Miracle-dz/UniFAR-FTUs huggingface dataset:
Features extraction for signal classification based on Wigner-Ville distribution and mutual information criterion

The presented method deals with the extraction of features for the classification of non-stationary signals, when the process is only described through training data. The features are determined using the Wigner-Ville distribution (WVD). Three kinds of features are researched: the energy, the temporal expectation and the frequential expectation of the WVD restricted to specific regions. The restriction of the WVD is obtained by applying on the WVD a bidimensional Gaussian window. Given a feature type and a center position of the window in the time-frequency plane, the window parameters are optimized to provide the most discriminant feature. The discriminant nature is measured using a mutual information criterion. This provides a measure of the class separability suitable with any distribution law, and assuming no specific structure of the final classifier. The procedure has been validated with a classification problem of sleep EEG signals.
Reducing susceptibility to drought under growing conditions as set by farmers: The impact of new generation drought tolerant maize varieties in Uganda

Given the challenges brought about by the increasing frequency of climatic stressors (droughts) and other biotic challenges (pests and diseases), breeding for tolerance to these traits is now seen as an indispensable adjunct to the enhancement of yield potential. Drought tolerant (DT) maize varieties that do well under moderate drought and outperform (or do not underperform) commercial checks under normal rainfall are becoming available. This study examines the role of these maize varieties in mitigating the effects of drought on maize yields in drought-prone areas of eastern Uganda. We estimate the causal impact of these new generations of maize varieties using a multinomial endogenous switching regression treatment effect framework. The average treatment effects of adopting DT maize show that farmers who actually cultivated DT maize achieve 30% more yield than what they would have obtained with non-DT hybrids. Similarly, average treatment effects on the untreated, revealed that farmers who grew non-DT modern and local maize would have 32 and 54% more yield, respectively, if they instead had adopted DT maize. While being superior to all other maize seeds, the magnitudes of the benefits of DT maize varieties were more pronounced in areas with comparatively less rainfall amount providing strong evidence that the yield potential of these varieties is stable across space and a wide range of rainfall conditions. If the genetic gains of these varieties can be secured over the long term, their impacts in improving the resilience of maize farming systems are likely to be considerably large and favorable.
Putative cause of seizure-induced cognitive alterations: The oscillatory reconfiguration of seizure network

Introduction The dynamic reconfiguration of network oscillations is connected with cognitive processes. Changes in how neural networks and signaling pathways work are crucial to how epilepsy and related conditions develop. Specifically, there is evidence that prolonged or recurrent seizures may induce or exacerbate cognitive impairment. However, it still needs to be determined how the seizure brain configures its functional structure to shape the battle of strong local oscillations vs. slow global oscillations in the network to impair cognitive function. Methods In this paper, we aim to deduce the network mechanisms underlying seizure-induced cognitive impairment by comparing the evolution of strong local oscillations with slow global oscillations and their link to the resting state of healthy controls. Here, we construct a dynamically efficient network of pathological seizures by calculating the synchrony and directionality of information flow between nine patients’ SEEG signals. Then, using a pattern-based method, we found hierarchical modules in the brain’s functional network and measured the functional balance between the network’s local strong and slow global oscillations. Results and discussion According to the findings, a tremendous rise in strong local oscillations during seizures and an increase in slow global oscillations after seizures corresponded to the initiation and recovery of cognitive impairment. Specifically, during the interictal period, local strong and slow global oscillations are in metastable balance, which is the same as a normal cognitive process and can be switched easily. During the pre-ictal period, the two show a bimodal pattern of separate peaks that cannot be easily switched, and some flexibility is lost. During the seizure period, a single-peak pattern with negative peaks is showcased, and the network eventually transitions to a very intense strong local oscillation state. These results shed light on the mechanism behind network oscillations in epilepsy-induced cognitive impairment. On the other hand, the differential (similarity) of oscillatory reorganization between the local (non) epileptogenic network and the global network may be an emergency protective mechanism of the brain, preventing the spread of pathological information flow to more healthy brain regions.
Do they really support “your freedom of choice”? FoPNL and the food industry in Brazil

Introduction In 2020, Brazil approved the introduction of a new front-of-package nutrition labeling (FoPNL) in the format of a magnifying glass (MG) after years of discussion. There is currently a lack of understanding of the role of the food industry in that process. This study aimed to describe the corporate political activity (CPA) of the food industry and conflicts of interest situations, as they happened during the development and approval of a new FoPNL system in Brazil. Materials and methods We undertook bibliographical and documentary searches using material from food companies, trade associations and front groups involved in the regulatory process. We (1) collected information about the case study context, (2) collected data from documentary sources, and (3) prepared a synthesis of the results and a timeline of key events. Results/Discussion During the FoPNL regulatory process in Brazil, the food industry opposed the introduction of warning labels, a model supported by health authorities and implemented with success in other countries in Latin America. The food industry rather promoted a traffic-light labeling system, known to be less effective at guiding individuals to make healthier food choices. Later in the process, when it was evident that its preferred model would not be used, and a MG would rather be introduced, the food industry argued for the use of a different version of this FoPNL model. We found that the food industry, all along the process, was directly involved in and influenced the development of the FoPNL, by providing technical support, advising and lobbying policymakers. The food industry also established relationships with a consumer non-governmental organization and nutrition professional societies. The food industry also produced and disseminated information supporting its position in order to influence public opinion and high-level decision makers, and used the legal system to delay the process. Conclusion The FoPNL in Brazil is neither aligned with the recommendations of international health organizations nor with existing independent scientific evidence. The new FoPNL, as adopted in Brazil, reflects some of the preferences of the industry; it is likely that the influence of that sector during the legislative process was pivotal, even if its initial proposal was not adopted.
Tau phosphorylation and PAD exposure in regulation of axonal growth

Introduction: Tau is a microtubule associated phosphoprotein found principally in neurons. Prevailing dogma continues to define microtubule stabilization as the major function of tau in vivo, despite several lines of evidence suggesting this is not the case. Most importantly, tau null mice have deficits in axonal outgrowth and neuronal migration while still possessing an extensive microtubule network. Instead, mounting evidence suggests that tau may have a major function in the regulation of fast axonal transport (FAT) through activation of neuronal signaling pathways. Previous studies identified a phosphatase activating domain (PAD) at the tau N-terminal that is normally sequestered, but is constitutively exposed in tauopathies. When exposed, the PAD activates a signaling cascade involving PP1 and GSK3β which affects cellular functions including release of cargo from kinesin. Furthermore, we discovered that PAD exposure can be regulated by a single phosphorylation at T205. Exposure of the PAD is an early event in multiple tauopathies and a major contributing factor to neurodegeneration associated with tau hyperphosphorylation. However, effects of tau PAD exposure on anterograde FAT raised the interesting possibility that this pathway may be a mechanism for physiological regulation of cargo delivery through site-specific phosphorylation of tau and transient activation of PP1 and GSK3β. Significantly, there is already evidence of local control of PP1 and GSK3β at sites which require cargo delivery. Methods: To investigate this hypothesis, first we evaluated cellular localization of tau PAD exposure, pT205 tau phosphorylation, and active GSK3β in primary hippocampal neurons during development. Second, we analyzed the axonal outgrowth of tau knockout neurons following transfection with full length hTau40-WT, hTau40-ΔPAD, or hTau40-T205A. Results and Discussion: The results presented here suggest that transient activation of a PP1-GSK3β signaling pathway through locally regulated PAD exposure is a mechanism for cargo delivery, and thereby important for neurite outgrowth of developing neurons.
Collision avoidance for autonomous ship using deep reinforcement learning and prior-knowledge-based approximate representation

Reinforcement learning (RL) has shown superior performance in solving sequential decision problems. In recent years, RL is gradually being used to solve unmanned driving collision avoidance decision-making problems in complex scenarios. However, ships encounter many scenarios, and the differences in scenarios will seriously hinder the application of RL in collision avoidance at sea. Moreover, the iterative speed of trial-and-error learning for RL in multi-ship encounter scenarios is slow. To solve this problem, this study develops a novel intelligent collision avoidance algorithm based on approximate representation reinforcement learning (AR-RL) to realize the collision avoidance of maritime autonomous surface ships (MASS) in a continuous state space environment involving interactive learning capability like a crew in navigation situation. The new algorithm uses an approximate representation model to deal with the optimization of collision avoidance strategies in a dynamic target encounter situation. The model is combined with prior knowledge and International Regulations for Preventing Collisions at Sea (COLREGs) for optimal performance. This is followed by a design of an online solution to a value function approximation model based on gradient descent. This approach can solve the problem of large-scale collision avoidance policy learning in static-dynamic obstacles mixed environment. Finally, algorithm tests were constructed though two scenarios (i.e., the coastal static obstacle environment and the static-dynamic obstacles mixed environment) using Tianjin Port as an example and compared with multiple groups of algorithms. The results show that the algorithm can improve the large-scale learning efficiency of continuous state space of dynamic obstacle environment by approximate representation. At the same time, the MASS can efficiently and safely avoid obstacles enroute to reaching its target destination. It therefore makes significant contributions to ensuring safety at sea in a mixed traffic involving both manned and MASS in near future.
Predictive model of language deficit after removing glioma involving language areas under general anesthesia

Purpose To establish a predictive model to predict the occurrence of language deficit for patients after surgery of glioma involving language areas (GILAs) under general anesthesia (GA). Methods Patients with GILAs were retrospectively collected in our center between January 2009 and December 2020. Clinical variables (age, sex, aphasia quotient [AQ], seizures and KPS), tumor-related variables (recurrent tumor or not, volume, language cortices invaded or not, shortest distance to language areas [SDLA], supplementary motor area or premotor area [SMA/PMA] involved or not and WHO grade) and intraoperative multimodal techniques (used or not) were analyzed by univariate and multivariate analysis to identify their association with temporary or permanent language deficits (TLD/PLD). The predictive model was established according to the identified significant variables. Receiver operating characteristic (ROC) curve was used to assess the accuracy of the predictive model. Results Among 530 patients with GILAs, 498 patients and 441 patients were eligible to assess TLD and PLD respectively. The multimodal group had the higher EOR and rate of GTR than conventional group. The incidence of PLD was 13.4% in multimodal group, which was much lower than that (27.6%, P<0.001) in conventional group. Three factors were associated with TLD, including SDLA (OR=0.85, P<0.001), preoperative AQ (OR=1.04, P<0.001) and multimodal techniques used (OR=0.41, P<0.001). Four factors were associated with PLD, including SDLA (OR=0.83, P=0.001), SMA/PMA involved (OR=3.04, P=0.007), preoperative AQ (OR=1.03, P=0.002) and multimodal techniques used (OR=0.35, P<0.001). The optimal shortest distance thresholds in detecting the occurrence of TLD/PLD were 1.5 and 4mm respectively. The optimal AQ thresholds in detecting the occurrence of TLD/PLD were 52 and 61 respectively. The cutoff values of the predictive probability for TLD/PLD were 23.7% and 16.1%. The area under ROC curve of predictive models for TLD and PLD were 0.70 (95%CI: 0.65-0.75) and 0.72 (95%CI: 0.66-0.79) respectively. Conclusion The use of multimodal techniques can reduce the risk of postoperative TLD/PLD after removing GILAs under general anesthesia. The established predictive model based on clinical variables can predict the probability of occurrence of TLD and PLD, and it had a moderate predictive accuracy.
Can alexithymia be assessed through an interview in adolescents? The Toronto Structured Interview for Alexithymia: Reliability, concurrent validity, discriminant validity, and relationships with emotional-behavioral symptoms

Alexithymia is connected to adolescents' psychopathology, but the current methods of assessment present limitations. The Toronto Structured Interview for Alexithymia (TSIA) was developed to overcome the limits of the main used self-rating scale in adults, but no studies investigated its feasibility with adolescents. This study involved 95 community adolescents aged 12–19 years. Adolescents were assessed with the TSIA, the 20-item Toronto Alexithymia Scale (TAS-20), the Verbal Comprehension Index of the WISC-IV for verbal skills, and the Child Behavior Checklist and Youth Self Report for emotional-behavioral symptoms. The aims were to investigate the TSIA internal consistency, concurrent validity with the TAS-20, discriminant validity with participants' verbal skills, and relationships with emotional-behavioral symptoms. TSIA showed good internal consistency, concurrent validity with the TAS-20 (except for factor DDF), and independence by participants' verbal skills, but few relationships with emotional-behavioral symptoms. In conclusion, TSIA showed some good psychometric proprieties but little convergence with research findings obtained with the TAS-20, suggesting the need for further research to check the feasibility of using the TSIA with adolescents. Meanwhile, a precautionary multi-method assessment of alexithymia is recommended.
Tipping the scales of understanding: An engineering approach to design and implement whole-body cardiac electrophysiology experimental models

The study of cardiac electrophysiology is built on experimental models that span all scales, from ion channels to whole-body preparations. Novel discoveries made at each scale have contributed to our fundamental understanding of human cardiac electrophysiology, which informs clinicians as they detect, diagnose, and treat complex cardiac pathologies. This expert review describes an engineering approach to developing experimental models that is applicable across scales. The review also outlines how we applied the approach to create a set of multiscale whole-body experimental models of cardiac electrophysiology, models that are driving new insights into the response of the myocardium to acute ischemia. Specifically, we propose that researchers must address three critical requirements to develop an effective experimental model: 1) how the experimental model replicates and maintains human physiological conditions, 2) how the interventions possible with the experimental model capture human pathophysiology, and 3) what signals need to be measured, at which levels of resolution and fidelity, and what are the resulting requirements of the measurement system and the access to the organs of interest. We will discuss these requirements in the context of two examples of whole-body experimental models, a closed chest in situ model of cardiac ischemia and an isolated-heart, torso-tank preparation, both of which we have developed over decades and used to gather valuable insights from hundreds of experiments.
Dynamic nanomechanics of zinc oxide nanowires

The electromechanical resonances of individual zinc oxide nanowires were induced by alternative current (ac) signals inside a transmission electron micrcrope, which have been used to measure the mechanical quality factors (Q) and elastic bending moduli (E) of a single zinc oxide (ZnO) nanowire. The resonance amplitudes were tuned by the applied ac voltages. The results indicate that Q drops as much as ∼80% with increasing resonance amplitudes, while E slightly decreases (∼3%). The mechanism of the amplitude-dependent mechanical properties is discussed. This study on dynamic nanomechanics of ZnO nanowires is significant for their cantilever-based applications.
Phenotypic screening and molecular characterization of cassava mosaic disease resistance in Côte d'Ivoire cassava germplasm

Cassava is the staple food crop for hundreds of millions of people in Africa. In Côte d'Ivoire, it is a main source of calories for over 26 million people. However, cassava mosaic disease (CMD), caused by cassava mosaic geminiviruses (CMGs) threaten its production. The development, adoption, and use of CMD resistant varieties remain a key CMD management strategy. Therefore, 610 accessions from the Côte d'Ivoire national cassava germplasm maintained by Centre National de Recherche Agronomique (CNRA) research stations in the cities of Man and Bouaké were characterized to assess their resistance to CMD. We found 72 accessions which were symptomless at both sites. Thirty five out of these 72 accessions were infected by African cassava mosaic virus (ACMV) without any CMD symptoms and 37 were virus free. None of the 72 symptomless accessions were infected by East African cassava mosaic Cameroon virus (EACMCMV). The remaining 538 accessions were CMD infected and displayed clear CMD symptoms. The promising 72 accessions (10 locals and 62 improved) were then tested for the presence of resistance genes, CMD1, CMD2 or CMD3. Except for 2 accessions for which no resistance gene was found, the remaining 70 accessions contained one or more resistance genes. Genotyping of the 69 symptomless accessions revealed that 56 were unique genotypes and 13 were potential duplicates. Accessions were structured in three groups with the variabilities at the individual's level. These findings reveal the existence of potential tolerant/resistant cassava accessions in CNRA's germplasm, which can contribute to CMD control and the increase of cassava production in Côte d'Ivoire.
LDP alleviates TKI-induced proteinuria through reversing the expression of RelA in renal tissues

Tyrosine kinase inhibitors (TKIs), as an important tumor therapy, can induce severe proteinuria that significantly affects anti-tumor therapy. Existing therapies against proteinuria induced by other etiologies are currently ineffective for TKI-induced proteinuria. It has been shown that various types of proteinuria are related to podocyte damage caused by changes in the RelA signaling pathway. Our experiments confirmed that TKIs activate the renal RelA signaling pathway, and induce death of podocytes and destruction of the glomerular filtration barrier. Here we found that Liuwei Dihuang Pill (LDP) attenuated the inflammatory injury of podocytes through inhibiting activation of RelA, and subsequently relieved TKI-related proteinuria and prevented the progression of TMA and FSGS. Our finding indicated that LDP may be effective for the treatment of TKI-induced proteinuria, which is clinically significant.
Comparative transcriptomic and proteomic analysis reveals common molecular factors responsive to heat and drought stresses in sweetpotaoto (Ipomoea batatas)

Introduction Crops are affected by various abiotic stresses, among which heat (HT) and drought (DR) stresses are the most common in summer. Many studies have been conducted on HT and DR, but relatively little is known about how drought and heat combination (DH) affects plants at molecular level. Methods Here, we investigated the responses of sweetpotato to HT, DR, and DH stresses by RNA-seq and data-independent acquisition (DIA) technologies, using controlled experiments and the quantification of both gene and protein levels in paired samples. Results Twelve cDNA libraries were created under HT, DR, and DH conditions and controls. We identified 536, 389, and 907 DEGs in response to HT, DR, and DH stresses, respectively. Of these, 147 genes were common and 447 were specifically associated with DH stress. Proteomic analysis identified 1609, 1168, and 1535 DEPs under HT, DR, and DH treatments, respectively, compared with the control, of which 656 were common and 358 were exclusive to DH stress. Further analysis revealed the DEGs/DEPs were associated with heat shock proteins, carbon metabolism, phenylalanine metabolism, starch and cellulose metabolism, and plant defense, amongst others. Correlation analysis identified 6465, 6607, and 6435 co-expressed genes and proteins under HT, DR, and DH stresses respectively. In addition, a combined analysis of the transcriptomic and proteomic data identified 59, 35, and 86 significantly co-expressed DEGs and DEPs under HT, DR, and DH stresses, respectively. Especially, top 5 up-regulated co-expressed DEGs and DEPs (At5g58770, C24B11.05, Os04g0679100, BACOVA_02659 and HSP70-5) and down-regulated co-expressed DEGs and DEPs (AN3, PMT2, TUBB5, FL and CYP98A3) were identified under DH stress. Discussion This is the first study of differential genes and proteins in sweetpotato under DH stress, and it is hoped that the findings will assist in clarifying the molecular mechanisms involved in sweetpotato resistance to heat and drought stress.