A study of the soil water potential threshold values to trigger irrigation of ‘Shimizu Hakuto’ peach at pivotal fruit developmental stages

Water management is an important practice that affects fruit size and quality.Effective implementation of irrigation scheduling requires knowledge of the appropriate indicators and thresholds,which are established manly based on the effects of water deficits on final fruit quality.Few studies have focused on the real-time effects of water status on fruit and shoot growth.To establish soil water potential (ψ_(soil)) thresholds to trigger irrigation of peach at pivotal fruit developmental stages,photogrammetry,^(13)C labelling,and other techniques were used in this study to investigate real-time changes in stem diameter,fruit projected area,net leaf photosynthetic rate (P_(n)),and allocation of photoassimilates to fruit under soil water potential conditions ranging from saturation to stress in 6-year-old Shimizu hakuto’peach.Stem growth,fruit growth,and P_n exhibited gradually decreasing sensitivity to water deficits during fruit developmental stages I,II,and III.Stem diameter growth was significantly inhibited whenψ_(soil)dropped to-8.5,-7.6,and-5.4 k Pa,respectively.Fruit growth rate was low,reaching zero when theψ_(soil)was-9.0 to-23.1,-14.9 to-21.4,and-16.5 to-23.3 k Pa,respectively,and P_ndecreased significantly when theψ_(soil)reached-24.2,-22.7,and-20.4 kPa,respectively.In addition,more photoassimilates were allocated to fruit under moderateψ_(soil)conditions (-10.1 to-17.0 k Pa) than under otherψ_(soil)values.Our results revealed threeψ_(soil)thresholds,-10.0,-15.0,and-15.0 kPa,suitable for triggering irrigation during stages I,II,and III,respectively.These thresholds can be helpful for controlling excessive tree vigor,maintaining rapid fruit growth and leaf photosynthesis,and promoting the allocation of more photoassimilates to fruit.

基于Valued ERGMs模型的核心技术网络成长机制研究——以量子计算领域为例

对核心技术网络及其成长机制的研究有助于梳理核心技术之间的依赖和促进关系,为研究核心技术演化提供新的理论视角和方法。以技术演化相关理论为基础,归纳核心技术网络成长的影响因素,基于量子计算领域专利数据,识别以技术概念和技术关系为基础的量子计算领域核心技术网络,并基于Valued ERGMs模型构建核心技术网络成长机制模型。结果表明,技术要素中心性、专利技术研发能力、与TRIZ进化法则匹配程度以及技术要素同配性对核心技术网络成长具有正向促进作用;在技术路径方面,核心技术网络成长受到技术要素路径依赖性和技术突破的双重影响。最后,根据量子计算领域核心技术网络成长机制的实证研究结果,从技术研发层面、企业层面、政府层面为相关领域技术发展提出策略建议。

Chest computed tomography findings of the Omicron variants of SARS-CoV-2 with different cycle threshold values

BACKGROUND The Omicron variant of severe acute respiratory syndrome coronavirus 2(SARSCoV-2)mainly infects the upper respiratory tract.This study aimed to determine whether the probability of pulmonary infection and the cycle threshold(Ct)measured using the fluorescent polymerase chain reaction(PCR)method were related to pulmonary infections diagnosed via computed tomography(CT).AIM To analyze the chest CT signs of SARS-CoV-2 Omicron variant infections with different Ct values,as determined via PCR.METHODS The chest CT images and PCR Ct values of 331 patients with SARS-CoV-2Omicron variant infections were retrospectively collected and categorized into low(<25),medium(25.00-34.99),and high(≥35)Ct groups.The characteristics of chest CT images in each group were statistically analyzed.RESULTS The PCR Ct values ranged from 13.36 to 39.81,with 99 patients in the low,155 in the medium,and 77 in the high Ct groups.Six abnormal chest CT signs were detected,namely,focal infection,patchy consolidation shadows,patchy groundglass shadows,mixed consolidation ground-glass shadows,subpleural interstitial changes,and pleural changes.Focal infections were less frequent in the low Ct group than in the medium and high Ct groups;these infections were the most common sign in the medium and high Ct groups.Patchy consolidation shadows and pleural changes were more frequent in the low Ct group than in the other two groups.The number of patients with two or more signs was greater in the low Ct group than in the medium and high Ct groups.CONCLUSION The chest CT signs of patients with pulmonary infection caused by the Omicron variants of SARSCoV-2 varied depending on the Ct values.Identification of the characteristics of Omicron variant infection can help subsequent planning of clinical treatment.

The Economics of Competing Water Uses under a FERC Licensing Agreement: Estimation of Property Value, Recreation, and Hydroelectric Impacts

Reservoirs provide a variety of services with economic values across multiple sectors. As demands for reservoir services continue to grow and precipitation patterns evolve, it becomes ever more important to consider the integrated suite of values and tradeoffs that attend changes in water uses and availability. Section 316 (b) of the Clean Water Act requires that owners of certain water cooled power plants evaluate technologies and operational measures that can reduce their impacts to aquatic organisms. The studies must discuss the social costs and benefits of alternative technologies including cooling towers (79 Fed. Reg. 158, 48300 - 48439). Cooling towers achieve their effect through evaporation. This manuscript estimates the property value, recreation, and hydroelectric generation impacts that could result from the evaporative water loss associated with installing cooling towers at the McGuire Nuclear Generating Station (McGuire) located on Lake Norman, North Carolina. Although this study specifically evaluates the effects of evaporative water loss from cooling towers, its methods are applicable to estimating the economic benefits and costs of a new water user or reduced water input in any complex reservoir system that supports steam electric generation, hydroelectric generation, residential properties, recreation, irrigation, and municipal water use.

Fractal model of spontaneous imbibition in low-permeability reservoirs coupled with heterogeneity of pore seepage channels and threshold pressure

Spontaneous imbibition(SI)is an important mechanism for enhancing oil recovery in low-permeability reservoirs.Due to the strong heterogeneity,and the non-Darcy flow,the construction of SI model for lowpermeability reservoirs is extremely challenging.Commonly,traditional SI models based on single or averaged capillary tortuosity ignore the influence of heterogeneity of pore seepage channels and the threshold pressure(TP)on imbibition.Therefore,in this work,based on capillary model and fractal theory,a mathematical model of characterizing SI considering heterogeneity of pore seepage channels is established.On this basis,the threshold pressure was introduced to determine the pore radius at which the wetted phase can displace oil.The proposed new SI model was verified by imbibition experimental data.The study shows that for weakly heterogeneous cores with permeability of 0-1 m D,the traditional SI model can characterize the imbibition process relatively accurately,and the new imbibition model can increase the coefficient of determination by 1.05 times.However,traditional model has serious deviations in predicting the imbibition recovery for cores with permeability of 10-50 m D.The new SI model coupling with heterogeneity of pore seepage channels and threshold pressure effectively solves this problem,and the determination coefficient is increased from 0.344 to 0.922,which is increased by2.68 times.For low-permeability reservoirs,the production of the oil in transitional pores(0.01-0.1μm)and mesopores(0.1-1μm)significantly affects the imbibition recovery,as the research shows that when the heterogeneity of pore seepage channels is ignored,the oil recovery in transitional pores and mesopores decreases by 7.54%and 4.26%,respectively.Sensitivity analysis shows that increasing interfacial tension,decreasing contact angle,oil-water viscosity ratio and threshold pressure will increase imbibition recovery.In addition,there are critical values for the influence of these factors on the imbibition recovery,which provides theoretical support for surfactant optimization.

Vector Dominance with Threshold Searchable Encryption (VDTSE) for the Internet of Things

The Internet of Medical Things(IoMT)is an application of the Internet of Things(IoT)in the medical field.It is a cutting-edge technique that connects medical sensors and their applications to healthcare systems,which is essential in smart healthcare.However,Personal Health Records(PHRs)are normally kept in public cloud servers controlled by IoMT service providers,so privacy and security incidents may be frequent.Fortunately,Searchable Encryption(SE),which can be used to execute queries on encrypted data,can address the issue above.Nevertheless,most existing SE schemes cannot solve the vector dominance threshold problem.In response to this,we present a SE scheme called Vector Dominance with Threshold Searchable Encryption(VDTSE)in this study.We use a Lagrangian polynomial technique and convert the vector dominance threshold problem into a constraint that the number of two equal-length vectors’corresponding bits excluding wildcards is not less than a threshold t.Then,we solve the problem using the proposed technique modified in Hidden Vector Encryption(HVE).This technique makes the trapdoor size linear to the number of attributes and thus much smaller than that of other similar SE schemes.A rigorous experimental analysis of a specific application for privacy-preserving diabetes demonstrates the feasibility of the proposed VDTSE scheme.

Chalcogenide Ovonic Threshold Switching Selector

Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimensional phase change memory,stands out as one of the most promising candidates.The Optane with cross-point architecture is constructed through layering a storage element and a selector known as the ovonic threshold switch(OTS).The OTS device,which employs chalcogenide film,has thereby gathered increased attention in recent years.In this paper,we begin by providing a brief introduction to the discovery process of the OTS phenomenon.Subsequently,we summarize the key elec-trical parameters of OTS devices and delve into recent explorations of OTS materials,which are categorized as Se-based,Te-based,and S-based material systems.Furthermore,we discuss various models for the OTS switching mechanism,including field-induced nucleation model,as well as several carrier injection models.Additionally,we review the progress and innovations in OTS mechanism research.Finally,we highlight the successful application of OTS devices in three-dimensional high-density memory and offer insights into their promising performance and extensive prospects in emerging applications,such as self-selecting memory and neuromorphic computing.

Decision Making Based on Valued Fuzzy Superhypergraphs

This paper explores the defects in fuzzy (hyper) graphs (as complex (hyper) networks) and extends the fuzzy(hyper) graphs to fuzzy (quasi) superhypergraphs as a new concept.We have modeled the fuzzy superhypergraphsas complex superhypernetworks in order to make a relation between labeled objects in the form of details andgeneralities. Indeed, the structure of fuzzy (quasi) superhypergraphs collects groups of labeled objects and analyzesthem in the form of the part to part of objects, the part of objects to the whole group of objects, and the whole tothe whole group of objects at the same time.We have investigated the properties of fuzzy (quasi) superhypergraphsbased on any positive real number as valued fuzzy (quasi) superhypergraphs, considering the complement of valuedfuzzy (quasi) superhypergraphs, the notation of isomorphism of valued fuzzy (quasi) superhypergraphs based onthe permutations, and we have presented the isomorphic conditions of (self complemented) valued fuzzy (quasi)superhypergraphs. The concept of impact membership value of fuzzy (quasi) superhypergraphs is introducedin this study and it is applied in designing the real problem in the real world. Finally, the problem of businesssuperhypernetworks is presented as an application of fuzzy valued quasi superhypergraphs in the real world.

Effect of Biostimulants Based on Natural Products on the Growth and Nutritional Value of Bean (Phaseolus vulgaris L.)

Beans (Phaseolus vulgaris L.) are widely grown in Cameroon and play a key role in the fight against food insecurity, malnutrition and poverty. However, its cultivation encounters problems due to abiotic and biotic stresses, which leads to the use of synthetic fertilizers and pesticides, which cause significant damage to the environment and human health due to the presence of synthetics residues in the seeds, pods and in the leaves that are eaten. Promoting the use of natural products is becoming a necessity for organic and eco-responsible agriculture that limits contamination problems and improves people’s purchasing power. This study aims to assess the effect of biostimulants based on natural products on the growth and nutritional value of common bean (Phaseolus vulgaris L.). Bean seedlings from white variety (MEX-142) and red variety (DOR-701) were treated every seven days in the field from their pre-emergence, emergence and growth to their maturation under a randomized block experimental design. Six treatments and three repetitions with the biostimulants based on natural products and controls were thus performed and the agromorphological parameters were measured. After 120 days, the contents of growth biomarkers and defense-related enzymes were evaluated in leaves, while the contents of macromolecules, minerals and antinutrients were evaluated in seeds. These biostimulants significantly increased (P P < 0.0001) of antinutrients including oxalates, phytates, tannins and saponins in seeds compared to controls (T+ and T−). Treatment with biostimulants, in particular BS4, improves the performance of bean plants in the field as well as the biofortification of seeds regardless of the variety.

Epidemic threshold influenced by non-pharmaceutical interventions in residential university environments

The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and dorms.They move from one place to another.To simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact networks.In close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical intervention.It can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so on.Their real-world influence remains uncertain.With numerical simulations,we obtain epidemic thresholds.The effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.

Research on Data Theory of Value

This paper explores the data theory of value along the line of reasoning epochal characteristics of data-theoretical innovation-paradigmatic transformation and,through a comparison of hard and soft factors and observation of data peculiar features,it draws the conclusion that data have the epochal characteristics of non-competitiveness and non-exclusivity,decreasing marginal cost and increasing marginal return,non-physical and intangible form,and non-finiteness and non-scarcity.It is the epochal characteristics of data that undermine the traditional theory of value and innovate the“production-exchange”theory,including data value generation,data value realization,data value rights determination and data value pricing.From the perspective of data value generation,the levels of data quality,processing,use and connectivity,data application scenarios and data openness will influence data value.From the perspective of data value realization,data,as independent factors of production,show value creation effect,create a value multiplier effect by empowering other factors of production,and substitute other factors of production to create a zero-price effect.From the perspective of data value rights determination,based on the theory of property,the tragedy of the private outweighs the comedy of the private with respect to data,and based on the theory of sharing economy,the comedy of the commons outweighs the tragedy of the commons with respect to data.From the perspective of data pricing,standardized data products can be priced according to the physical product attributes,and non-standardized data products can be priced according to the virtual product attributes.Based on the epochal characteristics of data and theoretical innovation,the“production-exchange”paradigm has undergone a transformation from“using tangible factors to produce tangible products and exchanging tangible products for tangible products”to“using intangible factors to produce tangible products and exchanging intangible products for tangible products”and ultimately to“using intangible factors to produce intangible products and exchanging intangible products for intangible products”.

Vehicle Abnormal Behavior Detection Based on Dense Block and Soft Thresholding

With the rapid advancement of social economies,intelligent transportation systems are gaining increasing atten-tion.Central to these systems is the detection of abnormal vehicle behavior,which remains a critical challenge due to the complexity of urban roadways and the variability of external conditions.Current research on detecting abnormal traffic behaviors is still nascent,with significant room for improvement in recognition accuracy.To address this,this research has developed a new model for recognizing abnormal traffic behaviors.This model employs the R3D network as its core architecture,incorporating a dense block to facilitate feature reuse.This approach not only enhances performance with fewer parameters and reduced computational demands but also allows for the acquisition of new features while simplifying the overall network structure.Additionally,this research integrates a self-attentive method that dynamically adjusts to the prevailing traffic conditions,optimizing the relevance of features for the task at hand.For temporal analysis,a Bi-LSTM layer is utilized to extract and learn from time-based data nuances.This research conducted a series of comparative experiments using the UCF-Crime dataset,achieving a notable accuracy of 89.30%on our test set.Our results demonstrate that our model not only operates with fewer parameters but also achieves superior recognition accuracy compared to previous models.

Evaluation of rainfall threshold models for debris flow initiation in the Jiangjia Gully,Yunnan Province,China

Systematically determining the discriminatory power of various rainfall properties and their combinations in identifying debris flow occurrence is crucial for early warning systems.In this study,we evaluated the discriminatory power of different univariate and multivariate rainfall threshold models in identifying triggering conditions of debris flow in the Jiangjia Gully,Yunnan Province,China.The univariate models used single rainfall properties as indicators,including total rainfall(R_(tot)),rainfall duration(D),mean intensity(I_(mean)),absolute energy(Eabs),storm kinetic energy(E_(s)),antecedent rainfall(R_(a)),and maximum rainfall intensity over various durations(I_(max_dur)).The evaluation reveals that the I_(max_dur)and Eabs models have the best performance,followed by the E_(s),R_(tot),and I_(mean)models,while the D and R_(a)models have poor performances.Specifically,the I_(max_dur)model has the highest performance metrics at a 40-min duration.We used logistic regression to combine at least two rainfall properties to establish multivariate threshold models.The results show that adding D or R_(a)to the models dominated by Eabs,E_(s),R_(tot),or I_(mean)generally improve their performances,specifically when D is combined with I_(mean)or when R_(a)is combined with Eabs or E_(s).Including R_(a)in the I_(max_dur)model,it performs better than the univariate I_(max_dur)model.A power-law relationship between I_(max_dur)and R_(a)or between Eabs and R_(a)has better performance than the traditional I_(mean)–D model,while the performance of the E_(s)–R_(a)model is moderate.Our evaluation reemphasizes the important role of the maximum intensity over short durations in debris flow occurrence.It also highlights the importance of systematically investigating the role of R_(a)in establishing rainfall thresholds for triggering debris flow.Given the regional variations in rainfall patterns worldwide,it is necessary to evaluate the findings of this study across diverse watersheds.

CT Thresholds for Spinal Bone Mineral Attenuation to Prioritize Eligible Older Women for Osteoporosis Screening

Introduction: Computed tomography (CT) measurements of bone mineral attenuation may be a useful means to identify older women who should be prioritized for bone mineral density screening. Methods: We compared bone mineral attenuation as measured in the L1 vertebra of CT studies to the results of dual-energy x-ray absorptiometry (DEXA) studies to determine what CT attenuation thresholds might yield a reasonable combination of sensitivity and specificity for the detection of osteoporosis. The study was limited to women between the ages of 65 and 75 years who had a DEXA study and a CT that included the L1 or adjacent vertebra performed within 3 years of the DEXA study. Results: There were 1226 women in this study, of whom 452 (38%) had osteoporosis based on a T-score ≤ −2.5 by DEXA. There were 830 CT studies performed with contrast and 396 studies which were performed without contrast. There was a statistically significant difference in the mean HU of those studies performed without contrast compared to those with contrast (unenhanced mean 103 HU versus 125 HU, p < 0.001). Different CT attenuation thresholds provided the most appropriate combination of sensitivity and specificity for the detection of osteoporosis when comparing CT studies performed without or with IV contrast and when all the CT data were used in aggregate. Conclusion: Different thresholds appear necessary when using the mean CT vertebral attenuation to identify older women for preferential referral for DEXA studies.

A Value for Games Defined on Graphs

Given a graph g=( V,A ) , we define a space of subgraphs M with the binary operation of union and the unique decomposition property into blocks. This space allows us to discuss a notion of minimal subgraphs (minimal coalitions) that are of interest for the game. Additionally, a partition of the game is defined in terms of the gain of each block, and subsequently, a solution to the game is defined based on distributing to each player (node and edge) present in each block a payment proportional to their contribution to the coalition.

Properties of radiation defects and threshold energy of displacement in zirconium hydride obtained by new deep-learning potential

Zirconium hydride(ZrH_(2)) is an ideal neutron moderator material. However, radiation effect significantly changes its properties, which affect its behavior and the lifespan of the reactor. The threshold energy of displacement is an important quantity of the number of radiation defects produced, which helps us to predict the evolution of radiation defects in ZrH_(2).Molecular dynamics(MD) and ab initio molecular dynamics(AIMD) are two main methods of calculating the threshold energy of displacement. The MD simulations with empirical potentials often cannot accurately depict the transitional states that lattice atoms must surpass to reach an interstitial state. Additionally, the AIMD method is unable to perform largescale calculation, which poses a computational challenge beyond the simulation range of density functional theory. Machine learning potentials are renowned for their high accuracy and efficiency, making them an increasingly preferred choice for molecular dynamics simulations. In this work, we develop an accurate potential energy model for the ZrH_(2) system by using the deep-potential(DP) method. The DP model has a high degree of agreement with first-principles calculations for the typical defect energy and mechanical properties of the ZrH_(2) system, including the basic bulk properties, formation energy of point defects, as well as diffusion behavior of hydrogen and zirconium. By integrating the DP model with Ziegler–Biersack–Littmark(ZBL) potential, we can predict the threshold energy of displacement of zirconium and hydrogen in ε-ZrH_(2).

Impacts of proppant distribution on development of tight oil reservoirs with threshold pressure gradient

Field evidence indicates that proppant distribution and threshold pressure gradient have great impacts on well productivity.Aiming at the development of unconventional oil reservoirs in Triassic Chang-7 Unit,Ordos Basin of China,we presented an integrated workflow to investigate how(1)proppant placement in induced fracture and(2)non-linear flow in reservoir matrix would affect well productivity and fluid flow in the reservoir.Compared with our research before(Yue et al.,2020),here we extended this study into the development of multi-stage fractured horizontal wells(MFHWs)with large-scale complicated fracture geometry.The integrated workflow is based on the finite element method and consists of simulation models for proppant-laden fluid flow,fracture flow,and non-linear seepage flow,respectively.Simulation results indicate that the distribution of proppant inside the induced cracks significantly affects the productivity of the MFHW.When we assign an idealized proppant distribution instead of the real distribution,there will be an overestimation of 44.98%in daily oil rate and 30.63%in cumulative oil production after continuous development of 1000 days.Besides,threshold pressure gradient(TPG)also significantly affects the well performance in tight oil reservoirs.If we simply apply linear Darcy’s law to the reservoir matrix,the overall cumulative oil production can be overrated by 77%after 1000 days of development.In general,this research provides new insights into the development of tight oil reservoirs with TPG and meanwhile reveals the significance of proppant distribution and non-linear fluid flow in the production scenario design.

AMicroseismic Signal Denoising Algorithm Combining VMD and Wavelet Threshold Denoising Optimized by BWOA

The denoising of microseismic signals is a prerequisite for subsequent analysis and research.In this research,a new microseismic signal denoising algorithm called the Black Widow Optimization Algorithm(BWOA)optimized VariationalMode Decomposition(VMD)jointWavelet Threshold Denoising(WTD)algorithm(BVW)is proposed.The BVW algorithm integrates VMD and WTD,both of which are optimized by BWOA.Specifically,this algorithm utilizes VMD to decompose the microseismic signal to be denoised into several Band-Limited IntrinsicMode Functions(BLIMFs).Subsequently,these BLIMFs whose correlation coefficients with the microseismic signal to be denoised are higher than a threshold are selected as the effective mode functions,and the effective mode functions are denoised using WTD to filter out the residual low-and intermediate-frequency noise.Finally,the denoised microseismic signal is obtained through reconstruction.The ideal values of VMD parameters and WTD parameters are acquired by searching with BWOA to achieve the best VMD decomposition performance and solve the problem of relying on experience and requiring a large workload in the application of the WTD algorithm.The outcomes of simulated experiments indicate that this algorithm is capable of achieving good denoising performance under noise of different intensities,and the denoising performance is significantly better than the commonly used VMD and Empirical Mode Decomposition(EMD)algorithms.The BVW algorithm is more efficient in filtering noise,the waveform after denoising is smoother,the amplitude of the waveform is the closest to the original signal,and the signal-to-noise ratio(SNR)and the root mean square error after denoising are more satisfying.The case based on Fankou Lead-Zinc Mine shows that for microseismic signals with different intensities of noise monitored on-site,compared with VMD and EMD,the BVW algorithm ismore efficient in filtering noise,and the SNR after denoising is higher.

Evaluation of the value of combined detection of tumor markers CA724,carcinoembryonic antigen,CA242,and CA19-9 in gastric cancer

BACKGROUND Gastric cancer is a global health concern that poses a significant threat to human well-being.AIM To detecting serum changes in carcinoembryonic antigen(CEA),carbohydrate antigens(CA)724,CA242,and CA19-9 expression among patients with gastric cancer.METHODS Eighty patients diagnosed with gastric cancer between January 2020 and January 2023 were included in the observation group,while 80 patients with benign gastric diseases were included in the control group.Both groups were tested for tumor markers(CA724,CEA,CA242,and CA19-9].Tumor marker indicators(CA724,CEA,CA242,and CA19-9)were compared between the two groups,assessing positive rates of tumor markers across various stages in the observation group.Additionally,single and combined detection of various tumor markers were examined.RESULTS The sensitivity,specificity,accuracy,positive predictive value,and negative predictive value observed for the combined detection of CA724,CEA,CA242,and CA19-9 were higher than those of CA724,CEA,CA242,and CA19-9 individually.Therefore,the combined detection of CA724,CEA,CA242,and CA19-9 has a high diagnostic accuracy and could reduce the occurrence of missed or misdiagnosed cases,facilitating the early diagnosis and treatment of patients.CONCLUSION CA724,CEA,CA242,and CA19-9 serum levels in gastric cancer patients significantly surpassed those in non-gastric cancer patients(P<0.05).Their combined detection can improve the diagnostic accuracy for gastric cancer,warranting clinical promotion.

Improving the nutritional values of yellow mealworm Tenebrio molitor(Coleoptera: Tenebrionidae) larvae as an animal feed ingredient: a review

Yellow mealworm larvae(YML;Tenebrio molitor) are considered as a valuable insect species for animal feed due to their high nutritional values and ability to grow under different substrates and rearing conditions. Advances in the understanding of entomophagy and animal nutrition over the past decades have propelled research areas toward testing multiple aspects of YML to exploit them better as animal feed sources. This review aims to summarize various approaches that could be exploited to maximize the nutritional values of YML as an animal feed ingredient. In addition, YML has the potential to be used as an antimicrobial or bioactive agent to improve animal health and immune function in production animals. The dynamics of the nutritional profile of YML can be influenced by multiple factors and should be taken into account when attempting to optimize the nutrient contents of YML as an animal feed ingredient. Specifically, the use of novel land-based and aquatic feeding resources, probiotics, and the exploitation of larval gut microbiomes as novel strategies can assist to maximize the nutritional potential of YML. Selection of relevant feed supplies, optimization of ambient conditions, the introduction of novel genetic selection procedures, and implementation of effective post-harvest processing may be required in the future to commercialize mealworm production. Furthermore, the use of appropriate agricultural practices and technological improvements within the mealworm production sector should be aimed at achieving both economic and environmental sustainability. The issues highlighted in this review could pave the way for future approaches to improve the nutritional value of YML.