Machine learning enables non-Gaussian investigation of changes to peripheral nerves related to electrical stimulation.

Electrical stimulation of the peripheral nervous system (PNS) is becoming increasingly important for the therapeutic treatment of numerous disorders. Thus, as peripheral nerves are increasingly the target of electrical stimulation, it is critical to determine how, and when, electrical stimulation results in anatomical changes in neural tissue. We introduce here a convolutional neural network and support vector machines for cell segmentation and analysis of histological samples of the sciatic nerve of rats stimulated with varying current intensities. We describe the methodologies and present results that highlight the validity of the approach: machine learning enabled highly efficient nerve measurement collection, while multivariate analysis revealed notable changes to nerves' anatomy, even when subjected to levels of stimulation thought to be safe according to the Shannon current limits.

Thiocyanate promoted difunctionalization and cyclization of unsaturated C-C bonds to construct 1-sulfur-2-nitrogen-functionalized alkenes and 2-thiocyanate indolines.

An unprecedented one-pot route to achieve highly regioselective 1-sulfur-functionalized 2-nitrogen-functionalized alkenes and 2-thiocyanate indolines from unsymmetrical ynamides (readily and generally available amides) using the commercially available inexpensive iodobenzene diacetate (PIDA) as the oxidant and potassium thiocyanate (KSCN) as the thiocyanate (SCN) source has been developed. The interconversion of thiocyanate (SCN) and isothiocyanate (NCS) groups simultaneously forms C-N and C-S bonds in this metal-free approach, while introducing important functional groups into homemade alkynes. A radical-chain mechanism, involving competing kinetically controlled chain transfer at the S atom and sterically-controlled chain transfer at the N atom of the thiocyanogen molecule in this mild approach, is proposed.

Electrical Stimulation Induced Current Distribution in Peripheral Nerves Varies Significantly with the Extent of Nerve Damage: A Computational Study Utilizing Convolutional Neural Network and Realistic Nerve Models.

Electrical stimulation of the peripheral nervous system is a promising therapeutic option for several conditions; however, its effects on tissue and the safety of the stimulation remain poorly understood. In order to devise stimulation protocols that enhance therapeutic efficacy without the risk of causing tissue damage, we constructed computational models of peripheral nerve and stimulation cuffs based on extremely high-resolution cross-sectional images of the nerves using the most recent advances in computing power and machine learning techniques. We developed nerve models using nonstimulated (healthy) and over-stimulated (damaged) rat sciatic nerves to explore how nerve damage affects the induced current density distribution. Using our in-house computational, quasi-static, platform, and the Admittance Method (AM), we estimated the induced current distribution within the nerves and compared it for healthy and damaged nerves. We also estimated the extent of localized cell damage in both healthy and damaged nerve samples. When the nerve is damaged, as demonstrated principally by the decreased nerve fiber packing, the current penetrates deeper into the over-stimulated nerve than in the healthy sample. As safety limits for electrical stimulation of peripheral nerves still refer to the Shannon criterion to distinguish between safe and unsafe stimulation, the capability this work demonstrated is an important step toward the development of safety criteria that are specific to peripheral nerve and make use of the latest advances in computational bioelectromagnetics and machine learning, such as Python-based AM and CNN-based nerve image segmentation.

Computational optimization of delivery parameters to guide the development of targeted Nasal spray.

Airborne transmission by droplets and aerosols is known to play a critical role in the spread of many viruses amongst which are the common flu and the more recent SARS-CoV-2 viruses. In the case of SARS-CoV-2, the nasal cavity not only constitutes an important viral entry point, but also a primary site of infection (Sungnak W. et al. Nat. Med. 26:681-687. https://doi.org/10.1038/s41591-020-0868-6 , 2020).. Although face masks are a well-established preventive measure, development of novel and easy-to-use prophylactic measures would be highly beneficial in fighting viral spread and the subsequent emergence of variants of concern (Tao K. et al. Nat Rev Genet 22:757-773. https://doi.org/10.1038/s41576-021-00408-x , 2021). Our group has been working on optimizing a nasal spray delivery system that deposits particles inside the susceptible regions of the nasal cavity to act as a mechanical barrier to impede viral entry. Here, we identify computationally the delivery parameters that maximize the protection offered by this barrier. We introduce the computational approach and quantify the protection rate obtained as a function of a broad range of delivery parameters. We also introduce a modified design and demonstrate that it significantly improves deposition, thus constituting a viable approach to protect against nasal infection of airborne viruses. We then discuss our findings and the implications of this novel system on the prevention of respiratory diseases and targeted drug delivery.

Security Analysis and Improvement of Vehicle Ethernet SOME/IP Protocol.

The combination of in-vehicle networks and smart car devices has gradually developed into Intelligent Connected Vehicles (ICVs). Through the vehicle security protocol, ICVs can quickly realize communication transmission. However, with the more frequent connections between smart in-vehicle devices and the network, the relationship between intelligent cars and external systems is becoming more and more complicated, and in-vehicle networks are gradually facing many security issues. Strengthening the security of in-vehicle protocols has become particularly important. This paper uses the model building method based on the Colored Petri Net (CPN) theory to model the Scalable service-Oriented MiddlewarE over IP (SOME/IP) protocol of the vehicle Ethernet. The security protocol is formally verified and analyzed by combining it with the Dolev-Yao adversary model detection method. After verification, the protocol is subject to three attack vulnerabilities: replay, tampering, and deception. We introduce timestamps and random numbers to strengthen the protocol security. After the final analysis and verification, the improved scheme in this paper can effectively improve the security performance of the protocol.

Study of the Adsorption Behavior of Surfactants on Carbonate Surface by Experiment and Molecular Dynamics Simulation.

Surfactants adsorption onto carbonate reservoirs would cause surfactants concentrations decrease in surfactant flooding, which would decrease surfactant efficiency in practical applications of enhanced oil recovery (EOR) processes. Different surfactants could be classified as cationic surfactants, anionic surfactants, non-ionic surfactants according to the main charge, or be classified as chemical surfactant and bio-surfactant according to the surfactant origin. However, the research on different type surfactants adsorption on carbonate reservoirs surface differences was few. Therefore, five representative surfactants (CTAB, SDS, TX-100, sophorolipid, rhamonilipid) adsorption effect onto carbonate reservoirs surface was studied. Owing to the fact that the salinity and temperature in underground carbonate reservoirs were high during the EOR process, it is vital to study the salinity effect and temperature effect on surfactant adsorption. In this study, different surfactants species, temperature and salinity adsorption onto carbonate reservoirs were studied. The adsorption isotherms were fitted by Langmuir, Freundlich, Temkin and Linear models, and the first three models fitting effect were good. The results showed that cationic surfactants adsorption quantity was higher than anionic surfactants, and the non-ionic surfactants adsorption quantity was the lowest. When the temperature increased, the surfactants adsorption would decrease, because the adsorption process was exothermic process, and increasing temperature would inhibit the adsorption. The higher salinity would increase surfactants adsorption because higher salinity could compress electric double layer. In order to decrease surfactants adsorption, SiO2 nanoparticles and TiO2 nanoparticles were added to surfactants solutions, and then surfactants could adsorb onto nanoparticles surface, then the steric hindrance between surfactant molecules would increase, which could decrease surfactants adsorption. Contact angle results indicated that surfactants adsorption made the carbonate reservoir wettability alteration. In the end, surfactants (with or without SiO2 nanoparticles) adsorption onto carbonate reservoirs mechanism were studied by molecular dynamics simulation. The simulation results indicated that the surfactants molecules could adsorb onto SiO2 nanoparticles surface, and then the surfactants adsorption quantity onto carbonate rocks would decrease, which was in accordance with the experiments results.

Electrochemical-Oxidation-Promoted Direct N-ortho-Selective Difluoromethylation of Heterocyclic N-Oxides.

An efficient and green electrochemical N-ortho-selective difluoromethylation method of various quinoline and isoquinoline N-oxides has been developed. In this method, sodium difluoromethanesulfinate (HCF2SO2Na) was used as the source of the difluoromethyl moiety, and various N-ortho-selective difluoromethylation quinoline and isoquinoline N-oxides were obtained in good to excellent yields under a constant current. In addition, the reaction was easy to scale up and maintained a good yield. Preliminary mechanism studies suggested that the reaction undergoes a free-radical addition and hydrogen elimination pathway.

Electrical Stimulation Induced Current Distribution in Peripheral Nerves Varies Significantly with the Extent of Nerve Damage: A Computational Study Utilizing Convolutional Neural Network and Realistic Nerve Models.

Although electrical stimulation is an established treatment option for multiple central nervous and peripheral nervous system diseases, its effects on the tissue and subsequent safety of the stimulation are not well understood. Therefore, it is crucial to design stimulation protocols that maximize therapeutic efficacy while avoiding any potential tissue damage. Further, the stimulation levels need to be adjusted regularly to ensure that they are safe even with the changes to the nerve due to long-term stimulation. Using the latest advances in computing capabilities and machine learning approaches, we developed computational models of peripheral nerve stimulation based on very high-resolution cross-sectional images of the nerves. We generated nerve models constructed from non-stimulated (healthy) and over-stimulated (damaged) rat sciatic nerves to examine how the current density distribution is affected by nerve damage. Using our in-house numerical solver, the Admittance Method (AM), we computed the induced current distribution inside the nerves and compared the current penetration for healthy and damaged nerves. Our computational results indicate that when the nerve is damaged, primarily evidenced by the decreased nerve fiber packing, the current penetrates deeper inside the nerve than in the healthy case. As safety limits for electrical stimulation of biological tissue are still debated, we ultimately aim to utilize our computational models to determine refined safety criteria and help design safer and more efficacious electrical stimulation protocols.

Electrode Spacing and Current Distribution in Electrical Stimulation of Peripheral Nerve: A Computational Modeling Study using Realistic Nerve Models.

Electrical stimulation of peripheral nerves has long been used and proven effective in restoring function caused by disease or injury. Accurate placement of electrodes is often critical to properly excite the nerve and yield the desired outcome. Computational modeling is becoming an important tool that can guide the rapid development and optimization of such implantable neural stimulation devices. Here, we developed a heterogeneous very high-resolution computational model of a realistic peripheral nerve stimulated by a current source through cuff electrodes. We then calculated the current distribution inside the nerve and investigated the effect of electrodes spacing on current penetration. In the present study, we first describe model implementation and calibration; we then detail the methodology we use to calculate current distribution and apply it to characterize the effect of electrodes distance on current penetration. Our computational results indicate that when the source and return cuff electrodes are placed close to each other, the penetration depth in the nerve is shallower than the cases in which the electrode distance is larger. This study outlines the utility of the proposed computational methods and anatomically correct high-resolution models in guiding and optimizing experimental nerve stimulation protocols.

Surfactants Enhanced Heavy Oil-Solid Separation from Carbonate Asphalt Rocks-Experiment and Molecular Dynamic Simulation.

In this study, surfactants were used to enhance heavy oil-solid separation, and a detailed mechanism was explored by SARA (saturates, aromatics, resins, asphaltenes) analysis, element analysis, AFM measurement, and molecular dynamic simulation. Surfactants could effectively decrease oil/solid interaction force and then oil-solid separation would be enhanced. The oil-solid interactive force was in relation to surfactants concentration, pH value, asphaltene content, and salinity. The molecular dynamics simulation results show that the dissociation of saturated hydrocarbon, aromatic hydrocarbon, resin, and asphaltene (SARA) on carbonate minerals is gradually weakened for all surfactants. In the process of molecular dynamics simulation of surfactant stripping SARA, firstly, the surfactant molecules adsorb on the surface of SARA molecules. After that, the surfactant peels SARA molecules off the surface of calcite under the influence of molecular thermal motion. In this process, surfactant molecules will not be directly adsorbed on the surface of trace minerals. The results of energy/temperature balance indicated that saturates, aromatics and resins could remain stable when the molecular dynamics simulation time reached 2000 ps with the phenomenon that saturates, aromatics could liberate from minerals totally within 2000 ps. The molecular dynamics simulation of asphaltenes will not liberate from calcite surface within 6000 ps, meanwhile, they could not reach the energy balance/energy balance within 6000 ps. The functional groups of surfactant molecules would have interactions with the SARA functional group, resulting in different dissociation effects of SARA. The results of molecular dynamics simulation are consistent with the experiment results. The separation effect of saturated hydrocarbon, aromatic hydrocarbon, resin, and asphaltene in five kinds of surfactants were different. The molecular dynamic simulation results were in accordance with the SARA analysis.

Conversion of phenolic mixture to refractory resins: A resourcezation strategy for phenolic distillation residues.

A new resourcezation way has been proposed to address the treatment challenges of the light phenolic distillation residue (LPDR) from the coal-based phenolic distillation residue. Herein, the LPDR, which was collected at 20 kPa and 220 °C from the phenolic distillation residue, has been further used to synthesize the phenolic resin (named as RPF) for MgO-C refractories. It is found that the conversion efficiency of crude phenol mixture to RPF is 71.3%, which is lower than that of pure phenol. To increase the conversion efficiency and improve the properties of RPF, the crude phenolic mixture was blended with pure phenol for the synthesis. The optimal addition mass ratio of phenol in the crude phenol mixture (phenol/total phenolic compounds) is determined to be 0.8, where the obtained RPF could satisfy or even better than the national standard. Further addition of 10 wt% of urotropine (HMTA) as curing agent and 9 wt% of ferrocene (Fc) as modifier (named as MRPF) are found to significantly improve the graphitization of RPF. Under these conditions, the DTG at temperature of maximum mass lose rate (Tmax) of MRPF was lower than that of commercial resin. The graphitization level was as high as 61.6% with the residual carbon rate up to 41.4%, which are higher than those of national standard. These findings provide insights for the resourcezation of the phenolic distillation residue.

Oxidant- and Catalyst-Free Synthesis of Sulfonated Benzothiophenes via Electrooxidative Tandem Cyclization.

A green and practical electrochemical method for the synthesis of C-3-sulfonated benzothiophenes from 2-alkynylthioanisoles and sodium sulfinates was developed under oxidant- and catalyst-free conditions. Moderate to good yields of sulfonated benzothiophenes bearing important and useful functional groups have been achieved at a constant current. Preliminary mechanistic studies indicated a tandem radical addition-cyclization pathway. Moreover, the protocol is easy to scale up and exhibits good reaction efficiency.

The Design of Large Scale IP Address and Port Scanning Tool.

The control network is an important supporting environment for the control system of the heavy ion accelerator in Lanzhou (HIRFL). It is of great importance to maintain the accelerator system's network security for the stable operation of the accelerator. With the rapid expansion of the network scale and the increasing complexity of accelerator system equipment, the security situation of the control network is becoming increasingly severe. Port scanning detection can effectively reduce the losses caused by viruses and Trojan horses. This article uses Go Concurrency Patterns, combined with transmission control protocol (TCP) full connection scanning and GIMP Toolkit (GTK) graphic display technology, to develop a tool called HIRFL Scanner. It can scan IP addresses in any range with any ports. This is a very fast, installation-free, cross-platform IP address and port scanning tool. Finally, a series of experiments show that the tool developed in this paper is much faster than the same type of software, and meets the expected development needs.

Electron Beam Irradiation Crosslinking and Flame Retardant of Ethylene Vinyl Acetate Using Melamine-Formaldehyde Microencapsulated.

The microcapsule particles were successfully prepared by means of in-situ copolymerization of layered double hydroxides (LDHs) with the melamine resin monomers, improving the compatibility of inorganic flame retardant LDH with polymer. The electron beam irradiation was introduced into the process to enhance the mechanical properties and thermostability of the flame retardant composite material. The flame-retardant composites were prepared by incorporating the microcapsule LDH into ethylene vinyl acetate (EVA). The compatibility of microcapsule particles with EVA, combustion and thermal behaviors were detected in sequence through SEM, TG analyses, LOI, UL-94 level and mechanical tests. It was shown that the irradiated EVA/LDH@MF composite had showed the best performances of flame retardancy and mechanical properties due to microencapsulation and irradiation processes. The uniform dispersion of microencapsulated LDH in the EVA matrix was due to the good compatibility of MF shell with EVA keeping the mechanical properties of EVA matrix. The irradiated EVA/LDH@MF with 200 kGy dose achieved a limiting oxygen index (LOI) of 25.5% and a UL-94 V-1 rating. When the dose rate was 100 kGy, the EVA/LDH@MF composite had the best mechanical properties of EVA composites. The microencapsulation of LDH with MF shell incorporated into EVA three-dimensioned network through electron beam irradiation induced crosslinking to enhance mechanical properties.

Mechanism and Kinetics of Dehydroxylation and Decarbonation of Mg-Fe Hydrotalcite.

Thermal behavior of hydrotalcites, which is a calcination process, is critical to prepare the metal oxide catalysts with high performances in the practical applications. In this paper, the MgFe-LDH with Mg/Fe molar ratio of 3.0 was prepared by urea method and the calcined products are obtained by calcining at different temperatures (473 K, 573 K, 673 K, 773 K, 873 K and 973 K) under a N2 atmosphere for 4 h. The structure, morphology, texture, pyrolysis kinetics and mechanism of the MgFe-LDH were studied in detail. On one hand, based on the TG/DSC curves, Starink, Kissinger and Flynn-Wall-Ozawa (FWO) methods were used to calculate the activation energy, on the other hand, the Satava-Sesták, Achar and Málek methods were used to define the most probable reaction mechanisms of pyrolysis behavior. The results suggested that the thermal decomposition of the LDH experienced two steps, i.e., removal of the interlayer water, followed by dehydroxylation and decarbonation. Moreover the Mákel method was used to define the most probable reaction mechanisms of the pyrolysis behavior.

Effect of Organo-Shell Materials on Compatibility of the Hydrotalcite Flame Retardant in Ethylene Vinyl Acetate.

The microcapsule nanoparticles were prepared by in-situ copolymerization of hydrotalcites (MAH) with the polymer (MF, PF, PS and PU) monomers, respectively, where the MF-wrapped MAH (MAH@MF) had the best monodispersity. The composites of the microcapsules and EVA were prepared by incorporating the microcapsule nanoparticles into ethylene vinyl acetate (EVA), respectively. To further understand the intrinsic correlation between microcapsule fillers and EVA matrix, molecular dynamics (MD) simulation was introduced to qualitatively analyze the contribution of microcapsule fillers on improving compatibility and mechanical properties of the EVA matrix. The compatibility of microcapsule nanoparticles with EVA matrix were detected in sequence through SEM, DSC and tensile strength tests. And the combustion, thermal behavior and flame retardance were also characterized by TG analyses as well as LOI and UL-94 level. As a result, the MAH@MF filler had the best performances in improving the flame retardancy and mechanical properties among the microcapsule fillers, attributed to high compatibility of the MAH@MF and EVA matrix, which made uniform distribution of the MAH@MF filler due to the reciprocity of triazine functional ring with vinyl acetate linkages.

Non-Isothermal Decomposition Kinetic of Polypropylene/Hydrotalcite Composite.

P3O5-10 pillared Mg/Al hydrotalcite (HTs) as a functional fire-retarding filler was successfully prepared by impregnation-reconstruction, where the HTs was used to prepare polypropylene (PP) and HTs composite (PP/HTs). Thermal decomposition was crucial for correctly identifying the thermal behavior for the PP/HTs, and studied using thermogravimetry (TG) at different heating rates. Based on single TG curves and Málek method, as well as 41 mechanism functions, the thermal decompositions of the PP/HTs composite and PP in nitrogen atmosphere were studied under non-isothermal conditions. The mechanism functions of the thermal decomposition reactions for the PP/HTs composite and PP were separately "chemical reaction F3" and "phase boundary reaction R2," which were also in good agreement with corresponding experimental data. It was found that the addition of the HTs increased the apparent activation energy Ea of the PP/HTs comparing to the PP, which improved the thermal stability of the polypropylene. A difference in the set of kinetic and thermodynamic parameters was also observed between the PP/HTs and PP, particularly with respect to lower ΔS≠ value assigned to higher thermal stability of the PP/HTs composite.

Microwave Pretreatment and Enzymolysis Optimization of the Lotus Seed Protein.

Pretreatment with a microwave was conducted before enzymolysis and shown to enhance the enzymolysis, which changed the secondary structure of the lotus seed protein. Under high-power microwave irradiation, sub bonds of the protein were broken, causing disaggregation and unfolding of the secondary structure, namely a decrease in the intermolecular aggregate structure and increase in the random coil structure, making the protein bonds susceptible to papain in the enzymolysis. On the other hand, a response surface methodology (RSM) was launched to investigate the influence of the enzymolysis process variables on the DH (degree of hydrolysis). The statistical analysis revealed that the optimized conditions were a protein substrate concentration of 15 g/L, pH of 5.5, enzymolysis temperature of 57 °C, papain amount of 0.5 g/L, and enzymolysis time of 45 min, for which the predicted value of the DH was 35.64%. The results indicated that a microwave also had better potential for applications in the enzymolysis of foods.

Facile Hydrothermal Preparation of Carboxymethyl Chitosan Functionalized Hydrotalcite Composite with Enhanced Adsorption Capacity for Cu(II) Ions.

In order to enhance the adsorption capacity of hydrotalcite material for heavy metal ions, the LDH/CMC composite was prepared by a simple hydrothermal method. The XRD pattern showed that the presence of CMC has no obvious influence on the crystal structure of hydrotalcites. The FT-IR and UV-vis DRS analyses showed that the CMC functionalized surface has been obtained. The SEM and BET/BJH showed that the morphologies, textural and surface chemical properties of LDH were affected remarkably after the introduction of CMC. The weight percentage of CMC in the LDH/CMC composite was estimated to be about 17.4%. The adsorption experiments showed the LDH/CMC composite exhibited high efficiency in the Cu(II) removal at pH > 6.5, affording Cu(II) removal rates of 92.3%. The results demonstrated that the LDH/CMC composite was a suitable adsorbent for Cu(II)-contaminated wastewater treatment.

REDD1 and p-AKT over-expression may predict poor prognosis in ovarian cancer.

We investigated the clinical significance of regulated in development and DNA damage response (REDD1) and p-AKT expression in human ovarian cancer (OC), explored the correlation of KRAS mutations with REDD1 expression, and assessed the therapeutic relevance of REDD1 in OC. We collected and immunohistochemically analyzed 118 formalin-fixed paraffin-embedded tumor tissue samples (100 primary OC and 18 borderline tumors) and 14 normal fallopian tubes, for REDD1 and p-AKT expression. Direct DNA sequencing for KRAS mutations and quantitative real-time polymerase chain reaction for detecting REDD1 mRNA expression were performed. REDD1 and p-AKT expressions were significantly higher in serous adenocarcinoma than other histological types, and this increase positively correlated with late-stage disease. REDD1 expression correlated with ascites formation, while p-AKT expression correlated with higher histological grade and chemoresistance. Kaplan Meier survival analysis showed significantly reduced disease-free survival (DFS) and overall survival (OS) in OC patients with both REDD1 and p-AKT overexpression. Patients with KRAS mutations had a longer DFS and OS. However, KRAS mutation and REDD1 over-expression was not correlated. Together, REDD1 and p-AKT over-expression may serve as a prognostic biomarker in OC, but KRAS mutations and REDD1 protein over-expression were not correlated in OC. We believe that with increasing knowledge of the role of REDD1 in cell migration, invasion, and proliferation pathways, the potential of REDD1 as a therapeutic target in OC may be uncovered.