Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification and Validation of Reference Genes for Gene Expression Analysis in Different Development Stages of Amylostereum areolatum

A strict relationship exists between the Sirex noctilio and the Amylostereum areolatum, which is carried and spread by its partner. The growth and development of this symbiotic fungus is key to complete the life history of the Sirex woodwasp. Real-time quantitative polymerase chain reaction (RT-qPCR) is used to measure gene expression in samples of A. areolatum at different growth stages and explore the key genes and pathways involved in the growth and development of this symbiotic fungus. To obtain accurate RT-qPCR data, target genes need to be normalized by reference genes that are stably expressed under specific experimental conditions. In our study, the stability of 10 candidate reference genes in symbiotic fungal samples at different growth and development stages was evaluated using geNorm, NormFinder, BestKeeper, delta Ct methods, and RefFinder. Meanwhile, laccase1 was used to validate the stability of the selected reference gene. Under the experimental conditions of this study, p450, CYP, and γ-TUB were identified as suitable reference genes. This work is the first to systematically evaluate the reference genes for RT-qPCR results normalization during the growth of this symbiotic fungus, which lays a foundation for further gene expression experiments and understanding the symbiotic relationship and mechanism between S. noctilio and A. areolatum.
A Pose Estimation and Optimization Method for Mobile Manipulator’s End-effectors Based on Stereo Vision and ICoP Algorithm*

The accurate pose estimation of the mobile manipulator’s end-effector is pivotal in mobile machining of large and complex components. In this paper, a pose tracking method based on binocular stereo vision in large-scale workspace is presented. The binocular camera and numbers of planar coded markers are used to estimate the pose of the mobile manipulator’s end-effector. Specifically, the binocular camera measures its relative pose by simultaneously photographing the fiducial markers on the ground and the tracking markers on the end-effector. Through the calibration of the fiducial markers’ absolute position, the pose of the end-effector is obtained. Besides, considering the influence of visual measurement error and calibration error on pose estimation accuracy, a robust high-accuracy poses estimation method based on iterative corresponding point optimization (ICoP) algorithm is proposed to deal with the influence of measurement error on pose estimation accuracy, which is more robust to data with large errors. Simulated comparison with the existing Chan’s algorithm and corresponding point algorithm is also studied to verify the superiority of the proposed method. A practical experiment was also performed and the results that the poses estimation accuracy for the mobile manipulator’s end-effector are ±0.215 mm and ±0.016° within the range of 6 m × 4 m × 1.5 m, respectively, demonstrates the proposed methods are effective.
A-PSPNet: A novel segmentation method of renal ultrasound image

Hydronephrosis is a common renal disease in children which can lead to a series of complications, and ultrasonography is a basic examination usually performed on suspected hydronephrosis patients. If we can use deep learning approaches to judge and grade the disease in the ultrasonic examination stage, we can save a lot of manpower, medical resources, money, and help the suffered patients. For the semantic segmentation of kidney ultrasound image, we designed an Attention-based Pyramid Scene Parsing Network (A-PSPNet), the core of which is the basic feature extraction network combining Convolutional Block Attention Module (CBAM) and pyramid analysis module. Experiments were carried out on a hydronephrosis dataset containing 1850 annotated ultrasound images, including the arrangement of attention units, statistical computing power, and comparison of the effectiveness between the benchmark and our proposed method. Our constructed model achieved better segmentation performance than benchmarks with only little extra overhead, which validated the lightweight and effectiveness of the model.
Growth and Wood Trait Relationships of Alnus glutinosa in Peatland Forest Stands With Contrasting Water Regimes

Human-driven peatland drainage has occurred in Europe for centuries, causing habitat degradation and leading to the emission of greenhouse gases. As such, in the last decades, there has been an increase in policies aiming at restoring these habitats through rewetting. Alder (Alnus glutinosa L.) is a widespread species in temperate forest peatlands with a seemingly high waterlogging tolerance. Yet, little is known about its specific response in growth and wood traits relevant for tree functioning when dealing with changing water table levels. In this study, we investigated the effects of rewetting and extreme flooding on alder growth and wood traits in a peatland forest in northern Germany. We took increment cores from several trees at a drained and a rewetted stand and analyzed changes in ring width, wood density, and xylem anatomical traits related to the hydraulic functioning, growth, and mechanical support for the period 1994–2018. This period included both the rewetting action and an extreme flooding event. We additionally used climate-growth and climate-density correlations to identify the stand-specific responses to climatic conditions. Our results showed that alder growth declined after an extreme flooding in the rewetted stand, whereas the opposite occurred in the drained stand. These changes were accompanied by changes in wood traits related to growth (i.e., number of vessels), but not in wood density and hydraulic-related traits. We found poor climate-growth and climate-density correlations, indicating that water table fluctuations have a stronger effect than climate on alder growth. Our results show detrimental effects on the growth of sudden water table changes leading to permanent waterlogging, but little implications for its wood density and hydraulic architecture. Rewetting actions should thus account for the loss of carbon allocation into wood and ensure suitable conditions for alder growth in temperate peatland forests.
Comparing the Outcomes of Population-averaged and Personalised Input Feature Selection for Transhumeral Prosthetic Interfaces

An interface for a powered upper limb prosthesis is designed to achieve the target poses intended by the human user as interpreted from input features measured from a variety of sensors typically worn on the residual limb. Selection of which input features to use in the interface is usually done based on which features provide the best likelihood to identify the intended target poses. This work investigates the outcomes of the prosthetic interfaces constructed with input features selected based on the performance of all subjects (population-averaged) vs. the performance of individual subjects (personalised). Specifically, two outcomes are evaluated. First, the diversity in the resulting input feature sets across different subjects is evaluated. Second, the accuracy in identifying the intended target pose using the input features selected through personalised and population-averaged data are analysed and compared. The experiment was conducted with 10 able-bodied subjects in a virtual reality (VR) platform. The corresponding kinematic information of their arm movements and muscle activities were recorded and utilised to construct the input features in the scenario of transhumeral prostheses. The outcomes show a significant variation in the resulting input feature sets from subject to subject. The accuracy of the personalised feature sets is found to be higher in classifying the intended target poses. For the case of selecting 2 out of the 41 input features constructed from the recorded sensor data, none of the 10 subjects shares any common set of input features and the accuracy is improved by 10.4±6.8% with the personalised selection. The outcomes demonstrate the extent of person-to-person variation that needs to be taken into account when designing prosthetic interfaces and the quantified potential gain (albeit in a specific application) from personalising interfaces.
SSVEP-Aided Recognition of Internally and Externally Directed Attention from Brain Activity

Steady-state visually evoked potentials (SSVEP) are a widely used paradigm for the detection of attended objects. However, their aid in the recognition of other attentional states has not yet been studied in detail. In this study (n=21), we assessed the benefits of including SSVEP stimuli as probes in a screen-based task to classify internal and external attention based on 16-channel EEG data offline. Previous studies have shown that the distinction between these two attentional states based on brain activity is possible. We compared several SSVEP-stimulus settings with a baseline where no SSVEP stimulus was present. Different flickering frequencies and stimulus placements were evaluated for the possibilities of different experimental setups. We found that the influence of the stimulus on the classification accuracy is highly dependent on the settings. The Linear Discriminant Analysis (LDA) performance increased significantly when an SSVEP-evoking stimulus with a low flickering frequency was present in the center of fixation. As well as when a Canonical Correlation Analysis (CCA)-coefficient was added as the SSVEP-specific feature to a generic band-power feature set. A simple training-free, person-independent threshold approach for internal and external attention detection resulted in accuracies significantly higher than chance based on SSVEP-features that were calculated only on three occipital electrodes. These results show that such stimuli can aid the recognition of internal and external attention. Thus, they can be used in experiments or applications for a more robust detection rate. Specifically, they could improve SSVEP-based BCI paradigms by adding another level of attention-awareness.
Immediate Transurethral Plasma Kinetic Enucleation of the Prostate Gland for Treatment of Benign Prostatic Hyperplasia-Associated Massive Hemorrhage: A Single-Center Experience

Purpose: Benign prostatic hyperplasia-associated massive hemorrhage is a urological emergency. We evaluated the outcome from immediate transurethral plasma kinetic enucleation of the prostate gland (i-TUPKEP) for BHM treatment. Methods: We retrospectively analyzed the records of 49 patients with acute BMH who underwent i-TUPKEP between January 2014 and November 2018 at our institution. The hemostatic effect, International Prostate Symptom Score (IPSS), and quality of life (QoL) score were evaluated preoperatively as well as 3, 6, and 12 months postoperatively. Postoperative follow-up also included measurement of the peak flow rate (Qmax) and post-void residual urine volume (PVR). Clinical characteristics, weight of resected tissue, duration of bladder irrigation, duration of hospital stay, complications, as well as the time required for enucleation and resection, were recorded. Results: BMH causes were attributed to transurethral surgery (17/49, 34.7%), violent catheterization (13/49, 26.5%), cystoscopy (10/49, 20.4%), and urethral dilatation (9/49, 18.4%). Bleeding was from different sites of prostate-gland tissues during i-TURKEP. i-TUPKEP-controlled BMH effectively induced immediate, notable, and lasting improvements in the IPSS and QoL score. Qmax was close to normal, and the PVR was within the physiological range, postoperatively. Long-term complications were not observed. Conclusion: Our preliminary data suggest that i-TUPKEP is a feasible method for controlling BHM and relieving BPH symptoms.
An ASP-based solution to the Operating Room Scheduling with care units

The optimization of daily operating room surgery schedule can be problematic because of many constraints, like to determine the start time of different surgeries and allocating the required resources, including the availability of beds in different units. Recently, Answer Set Programming (ASP) has been successfully employed for addressing and solving real-life scheduling and planning problems in the health-care domain. In this paper we present an enhanced solution using ASP for scheduling and rescheduling operating rooms taking explicitly into considerations the availability of beds for intensive and post-anesthesia care units. We tested our solution on different benchmarks with realistic parameters. The results of our experiments show that ASP is a suitable methodology for solving also such enhanced problem.
German Laypeople’s Willingness to Donate Toward Insect Conservation: Application of an Extended Protection Motivation Theory

It is essential to engage the public in conservation measures to conserve insects. We investigate the Protection Motivation Theory (PMT), as well as knowledge, attitudes, and sociodemographic variables (gender, age, education level, and income) as predictors of willingness to donate (WTD) and actual donations to insect conservation for a representative German sample (N = 515; MAge = 49.36, SD = 16.73; female = 50.1%). The PMT subcomponents severity, self-efficacy, and response efficacy, as well as attitudes toward insects, income, and education level, significantly predicted WTD. In contrast, severity, response barriers, age, gender, and the WTD significantly influenced actual donations. Overall, components of the PMT have high predictive power for both dependent variables. Our results suggest that an intention-behavior gap exists between the intention to donate and the actual donation toward insect conservation. Measures to increase WTD and actual donations for insect conservation are discussed.
The Draft Genome of Cryptocaryon irritans Provides Preliminary Insights on the Phylogeny of Ciliates

State Key Laboratory of Large Yellow Croaker Breeding, Ningde Fufa Fisheries Company Limited, Ningde, China, State Key Laboratory of Marine Environmental Science, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China, Biotechnology Institute, Fujian Academy of Agricultural Sciences, Fuzhou, China, Fujian Key Laboratory of Genetics and Breeding of Marine Organisms, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China
Neuropsychiatric Symptoms Mediated the Relationship Between Odor Identification and Cognition in Alzheimer's Disease Spectrum: A Structural Equation Model Analysis

Background: Odor identification dysfunction is an early predictor of the development of Alzheimer's disease (AD), but neuropsychiatric symptoms (NPS), which are common in AD and mild cognitive impairment (MCI), are also associated with odor identification dysfunction. Whether NPS affect the specificity of using odor identification dysfunction to predict cognitive decline in AD and MCI remains unclear. Methods: Patients (233 with MCI and 45 with AD) and 45 healthy controls (HCs) underwent assessments of odor identification (Sniffin' Sticks), NPS (Neuropsychiatric Inventory-12), and cognitive function (global cognition, memory, language, executive function, visual-spatial skill, and attention). Structural equation modeling (SEM) with bootstrapping estimation was conducted to explore the relationships between odor identification, NPS, and cognition. Results: Patients with NPS showed significantly worse performance in odor identification and cognition than patients without NPS and HCs. The SEM showed odor identification to be positively associated with cognition, and cognition had special indirect effects on odor identification through affective and psychosis symptoms (two factors extracted from Neuropsychiatric Inventory-12). Additionally, affective and psychosis symptoms partially mediated the effect of cognition on odor identification. Conclusion: Neuropsychiatric symptoms are associated with odor identification dysfunction in patients with AD and MCI. Studies exploring the relationship between odor identification dysfunction and cognitive decline in patients with AD and MCI should include an assessment of affective and psychosis symptoms, and adjust their confounding effects.
Sub- and Supra-Second Timing in Auditory Perception: Evidence for Cross-Domain Relationships

Previous studies indicate that there are at least two levels of temporal processing: the sub- and supra-second domains. The relationship between these domains remains unclear. The aim of this study was to test whether performance on the sub-second level is related to that on the supra-second one, or whether these two domains operate independently. Participants were 118 healthy adults (mean age = 23 years). The sub-second level was studied with a temporal-order judgment task and indexed by the Temporal Order Threshold (TOT), on which lower values corresponded to better performance. On the basis of TOT results, the initial sample was classified into two groups characterized by either higher temporal efficiency (HTE) or lower temporal efficiency (LTE). Next, the efficiency of performance on the supra-second level was studied in these two groups using the subjective accentuation task, in which participants listened to monotonous sequences of beats and were asked to mentally accentuate every n-th beat to create individual rhythmic patterns. The extent of temporal integration was assessed on the basis of the number of beats being united and better performance corresponded to longer units. The novel results are differences between groups in this temporal integration. The HTE group integrated beats in significantly longer units than did the LTE group. Moreover, for tasks with higher mental load, the HTE group relied more on a constant time strategy, whereas the LTE group relied more on mental counting, probably because of less efficient temporal integration. These findings provide insight into associations between sub- and supra-second levels of processing and point to a common time keeping system, which is active independently of temporal domain.
Use of 30-Hz Accelerated iTBS in Drug-Resistant Unipolar and Bipolar Depression in a Public Healthcare Setting: A Case Series

Background: Depressive episodes, especially when resistant to pharmacotherapy, are a hard challenge to face for clinicians and a leading cause of disability worldwide. Neuromodulation has emerged as a potential therapeutic option for treatment-resistant depression (TRD), in particular transcranial magnetic stimulation (TMS). In this article, we present a case series of six patients who received TMS with an accelerated intermittent theta-burst stimulation (iTBS) protocol in a public healthcare setting. Methods: We enrolled a total number of six participants, affected by a treatment-resistant depressive episode, in either Major Depressive Disorder (MDD) or Bipolar Disorder (BD). Patients underwent an accelerated iTBS protocol, targeted to the left dorsolateral prefrontal cortex (DLPFC), 3-week-long, with a total of 6 days of overall stimulation. On each stimulation day, the participants received 3 iTBS sessions, with a 15-min pause between them. Patients were assessed by the Hamilton Rating Scale for Depression (HAM-D), the Montgomery-Asberg Depression Rating Scale (MADRS), the Hamilton Rating Scale for Anxiety (HAM-A), and the Mania Rating Scale (MRS). At baseline (T0), at the end of the second week (T1), and at the end of the cycle of stimulation (T2). Results: The rANOVA (repeated Analysis of Variance) statistics showed no significant effect of time on the rating scale scores, with a slight decrease in MADRS scores and a very slight increase in HAM-A and HAM-D scores. No manic symptoms emerged during the entire protocol. Conclusions: Although accelerated iTBS might be considered a less time-consuming strategy for TMS administration, useful in a public healthcare setting, our results in a real-word six-patient population with TRD did not show a significant effect. Further studies on wider samples are needed to fully elucidate the potential of accelerated iTBS protocols in treatment-resistant depression.
An Impending Paradigm Shift in Motor Imagery Based Brain-Computer Interfaces

The development of reliable assistive devices for patients that suffer from motor impairments following central nervous system lesions remains a major challenge in the field of non-invasive Brain-Computer Interfaces (BCIs). These approaches are predominated by electroencephalography and rely on advanced signal processing and machine learning methods to extract neural correlates of motor activity. However, despite tremendous and still ongoing efforts, their value as effective clinical tools remains limited. We advocate that a rather overlooked research avenue lies in efforts to question neurophysiological markers traditionally targeted in non-invasive motor BCIs. We propose an alternative approach grounded by recent fundamental advances in non-invasive neurophysiology, specifically subject-specific feature extraction of sensorimotor bursts of activity recorded via (possibly magnetoencephalography-optimized) electroencephalography. This path holds promise in overcoming a significant proportion of existing limitations, and could foster the wider adoption of online BCIs in rehabilitation protocols.
Evaluation of Socially-Aware Robot Navigation

As mobile robots are increasingly introduced into our daily lives, it grows ever more imperative that these robots navigate with and among people in a safe and socially acceptable manner, particularly in shared spaces. While research on enabling socially-aware robot navigation has expanded over the years, there are no agreed-upon evaluation protocols or benchmarks to allow for the systematic development and evaluation of socially-aware navigation. As an effort to aid more productive development and progress comparisons, in this paper we review the evaluation methods, scenarios, datasets, and metrics commonly used in previous socially-aware navigation research, discuss the limitations of existing evaluation protocols, and highlight research opportunities for advancing socially-aware robot navigation.
mMCP7, a Mouse Ortholog of δ Tryptase, Mediates Pelvic Tactile Allodynia in a Model of Chronic Pelvic Pain

Chronic prostatitis/Chronic pelvic pain syndrome (CP/CPPS) is a condition that affects a large number of men and has unknown etiology. We have previously demonstrated the presence of elevated levels of mast cell tryptase in expressed prostatic secretions (EPS) of CP/CPPS patients. In a murine model of CP/CPPS, we showed tryptase and its cognate receptor PAR2 as critical to the development of pelvic pain and lower urinary tract symptoms. Here, we extend these observations to demonstrate that an isoform of tryptase called delta (δ)-tryptase, is elevated in the EPS of patients with CP/CPPS and is correlated with pelvic pain symptoms. Using an Escherichia coli (CP1) -induced murine model of CP/CPPS, we demonstrated a differential response in C57BL/6J and NOD/ShiLtJ mice, with C57BL6/J mice being resistant to an increase in pelvic tactile allodynia, despite having equivalent levels of activated mast cells in the prostate. Activated tryptase+ve mast cells were observed to be in closer apposition to PGP9.5+ve nerve fibers in the prostate stroma of NOD/ShiLtJ in comparison to C57BL/6J mice. The mouse ortholog of δ-tryptase, mouse mast cell protease 7 (mMCP7) has been reported to be unexpressed in C57BL/6J mice. We confirmed the absence of mMCP7 in the prostates of C57BL/6J and its presence in NOD/ShiLtJ mice. To evaluate a role for mMCP7 in the differential allodynia responses, we performed direct intra-urethral instillations of mMCP7 and the beta (β)-tryptase isoform ortholog, mMCP6 in the CP1-infection model. mMCP7, but not mMCP6 was able to induce an acute pelvic allodynia response in C57BL/6J mice. In-vitro studies with mMCP7 on cultured mast cells as well as dissociated primary neurons demonstrated the ability to induce differential activation of pain and inflammation associated molecules compared to mMCP6. We conclude that mMCP7, and possibility its human ortholog δ-tryptase, may play an important role in mediating the development of pelvic tactile allodynia in the mouse model of pelvic pain and in patients with CP/CPPS.