Partially functional linear regression in high dimensions

In modern experiments, functional and nonfunctional data are often encountered simultaneously when observations are sampled from random processes and high-dimensional scalar covariates. It is difficult to apply existing methods for model selection and estimation. We propose a new class of partially functional linear models to characterize the regression between a scalar response and covariates of both functional and scalar types. The new approach provides a unified and flexible framework that simultaneously takes into account multiple functional and ultrahigh-dimensional scalar predictors, enables us to identify important features, and offers improved interpretability of the estimators. The underlying processes of the functional predictors are considered to be infinite-dimensional, and one of our contributions is to characterize the effects of regularization on the resulting estimators. We establish the consistency and oracle properties of the proposed method under mild conditions, demonstrate its performance with simulation studies, and illustrate its application using air pollution data

Optimal scheduling of industrial task-continuous load management for smart power utilization

In the context of climate change and energy crisis around the world, an increasing amount of attention has been paid to developing clean energy and improving energy efficiency. The penetration of distributed generation (DG) is increasing rapidly on the user’s side of an increasingly intelligent power system. This paper proposes an optimization method for industrial task-continuous load management in which distributed generation (including photovoltaic systems and wind generation) and energy storage devices are both considered. To begin with, a model of distributed generation and an energy storage device are built. Then, subject to various constraints, an operation optimization problem is formulated to maximize user profit, renewable energy efficiency, and the local consumption of distributed generation. Finally, the effectiveness of the method is verified by comparing user profit under different power modes

The current status of mercury repair technology in the environment

In recent years, due to the pollution of heavy metals in the environment, it has brought a serious crisis to my country's ecological balance, especially the pollution of heavy metal mercury (Hg), so the repair of mercury in the environment is crucial. At present, there are many technologies for repairing mercury in the environment. The main repair techniques include physical repair technology and chemical repair technology. However, there are many problems in these two repair methods, such as high repair costs, and it is easy to cause secondary pollution. Microbial repair method is a method of repairing the environment. It can not only adsorb and fix heavy metal mercury, and does not bring pollution to the environment. Therefore, using microorganisms to remove mercury in the environment is by far the most promising environmental repair technology

Partially functional linear regression in high dimensions

SUMMARY In modern experiments, functional and nonfunctional data are often encountered simultaneously when observations are sampled from random processes and high-dimensional scalar covariates. It is difficult to apply existing methods for model selection and estimation. We propose a new class of partially functional linear models to characterize the regression between a scalar response and covariates of both functional and scalar types. The new approach provides a unified and flexible framework that simultaneously takes into account multiple functional and ultrahigh-dimensional scalar predictors, enables us to identify important features, and offers improved interpretability of the estimators. The underlying processes of the functional predictors are considered to be infinite-dimensional, and one of our contributions is to characterize the effects of regularization on the resulting estimators. We establish the consistency and oracle properties of the proposed method under mild conditions, demonstrate its performance with simulation studies, and illustrate its application using air pollution data

Effects of transcranial magnetic stimulation on sleep structure and quality in children with autism

IntroductionSleep disorders are common in children with autism spectrum disorder (ASD). Transcranial magnetic stimulation (TMS) can influence the excitability of neuronal cells in stimulated areas, leading to improvements in sleep and other autistic symptoms. However, studies on clinical mechanisms of TMS in treating sleep disorders associated with ASD are limited. Therefore, we aimed to explore the effects of TMS on sleep structure and quality in children with ASD.MethodsBetween January 2020 and December 2021, recruitment was advertised through child and adolescent outpatient clinics and online platforms by the Hangzhou Seventh People’s Hospital and Lishui Second People’s Hospital. Sixty children with ASD who met the diagnostic criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, were selected and randomly divided into the active TMS and sham TMS treatment groups. Thirty healthy children of the same age were recruited as controls. The active TMS group received bilateral low-frequency (0.5 Hz) TMS targeting the dorsolateral prefrontal cortex on both sides in children with ASD, whereas the sham TMS group received sham stimulation with the same stimulation time and location as the experimental group. Both groups were treated for 6 weeks, and the participants were assessed using the Sleep Disturbance Scale for Children (SDSC) before treatment, at 3 weeks, and at 6 weeks of intervention. Independent sample t-tests and difference t-tests were used for statistical analysis of the data.ResultsNo significant differences were observed in general demographic variables, such as age and sex, between the ASD and control groups (P>0.05). Independent sample t-test analysis showed that the total SDSC score, difficulty falling asleep, sleep maintenance, awakening disorders, sleep-wake transition disorders, excessive daytime sleepiness, and nocturnal hyperhidrosis scores were significantly higher in the ASD group than in the control group (P<0.05). Before treatment, no significant differences were observed in the factor or total SDSC scores between the sham TMS group and the active TMS group (P>0.05). After 15 and 30 treatment sessions, the total SDSC score, difficulty falling asleep, sleep maintenance, sleep-wake transition disorders, and excessive daytime sleepiness scores were significantly higher in the sham TMS group than in the active TMS group (P<0.05). The difference t-test analysis showed that after 30 treatment sessions, the reduction rates of the total SDSC score, difficulty falling asleep, sleep maintenance, awakening disorders, sleep-wake transition disorders, excessive daytime sleepiness, and nocturnal hyperhidrosis dimensions were significantly higher in the active TMS group than in the sham TMS group (P<0.05).ConclusionLow-frequency TMS targeting the dorsolateral prefrontal cortex in children with ASD can effectively improve their sleep status, and significant improvement can be achieved after 6 weeks (30 sessions) of treatment

Effect of high-pressure homogenization on maize starch-stearic acid and maize starch-stearic acid-whey protein complexes

The maize starch (MS)-stearic acid (SA) and MS-SA-whey protein (WP) complexes were prepared using the high-pressure homogenization (HPH). Results from X-ray diffraction (XRD) showed that MS-SA complexes presented an increase in the long-range molecular order with increasing the homogenization pressure, and MS-SA-WP complexes showed only an increase with increasing the homogenization pressure from 10 to 50 MPa. Results from differential scanning calorimetry (DSC) and Raman spectroscopy showed that the amount of complexes and the short-range order of both MS-SA and MS-SA-WP complexes increased with increasing the homogenization pressure. The addition of WP to MS-SA altered significantly the structure and digestion of complexes. Results revealed that MS-SA-WP complexes have more ordered structure and lower digestion than the corresponding MS-SA complexes. The digestibility of all complexes decreased with increasing the homogenization pressure. There was a significant correlation between the digestibility and structural characteristics of complexes. Complexes with better structural stability have better anti-digestion properties. The obtained results are helpful in understanding the structure and digestibility of complexes prepared by HPH, which is valuable for controlling the quality and nutrition of starchy food

B-RAF kinase drives developmental axon growth and promotes axon regeneration in the injured mature CNS

Activation of intrinsic growth programs that promote developmental axon growth may also facilitate axon regeneration in injured adult neurons. Here, we demonstrate that conditional activation of B-RAF kinase alone in mouse embryonic neurons is sufficient to drive the growth of long-range peripheral sensory axon projections in vivo in the absence of upstream neurotrophin signaling. We further show that activated B-RAF signaling enables robust regenerative growth of sensory axons into the spinal cord after a dorsal root crush as well as substantial axon regrowth in the crush-lesioned optic nerve. Finally, the combination of B-RAF gain-of-function and PTEN loss-of-function promotes optic nerve axon extension beyond what would be predicted for a simple additive effect. We conclude that cell-intrinsic RAF signaling is a crucial pathway promoting developmental and regenerative axon growth in the peripheral and central nervous systems

The current status of mercury repair technology in the environment

In recent years, due to the pollution of heavy metals in the environment, it has brought a serious crisis to my country's ecological balance, especially the pollution of heavy metal mercury (Hg), so the repair of mercury in the environment is crucial. At present, there are many technologies for repairing mercury in the environment. The main repair techniques include physical repair technology and chemical repair technology. However, there are many problems in these two repair methods, such as high repair costs, and it is easy to cause secondary pollution. Microbial repair method is a method of repairing the environment. It can not only adsorb and fix heavy metal mercury, and does not bring pollution to the environment. Therefore, using microorganisms to remove mercury in the environment is by far the most promising environmental repair technology