Miracle-dz/UniFAR-FTUs huggingface dataset:
Winge's sex-linked color patterns and SDL in the guppy: genes or gene complexes?

In Poecilia reticulata, different phenotypes appear due to dominance, codominance, poligeny, or some demonstrated interallelic interactions. Recent (both molecular and classical) investigations suggest a mechanism of expression of several different loci in a single color pattern, resulting in high numbers of possible color pattern phenotypes. The color pattern seems to be determined by complex interactions of many genes (at the same locus or not, located on the same chromosome or not), under variable environmental conditions. For example, the Maculatus color pattern is due to the presence of both Maculatus red and Maculatus black elements. On their turn, having in view the latest definitions of the gene, both Maculatus red and Maculatus black could have a composite nature, too. Sexdetermination in the guppy is studied since the 1920s. The deepest mechanism of sex determination is not clear yet, but classical studies of Winge early in the past century and recent molecular studies revealed a possible composite nature of the so called master sex determining gene, located at SDL of the Y chromosome.
Undulating Tongue and Wilson's Disease

We read with interest the letter to the editor reported by Agarwal et al. describing the case of a 10-year-old child diagnosed with Wilson’s disease revealed by an isolated involuntary movement of the tongue, exclusively at protrusion, with a striatal abnormality at brain MRI. Our case is closely similar to it, regarding the movement’s semiology and neuroimaging. However, phenomenology remains difficult to describe. The tongue was animated by slow, sinuous, writhing movements qualified as “undulating. ” An improvement was noted 3 months following copper chelation. One of the particular features of our case was its rapid onset in a few days, which is rare, but well documented in the literature. Dozens of involuntary (rarely isolated) lingual movements were reported in the course of Wilson’s disease. This raises two points to be discussed: the location and the phenomenology of this movement disorder. Buccolingual and laryngeal involvement is, by far, the most common, initial, neurological manifestation of Wilson’s disease. In a somatotopic matter, the tongue is well represented in the corticobulbar motor pathway, which could explain its frequent involvement. However, it is unusual for it to be isolated given that it is probably clinically insignificant or subtle and often “submerged” by other bulbar manifestations, such as dysarthria, dysphagia, drooling, and the sardonic smile, indicating an already spread lesion. The phenomenology of this involuntary movement is difficult to classify in a known category. However, it seems to be dystonic, given its slow, sometimes sustained character, worsening by movements. Its elective appearance at tongue protrusion in Agarwal et al.’s observation supports this hypothesis. This ripple-like appearance is probably linked to the complex function and anatomy of this organ, containing 17 muscles. In Agarwal et al.’s observation, unlike ours, no improvement was observed following 4 months’ anticopper treatment. Later recoveries are common, and it is possibly the case in this observation. Indeed, in our case, lingual movements resolved after 3 months, and it took 12 months to improve the dysarthria. The same findings were reported by Nagappa et al. We are convinced that lingual dyskinesias are a frequent and early manifestation in the course of Wilson’s disease. However, an isolated involuntary tongue movement is generally paucisymptomatic, and its progression toward laryngeal involvement with a clinically significant dysarthria remains the frequently revealing complaint. So, we totally agree with Agarwal et al. that this involuntary movement could represent a clue for an early diagnosis of such a treatable disease. However, we believe that the oral cavity is “the window” that clinicians should probably consider opening, especially in the présence of subtle bulbar symptoms. “If you can’t see through the window, might as well open it. ”
Analysis of Real-World Fuel Consumption Characteristics of Heavy-Duty Commercial Diesel Vehicle Based on OBD Method

In this paper, heavy-duty commercial diesel vehicles were selected for the actual road, vehicle emission test system (PEMS), C-WTVC and CATC test, and each test was connected to the OBD remote monitoring equipment. Through PEMS test and C-WTVC test, the instantaneous fuel consumption data and carbon balance fuel consumption data of OBD remote monitoring equipment are compared within 10%, which proves that OBD remote monitoring has good accuracy. The fuel consumption of the actual road test normalized to CATC is 10.8%-88.0% higher than that of the ministry of industry and information technology type certification, with an average value of 45.1%. The fuel consumption under the normalized C-WTVC condition is 10.1%∼76.6% higher than that under the type approval of the ministry of industry and information technology, with an average value of 40.0% 23.9%. This difference is relatively smaller than that under the normalized to CATC. It is of great significance to correctly guide the development and calibration of vehicles and promote the research and application of vehicle energy conservation and emission reduction technologies suitable for China’s traffic characteristics and actual use characteristics.
Using the multi-theory model of health behavior change to identify correlates of change in substance use behavior in a mental health clinic-based sample

ABSTRACT Background: Substance use is a chronic disorder that requires lifelong multimodal management. This study utilized the Multi-Theory Model (MTM) of Health Behavior Change to identify correlates of change in substance use behavior. Methods: Data were collected, using a cross-sectional design, from 93 participants who completed treatment at a substance use treatment facility. Participants completed a 40-item, newly developed, self-administered questionnaire, grounded on relevant substance use, treatment, and health-related behavior. Cronbach’s alpha of all subscales were over 0.70 and deemed acceptable. Results: The majority of the participants were Caucasian (72.7%). Males comprised 60% of the sample. A stepwise multiple regression predicting initiation and sustenance of intentional substance use cessation showed a total of 34.2% of the variance. The initiation for the intentional substance use cessation was accounted for by participatory dialogue, advantages minus disadvantages (p = .001) and behavioral confidence (p = < 0.001). The sustenance for intentional substance use cessation was accounted for a total of 33% of the variance by practice for change (p = .004) and changes in the social environment (p = < 0.003). Conclusions: The MTM could be a useful model for predicting substance use behavior change. Clinicians and patients can gain insight and discuss behavioral changes necessary for recovery.
Mesophilic and Thermophilic Anaerobic Digestion of Organic Fraction Separated during Mechanical Heat Treatment of Municipal Waste

The objective of this study was to investigate the effect of process temperature on semi-continuous anaerobic digestion of the organic fraction separated during autoclaving of municipal waste. Tests were carried out in reactors with full mixing. Biogas production was higher in thermophilic conditions than in mesophilic conditions (0.92 L/g volatile solids at 55 °C vs. 0.42 L/g volatile solids at 37 °C, respectively). The resulting methane yields were 0.25-0.32 L CH4/g VS and 0.56–0.70 L CH4/g VS in mesophilic and thermophilic conditions, respectively. In both variants, the methane share was over 70% v/v. This work also discusses the potential impact of Maillard compounds on the efficiency of the fermentation process, which were probably produced during the process of autoclaving of municipal waste. These results indicate that, after autoclaving, the organic fraction of municipal waste can be an effective substrate for anaerobic digestion in thermophilic conditions.
Identifying G-protein Coupled Receptors Using Mixed-Feature Extraction Methods and Machine Learning Methods

G-protein-coupled receptors (GPCRs) are important protein molecules in the field of cell signaling and are widely found in various organisms. GPCRs play an important role in a variety of physiological processes and are important drug targets for a variety of diseases. Accurate prediction of GPCRs using machine learning is useful for drug design in a variety of related diseases. In this paper, we propose a method for identifying GPCRs based on mixed-feature vectors. We combine three individual features, such as 400D, N-gram and Parallel correlation pseudo amino acid composition (PC-PseAAC), using mixed-feature representation methods, which are evaluated by Random Forest, Naïve Bayes, and J48 for classification purposes. To measure the performance of this classifier, ten-fold cross-validation is used. Two dimensionality reduction methods—the max-relevance-max-distance (MRMD) and t-Distributed Stochastic Neighbor Embedding (t-SNE)—are applied to reduce the feature dimension. The 400D and PC-PseAAC feature extraction methods are combined, the random forest is used as the classifier, and the area under the curve (AUC) is up to 0.9413. Therefore, among these methods, the new feature vector obtained by combining the two features shows the best performance, and the mixed feature is better than the single feature.
The effects of electoral anticipation on portfolio allocation

Whereas much of the existing literature on coalition formation has focused on the disparity between Gamsonian payoffs and the outcomes of bargaining models, dangers of ministerial drift, party ideal points, issue salience/emphasis, and negotiation complexity, very little has been said on the role of the way public opinion affects political behavior via expectation of future electoral returns. Following the logic of “issue yield,” this article argues that politicians allocate ministerial portfolios according to the distribution of public opinion in the hopes of obtaining better returns in subsequent elections and find compelling evidence linking public opinion with portfolio allocation.
Principles and methods of plant breeding

Shortened Contents: 1. Importance of Plant Breeding. 2. Phytogeographical Differentiation as a Basis of Plant Breeding. 3. Sources of Genetic Variability. 4. Genetic Basis of Breeding Self-Pollinated Plants. 5. Genetic Basis of Breeding Open Pollinated Plants. 6. Trait, Genotype and Phenotype. 7. Methodologies of Plant Breeding. 8. Concept of Development of Cultivars. 9. Selection of Material for Breeding. 10. Importance of Crossing Methods. 11. Number of Cross Combinations and Size of F 2 Population. 12. Methods of Selection. 13. Selection for Traits and Genetic Gain from Selection. 14. Plant Breeding for Resistance to Parasites. 15. Breeding for Yield. 16. Use of Heterosis. 17. Mutations in Plant Breeding. 18. Chromosome Engineering. 19. Genetic Engineering. 20. Breeding Vegetatively Propagated Plants. 21. Genetic Composition and Adaptability of the Cultivar. 22. Genetic Basis of Seed Production and Introduction of Cultivars into Practice. Author index. Subject index. [/cmt]
Genital morphology differentiates three subspecies of the terrestrial slug Arion ater (Linnæus, 1758) s.l. and reveals a continuum of intermediates with the invasive A. vulgaris Moquin-Tandon, 1855

The terrestrial slug Arion vulgaris Moquin-Tandon (= A. lusitanicus auct. non Mabille) is an important agricultural pest that has invaded much of Europe. Previous work has demonstrated hybridisation with A. ater (Linnæus) s.l. We describe the genital anatomy of morphological intermediates found in eastern Saxony (Germany), comparing them with the parent species. We recommend a standard method of genital dissection and consider a set of five genital characters. The intermediates demonstrate the homology of the ligula-bearing organs of the two species; the ancestral position of the ligula in the dilated part of the oviduct has moved to the upper atrium in A. ater s.l. Furthermore we differentiate three morphotypes of A. ater s.l. in eastern Saxony, associated with different mitochondrial DNA sequences. One is A. ater ater, previously unrecognised from this part of Germany and the Czech Republic. The two other morphotypes correspond to the predominantly British and the Continental subspecies previously recognised on genetic and morphological grounds. We designate as the lectotype of Limax rufus Linnæus, 1758 a non-surviving specimen from Almondbury, England, described by Lister; thus the predominantly British subspecies becomes A. ater rufus. The appropriate name for the Continental form is A. ater ruber (Garsault, 1764). key woRd: Arion ater ruber, Arion lusitanicus, Arion rufus, Spanish slug, Pulmonata, Arionidae, COI, hybrid, lectotype, ligula, Martin Lister, pest slug
SAMPLE SIZE PLANNING IN QUANTITATIVE L2 RESEARCH

Abstract Researchers are traditionally advised to plan for their required sample size such that achieving a sufficient level of statistical power is ensured (Cohen, 1988). While this method helps distinguishing statistically significant effects from the nonsignificant ones, it does not help achieving the higher goal of accurately estimating the actual size of those effects in an intended study. Adopting an open-science approach, this article presents an alternative approach, accuracy in effect size estimation (AESE), to sample size planning that ensures that researchers obtain adequately narrow confidence intervals (CI) for their effect sizes of interest thereby ensuring accuracy in estimating the actual size of those effects. Specifically, I (a) compare the underpinnings of power-analytic and AESE methods, (b) provide a practical definition of narrow CIs, (c) apply the AESE method to various research studies from L2 literature, and (d) offer several flexible R programs to implement the methods discussed in this article.
Spatial prediction of landslide susceptibility based on the neighborhood rough set

This paper discusses the feasibility of reducing the landslide inducing factors by the neighborhood rough set algorithm in data processing section, which could improve the accuracy and timeliness of landslides susceptibility prediction models effectively. 15 predisposing factors for a continuous value that has not been graded were reduced by nighborhood rough set, a granularity calculation method, based on the importance degree of each factor. Then the combination of factors before and after optimization was put into random forest (RF) and support vector machine (SVM) for modelling. ROC curve and statistical indicators show that: the average performance of the reduced factors combination is superior to that before optimization. In addition, we used the RF which has a better performs in evaluation to map the landslides susceptibility in Jiuzhaigou area, discuss the timeliness of the assessment of landslides prediction and the weight of the predisposing factors.
Almost a Principal: Coaching and Training Assistant Principals for the Next Level of Leadership

Through this study, we examined a university–district sponsored leadership academy to explore the perceptions of assistant principals, who participated in a yearlong professional development and coaching program, on how the program supported them in improving their leadership capacity and advancing their career. Using a single qualitative case study design, we explored the perceptions of 26 experienced assistant principals in a single school district in Texas. These participants were identified by the district as strong and viable candidates for future principal openings within the district. Data were collected through semistructured interviews, focus groups, and observations of class sessions. We used a leadership development and succession planning conceptual framework to guide our data analysis, focusing on identifying leadership talent, assigning developmental activities, and developing pervasive mentoring relationships. The findings illustrate increased confidence in the participants’ leadership abilities, promising practices in leadership development programming, and the importance of the university–district partnership in supporting experienced assistant principals. Although these findings are not necessarily innovative practices in the field of principal preparation, they are significant for understanding how to create meaningful professional development for mid-career assistant principals who have not transitioned to the role of the principal and for recognizing the critical role university–district partnerships have on leadership development.
The Identification of Alzheimer’s Disease Using Functional Connectivity Between Activity Voxels in Resting-State fMRI Data

Background: Alzheimer’s disease (AD) is a common neurodegenerative disease occurring in the elderly population. The effective and accurate classification of AD symptoms by using functional magnetic resonance imaging (fMRI) has a great significance for the clinical diagnosis and prediction of AD patients. Methods: Therefore, this paper proposes a new method for identifying AD patients from healthy subjects by using functional connectivities (FCs) between the activity voxels in the brain based on fMRI data analysis. Firstly, independent component analysis is used to detect the activity voxels in the fMRI signals of AD patients and healthy subjects; Secondly, the FCs between the common activity voxels of the two groups are calculated, and then the FCs with significant differences are further identified by statistical analysis between them; Finally, the classification of AD patients from healthy subjects is realized by using FCs with significant differences as the feature samples in support vector machine. Results: The results show that the proposed identification method can obtain higher classification accuracy, and the FCs between activity voxels within prefrontal lobe as well as those between prefrontal and parietal lobes play an important role in the prediction of AD patients. Furthermore, we also find that more brain regions and much more voxels in some regions are activity in AD group compared with health control group. Conclusion: It has a great potential value for the AD pathogenesis mechanism study.
Testing the interplay between physiological and life-history traits: an experimental study in Drosophila

Question: Developmental time and metabolic rate are correlated at higher levels of organization. Does this allometric relationship scale down to the intraspecific level? Methods: We exposed flies of three species of Drosophila collected at contrasting altitudes and similar latitudes to varying experimental thermal regimes. Metabolic rate was measured as CO2 production using a ‘closed system’. Developmental time was estimated as the time elapsed from the first instar larval stage until adult emergence. Results: We observed a positive correlation between metabolic rate and developmental time among species. However, such allometry was not detected within species. Interestingly, both variables presented different patterns of interactions with sex and thermal treatment. Conclusions: It may not be possible to extrapolate allometric rules of macroecology to within-species variation. Indeed, the factors that affect variation in physiological variables at the intraspecific and interspecific levels should be different.
Hearing aid Research Data Set for Acoustic Environment Recognition

State-of-the-art hearing aids (HA) are limited in recognizing acoustic environments. Much effort is spent on research to improve listening experience for HA users in every acoustic situation. There is, however, no dedicated public database to train acoustic environment recognition algorithms with a specific focus on HA applications accounting for their requirements. Existing acoustic scene classification databases are inappropriate for HA signal processing. In this work we propose a novel, binaural HA acoustic environment recognition data set (HEAR-DS) suitable for the environment recognition needs of HAs. We present the details about each individual environment provided within the data set. To show separability of these acoustic environments we trained a group of deep neural network-based classifiers which vary in complexity. The obtained classification accuracies provide a reliable indicator about the validity and separability of the provided data set. Finally, as we do not aim at providing the best possible neural network architecture to perform such a classification, but propose solely a novel data set, further research is needed to streamline such networks and optimize them for robustness, real-time and limited computational capability to fit into modern HAs.
THE SUPPOSED CRETACEOUS ANTCRETACOFORMICA EXPLICATAJELL AND DUNCAN (HYMENOPTERA)

The holotype of Cretacoformica explicata Jell and Duncan from the early Cretaceous Koonwarra Fossil Beds, Victoria, is redescribed and the wing venation re-interpreted. Placement of the species within the Formicidae cannot be confirmed and a recent transfer of the species to the Diapriidae is not supported.
Breeding of High-yield Alkaline Protease Producing Strain by Atmospheric and Room Temperature Plasma Mutagenesis

To obtain alkaline protease producing strain with high-yield, the strain Bacillus subtilis was treated by atmospheric and room temperature plasma (ARTP) mutagenesis. The results showed that the strain had a higher positive mutation rate when the mutagenesis time was 50s. Finally, a high-yield mutant strain A59 was obtained after repeated mutagenesis by ARTP and enzyme activity increased by 23.38% from 6835U/mL to 8433U/mL. Then fermentation conditions of mutant strain were optimized by single-factor method and response surface method, and the optimum fermentation conditions were as follows: 3.6% soybean meal, 5.2% corn meal, 0.9115% Na2HPO4, 0.1593% Mg2+, 0.09% Tween-80 and 5% inoculation volume. Under the conditions of the verification experiment, the enzyme activity of the A59 strain reached 14026 U/mL, which was 2.05 times that of the original strain.
Recurrent Neural Audiovisual Word Embeddings for Synchronized Speech and Real-Time Mri

In this paper, the use of word embeddings for the segments found in audio and real-time magnetic resonance imaging (rtMRI) videos is addressed. In this study, word embeddings are created to store and retrieve data efficiently, and their representation power of the original data is evaluated by the same-different word-discrimination task that is defined for both unimodal and cross-view settings. In order to create the word embeddings for two different data modalities independently for the unimodal setting, a Siamese neural network is designed. For the rtMRI videos, inputs to the network are generated through a correspondence autoencoder. In the cross-view setting, a recurrent neural network (RNN), which inputs data of different modalities, is trained to generate embeddings jointly for both data sources. The problem of objective function selection to the RNN is also investigated. The results on the USC-TIMIT rtMRI dataset outperform the conventional dynamic time warping (DTW) baseline by a clear margin. Outcomes demonstrate that the proposed word embeddings can be a step towards faster unimodal or cross-view queryby-example search tasks.