Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of functional gastrointestinal disorders in children aged 4-10 years with autism spectrum disorder.

BACKGROUND Gastrointestinal system disorders are known to be prevalent among children with autism spectrum disorder (ASD). Some ASD-associated comorbidities are abdominal pain, constipation, diarrhea, gastroesophageal reflux, sleep disturbances, epilepsy, and psychiatric problems. Nonetheless, there is still limited information about the presence of functional GI disorders (FGIDs) among children with ASD, especially in Türkiye. Using the Rome criteria, we aimed to investigate FGIDs in children with ASD. METHODS The sample of the study consisted of 68 children aged 4-10 years, diagnosed with ASD according to the DSM-5 diagnostic criteria and had scores greater than 30 on the Childhood Autism Rating Scale (CARS-2) and an age-sex matched control group (n=78). The Rome III criteria were used to evaluate FGIDs. RESULTS The frequency of FGIDs in the ASD group was higher (76.5%) compared to the control group (p < 0.001). Compared to the control group, abdominal migraine frequency increased 10 times (p=0.012), functional constipation 7 times (p < 0.001), and fecal incontinence 6 times (p < 0.001) in the ASD group. Stool retention was not present in most children in the ASD group who were found to have fecal incontinence. CONCLUSION In this study, the most common FGIDs in the ASD group were abdominal migraine, functional constipation, and non-retentive fecal incontinence. The finding that most children with ASD who had fecal incontinence did not show stool retention implicated social, psychological, and behavioral factors as the causes of incontinence. Raising awareness of healthcare professionals about the frequency of FGIDs in children with ASD will improve many areas in the daily lives of these children.
Energy expenditure: components and evaluation methods.

INTRODUCTION The determination of energy expenditure, considering the physical activity level and health status, is very important to adjust the individuals' nutritional supply. Energy expenditure can be determined by using indirect calorimetry, bioelectrical impedance, doubly labeled water, predictive equations, among others. All these methods have been used in clinical and research areas. However, considering the inconsistence in several research results, there is no consensus yet about the applicability of many of these methods. OBJECTIVES The aim of this review is to describe the components of energy expenditure and the methods for its determination and estimation, summarizing their main advantages and limitations. RESULTS AND DISCUSSION Indirect calorimetry and doubly labeled water are considered more accurate methods, but expensive. On the other hand, even though other methods present limitations, they are convenient and less expensive, and can be used with some caution.
The effect of vibration frequency and amplitude on biofouling deterrence

The use of vibration is proposed as a means of controlling the settlement of marine fouling organisms. In this study, panels with embedded lead zirconate titanate, known as PZT, were placed in the field over 3 months. The panels were vibrated at different velocity levels at frequencies between 70 and 445 Hz. It was found that barnacles (Amphibalanus variegatus Darwin and Elminius sp.) were the only fouling organisms affected by the applied vibration, and these organisms settled in significantly lower numbers when the plates were excited at specific frequencies and amplitudes. Panels vibrating at relatively higher frequencies, greater than 260 Hz, exhibited reduced barnacle settlement, whilst lower frequencies in the 70–100 Hz range had little or no effect. The settlement of other fouling organisms such as tubeworms, bryozoans, ascidians and algae did not appear to be affected by the applied excitation. The experimental results showed that increasing the velocity amplitude of vibration was a contributing factor in inhibiting barnacle settlement.
Improving Translation Model by Monolingual Data

We use target-side monolingual data to extend the vocabulary of the translation model in statistical machine translation. This method called "reverse self-training" improves the decoder's ability to produce grammatically correct translations into languages with morphology richer than the source language esp. in small-data setting. We empirically evaluate the gains for several pairs of European languages and discuss some approaches of the underlying back-off techniques needed to translate unseen forms of known words. We also provide a description of the systems we submitted to WMT11 Shared Task.
Scalable video multicast using flexible multicast service over IEEE 802.11 WLAN

In video multicast, it is a challenging task to deliver video at a satisfactory level to multiple receivers with different channel quality and different battery capacities. In order to resolve such receiver heterogeneity, we propose a video multicast system that integrates scalable video coding (SVC) and flexible multicast service (FMS). The system is designed to transmit the base layer (BL) and the enhancement layer (EL) of an SVC-encoded video at different delivery traffic indication maps (DTIMs) such that each receiver can freely select either energy-intensive high quality video or energy-saving baseline quality video. Moreover, we enhance reliability by adding a functionality of intra-flow network coding (NC). As a measure of user satisfaction, we develop a multi-attribute utility model, and then, based on the utility model, we develop a Stakelberg game-based optimization framework to determine modulation and coding scheme (MCS) and the number of NC-generated packets for each layer. Through simulations, we confirm that the proposed scheme achieves higher user satisfaction by exhibiting performance gain of 16.4% to 47% over the legacy 802.11 scheme.
SUAVE: painless extension for an object-oriented VHDL

The SUAVE project aims to introduce object-oriented extensions to data modeling into VHDL in a way that does not disturb the existing language or its use. Designers regularly define abstract data types by using aspects of VHDL's type system, subprograms, and packages. The SUAVE approach builds on these basic mechanisms by strengthening the facilities for encapsulation and adding an inheritance mechanism. In addition to supporting object-orientation, these extended mechanisms improve the expressiveness of VHDL across the modeling spectrum, from high-level to gate-level. By choosing an incremental and evolutionary approach to extensions, SUAVE avoids major additions to the language that would complicate choice of mechanisms for expressing a design. The paper outlines the SUAVE extensions and illustrates their use through some examples. The mechanisms and examples are readily understood as incremental extensions to current modeling practices, hence "painless extension".
Terrain classification and identification of tree stems using ground‐based LiDAR

To operate autonomously in forested terrain, unmanned ground vehicles must be able to identify the load‐bearing surface of the terrain (i.e., the ground) and obstacles in the environment. To travel long distances, they must be able to track their position even when the forest canopy obstructs GPS signals, e.g., by tracking progress relative to tree stems. This paper presents a novel, robust approach for modeling the ground plane and tree stems in forests from a single viewpoint using a lightweight LiDAR scanner. Ground plane identification is implemented using a two‐stage approach. The first stage, a local height‐based filter, discards most nonground points. The second stage, based on a support vector machine classifier, identifies which of the remaining points belong to the ground. Main tree stems are modeled as cylinders or cones to estimate the diameter 130 cm above the ground plane. To fit these models, candidate main stem data are selected by finding points approximately 130 cm above the ground. These points are clustered into separate point clouds for each stem. Cylinders and cones are fit to each point cloud, and heuristic filters identify which fits correspond to tree stems. Experimental results from five forested environments demonstrate the effectiveness of this approach. For ground plane estimation, the overall classification accuracy was 86.28% with a mean error for the ground height of approximately 4.7 cm. For stem estimation, up to 50% of the main stems were accurately modeled using cones, with a root mean square diameter error of 13.2 cm. © 2012 Wiley Periodicals, Inc.
MIDDAS-M: Motif-Independent De Novo Detection of Secondary Metabolite Gene Clusters through the Integration of Genome Sequencing and Transcriptome Data

Many bioactive natural products are produced as “secondary metabolites” by plants, bacteria, and fungi. During the middle of the 20th century, several secondary metabolites from fungi revolutionized the pharmaceutical industry, for example, penicillin, lovastatin, and cyclosporine. They are generally biosynthesized by enzymes encoded by clusters of coordinately regulated genes, and several motif-based methods have been developed to detect secondary metabolite biosynthetic (SMB) gene clusters using the sequence information of typical SMB core genes such as polyketide synthases (PKS) and non-ribosomal peptide synthetases (NRPS). However, no detection method exists for SMB gene clusters that are functional and do not include core SMB genes at present. To advance the exploration of SMB gene clusters, especially those without known core genes, we developed MIDDAS-M, a motif-independent de novo detection algorithm for SMB gene clusters. We integrated virtual gene cluster generation in an annotated genome sequence with highly sensitive scoring of the cooperative transcriptional regulation of cluster member genes. MIDDAS-M accurately predicted 38 SMB gene clusters that have been experimentally confirmed and/or predicted by other motif-based methods in 3 fungal strains. MIDDAS-M further identified a new SMB gene cluster for ustiloxin B, which was experimentally validated. Sequence analysis of the cluster genes indicated a novel mechanism for peptide biosynthesis independent of NRPS. Because it is fully computational and independent of empirical knowledge about SMB core genes, MIDDAS-M allows a large-scale, comprehensive analysis of SMB gene clusters, including those with novel biosynthetic mechanisms that do not contain any functionally characterized genes.
Durability assessment of chemically treated Gigantochloa scortechinii in unsterile soil laboratory burial tests

Culms of Gigantochloa scortechinii belonging to two age groups, 2 and 4 years, were chemically treated with ammoniacal-copper-quaternary (ACQ), borax-boric acid (BBA) and copper-chrome-arsenate (CCA) at 1, 2, 4 and 8 per cent solution strength by soaking, vacuum impregnation and high pressure sap-displacement processes. Unsterile soil laboratory burial tests were then conducted on 2- and 4-year-old bamboo blocks. At the end of the testing period (8 weeks), the 2-year-old culms showed higher weight loss than the 4-year-old culms to attack of decay fungi. Among the treatments, the vacuum pressure treated blocks showed lower weight loss against decay fungi. The 4 per cent preservative solution strength was found to be sufficient in controlling the decay fungi. Â© KFRI 2007.
Distinctive Patterns of Evolution of the δ-Globin Gene (HBD) in Primates

In most vertebrates, hemoglobin (Hb) is a heterotetramer composed of two dissimilar globin chains, which change during development according to the patterns of expression of α- and β-globin family members. In placental mammals, the β-globin cluster includes three early-expressed genes, ε(HBE)-γ(HBG)-ψβ(HBBP1), and the late expressed genes, δ (HBD) and β (HBB). While HBB encodes the major adult β-globin chain, HBD is weakly expressed or totally silent. Paradoxically, in human populations HBD shows high levels of conservation typical of genes under strong evolutionary constraints, possibly due to a regulatory role in the fetal-to-adult switch unique of Anthropoid primates. In this study, we have performed a comprehensive phylogenetic and comparative analysis of the two adult β-like globin genes in a set of diverse mammalian taxa, focusing on the evolution and functional divergence of HBD in primates. Our analysis revealed that anthropoids are an exception to a general pattern of concerted evolution in placental mammals, showing a high level of sequence conservation at HBD, less frequent and shorter gene conversion events. Moreover, this lineage is unique in the retention of a functional GATA-1 motif, known to be involved in the control of the developmental expression of the β-like globin genes. We further show that not only the mode but also the rate of evolution of the δ-globin gene in higher primates are strictly associated with the fetal/adult β-cluster developmental switch. To gain further insight into the possible functional constraints that have been shaping the evolutionary history of HBD in primates, we calculated dN/dS (ω) ratios under alternative models of gene evolution. Although our results indicate that HBD might have experienced different selective pressures throughout primate evolution, as shown by different ω values between apes and Old World Monkeys + New World Monkeys (0.06 versus 0.43, respectively), these estimates corroborated a constrained evolution for HBD in Anthropoid lineages, which is unlikely to be related to protein function. Collectively, these findings suggest that sequence change at the δ-globin gene has been under strong selective constraints over 65 Myr of primate evolution, likely due to a regulatory role in ontogenic switches of gene expression.
Real-Time Detection of Drill Pipe Joints Using Improved YOLOv5x Model Applied to Drilling Operation Images

It is widely known that pipe assembly and disassembly still lacks automation. To enhance drilling efficiency, we propose an autonomous detection and positioning model based on improved YOLOv5x for drill pipe joints. Firstly, we use Activate or Not (ACON) activation function and Convolution Block Attention Module (CBAM) to enhance feature extraction and representation ability. Then, the loss function is changed from Complete IoU (CIOU) loss to Scale-Invariant IoU (SIOU) loss, which increases the accuracy of the bounding box regression. Finally, the predict heads are tailored to be more effective in detecting tiny targets. Following network training, the final drill pipe joint detection model, based on the improved YOLOv5x, achieved an average accuracy of 99.10%, a 3.5% improvement over the base YOLOv5x algorithm. The proposed method effectively promotes the intelligence of oil drilling equipment by quickly and accurately detecting drill pipe joints, consequently enhancing drilling operation efficiency.
How tools in IDEs shape developers' navigation behavior

Understanding source code is crucial for successful software maintenance, and navigating the call graph is especially helpful to understand source code [12]. We compared maintenance performance across four different development environments: an IDE without any call graph exploration tool, a Call Hierarchy tool as found in Eclipse, and the tools Stacksplorer [7]and Blaze [11]. Using any of the call graph exploration tools more developers could solve certain maintenance tasks correctly. Only Stacksplorer and Blaze, however, were also able to decrease task completion times, although the Call Hierarchy offers access to a larger part of the call graph. To investigate if this result was caused by a change in navigation behavior between the tools, we used a set of predictive models to create formally comparable descriptions of programmer navigation. The results suggest that the decrease in task completion times has been caused by Stacksplorer and Blaze promoting call graph navigation more than the Call Hierarchy tool.
Anosognosia in Patients With Cerebrovascular Lesions: A Study of Causative Factors

Background and Purpose: Psychological and biological hypotheses have been proposed to explain anosognosia. We correlated the presence of anosognosia with the presence and severity of psychiatric disturbances, neglect, intellectual impairments, and computed tomographic evidence of lesion size, location, and measurements of brain atrophy. Methods: A series of 80 patients with acute stroke were assessed using a battery of psychiatric and neuropsychological tests and computed tomography. Results: There were five main findings. First, 27 (28%) of the 96 patients originally screened showed anosognosia. Second, patients with anosognosia had significantly higher frequencies of hemispatial neglect and related phenomena, as well as deficits in recognizing facial emotions and in receptive prosody. Third, depression was equally frequent among patients with and without anosognosia. Fourth, patients with anosognosia had a significantly higher frequency of right hemisphere lesions, primarily involving the temporoparietal junction, thalamus, and basal ganglia. Fifth, patients with anosognosia showed significantly more subcortical brain atrophy, primarily involving the frontal white matter and diencephalic areas. Conclusions: The present study demonstrates that anosognosia does not “protect” stroke patients from depressive feelings; rather, it represents arousal‐attentional disorders after lesions in specific areas of the right hemisphere in nonaphasic patients with preexisting subcortical atrophy. (Stroke 1992;23:1446‐1453)
Cortical organization in gustation (Macaca mulatta).

THE EVIDENCE for a cortical representation of gustation in primates is meagre and inconsistent. In a recent publication, Patton (11) reviews the experiments implicating the parainsular opercular cortex near the foot of the central fissure. He agrees, however, that the experiments reviewed are inconclusive, especially with respect to the possible role of the Island of Reil. He does state that the evidence seems to vindicate Bornstein's (5, 6) rejection of the classical view which places the representation of taste in the temporal allocortex. However, such an interpretation fails to account for the finding that, following temporal lobectomy, monkeys show a marked change in dietary habits (8). 1 Several primate studies concerning these problems have been completed since Patton's review. No alteration of quinine acceptance thresholds follows extensive ablation of the lateral parieto-temporo-preoccipital cortex (2). Dissociation of the change in dietary habits from a change in quinine acceptance threshold has been reported in two series of experiments: Following temporal lobectomy or anteromedial temporal ablations a marked change in dietary habits from herbivorous to omniverous is not accompanied by any marked change in acceptance threshold for quinine (2, 13). On the other hand, ablations in the neighborhood of the anterior insula do alter quinine acceptance thresholds although no change in dietary habits can be observed (13). This report deals with experiments designed to amplify the latter observation.
Active Robust Learning

In many practical applications of learning algorithms, unlabeled data is cheap and abundant whereas labeled data is expensive. Active learning algorithms developed to achieve better performance with lower cost. Usually Representativeness and Informativeness are used in active learning algoirthms. Advanced recent active learning methods consider both of these criteria. Despite its vast literature, very few active learning methods consider noisy instances, i.e. label noisy and outlier instances. Also, these methods didn't consider accuracy in computing representativeness and informativeness. Based on the idea that inaccuracy in these measures and not taking noisy instances into consideration are two sides of a coin and are inherently related, a new loss function is proposed. This new loss function helps to decrease the effect of noisy instances while at the same time, reduces bias. We defined "instance complexity" as a new notion of complexity for instances of a learning problem. It is proved that noisy instances in the data if any, are the ones with maximum instance complexity. Based on this loss function which has two functions for classifying ordinary and noisy instances, a new classifier, named "Simple-Complex Classifier" is proposed. In this classifier there are a simple and a complex function, with the complex function responsible for selecting noisy instances. The resulting optimization problem for both learning and active learning is highly non-convex and very challenging. In order to solve it, a convex relaxation is proposed.
Behavior modes, pathways and overall trajectories: eigenvector and eigenvalue analysis of dynamic systems

One of the most fundamental principles in system dynamics is the premise that the structure of the system will generate its behavior. Such philosophical position has fostered the development of a number of formal methods aimed at understanding the causes of model behavior. To most in the field of system dynamics, behavior is commonly understood as modes of behavior (e.g., exponential growth, exponential decay, and oscillation) because of their direct association with the feedback loops (e.g., reinforcing, balancing, and balancing with delays, respectively) that generate them. Hence, traditional research on formal model analysis has emphasized which loops cause a particular "mode" of behavior, with eigenvalues representing the most important link between structure and behavior. The main contribution of this work arises from a choice to focus our analysis in the overall trajectory of a state variable - a broader definition of behavior than that of a specific behavior mode. When we consider overall behavior trajectories, contributions from eigenvectors are just as central as those from eigenvalues. Our approach to understanding model behavior derives an equation describing overall behavior trajectories in terms of both eigenvalues and eigenvectors. We then use the derivatives of both eigenvalues and eigenvectors with respect to link (or loop) gains to measure how they affect overall behavior trajectories over time. The direct consequence of focusing on behavior trajectories is that system dynamics researchers' reliance on eigenvalue elasticities can be seen as too-narrow a focus on model behavior - a focus that has excluded the short term impact of a change in loop (or link) gain in its analysis.