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.

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.

Future of neurocritical care:Integrating neurophysics,multimodal monitoring,and machine learning

Multimodal monitoring(MMM)in the intensive care unit(ICU)has become increasingly sophisticated with the integration of neurophysical principles.However,the challenge remains to select and interpret the most appropriate combination of neuromonitoring modalities to optimize patient outcomes.This manuscript reviewed current neuromonitoring tools,focusing on intracranial pressure,cerebral electrical activity,metabolism,and invasive and noninvasive autoregulation moni-toring.In addition,the integration of advanced machine learning and data science tools within the ICU were discussed.Invasive monitoring includes analysis of intracranial pressure waveforms,jugular venous oximetry,monitoring of brain tissue oxygenation,thermal diffusion flowmetry,electrocorticography,depth electroencephalography,and cerebral microdialysis.Noninvasive measures include transcranial Doppler,tympanic membrane displacement,near-infrared spectroscopy,optic nerve sheath diameter,positron emission tomography,and systemic hemodynamic monitoring including heart rate variability analysis.The neurophysical basis and clinical relevance of each method within the ICU setting were examined.Machine learning algorithms have shown promise by helping to analyze and interpret data in real time from continuous MMM tools,helping clinicians make more accurate and timely decisions.These algorithms can integrate diverse data streams to generate predictive models for patient outcomes and optimize treatment strategies.MMM,grounded in neurophysics,offers a more nuanced understanding of cerebral physiology and disease in the ICU.Although each modality has its strengths and limitations,its integrated use,especially in combination with machine learning algorithms,can offer invaluable information for individualized patient care.

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.

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。

Semi-analytical solution for drained expansion analysis of a hollow cylinder of critical state soils

The expansion of a thick-walled hollow cylinder in soil is of non-self-similar nature that the stress/deformation paths are not the same for different soil material points.As a result,this problem cannot be solved by the common self-similar-based similarity techniques.This paper proposes a novel,exact solution for rigorous drained expansion analysis of a hollow cylinder of critical state soils.Considering stress-dependent elastic moduli of soils,new analytical stress and displacement solutions for the nonself-similar problem are developed taking the small strain assumption in the elastic zone.In the plastic zone,the cavity expansion response is formulated into a set of first-order partial differential equations(PDEs)with the combination use of Eulerian and Lagrangian descriptions,and a novel solution algorithm is developed to efficiently solve this complex boundary value problem.The solution is presented in a general form and thus can be useful for a wide range of soils.With the new solution,the non-self-similar nature induced by the finite outer boundary is clearly demonstrated and highlighted,which is found to be greatly different to the behaviour of cavity expansion in infinite soil mass.The present solution may serve as a benchmark for verifying the performance of advanced numerical techniques with critical state soil models and be used to capture the finite boundary effect for pressuremeter tests in small-sized calibration chambers.

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.

21st century critical care medicine:An overview

Critical care medicine in the 21st century has witnessed remarkable advancements that have significantly improved patient outcomes in intensive care units(ICUs).This abstract provides a concise summary of the latest developments in critical care,highlighting key areas of innovation.Recent advancements in critical care include Precision Medicine:Tailoring treatments based on individual patient characteristics,genomics,and biomarkers to enhance the effectiveness of therapies.The objective is to describe the recent advancements in Critical Care Medicine.Telemedicine:The integration of telehealth technologies for remote patient monitoring and consultation,facilitating timely interventions.Artificial intelligence(AI):AI-driven tools for early disease detection,predictive analytics,and treatment optimization,enhancing clinical decision-making.Organ Support:Advanced life support systems,such as Extracorporeal Membrane Oxygenation and Continuous Renal Replacement Therapy provide better organ support.Infection Control:Innovative infection control measures to combat emerging pathogens and reduce healthcare-associated infections.Ventilation Strategies:Precision ventilation modes and lung-protective strategies to minimize ventilatorinduced lung injury.Sepsis Management:Early recognition and aggressive management of sepsis with tailored interventions.Patient-Centered Care:A shift towards patient-centered care focusing on psychological and emotional wellbeing in addition to medical needs.We conducted a thorough literature search on PubMed,EMBASE,and Scopus using our tailored strategy,incorporating keywords such as critical care,telemedicine,and sepsis management.A total of 125 articles meeting our criteria were included for qualitative synthesis.To ensure reliability,we focused only on articles published in the English language within the last two decades,excluding animal studies,in vitro/molecular studies,and non-original data like editorials,letters,protocols,and conference abstracts.These advancements reflect a dynamic landscape in critical care medicine,where technology,research,and patient-centered approaches converge to improve the quality of care and save lives in ICUs.The future of critical care promises even more innovative solutions to meet the evolving challenges of modern medicine.

A novel framework to intercept GPS-denied,bomb-carrying,nonmilitary,kamikaze drones:Towards protecting critical infrastructures

Protection of urban critical infrastructures(CIs)from GPS-denied,bomb-carrying kamikaze drones(G-BKDs)is very challenging.Previous approaches based on drone jamming,spoofing,communication interruption and hijacking cannot be applied in the case under examination,since G-B-KDs are uncontrolled.On the other hand,drone capturing schemes and electromagnetic pulse(EMP)weapons seem to be effective.However,again,existing approaches present various limitations,while most of them do not examine the case of G-B-KDs.This paper,focuses on the aforementioned under-researched field,where the G-B-KD is confronted by two defensive drones.The first neutralizes and captures the kamikaze drone,while the second captures the bomb.Both defensive drones are equipped with a net-gun and an innovative algorithm,which,among others,estimates the locations of interception,using a real-world trajectory model.Additionally,one of the defensive drones is also equipped with an EMP weapon to damage the electronics equipment of the kamikaze drone and reduce the capturing time and the overall risk.Extensive simulated experiments and comparisons to state-of-art methods,reveal the advantages and limitations of the proposed approach.More specifically,compared to state-of-art,the proposed approach improves:(a)time to neutralize the target by at least 6.89%,(b)maximum number of missions by at least 1.27%and(c)total cost by at least 5.15%.

Prediction and critical transition mechanism for granite fracture:Insights from critical slowing down theory

Rock fracture warning is one of the significant challenges in rock mechanics.Many true triaxial and synchronous acoustic emission(AE)tests were conducted on granite samples.The investigation focused on the characteristics of AE signals preceding granite fracture,based on the critical slowing down(CSD)theory.The granite undergoes a transition from the stable phase to the fracture phase and exhibits a clear CSD phenomenon,characterized by a pronounced increase in variance and autocorrelation coefficient.The variance mutation points were found to be more identifiable and suitable as the primary criterion for predicting precursor information related to granite fracture,compared to the autocorrelation coefficient.It is noteworthy to emphasize that the CSD factor holds greater potential in elucidating the underlying mechanisms responsible for the critical transition of granite fracture,in comparison to the AE timing parameters.Furthermore,a novel multi-parameter collaborative prediction method for rock fracture was developed by comprehensively analyzing predictive information,including abnormal variation modes and the CSD factor of AE characteristic parameters.This method enhances the understanding and prediction of rock fracture-related geohazards.

Natural vibration and critical velocity of translating Timoshenko beam with non-homogeneous boundaries

In most practical engineering applications,the translating belt wraps around two fixed wheels.The boundary conditions of the dynamic model are typically specified as simply supported or fixed boundaries.In this paper,non-homogeneous boundaries are introduced by the support wheels.Utilizing the translating belt as the mechanical prototype,the vibration characteristics of translating Timoshenko beam models with nonhomogeneous boundaries are investigated for the first time.The governing equations of Timoshenko beam are deduced by employing the generalized Hamilton's principle.The effects of parameters such as the radius of wheel and the length of belt on vibration characteristics including the equilibrium deformations,critical velocities,natural frequencies,and modes,are numerically calculated and analyzed.The numerical results indicate that the beam experiences deformation characterized by varying curvatures near the wheels.The radii of the wheels play a pivotal role in determining the change in trend of the relative difference between two beam models.Comparing the results unearths that the relative difference in equilibrium deformations between the two beam models is more pronounced with smaller-sized wheels.When the two wheels are of equal size,the critical velocities of both beam models reach their respective minima.In addition,the relative difference in natural frequencies between the two beam models exhibits nonlinear variation and can easily exceed 50%.Furthermore,as the axial velocities increase,the impact of non-homogeneous boundaries on modal shape of translating beam becomes more significant.Although dealing with non-homogeneous boundaries is challenging,beam models with non-homogeneous boundaries are more sensitive to parameters,and the differences between the two types of beams undergo some interesting variations under the influence of non-homogeneous boundaries.

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.

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.

Geometric properties of the first singlet S-wave excited state of two-electron atoms near the critical nuclear charge

The geometric structure parameters and radial density distribution of 1s2s1S excited state of the two-electron atomic system near the critical nuclear charge Z_(c)were calculated in detail under tripled Hylleraas basis set.Contrary to the localized behavior observed in the ground and the doubly excited 2p^(23)Pe states,for this state our results identify that while the behavior of the inner electron increasingly resembles that of a hydrogen-like atomic system,the outer electron in the excited state exhibits diffused hydrogen-like character and becomes perpendicular to the inner electron as nuclear charge Z approaches Z_(c).This study provides insights into the electronic structure and stability of the two-electron system in the vicinity of the critical nuclear charge.

Critical behavior of quasi-two-dimensional ferromagnet Cr_(1.04)Te_(2)

The self-intercalation of Cr into pristine two-dimensional(2D) van der Waals ferromagnetic CrTe_(2),which forms chromium tellurides(Cr_(x)Te_(2)),has garnered interest due to their remarkable magnetic characteristics and the wide variety of chemical compositions available.Here,comprehensive basic characterization and magnetic studies are conducted on quasi-2D ferromagnetic Cr_(1.04)Te_(2) crystals.Measurements of the isothermal magnetization curves are conducted around the critical temperature to systematically investigate the critical behavior.Specifically,the critical exponents β=0.2399,γ=0.859,and δ=4.3498,as well as the Curie temperature T_(C)=249.56 K,are determined using various methods,including the modified Arrott plots,the Kouvel-Fisher method,the Widom scaling method,and the critical isotherm analysis.These results indicate that the tricritical mean-field model accurately represents the critical behavior of Cr_(1.04)Te_(2.A magnetic phase diagram with tricritical phenomenon is thus constructed.Further investigations confirm that the critical exponents obtained conform to the scalar equation near T_(C),indicating their self-consistency and reliability.Our work sheds light on the magnetic properties of quasi-2D Cr_(1.04)Te_(2),broadening the scope of the van der Waals crystals for developments of future spintronic devices operable at room temperature.

Determination of critical state line(CSL)for silty-sandy iron ore tailings subjected to low-high confining pressures

The disposal of filtered tailings in high dry stacks can induce particle breakage,changing the material's behaviour during the structure's lifetime.The grading changes influence material properties at the critical state,and this is not mature for intermediate artificial soils(tailings)in a broad range of confining pressures.In this paper,it aims to describe the behaviour of iron ore tailings in a spectrum of confining pressures broader than the reported in previous studies.A series of consolidated drained(CD)triaxial tests was carried out with confining pressures ranging from 0.075 MPa to 120 MPa.These results show that the amount of breakage plays an essential role in the response of iron ore tailings.The existence of curved critical state line(CSL)in both specific volume(ν)-logarithm of mean effective stress(p′)and deviatoric stress(q)-mean effective stress(p′)planes,and different responses in the deviatoric stress-axial strain-volumetric strain curves were verified.An inverse S-shaped equation was proposed to represent the silty-sandy tailings'behaviour up to high pressures onν-lnp′plane.The proposed equation provides a basis for enhancing constitutive models and considers the evolution of the grading up to severe loading conditions.The adjustment considered three regions with different responses associated with particle breakage at different pressure levels.

Quantitative determination of the critical points of Mott metal–insulator transition in strongly correlated systems

Mottness is at the heart of the essential physics in a strongly correlated system as many novel quantum phenomena occur in the metallic phase near the Mott metal–insulator transition. We investigate the Mott transition in a Hubbard model by using the dynamical mean-field theory and introduce the local quantum state fidelity to depict the Mott metal–insulator transition. The local quantum state fidelity provides a convenient approach to determining the critical point of the Mott transition. Additionally, it presents a consistent description of the two distinct forms of the Mott transition points.

Connection-Free Transmission for Critical MTC

In this paper,a contention-based connection-free transmission scheme is proposed to meet the stringent requirements of ultra-reliability and low-latency for critical machine-type communication(cMTC).To improve reliability,we design multiple independent sparse orthogonal pilots(MISOP)to significantly reduce the probability of pilot collision to the order of 10^(−5).Besides,the advancements of massive MIMO(mMIMO)are exploited to further enhance the reliability.To achieve low latency,connection-free slot-based one-shot transmission without retransmissions is adopted.On the receiver side,single round of multi-user detection(MUD)without interference cancellation(IC)can reduce the processing delay.The imprecise synchronization between cMTC device and the gNB in connection-free transmission,e.g.,time and frequency offsets,are also considered.The simulation results shows that the proposed scheme can well satisfy the ambitious requirements of cMTC,and has the potential applications in supporting massive cMTC devices in 6G.

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.

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.