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.

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.

Design and high-power testing of offline conditioning cavity for CiADS RFQ high-power coupler

To validate the design rationality of the power coupler for the RFQ cavity and minimize cavity contamination,we designed a low-loss offline conditioning cavity and conducted high-power testing.This offline cavity features two coupling ports and two tuners,operating at a frequency of 162.5 MHz with a tuning range of 3.2 MHz.Adjusting the installation angle of the coupling ring and the insertion depth of the tuner helps minimize cavity losses.We performed electromagnetic structural and multiphysics simulations,revealing a minimal theoretical power loss of 4.3%.However,when the cavity frequency varied by110 kHz,theoretical power losses increased to10%,necessitating constant tuner adjustments during conditioning.Multiphysics simulations indicated that increased cavity temperature did not affect frequency variation.Upon completion of the offline high-power conditioning platform,we measured the transmission performance,revealing a power loss of 6.3%,exceeding the theoretical calculation.Conditioning utilized efficient automatic range scanning and standing wave resonant methods.To fully condition the power coupler,a 15°phase difference between two standing wave points in the condition-ing system was necessary.Notably,the maximum continuous wave power surpassed 20 kW,exceeding the expected target.

Tailoring Classical Conditioning Behavior in TiO_(2) Nanowires:ZnO QDs-Based Optoelectronic Memristors for Neuromorphic Hardware

Neuromorphic hardware equipped with associative learn-ing capabilities presents fascinating applications in the next generation of artificial intelligence.However,research into synaptic devices exhibiting complex associative learning behaviors is still nascent.Here,an optoelec-tronic memristor based on Ag/TiO_(2) Nanowires:ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning behaviors.Effective implementation of synaptic behaviors,including long and short-term plasticity,and learning-forgetting-relearning behaviors,were achieved in the device through the application of light and electrical stimuli.Leveraging the optoelectronic co-modulated characteristics,a simulation of neuromorphic computing was conducted,resulting in a handwriting digit recognition accuracy of 88.9%.Furthermore,a 3×7 memristor array was constructed,confirming its application in artificial visual memory.Most importantly,complex biological associative learning behaviors were emulated by mapping the light and electrical stimuli into conditioned and unconditioned stimuli,respectively.After training through associative pairs,reflexes could be triggered solely using light stimuli.Comprehen-sively,under specific optoelectronic signal applications,the four features of classical conditioning,namely acquisition,extinction,recovery,and generalization,were elegantly emulated.This work provides an optoelectronic memristor with associative behavior capabilities,offering a pathway for advancing brain-machine interfaces,autonomous robots,and machine self-learning in the future.

Operating Parameters of the District Heating Substation Cooperating With the Installation of Technological Air Conditioning With High Efficiency of Heat Recovery

The article analyses the problem of determining the operating parameters of the district heating substation cooperating with the air heating system in technological air conditioning systems equipped with heat exchangers with high efficiency of heat recovery.Attention was paid to the correct selection of heat exchangers for the heat output balance depending on the heat recovery protection algorithms against a drop in the temperature of the heat transfer surface below 0℃.Critical parameters were determined in Polish climatic conditions,at which the operation of the heat recovery exchanger in the air conditioning system is switched off or limited.It has been proven that the proper functioning of the district heating substation cooperating with the installation of air conditioning with high heat recovery efficiency requires the use of two heat exchangers with different characteristics,equipped with properly selected temperature control systems.The optimal model of cooperation between the technological air conditioning system and the heating substation was also indicated.

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.

Analysis and Modeling of the Central Air-Conditioning System in Intelligent Buildings

The central air conditioning system in an intelligent building (IB) was analyzed and modeled in order to perform the optimization scheduling strategy of the central air conditioning system. A set of models proposed and a type of periodically autoregressive model (PAR) based on the improved genetic algorithms (IGA) were used to perform the optimum energy saving scheduling. The example of the Liangmahe Plaza was taken to show the effectiveness of the methods.

磁共振AIR-魔毯线圈在胸椎结核扫描中的应用价值

目的探讨联合应用AIR-魔毯线圈磁共振成像(MRI)对胸椎结核扫描图像信噪比(signal to noise ratio,SNR)、对比噪声比(contrast to noise ratio,CNR)和脂肪抑制成像效果的价值。方法选取我院80例经手术病理证实为胸椎结核患者,按1:1随机分为两组,应用常规线圈(脊柱相控阵线圈,头颈联合线圈)、常规线圈联合AIR魔毯线圈对两组患者分别进行扫描。扫描序列包括胸椎矢状位T_(2)WI,T_(1)WI,T_(2)FLEX,进一步测量、比较SNR,CNR及脂肪抑制效果,分析MRI多序列诊断胸腰椎结核的准确率、特异度和灵敏度。结果常规线圈联合AIR-魔毯线圈扫描组,胸椎矢状位图像的SNR、CNR及压脂效果优于常规线圈组。结论联合应用AIR-魔毯线圈的图像SNR、CNR得到提高,脂肪抑制效果稳定良好。

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%.

Landslide susceptibility prediction using slope unit-based machine learning models considering the heterogeneity of conditioning factors

To perform landslide susceptibility prediction(LSP),it is important to select appropriate mapping unit and landslide-related conditioning factors.The efficient and automatic multi-scale segmentation(MSS)method proposed by the authors promotes the application of slope units.However,LSP modeling based on these slope units has not been performed.Moreover,the heterogeneity of conditioning factors in slope units is neglected,leading to incomplete input variables of LSP modeling.In this study,the slope units extracted by the MSS method are used to construct LSP modeling,and the heterogeneity of conditioning factors is represented by the internal variations of conditioning factors within slope unit using the descriptive statistics features of mean,standard deviation and range.Thus,slope units-based machine learning models considering internal variations of conditioning factors(variant slope-machine learning)are proposed.The Chongyi County is selected as the case study and is divided into 53,055 slope units.Fifteen original slope unit-based conditioning factors are expanded to 38 slope unit-based conditioning factors through considering their internal variations.Random forest(RF)and multi-layer perceptron(MLP)machine learning models are used to construct variant Slope-RF and Slope-MLP models.Meanwhile,the Slope-RF and Slope-MLP models without considering the internal variations of conditioning factors,and conventional grid units-based machine learning(Grid-RF and MLP)models are built for comparisons through the LSP performance assessments.Results show that the variant Slopemachine learning models have higher LSP performances than Slope-machine learning models;LSP results of variant Slope-machine learning models have stronger directivity and practical application than Grid-machine learning models.It is concluded that slope units extracted by MSS method can be appropriate for LSP modeling,and the heterogeneity of conditioning factors within slope units can more comprehensively reflect the relationships between conditioning factors and landslides.The research results have important reference significance for land use and landslide prevention.

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.

Air-condition process for scalable fabrication of CdS/ZnS 1D/2D heterojunctions toward efficient and stable photocatalytic hydrogen production

We report the scalable fabrication of CdS/ZnS 1D/2D heterojunctions under ambient air conditions(i.e.,room temperature and atmospheric pressure)in which ZnS nanoparticles are anchored on the surface of CdS nanosheets.The as-formed heterojunctions exhibit a significantly enhanced photocatalytic H_(2) evolution rate of 14.02 mmol h^(-1) g^(-1) when irradiated with visible light,which is~10 and 85 times higher than those of pristine CdS nanosheets and CdS nanoparticles,respectively,and superior to most of the CdS-based photocatalysts reported to date.Furthermore,they provide robust photocatalytic performance with demonstratable stability over 58 h,indicating their potential for practical applications.The formation of 1D/2D heterojunctions not only provides improved exposed active sites that respond to illumination but also provides a rapid pathway to generate photogenerated carriers for efficient separation and transfer through the matrix of single-crystalline CdS nanosheets.In addition,first-principles simulations demonstrate that the existence of rich Zn vacancies increases the energy level of the ZnS valence band maximum to construct type-II and Z-scheme mixed heterojunctions,which plays a critical role in suppressing the recombination of carriers with limited photocorrosion of CdS to enhance photocatalytic behavior.

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.

Modelling of a Two-Phase Thermosyphon Loop for Passive Air-Conditioning of a House in Hot and Dry Climate Countries

The two-phase thermosyphon loop is an efficient solution for space cooling. This paper presents the simulation results of numerical studies on the heat transfer and thermal performance of a two-phase thermosiphon loop for passive air-conditioning of a house. The fluid considered in this study is methanol, which is compatible with copper and is environmentally friendly. These numerical results show that the temperature at the evaporator wall drops from 23°C to 13°C and increases at the condenser. The solar flux density has a strong influence on the condenser temperature. The mass flow rates and masses at the evaporator and condenser increase with temperature. The variation of evaporating and condensing temperature affects the performance of the system. For a constant evaporating and condensing temperature of 2°C and 29°C, the COP is 0.77 and 0.84 respectively. With these results, the use of the two-phase thermosyphon loop in air conditioning is possible to obtain a thermal comfort of the occupants acceptable by the standards but with a large exchange surface of the evaporator.

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.

Localized Theoretical Analysis of Thermal Performance of Individually Finned Heat Pipe Heat Exchanger for Air Conditioning with Freon R404A as Working Fluid

This work contributes to the improvement of energy-saving in air conditioning systems. The objective is to apply the thermal efficiency of heat exchangers for localized determination of the thermal performance of heat exchangers with individually finned heat pipes. The fundamental parameters used for performance analysis were the number of fins per heat pipe, the number of heat pipes, the inlet temperatures, and the flow rates of hot and cold fluids. The heat exchanger under analysis uses Freon 404A as a working fluid in an air conditioning system for cooling in the Evaporator and energy recovery in the Condenser. The theoretical model is localized and applied individually to the Evaporator, Condenser, and heat exchanger regions. The results obtained through the simulation are compared with experimental results that use a global approach for the heat exchanger. The thermal quantities obtained through the theoretical model in the mentioned regions are air velocity, Nusselt number, thermal effectiveness, heat transfer rate, and outlet temperature. The comparisons made with global experimental results are in excellent agreement, demonstrating that the localized theoretical approach developed is consistent and can be used as a comprehensive analysis tool for heat exchangers using heat pipes.

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.

System design and analysis of the trans-critical carbon-dioxide automotive air-conditioning system

As an environmentally harmless and feasible alternate refrigerant, CO 2 has attracted worldwide attention, especially in the area of automobile air conditioning (AAC). The thermal property of CO 2 and its trans critical refrigeration cycle is very different from that of the traditional CFC or HCFC system. The detailed process of CO 2 system thermal cycle design and optimization is described in this paper. System prototype and performance test bench were developed to analyze the performance of the CO 2 AAC system.

Localized Theoretical Analysis of Thermal Performance of Individually Finned Heat Pipe Heat Exchanger for Air Conditioning with Freon R404A as Working Fluid

This work contributes to the improvement of energy-saving in air conditioning systems. The objective is to apply the thermal efficiency of heat exchangers for localized determination of the thermal performance of heat exchangers with individually finned heat pipes. The fundamental parameters used for performance analysis were the number of fins per heat pipe, the number of heat pipes, the inlet temperatures, and the flow rates of hot and cold fluids. The heat exchanger under analysis uses Freon 404A as a working fluid in an air conditioning system for cooling in the Evaporator and energy recovery in the Condenser. The theoretical model is localized and applied individually to the Evaporator, Condenser, and heat exchanger regions. The results obtained through the simulation are compared with experimental results that use a global approach for the heat exchanger. The thermal quantities obtained through the theoretical model in the mentioned regions are air velocity, Nusselt number, thermal effectiveness, heat transfer rate, and outlet temperature. The comparisons made with global experimental results are in excellent agreement, demonstrating that the localized theoretical approach developed is consistent and can be used as a comprehensive analysis tool for heat exchangers using heat pipes.

A Case Study:Distribution of Bacterial and Fungal Aerosols in Air-Conditioning Systems in Shaanxi History Museum

In order to investigate the bacteria and fungi aerosol characteristic distribution in HVAC-system and its components at Shaanxi History Museum.Measurements were performed to probe the bacteria and fungi aerosol in HVAC systems,located at Xi'an city,China.The results showed that there was fungi growth inside the ventilation ducts,fungi contamination was worse than bacteria,and both of them were distributed into occupied space with the air supply ducts.The dominating genera of fungi was found to be Penicillium spp.and Aspergillus spp.,which was respectively 46.1% and 20.7% in settling fungi,and the dominating genera of fungi in dust were Cladosporium spp.and Penicillium spp.,which was 41.8% and 30.1% respectively.It suggests that available measures to improve and control the performance of HVAC-systems such as the maintenance,management and cleaning should be taken to prevent this pollution and to develop strategies to keep this pollution away.