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。

面向Critical MTC的无连接传输

关键机器类通信(Critical MTC)对时延和可靠性都有极高的要求。支持海量Critical MTC的终端是一个巨大挑战。提出了一种面向海量Critical MTC终端的无连接传输方案。为了降低时延,提出了基于竞争的无连接单次传输方案;为了实现高可靠性,设计了具有极低导频碰撞概率的稀疏正交多导频。进一步利用大规模多输入多输出(MIMO)的增益来提高可靠性以及在空域复用大量用户。仿真结果表明,提出的方案可以支持海量Critical MTC终端,同时满足低时延和高可靠的严格要求。

Predictive value of controlling nutritional status score for progression to chronic critical illness in elderly patients with sepsis

Objective:To investigate the predictive value of controlling nutritional status(CONUT)score for progression to chronic critical illness sepsis in elderly patients,and to construct a predictive model based on CONUT score histogram.Methods:739 elderly patients with sepsis admitted from January 2020 to December 2022 were selected as the study objects,and were divided into chronic critical illness group(n=188)and non-chronic critical illness group(n=551)according to whether chronic critical illness disease occurred.Clinical data of the patients were collected and compared.The predictive value of CONUT score,PNI and NLR in the progression of senile sepsis to chronic severe disease was compared,and the optimal threshold value was determined,which was used to convert the numerical variables into binary variables.Through univariate analysis and multivariate Logistic regression analysis,the risk factors affecting the progression of elderly sepsis patients to chronic critical illness disease were screened out,and the prediction model was built based on the nomogram.The efficacy and clinical utility of the prediction model were evaluated by the area under the ROC curve(AUC),calibration curve and decision curve analysis(DCA).Results:The best cut-off value for CONUT score in predicting elderly sepsis progressing to chronic critical illness was 4 points.The predictive performance of CONUT score(AUC=0.739)was better than that of PNI(AUC=0.609)and NLR(AUC=0.582)in elderly sepsis progressing to chronic critical illness(CONUT score vs PNI:Z=5.960,P<0.001;CONUT score vs NLR:Z=6.119,P<0.001).Univariate analysis showed that age,CCI score,SOFA score,sepsis shock,serum Lac,CONUT score,mechanical ventilation(MV),and continuous renal replacement therapy(CRRT)treatment were related to elderly sepsis progressing to chronic critical illness(P<0.05).Multivariate logistic regression analysis showed that CONUT score≥4 points,age≥75 years,CCI score≥3 points,SOFA score>5 points,sepsis shock,and serum Lac≥4 mmol/L were independent risk factors for elderly sepsis progressing to chronic critical illness(P<0.05).The nomogram showed that CONUT score had the greatest contribution value in predicting elderly sepsis progressing to chronic critical illness.Based on this,the nomogram prediction model had an AUC of 0.846[95%CI(0.812~0.879)],with a sensitivity of 75.5%and specificity of 81.3%,indicating good predictive performance.The calibration curve was close to the ideal curve,and the DCA threshold had clinical utility advantages when ranging from 0.1 to 0.9.Conclusion:The nomographic prediction model based on CONUT score can effectively predict the risk probability of senile sepsis progressing to chronic critical illness,helpful for clinicians to identify the high risk group of chronic and severe senile sepsis,which is helpful for clinicians to identify high-risk populations of elderly sepsis with chronic critical illness.

Enhancing Critical Path Problem in Neutrosophic Environment Using Python

In the real world,one of the most common problems in project management is the unpredictability of resources and timelines.An efficient way to resolve uncertainty problems and overcome such obstacles is through an extended fuzzy approach,often known as neutrosophic logic.Our rigorous proposed model has led to the creation of an advanced technique for computing the triangular single-valued neutrosophic number.This innovative approach evaluates the inherent uncertainty in project durations of the planning phase,which enhances the potential significance of the decision-making process in the project.Our proposed method,for the first time in the neutrosophic set literature,not only solves existing problems but also introduces a new set of problems not yet explored in previous research.A comparative study using Python programming was conducted to examine the effectiveness of responsive and adaptive planning,as well as their differences from other existing models such as the classical critical path problem and the fuzzy critical path problem.The study highlights the use of neutrosophic logic in handling complex projects by illustrating an innovative dynamic programming framework that is robust and flexible,according to the derived results,and sets the stage for future discussions on its scalability and application across different industries.

Predicted Critical State Based on Invariance of the Lyapunov Exponent in Dual Spaces

Critical states in disordered systems,fascinating and subtle eigenstates,have attracted a lot of research interests.However,the nature of critical states is difficult to describe quantitatively,and in general,it cannot predict a system that hosts the critical state.We propose an explicit criterion whereby the Lyapunov exponent of the critical state should be 0 simultaneously in dual spaces,namely the Lyapunov exponent remains invariant under the Fourier transform.With this criterion,we can exactly predict a one-dimensional quasiperiodic model which is not of self-duality,but hosts a large number of critical states.Then,we perform numerical verification of the theoretical prediction and display the self-similarity of the critical state.Due to computational complexity,calculations are not performed for higher dimensional models.However,since the description of extended and localized states by the Lyapunov exponent is universal and dimensionless,utilizing the Lyapunov exponent of dual spaces to describe critical states should also be universal.Finally,we conjecture that some kind of connection exists between the invariance of the Lyapunov exponent and conformal invariance,which can promote the research of critical phenomena.

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.

Engineering Quantum Criticality for Quantum Dot Power Harvesting

Coupling of quantum-dot circuits to microwave photons enables us to investigate photon-assisted quantum transport.Here,we revisit this typical circuit quantum electrodynamical setup by introducing the Kerr nonlinearity of photons.By exploiting quantum critical behavior,we propose a powerful scheme to control the power-harvesting efficiency in the microwave regime,where the driven-dissipative optical system acts as an energy pump.It drives electron transport against a load in the quantum-dot circuit.The energy transfer and,consequently,the harvesting efficiency are enhanced near the critical point.As the critical point moves towards to low input power,high efficiency within experimental parameters is achieved.Our results complement fundamental studies of photon-to-electron conversion at the nanoscale and provide practical guidance for designs of integrated photoelectric devices through quantum criticality.

Anisotropic s-Wave Gap in the Vicinity of a Quantum Critical Point in Superconducting BaFe_(2)(As_(1-x)P_(x))_(2) Single Crystals:A Study of Point-Contact Spectroscopy

We report on soft c-axis point-contact Andreev reflection(PCAR)spectroscopy combining with resistivity measurements on BaFe_(2)(As_(0.7)P_(0.3))_(2),to elucidate the superconducting gap structure in the vicinity of the quantum critical point.A double peak at the gap edge plus a dip feature at zero-bias has been observed on the PCAR spectra,indicative of the presence of a nodeless gap in BaFe_(2)(As_(0.7)P_(0.3))_(2).Detailed analysis within a sophisticated theoretical model reveals an anisotropic gap with deep gap minima.The PCARs also feature additional structures related to the electron-bosonic coupling mode.Using the extracted superconducting energy gap value,a characteristic bosonic energy Ω_(b) and its temperature dependence are obtained,comparable with the spin-resonance energy observed in neutron scattering experiment.These results indicate a magnetism-driven quantum critical point in the BaFe_(2)(As_(1-x)P_(x))_(2) system.

Characterization of bright betatron radiation generated by direct laser acceleration of electrons in plasma of near critical density

Directed x-rays produced in the interaction of sub-picosecond laser pulses of moderate relativistic intensity with plasma of near-critical density are investigated. Synchrotron-like (betatron) radiation occurs in the process of direct laser acceleration (DLA) of electrons in a relativisticlaser channel when the electrons undergo transverse betatron oscillations in self-generated quasi-static electric and magnetic fields. In anexperiment at the PHELIX laser system, high-current directed beams of DLA electrons with a mean energy ten times higher than the ponderomotive potential and maximum energy up to 100 MeV were measured at 10^(19) W/cm^(2)laser intensity. The spectrum of directed x-raysin the range of 5–60 keV was evaluated using two sets of Ross filters placed at 0°and 10°to the laser pulse propagation axis. The differential x-ray absorption method allowed for absolute measurements of the angular-dependent photon fluence. We report 10^(13) photons/sr withenergies >5 keV measured at 0°to the laser axis and a brilliance of 10^(21) photons s^(−1) mm^(−2) mrad−2(0.1%BW)−1. The angular distributionof the emission has an FWHM of 14°–16°. Thanks to the ultra-high photon fluence, point-like radiation source, and ultra-short emissiontime, DLA-based keV backlighters are promising for various applications in high-energy-density research with kilojoule petawatt-class laserfacilities.

Exploring Critical Thinking Dispositions among Fourth Year BSc Nursing Students of Various Colleges of Nursing, Pakistan

Background: Critical Thinking (CT) dispositions in nursing are prominent predictors of competence in delivering high-quality care, and of professionalism, in newly graduated nurses. CT skills, in isolation of CT dispositions, do not guarantee success in the workplace, because Critical Thinking Dispositions (CTD) are important elements of intellectual reasoning that simulate a person towards using the CT skills. Therefore, nursing educational programs should promote lifelong learning rather than focusing on transferring the content of nursing knowledge only. And for this purpose, quality education is the key. Education should focus on teaching from diverse perspectives, incorporating various teaching learning strategies that are congruent with the modern era. Purpose: The purpose of this study is to explore critical thinking dispositions among final year Baccalaureate Nursing students of various military colleges of nursing, in Pakistan. Methodology: A descriptive qualitative exploratory study design was used to investigate the CTD of BSc final year nursing students. The study population included twelve willing nursing students, from six military colleges across the country. Demographic information and consent was taken from the participants of the study. In-depth interviews, through a semi structured interview guide, and probes were used to obtain data related to personal experiences of CTD amongst the nursing students. Results: Data analysis showed two broad themes: 1) Perceptions of CT, and 2) Experiences of CT dispositions. In theme one, the emerging category was: Clarity of CT;whereas in theme two, the categories that emerged were: a) Truth Seeking, b) Open Mindedness, c) Inquisitiveness, and d) Self Organization. Conclusion: The findings of the study revealed positive dispositions towards truth seeking, open mindedness, and self-organization, whereas disposition towards inquisitiveness was weak. Self-confidence and maturity also emerged as positive factors that the students possessed. This study recommends that faculty and learners should extend their concept of CTD, and emphasizes its application in daily routine. Additionally, faculty should modify their instructional strategies and focus on the cultivation of dispositions of inquisitiveness, curiosity, and allow questioning by students in the class.

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.

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”.

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.

Predictive modeling of critical temperatures in magnesium compounds using transfer learning

This study presents a transfer learning approach for discovering potential Mg-based superconductors utilizing a comprehensive target dataset.Initially,a large source dataset(Bandgap dataset)comprising approximately∼75k compounds is utilized for pretraining,followed by fine-tuning with a smaller Critical Temperature(T_(c))dataset containing∼300 compounds.Comparatively,there is a significant improvement in the performance of the transfer learning model over the traditional deep learning(DL)model in predicting Tc.Subsequently,the transfer learning model is applied to predict the properties of approximately 150k compounds.Predictions are validated computationally using density functional theory(DFT)calculations based on lattice dynamics-related theory.Moreover,to demonstrate the extended predictive capability of the transfer learning model for new materials,a pool of virtual compounds derived from prototype crystal structures from the Materials Project(MP)database is generated.T_(c) predictions are obtained for∼3600 virtual compounds,which underwent screening for electroneutrality and thermodynamic stability.An Extra Trees-based model is trained to utilize E_(hull)values to obtain thermodynamically stable materials,employing a dataset containing Ehull values for approximately 150k materials for training.Materials with Ehull values exceeding 5 meV/atom were filtered out,resulting in a refined list of potential Mg-based superconductors.This study showcases the effectiveness of transfer learning in predicting superconducting properties and highlights its potential for accelerating the discovery of Mg-based materials in the field of superconductivity.

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.

Advancing critical care recovery:The pivotal role of machine learning in early detection of intensive care unit-acquired weakness

This editorial explores the significant challenge of intensive care unit-acquiredweakness(ICU-AW),a prevalent condition affecting critically ill patients,characterizedby profound muscle weakness and complicating patient recovery.Highlightingthe paradox of modern medical advances,it emphasizes the urgent needfor early identification and intervention to mitigate ICU-AW's impact.Innovatively,the study by Wang et al is showcased for employing a multilayer perceptronneural network model,achieving high accuracy in predicting ICU-AWrisk.This advancement underscores the potential of neural network models inenhancing patient care but also calls for continued research to address limitationsand improve model applicability.The editorial advocates for the developmentand validation of sophisticated predictive tools,aiming for personalized carestrategies to reduce ICU-AW incidence and severity,ultimately improving patientoutcomes in critical care settings.

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.

Critical Solvation Structures Arrested Active Molecules for Reversible Zn Electrochemistry

Aqueous Zn-ion batteries(AZIBs)have attracted increasing attention in next-generation energy storage systems due to their high safety and economic.Unfortunately,the side reactions,dendrites and hydrogen evolution effects at the zinc anode interface in aqueous electrolytes seriously hinder the application of aqueous zinc-ion batteries.Here,we report a critical solvation strategy to achieve reversible zinc electrochemistry by introducing a small polar molecule acetonitrile to form a“catcher”to arrest active molecules(bound water molecules).The stable solvation structure of[Zn(H_(2)O)_(6)]^(2+)is capable of maintaining and completely inhibiting free water molecules.When[Zn(H_(2)O)_(6)]^(2+)is partially desolvated in the Helmholtz outer layer,the separated active molecules will be arrested by the“catcher”formed by the strong hydrogen bond N-H bond,ensuring the stable desolvation of Zn^(2+).The Zn||Zn symmetric battery can stably cycle for 2250 h at 1 mAh cm^(-2),Zn||V_(6)O_(13) full battery achieved a capacity retention rate of 99.2%after 10,000 cycles at 10 A g^(-1).This paper proposes a novel critical solvation strategy that paves the route for the construction of high-performance AZIBs.

Extreme value theory applied to the auroral electrojet indices

The study of extreme weather and space events has gained paramount importance in modern society owing to rapid advances in high technology.Understanding and describing exceptional occurrences plays a crucial role in making decisive assessments of their potential impact on technical,economic,and social aspects in various fields.This research focuses on analyzing the hourly values of the auroral electrojet(AE)geomagnetic index from 1957 to 2019 by using the peak over threshold method in extreme value theory.By fitting the generalized Pareto distribution to extreme AE values,shape parameter indices were derived,revealing negative values that establish an upper bound for this time series.Consequently,it became evident that the AE values had reached a plateau,suggesting that extreme events exceeding the established upper limit are rare.As a result,although the need for diligent precautions to mitigate the consequences of such extreme events persists,surpassing the upper limit of AE values becomes increasingly challenging.It is also possible to observe an aurora in the middle-and low-latitude regions during the maximum period of the AE index.

Mental health status among COVID-19 patients survivors of critical illness in Saudi Arabia:A 6-month follow-up questionnaire study

BACKGROUND Psychological assessment after intensive care unit(ICU)discharge is increasingly used to assess patients'cognitive and psychological well-being.However,few studies have examined those who recovered from coronavirus disease 2019(COVID-19).There is a paucity of data from the Middle East assessing the post-ICU discharge mental health status of patients who had COVID-19.AIM To evaluate anxiety and depression among patients who had severe COVID-19.METHODS This is a prospective single-center follow-up questionnaire-based study of adults who were admitted to the ICU or under ICU consultation for>24 h for COVID-19.Eligible patients were contacted via telephone.The patient’s anxiety and depression six months after ICU discharge were assessed using the Hospital Anxiety and Depression Scale(HADS).The primary outcome was the mean HADS score.The secondary outcomes were risk factors of anxiety and/or depression.RESULTS Patients who were admitted to the ICU because of COVID-19 were screened(n=518).Of these,48 completed the questionnaires.The mean age was 56.3±17.2 years.Thirty patients(62.5%)were male.The main comorbidities were endocrine(n=24,50%)and cardiovascular(n=21,43.8%)diseases.The mean overall HADS score for anxiety and depression at 6 months post-ICU discharge was 11.4(SD±8.5).A HADS score of>7 for anxiety and depression was detected in 15 patients(30%)and 18 patients(36%),respectively.Results from the multivariable ordered logistic regression demonstrated that vasopressor use was associated with the development of anxiety and depression[odds ratio(OR)39.06,95% confidence interval:1.309-1165.8;P<0.05].CONCLUSION Six months after ICU discharge,30% of patients who had COVID-19 demonstrated a HADS score that confirmed anxiety and depression.To compare the psychological status of patients following an ICU admission(with vs without COVID-19),further studies are warranted.