Enabling High Reversibility of Zn anode via Interfacial Engineering Induced by Amino acid Electrolyte Additive.

Despite possessing substantial benefits of enhanced safety and cost-effectiveness, the aqueous zinc ion batteries (AZIBs) still suffers with the critical challenges induced by inherent instability of Zn metal in aqueous electrolytes. Zn dendrites, surface passivation, and corrosion are some of the key challenges governed by water-driven side reactions in Zn anodes. Herein, a highly reversible Zn anode is demonstrated via interfacial engineering of Zn/electrolyte driven by amino acid D-Phenylalanine (DPA) additions. The preferential adsorption of DPA and the development of compact SEI on the Zn anode suppressed the side reactions, leading to controlled and uniform Zn deposition. As a result, DPA added aqueous electrolyte stabilized Zn anode under severe test environments of 20.0 mA cm-2 and 10.0 mAh cm-2 along with an average plating/stripping Coulombic efficiency of 99.37%. Under multiple testing conditions, the DPA-incorporated electrolyte outperforms the control group electrolyte, revealing the critical additive impact on Zn anode stability. This study advances interfacial engineering through versatile electrolyte additive(s) toward development of stable Zn anode, which may lead to its practical implementation in aqueous rechargeable zinc batteries.

Nutrition, phytochemical profiling, in vitro biological activities, and in silico studies of South Chinese white pitaya (Hylocereus undatus).

Background: White pitaya, a popular tropical fruit, is known for its high nutritional value. It is commercially cultivated worldwide for its potential use in the food and pharmaceutical industries. This study aims to assess the nutritional and phytochemical contents and biological potential of the South Chinese White Pitaya (SCWP) peel, flesh, and seed extracts. Methods: Extract fractions with increasing polarity (ethyl acetate < acetone < ethanol < methanol < aqueous) were prepared. Antibacterial potential was tested against multidrug-resistant (MDR) bacteria, and antioxidant activity was determined using, 2-diphenyl-1-picrylhydrazyl (DPPH) and 2,2'-Azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) radical scavenging assays, and cytotoxic activity against human keratinocyte cells using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl-2H-tetrazolium bromide (MTT) assay. Pharmacological screening and molecular docking simulations were conducted to identify potential antibacterial compounds with druggable characteristics. Molecular dynamics simulation (MDS) was employed to validate the binding stability of the promising ligand-protein complexes. Results: All parts of the fruit exhibited a substantial amount of crucial nutrients (minerals, sugars, proteins, vitamins, and fatty acids). The ethanol (ET) and acetone (AC) fractions of all samples demonstrated notable inhibitory effects against tested MDR bacteria, with MIC50 ranges of 74-925 µg/mL. Both ET and AC fractions also displayed remarkable antioxidant activity, with MIC50 ranges of 3-39 µg/mL. Cytotoxicity assays on HaCaT cells revealed no adverse effects from the crude extract fractions. LC-MS/MS analyses identified a diverse array of compounds, known and unknown, with antibacterial and antioxidant activities. Molecular docking simulations and pharmacological property screening highlighted two active compounds, baicalein (BCN) and lenticin (LTN), showing strong binding affinity with selected target proteins and adhering to pharmacological parameters. MDS indicated a stable interaction between the ligands (BCN and LTN) and the receptor proteins over a 100-ns simulation period. Conclusion: Our study provides essential information on the nutritional profile and pharmacological potential of the peel, flesh, and seeds of SCWP. Furthermore, our findings contribute to the identification of novel antioxidants and antibacterial agents that could be capable of overcoming the resistance barrier posed by MDR bacteria.

Machine learning-based prediction of heat transfer performance in annular fins with functionally graded materials.

This paper presents a study investigating the performance of functionally graded material (FGM) annular fins in heat transfer applications. An annular fin is a circular or annular structure used to improve heat transfer in various systems such as heat exchangers, electronic cooling systems, and power generation equipment. The main objective of this study is to analyze the efficiency of the ring fin in terms of heat transfer and temperature distribution. The fin surfaces are exposed to convection and radiation to dissipate heat. A supervised machine learning method was used to study the heat transfer characteristics and temperature distribution in the annular fin. In particular, a feedback architecture with the BFGS Quasi-Newton training algorithm (trainbfg) was used to analyze the solutions of the mathematical model governing the problem. This approach allows an in-depth study of the performance of fins, taking into account various physical parameters that affect its performance. To ensure the accuracy of the obtained solutions, a comparative analysis was performed using guided machine learning. The results were compared with those obtained by conventional methods such as the homotopy perturbation method, the finite difference method, and the Runge-Kutta method. In addition, a thorough statistical analysis was performed to confirm the reliability of the solutions. The results of this study provide valuable information on the behavior and performance of annular fins made from functionally graded materials. These findings contribute to the design and optimization of heat transfer systems, enabling better heat management and efficient use of available space.

Uncovering Potentially Therapeutic Phytochemicals, In silico Analysis, and Biological Assessment of South-Chinese Red Dragon Fruit (Hylocereus polyrhizus).

Red dragon fruit is gaining popularity globally due to its nutritional value and bioactive components. The study aimed to assess the phytochemical, nutritional composition, antioxidant, antibacterial, and cytotoxic properties of extracts from the South Chinese red dragon fruit peel, flesh, and seeds. Extract fractions with increasing polarity (ethyl acetate

Nitrogen-vacancy-rich molybdenum nitride nanosheets as highly efficient electrocatalysts for nitrogen reduction reaction.

The development of low-cost earth-abundant electrocatalysts to produce ammonia (NH3) with high efficiency for the nitrogen (N2) reduction reaction (NRR) remains challenging. Herein, we propose the development of highly efficient ultrathin nitrogen-vacancy-rich molybdenum nitride nanosheets (MoN-NV) for NRR using basic electrolytes under ambient conditions. In 0.1 M KOH, this catalyst attained a high faradaic efficiency (FE) of ∼14% with an NH3 yield of 22.5 µg h-1 mg-1cat at -0.3 V vs. a reversible hydrogen electrode under ambient conditions. The characterization results and electrochemical studies disclosed that nitrogen vacancies in the MoN-NV nanosheets played a critical role in the enhanced electrocatalytic activity for NRR. Furthermore, the recycling tests confirmed the stability of the catalyst during NRR electrolysis.

Contemporary advances in photocatalytic CO2 reduction using single-atom catalysts supported on carbon-based materials.

The persistent issue of CO2 emissions and their subsequent impact on the Earth's atmosphere can be effectively addressed through the utilization of efficient photocatalysts. Employing a sustainable carbon cycle via photocatalysis presents a promising technology for simultaneously managing the greenhouse effect and the energy dilemma. However, the efficiency of energy conversion encounters limitations due to inadequate carrier utilization and a deficiency of reactive sites. Single-atom catalysts (SACs) have demonstrated exceptional performance in efficiently addressing the aforementioned challenges. This review article commences with an overview of SAC types, structures, fundamentals, synthesis strategies, and characterizations, providing a logical foundation for the design and properties of SACs based on the correlation between their structure and efficiency. Additionally, we delve into the general mechanism and the role of SACs in photocatalytic CO2 reduction. Furthermore, we furnish a comprehensive survey of the latest advancements in SACs concerning their capacity to enhance efficiency, long-term stability, and selectivity in CO2 reduction. Carbon-structured support materials such as covalent organic frameworks (COFs), graphitic carbon nitride (g-C3N4), metal-organic frameworks (MOFs), covalent triazine frameworks (CTFs), and graphene-based photocatalysts have garnered significant attention due to their substantial surface area, superior conductivity, and chemical stability. These carbon-based materials are frequently chosen as support matrices for anchoring single metal atoms, thereby enhancing catalytic activity and selectivity. The motivation behind this review article lies in evaluating recent developments in photocatalytic CO2 reduction employing SACs supported on carbon substrates. In conclusion, we highlight critical issues associated with SACs, potential prospects in photocatalytic CO2 reduction, and existing challenges. This review article is dedicated to providing a comprehensive and organized compilation of recent research findings on carbon support materials for SACs in photocatalytic CO2 reduction, with a specific focus on materials that are environmentally friendly, readily accessible, cost-effective, and exceptionally efficient. This work offers a critical assessment and serves as a systematic reference for the development of SACs supported on MOFs, COFs, g-C3N4, graphene, and CTFs support materials to enhance photocatalytic CO2 conversion.

Mixed Diffuse and Tumoral Form of Bing-Neel Syndrome Successfully Treated with Ibrutinib.

Introduction: Bing-Neel syndrome (BNS) is a rare and heterogenous manifestation of Waldenström macroglobulinemia (WM) involving central nervous system (CNS) infiltration by malignant lymphoplasmacytic cells. Efforts to standardize diagnostic criteria have improved in recent years, as have treatment options including the use of the Bruton tyrosine kinase inhibitor (BTKI) ibrutinib. Case Presentation: Here, we present the case of a 70-year-old male with a remote history of WM previously treated with bendamustine and rituximab, who presented to medical attention with several months of left-sided weakness, headache, and ataxia. Brain magnetic resonance imaging revealed numerous enhancing masses in the bilateral cerebral hemispheres, inferior medulla, and upper cervical spine. Laboratory studies showed serum IgM lambda monoclonal gammopathy and elevated free serum kappa and lambda light chains, while cerebrospinal fluid flow cytometry revealed CD19+ B cells. Stereotactic brain biopsy of a right frontal brain lesion was consistent with lymphoplasmacytic lymphoma, confirmed by a positive MYD88 L265P mutation. He received ibrutinib 420 mg orally daily, and this resulted in appreciable clinical and radiologic responses, which have persisted over a 31-month period. Conclusion: The advent of molecularly targeted agents and novel therapies for WM has provided patients and clinicians with additional therapeutic options. The use of BTK inhibitors with their high-level CNS penetrance, in particular, offers a novel way to treat BNS and improve patient overall survival while maintaining a high level of quality of life. We discuss the importance of MYD88 L265P testing in the context of BNS as well as the expanding role of BTKIs in treating this disease.

High-Current Capable and Non-Flammable Protic Organic Electrolyte for Rechargeable Zn Batteries.

Rechargeable Zinc batteries (RZBs) are considered a potent competitor for next-generation electrochemical devices, due to their multiple advantages. Nevertheless, traditional aqueous electrolytes may cause serious hazards to long-term battery cycling through fast capacity fading and poor Coulombic efficiency (CE), which happens due to complex reaction kinetics in aqueous systems. Herein, we proposed the novel adoption of the protic amide solvent, N-methyl formamide (NMF) as a Zinc battery electrolyte, which possesses a high dielectric constant and high flash point to promote fast kinetics and battery safety simultaneously. Dendrite-free and granular Zn deposition in Zn-NMF electrolyte assures ultra-long lifespan of 2000 h at 2.0 mA cm-2 /2.0 mAh cm-2 , high CE of 99.57 %, wide electrochemical window (≈3.43 V vs. Zn2+ /Zn), and outstanding durability up to 10.0 mAh cm-2 . This work sheds light on the efficient performance of the protic non-aqueous electrolyte, which will open new opportunities to promote safe and energy-dense RZBs.

The interplay between servant leadership, psychological safety, trust in a leader and burnout: assessing causal relationships through a three-wave longitudinal study.

COVID-19 pandemic has brought unprecedented psychological challenges for frontline healthcare workers, especially nurses, causing anxiety and depression leading to burnout. The responsibility of healthcare leaders has increased manyfold to deal with such challenges. This study attempts to employ the conservation of resources theory to examine the relationship between servant leadership and nurses' burnout, with the mediating role of psychological safety and the moderating effect of trust in leader. A three-wave longitudinal design was employed for data collection from 1204 nurses from 27 hospitals in China. The partial least squares structural equation modeling technique was used for data analyses with SmartPLS version 3.2.8. The findings endorse that servant leadership at time 1 significantly reduces nurses' burnout measured at time 3 through the mediating role of psychological safety measured at time 2, and that a higher level of trust in the leader enhances the impact of servant leadership in reducing nurses' burnout.

Analysis of heat transmission in convective, radiative and moving rod with thermal conductivity using meta-heuristic-driven soft computing technique.

Abstract: The present study analyzes the thermal attribute of conductive, convective, and radiative moving fin with thermal conductivity and constant velocity. The basic Darcy's model is utilized to formulate the governing equation for the problem, which is further nondimensionalized using certain variables. Moreover, an effective soft computing paradigm based on the approximating ability of the feedforword artificial neural networks (FANN's) and meta-heuristic approach of global and local search optimization techniques is developed to quantify the effect of variations in significant parameters such as ambient temperature, radiation-conduction number, Peclet number, nonconstant thermal conductivity, and initial temperature parameter on the temperature gradient of the rod. The results by the proposed FANN-AOA-SQP algorithm are compared with radial basis function approximation, Runge-Kutta-Fehlberg method and machine-learning algorithms. An extensive graphical and statistical analysis based on solution curves and errors such as absolute errors, mean square error, standard deviations in Nash-Sutcliffe efficiency, mean absolute deviations, and Theil's inequality coefficient are performed to show the accuracy, ease of implementation, and robustness of the design scheme.

Evaluation of the Dielectric and Insulating Properties of Newly Synthesized Ethylene/1-Hexene/4-Vinylcyclohexene Terpolymers.

Terpolymerizations of newly synthesized ethylene (E), vinylcyclohexene (VCH), and 1-hexene were carried out with symmetrical metallocene catalysts rac-Me2Si(2-Me-4-Ph-Ind)2ZrCl2 (catalyst A) and rac-Et(Ind)2ZrCl2 (catalyst B). X-ray diffractometry (XRD), scanning electron microscopy (SEM), differential scanning calorimetry (DSC), high-temperature gel permeation chromatography (GPC), and nuclear magnetic resonance (NMR) spectroscopy were used to evaluate the behavior and microstructure of the polymers. The activity of catalyst B was 1.49 × 106 gm/mmolMt·h), with a T m of 73.45 (°C) and ΔH m of 43.19 (J/g), while catalyst A produced first higher 1-hexene, 19.6 mol %, and VCH contents with a narrow molecular weight distribution (MWD). In previous reports, ethylene propylene monomer dienes (EPDM) had a low content and were used for dielectric and insulating properties with nanomaterials. Second, this paper presents a kind of elastomeric polymers based on E/1-hexene and VCH with a high dielectric constant (k = 6-4) and mechanical properties. In addition, low dielectric loss suggests the suitable application potential of these polymeric materials for the fabrications of capacitors. Also, this work reveals that these polymers can be a better candidate for high-voltage electrical insulation due to their enhanced dielectric, mechanical, and thermal characteristics. To examine the insulating property, the interface characteristics of the polymer were evaluated using electrochemical impedance spectroscopy (EIS) with a frequency range of 1 × 105-0.01 Hz and an amplitude of 5.0 mV. EIS is an effective method to investigate the polymers' interfacial electron transfer characteristics. The EIS Nyquist plot showed high Warburg impedance features in the low-frequency domain with straight lines without a semicircle, suggesting that the property of the polymer owing to the high electrical resistance and poor conductivity for ionic kinetics in the electrolyte may have surpassed that of the semicircle. Although the slope of low frequencies in polymers holding potent exoelectrogenic bacteria (Shewanella oneidensis MR-1) as a charge carrier in the electrolyte could significantly reduce the Warburg resistance, it still could not improve the conductivity, which demonstrated that the external charge supply could not alter the insulating property in the used polymers.

On the Computational Study of a Fully Wetted Longitudinal Porous Heat Exchanger Using a Machine Learning Approach.

The present study concerns the modeling of the thermal behavior of a porous longitudinal fin under fully wetted conditions with linear, quadratic, and exponential thermal conductivities surrounded by environments that are convective, conductive, and radiative. Porous fins are widely used in various engineering and everyday life applications. The Darcy model was used to formulate the governing non-linear singular differential equation for the heat transfer phenomenon in the fin. The universal approximation power of multilayer perceptron artificial neural networks (ANN) was applied to establish a model of approximate solutions for the singular non-linear boundary value problem. The optimization strategy of a sports-inspired meta-heuristic paradigm, the Tiki-Taka algorithm (TTA) with sequential quadratic programming (SQP), was utilized to determine the thermal performance and the effective use of fins for diverse values of physical parameters, such as parameter for the moist porous medium, dimensionless ambient temperature, radiation coefficient, power index, in-homogeneity index, convection coefficient, and dimensionless temperature. The results of the designed ANN-TTA-SQP algorithm were validated by comparison with state-of-the-art techniques, including the whale optimization algorithm (WOA), cuckoo search algorithm (CSA), grey wolf optimization (GWO) algorithm, particle swarm optimization (PSO) algorithm, and machine learning algorithms. The percentage of absolute errors and the mean square error in the solutions of the proposed technique were found to lie between 10-4 to 10-5 and 10-8 to 10-10, respectively. A comprehensive study of graphs, statistics of the solutions, and errors demonstrated that the proposed scheme's results were accurate, stable, and reliable. It was concluded that the pace at which heat is transferred from the surface of the fin to the surrounding environment increases in proportion to the degree to which the wet porosity parameter is increased. At the same time, inverse behavior was observed for increase in the power index. The results obtained may support the structural design of thermally effective cooling methods for various electronic consumer devices.

Progress toward Polymerization Reaction Monitoring with Different Dienes: How Small Amounts of Dienes Affect ansa-Zirconocenes/Borate/Triisobutylaluminium Catalyst Systems.

The objectives of this work were to address the fundamental characteristics of ansa-zirconocene catalyzed E/diene copolymerization and E/diene/1-hexene and E/diene/propylene terpolymerizations, and the quantitative relationship between diene structure and polymer chain propagation rate constant in term of quantifiable catalytic active sites. One of the most important but unknown factors in olefins ansa-zirconocene complexes is the distribution of the catalyst between sites actively participating in polymer chain formation and dormant sites. A set of ethylene/dienes copolymerizations, and ethylene/dienes/1-hexene and ethylene/dienes/1-hexene terpolymerizations catalyzed with ansa-zirconocenes/borate/triisobutylaluminium (rac-Et(Ind)2ZrCl2/[Ph3C][B(C6F5)4]/triisobutylaluminium (TIBA) were performed in toluene at 50 °C To determine the active center [C*]/[Zr] ratio variation in the copolymerization of E with different dienes and their terpolymerization with 1-hexene and propylene, each polymer propagation chain ends were quenched with 2-thiophenecarbonyl, which selectively quenches the metal-polymer bonds through acyl chloride. The ethylene, propylene, 1-hexene, and diene composition-based propagation rate constants (kpE, kpP, kp1-H, and kpdiene), thermal (melting and crystalline) properties, composition (mol% of ethylene, propylene, 1-hexene, and diene), molecular weight, and polydispersity were also studied in this work. Systematic comparisons of the proportion of catalytically [Zr]/[C*] active sites and polymerization rate constant (kp) for ansa-zirconocenes catalyzed E/diene, E/diene/1-hexene, and E/diene/propylene polymerization have not been reported before. We evaluated the addition of 1-hexene and propylene as termonomers in the copolymerization with E/diene. To make a comparison for each diene under identical conditions, we started the polymerization by introducing an 80/20 mole ratio of E/P and 0.12 mol/L of 1-hexene in the system. The catalyst behavior against different dienes, 1-hexene, and propylene is very interesting, including changes in thermal properties, cyclization of 1-hexene, and decreased incorporation of isoprene and butadiene, changes in the diffusion barriers in the system, and its effect on kp.

Heat Transfer Analysis of Nanofluid Flow in a Rotating System with Magnetic Field Using an Intelligent Strength Stochastic-Driven Approach.

This paper investigates the heat transfer of two-phase nanofluid flow between horizontal plates in a rotating system with a magnetic field and external forces. The basic continuity and momentum equations are considered to formulate the governing mathematical model of the problem. Furthermore, certain similarity transformations are used to reduce a governing system of non-linear partial differential equations (PDEs) into a non-linear system of ordinary differential equations. Moreover, an efficient stochastic technique based on feed-forward neural networks (FFNNs) with a back-propagated Levenberg-Marquardt (BLM) algorithm is developed to examine the effect of variations in various parameters on velocity, gravitational acceleration, temperature, and concentration profiles of the nanofluid. To validate the accuracy, efficiency, and computational complexity of the FFNN-BLM algorithm, different performance functions are defined based on mean absolute deviations (MAD), error in Nash-Sutcliffe efficiency (ENSE), and Theil's inequality coefficient (TIC). The approximate solutions achieved by the proposed technique are validated by comparing with the least square method (LSM), machine learning algorithms such as NARX-LM, and numerical solutions by the Runge-Kutta-Fehlberg method (RKFM). The results demonstrate that the mean percentage error in our solutions and values of ENSE, TIC, and MAD is almost zero, showing the design algorithm's robustness and correctness.

Polymerization kinetics of bicyclic olefins and mechanism with symmetrical ansa-metallocene catalysts associated with active center count: relationship between their activities and structure and activation path.

Copolymerization of ethylene (E) with 5-vinyl-2-norbornene (VNB) catalyzed by ansa-metallocenes allows the precise control of essential polymeric properties such as comonomer incorporation, molecular weight (M w), and polydispersity (D). Significant efforts have been devoted to synthesizing and developing novel catalysts, cocatalysts, and activators, although the fundamental elements of catalytic processes remain unclear. For example, it is questionable how polymeric catalysts are divided across dormant and active sites and how this distribution affects the order of monomers for the propagation rate, which widely vary in the literature. Furthermore, although the empirical correlation between the monomers and average M w has been established in many systems, the fundamental processes of chain termination remain unknown. Furthermore, the involvement of ion-pairing in metallocene-catalyzed polymerization and the termination mechanisms are also contentious issues. In this study, we describe the use of a quenched-labeling technique based on acyl chloride to selectively quench the zirconium metal-polymeric bond, which can be used to study the kinetics, active site [Zr][C*] counting, copolymer microstructure, and molecular weight distribution (MWD) to determine the rate laws for chain initiation, chain propagation rate (R p), propagation rate constant (k p) and chain termination. In addition, we also predict previously unknown chemical characteristics of E/bicyclic copolymerization processes, where either a cis-endocyclic double bond with steric properties or a vinyl exocyclic double bond affects the activity, i.e., [Zr]/[*C], (R p) and (k p). All these properties require the implementation of a particular kinetic mechanism that assumes the low activity of the building copolymer chains incorporating a single ethylene/VNB unit, i.e., the Cp2Zr-C2H5 group, in the ethylene addition process in the Cp2Zr-C bond. Due to ß-agostic stabilization, the Cp2Zr-C2H5 group exhibits a distinct feature. These effects were confirmed experimentally, such as the E/VNB co-polymer activity and VNB mol%, propagation rate decrease in the polymerization time (t p) of 120 s to 1800 s, crystalline properties, and significant increase in molecular weight. The active center [Zr]/[*C] fraction considerably increased in the initial (t p) 840 s, and subsequently tended to the steady stage of 33%, which is lower than previously reported E homo- and E/P copolymerization. The lower [C*]/[Zr] in both the early and stable stages, decrease in VNB mol%, and R p with t p can be associated with the more significant fraction of Cp2Zr-CH2CH3-type dormant site by the ß-agostic hydrogen interaction with the Cp2Zr metal. The t p versus R pE, R pVNB, k pE, k pVNB, and [Zr]/[C*] count could be fitted to a model that invokes deactivation of the growing polymer chains. In the case of the thermal behavior of the copolymers (melting temperature (T m) and crystalline temperature (ΔH m)), T m varied from 101 °C to 121 °C, while ΔH m varied from 9 to 16 (J g-1).

Exploring Green Creativity: The Effects of Green Transformational Leadership, Green Innovation Climate, and Green Autonomy.

None of the studies published in the extant literature has discussed the role of green innovation climate and green autonomy concerning green creativity and this study aims to offer these two novel constructs. By introducing the componential theory of creativity, this study explores green transformational leadership (GTL), green innovation climate, and green autonomy as antecedents of green creativity. The authors employed structural equation modeling (SEM) to analyze survey-based data collected from automotive firms in China. Data were collected from employee-supervisor working in the automotive industry located in Liaoning province, China. The findings reveal that GTL directly and indirectly via green innovation climate partially mediates the green creativity of employees in China. Moreover, green autonomy moderates the relationship between green innovation climate and green creativity. This pivotal contribution suggests that automotive business enterprises should develop GTL to nurture a green innovation climate and offer green autonomy for the green creativity of employees. The above antecedents of green creativity may enable business firms to gain a competitive advantage by innovating green products and practices.

Severe Thrombocytopenia in Patients With Advanced Neuroendocrine Tumor Treated With Peptide Receptor Radioligand Therapy.

BACKGROUND: Peptide receptor radioligand therapy (PRRT) was Food and Drug Administration approved in 2018 for the treatment of unresectable somatostatin receptor-positive gastroenteropancreatic neuroendocrine tumors (NETs) and provides an important option for patients with advanced disease. A known adverse effect of this treatment is hematologic toxicity, although usually transient. We present 3 patients with metastatic gastroenteropancreatic NETs treated with PRRT who were evaluated for severe persistent thrombocytopenia. METHODS: Three patients who commenced therapy with PRRT were known to proceed to a bone marrow (BM) biopsy for persistent severe thrombocytopenia and were included in this study. These patients were identified retrospectively and evaluated for their tumor properties, including immunohistochemical markers, treatment modalities, and clinical outcomes. RESULTS: All 3 patients had metastatic NETs that progressed on prior lines of therapy and were treated with 1 to 4 doses of 177Lu-DOTATATE 7.4 GBq (200 mCi) before developing grade 3 (25,000 to 50,000/µL) refractory thrombocytopenia. All patients had concurrent bone metastases, and 2 of the 3 had baseline grade 1 thrombocytopenia. In all 3 cases, BM biopsy documented widespread tumor infiltration. CONCLUSIONS: Severe refractory thrombocytopenia after PRRT is rare and may result from numerous known causes, including radiation-induced myelotoxicity, myelodysplastic syndrome, and tumor BM infiltration. We present 3 cases of thrombocytopenia related to persistent or progressive BM metastasis. Although known bone metastasis is not a contraindication to PRRT, thrombocytopenia may be a manifestation of tumor progression and should be considered when making decisions about continuation of therapy.

Investigation of Three-Dimensional Condensation Film Problem over an Inclined Rotating Disk Using a Nonlinear Autoregressive Exogenous Model.

This paper analyzed the three-dimensional (3D) condensation film problem over an inclined rotating disk. The mathematical model of the problem is governed by nonlinear partial differential equations (NPDE's), which are reduced to the system of nonlinear ordinary differential equations (NODE's) using a similarity transformation. Furthermore, the system of NODEs is solved by the supervised machine learning strategy of the nonlinear autoregressive exogenous (NARX) neural network model with the Levenberg-Marquardt algorithm. The dimensionless profiles of velocity, acceleration, and temperature are investigated under the effect of variations in the Prandtl number and normalized thickness of the film. The results demonstrate that increasing the Prandtl number causes an increase in the fluid's temperature profile. The solutions obtained by the proposed algorithm are compared with the state-of-the-art techniques that show the accuracy of the approximate solutions by NARX-BLM. The mean percentage errors in the results by the proposed algorithm for Θ(η), Ψ(η), k(η), -s(η), and (θ(η)) are 0.0000180%, 0.000084%, 0.0000135%, 0.000075%, and 0.00026%, respectively. The values of performance indicators, such as mean square error and absolute errors, are approaching zero. Thus, it validates the worth and efficiency of the design scheme.

Environmentally Specific Servant Leadership and Employees' Pro-Environmental Behavior: Mediating Role of Green Self Efficacy.

INTRODUCTION: Employees' pro-environmental behavior is crucial for accomplishing organizations' green initiatives. There is a dearth of empirical research that explored the underlying mechanism of environmentally specific servant leadership (ESL) influencing employees' pro-environmental behavior (EPB). The theoretical lens of self-efficacy theory is employed to explore the influence of ESL in predicting EPB. Employees' green self-efficacy was introduced as the mediator through which ESL influences EPB. METHODOLOGY: Time-lagged data from 381 dyads of employee-supervisor from Pakistan's energy sector were collected during the months of June and July 2021 through systematic random sampling. The partial least squares structural equation modeling (PLS-SEM) technique was employed to analyze data and assess hypothesized relationships. RESULTS: The results show that all hypotheses are supported. Findings indicate that environmentally specific servant leadership has a significant direct impact on employees' pro-environmental behavior and employees' green self-efficacy partially mediates the positive influence of ESL on EPB. DISCUSSION: The study's managerial and theoretical implications are presented along with future research directions.

Analysis of Nanofluid Particles in a Duct with Thermal Radiation by Using an Efficient Metaheuristic-Driven Approach.

This study investigated the steady two-phase flow of a nanofluid in a permeable duct with thermal radiation, a magnetic field, and external forces. The basic continuity and momentum equations were considered along with the Buongiorno model to formulate the governing mathematical model of the problem. Furthermore, the intelligent computational strength of artificial neural networks (ANNs) was utilized to construct the approximate solution for the problem. The unsupervised objective functions of the governing equations in terms of mean square error were optimized by hybridizing the global search ability of an arithmetic optimization algorithm (AOA) with the local search capability of an interior point algorithm (IPA). The proposed ANN-AOA-IPA technique was implemented to study the effect of variations in the thermophoretic parameter (Nt), Hartmann number (Ha), Brownian (Nb) and radiation (Rd) motion parameters, Eckert number (Ec), Reynolds number (Re) and Schmidt number (Sc) on the velocity profile, thermal profile, Nusselt number and skin friction coefficient of the nanofluid. The results obtained by the designed metaheuristic algorithm were compared with the numerical solutions obtained by the Runge-Kutta method of order 4 (RK-4) and machine learning algorithms based on a nonlinear autoregressive network with exogenous inputs (NARX) and backpropagated Levenberg-Marquardt algorithm. The mean percentage errors in approximate solutions obtained by ANN-AOA-IPA are around 10-6 to 10-7. The graphical analysis illustrates that the velocity, temperature, and concentration profiles of the nanofluid increase with an increase in the suction parameter, Eckert number and Schmidt number, respectively. Solutions and the results of performance indicators such as mean absolute deviation, Theil's inequality coefficient and error in Nash-Sutcliffe efficiency further validate the proposed algorithm's utility and efficiency.