Search Results (329)

This paper showcases current developments in the use of carbon nanotube (CNT) and nanoparticle-based materials for electromagnetic radiation shielding. Electromagnetic radiation involves different types of radiation covering a wide spectrum of frequencies. Due to their good electrical conductivity, small diameter, and light weight, individual CNTs are good candidates for shielding radio and microwaves. CNTs can be organized into macroscale forms by dispersing them in polymers or by wrapping CNT strands into fabrics or yarn. Magnetic nanoparticles can also be incorporated into the CNT fabric to provide excellent shielding of electromagnetic waves. However, for shielding higher-frequency X-ray and gamma ray radiation, the situation is reversed. Carbon’s low atomic number means that CNTs alone are less effective than metals. Thus, different nanoparticles such as tungsten are added to the CNT materials to provide improved shielding of photons. The goal is to achieve a desired combination of light weight, flexibility, safety, and multifunctionality for use in shielding spacecraft, satellites, nuclear reactors, and medical garments and to support lunar colonization. Future research should investigate the effect of the size, shape, and configuration of nanoparticles on radiation shielding. Developing large-scale low-cost methods for the continuous manufacturing of lightweight multifunctional nanoparticle-based materials is also needed. Full article

The deterioration of uterine calcium transport capacity induced by aging is a common problem for late-laying period hens, causing decline in eggshell quality. This study aimed to investigate the effects and possible regulatory mechanisms of dietary puerarin (PU) on calcium transport and eggshell quality in aged hens. Two hundred eighty-eight Hubbard Efficiency Plus broiler breeder hens (50-week-old) were randomly allocated to three dietary treatments containing 0, 40, or 200 mg/kg puerarin (PU), with 8 replicates of 12 birds each, for an 8-week trial. The results demonstrated that dietary PU ameliorated the eggshell thickness and strength, which in turn reduced the broken egg rate (p < 0.05). Histological analysis showed that PU improved uterus morphology and increased epithelium height in the uterus (p < 0.05). Antioxidative capacity was significantly improved via upregulation of Nrf2, HO-1, and GPX1 mRNA expression in the uterus (p < 0.05), along with enhanced total antioxidant capacity (T-AOC) and glutathione peroxidase (GSH-PX) activity, and decreased levels of the oxidative stress marker malondialdehyde (MDA) (p < 0.05). Meanwhile, PU treatment reduced the apoptotic index of the uterus, followed by a significant decrease in expression of pro-apoptotic genes Caspase3 and BAX and the rate of BAX/BCL-2. Additionally, calcium content in serum and uterus, as well as the activity of Ca²⁺-ATPase in the duodenum and uterus, were increased by dietary PU (p < 0.05). The genes involved in calcium transport including ERα, KCNA1, CABP-28K, and OPN in the uterus were upregulated by PU supplementation (p < 0.05). The 16S rRNA gene sequencing revealed that dietary PU supplementation could reverse the age-related decline in the relative abundance of Bacteroidota within the uterus (p < 0.05). Overall, dietary PU can improve eggshell quality and calcium transport through enhanced antioxidative defenses and mitigation of age-related uterine degeneration. Full article

The focus on selecting broilers for rapid growth rates and enhanced breast muscle yield has resulted in a decline in meat quality. The differences in carcass characteristics and meat quality between Hubbard white broilers (HWs, a commercial breed) and Xueshan chickens (XSs, an indigenous breed) at market age were analyzed to determine the potential mechanisms responsible for these differences. The results show that HWs exhibited significantly better carcass performance than XSs, including the larger weight of the carcass, the breast muscle, and the thigh muscle (p < 0.01). In addition, based on HE staining analysis, HWs’ breast muscles had a considerably larger average myofiber area and diameter than those of XSs (p < 0.01). Furthermore, the physical characteristics of the meat revealed that XSs had higher redness and yellowness and also higher lightness. HW meat had a higher pH and thermal loss, but a lower shear force and drip loss than XS meat (p < 0.01). The content of saturated fatty acids (SFAs) and polyunsaturated fatty acids (PUFAs) was, remarkably, lower in the breast muscles of HWs than of XSs (p < 0.01). In contrast, HWs had a larger concentration of monounsaturated fatty acids (MUFAs) than XSs (p < 0.01). Finally, the breast muscles of XSs had lower levels of mRNA expression for genes linked to lipid metabolism, such as fatty acid binding protein 4 (Fabp4) and peroxisome proliferator-activated receptor alpha (Pparα), and had higher levels of the phosphofructokinase muscle type (Pfkm) compared to HWs (p < 0.01). These results indicate that a lower carcass yield was observed in XSs compared with HWs, but that XSs showed better performance in terms of meat quality than HW. Full article

We present a brief overview of the field of charge density waves (CDW) in condensed systems with focus set to the underlying mechanisms behind the CDW ground state. Our intention in this short review is not to count all related facts from the vast volume of literature about this decades-old and still developing field, but rather to pinpoint the most important, mostly theoretical ones, presenting the development of the field. Starting from the “early days”, mainly based on weakly coupled, chain-like quasi-1D systems and Peierls instability, in which the Fermi surface nesting has been the predominant and practically paradigmatic mechanism of the CDW ground state stabilisation, we track the change in paradigms while entering the field of layered quasi-2D systems, with Fermi surface far away from the nesting regime, in which rather strong, essentially momentum-dependent interactions and particular reconstructions of the Fermi surface become essential. Examples of real quasi-1D materials, such as organic and inorganic conductors like Bechgaard salts or transition metal trichalcogenides and bronzes, in which experiment and theory have been extremely successful in providing detailed understanding, are contrasted to layered quasi-2D materials, such as ${\mathrm{high-T}}_c$ superconducting cuprates, intercalated graphite compounds or transition metal dichalcogenides, for which the theory explaining an onset of the CDWs constitutes a frontier of this fast-evolving field, strongly boosted by development of modern ab initio calculation methods. Full article

Early-lactation high-producing dairy cows require highly digestible forages. Thirty early-lactation (58 days in milk; 38.9 kg/d milk) cows were blocked and randomly assigned to one of two treatments. The treatments were the control (CON), consisting of corn silage and alfalfa haylage produced via university crop production practices, versus supplementing soil and crop additives (SCA) during crop production. Milk production (32.6 and 36.9 kg/d for CON and SCA, respectively) increased (p < 0.04) when cows were fed SCA forages compared with cows fed CON forages, while the dry matter intakes were similar (p < 0.46). The yields of milk fat were similar (p > 0.26), but the milk protein (0.98 and 1.09 kg/d), lactose (1.62 and 1.88 kg/d), and total solids (3.77 and 4.25 kg/d) contents were greater (p < 0.05) for cows fed SCA compared with cows fed CON. The total-tract apparent neutral detergent fiber (48.5 and 54.7%) and acid detergent fiber (48.3 and 54.4%) digestibility increased (p < 0.03), while the starch digestibility (97.9 and 98.4%) tended (p < 0.06) to increase for cows fed SCA compared with cows fed CON. Feeding highly digestible forages during early lactation improved milk production, milk composition, and fiber digestibility in a high-forage ration. Full article

The current study is motivated by a difficulty in reconciling between particle number conservation and superconductivity. An alternative modeling, which is based on the hypothesis that disentanglement spontaneously ocuurs in quantum systems, is explored. The Fermi–Hubbard mode is employed to demonstrate a disentanglement-induced quantum phase transition into a state with a finite superconducting order parameter. Moreover, the effect of disentanglement on Josephson junction’s current phase relation is explored Full article

Many dynamic systems experience unwanted actuation caused by an unknown exogenous input. Typically, when these exogenous inputs are stochastically bounded and a basis set cannot be identified, a Kalman-like estimator may suffice for state estimation, provided there is minimal uncertainty regarding the true system dynamics. However, such exogenous inputs can encompass environmental factors that constrain and influence system dynamics and overall performance. These environmental factors can modify the system’s internal interactions and constitutive constants. The proposed control scheme examines the case where the true system’s plant changes due to environmental or health factors while being actuated by stochastic variances. This approach updates the reference model by utilizing the input and output of the true system. Lyapunov stability analysis guarantees that both internal and external error states will converge to a neighborhood around zero asymptotically, provided the assumptions and constraints of the proof are satisfied. Full article

This paper provides a novel approach to airport sustainability with a comparative analysis of frameworks presented by Airports Council International (ACI) and the World Economic Forum (WEF), a case study on environmental social governance (ESG) reporting for large US airports, a historical perspective and discussion regarding legal considerations, and sustainability metrics. Airport sustainability reporting provides numerous advantages, including enhanced transparency and accountability, and it also supports risk management, regulatory compliance, operational efficiency, risk management, community engagement, and investor relations. There are 30 large hub airports in the US, and each one of these publishes information on sustainability, which may consist of a sustainability report, reports on sustainability related topics, or website information. Eight of these large US airports publish an ESG report. ESG reports are of increasing interest due to their use internationally and due to the role of ESG reports in investment decisions. This paper presents an analysis of the information contained in ESG reports published by US airports and compares the frame of reference used by airports that utilize UN Sustainable Development Goals (SDGs) in their reporting. Case studies of ESG reports for Salt Lake City and Dallas Fort Worth Airports are presented to illustrate ESG reports, and the use of the SDG identified in these reports is compared the framework identified by Airports Council International (ACI) and the World Economic Forum (WEF). The discussion of airport ESG reporting provides a thorough and contextual review of the topic and examines how this framework may evolve to address the increasing interest in ESG reporting for US airports. The information provided may be used by airports to improve their sustainability reporting. Full article

In this work, a density functional theory (DFT) with Hubbard correction (U) approaches implemented through the Quantum ESPRESSO code is utilized to investigate the effects of fluorine (F) doping on the structural, electronic, and optical properties of rutile TiO₂. Rutile TiO₂ is a promising material for renewable energy production and environmental remediation, but its wide bandgap limits its application to the UV spectrum, which is narrow and expensive. To extend the absorption edge of TiO₂ into the visible light range, different concentrations of F were substituted at oxygen atom sites. The structural analysis reveals that the lattice constants and bond lengths of TiO₂ increased with F concentrations. Ab initio molecular dynamics simulations (AIMD) at 1000 K confirm that both pristine and F-doped rutile TiO₂ maintains structural integrity, indicating excellent thermal stability essential for high-temperature photocatalytic applications. Band structure calculations show that pure rutile TiO₂ has a bandgap of 3.0 eV, which increases as the F concentration rises, with the 0.25 F-doped structures exhibiting an even larger bandgap, preventing it from responding to visible light. The absorption edge of doped TiO₂ shifts towards the visible region, as shown by the imaginary part of the dielectric function. This research provides valuable insights for experimentalists, helping them understand how varying F concentrations influence the properties of rutile TiO₂ for photocatalytic applications. Full article

We investigate the entanglement properties in semiconductor quantum dot systems modeled by the extended Hubbard model, focusing on the impacts of potential energy variations and electron interactions within a four-site quantum dot spin chain. Our study explores local and pairwise entanglement across configurations with electron counts $N=4$ and $N=6$, under different potential energy settings. By adjusting the potential energy in specific dots and examining the entanglement across various interaction regimes, we identify significant variations in the ground states of quantum dots. We extend this analysis to larger systems with $L=6$ and $L=8$, comparing electron counts $N=L$ and $N=L+2$, revealing sharper entanglement transitions and reduced finite-size effects as the system size increases. Our results show that local potential shifts and the Coulomb interaction strength lead to notable redistributions of the electron configurations in the quantum dot spin chain, significantly affecting the entanglement properties. These changes are depicted in phase diagrams that highlight entanglements’ dependencies on the interaction strengths and potential energy adjustments, illustrating complex entanglement dynamics shifts triggered by interdot interactions. Full article

The problem of using accounting semi-identity-based (ASI) models in Econometrics can be severe in certain circumstances, and estimations from OLS regressions in such models may not accurately reflect causal relationships. This dataset was generated through Monte Carlo simulations, which allowed for the precise control of a causal relationship. The problem of an ASI cannot be directly demonstrated in real samples, as researchers lack insight into the specific factors driving each company’s investment policy. Consequently, it is impossible to distinguish whether regression results in such datasets stem from actual causality or are merely a byproduct of arithmetic distortions introduced by the ASI. The strategy of addressing this issue through simulations allows researchers to determine the true value of any estimator with certainty. The selected model for testing the influence of the ASI problem is the investment-cash flow sensitivity model (Fazzari, Hubbard and Petersen (FHP hereinafter) (1988)), which seeks to establish a relationship between a company’s investments and its cash flows and which is an ASI as well. The dataset included randomly generated independent variables (cash flows and Tobin’s Q) to analyze how they influence the dependent variable (cash flows). The Monte Carlo methodology in Stata enabled repeated sampling to assess how ASIs affect regression models, highlighting their impact on variable relationships and the unreliability of estimated coefficients. The purpose of this paper is twofold: its first goal is to provide a deeper explanation of the syntax in the related article, offering more insights into the ASI problem. The openly available dataset supports replication and further research on ASIs’ effects in economic models and can be adapted for other ASI-based analyses, as the information comprised in the reusability examples prove. Second, our aim is to encourage research supported by Monte Carlo simulations, as they enable the modeling of a comprehensive ecosystem of economic relationships between variables. This allows researchers to address a variety of issues, such as partial correlations, heteroskedasticity, multicollinearity, autocorrelation, endogeneity, and more, while testing their impact on the true value of coefficients. Full article

We perform a comprehensive analysis of the correlated electronic structure reconstruction of the ferromagnetic CrSBr van der Waals (vdW) bulk crystal. Using generalized gradient approximation combined with dynamical mean-field theory, we show the minor role played by multi-orbital electron–electron interactions in semiconducting CrSBr. Our study is relevant to understanding the electronic structure within the ${Cr}^{3+}$ oxidation state with strongly spin-polarized $t_{2g}$ orbitals and should be applicable to other ferromagnetic vdW materials from bulk down to the low-dimensional limit. This work is relevant for understanding orbital and spin selectivity and its link to the memristor current–voltage characteristic of CrSBr for future neuromorphic computing. Full article

Background: Uveal melanoma (UM) is a rare subtype of melanoma with distinct clinical and molecular features compared to other melanoma subtypes. UM tumors are frequently detected with mutations in GNA11, GNAQ, EIF1AX, BAP1, and SF3B1 instead of the typical mutations associated with cutaneous melanoma. Although hereditary UM is rare, germline BAP1 loss predisposes patients to UM and various other cancers. The CHEK2 (Checkpoint kinase 2) gene that encodes the protein CHK2, a serine-threonine kinase, is a cell cycle checkpoint regulator that acts as a tumor suppressor. CHK2 is involved in DNA repair, cell cycle arrest, or apoptosis in response to DNA damage. CHEK2 mutations have been linked to various cancers. While there is no strong evidence that CHEK2 mutations increase the risk of melanoma, two cases of germline CHEK2 mutations in UM patients have been reported. However, the incidence of CHEK2 variants in metastatic UM (MUM) has not been investigated. Thus, we conducted a retrospective analysis of patients with MUM and CHEK2 variants to understand this link better. Methods: We collected MUM cases from 2016 to 2024 from institutional databases. Tissues underwent analyses of molecular and genomic features, including tumor mutational burden, and were performed by a Clinically Certified Laboratory. Next-generation sequencing and variant calling were conducted to identify CHEK2 variants. Results: In this study, we reported ten patients with CHEK2 variants among 740 metastatic UM patients (1.4%) and four primary UM patients with CHEK2 germline mutations. Conclusions: Although rare, UM patients with an abnormal ATM–CHEK2 axis might receive clinical benefits from medications that target DNA repair mechanisms. Full article

Modeling many-body quantum systems is widely regarded as one of the most promising applications for near-term noisy quantum computers. However, in the near term, system size limitation will remain a severe barrier for applications in materials science or strongly correlated systems. A promising avenue of research is to combine many-body physics with machine learning for the classification of distinct phases. We present a workflow that synergizes quantum computing, many-body theory, and quantum machine learning (QML) for studying strongly correlated systems. In particular, it can capture a putative quantum phase transition of the stereotypical strongly correlated system, the Hubbard model. Following the recent proposal of the hybrid quantum-classical algorithm for the two-site dynamical mean-field theory (DMFT), we present a modification that allows the self-consistent solution of the single bath site DMFT. The modified algorithm can be generalized for multiple bath sites. This approach is used to generate a database of zero-temperature wavefunctions of the Hubbard model within the DMFT approximation. We then use a QML algorithm to distinguish between the metallic phase and the Mott insulator phase to capture the metal-to-Mott insulator phase transition. We train a recently proposed quantum convolutional neural network (QCNN) and then utilize the QCNN as a quantum classifier to capture the phase transition region. This work provides a recipe for application to other phase transitions in strongly correlated systems and represents an exciting application of small-scale quantum devices realizable with near-term technology. Full article