The potential mechanism and clinical application value of remote ischemic conditioning in stroke

Some studies have confirmed the neuroprotective effect of remote ischemic conditioning against stroke. Although numerous animal researches have shown that the neuroprotective effect of remote ischemic conditioning may be related to neuroinflammation, cellular immunity, apoptosis, and autophagy, the exact underlying molecular mechanisms are unclear. This review summarizes the current status of different types of remote ischemic conditioning methods in animal and clinical studies and analyzes their commonalities and differences in neuroprotective mechanisms and signaling pathways. Remote ischemic conditioning has emerged as a potential therapeutic approach for improving stroke-induced brain injury owing to its simplicity, non-invasiveness, safety, and patient tolerability. Different forms of remote ischemic conditioning exhibit distinct intervention patterns, timing, and application range. Mechanistically, remote ischemic conditioning can exert neuroprotective effects by activating the Notch1/phosphatidylinositol 3-kinase/Akt signaling pathway, improving cerebral perfusion, suppressing neuroinflammation, inhibiting cell apoptosis, activating autophagy, and promoting neural regeneration. While remote ischemic conditioning has shown potential in improving stroke outcomes, its full clinical translation has not yet been achieved.

Optimum Energy Management of the Central Air-Conditioning System in Intelligent Buildings

An optimum energy saving scheduling strategy of the central air conditioning system in an intelligent building (IB) was proposed. Based on the system analysis a set of models of the central air conditioning system was established. The periodically autoregressive models (PARM) based on genetic algorithms (GA) were used to predict the next day’s cold load. The improved genetic algorithms (IGA) with stochastic real number coding were used to finish the optimum energy saving scheduling of the system. The simulation results for the building of the Liangmahe Plaza show that the proposed strategy can save energy up to about 24 5%.

Study on the Optimum Moisture Amount Added to Brown Rice once during the Wet Conditioning

In the experiment, the brown rice whose moisture content was 12.5% was used as raw material. The brown rice was grouped, then moisturized differently and milled. While milling, the energy consumption, the rate of broken rice and the crack rate were tested. It is confirmed that the stress crack owing to the moisture added to the brown rice can be avoided when the moisture amount added once is limited to no more than 1.5%. It is also proved that the energy consumption can be reduced, the yielding rate of rice can be increased and that the quality of rice can be improved.

Optimum of Mobile Phase Condition for Resolving Isoflavones in RP-HPLC

In reversed-phase high performance liquid chromatography （RP-HPLC）, the mobile phase condition for separating eight isoflavones （daidzin, glycitin, genistin, 6＇-o-acetyl daidzin, 6＇-o-malonyl genistin, daidzein, glycitein and genistein） was optimized using the HCI （High-Purity Separation Laboratory, Department of Chemical Engineering, Inha University） program software. The optimum composition of mobile phase for the separation of the eight isoflavones was obtained. The elution profiles were calculated by the plate theory based on the equations of retention factor, In k=A＋BF＋CF2, where F was the volume percentage of acetonitrile with 0.1% acetic acid （AA）. The first mobile phase composition was water with 0.1% AA/acetonitrile with 0.1% AA （88%/12%, by volume）, followed at 9min later by the second composition of mobile phase which was step-changed to 85%/15%, at 19rain by the third composition which was step-changed to 73%/27%, at 30min when it was changed to 65%/35% and finally it was maintained in isocratic mode to the end of the run time at 50rain. Although, using step gradient mode to separate the isoflavones, the calculated and experimented data were not achieved very good agreement, we could estimate the closed retention time before experiment. And the agreement between the experimental data and the calculated values was relatively good using isocratic separation for eight isoflavones, but the retention time is very long.

Optimum conditions to treat high-concentration microparticle slime water with bioflocculants

We studied how bioflocculants,produced by white-rot fungi,affect flocculation in slime water.Based on a test in an orthogonal design,flocculation conditions were optimized.The results show that flocculation activity is at its highest when the following conditions are met:slime water concentration 27.42 g/L;coagulant aid(CaCl_2) mass concentration 5.0 g/L;two-segment stirrings:the first at a stirring speed of 60 r/min for 180 s and the second 180 r/min for 60 s;a pH of 11 and a flocculant concentration of 15 mL/L.The flocculation activity can be up to 98.71%of bioflocculants at the time.Further experiments indicate that most of the flocculation active material is found outside the mycelium cells.This is the extracellular secretion produced by mycelium cells during the fermentation process.This flocculant has strong thermal stability.Many kinds of cations have a flocculation function to assist bioflocculants.This aid-flocculation effect of the divalent cation Ca^(2+) is obvious in the bioflocculant produced by the white-rot fungus.Therefore,this is of great value when applied to control engineering in the battle against water pollution.

Optimum condition by mechanical characteristic evaluation in friction stir welding for 5083-O Al alloy

The mechanical characteristies for friction stir welding (FSW) of 5083-O Al alloy were evaluated. The results show that in FSW at 800 r/min and 124 mm/min, a weld defect is observed at the start point. However, the button shape at the end point is good and the stir zone has a soft appearance. At 267 mm/min, a void occurs at the button. A slight weld defect and rough stir zone are seen both at the start and end points at 342 mm/min. Moreover, at the bottom, a tunnel-type void is observed from an early stage to the end point, and at 1 800 r/min, a weld defect can be found from an early stage to the end point. These defects are rough with imperfect joining due to excessive rotation speed and high physical force. Weld fractures relative to rotational and travel speeds are observed at the stir zone. The optimum FSW conditions are a welding speed of 124 mm/min and a rotational speed of 800 r/min.

Biological identification and determination of optimum growth conditions for four species of Navicula

Four species in the genus Navicula were isolated using the serial dilution method. Based on scanning elec-tron microscopy （SEM） and sequence comparisons of two segments of genes （small ribosomal subunit and large subunit of Rubisco）, the species were identified asNavicula perminuta,N. pseudacceptata,N. vara, andN. rhynchocephala. Based on phylogenetic analysis and culture trials,there was a close relationship betweenN. perminutaandN. vara. Growth of these species was evaluated using measurements of optical density at 680 nm （OD680） under various environmental factors. Results showed that the optimum culture conditions were 25°C, 50-100 μmol photons m-2 s-1, pH 8.0, and salinities from 25 to 30. However, the favor-able salinity forN. perminuta was surprisingly high at 35. Nutrient requirement analysis demonstrated that growth ofNavicula depended on the availability of SiO32-. Their relative growth rates （RGR） peaked at the highest tested level （0.25 mmol/L）. The optimal concentrations of NO3-and PO43- were 3.6 mmol/L and 0.18 mmol/L, respectively. Culture of theseNavicula species for abalone or sea cucumber aquaculture should take these factors into consideration.

Determination of Optimum Conditions for X-Ray Fluorescence Analysis Using Coupling Equations

Coupling equations used to calculate the chemical composition of substances by X-ray fluorescence analysis can be classified as empirical, theoretical or semi-empirical based on the method for determining the coefficients of the calibration function. The advantages and disadvantages of each class of equations are discussed. Recommendations for the selecting the optimum conditions for determining empirical correction coefficients and their control during analysis are provided.

Conditioned medium from human dental pulp stem cells treats spinal cord injury by inhibiting microglial pyroptosis

Human dental pulp stem cell transplantation has been shown to be an effective therapeutic strategy for spinal cord injury.However,whether the human dental pulp stem cell secretome can contribute to functional recovery after spinal cord injury remains unclear.In the present study,we established a rat model of spinal cord injury based on impact injury from a dropped weight and then intraperitoneally injected the rats with conditioned medium from human dental pulp stem cells.We found that the conditioned medium effectively promoted the recovery of sensory and motor functions in rats with spinal cord injury,decreased expression of the microglial pyroptosis markers NLRP3,GSDMD,caspase-1,and interleukin-1β,promoted axonal and myelin regeneration,and inhibited the formation of glial scars.In addition,in a lipopolysaccharide-induced BV2 microglia model,conditioned medium from human dental pulp stem cells protected cells from pyroptosis by inhibiting the NLRP3/caspase-1/interleukin-1βpathway.These results indicate that conditioned medium from human dental pulp stem cells can reduce microglial pyroptosis by inhibiting the NLRP3/caspase-1/interleukin-1βpathway,thereby promoting the recovery of neurological function after spinal cord injury.Therefore,conditioned medium from human dental pulp stem cells may become an alternative therapy for spinal cord injury.

Uncertainties of landslide susceptibility prediction: Influences of random errors in landslide conditioning factors and errors reduction by low pass filter method

In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.

Mixed D-vine copula-based conditional quantile model for stochastic monthly streamflow simulation

Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate block for all months.To address this limitation,this study developed a mixed D-vine copula-based conditional quantile model that can capture temporal correlations.This model can generate streamflow by selecting different historical streamflow variables as the conditions for different months and by exploiting the conditional quantile functions of streamflows in different months with mixed D-vine copulas.The up-to-down sequential method,which couples the maximum weight approach with the Akaike information criteria and the maximum likelihood approach,was used to determine the structures of multivariate Dvine copulas.The developed model was used in a case study to synthesize the monthly streamflow at the Tangnaihai hydrological station,the inflow control station of the Longyangxia Reservoir in the Yellow River Basin.The results showed that the developed model outperformed the commonly used bivariate copula model in terms of the performance in simulating the seasonality and interannual variability of streamflow.This model provides useful information for water-related natural hazard risk assessment and integrated water resources management and utilization.

Genesis of LCT Pegmatites during Early Paleozoic Orogeny of the North Qinling Orogenic Belt,China:Emplacement Conditions and Structural Control

The Guanpo pegmatite field in the North Qinling orogenic belt(NQB),China,hosts the most abundant LCT pegmatites.However,their emplacement conditions and structural control remain unexplored.In this contribution,we investigated it combining pegmatite orientation measurement with oxygen isotope geothermometry and fluid inclusion study.The orientations of type A1 pegmatites(P_(f)<σ_(2))are predominantly influenced by P-and T-fractures due to simple shearing in Shiziping dextral thrust shear zone during D_(2)deformation,whereas type A2 pegmatites(contemporaneous with D_(4))are governed by hydraulic fractures aligned with S_(0)and S_(0+1)stemming from fluid pressure(P_(f)<σ_(2)).Additionally,type B pegmatites(P_(f)≤σ_(2))exhibit orientations shaped by en echelon extensional fractures in local ductile shear zones(contemporaneous with D_(3)).The albite-quartz oxygen isotope geothermometry and microthermometric analysis of fluid inclusions in elbaites from the latest pegmatites(including types B and A2)suggest that the crystallization P-T for late magmatic and hydrothermal stages are 527.5-559.2℃,320℃,3.1-3.6 kbar and 2.0 kbar,respectively.Our observations along with previous studies suggest that the genesis of the LCT pegmatites was a long-term,multi-stage event during early Paleozoic orogeny(including the collision stage)of the NQB,and was facilitated by various local fractures.

Ambient-Condition Strategy for Production of Hollow Ga_(2)O_(3)@rGO Crystalline Nanostructures Toward Efficient Lithium Storage

Crystallineγ-Ga_(2)O_(3)@rGO core-shell nanostructures are synthesized in gram scale,which are accomplished by a facile sonochemical strategy under ambient condition.They are composed of uniformγ-Ga_(2)O_(3)nanospheres encapsulated by reduced graphene oxide(rGO)nanolayers,and their formation is mainly attributed to the existed opposite zeta potential between the Ga_(2)O_(3)and rGO.The as-constructed lithium-ion batteries(LIBs)based on as-fabricatedγ-Ga_(2)O_(3)@rGO nanostructures deliver an initial discharge capacity of 1000 mAh g^(-1)at 100 mA g^(-1)and reversible capacity of 600 mAh g^(-1)under 500 mA g^(-1)after 1000 cycles,respectively,which are remarkably higher than those of pristineγ-Ga_(2)O_(3)with a much reduced lifetime of 100 cycles and much lower capacity.Ex situ XRD and XPS analyses demonstrate that the reversible LIBs storage is dominant by a conversion reaction and alloying mechanism,where the discharged product of liquid metal Ga exhibits self-healing ability,thus preventing the destroy of electrodes.Additionally,the rGO shell could act robustly as conductive network of the electrode for significantly improved conductivity,endowing the efficient Li storage behaviors.This work might provide some insight on mass production of advanced electrode materials under mild condition for energy storage and conversion applications.

Autologous hematopoietic stem cell transplantation conditioning regimens and chimeric antigen receptor T cell therapy in various diseases

Conditioning regimens employed in autologous stem cell transplantation have been proven useful in various hematological disorders and underlying malignancies;however,despite being efficacious in various instances,negative consequences have also been recorded.Multiple conditioning regimens were extracted from various literature searches from databases like PubMed,Google scholar,EMBASE,and Cochrane.Conditioning regimens for each disease were compared by using various end points such as overall survival(OS),progression free survival(PFS),and leukemia free survival(LFS).Variables were presented on graphs and analyzed to conclude a more efficacious conditioning regimen.In multiple myeloma,the most effective regimen was high dose melphalan(MEL)given at a dose of 200/mg/m2.The comparative results of acute myeloid leukemia were presented and the regimens that proved to be at an admirable position were busulfan(BU)+MEL regarding OS and BU+VP16 regarding LFS.In case of acute lymphoblastic leukemia(ALL),BU,fludarabine,and etoposide(BuFluVP)conferred good disease control not only with a paramount improvement in survival rate but also low risk of recurrence.However,for ALL,chimeric antigen receptor(CAR)T cell therapy was preferred in the context of better OS and LFS.With respect to Hodgkin’s lymphoma,mitoxantrone(MITO)/MEL overtook carmustine,VP16,cytarabine,and MEL in view of PFS and vice versa regarding OS.Non-Hodgkin’s lymphoma patients were administered MITO(60 mg/m2)and MEL(180 mg/m2)which showed promising results.Lastly,amyloidosis was considered,and the regimen that proved to be competent was MEL 200(200 mg/m2).This review article demonstrates a comparison between various conditioning regimens employed in different diseases.

Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.

IoT-based green-smart photovoltaic system under extreme climatic conditions for sustainable energy development

To realize carbon neutrality,there is an urgent need to develop sustainable,green energy systems(especially solar energy systems)owing to the environmental friendliness of solar energy,given the substantial greenhouse gas emissions from fossil fuel-based power sources.When it comes to the evolution of intelligent green energy systems,Internet of Things(IoT)-based green-smart photovoltaic(PV)systems have been brought into the spotlight owing to their cutting-edge sensing and data-processing technologies.This review is focused on three critical segments of IoT-based green-smart PV systems.First,the climatic parameters and sensing technologies for IoT-based PV systems under extreme weather conditions are presented.Second,the methods for processing data from smart sensors are discussed,in order to realize health monitoring of PV systems under extreme environmental conditions.Third,the smart materials applied to sensors and the insulation materials used in PV backsheets are susceptible to aging,and these materials and their aging phenomena are highlighted in this review.This review also offers new perspectives for optimizing the current international standards for green energy systems using big data from IoT-based smart sensors.

Autophagy and mitophagy as potential therapeutic targets in diabetic heart condition:Harnessing the power of nanotheranostics

Autophagy and mitophagy pose unresolved challenges in understanding the pathology of diabetic heart condition(DHC),which encompasses a complex range of cardiovascular issues linked to diabetes and associated cardiomyopathies.Despite significant progress in reducing mortality rates from cardiovascular diseases(CVDs),heart failure remains a major cause of increased morbidity among diabetic patients.These cellular processes are essential for maintaining cellular balance and removing damaged or dysfunctional components,and their involvement in the development of diabetic heart disease makes them attractive targets for diagnosis and treatment.While a variety of conventional diagnostic and therapeutic strategies are available,DHC continues to present a significant challenge.Point-of-care diagnostics,supported by nanobiosensing techniques,offer a promising alternative for these complex scenarios.Although conventional medications have been widely used in DHC patients,they raise several concerns regarding various physiological aspects.Modern medicine places great emphasis on the application of nanotechnology to target autophagy and mitophagy in DHC,offering a promising approach to deliver drugs beyond the limitations of traditional therapies.This article aims to explore the potential connections between autophagy,mitophagy and DHC,while also discussing the promise of nanotechnology-based theranostic interventions that specifically target these molecular pathways.

Oscillation properties of eigenfunctions for Sturm-Liouville problems with interface conditions via Prufer transformation

A class of Sturm-Liouville problems with discontinuity is studied in this paper.The oscillation properties of eigenfunctions for Sturm-Liouville problems with interface conditions are obtained.The main method used in this paper is based on Prufer transformation,which is different from the classical ones.Moreover,we give two examples to verify our main results.

Work Condition and Health at a Body Paint Workshop in Conakry

Context: Working conditions in the car repair sector are difficult in general. This leads to health risk factors for inexperienced staff. In the bodywork painting workshop, the staff seemed less interested in the risks probably due to negligence or by lack of knowledge. This work aimed to describe the working conditions and their impact on the workers’ health in a workshop of bodywork painting in Conakry. Material and Methods: This was a cross-sectional study over 06 months (from July 01, 2021, to December 31, 2021). Were included the bodybuilders-painters, the painters and the bodybuilders. The data was collected during an interview. We analysed the personal data of the workers, the physical environment factors (lighting, noise, etc.) and, the clinical manifestations felt by the workers. Results: The average age was 37 years extenting from 18 to 54 years and, they were all men. Over 80% of workers were exposed to more than 1000 lux and, 78.2% of workers were exposed to the vibratory intensity level of the cordless drill > 2.5 m/s2. The most frequent symptoms were back pain, headache, itchy eyes, and numbness of fingers and hands. The analysis of working conditions and clinical manifestations showed a significant relationship between the level of illumination and the tingling eyes (p = 0.0007), the vibratory intensity of the drill and the numbness of fingers and hands (p = 0.01). This study revealed that some of the complaints cited are related to the working conditions. Conclusion: Working conditions in a bodywork paint workshop are occupational risk factors that become dangerous if they are unknown. A longitudinal study on the assessment of working conditions could better enlighten us on this phenomenon.

Role of outdoor trees on pedestrian wind and thermal conditions around a pre-education building for sustainable energy management

Finding sustainable energy resources is essential to face the increasing energy demand.Trees are an important part of ancient architecture but are becoming rare in urban areas.Trees can control and tune the pedestrian-level wind velocity and thermal condition.In this study,a numerical investigation is employed to assess the role of trees planted in the windward direction of the building complex on the thermal and pedestrian wind velocity conditions around/inside a pre-education building located in the center of the complex.Compared to the previous studies(which considered only outside buildings),this work considers the effects of trees on microclimate change both inside/outside buildings.Effects of different parameters including the leaf area density and number of trees,number of rows,far-field velocity magnitude,and thermal condition around the main building are assessed.The results show that the flow velocity in the spacing between the first-row buildings is reduced by 30%-40% when the one-row trees with 2 m height are planted 15 m farther than the buildings.Furthermore,two rows of trees are more effective in higher velocities and reduce the maximum velocity by about 50%.The investigation shows that trees also could reduce the temperature by about 1℃around the building.