total number of cultivars that have been examined for cytoplasmic diversity and includes many of the maternal ancestors of currently grown cultivars. It also allows comparison with studies involving chloroplast diversity in soybean(.)
Absolute and relative reliability of pain sensitivity and functional outcomes of the affected shoulder among women with pain after breast cancer treatment

Objective Breast cancer survivors (BCS) are often characterized by decreased pressure pain thresholds (PPT), range of motion (ROM) and strength in and around the shoulder affected by the treatment. This intra-rater reliability study was to establish the relative and absolute reliability of PPT’s, active ROM and maximal isokinetic muscle strength (MIMS) of the affected shoulder in BCS with persistent pain after treatment. Methods Twenty-one BCS participated in the study. The PPTs of 17 locations and pain intensity were assessed using a pressure algometer and a numeric rating scale. The ROM was measured using a universal goniometer and MIMS was measured using an isokinetic dynamometer. Relative reliability was estimated using intra class correlation coefficient (ICC), and absolute reliability using standard error of measurement (SEM). Minimum detectable change (MDC) was calculated from SEM. Results The ICCs for PPTs ranged from 0.88–0.97, with SEM values ranging from 12.0 to 28.2 kPa and MDC ranging from 33.2 to 78.2 kPa. The ICCs for ROM ranged from 0.66–0.97, with SEM values ranging from 3.0 to 7.5° and MDC ranging from 8.4 to 20.8°. Finally, ICCs for MIMS ranged from 0.62–0.92, with SEM values ranging from 0.03 to 0.07 Nm/Kg FFM and MDC ranging from 0.09 to 0.19 Nm/kg FFM. Conclusion The results of this study indicate that PPTs, ROM and MIMS can be measured reliably on the affected shoulder in BCS with pain after treatment. This offer the possibility of using these measures to assess the effectiveness of interventions in this population.
Stochastic Analysis of Benue River Flow Using Moving Average (Ma) Model

-Stochastic analysis is an established method of generating data,this was used to analyze 31 years of average monthly stream flowsof Benue River, the popular model known as Moving average ( MA) was fitted to the data . The Parametersfor the model was estimated accompanied bydiagnostic checks, which showed the model fitness to the dataadequately, also the histogram of the residuals revealed that themodel assumption was correct (i.e. residualsare normally distributed), this was further tested by forecasting of10 years of stream flows at 95% confidence. The resultsdemonstrated the usefulness of the method in generatingadditional data in watersheds where there is paucity of time series data.
Characterization and Therapeutic Effect of a pH Stimuli Responsive Polymeric Nanoformulation for Controlled Drug Release

Despite the large number of polymeric nanodelivery systems that have been recently developed, there is still room for improvement in terms of therapeutic efficiency. Most reported nanodevices for controlled release are based on drug encapsulation, which can lead to undesired drug leakage with a consequent reduction in efficacy and an increase in systemic toxicity. Herein, we present a strategy for covalent drug conjugation to the nanodevice to overcome this drawback. In particular, we characterize and evaluate an effective therapeutic polymeric PEGylated nanosystem for controlled pH-sensitive drug release on a breast cancer (MDA-MB-231) and two lung cancer (A549 and H520) cell lines. A significant reduction in the required drug dose to reach its half maximal inhibitory concentration (IC50 value) was achieved by conjugation of the drug to the nanoparticles, which leads to an improvement in the therapeutic index by increasing the efficiency. The genotoxic effect of this nanodevice in cancer cells was confirmed by nucleus histone H2AX specific immunostaining. In summary, we successfully characterized and validated a pH responsive therapeutic polymeric nanodevice in vitro for controlled anticancer drug release.
Ecological factors influencing the spatial pattern of Canada lynx relative to its southern range edge in Alberta, Canada

We examined the spatial pattern of Canada lynx (Lynx canadensis Kerr, 1792) relative to its southern range edge at the boreal plains – prairie ecotone in Alberta, Canada. Relative to the original distribution of boreal forest in our study area, lynx range seems to have contracted up to 22%. In 100 km2 sampling areas, lynx occupancy rate increased 1.93 times every 100 km farther (north) from the range edge that we sampled. An information–theoretic approach was used to evaluate 31 models to see which environmental factors were the best predictors of this spatial pattern. Lynx were strongly correlated with track counts of their primary prey, the snowshoe hare (Lepus americanus Erxleben, 1777), but this did not explain the observed increase in occupancy farther north. Rather, lynx occupancy was lower in areas with higher road densities and this effect was magnified in areas where coyote (Canis latrans Say, 1823) activity was highest. The inclusion of these effects rendered the south–north pattern no longer si.
Automatic hoof-on and -off detection in horses using hoof-mounted inertial measurement unit sensors

For gait classification, hoof-on and hoof-off events are fundamental locomotion characteristics of interest. These events can be measured with inertial measurement units (IMUs) which measure the acceleration and angular velocity in three directions. The aim of this study was to present two algorithms for automatic detection of hoof-events from the acceleration and angular velocity signals measured by hoof-mounted IMUs in walk and trot on a hard surface. Seven Warmblood horses were equipped with two wireless IMUs, which were attached to the lateral wall of the right front (RF) and hind (RH) hooves. Horses were walked and trotted on a lead over a force plate for internal validation. The agreement between the algorithms for the acceleration and angular velocity signals with the force plate was evaluated by Bland Altman analysis and linear mixed model analysis. These analyses were performed for both hoof-on and hoof-off detection and for both algorithms separately. For the hoof-on detection, the angular velocity algorithm was the most accurate with an accuracy between 2.39 and 12.22 ms and a precision of around 13.80 ms, depending on gait and hoof. For hoof-off detection, the acceleration algorithm was the most accurate with an accuracy of 3.20 ms and precision of 6.39 ms, independent of gait and hoof. These algorithms look highly promising for gait classification purposes although the applicability of these algorithms should be investigated under different circumstances, such as different surfaces and different hoof trimming conditions.
Area and Energy Efficient Approximate Square Rooters for Error Resilient Applications

Approximate Computing is gaining momentum for design of accuracy-energy configurable circuits for error-tolerant applications. In this paper, a low power reduced area square root (SQR) circuit is presented that achieves remarkable area and energy efficiency, while introducing trivial inaccuracies in the results. Two approximate designs are proposed for restoring array based square-root circuit for error-resilient applications. In the first design, approximate restoring subtractor cells are used to substitute exact SQR subtractor cells by simplifying the boolean expressions. The second design reduces the design complexity and increases energy efficiency by using the classic approximate computing technique of bit-truncation. Both the designs are implemented for 8- and 16-bit square-root circuit design with different values of approximation parameter ‘d’ for achieving various design trade-off points. Our results indicate that the proposed approximated SQR designs show an improvement in terms of delay, power consumption, energy and area and improves these parameters on average by 37%, 24%, 18%, and 44%, respectively for 16-bit SQR designs when implemented on CMOS 45-nm technology node without compromising much on accuracy. Also, the proposed approximate designs are tested on error tolerant applications including contrast enhancement for medical images and envelope detection in AM (Amplitude Modulation) communication systems. Furthermore, our results validate the approximate square-root designs with improvement in Contrast to Noise ratio (CNR) for image processing applications and an acceptable Signal to Noise ratio (SNR) for analog communication system.
Can inspiratory muscle training benefit patients after stroke? A systematic review and meta-analysis of randomized controlled trials

Objectives: The aim of this study was to investigate the effects of inspiratory muscle training in post-stroke patients and to explore the effective training protocol. Data sources: PubMed/Medline, Web of Science, Scopus, Embase, Cochrane database, China National Knowledge Infrastructure, and China Science Periodical Database were searched through April 2020. Review methods: Trials examining effects of inspiratory muscle training on pulmonary function, cardiopulmonary endurance, pulmonary infection incidence, and quality of life in post-stroke patients were included. Subgroup analysis was performed to compare different training programs. Mean differences and risk ratios with 95% confidence intervals were presented. Risk of bias was assessed with the Cochrane tool. Results: Thirteen randomized controlled trials involving a total of 373 participants were identified. Meta-analysis conducted in 8 out of 13 trials revealed evidence for beneficial effects of inspiratory muscle training on forced vital capacity (MD: 0.47, 95% CI: 0.28–0.66), forced expired volume in 1 second (MD: 0.26, 95% CI: 0.18–0.35), 6-minute walk test (MD: 52.61, 95% CI: 25.22–80.01), maximum inspiratory pressure (MD: 18.18, 95% CI: 5.58–30.78), inspiratory muscle endurance (MD: 19.99, 95% CI: 13.58–26.40), and pulmonary infection incidence (RR: 0.11, 95% CI: 0.03–0.40). Omitting individual trials from the meta-analysis did not significantly change the results. The effective inspiratory muscle training protocol was suggested by subgroup analysis with three repetitions per week and more than 20 minutes per day for three weeks. Conclusion: Inspiratory muscle training can be considered as an effective intervention for improving pulmonary function and cardiopulmonary endurance, and reducing pulmonary infection incidence in patients after stroke.
Contribution of fungi and bacteria to the formation of dissolved organic carbon from decaying common reed (Phragmites australis)

Bacteria and fungi dominate the decomposition of aquatic plants, a major process in the carbon and nutrient cycling in many aquatic systems. Although phylogenetically distant, bacteria and fungi often live in close proximity with each other. Since these microorganisms also have similar ecological functions, interactions have developed between them. This thesis explores the nature of such interactions, and the potential effects on key components of the decomposition process. The thesis includes a critical assessment of the ergosterol method for determination of fungal biomass, a survey of the environmental factors determining the distribution and taxa numbers of litter-decomposing bacteria and fungi in lakes, and a number of experiments on the interactions between bacteria and fungi. In all the experiments performed, fungi responded to bacterial presence through antagonism, although different fungal strains, bacterial communities and substrates were used. The antagonism seemed to be caused by interference competition for substrate. The fungal effect on bacteria was less consistent. Bacterial growth was suppressed, unaffected, or even enhanced by the presence of fungi. Fungi contributed more to extracellular enzyme production than bacteria, and bacteria were probably able to assimilate intermediate decomposition products formed through the activity of extracellular enzymes of fungal origin. Thus, the effect on bacteria from interacting with fungi was determined by the balance between competition and benefit from excreted enzymes. Bacteria and fungi also used different size fractions of the organic matter, according to their different enzymatic capacities. Hence, bacteria appeared to assimilate low-molecular-weight compounds, while high-molecular-weight compounds were utilized primarily by fungi. In brief, the ecological interactions influenced the growth and hence also the biomass development of bacteria and fungi, which affected enzyme activity as well as utilization of dissolved organic matter. Therefore, I suggest that interactions between bacteria and fungi influence degradation of plant litter in aquatic systems.
Truncated mutants of beta-glucosidase 2 (GBA2) are localized in the mitochondrial matrix and cause mitochondrial fragmentation

The enzyme β-glucosidase 2 (GBA2) is clinically relevant because it is targeted by the drug miglustat (Zavesca®) and because it is involved in inherited diseases. Mutations in the GBA2 gene are associated with two neurological diseases on the ataxia-spasticity spectrum, hereditary spastic paraplegia 46 (SPG46) and Marinesco-Sjögren-like syndrome (MSS). To establish how GBA2 mutations give rise to neurological pathology, we have begun to investigate mutant forms of GBA2 encoded by disease-associated GBA2 alleles. Previously, we found that five GBA2 missense mutants and five C-terminally truncated mutants lacked enzyme activity. Here we have examined the cellular locations of wild-type (WT) and mutant forms of GBA2 by confocal and electron microscopy, using transfected cells. Similar to GBA2-WT, the D594H and M510Vfs*17 GBA2 mutants were located at the plasma membrane, whereas the C-terminally truncated mutants terminating after amino acids 233 and 339 (GBA2-233 and -339) were present in the mitochondrial matrix, induced mitochondrial fragmentation and loss of mitochondrial transmembrane potential. Deletional mutagenesis indicated that residues 161–200 are critical for the mitochondrial fragmentation of GBA2-233 and -339. Considering that the mitochondrial fragmentation induced by GBA2-233 and -339 is consistently accompanied by their localization to the mitochondrial matrix, our deletional analysis raises the possibility that that GBA2 residues 161–200 harbor an internal targeting sequence for transport to the mitochondrial matrix. Altogether, our work provides new insights into the behaviour of GBA2-WT and disease-associated forms of GBA2.
Intracellular X‐prolyl dipeptidyl peptidase from Lactococcus lactis spp. lactis: purification and properties

An X-prolyl dipeptidyl peptidase (EC 3.4.14.5) has been purified from a crude intracellular extract from Lactococcus lactis spp. lactis NCDO 763 by ion-exchange chromatography and gel filtration. One protein band was detected after electrophoresis of the purified enzyme in the presence or absence of sodium dodecyl sulphate. The enzyme is a 190 kDa dimer composed of identical subunits. Optimal activity occurs at pH 8.5 and 40–45°C and the enzyme is inhibited by reagents specific for serine proteases, such as diisopropylfluorophosphate. The enzyme hydrolyzes p-nitroanilide- or β-naphthylamide-substituted X-Pro dipeptides, as well as β-casomorphin.
TRANSITIONAL MORPHOLOGY IN HYBRIDS OF HIRUDO VERBANA AND H. ORIENTALIS (CLITELLATA, HIRUDINIDA)

Abstract The aim of this research was to test the ability of hybridizing Hirudo orientalis S. Utevsky et Trontelj, 2005 and Hirudo verbana Carena, 1820. We obtained offspring from both species. The color pattern of all the hybrids was uniform and quite different from both the parents. The venter was similar to H. verbana. The dorsum was very similar to the color pattern of Hirudo medicinalis Linnaeus, 1758 that was not involved to the experiment. The coloration pattern of the hybrids, which is very similar to that of H. medicinalis suggests the hybrid origin of this species.
Data Mining Algorithms for Traffic Interruption Detection

Detection of traffic interruptions (caused by vehicular breakdowns, road accidents etc.) is a critical aspect of managing traffic on urban road networks. This work outlines a semi-supervised strategy to automatically detect traffic interruptions occurring on arteries in urban road networks using high resolution data from widely deployed fixed point sensors (inductive loop detectors). The techniques highlighted in this paper are tested on data collected from detectors installed on more than 300 signalized intersections.
Computational Modeling for Surgical Reconstruction of Aortic Valve by Using Autologous Pericardium

The objective of this study was to evaluate the clinical effectiveness of surgical reconstruction of aortic valve using autologous pericardium, and the hemodynamic impact of matching the circumferential direction of the trimmed leaflet to inherent fiber orientation of the pericardium during surgery. A patient specific aortic valve model was built based on CTA data. The reconstructive surgery was carried out on the model following normal operating procedures. FSI simulation was performed to analyze the hemodynamic characteristics among the diseased model, normal model and three operative models with different misaligned angles between the circumferential direction of the substitute and inherent fiber orientation. The differences of EOA, velocity distribution, stress and strain on leaflets, and the valve deformation between the five models were compared and analyzed. The results showed that reconstructive surgery helps enlarge EOA, reduce abnormity of leaflet motion and blood ejection compared to diseased model. There was no significant difference between operative models with different misaligned angles in terms of leaflet motion and flow pattern, but as the misaligned angle increased, greater strain and deformation were observed on leaflets during the diastolic period. The present study demonstrated the instant clinical effectiveness of the reconstructive surgery of aortic valve by the improvement of EOA and flow pattern, and suggested that during the operation it may be unnecessary to match the circumferential direction of the substitute to inherent fiber orientation of the pericardium since the hemodynamic characteristics were insensitive to the fiber alignment, but the strain and deformation increment on the substitutes during diastolic period still raised concern about their durability.
A Method for Analyzing Selection in Hierarchically Structured Populations

Individual fitness depends on the particular ecological, genetic, and social contexts in which organisms are found. Variation in individual context among subunits of a population thus raises interesting questions about selection in nature but also complicates its study. We present a method for analyzing phenotypic selection in hierarchically structured populations. Applying this method, called contextual analysis, to the study of selection allows explicit answers to two frequently controversial questions. First, must group membership be taken into account in explaining differences in individual fitness? Second, what particular group properties are associated with observable group-level effects? Contextual analysis is a generalization to structured populations of the "selection gradient" method developed by Lande and Arnold (1983). The aim of the gradient method is to distinguish characters that have a causal relationship with fitness from others that do not but are still subject to selection as a result of their phenotypic correlations with other traits. This distinction is made using the partial regression coefficients of fitness on the set of characters being investigated. Contextual analysis extends this method to include group as well as individual characters in a multiple-regression analysis of fitness. The partial regression coefficients associated with the group characters estimate the ability of specific group properties to account for variance in individual fitness in excess of what can be accounted for by the phenotypes of the group members themselves. In this way, contextual analysis permits independent group-level effects on fitness to be distinguished from changes in group characters solely as a result of their correlations with individual-level traits. While applicable to a wide range of problems, contextual analysis makes two particular contributions to the study of group selection: it clarifies the much-debated concept of "emergence"; and it provides a powerful analytic tool for studying group selection in nature.