Data-driven prediction of dimensionless quantities for semi-infinite target penetration by integrating machine-learning and feature selection methods

This study employs a data-driven methodology that embeds the principle of dimensional invariance into an artificial neural network to automatically identify dominant dimensionless quantities in the penetration of rod projectiles into semi-infinite metal targets from experimental measurements.The derived mathematical expressions of dimensionless quantities are simplified by the examination of the exponent matrix and coupling relationships between feature variables.As a physics-based dimension reduction methodology,this way reduces high-dimensional parameter spaces to descriptions involving only a few physically interpretable dimensionless quantities in penetrating cases.Then the relative importance of various dimensionless feature variables on the penetration efficiencies for four impacting conditions is evaluated through feature selection engineering.The results indicate that the selected critical dimensionless feature variables by this synergistic method,without referring to the complex theoretical equations and aiding in the detailed knowledge of penetration mechanics,are in accordance with those reported in the reference.Lastly,the determined dimensionless quantities can be efficiently applied to conduct semi-empirical analysis for the specific penetrating case,and the reliability of regression functions is validated.

Investigation on the penetration of jacketed rods with striking velocities of 0.9-3.3 km/s into semi-infinite targets

In this study, a combined experimental, numerical and theoretical investigation is conducted on the penetration of semi-infinite 4340 steel targets by a homogeneous 93 W rod and two types of jacketed rods with striking velocities of 0.9-3.3 km/s. The results show that the jacketed rods produced typical“co-erosion” damage at all test velocities, except for the 93 W/1060 Al jacketed rod, which switched from an early “bi-erosion” damage to later “co-erosion” damage at a striking velocity of 936 m/s. However, the homogeneous 93 W rod always forms a large mushroom head during the penetration process. The damage mechanisms of these two types of jacketed rods differ for striking velocities of 0.9-2.0 km/s, but this difference gradually decreases with increased striking velocity. For velocities of 2.0-3.3 km/s, all three types of projectiles exhibit typical hydrodynamic penetration characteristics, and the damage mechanisms of the two types of jacketed rods are almost identical. For the same initial kinetic energy, the penetration performance of the jacketed rods is distinctly superior to that of the homogeneous 93 W rods.Compared with jacket density, jacket strength shows a more significant influence on the damage mechanism and penetration performance of the jacketed rod. Finally, an existing theoretical prediction model of the penetration depth of jacketed rods on semi-infinite targets in the co-erosion mode is modified. It transpires that-in terms of penetration depth-the modified theoretical model is in good agreement with the experimental and numerical observations for 93 W/TC4 and 93 W/1060 Al jacketed rods penetrating semi-infinite 4340 steel targets.

Analytical models for the penetration of semi-infinite targets by rigid,deformable and erosive long rods

A theoretical study is presented herein on the pen- etration of a semi-infinite target by a spherical-headed long rod for Yp 〉 S, where Yp is the penetrator strength and S is the static target resistance. For Yp 〉 S, depending upon initial impact velocity, there exist three types of penetration, namely, penetration by a rigid long rod, penetration by a deforming non-erosive long rod and penetration by an erosive long rod. If the impact velocity of the penetrator is higher than the hydrodynamic velocity （VH）, it will penetrate the target in an erosive mode; if the impact velocity lies between the hydrodynamic velocity （VH） and the rigid body velocity （VR）, it will penetrate the target in a deformable mode; if the impact velocity is less than the rigid body velocity （VR）, it will penetrate the target in a rigid mode. The critical conditions for the transition among these three penetration modes are proposed. It is demonstrated that the present model predictions correlate well with the experimental observations in terms of depth of penetration （DOP） and the critical transition conditions.

Mitochondrial targeting sequence of magnetoreceptor MagR:More than just targeting

Iron-sulfur clusters(ISC)are essential cofactors for proteins involved in various biological processes,such as electron transport,biosynthetic reactions,DNA repair,and gene expression regulation.ISC assembly protein IscA1(or MagR)is found within the mitochondria of most eukaryotes.Magnetoreceptor(MagR)is a highly conserved A-type iron and iron-sulfur cluster-binding protein,characterized by two distinct types of iron-sulfur clusters,[2Fe-2S]and[3Fe-4S],each conferring unique magnetic properties.MagR forms a rod-like polymer structure in complex with photoreceptive cryptochrome(Cry)and serves as a putative magnetoreceptor for retrieving geomagnetic information in animal navigation.Although the N-terminal sequences of MagR vary among species,their specific function remains unknown.In the present study,we found that the N-terminal sequences of pigeon MagR,previously thought to serve as a mitochondrial targeting signal(MTS),were not cleaved following mitochondrial entry but instead modulated the efficiency with which iron-sulfur clusters and irons are bound.Moreover,the N-terminal region of MagR was required for the formation of a stable MagR/Cry complex.Thus,the N-terminal sequences in pigeon MagR fulfil more important functional roles than just mitochondrial targeting.These results further extend our understanding of the function of MagR and provide new insights into the origin of magnetoreception from an evolutionary perspective.

Classification and technical target of water electrolysis for hydrogen production

Continuous efforts are underway to reduce carbon emissions worldwide in response to global climate change.Water electrolysis technology,in conjunction with renewable energy,is considered the most feasible hydrogen production technology based on the viable possibility of large-scale hydrogen production and the zero-carbon-emission nature of the process.However,for hydrogen produced via water electrolysis systems to be utilized in various fields in practice,the unit cost of hydrogen production must be reduced to$1/kg H_(2).To achieve this unit cost,technical targets for water electrolysis have been suggested regarding components in the system.In this paper,the types of water electrolysis systems and the limitations of water electrolysis system components are explained.We suggest guideline with recent trend for achieving this technical target and insights for the potential utilization of water electrolysis technology.

Targeted regeneration and upcycling of spent graphite by defect‐driven tin nucleation

The recycling of spent batteries has become increasingly important owing to their wide applications,abundant raw material supply,and sustainable development.Compared with the degraded cathode,spent anode graphite often has a relatively intact structure with few defects after long cycling.Yet,most spent graphite is simply burned or discarded due to its limited value and inferior performance on using conventional recycling methods that are complex,have low efficiency,and fail in performance restoration.Herein,we propose a fast,efficient,and“intelligent”strategy to regenerate and upcycle spent graphite based on defect‐driven targeted remediation.Using Sn as a nanoscale healant,we used rapid heating(~50 ms)to enable dynamic Sn droplets to automatically nucleate around the surface defects on the graphite upon cooling owing to strong binding to the defects(~5.84 eV/atom),thus simultaneously achieving Sn dispersion and graphite remediation.As a result,the regenerated graphite showed enhanced capacity and cycle stability(458.9 mAh g^(−1) at 0.2 A g^(−1) after 100 cycles),superior to those of commercial graphite.Benefiting from the self‐adaption of Sn dispersion,spent graphite with different degrees of defects can be regenerated to similar structures and performance.EverBatt analysis indicates that targeted regeneration and upcycling have significantly lower energy consumption(~99%reduction)and near‐zero CO_(2) emission,and yield much higher profit than hydrometallurgy,which opens a new avenue for direct upcycling of spend graphite in an efficient,green,and profitable manner for sustainable battery manufacture.

Mitophagy in intracerebral hemorrhage:a new target for therapeutic intervention

Intracerebral hemorrhage is a life-threatening condition with a high fatality rate and severe sequelae.However,there is currently no treatment available for intracerebral hemorrhage,unlike for other stroke subtypes.Recent studies have indicated that mitochondrial dysfunction and mitophagy likely relate to the pathophysiology of intracerebral hemorrhage.Mitophagy,or selective autophagy of mitochondria,is an essential pathway to preserve mitochondrial homeostasis by clearing up damaged mitochondria.Mitophagy markedly contributes to the reduction of secondary brain injury caused by mitochondrial dysfunction after intracerebral hemorrhage.This review provides an overview of the mitochondrial dysfunction that occurs after intracerebral hemorrhage and the underlying mechanisms regarding how mitophagy regulates it,and discusses the new direction of therapeutic strategies targeting mitophagy for intracerebral hemorrhage,aiming to determine the close connection between mitophagy and intracerebral hemorrhage and identify new therapies to modulate mitophagy after intracerebral hemorrhage.In conclusion,although only a small number of drugs modulating mitophagy in intracerebral hemorrhage have been found thus far,most of which are in the preclinical stage and require further investigation,mitophagy is still a very valid and promising therapeutic target for intracerebral hemorrhage in the long run.

High-speed penetration of ogive-nose projectiles into thick concrete targets:Tests and a projectile nose evolution model

The majority of the projectiles used in the hypersonic penetration study are solid flat-nosed cylindrical projectiles with a diameter of less than 20 mm.This study aims to fill the gap in the experimental and analytical study of the evolution of the nose shape of larger hollow projectiles under hypersonic penetration.In the hypersonic penetration test,eight ogive-nose AerMet100 steel projectiles with a diameter of 40 mm were launched to hit concrete targets with impact velocities that ranged from 1351 to 1877 m/s.Severe erosion of the projectiles was observed during high-speed penetration of heterogeneous targets,and apparent localized mushrooming occurred in the front nose of recovered projectiles.By examining the damage to projectiles,a linear relationship was found between the relative length reduction rate and the initial kinetic energy of projectiles in different penetration tests.Furthermore,microscopic analysis revealed the forming mechanism of the localized mushrooming phenomenon for eroding penetration,i.e.,material spall erosion abrasion mechanism,material flow and redistribution abrasion mechanism and localized radial upsetting deformation mechanism.Finally,a model of highspeed penetration that included erosion was established on the basis of a model of the evolution of the projectile nose that considers radial upsetting;the model was validated by test data from the literature and the present study.Depending upon the impact velocity,v0,the projectile nose may behave as undistorted,radially distorted or hemispherical.Due to the effects of abrasion of the projectile and enhancement of radial upsetting on the duration and amplitude of the secondary rising segment in the pulse shape of projectile deceleration,the predicted DOP had an upper limit.

Precision targeting in hepatocellular carcinoma:Exploring ligandreceptor mediated nanotherapy

Hepatocellular carcinoma(HCC)is the most common primary liver cancer and poses a major challenge to global health due to its high morbidity and mortality.Conventional chemotherapy is usually targeted to patients with intermediate to advanced stages,but it is often ineffective and suffers from problems such as multidrug resistance,rapid drug clearance,nonspecific targeting,high side effects,and low drug accumulation in tumor cells.In response to these limitations,recent advances in nanoparticle-mediated targeted drug delivery technologies have emerged as breakthrough approaches for the treatment of HCC.This review focuses on recent advances in nanoparticle-based targeted drug delivery systems,with special attention to various receptors overexpressed on HCC cells.These receptors are key to enhancing the specificity and efficacy of nanoparticle delivery and represent a new paradigm for actively targeting and combating HCC.We comprehensively summarize the current understanding of these receptors,their role in nanoparticle targeting,and the impact of such targeted therapies on HCC.By gaining a deeper understanding of the receptor-mediated mechanisms of these innovative therapies,more effective and precise treatment of HCC can be achieved.

基于TARGET融合ARCS动机模型的应用统计学课程教学改革研究

学生的学习动机直接关系到课程教学目标的达成,激发学习动机是推动课程教学改革的应有之义。将TARGET和ARCS学习动机模型引入应用统计学课程教学,分析当前教学中存在的动机问题,提出有效激发学生动机的教学方案和实践策略,结果既可促进应用统计学课程教学质量提升,也可为其他相似课程教学设计提供参考借鉴。

Real-time Rescue Target Detection Based on UAV Imagery for Flood Emergency Response

Timely acquisition of rescue target information is critical for emergency response after a flood disaster.Unmanned Aerial Vehicles(UAVs)equipped with remote sensing capabilities offer distinct advantages,including high-resolution imagery and exceptional mobility,making them well suited for monitoring flood extent and identifying rescue targets during floods.However,there are some challenges in interpreting rescue information in real time from flood images captured by UAVs,such as the complexity of the scenarios of UAV images,the lack of flood rescue target detection datasets and the limited real-time processing capabilities of the airborne on-board platform.Thus,we propose a real-time rescue target detection method for UAVs that is capable of efficiently delineating flood extent and identifying rescue targets(i.e.,pedestrians and vehicles trapped by floods).The proposed method achieves real-time rescue information extraction for UAV platforms by lightweight processing and fusion of flood extent extraction model and target detection model.The flood inundation range is extracted by the proposed method in real time and detects targets such as people and vehicles to be rescued based on this layer.Our experimental results demonstrate that the Intersection over Union(IoU)for flood water extraction reaches an impressive 80%,and the IoU for real-time flood water extraction stands at a commendable 76.4%.The information on flood stricken targets extracted by this method in real time can be used for flood emergency rescue.

Deployment optimization for target perpetual coverage in energy harvesting wireless sensor network

Energy limitation of traditional Wireless Sensor Networks(WSNs)greatly confines the network lifetime due to generating and processing massive sensing data with a limited battery.The energy harvesting WSN is a novel network architecture to address the limitation of traditional WSN.However,existing coverage and deployment schemes neglect the environmental correlation of sensor nodes and external energy with respect to physical space.Comprehensively considering the spatial correlation of the environment and the uneven distribution of energy in energy harvesting WSN,we investigate how to deploy a collection of sensor nodes to save the deployment cost while ensuring the target perpetual coverage.The Confident Information Coverage(CIC)model is adopted to formulate the CIC Minimum Deployment Cost Target Perpetual Coverage(CICMTP)problem to minimize the deployed sensor nodes.As the CICMTP is NP-hard,we devise two approximation algorithms named Local Greedy Threshold Algorithm based on CIC(LGTA-CIC)and Overall Greedy Search Algorithm based on CIC(OGSA-CIC).The LGTA-CIC has a low time complexity and the OGSA-CIC has a better approximation rate.Extensive simulation results demonstrate that the OGSA-CIC is able to achieve lower deployment cost and the performance of the proposed algorithms outperforms GRNP,TPNP and EENP algorithms.

Humanβ-defensin-1 affects the mammalian target of rapamycin pathway and autophagy in colon cancer cells through long noncoding RNA TCONS_00014506

BACKGROUND Colorectal cancer has a low 5-year survival rate and high mortality.Humanβ-defensin-1(hBD-1)may play an integral function in the innate immune system,contributing to the recognition and destruction of cancer cells.Long non-coding RNAs(lncRNAs)are involved in the process of cell differentiation and growth.AIM To investigate the effect of hBD-1 on the mammalian target of rapamycin(mTOR)pathway and autophagy in human colon cancer SW620 cells.METHODS CCK8 assay was utilized for the detection of cell proliferation and determination of the optimal drug concentration.Colony formation assay was employed to assess the effect of hBD-1 on SW620 cell proliferation.Bioinformatics was used to screen potentially biologically significant lncRNAs related to the mTOR pathway.Additionally,p-mTOR(Ser2448),Beclin1,and LC3II/I expression levels in SW620 cells were assessed through Western blot analysis.RESULTS hBD-1 inhibited the proliferative ability of SW620 cells,as evidenced by the reduction in the colony formation capacity of SW620 cells upon exposure to hBD-1.hBD-1 decreased the expression of p-mTOR(Ser2448)protein and increased the expression of Beclin1 and LC3II/I protein.Furthermore,bioinformatics analysis identified seven lncRNAs(2 upregulated and 5 downregulated)related to the mTOR pathway.The lncRNA TCONS_00014506 was ultimately selected.Following the inhibition of the lncRNA TCONS_00014506,exposure to hBD-1 inhibited p-mTOR(Ser2448)and promoted Beclin1 and LC3II/I protein expression.CONCLUSION hBD-1 inhibits the mTOR pathway and promotes autophagy by upregulating the expression of the lncRNA TCONS_00014506 in SW620 cells.

Natural gas exploration potential and favorable targets of Permian Fengcheng Formation in the western Central Depression of Junggar Basin,NW China

Based on the organic geochemical data and the molecular and stable carbon isotopic compositions of natural gas of the Lower Permian Fengcheng Formation in the western Central Depression of Junggar Basin,combined with sedimentary environment analysis and hydrocarbon-generating simulation,the gas-generating potential of the Fengcheng source rock is evaluated,the distribution of large-scale effective source kitchen is described,the genetic types of natural gas are clarified,and four types of favorable exploration targets are selected.The results show that:(1)The Fengcheng Formation is a set of oil-prone source rocks,and the retained liquid hydrocarbon is conducive to late cracking into gas,with characteristics of high gas-generating potential and late accumulation;(2)The maximum thickness of Fengcheng source rock reaches 900 m.The source rock has entered the main gas-generating stage in Penyijingxi and Shawan sags,and the area with gas-generating intensity greater than 20×10^(8) m^(3)/km^(2) is approximately 6500 km^(2).(3)Around the western Central Depression,highly mature oil-type gas with light carbon isotope composition was identified to be derived from the Fengcheng source rocks mainly,while the rest was coal-derived gas from the Carboniferous source rock;(4)Four types of favorable exploration targets with exploration potential were developed in the western Central Depression which are structural traps neighboring to the source,stratigraphic traps neighboring to the source,shale-gas type within the source,and structural traps within the source.Great attention should be paid to these targets.

Target acquisition performance in the presence of JPEG image compression

This paper presents an investigation on the effect of JPEG compression on the similarity between the target image and the background,where the similarity is further used to determine the degree of clutter in the image.Four new clutter metrics based on image quality assessment are introduced,among which the Haar wavelet-based perceptual similarity index,known as HaarPSI,provides the best target acquisition prediction results.It is shown that the similarity between the target and the background at the boundary between visually lossless and visually lossy compression does not change significantly compared to the case when an uncompressed image is used.In future work,through subjective tests,it is necessary to check whether this presence of compression at the threshold of just noticeable differences will affect the human target acquisition performance.Similarity values are compared with the results of subjective tests of the well-known target Search_2 database,where the degree of agreement between objective and subjective scores,measured through linear correlation,reached a value of 90%.

Potentials of ribosomopathy gene as pharmaceutical targets for cancer treatment

Ribosomopathies encompass a spectrum of disorders arising from impaired ribosome biogenesis and reduced functionality.Mutation or dysexpression of the genes that disturb any finely regulated steps of ribosome biogenesis can result in different types of ribosomopathies in clinic,collectively known as ribosomopathy genes.Emerging data suggest that ribosomopathy patients exhibit a significantly heightened susceptibility to cancer.Abnormal ribosome biogenesis and dysregulation of some ribosomopathy genes have also been found to be intimately associated with cancer development.The correlation between ribosome biogenesis or ribosomopathy and the development of malignancies has been well established.This work aims to review the recent advances in the research of ribosomopathy genes among human cancers and meanwhile,to excavate the potential role of these genes,which have not or rarely been reported in cancer,in the disease development across cancers.We plan to establish a theoretical framework between the ribosomopathy gene and cancer development,to further facilitate the potential of these genes as diagnostic biomarker as well as pharmaceutical targets for cancer treatment.

An equivalent target plate damage probability calculation mathematics model and damage evaluation method

Aiming at the requirement of damage testing and evaluation of equivalent target plate based on the explosion of intelligent ammunition, this paper proposes a novel method for damage testing and evaluation method of circumferential equivalent target plate. Leveraging the dispersion characteristics parameters of fragment, we establish a calculation model of the fragment power situation and the damage calculation model under the condition of fragment ultimate penetration equivalent target plate. The damage model of equivalent target plate involves the fragment dispersion density, the local perforation damage criterion, the tearing damage model, and the damage probability. We use the camera to obtain the image of the equivalent target plate with fragment perforation, and research the algorithm of fragment distribution position recognition and fragment perforation area calculation method on the equivalent target plate by image processing technology. Based on the obtained parameters of the breakdown position and perforation area of fragments on equivalent target plate, we apply to damage calculation model of equivalent target plate, and calculate the damage probability of each equivalent target plate, and use the combined probabilistic damage calculation method to obtain the damage evaluation results of the circumferential equivalent target plate in an intelligent ammunition explosion experiment. Through an experimental testing, we verify the feasibility and rationality of the proposed damage evaluation method by comparison, the calculation results can reflect the actual damage effect of the equivalent target plate.

Target Detection Algorithm in Foggy Scenes Based on Dual Subnets

Under the influence of air humidity,dust,aerosols,etc.,in real scenes,haze presents an uneven state.In this way,the image quality and contrast will decrease.In this case,It is difficult to detect the target in the image by the universal detection network.Thus,a dual subnet based on multi-task collaborative training(DSMCT)is proposed in this paper.Firstly,in the training phase,the Gated Context Aggregation Network(GCANet)is used as the supervisory network of YOLOX to promote the extraction of clean information in foggy scenes.In the test phase,only the YOLOX branch needs to be activated to ensure the detection speed of the model.Secondly,the deformable convolution module is used to improve GCANet to enhance the model’s ability to capture details of non-homogeneous fog.Finally,the Coordinate Attention mechanism is introduced into the Vision Transformer and the backbone network of YOLOX is redesigned.In this way,the feature extraction ability of the network for deep-level information can be enhanced.The experimental results on artificial fog data set FOG_VOC and real fog data set RTTS show that the map value of DSMCT reached 86.56%and 62.39%,respectively,which was 2.27%and 4.41%higher than the current most advanced detection model.The DSMCT network has high practicality and effectiveness for target detection in real foggy scenes.

Inflammatory signaling in targeted therapy resistance:focus on EGFR-targeted treatment

Gene mutations drive oncogene addiction in tumor cells,presenting opportunities for targeted gene therapy.Currently,targeted therapy is one of the most effective cancer treatment modalities.However,tumor cells demonstrate remarkable plasticity,acquiring genetic mutations or activating alternative signaling pathways to evade targeted agents.Drug resistance frequently emerges,significantly diminishing the efficacy of targeted therapy.The precise causes of this resistance is unclear.The intricate interplay of immune and inflammatory pathways is integral to cancer development and response to treatment.Emerging evidence suggests that inflammatory pathways have pivotal roles in mediating resistance to targeted therapies across various cancer types,yet the exact mechanisms remain obscure.Herein we present an overview of the mechanisms underlying resistance to targeted therapies induced by inflammatory signaling,with a particular focus on inflammatory-driven resistance to EGFR-targeted therapies.

Bone targeted nano-drug and nano-delivery

There are currently no targeted delivery systems to satisfactorily treat bone-related disorders.Many clinical drugs consisting of small organic molecules have a short circulation half-life and do not effectively reach the diseased tissue site.This coupled with repeatedly high dose usage that leads to severe side effects.