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Previous studies on gestures and personality suggest an ambiguous picture of the effects of the various personality dimensions on the different types of speechgestures and adaptors. In foreign language learning an additional variable to take into account is proficiency, which some studies have shown to affect gestures. In this study, we explore how various intrinsic variables, including personality, proficiency, gender and age affect the gestures of 61 Cantonese speakers of English as a second language. Participants were asked to narrate a video cartoon. Their proficiency and the frequency of gestures produced was based on those narrations. A functional categorization of gestures was followed, dividing them into semantic and discursive, and that also noted adaptors and micro-gestures, referred to as "flutters." Personality was self-reported using the 44 question Big-Five inventory. Correlations and a series of generalized linear models were developed to explore the interplay between variables. Agreeableness was found to be positively correlated with semantic gestures; and neuroticism and age were negatively correlated with flutter duration. Contrary to the findings from previous studies, no significant relationships were found between neuroticism and adaptors or semantic gestures, nor between extraversion or openness and semantic gestures. Proficiency and gender had little effect on gestures. As personality has been shown to be an important factor in gesture production in mother tongue speakers, we expected to also see a similar result with foreign language speakers, this not being so suggests that other variables, aside from those tested, should be considered. In particular, the results suggest that emotion and emotional constructs, such as anxiety, self-confidence or empathy, might have a greater impact on gesture production than proficiency or personality, a point which should be taken into account especially in language evaluation contexts or professional contexts with second language speakers. [ABSTRACT FROM AUTHOR]

Proteins, fundamental to cellular activities, reveal their function and evolution through their structure and sequence. CATH functional families (FunFams) are coherent clusters of protein domain sequences in which the function is conserved across their members. The increasing volume and complexity of protein data enabled by large‐scale repositories like MGnify or AlphaFold Database requires more powerful approaches that can scale to the size of these new resources. In this work, we introduce MARC and FRAN, two algorithms developed to build upon and address limitations of GeMMA/FunFHMMER, our original methods developed to classify proteins with related functions using a hierarchical approach. We also present CATH‐eMMA, which uses embeddings or Foldseek distances to form relationship trees from distance matrices, reducing computational demands and handling various data types effectively. CATH‐eMMA offers a highly robust and much faster tool for clustering protein functions on a large scale, providing a new tool for future studies in protein function and evolution. [ABSTRACT FROM AUTHOR]

We introduce a novel framework for the classification of functional data supported on nonlinear, and possibly random, manifold domains. The motivating application is the identification of subjects with Alzheimer's disease from their cortical surface geometry and associated cortical thickness map. The proposed model is based upon a reformulation of the classification problem as a regularized multivariate functional linear regression model. This allows us to adopt a direct approach to the estimation of the most discriminant direction while controlling for its complexity with appropriate differential regularization. Our approach does not require prior estimation of the covariance structure of the functional predictors, which is computationally prohibitive in our application setting. We provide a theoretical analysis of the out-of-sample prediction error of the proposed model and explore the finite sample performance in a simulation setting. We apply the proposed method to a pooled dataset from Alzheimer's Disease Neuroimaging Initiative and Parkinson's Progression Markers Initiative. Through this application, we identify discriminant directions that capture both cortical geometric and thickness predictive features of Alzheimer's disease that are consistent with the existing neuroscience literature. [ABSTRACT FROM AUTHOR]

Background: Drought stress restricts the growth, distribution and productivity of alfalfa (Medicago sativa L.). In order to study the response differences of alfalfa cultivars to drought stress, we previously carried out physiological and molecular comparative analysis on two alfalfa varieties with contrasting drought resistance (relatively drought-tolerant Longdong and drought-sensitive Algonquin). However, the differences in proteomic factors of the two varieties in response to drought stress still need to be further studied. Therefore, TMT-based quantitative proteomic analysis was performed using leaf tissues of the two alfalfa cultivars to identify and uncover differentially abundant proteins (DAPs). Results: In total, 677 DAPs were identified in Algonquin and 277 in Longdong under drought stress. Subsequently, we conducted various bioinformatics analysis on these DAPs, including subcellular location, functional classification and biological pathway enrichment. The first two main COG functional categories of DAPs in both alfalfa varieties after drought stress were ‘Translation, ribosomal structure and biogenesis’ and ‘Posttranslational modification, protein turnover, chaperones’. According to KEGG database, the DAPs of the two alfalfa cultivars after drought treatment were differentially enriched in different biological pathways. The DAPs from Algonquin were enriched in ‘photosynthesis’ and ‘ribosome’. The pathways of ‘linoleic acid metabolism’, ‘protein processing in endoplasmic reticulum’ and ‘RNA transport’ in Longdong were significantly enriched. Finally, we found significant differences in DAP enrichment and expression patterns between Longdong and Algonquin in glycolysis/glycogenesis, TCA cycle, photosynthesis, protein biosynthesis, flavonoid and isoflavonoid biosynthesis, and plant-pathogen interaction pathway after drought treatment. Conclusions: The differences of DAPs involved in various metabolic pathways may explain the differences in the resistance of the two varieties to drought stress. These DAPs can be used as candidate proteins for molecular breeding of alfalfa to cultivate new germplasm with more drought tolerance to adapt to unfavorable environments. [ABSTRACT FROM AUTHOR]

Background: In recent years, there has been a rapid increase in the number of microbial genomes reconstructed through shotgun sequencing, and obtained by newly developed approaches including metagenomic binning and single-cell sequencing. However, our ability to functionally characterize these genomes by experimental assays is orders of magnitude less efficient. Consequently, there is a pressing need for the development of swift and automated strategies for the functional classification of microbial genomes. Results: The present work leverages a suite of supervised machine learning algorithms to establish a range of 86 metabolic and other ecological functions, such as methanotrophy and plastic degradation, starting from widely obtainable microbial genome annotations. Tests performed on independent datasets demonstrated robust performance across complete, fragmented, and incomplete genomes above a 70% completeness level for most of the considered functions. Application of the algorithms to the Biogas Microbiome database yielded predictions broadly consistent with current biological knowledge and correctly detecting functionally-related nuances of archaeal genomes. Finally, a case study focused on acetoclastic methanogenesis demonstrated how the developed machine learning models can be refined or expanded with models describing novel functions of interest. Conclusions: The resulting tool, MICROPHERRET, incorporates a total of 86 models, one for each tested functional class, and can be applied to high-quality microbial genomes as well as to low-quality genomes derived from metagenomics and single-cell sequencing. MICROPHERRET can thus aid in understanding the functional role of newly generated genomes within their micro-ecological context. [ABSTRACT FROM AUTHOR]

Abstract Background Drought stress restricts the growth, distribution and productivity of alfalfa (Medicago sativa L.). In order to study the response differences of alfalfa cultivars to drought stress, we previously carried out physiological and molecular comparative analysis on two alfalfa varieties with contrasting drought resistance (relatively drought-tolerant Longdong and drought-sensitive Algonquin). However, the differences in proteomic factors of the two varieties in response to drought stress still need to be further studied. Therefore, TMT-based quantitative proteomic analysis was performed using leaf tissues of the two alfalfa cultivars to identify and uncover differentially abundant proteins (DAPs). Results In total, 677 DAPs were identified in Algonquin and 277 in Longdong under drought stress. Subsequently, we conducted various bioinformatics analysis on these DAPs, including subcellular location, functional classification and biological pathway enrichment. The first two main COG functional categories of DAPs in both alfalfa varieties after drought stress were ‘Translation, ribosomal structure and biogenesis’ and ‘Posttranslational modification, protein turnover, chaperones’. According to KEGG database, the DAPs of the two alfalfa cultivars after drought treatment were differentially enriched in different biological pathways. The DAPs from Algonquin were enriched in ‘photosynthesis’ and ‘ribosome’. The pathways of ‘linoleic acid metabolism’, ‘protein processing in endoplasmic reticulum’ and ‘RNA transport’ in Longdong were significantly enriched. Finally, we found significant differences in DAP enrichment and expression patterns between Longdong and Algonquin in glycolysis/glycogenesis, TCA cycle, photosynthesis, protein biosynthesis, flavonoid and isoflavonoid biosynthesis, and plant-pathogen interaction pathway after drought treatment. Conclusions The differences of DAPs involved in various metabolic pathways may explain the differences in the resistance of the two varieties to drought stress. These DAPs can be used as candidate proteins for molecular breeding of alfalfa to cultivate new germplasm with more drought tolerance to adapt to unfavorable environments.

Abstract Background In recent years, there has been a rapid increase in the number of microbial genomes reconstructed through shotgun sequencing, and obtained by newly developed approaches including metagenomic binning and single-cell sequencing. However, our ability to functionally characterize these genomes by experimental assays is orders of magnitude less efficient. Consequently, there is a pressing need for the development of swift and automated strategies for the functional classification of microbial genomes. Results The present work leverages a suite of supervised machine learning algorithms to establish a range of 86 metabolic and other ecological functions, such as methanotrophy and plastic degradation, starting from widely obtainable microbial genome annotations. Tests performed on independent datasets demonstrated robust performance across complete, fragmented, and incomplete genomes above a 70% completeness level for most of the considered functions. Application of the algorithms to the Biogas Microbiome database yielded predictions broadly consistent with current biological knowledge and correctly detecting functionally-related nuances of archaeal genomes. Finally, a case study focused on acetoclastic methanogenesis demonstrated how the developed machine learning models can be refined or expanded with models describing novel functions of interest. Conclusions The resulting tool, MICROPHERRET, incorporates a total of 86 models, one for each tested functional class, and can be applied to high-quality microbial genomes as well as to low-quality genomes derived from metagenomics and single-cell sequencing. MICROPHERRET can thus aid in understanding the functional role of newly generated genomes within their micro-ecological context.

Bioactive peptides are short amino acid chains possessing biological activity and exerting physiological effects relevant to human health. Despite their therapeutic value, their identification remains a major problem, as it mainly relies on time-consuming in vitro tests. While bioinformatic tools for the identification of bioactive peptides are available, they are focused on specific functional classes and have not been systematically tested on realistic settings. To tackle this problem, bioactive peptide sequences and functions were here gathered from a variety of databases to generate a unified collection of bioactive peptides from microbial fermentation. This collection was organized into nine functional classes including some previously studied and some unexplored such as immunomodulatory, opioid and cardiovascular peptides. Upon assessing their sequence properties, four alternative encoding methods were tested in combination with a multitude of machine learning algorithms, from basic classifiers like logistic regression to advanced algorithms like BERT. Tests on a total of 171 models showed that, while some functions are intrinsically easier to detect, no single combination of classifiers and encoders worked universally well for all classes. For this reason, we unified all the best individual models for each class and generated CICERON (Classification of bIoaCtive pEptides fRom micrObial fermeNtation), a classification tool for the functional classification of peptides. State-of-the-art classifiers were found to underperform on our realistic benchmark dataset compared to the models included in CICERON. Altogether, our work provides a tool for real-world peptide classification and can serve as a benchmark for future model development.

Background: Heart failure may cause peripheral and respiratory muscle alterations, dyspnea, fatigue, and exercise intolerance, worsening the quality of life of patients. Objectives: The aims of this study were to analyze respiratory muscle strength and quality of life of patients with heart failure and correlate them with clinical variables and functional classification. Methods: This cross-sectional study involved patients with heart failure. A manovacuometer assessed maximum inspiratory and expiratory pressures, and quality of life was assessed using the Minnesota Living with Heart Failure Questionnaire. Functional classification was categorized according to the New York Heart Association (NYHA) class in I, II, III, or IV. Results: We included 60 patients (66.7%male) with a mean age of 62.0 years and mean left ventricular ejection fraction of 42.0%. Maximum inspiratory pressure and maximum expiratory pressure were close to normal (>70% of predicted) in most patients; however, a subgroup composedmostly of patients with dilated heart failure and NYHA class III (n = 21) presented lowmaximum inspiratory pressure values (59.2%; 95%confidence interval, 55.7%-62.8%). The mean total score of theMinnesota Livingwith Heart Failure Questionnairewas 44.4 points, being negatively correlated with left ventricular ejection fraction (r = -0.29, P = .02). Patients withNYHAclass III and disease duration longer than 120months presented higher total (P < .01) and physical dimension scores. Conclusions: Most patients had respiratory muscle strength close to normal; however, thosewith dilated heart failure and NYHA class III presented lowmaximum inspiratory pressure values. Quality of life wasmoderately compromised, mainly because of long disease duration, NYHA class III, and low left ventricular ejection fraction. [ABSTRACT FROM AUTHOR]

High-throughput DNA sequencing technologies decode tremendous amounts of microbial protein-coding gene sequences. However, accurately assigning protein functions to novel gene sequences remain a challenge. To this end, we developed FunGeneTyper, an extensible framework with two new deep learning models (i.e. FunTrans and FunRep), structured databases, and supporting resources for achieving highly accurate (Accuracy > 0.99, F1-score > 0.97) and fine-grained classification of antibiotic resistance genes (ARGs) and virulence factor genes. Using an experimentally confirmed dataset of ARGs comprising remote homologous sequences as the test set, our framework achieves by-far-the-best performance in the discovery of new ARGs from human gut (F1-score: 0.6948), wastewater (0.6072), and soil (0.5445) microbiomes, beating the state-of-the-art bioinformatics tools and sequence alignment-based (F1-score: 0.0556–0.5065) and domain-based (F1-score: 0.2630–0.5224) annotation approaches. Furthermore, our framework is implemented as a lightweight, privacy-preserving, and plug-and-play neural network module, facilitating its versatility and accessibility to developers and users worldwide. We anticipate widespread utilization of FunGeneTyper (https://github.com/emblab-westlake/FunGeneTyper) for precise classification of protein-coding gene functions and the discovery of numerous valuable enzymes. This advancement will have a significant impact on various fields, including microbiome research, biotechnology, metagenomics, and bioinformatics. [ABSTRACT FROM AUTHOR]

Previous studies on gestures and personality suggest an ambiguous picture of the effects of the various personality dimensions on the different types of speech-gestures and adaptors. In foreign language learning an additional variable to take into account is proficiency, which some studies have shown to affect gestures. In this study, we explore how various intrinsic variables, including personality, proficiency, gender and age affect the gestures of 61 Cantonese speakers of English as a second language. Participants were asked to narrate a video cartoon. Their proficiency and the frequency of gestures produced was based on those narrations. A functional categorization of gestures was followed, dividing them into semantic and discursive, and that also noted adaptors and micro-gestures, referred to as “flutters.” Personality was self-reported using the 44 question Big-Five inventory. Correlations and a series of generalized linear models were developed to explore the interplay between variables. Agreeableness was found to be positively correlated with semantic gestures; and neuroticism and age were negatively correlated with flutter duration. Contrary to the findings from previous studies, no significant relationships were found between neuroticism and adaptors or semantic gestures, nor between extraversion or openness and semantic gestures. Proficiency and gender had little effect on gestures. As personality has been shown to be an important factor in gesture production in mother tongue speakers, we expected to also see a similar result with foreign language speakers, this not being so suggests that other variables, aside from those tested, should be considered. In particular, the results suggest that emotion and emotional constructs, such as anxiety, self-confidence or empathy, might have a greater impact on gesture production than proficiency or personality, a point which should be taken into account especially in language evaluation contexts or professional contexts with second language speakers.

Visual processing in the retina depends on the collective activity of large ensembles of neurons organized in different layers. Current techniques for measuring activity of layer-specific neural ensembles rely on expensive pulsed infrared lasers to drive 2-photon activation of calcium-dependent fluorescent reporters. We present a 1-photon light-sheet imaging system that can measure the activity in hundreds of neurons in the ex vivo retina over a large field of view while presenting visual stimuli. This allows for a reliable functional classification of different retinal cell types. We also demonstrate that the system has sufficient resolution to image calcium entry at individual synaptic release sites across the axon terminals of dozens of simultaneously imaged bipolar cells. The simple design, large field of view, and fast image acquisition make this a powerful system for high-throughput and high-resolution measurements of retinal processing at a fraction of the cost of alternative approaches.

Mechanosensory neurons that innervate the tongue provide essential information to guide feeding, speech, and social grooming. We use in vivo calcium imaging of mouse trigeminal ganglion neurons to identify functional groups of mechanosensory neurons innervating the anterior tongue. These sensory neurons respond to thermal and mechanical stimulation. Analysis of neuronal activity patterns reveal that most mechanosensory trigeminal neurons are tuned to detect moving stimuli across the tongue. Using an unbiased, multilayer hierarchical clustering approach to classify pressure-evoked activity based on temporal response dynamics, we identify five functional classes of mechanosensory neurons with distinct force-response relations and adaptation profiles. These populations are tuned to detect different features of touch. Molecular markers of functionally distinct clusters are identified by analyzing cluster representation in genetically marked neuronal subsets. Collectively, these studies provide a platform for defining the contributions of functionally distinct mechanosensory neurons to oral behaviors crucial for survival in mammals.

Mammalian herbivores play a pivotal role in Earth System processes by affecting biogeochemical cycles and ecosystem functioning, potentially leading to significant repercussions on atmosphere–biosphere feedbacks. Global dynamic models of mammalian populations can improve our understanding of their ecological role at large scales and the consequences of their extinctions. However, such models are still lacking and mammals are poorly integrated in Earth System Science.We developed a mechanistic global model of terrestrial herbivore populations simulated with 37 functional groups defined through the analysis of eco‐physiological traits across all extant herbivores (2599 species). We coupled this model with a global vegetation model to predict herbivores' maximum potential biomass in pre‐industrial and at present‐day and to study the environmental drivers explaining the distribution of herbivore biomass. Present‐day biomass was estimated by accounting for anthropogenic activity causing habitat and range losses.We show that natural ecosystems could have sustained a potential wild herbivore wet biomass of 330 Mt (95% CI: 245–417), comprised of 193 Mt (95% CI: 177–208) by large species (body mass >1–10 kg, depending on functional group) and 138 Mt (95% CI: 68–209) by small species. We estimate that the remaining present‐day large herbivores biomass is 82 Mt (95% CI: 32–133), reduced by 57% due to anthropogenic activity; consequently, small herbivores currently dominate global herbivore biomass with 98 Mt (95% CI: 91–106, −29%). Losses vary greatly across climatic zones and functional groups, suggesting that size is not the only discriminant feature of biomass decline.Actual evapotranspiration is the most important driver of total, large and small herbivore biomass and explains 64%, 59% and 49% of its variation, respectively. Distribution of modelled and observed large herbivores' biomass suggested a high dependency on energy and water with more biomass in hot and wet areas. These results challenge the notion that large herbivore biomass peaks primarily in ecosystems with intermediate precipitation levels such as savannas.Outside Africa and the Tropics, pre‐industrial biomass hotspots occur in areas today dominated by humans; this could undermine the recovery of larger species biomass in certain areas. Our herbivore biomass estimates provide a quantitative benchmark for setting conservation and rewilding goals at large spatial scales. The herbivore model and functional classification create new opportunities to integrate mammals into Earth System Science and models. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Featured Application: Analyzing the performance of Wheelchair Basketball players according to Functional Classification and game indicators to provide relevant information regarding the identification of details which can determine indicial and team success in each of the different Functional Classifications. Game statistics are used for the analysis of the performance of athletes. This allows the strengths and weaknesses of the players to be understood, and to design and implement training sessions for performance enhancement. Therefore, the objective of this study was to analyse the game statistics of the 2021 and 2023 European Champions and the 2023 World Champions in Wheelchair Basketball (WB), both male and female. For this purpose, the game statistics of all the championships were collected, and the differences according to gender and competition analysed through a statistical and inferential analysis, considering the functional classification of the players, based on the Mann–Whitney U test for the comparison of gender, and the Kruskal–Wallis H test for the comparison between championships. The results showed that players with a classification higher than 3.0 have higher three-point and two-point throws, while players with a classification of 1.0 have lower effectiveness in shooting. Depending on the championship, a greater number of three-point throws and respective effectiveness was found in the 2023 World Championships, with the male athletes presenting a greater number of points. This information will support WB coaches in designing and implementing training sessions and patterns of play and movements in competitive moments to improve individual and team performance. [ABSTRACT FROM AUTHOR]

Under irrigation with saline wastewater, SO42−, Cl−, and Ca2+ aggregated in the topsoil, and Mg2+ was significantly higher in the deeper soil than in the topsoil and 40 cm soil layers. The abundance of Zoopagomycota, Ascomycota, Mortierellomycota, Basidiomycota, Chytridiomycota, Rozellomycota, Blastocladiomycota, Monoblepharomycota, Mucoromycota and Olpidiomycota in the surface soil was influenced by Mg2+, whereas Ca2+ affected the abundance of Zoopagomycota and Chytridiomycota. In the 40 cm soil layer, Mg2+ and Cl− promoted Actinobacteria, Proteobacteria, Nitrospirae, Firmicutes, Entotheonellaeota, Myxococcota, Gemmatimonadota and Methylomirabilota, whereas they inhibited Planctomycetota, Acidobacteria, Chloroflexi, Patescibacteria and Bacteroidota. In the 80 cm soil layer, SO42− and Cl− promoted Rozellomycota, Mortierellomycota, Chytridiomycota, Ascomycota, and Mucoromycota, but had a negative effect on Glomeromycota, Blastocladiomycota, Olpidiomycota and Monoblepharomycota. The increase in salinity significantly reduced the abundance of the Actinomycetes phylum and the Amoebozoa phylum. Both saprophytic and symbiotic fungi decreased with increasing salinity. [ABSTRACT FROM AUTHOR]

Wheelchair basketball is a Paralympic sport that has been included in the Paralympic Games since 1960. Today, it is played in over one hundred countries by approximately thirty thousand athletes. The rules are like those of traditional basketball, with specific adaptations for wheelchairs and a classification system based on the athletes’ functional abilities. This sport offers numerous physiological, mental, and social benefits, enhancing the independence and inclusion of people with disabilities. However, it also carries a high risk of injuries, both traumatic and overuse, particularly to the shoulders and hands due to falls and intense movements. Injury prevention is crucial and requires targeted training programs and a multidisciplinary approach. Preventive and rehabilitative strategies, such as improving propulsion techniques and using advanced technologies, can reduce the incidence of injuries and improve the quality of life for athletes. [ABSTRACT FROM AUTHOR]

Reduced traffic exposure due to COVID-19 lockdowns may have resulted in changes to both the frequency and severity of motor vehicle crashes. In order to better understand the impact of COVID-19 lockdowns on traffic safety outcomes in US DOT Region 6, we explored the role of vehicle, user, and built environment factors on fatalities, injuries, and total crashes before and during COVID-19 lockdowns in Oklahoma and Texas. Findings suggest that while crash counts in Region 6 were 45%-50% lower during the COVID-19 lockdowns than the previous five-year averages, crashes were more severe. Fatal pedestrian crash counts decreased 3.9% during COVID-19 and fatal bicyclist crash counts increased 22.0%. These Region 6 outcomes were worse than the US as a whole. COVID-19 crashes were more likely single-vehicle fixed-object or rollover crashes involving unsafe speeds. In Texas, suburban areas saw the most crashes before and during COVID-19. Rural Texas crashes were most likely to result in a serious or fatal injury, and that likelihood got worse during the COVID-19 lockdowns.

Inertial devices (ID) have been used in professional sports to quantify the external and internal load, due to their great functionality in the characterization of players' performance levels. Wheelchair Basketball (WB) is a sport designed for people with disabilities, who have a functional classification (FC), according to their range of movements and trunk stability (1.0 to 4.5 FC). This study aimed to analyse the external and internal load of WB players, according to the players' FC. The results showed that players of FC4.0 present better values in most of the analysed variables. Players of FC1.0 presented the highest maximum values in acceleration and deceleration. Determining the load to which WB players are subjected in simulated competition situations will allow training sessions to be personalized considering the physical demands of the competition. Analysing the external and internal load of the players during training tasks gives the coaching staff a great quantity of information, allowing to personalise the training tasks according to the competition demands, to obtain the best performance of each player, through a progressive training process. [ABSTRACT FROM AUTHOR]

Featured Application: Quantifying the external and internal load of the wheelchair basketball will allow the coaching staff to analyze the physical demands of the players during training. The systematic and programmed control and evaluation of the external and internal load of high-performance athletes during training sessions and high-level competitions allows the coaching staff to know a great amount of information to evaluate the physical condition of the players and the tactical positioning as well as to identify optimal performance. Therefore, this study aimed to analyse the external and internal load of wheelchair basketball players during training and competition matches considering the functional classification of the players. WIMU PROTM inertial devices were used to collect the data. As independent variables, the sporting context and the functional classification were selected, and as dependent variables, the variables related to the external and internal load were established. The results reported significant differences between the contexts, with higher values in the competition than in the training sessions considering the internal and external load. Taking into account the functional classification, it is shown that the player with a higher functional classification obtained more differences and higher values. Understanding the external and internal load of the players during training and competitions is very important to personalise the training load according to the demands of the competition. It allows development of a progressive and modular training programme of loads to obtain the best performance. Consequently, injury risk of players due to overload will also be reduced. [ABSTRACT FROM AUTHOR]

We propose a new approach, called as functional deep neural network (FDNN), for classifying multidimensional functional data. Specifically, a deep neural network is trained based on the principal components of the training data which shall be used to predict the class label of a future data function. Unlike the popular functional discriminant analysis approaches which only work for one‐dimensional functional data, the proposed FDNN approach applies to general non‐Gaussian multidimensional functional data. Moreover, when the log density ratio possesses a locally connected functional modular structure, we show that FDNN achieves minimax optimality. The superiority of our approach is demonstrated through both simulated and real‐world datasets. [ABSTRACT FROM AUTHOR]

Telomeres are the terminal regions of chromosomes that ensure their stability while cell division. Telomere shortening initiates cellular senescence, which can lead to degeneration and atrophy of tissues, so the process is associated with a reduction in life expectancy and predisposition to a number of diseases. An accelerated rate of telomere attrition can serve as a predictor of life expectancy and health status of an individual. Telomere length is a complex phenotypic trait that is determined by many factors, including the genetic ones. Numerous studies (including genome-wide association studies, GWAS) indicate the polygenic nature of telomere length control. The objective of the present study was to characterize the genetic basis of the telomere length regulation using the GWAS data obtained during the studies of various human and other animal populations. To do so, a compilation of the genes associated with telomere length in GWAS experiments was collected, which included information on 270 human genes, as well as 23, 22, and 9 genes identified in the cattle, sparrow, and nematode, respectively. Among them were two orthologous genes encoding a shelterin protein (POT1 in humans and pot-2 in C. elegans). Functional analysis has shown that telomere length can be influenced by genetic variants in the genes encoding: (1) structural components of telomerase; (2) the protein components of telomeric regions (shelterin and CST complexes); (3) the proteins involved in telomerase biogenesis and regulating its activity; (4) the proteins that regulate the functional activity of the shelterin components; (5) the proteins involved in telomere replication and/or capping; (6) the proteins involved in the alternative telomere lengthening; (7) the proteins that respond to DNA damage and are responsible for DNA repair; (8) RNA-exosome components. The human genes identified by several research groups in populations of different ethnic origins are the genes encoding telomerase components such as TERC and TERT as well as STN1 encoding the CST complex component. Apparently, the polymorphic loci affecting the functions of these genes may be the most reliable susceptibility markers for telomere-related diseases. The systematized data about the genes and their functions can serve as a basis for the development of prognostic criteria for telomere length-associated diseases in humans. Information about the genes and processes that control telomere length can be used for marker-assisted and genomic selection in the farm animals, aimed at increasing the duration of their productive lifetime.

Traditional natural products in China have a long history and a vast pharmacological repertoire that has garnered significant attention due to their safety and efficacy in disease prevention and treatment. Among the bioactive components of traditional natural products in China, bioactive peptides (BPs) are specific protein fragments that have beneficial effects on human health. Despite many of the traditional natural products in China ingredients being rich in protein, BPs have not received sufficient attention as a critical factor influencing overall therapeutic efficacy. Therefore, the purpose of this review is to provide a comprehensive summary of the current methodologies for the preparation, isolation, and identification of BPs from traditional natural products in China and to classify the functions of discovered BPs. Insights from this review are expected to facilitate the development of targeted drugs and functional foods derived from traditional natural products in China in the future. [ABSTRACT FROM AUTHOR]

Reduced traffic exposure due to COVID-19 lockdowns may have resulted in changes to both the frequency and severity of motor vehicle crashes. In order to better understand the impact of COVID-19 lockdowns on traffic safety outcomes in US DOT Region 6, we explored the role of vehicle, user, and built environment factors on fatalities, injuries, and total crashes before and during COVID-19 lockdowns in Oklahoma and Texas. Findings suggest that while crash counts in Region 6 were 45%-50% lower during the COVID-19 lockdowns than the previous five-year averages, crashes were more severe. Fatal pedestrian crash counts decreased 3.9% during COVID-19 and fatal bicyclist crash counts increased 22.0%. These Region 6 outcomes were worse than the US as a whole. COVID-19 crashes were more likely single-vehicle fixed-object or rollover crashes involving unsafe speeds. In Texas, suburban areas saw the most crashes before and during COVID-19. Rural Texas crashes were most likely to result in a serious or fatal injury, and that likelihood got worse during the COVID-19 lockdowns. [ABSTRACT FROM AUTHOR]

Game statistics are used for the analysis of the performance of athletes. This allows the strengths and weaknesses of the players to be understood, and to design and implement training sessions for performance enhancement. Therefore, the objective of this study was to analyse the game statistics of the 2021 and 2023 European Champions and the 2023 World Champions in Wheelchair Basketball (WB), both male and female. For this purpose, the game statistics of all the championships were collected, and the differences according to gender and competition analysed through a statistical and inferential analysis, considering the functional classification of the players, based on the Mann–Whitney U test for the comparison of gender, and the Kruskal–Wallis H test for the comparison between championships. The results showed that players with a classification higher than 3.0 have higher three-point and two-point throws, while players with a classification of 1.0 have lower effectiveness in shooting. Depending on the championship, a greater number of three-point throws and respective effectiveness was found in the 2023 World Championships, with the male athletes presenting a greater number of points. This information will support WB coaches in designing and implementing training sessions and patterns of play and movements in competitive moments to improve individual and team performance.

Under irrigation with saline wastewater, SO42−, Cl−, and Ca2+ aggregated in the topsoil, and Mg2+ was significantly higher in the deeper soil than in the topsoil and 40 cm soil layers. The abundance of Zoopagomycota, Ascomycota, Mortierellomycota, Basidiomycota, Chytridiomycota, Rozellomycota, Blastocladiomycota, Monoblepharomycota, Mucoromycota and Olpidiomycota in the surface soil was influenced by Mg2+, whereas Ca2+ affected the abundance of Zoopagomycota and Chytridiomycota. In the 40 cm soil layer, Mg2+ and Cl− promoted Actinobacteria, Proteobacteria, Nitrospirae, Firmicutes, Entotheonellaeota, Myxococcota, Gemmatimonadota and Methylomirabilota, whereas they inhibited Planctomycetota, Acidobacteria, Chloroflexi, Patescibacteria and Bacteroidota. In the 80 cm soil layer, SO42− and Cl− promoted Rozellomycota, Mortierellomycota, Chytridiomycota, Ascomycota, and Mucoromycota, but had a negative effect on Glomeromycota, Blastocladiomycota, Olpidiomycota and Monoblepharomycota. The increase in salinity significantly reduced the abundance of the Actinomycetes phylum and the Amoebozoa phylum. Both saprophytic and symbiotic fungi decreased with increasing salinity.

The intrinsic infinite-dimensional nature of functional data creates a bottleneck in the application of traditional classifiers to functional settings. These classifiers are generally either unable to generalize to infinite dimensions or have poor performance due to the curse of dimensionality. To address this concern, we propose building a distance-weighted discrimination (DWD) classifier on scores obtained by projecting data onto one specific direction. We choose this direction by minimizing, over a reproducing kernel Hilbert space, an empirical risk function containing the DWD classifier loss function. Our proposed classifier avoids overfitting and enjoys the appealing properties of DWD classifiers. We further extend this framework to accommodate functional data classification problems where scalar covariates are involved. In contrast to previous work, we establish a nonasymptotic estimation error bound on the relative misclassification rate. Through simulation studies and a real-world application, we demonstrate that the proposed classifier performs favorably relative to other commonly used functional classifiers in terms of prediction accuracy in finite-sample settings. for this article are available online. [ABSTRACT FROM AUTHOR]

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The article examines changes in the structure of the expenditure part of the German federal budget. Data on the execution of annual budgets in 2017–2021 and of a five-year financial plan for 2022–2026 are analysed. Comparison of structures is carried out according to a cross-classification that combines a functional classification (divided into ten sections in accordance with the classification of the International Monetary Fund) and an economic classification (divided into two sections – current and capital expenditures). The author identifies the areas with a key role in the spending hierarchy, highlights the main factors of the expected dynamics in the next five years, and also considers the features of three periods (2017–2019, 2020–2021 and 2022–2026) in terms of speed and contradictoriness of the structural changes that have taken place and are planned. Based on the analysis, the article concludes that there have been significant and rapid structural changes that have taken place during the pandemic, and that the most important «pre-Covid» indicators (primarily an increase in the share of current expenses on social protection) are planned to be restored. This restoration, however, may be hindered by the implementation of a large-scale «protective umbrella for the economy» – a set of measures developed, but not yet included in the financial plan, to support the German industry, which suffered from a jump in gas prices.

Purpose: to determine the value of the functional classification and its influence on the result of the competitive activity of Paralympic cross-country sit-skiers. Material and methods: to solve the problems of the study, the data of 164 Paralympic cross-country sit-skiers were analyzed, including 98 men and 66 women, participants of the Winter Paralympic Games, namely: Sochi 2014 – 47 athletes (24 men and 25 women) PyeongChang 2018 – 61 men and 25 women), Beijing 2022 – 56 athletes (38 men and 18 women) with a functional class LW10-12 and are representatives of the sitting category, performing in the sprint ski race. During the study, the following methods were used: theoretical analysis of scientific and methodological literature and Internet sources, generalization of best practices, analysis of protocols and videos of competitive activity, methods of mathematical statistics. Results: changes were revealed in relation to representatives of different classes in the final round of the sprint ski race among athletes of the sitting category: Sochi 2014: men – LW10 – 1 and LW12 – 5, women – LW11 – 2 and LW12 – 4; PyeongChang 2018: men – LW11.5 – 1 and LW12 – 5, women – LW11 – 1 and LW12 – 5; Beijing 2022: men LW10 – 2, LW11.5 – 1 and LW12, women – LW10 – 1, LW10.5 – 1, LW11.5 – 1 and LW12 – 3. Conclusions: it has been proven that one of the topical issues in holding competitions among athletes with disabilities is the classification process aimed at fair competition between athletes, despite their individual functional capabilities; despite this, modern research proves that there are some factors that affect the result of competitive activity, but which are not taken into account by the classification system; the modern classification strategy is aimed at improving this process (percentage system), which helps to increase the competitiveness of representatives of all classes included in the sitting category.

Relevance and goals. In the context of global climate change, the climate-regulating function of forests deserves special attention. There is still no functional classification of forests according to the effectiveness of their carbon storage function. The purpose of this article is to discuss an approach to such classification based on the assessment of the quality of tree litter. Objects and methods. To test the approach to the identification of functional types of forests (FTL) based on the quality of tree litter, taking into account the position in the landscape and the mechanical composition of soil-forming rocks, data on soils and vegetation obtained at 23 sites operating in the subzone of coniferous-broadleaf forests of the European part of Russia on the territory of Bryansk Polesie and Moskvoretsko-Okskaya plain were used. For indirect (on the ecological scale of E. Landolt using the SpeDiv program) to assess differences in the soil richness of forests belonging to different FTLS, the species composition of 160 descriptions of forest vegetation of the Moscow, Bryansk, Smolensk, Kostroma regions, Krasnodar Krai and the Republic of Adygea (North-Western Caucasus) was analyzed. Results. Examples of functional forest types (FTL) for coniferous and broad-leaved forests of the European part of Russia are given. The differences in the level of soil carbon accumulation between different FTLS are shown, and a preliminary assessment of the influence of the position in the landscape and the mechanical composition of soils on the accumulation of carbon in soils within FTLS is given. Conclusion. Based on the quality of the fall of tree litter, 15 FTL were identified, which are confirmed by examples based on geobotanical descriptions of forest communities common in the zone of coniferous-deciduous forests of the European part of Russia and in the belt of coniferous-deciduous forests of the North-Western Caucasus. The validity of the allocation of FTL for the efficiency of carbon accumulation in soils based on the quality of plant litter, taking into account the influence of “external factors” (the position in the landscape and the mechanical composition of soil-forming rocks) is confirmed by data obtained at 23 sites; estimates of the carbon reserves in the soil, as well as the soil richness estimated on an ecological scale, revealed differences between the allocated FTLS. Differences in carbon stocks in forest ecosystems in the same FTL formed on loamy and sandy loam soil-forming rocks were revealed. Differences in soil carbon reserves in forests belonging to the same FTL, but formed at different positions in the landscape, have been confirmed; in transit landscapes, soil carbon reserves are higher than in autonomous ones.

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Copyright of Dirasat: Educational Sciences is the property of University of Jordan and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

China's state-owned enterprises (SOEs) are facing an embedded integration of new functional mission, new classification reform and new digital development. These new tasks require SOEs to embrace digital strategic transformation and innovation for high-quality fulfillment of their national mission. Studying their digital transformation practices, this paper systematically explores the mechanism and path of embedding national mission into SOE digital transformation, and the mode selection of SOE digital transformation under different mission guidance. The findings are: (1) The SOE functional mission focusing on economic development, strategic support and public services in the new era is undertaken by for-profit, strategic and public functional SOEs; (2) the foreign circulation path based on the positioning mechanism-mapping mechanism and the internal consumption connection path for the state capital strategic positioning constitute a double twoway mechanism of embedding the national mission to the SOE digital strategic transformation, leading SOEs to build market-oriented, capacity-oriented and public-oriented digital transformation modes; (3) the three types of reform modes have respectively produced the action mechanism featuring agile strengthening, toughness strengthening and adaptability strengthening, which support the SOE classification performance. This paper attempts to make up for the research gap such as the lack of integration of the SOE digital strategic transformation mode by constructing the theoretical mode of SOE digital strategic transformation under the guidance of national mission, and reveals the intermediary mechanism of digital strategic transformation to support SOEs for fulfilling their functional missions. [ABSTRACT FROM AUTHOR]

The systematic and programmed control and evaluation of the external and internal load of high-performance athletes during training sessions and high-level competitions allows the coaching staff to know a great amount of information to evaluate the physical condition of the players and the tactical positioning as well as to identify optimal performance. Therefore, this study aimed to analyse the external and internal load of wheelchair basketball players during training and competition matches considering the functional classification of the players. WIMU PROTM inertial devices were used to collect the data. As independent variables, the sporting context and the functional classification were selected, and as dependent variables, the variables related to the external and internal load were established. The results reported significant differences between the contexts, with higher values in the competition than in the training sessions considering the internal and external load. Taking into account the functional classification, it is shown that the player with a higher functional classification obtained more differences and higher values. Understanding the external and internal load of the players during training and competitions is very important to personalise the training load according to the demands of the competition. It allows development of a progressive and modular training programme of loads to obtain the best performance. Consequently, injury risk of players due to overload will also be reduced.

Objectives: This study aimed to identify the impact of the functional classification of wheelchair basketball players on blood pressure values after sub-maximal exercise. Methods: the researchers used semi-experimental method with all its procedures to achieve the study objectives. The study sample consisted of (8) players out of the (12) players representing the Jordan national wheelchair basketball team based on the records of the Jordan Paralympic Committee for years 2021, and the players were selected deliberately. The researchers used the semi-experimental method to achieve the study objectives. Moreover, the researchers used the VO2PEAK test and Borg scale of perceived severity statistically, the One Way ANOVA test and the LSD test were used, in addition to the arithmetic mean. Results: The results showed a significant decrease in the value of diastolic blood pressure in the categories (1-1.5) and (2-2.5). This took place lower due to the nature of the disabilities falling under these two categories are according to the classification of wheelchair basketball players. Conclusions: In light of the results, the researchers recommend taking into consideration the values of diastolic blood pressure when developing training programs, especially for players with amputations from the classification of amputations of the lower limbs above the knee.

We investigated changes in the prevalence of speeding during March–June 2020, the beginning of the COVID-19 pandemic, in Virginia. Vehicle speed data from 506 permanent speed counter stations around the state collected during March–June 2019 and March–June 2020 were analyzed. Increases in the proportion of vehicles traveling at least 5 mph and 10 mph above the speed limit were greatest on urban interstates and other freeways, during early morning (6:00–8:59 a.m.) and afternoon commuting hours (3:00–5:59 p.m.) on weekdays, and during afternoons (12:00–5:59 p.m.) on weekends. Logistic regression revealed that the risk of speeding by at least 5 mph increased in 2020 by 22% and by at least 10 mph increased 51% after accounting for road type, time of day, day of week, and traffic volume, relative to 2019. Future research should continue to identify where and when speeding problems are most severe, and countermeasures should be directed to the roads and time periods with the largest speeding problems. [ABSTRACT FROM AUTHOR]

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Traditional natural products in China have a long history and a vast pharmacological repertoire that has garnered significant attention due to their safety and efficacy in disease prevention and treatment. Among the bioactive components of traditional natural products in China, bioactive peptides (BPs) are specific protein fragments that have beneficial effects on human health. Despite many of the traditional natural products in China ingredients being rich in protein, BPs have not received sufficient attention as a critical factor influencing overall therapeutic efficacy. Therefore, the purpose of this review is to provide a comprehensive summary of the current methodologies for the preparation, isolation, and identification of BPs from traditional natural products in China and to classify the functions of discovered BPs. Insights from this review are expected to facilitate the development of targeted drugs and functional foods derived from traditional natural products in China in the future.

Wheelchair rugby is a contact sport in which falls are common and injury rates are high, yet the characteristics of the falls are still under-reported. We investigated the fall characteristics of men's wheelchair rugby players by functional classification, using all 36 official match videos from the Rio 2016 and Tokyo 2020 summer Paralympic Games. The videos were analyzed to evaluate the number of falls, playing time when the fall occurred, playing phase (offense or defense), contact with other players, foul judgement, direction of the fall, and the body part first in contact with the floor. All 182 men's wheelchair rugby players (Rio 2016, 94; Tokyo 2020, 88) were classified as low-point players or high-point players depending on their functional classification. A total of 200 falls were detected, 27 (13.5%) for low-point players and 173 (86.5%) for high-point players. Significant differences were noted between low-point players and high-point players in the direction of the fall and body part first in contact with the floor. High-point players had more falls in the forward and left-right directions, whereas low-point players were characterized by a higher percentage of falls in the left-right and backward directions. Additionally, high-point players landed on the floor with their hands with high frequency, whereas low-point players landed with their elbows and shoulders more often. Our findings suggest the significance of devising measures to prevent falls during men's wheelchair rugby games according to their functional classification. [ABSTRACT FROM AUTHOR]

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Background: Prevalence of heart failure has been increasing worldwide. Decreased muscle mass, poor physical activity, and reduced physical performance or muscle strength might lead to sarcopenia among heart failure patients and therefore lead to low cardiac output, and vice versa. Symptoms of depression are also common mental health problems in heart failure. However, little is known about the prevalence of depressive symptoms in heart failure patients with sarcopenia and the relationship with its. This study aimed to explore the prevalence of and relationship between sarcopenia and depressive symptoms in heart failure patients. Methods: A cross-sectional study comprised of 150 participants aged 35 years or older. Sarcopenia and no sarcopenia were classified by using the Asian Working Group for Sarcopenia 2019 criteria. Physical performance, muscle strength, and skeletal muscle mass were examined. Symptoms of depression were assessed through utilization of the validated Thai version of Patient Health Questionnaire 9. Results: The prevalence of sarcopenia was 18.67% and depression was 5.33% in heart failure patients. In addition, the prevalence of depression in heart failure patients with sarcopenia were 3.57%. The relationship was observed based on depression scores and New York Heart Association functional classification ( r = 0.319, pConclusion s : Prevalence of sarcopenia in heart failure patients was 18.67% and only 5.33% exhibited depressive symptoms. Only 3.57% exhibited both depression and sarcopenia. Additionally, New York Heart Association functional classification was related to depression.

Proteins, fundamental to cellular activities, reveal their function and evolution through their structure and sequence. CATH functional families (FunFams) are coherent clusters of protein domain sequences in which the function is conserved across their members. The increasing volume and complexity of protein data enabled by large-scale repositories like MGnify or AlphaFold Database requires more powerful approaches that can scale to the size of these new resources. In this work, we introduce MARC and FRAN, two algorithms developed to build upon and address limitations of GeMMA/FunFHMMER, our original methods developed to classify proteins with related functions using a hierarchical approach. We also present CATH-eMMA, which uses embeddings or Foldseek distances to form relationship trees from distance matrices, reducing computational demands and handling various data types effectively. CATH-eMMA offers a highly robust and much faster tool for clustering protein functions on a large scale, providing a new tool for future studies in protein function and evolution., (© 2024 The Author(s). Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.)

Classification of cardinal numerals is an important step in studying Chinese numerals. The study is carried out in the framework of the functional, structural (morphemic), and functional-structural (combined) classification approaches, as well as in accordance with the integrity of numerals and the accuracy of their quantifying properties. Chinese numerals are considered from the perspective of the first three classifications. The results obtained reveal the nomenclature volatility of Chinese cardinal numerals with the same classification group having several names to denote it. Hence, the article attempts to streamline the respective terminology. The functional classification divides cardinal numerals into coefficient and digit-position numerals. The cases when digit-position numerals may function as coefficient numerals are analyzed. In the framework of the structural classification, it is suggested to divide cardinal numerals into simple (coefficient) and compound ones, the latter being broken into additive (elementary and miscellaneous) and multiplicative. The article also focuses on answering the question of whether compound numerals should be regarded as words or phrases. The conclusion is made that they should be perceived as words. The functional-structural classification makes a substantial contribution to the study of Chinese cardinal numerals. The classification has not been introduced to the Russian sinology yet. This fact entails the necessity to translate the respective terms and expressions, the choice of which is explained in this article. The variations of the combined functional-structural classification introduced by Zhu Dexi, Guan Yanqìng, Xiao Guozheng, and Li Yingzhe are discussed. Based on the analysis of these variations, an understanding of the combined functional-structural division of Chinese cardinal numerals is suggested.

Central government budget expenditures, which are very important for parliamentary systems, are respectively in Turkey; It goes through the stages of preparation, approval, implementation and control. Stability is essential for these public expenditures, which will take place in the following fiscal year. Otherwise, budget deficit occurs as a result of public expenditures being more than public revenues. Central government budget expenditures are divided into two as economic and functional classification. The parameters included in the economic and functional classification are presented as the sum of the expenses under them. The aim of this study is to examine the cluster analysis results of Central government budget expenditures per capita in Turkey with Self-Organizing Maps, which is an artificial neural network model and also a clustering analysis method. [ABSTRACT FROM AUTHOR]

Functional classification of proteins from sequences alone has become a critical bottleneck in understanding the myriad of protein sequences that accumulate in our databases. The great diversity of homologous sequences hides, in many cases, a variety of functional activities that cannot be anticipated. Their identification appears critical for a fundamental understanding of the evolution of living organisms and for biotechnological applications. ProfileView is a sequence-based computational method, designed to functionally classify sets of homologous sequences. It relies on two main ideas: the use of multiple profile models whose construction explores evolutionary information in available databases, and a novel definition of a representation space in which to analyze sequences with multiple profile models combined together. ProfileView classifies protein families by enriching known functional groups with new sequences and discovering new groups and subgroups. We validate ProfileView on seven classes of widespread proteins involved in the interaction with nucleic acids, amino acids and small molecules, and in a large variety of functions and enzymatic reactions. ProfileView agrees with the large set of functional data collected for these proteins from the literature regarding the organization into functional subgroups and residues that characterize the functions. In addition, ProfileView resolves undefined functional classifications and extracts the molecular determinants underlying protein functional diversity, showing its potential to select sequences towards accurate experimental design and discovery of novel biological functions. On protein families with complex domain architecture, ProfileView functional classification reconciles domain combinations, unlike phylogenetic reconstruction. ProfileView proves to outperform the functional classification approach PANTHER, the two k-mer-based methods CUPP and eCAMI and a neural network approach based on Restricted Boltzmann Machines. It overcomes time complexity limitations of the latter. [ABSTRACT FROM AUTHOR]

The aim was to study functional abilities and to create functional classification of children with cerebral palsy (CP) in Krapina-Zagorje County, based on the classification of gross and fine motor skills and associated impairments. Classification was performed according to the SCPE (Surveillance of Cerebral Palsy in Europe) criteria. We used standardized and complementary functional classification systems for cerebral palsy to create a functional profile. Research included 44 children with CP in the age range of 4 to 18 years. The results showed that the majority of children had bilateral spastic CP (63.6%), followed by unilateral spastic (22.7%) while the representation of dyskinetic CP was 9.09% and ataxic CP 4.55%. Based on the classification of gross and fine motor skills, 43.2% of children had the ability to walk, 11% of children could walk with assistive mobility devices, while 45.4% of children had a low functional level. The study also analyzed the associated impairments where higher classification score of motor impairment correlated with the severity of impairment. The results showed that children with dyskinetic CP and severe motor impairment could have mild cognitive impairment. We systematically present the neuropsychological and functional profile according to the CP type.