Prediction and driving factors of forest fire occurrence in Jilin Province,China

Forest fires are natural disasters that can occur suddenly and can be very damaging,burning thousands of square kilometers.Prevention is better than suppression and prediction models of forest fire occurrence have developed from the logistic regression model,the geographical weighted logistic regression model,the Lasso regression model,the random forest model,and the support vector machine model based on historical forest fire data from 2000 to 2019 in Jilin Province.The models,along with a distribution map are presented in this paper to provide a theoretical basis for forest fire management in this area.Existing studies show that the prediction accuracies of the two machine learning models are higher than those of the three generalized linear regression models.The accuracies of the random forest model,the support vector machine model,geographical weighted logistic regression model,the Lasso regression model,and logistic model were 88.7%,87.7%,86.0%,85.0%and 84.6%,respectively.Weather is the main factor affecting forest fires,while the impacts of topography factors,human and social-economic factors on fire occurrence were similar.

Hydraulic Fracture Parameter Inversion Method for Shale GasWells Based on Transient Pressure-Drop Analysis during Hydraulic Fracturing Shut-in Period

Horizontal well drilling and multi-stage hydraulic fracturing are key technologies for the development of shale gas reservoirs.Instantaneous acquisition of hydraulic fracture parameters is crucial for evaluating fracturing effectiveness,optimizing processes,and predicting gas productivity.This paper establishes a transient flow model for shale gas wells based on the boundary element method,achieving the characterization of stimulated reservoir volume for a single stage.By integrating pressure monitoring data following the pumping shut-in period of hydraulic fracturing for well testing interpretation,a workflow for inverting fracture parameters of shale gas wells is established.This new method eliminates the need for prolonged production testing and can interpret parameters of individual hydraulic fracture segments,offering significant advantages over the conventional pressure transient analysismethod.The practical application of thismethodology was conducted on 10 shale gaswellswithin the Changning shale gas block of Sichuan,China.The results show a high correlation between the interpreted single-stage total length and surface area of hydraulic fractures and the outcomes of gas production profile tests.Additionally,significant correlations are observed between these parameters and cluster number,horizontal stress difference,and natural fracture density.This demonstrates the effectiveness of the proposed fracture parameter inversion method and the feasibility of field application.The findings of this study aim to provide solutions and references for the inversion of fracture parameters in shale gas wells.

Gene Cloning and Bioinformatics Analysis of phoR Gene from Vibrio alginolyticus HY9901

PhoR is a histidine kinase in a two-component regulatory system that regulates phosphorus metabolic pathways and undertakes the key mission of information transmission in pathogenic bacteria.The full-length phoR gene was successfully cloned from the Vibrio alginolyticus HY9901 strain.A comprehensive analysis of the cloned gene was conducted using bioinformatics.Sequence analysis revealed that the total length of the phoR gene(GenBank accession No.:KJ958404.1)is 1299 bp,with the coding region containing a total of 432 amino acid residues.The phylogenetic tree of PhoR revealed that it belongs to the same subclade as V.diabolicus.The SMART program was employed for the purpose of functional domain prediction,which revealed that PhoR possesses three major functional domains:PAS(amino acids 98-166),HisKA(amino acids 205-272),and HATPase_c(amino acids 317-429).

甲磺酸阿帕替尼治疗二线化疗失败上皮性卵巢癌的疗效分析

目的:探讨甲磺酸阿帕替尼治疗二线化疗失败上皮性卵巢癌(epithelial ovarian cancer,EOC)患者的疗效与安全性。方法:收集2017年9月至2018年11月46例天津医科大学肿瘤医院收治的二线化疗失败的复发性EOC患者的临床资料,分析甲磺酸阿帕替尼的疗效及治疗相关的不良事件,并评估其安全性。结果:46例患者的中位随访时间为12个月,中位总生存(overall survival,OS)时间为6(2~15)个月。客观缓解率(objective response rate,ORR)为26.1%(12/46),疾病控制率(disease control rate,DCR)为86.9%(40/46)。46例患者中30例(65.2%)出现不良反应,主要为1~2级,最常见的治疗相关不良反应为高血压占39.1%(18/46),手足皮肤综合征占30.4%(14/46),仅1例患者出现3级治疗相关性高血压,所有患者的1、2级不良事件均能迅速缓解,且甲磺酸阿帕替尼治疗后患者耐受性良好。结论:甲磺酸阿帕替尼对于二线化疗失败的EOC患者可能是一种安全且有效的治疗选择,但仍需开展大规模的临床试验进一步研究。

Exploring the employment readiness and return to work status of breast cancer patients and related factors

Objective:To investigate the employment status,employment readiness,and other factors affecting the ease or difficulty with which breast cancer patients effect their return to work(RTW).Methods:This study adopted a mixed-method design,recruiting participants from among breast cancer patients in a cancer hospital in Hunan from December 2018 to June 2019.We approached 300 individuals,192 of whom ultimately participated in this study.The quantitative part of the study involved several scales:the Patient Health Questionnaire-9(PHQ-9),the Brief Fatigue Inventory(BFI),the Work Ability Index(WAI),and the Lam Assessment of Employment Readiness(LASER).The qualitative part involved a set of open-ended questions and written responses collected from 41 participants who had already returned to work at the time of data collection.Their written responses mainly concerned factors influencing RTW.Results:Forty-one breast cancer patients had returned to work.The results reported a median total Cognitive Symptom Checklist score of 9.00(6.00,15.25),a median WAI score of 5.00(3.50,9.75),a median BFI score of 26.00(14.75,42.00),a median total PHQ-9 score of 8.00(5.25,17.00),and a LASER score of 50.35±11.90.Multiple regression analysis showed that the participants’cancer stage,cognitive limitations,depression,fatigue,and work ability were significant predictors of employment readiness(P<0.05).Exploring the qualitative data,we found that higher skill levels,better social support,and a flexible work schedule facilitated RTW;stress,lack of confidence in one’s work skills,depression,and fatigue are all possible barriers to RTW.Conclusion:The findings indicate that breast cancer patients have a low level of employment readiness.Nurses and other healthcare providers can develop relevant interventions to promote employment readiness and ultimately achieve RTW in this study population.

Noninherited Factors in Fetal Congenital Heart Diseases Based on Bayesian Network:A Large Multicenter Study

Background:Current studies have confirmed that fetal congenital heart diseases(CHDs)are caused by various factors.However,the quantitative risk of CHD is not clear given the combined effects of multiple factors.Objective:This cross-sectional study aimed to detect associated factors of fetal CHD using a Bayesian network in a large sample and quantitatively analyze relative risk ratios(RRs).Methods:Pregnant women who underwent fetal echocardiography(N=16,086 including 3,312 with CHD fetuses)were analyzed.Twenty-six maternal and fetal factors were obtained.A Bayesian network is constructed based on all variables through structural learning and parameter learning methods to find the environmental factors that directly and indirectly associated with outcome,and the probability of fetal CHD in the two groups is predicted through a junction tree reasoning algorithm,so as to obtain RR for fetal CHD under different exposure factor combinations.Taking into account the effect of gestational week on the accuracy of model prediction,we conducted sensitivity analysis on gestational week groups.Results:The single-factor analysis showed that the RRs for the numbers of births,spontaneous abortions,and parental smoking were 1.50,1.38,and 1.11(P<0.001),respectively.The risk gradually increased with the synergistic effect of ranging from one to more environmental factors above.The risk was higher among subjects with five synergistic factors,including the number of births,upper respiratory tract infection during early pregnancy,anemia,and mental stress as well as a history of spontaneous abortions or parental smoking,than in those with less than 5 factors(RR=2.62 or 2.28,P<0.001).This result was consistent across the participants grouped by GWs.Conclusion:We identified six factors that were directly associated with fetal CHD.A higher number of these factors led to a higher risk of CHD.These findings suggest that it is important to strengthen healthcare and prenatal counseling for women with these factors.

Investigation of Movement and Deposition Behaviors of Solid Particles in Hydraulic Water Reservoir via the CFD‑DEM Coupling Method

Solid contamination existing as solid particles in power fluid transmission systems may lead to transmission performance reduction,system failures,and component damage.The hydraulic reservoir will deposit the contamination and store hydraulic fluid.To investigate its purification ability for solid contamination,experiments and simulations for the motion and deposition status of the typical hydraulic system particles are carried out to reveal the interaction of particles and fluid in hydraulic water reservoirs.The results show that the CFD-DEM coupling method could predict the accurate deposition position of iron particles and sand particles when ignoring the small-scale turbulence effect in the flow field.Besides,the particle motion traces and deposition patterns in the reservoir illustrate that the flow development on the bottom surface results in the particles turning,and particles tend to settle in the low flow energy position.The motion of particles is also linked to particles Stokes number,and the same-size sand particles are easily driven by the fluid.The contribution of this paper could provide a guide for predicting the particle motion and deposition pattern in the hydraulic reservoir.

Double-face intelligent hole position planning method for precision blasting in roadways using a computer-controlled drill jumbo

To solve the uneven burden of same-type holes reducing the blasting efficiency due to the limitation of drilling equipment,we need a double-face program-controlled planning method for hole position parameters used on a computer-controlled drilling jumbo.The cross-section splits into even and uneven areas.It also considers the uneven burden at the hole’s entrance and bottom.In the uneven area,various qualifying factors are made to optimize the hole spacing and maximize the burden uniformity,combined with the features of the area edges and gridbased segmentation methods.The hole position coordinates and angles in the even area are derived using recursion and iteration algorithms.As a case,this method presents all holes in a 4.8 m wide and 3.6 m high cross-section.Compared with the design produced by the drawing method,our planning in the uneven area improved the standard deviation of the hole burden by 40%.The improved hole layout facilitates the evolution of precise,efficient,and intelligent blasting in underground mines.

HY-PC:Enabling Consistent Positioning and Communication Using Visible Light

Visible light(VL)plays an important role in achieving high-precision positioning and low bit error radio(BER)data communication.However,most VL-based systems can not achieve positioning and communication,simultaneously.There are two problems:1)the hybrid systems are difficult to extract distinguishable positioning beacon features without affecting communication performance,2)in the hybrid systems,the lost data bits in the inter-frame gap(IFG)are hard to recover,which affects positioning and communication performance.Therefore,in this article,we propose a novel VL-based hybrid positioning and communication system,named HY-PC system,to solve the above problems.First,we propose the robust T-W mapping for recognizing specific Light Emitting Diodes(LEDs),which can provide stable LED recognition accuracy without adding extra beacon data and does not decrease the communication rate.Furthermore,we also propose the novel linear block coding and bit interleaving mechanism,which can recover the lost data bits in the IFG and improve data communication performance.Finally,we use commercial off-the-shelf devices to implement our HY-PC system,extensive experimental results show that our HY-PC system can achieve consistent high-precision positioning and low-BER data communication,simultaneously.

Dynamic Visible Light Positioning Based on Enhanced Visual Target Tracking

In visible light positioning systems,some scholars have proposed target tracking algorithms to balance the relationship among positioning accuracy,real-time performance,and robustness.However,there are still two problems:(1)When the captured LED disappears and the uncertain LED reappears,existing tracking algorithms may recognize the landmark in error;(2)The receiver is not always able to achieve positioning under various moving statuses.In this paper,we propose an enhanced visual target tracking algorithm to solve the above problems.First,we design the lightweight recognition/demodulation mechanism,which combines Kalman filtering with simple image preprocessing to quickly track and accurately demodulate the landmark.Then,we use the Gaussian mixture model and the LED color feature to enable the system to achieve positioning,when the receiver is under various moving statuses.Experimental results show that our system can achieve high-precision dynamic positioning and improve the system’s comprehensive performance.

MBB-IoT:Construction and Evaluation of IoT DDoS Traffic Dataset from a New Perspective

Distributed Denial of Service(DDoS)attacks have always been a major concern in the security field.With the release of malware source codes such as BASHLITE and Mirai,Internet of Things(IoT)devices have become the new source of DDoS attacks against many Internet applications.Although there are many datasets in the field of IoT intrusion detection,such as Bot-IoT,ConstrainedApplication Protocol–Denial of Service(CoAPDoS),and LATAM-DDoS-IoT(some of the names of DDoS datasets),which mainly focus on DDoS attacks,the datasets describing new IoT DDoS attack scenarios are extremely rare,and only N-BaIoT and IoT-23 datasets used IoT devices as DDoS attackers in the construction process,while they did not use Internet applications as victims either.To supplement the description of the new trend of DDoS attacks in the dataset,we built an IoT environment with mainstream DDoS attack tools such as Mirai and BASHLITE being used to infect IoT devices and implement DDoS attacks against WEB servers.Then,data aggregated into a dataset namedMBB-IoTwere captured atWEBservers and IoT nodes.After the MBB-IoT dataset was split into a training set and a test set,it was applied to the training and testing of the Random Forests classification algorithm.The multi-class classification metrics were good and all above 90%.Secondly,in a cross-evaluation experiment based on Support Vector Machine(SVM),Light Gradient Boosting Machine(LightGBM),and Long Short Term Memory networks(LSTM)classification algorithms,the training set and test set were derived from different datasets(MBB-IoT or IoT-23),and the test performance is better when MBB-IoT is used as the training set.

An Intelligent Algorithm for Solving Weapon-Target Assignment Problem:DDPG-DNPE Algorithm

Aiming at the problems of traditional dynamic weapon-target assignment algorithms in command decisionmaking,such as large computational amount,slow solution speed,and low calculation accuracy,combined with deep reinforcement learning theory,an improved Deep Deterministic Policy Gradient algorithm with dual noise and prioritized experience replay is proposed,which uses a double noise mechanism to expand the search range of the action,and introduces a priority experience playback mechanism to effectively achieve data utilization.Finally,the algorithm is simulated and validated on the ground-to-air countermeasures digital battlefield.The results of the experiment show that,under the framework of the deep neural network for intelligent weapon-target assignment proposed in this paper,compared to the traditional RELU algorithm,the agent trained with reinforcement learning algorithms,such asDeepDeterministic Policy Gradient algorithm,Asynchronous Advantage Actor-Critic algorithm,Deep Q Network algorithm performs better.It shows that the use of deep reinforcement learning algorithms to solve the weapon-target assignment problem in the field of air defense operations is scientific.In contrast to other reinforcement learning algorithms,the agent trained by the improved Deep Deterministic Policy Gradient algorithm has a higher win rate and reward in confrontation,and the use of weapon resources is more efficient.It shows that the model and algorithm have certain superiority and rationality.The results of this paper provide new ideas for solving the problemof weapon-target assignment in air defense combat command decisions.

Early Identification and Diagnosis of Adrenal Crisis after Retroperitoneal Laparoscopic Unilateral Adrenalectomy

The occurrence of adrenal crisis after retroperitoneal laparoscopic unilateral adrenalectomy is usually concealed.If not timely diagnosis and treatment,it may cause shock,and even lead to death.It is very difficult to distinguish the clinical manifestations of adrenal crisis from nausea,vomiting,fatigue,gas separation from the lower diaphragm,abdominal pain,hypotension,hypertension,fever and hypothermia after operation.This makes it very difficult to identify and diagnose adrenal crisis early.This article mainly discusses the early recognition,diagnosis and treatment of adrenal crisis after unilateral adrenalectomy by retroperitoneoscope.

Analysis and Defense of Network Attacking Based on the Linux Server

The kernel of the Linux server is analyzed to find out the main cause of the server’s denial of service when it is attacked. In the kernel, when the connection request information memory is full, the new connection request is discarded. Therefore, the printk function was used to alert the kernel output log when the memory was full, the processing of discarding the connection request in the kernel was changed, and the function tcp_syn_flood_action was applied to full memory processing. In the function tcp_syn_flood_action, the free function was used to release the memory according to the condition, so that the new connection request has a storage space, thereby offering the server’s normal service. Finally, the proposed defense technology is verified to be effective.

Validation Research on the Application of Depthwise Separable Convolutional Al Facial Expression Recognition in Non-pharmacological Treatment of BPSD

One of the most obvious clinical reasons of dementia or The Behavioral and Psychological Symptoms of Dementia(BPSD)are the lack of emotional expression,the increased frequency of negative emotions,and the impermanence of emotions.Observing the reduction of BPSD in dementia through emotions can be considered effective and widely used in the field of non-pharmacological therapy.At present,this article will verify whether the image recognition artificial intelligence(AI)system can correctly reflect the emotional performance of the elderly with dementia through a questionnaire survey of three professional elderly nursing staff.The ANOVA(sig.=0.50)is used to determine that the judgment given by the nursing staff has no obvious deviation,and then Kendall's test(0.722**)and spearman's test(0.863**)are used to verify the judgment severity of the emotion recognition system and the nursing staff unanimously.This implies the usability of the tool.Additionally,it can be expected to be further applied in the research related to BPSD elderly emotion detection.

Alkali-resistant NO_(x) reduction over FeVO_(4)/TiO_(2)catalysts via regulating the electron transfer between Fe and V

The presence of alkali metals in exhaust gas from stationary resources causes a grand challenge for the practical application of selective catalytic reduction(SCR)of NO_(x) with NH_(3).Here,alkali-resistant NO_(x) reduction has been successfully implemented via tailoring the electron transfer over Fe and V species on FeVO_(4)/TiO_(2)catalysts.The strong interaction between Fe and V induced electron transfer from V to Fe and strengthened the adsorption and activation of NH_(3)and NO over active VO_(x) sites.In the presence of K_(2)O,the strong electron withdrawing effect of Fe offset the electron donating effect of K on the VO_(x) species,thus protecting the active species VO_(x) to maintain the NO_(x) reduction ability.The enhanced adsorption and activation of NH_(3) allowed SCR reaction to proceed via E-R mechanism even after K_(2)O poisoning.This work elucidated the electronic effects on the alkali metals resistance of traditional ferric vanadate SCR catalysts and provided a promising strategy to design SCR catalysts with superior alkali resistance.

Multiple interface coupling on natural tourmaline enables high-efficiency removal of antibiotic:Superior property and mechanism

Reasonably designing highly active,environmentally friendly,and cost-effective catalysts for efficient elimination of pollutants from water is desirable but challenging.Herein,an efficient heterogeneous photo-Fenton catalyst tourmaline(TM)/tungsten oxide(WO_(3-x))(named TW10)containing tungsten/boron/iron(W/B/Fe)synergistic active centers and 90%of cheap natural tourmaline(TM)mineral rich in Fe and B elements.The TW10 catalyst can quickly activate peroxymonosulfate(PMS)to generate massive active free radicals,which may induce the rapid and efficient degradation of tetracycline(TC).The TW10/PMS/Visible light system can effectively degrade up to 98.7%of tetracycline(TC)in actual waters(i.e.seawater,Yellow River,and Yangtze River water),and the catalytic degradation rates reach 1.65,5.569,and 2.38 times higher than those of TM,WO_(3-x),and commercial P25(Degussa,Germany),respectively.In addition,the catalyst can be recycled and reused multiple times.Electron spin resonance spectroscopy(EPR),X-ray photoelectron spectroscopy(XPS),and liquid chromatograph-mass spectrometer(LC-MS)analyses confirm that the synergistic catalytic effect of W/B/Fe sites on the TW10 catalyst accelerates the electron transfer between Fe(Ⅱ)and Fe(Ⅲ),as well as between W(Ⅴ)and W(Ⅵ),and thus promotes the rapid degradation of TC.The catalytic reaction mechanism and degradation pathway of TC were explored.This work provides a feasible route for the design and development of new eco-friendly and efficient catalyst.

Structural evolution and zero-field SMM behaviour in ferromagnetically-coupled disk-type Co_(7)clusters bearing exclusively end-on azido bridges

Concise chemistry leads to a family of heptanuclear Co^(Ⅱ)-clusters,[Co_(7)(N_(3))_(12)(CH_(3)CN)_(12)][Y_(2)(NO_(3))_(4)(piv)_(4)]·2CH_(3)CN(DC1)(pivH=pivalic acid),[Co_(7)(N_(3))_(12)(CH_(3)CN)_(10)(NO_(3))_(0.4)(Cl)_(1.6)]·4CH_(3)CN(DC2)and[Co_(7)(N_(3))_(12)(CH_(3)CN)_(10)(NO_(3))_(2)]·4CH_(3)CN(DC3),in which the metal ions are exclusively bridged by end-on azido ligands to stabilize a beautiful disk-like topology.The resulting clusters exhibit interesting structural transformations and thermodynamically-distinct steady states verified by theoretical calcula-tions.Magnetic studies reveal the first observation of zero-field SMM behaviour in disk-like heptanuclear Co^(Ⅱ)complexes.

Hydrothermally stable metal oxide-zeolite composite catalysts for low-temperature NO_(x) reduction with improved N_(2) selectivity

Development of hydrothermally stable,low-temperature catalysts for controlling nitrogen oxides emissions from mobile sources remains an urgent challenge.We have prepared a metal oxide-zeolite composite catalyst by depositing Mn active species on a mixture support of CeO_(2)/Al_(2)O_(3) and ZSM-5.This composite catalyst is hydrothermally stable and shows improved low-temperature SCR activity and significantly reduced N_(2)O formation than the corresponding metal oxide catalyst.Comparing with a Cu-CHA catalyst,the composite catalyst has a faster response to NH_(3) injection and less NH_(3) slip.Our characterization results reveal that such an oxide-zeolite composite catalyst contains more acidic sites and Mn^(3+)species as a result of oxide-zeolite interaction,and this interaction leads to the generation of more NH_(4)^(+)species bound to the Br?nsted acid sites and more reactive NOxspecies absorbed on the Mn sites.Herein,we report our mechanistic understanding of the oxide-zeolite composite catalyst and its molecular pathway for improving the low-temperature activity and N_(2) selectivity for NH_(3)-SCR reaction.Practically,this work may provide an alternative methodology for low-temperature NO_(x) control from diesel vehicles.

Payload-free protein nanoparticles target inflamed colons to restore intestinal barrier integrity for effectively treating inflammatory bowel diseases

Anti-inflammatory compounds,delivered as a payload to the gastrointestinal tract(GIT)by carriers,still cannot treat inflammatory bowel diseases without avoid-ing side effects.Here,we developed payload-free protein nanoparticles(PNPs)that crossed GIT to retain in the colon and treat colitis by restoring intestinal bar-rier integrity by modulating gut microbiome and metabolome.Specifically,PNPs,orally administered to mice with acute colitis,reached the colon within three hours.Consequently,PNPs improve gut microbiota dysbiosis to reverse metabolism bal-ance,suppressing the expression of tumor-necrosis factorαand toll-like receptor 4 that restores the intestinal barrier integrity.PNPs then ameliorated colon inflam-mation and attenuated gut microbiota dysbiosis by exerting probiotic effects on gut microbiota,treating colitis in a week more effectively than the clinically often used 5-aminosalicylic acid without causing undesired side effects.Such PNPs repre-sent safe,sustainable,and cost-effective therapeutics for treating inflammatory and metabolic diseases by eliminating microbial and metabolomic imbalance.