Dynamic channel pruning is widely used in model compression to improve the efficiency of neural networks. Although dynamic pruning can remove redundant channels dynamically, the parameters still remain unchanged, which can limit the performance as the response of each neuron changes with different inputs. In this paper, we propose a novel dynamic channel pruning method with adaptive weight learning, which can adaptively adjust both the parameters and widths of the filters simultaneously. Specifically, we design an adaptive-weight convolution module, which can be customized for different inputs under the guidance of global context information to capture representative local patterns and synthesize interested features. At the same time, we utilize a channel importance prediction module to predict the saliency of each channel. Based on the channel saliency, unimportant channels can be removed dynamically to speed up the convolution. These two modules work jointly to achieve a good trade-off between model performance and computational complexity. Experiments on image classification and object detection tasks demonstrate that our method can greatly reduce the computational burden while maintaining the performance, which outperforms state-of-the-art methods.

Background and purpose: Osteoporotic fracture (OPF) disrupts the balance of bone formation by osteoblasts and bone resorption by osteoclasts. we found that compounds from herbal medicine, Invigorate the Spleen and Tonify the Kidney Formula (ISTKF) accelerates fracture healing. Identification of the active ingredients in ISFKF and the mechanisms of fracture healing involved was carried out. Experimental approach: Using Pax7-CreERT2/+;β-cateninfx/fx conditional knockout(cKO) mice, the mechanisms involved in promoting fracture healing were assessed by looking at the fracture site and its surrounding muscle tissue, using various experiments to analyze the signaling involved. The key molecules and compounds involved in this fracture-promoting effect were identified by HPLC analysis. Key results: Histopathological staining of muscles and micro-CT of bone revealed that β-catenin knockout in skeletal muscle satellite cells (SMSCs) gives rise to sarcopenia and osteopenia, and ISTKF significantly promoted muscle firmness and also increased proliferation and osteogenic differentiation of SMSCs. ISTKF inhibits the significant decrease in bone mass and the destruction of bone microstructure in Pax7-CreERT2/+;β-cateninfx/fx cKO mice. ISTKF mediates the β-catenin signaling pathway to mobilize SMSCs to migrate to the fracture site, promotes the osteogenic differentiation of SMSCs, and promotes the activity of cartilage and osteoblasts at the OPF site. When β-catenin is promoted by ISTKF, it promotes skeletal muscle fiber remodeling and fractures healing. Conclusion and implications: These results provided the first practical evidence for ISTKF-mediated regulation of SMSCs via β-catenin to promote fracture healing with clinical implications that would aid in the treatment of delayed healing and nonunion of fractures.

Conflicts at work are usually seen as obstacles to organizational performance. thus, in their seminal work on the theory of organizations. March define conflict as a blockage of the normal mechanisms of decision making. at the same time, according to a study of the cabinet opp, carried out in 2008 with 5000 European and American employees, 85% of French employees say they are regularly confronted with a conflict at work. the scale and consequences of conflicts should therefore lead organizations to be equipped to process them. however, according to this same study, 73% of employees have never received training and 45% expect their manager to intervention. conflict management is therefore a real challenge. Introduction:

A document by Gaurav Rao. Click on the document to view its contents.

Classic autoimmune hepatitis (AIH) is a multifarious hepatic pathology of undefined etiology that leads to liver damage directed by the body’s own immune system. In this case report, we described how the early diagnosis and treatment of seronegative autoimmune hepatitis (SAIH) with steroids could be beneficial.

Primary breast lymphomas are a very rare group of breast malignancies .Imaging findings in lymphoma are nonspecific and whole body imaging is an essential part of the workup to rule out disease in other parts of the body and to be labelled as primary breast lymphoma

We present a case of a 75-year-old male who presented with constipation, nausea, and vomiting for 4 days. Two diverticula were discovered 1 and 2 feet away from the duodenojejunal (DJ) junction. Due to excessive ileal edema, ileal resection, and a double barrel ileostomy was performed.

Engineering biological systems to test new pathway variants containing different enzyme homologs is laborious and time-consuming. To tackle this challenge, a novel strategy was developed for rapidly prototyping enzyme homologs by combining cell-free protein synthesis (CFPS) with split GFP. This strategy featured two main advantages: 1) dozens of enzyme homologs were parallelly produced by CFPS within hours, and 2) the expression level and activity of each homolog was determined [simultaneously](javascript:;) by using the split GFP assay. As a model, this strategy was applied to optimize a 3-step pathway for nicotinamide mononucleotide (NMN) synthesis. Ten enzyme homologs from different organisms were selected for each step. Here, the most productive homolog of each step was identified within 24 h rather than weeks or months. Finally, the titer of NMN was increased to 1213 mg/L by improving physiochemical conditions, tuning enzyme ratios and cofactor concentrations, and decreasing the feedback inhibition, which was a more than 12-fold improvement over the initial setup. This strategy would provide a promising way to accelerate design-build-test cycles for metabolic engineering to improve the production of desired products.

In the recent decade, metal-based conductive nano-inks comprising of nanometer-sized metallic particles of high electrical conductivity (mainly Ag and Cu) suspended in a polymer have revolutionized the field of printed electronics. The present review aims to provide an overview of the current state of research in synthesis and characterization techniques for metallic nano-inks and associated challenges. Moreover, the end of the review will discuss future perspectives in this field (from industrial and academic viewpoints).

In the recent decade, metal-based conductive nano-inks comprising of nanometer-sized metallic particles of high electrical conductivity (mainly Ag and Cu) suspended in a polymer have revolutionized the field of printed electronics. The present review aims to provide an overview of the current state of research in synthesis and characterization techniques for metallic nano-inks and associated challenges. Moreover, the end of the review will discuss future perspectives in this field (from industrial and academic viewpoints).

We propose eBoF, a novel time-varying ensemble data visualization approach based on bag-of-features (BoF). In the eBoF model, we take a simple and monotone interval from all target variables of ensemble scalar data as a local feature patch of BoF model and the duration time of each interval (i.e., feature patch) as its frequency. The feature clusters in ensemble runs are then identified based on the similarity of temporal correlations. eBoF generates the clusters together with their probability distribution across all the feature patches while storing the geo-spatial information, which is often lost in the traditional topic modelling or clustering algorithms. The probability distribution across different clusters can help to generate reasonable clustering results evaluated by the domain knowledge. We conduct several case studies and performance analyses. We also consult the domain experts to evaluate the proposed eBoF model. Evaluation results suggest the proposed eBoF can provide insightful and comprehensive evidence on ensemble simulation data analysis.

Interdisciplinary orthodontics can synchronize with tissue designing standards of periodontal regenerative medical procedure to make quick orthodontic results. Periodontally accelerated osteogenic orthodontics (PAOO) using piezosurgery, a novel approach, has found numerous applications in the field of osseous surgery. It helps to overcome the drawbacks of traditional rotary instruments.

Oil-immersed transformers play an important role in the stable operation of power systems. In order to improve the accuracy of transformer fault diagnosis, a transformer fault diagnosis method based on Isomap and IChOA-LSSVM is proposed. Firstly, Isomap is used to reduce the dimensionality of the 14-dimensional transformer fault characteristics data to eliminate redundant data between variables; then the Chimpanzee Optimisation Algorithm (ChOA) is improved by combining Circle uniform initialisation, position weighting strategy with proportional weights, and the Cauchy Gaussian variation factor. Circle uniform initialisation to make the population distribution uniform, position weighting strategy with proportional weights to improve the convergence speed and Cauchy Gaussian variation factor to optimize the population selection. The improved ChOA is compared with the original ChOA, PSO, and GWO algorithms by five benchmark test functions. Finally, the improved Chimpanzee Optimisation algorithm was used to find the parameters of the Least Squares Support Vector Machine (LSSVM) to obtain the fault diagnosis model combining Isomap and IChOA-LSSVM. The model is compared with PSO-LSSVM, ChOA-LSSVM, and GWO-LSSVM. The diagnostic accuracy is 90.83%, 81.67%, 83.33%, and 80%, respectively. The results demonstrate that the proposed method can effectively improve the performance of transformer fault diagnosis.

Chenopodium quinoa is an important crop that is known for its salt tolerance. Salinity is an osmotic stress and accumulation of ions in the root zone causes a reduction in soil water availability, which negatively affects the uptake of essential nutrients, changes seed composition, and reduces biomass. Therefore, there is a need to develop crops that are highly productive under poor soils. This research examines the effect of salt stress on quinoa photosynthetic efficiency and chloroplast development. Sensitive and tolerant quinoa lines were examined under salt stress conditions when a concentration of 155mM NaCl was applied. Electrical soil conductivity was monitored during the experiment to assure salt stress and at approximately two months old, CropReporter images, which are used to estimate photosystem II efficiency, non-photochemical quenching (NPQ), chlorophyll content, and anthocyanin content were captured and analyzed using PlantCV. The analysis showed that the salt treatment did not negatively affect the plant photosynthetic efficiency (no changes in Fv/Fm, NPQ, Fq'/Fm') but leaf area and chlorophyll content was statistically negatively affected by the treatment when comparing genotypes. Leaf tissue was sampled and chloroplasts were imaged using super-resolution microscopy. Salt-sensitive lines showed swelling of the chloroplast lamellae, starch accumulation, and unrecognizable grana structure. A comprehensive understanding of the quinoa salt tolerant mechanisms by employing multidisciplinary approaches is necessary for their effective incorporation into salt-sensitive crops for better crop yields under stressful environments.

This paper proposes a DC traction power supply system for electrified railroads with ice-melting function, which is used to solve the problems of power quality and line icing of single-phase AC traction power supply system. The proposed system consists of a multi-tap regulating transformer, a DC traction converter, a DC step-down converter, and a three-phase inverter. The DC traction converter adopts the topology of input-parallel-output-series (IPOS) uncontrolled rectifier and fully controlled converter. Its main capacity is assumed by the uncontrolled rectifier, which has the advantages of low cost, simple structure and easy to realize engineering applications. In this paper, the voltage regulating transformer is used for shifting and voltage regulation to expand the ice melting function, which can be used to solve the icing problem of the railway traction system. In order to realize the functions of harmonic compensation, DC-side voltage stabilization and power distribution in multiple parallel operation of DC traction converter, this paper proposes a compound control method for traction converter, which realizes power distribution by droop control with voltage compensation, voltage stabilization by suppressing voltage fluctuation by power feedforward control, and harmonic compensation by harmonic current compensation control. The small-signal model of the system under this control strategy is also established, and the stability of the control parameters on the system is analyzed. Finally, a simulation platform is built to verify the superiority of this topology and the feasibility of the control method.

Partial discharge (PD) is a dynamical system with nonlinear chaotic characteristics. Research on the time series of PD is helpful to extract the discharge mechanism. This paper takes a PD optical-UHF detection platform to detect the PD signals of typical defects. The optical and UHF signal are fused to avoid the insensitivity of single method in specific defects. The phases of PDs are taken as one-dimensional time series. The PD phase series are reconstructed in phase space and the attractors and the recurrence plots are presented. The attractors in phase space characteristic the PD system from predictability, stability, and complexity. The typical recurrence characteristics such as recurrence rate, determinism, laminarity, and entropy are extracted as evaluation parameters. Results show that the PD phase attractors are more random under low voltage and tends to be more ordered, stable, and complex when the applied voltage increases. The order of predictability, stability, and complexity of the four defect types from high to low is: point discharge, surface discharge, suspended discharge, air-gap discharge. The recognition accuracy based on recurrence characteristics achieves 100% with the most basic BPNNs.

Prediction of electrical power harmonics promotes development and provision of clean power supply. However, the elevated frequency combined with noise of harmonics make precise forecasting challenging and demanding. Due to the stochastic nature of harmonics occurrence and the challenge of attaining a dependable, and efficient working model, to this date research efforts have not been sufficient. Although various statistical and machine learning algorithms have shown very interesting and promising results, but work is still being done on algorithms that would produce the least possible error. This research uses hybrid convolutional neural network (CNN) and bidirectional long short term memory (BiLSTM) with Attention Mechanism (AM) model, to predict load harmonics at Nestle, a confectionary manufacturing plant in South Africa. Historical load harmonics data is used as the dataset. The results show that the hybrid deep machine learning method CNN – BiLSTM – AM has better performance compared to other five prediction models when detecting and forecasting load harmonics. The hybrid algorithm has a prediction accuracy of 92.3569 % and the lowest RMSE of 0.0000002215.

Microgrid, which can be considered as an integration of various dispersed resources (DRS), is characterized by the number of DRs interfaced through the power electronics converters. The microgrid comprising these DRs is often operated in an islanded mode. The droop control method is traditionally adopted to distribute active and reactive power among the DRS operating in parallel. However, the accuracy of distribution of reactive power among the DRS controlled by the conventional droop control approach is highly dependent on the value of line impedance, R/X i.e. resistance to reactance ratio of the line, voltage setting of inverters etc. In this paper, a control strategy has been presented to improve the reactive power sharing among distributed generation units in the islanded microgrids. The proposed control method is based on exerting reactive current injection to correct the output reference voltage is the common method of droop control. Reactive power distribution error is reduced by modifying the reference voltage. To evaluate the performance and effectiveness of the proposed control strategy, it is implemented on an island microgrid consisting of three distributed generation units. The simulation results show the proper performance and efficiency of the proposed method.

The majority of domesticated plant species are herbaceous annuals and woody perennials, yet many herbaceous perennial species hold potential for future agricultural systems. In addition to multiyear harvests, herbaceous perennials provide many ecosystem services, including erosion control as a result of their large and persistent root systems. However, the multiyear lifespan of perennial species has been a barrier to rapid domestication as breeding cycles require phenotyping over multiple growing seasons. Using phenomic selection, high-dimensional secondary traits measured on seedlings could be used to develop relationship matrices among individuals which are then used to predict field traits. Additionally, these models can serve as the selection criteria to identify individuals to advance to the next (pre)breeding generation, thus shortening the breeding cycle. This project substitutes costly genomics data with high-dimensional phenomics data asking: Can elite individuals of perennial species be predicted by phenomic relatedness models based on high-dimensional traits recorded on seedlings? To date, we have imaged 2280 seedlings from each of the following three perennial crop candidate species: intermediate wheatgrass (Thinopyrum intermedium), sainfoin (Onobrychis viciifolia), and silphium (Silphium integrifolium) on the Bellwether Foundation Phenotyping Facility housed at the Danforth Center. The images were processed using PlantCV to generate high-dimensional color and near-infrared profiles for each plant on each image day. Additionally, profiles were generated with handheld spectrometers. This work re-imagines innovations in plant traits, kinship matrices, genomic selection, phenotyping centers, and ultimately domestication, in order to expedite the development of an emerging generation of climate resilient, ecologically sustainable crops.

Since the market launch of alprazolam (in many countries under the brand name Xanax), this highly potent benzodiazepine has had a disastrous public reputation. Even in media, entertainment and pop culture, its very powerful effects have made it emblematic of a sinister psychodrug that drags its users into an abyss of dependence and suffering. Indeed, the substance has certain specific properties (mood elevating, extremely fast acting, very short half-life, effects on adrenaline), but at its core it is a benzodiazepine like any other. How Xanax came to be demonized is therefore an important question to be discussed. On the other hand, the substance alprazolam possesses a unique property that is hardly known even among experts to this day and can be life-saving for people whose body's own adrenaline synthesis and regulation is disturbed by certain (often hereditary, auto-immune, or toxic) rare diseases. For these patients, there is virtually no other medication available than alprazolam, which quickly, specifically and highly effectively inhibits pathological adrenaline surges, for example due to disorders of the SAM axis, effectively at the site of adrenaline (epinephrine) synthesis by up to 50%. Logically, this also gives rise to the legendary reputation that alprazolam is more effective than any other benzodiazepine, especially in patients with panic disorders. This paper, a source-supported opinion piece, is intended to remind the worldwide community of medical professionals that alprazolam is a legitimate, and often the only available, treatment option for abnormal adrenaline balance involving the adrenal gland and/or the SAM axis. Demonizing alprazolam in a clinically well regulated setting is therefore immoral and detrimental to the patients health and compliance.

Drought and high salinity are major environmental factors that reduce plant growth and development, leading to loss of plant productivity in agriculture. Under these stress conditions, photosynthesis is greatly suppressed despite the high cellular energy cost of stress response processes. Currently, the process that allows plants to secure the energy required for osmotic stress responses remains elusive. Here, we provide evidence that CBR1, a cytochrome b5 reductase, plays an important role in ATP production in response to NaCl and dehydration stresses. Overexpression and loss of function of CBR1 led to enhanced resistance and sensitivity, respectively, to osmotic stress. Upon exposure to osmotic stress, CBR1 was localized to the endoplasmic reticulum (ER) instead of to mitochondria, where it was localized under normal conditions. Transgenic plants overexpressing ER-targeted CBR1, but not mitochondria-targeted CBR1, showed enhanced resistance to osmotic stress and higher expression of SOS1/2/3 and RD29A/B under osmotic stress. CBR1-ER and CBR1-OX plants, but not CBR1-MT plants, had higher levels of ATP and unsaturated fatty acids under osmotic stress. Moreover, these effects were abrogated by thioridazine and 2-deoxy glucose, inhibitors of β-oxidation and glycolysis, respectively, but not by thiazolidinedione, an inhibitor of the mitochondrial pyruvate transporter. Based on these results, we propose that ER-localized CBR1 triggers ATP production via the production and β-oxidation of polyunsaturated fatty acids under osmotic stress.

Automated monitoring and evaluation systems for plant phenotyping are one of the keys to advance and strengthen crop breeding programs. In this study, the improvements of the camera-based sensor system and a weather station from a previous study-assembled mainly from Raspberry Pi products-board with dual cameras (RGB and NoIR) providing high spatial and temporal resolution data-is outlined. Hardware for the internet connection and the power supply system of the sensor were upgraded. Previously, the sensor could automatically capture plant images following user-defined time points; thus, an image processing algorithm (edge computing) was developed and installed to extract digital phenotypic traits from the images after capturing process. With the development, the new sensor system could be integrated with the internet, and a cloud server was configured to store data online (digital traits and raw images). A real-time monitoring system was created to visualize the time series data of a trait development and plant images throughout the season. With such a system, plant breeders will be able to monitor multiple trials for timely crop management and decision-making process, which is also resources efficiency.

ABSTRACT Orexins, also known as hypocretins, are two neuropeptides secreted from orexin-containing neurons, mainly in the lateral hypothalamus (LH). The mTOR pathway is an essential component of the Orexin/GPCR downstream signaling network and can be activated and activated by Orexin. This review article summarizes the Orexin system and its inhibition of various diseases through mTOR signaling pathway. In addition, the potential of targeting the Orexin system for treating a wide range of conditions is discussed.

A document by Uzair Yaqoob. Click on the document to view its contents.