Lower Bound Research Articles

Trade-offs between optimal and robust scheduling in one-stage production

Given stochastic disturbances, such as variation in processing times, robust scheduling is recommended over optimal scheduling for production. Different from optimal scheduling that seeks an optimal solution to a key performance indicator (KPI), which relates to the average of a KPI, robust scheduling is to minimize the largest deviation from the optimum for the worst-case scenarios, which relates to the variance of a KPI. However, minimizing the variance does not necessarily optimize the average of a KPI. As one of the fundamental KPIs in production scheduling, total completion time (TCT) drives many other KPIs, such as average flow time, waiting time, due dates, and length of stay. Stochastic processing times and NP-hardness to minimize the variance of TCT, i.e., min(VTCT), are two challenges in production scheduling. To investigate the trade-offs between optimal and robust scheduling, we apply the differentiation method to analyze the first and second moments of TCT. In our approach, we use three statistical measures for processing times, which are the lower bound, the expected value, and the upper bound. We also use three terms for sequencing, which are x(1) the processing time of the initial job, x(i) the processing time of a job in the current position i of a sequence, and x′(i) the difference of processing times between two adjacent jobs. Applying the three measures for processing times to each of the three independent terms for sequencing, we generate 27=3·3·3 sequences to analyze the dynamics of VTCT. Through numerical analysis in our case studies, we show that our sequencing scheme can generate optimal solutions to min(TCT), and solid variation ranges of VTCT. Consequently, we can not only balance the trade-offs between min(TCT) and min(VTCT), but also analyze the trade-offs between optimal scheduling focusing on the first-moment of a KPI and robust scheduling focusing on the second moment. Moreover, our analysis approach using the differentiation method is unique for production scheduling, which enables us to develop analytical methods and heuristics for balancing trade-offs between optimal and robust scheduling.

On the biggest purely non-free conformal actions on compact Riemann surfaces and their asymptotic properties

A continuous action of a finite group G on a closed orientable surface X is said to be gpnf (Gilman purely non-free) if every element of G has a fixed point on X. We prove that the biggest order μ(g), of a gpnf-action on a surface of even genus g≥2, is bounded below by 8g and that this bound is sharp for infinitely many even g as well. This provides, for even genera, a gpnf-action analog of the celebrated Accola-Maclachlan bound 8g+8 for arbitrary finite continuous actions. We also describe the asymptotic behavior of μ. We define M as the set of values of the formμ˜(g)=μ(g)g+1, and its subsets M+ and M− corresponding to even and odd genera g. We show that the set M+d, of accumulation points of M+, consists of a single number 8. If g is odd, then we prove that 4g≤μ(g)<8g. We conjecture that this lower bound is sharp for infinitely many odd g. Finally, we prove that this conjecture implies that 4 is the only element of M−d, leading to Md={4,8}.

Neoadjuvant treatment with regorafenib and capecitabine combined with radiotherapy in locally advanced rectal cancer: a multicenter phase Ib trial (RECAP)–SAKK 41/16

BackgroundThe multi tyrosine kinase inhibitor regorafenib is active in metastatic colorectal cancer. Improvement in clinical outcome by adding regorafenib to long-course chemoradiotherapy (LcCRT) was investigated in molecularly undefined LARC. MethodsPatients with T3–4 and/or N+ but M0 rectal cancer were included. Neoadjuvant LcRCT consisted in capecitabine (C) 825mg/m2 d1–d38 and 28 fractions of 1.8Gy (50.4Gy). Regorafenib was added d1–14 and d22–35 in three dose escalation (DE) cohorts (40mg/80mg/120mg). The recommended dose (RD) was used for the expansion (EXP) cohort. Primary endpoints were dose-limiting toxicity (DLT) for DE and pathological response (near-complete regression [npCR] or complete regression [pCR]) for EXP. ResultsOverall, 25 patients were included. Two DLTs occurred at the regorafenib dose level of 120 mg, thereby establishing the RD at 80mg daily. Among the 19 patients who were treated at the RD, eight (42.1%; one-sided 80% confidence interval [CI] (lower bound): 30.7%; 95% CI: 20.3%–66.5%) reached the primary endpoint (five [26.3%] had npCR and three [15.8%] pCR). One additional patient received no surgery due to clinical complete response. All patients had R0 resections and clear circumferential margins. Postoperative complications occurred in six patients (35.3%). The most common grade ≥3 treatment-related adverse event in the EXP cohort was diarrhea (two patients). ConclusionAdding regorafenib 80mg to LcCRT in LARC resulted in both primary endpoints being met and yielded an expectedpathological response rate. Toxicity was manageable, and postoperative complications were as expected. Micro AbstractThe SAKK 41/16 study investigated the addition of regorafenib to the standard neoadjvuant chemoradiation with capecitabine. We could show expected pathological response rate and manageable toxicity at the recommended dose of regorafenib. Regorafenib may be potential partner for future trials investigating treatment intensification for high-risk locally advanced rectal cancer.

The Elasticity of Aggregate Output with Respect to Capital and Labor

It is often assumed that the elasticity of GDP with respect to capital is one-third, but this assumes zero markups and an aggregate production function. I estimate the elasticity allowing markups to vary by industry and with a rich input-output structure. Assumptions about capital costs provide bounds on elasticity. In the United States from 1948–1995, the capital elasticity ranged from 0.19–0.32 and shifted to 0. 24–0.37 by 1996–2018. Excluding housing or decapitalizing intellectual property lowers bounds to as low as 0. 11–0.26. Based on these elasticities, common estimates of total factor productivity growth represent a lower bound. (JEL E13, E22, E23, E25, N12)

Effects of inclined loads on strip footings with an underlying tunnel

The self-developed Finite Element Limit Analysis (FELA) code was utilized to examine the ultimate bearing capacity of strip footings positioned above tunnels affected by inclined loads. Bearing capacity factors were predicted using both upper bound (UB) and lower bound (LB) solutions, with a variance of less than 3 %. The primary focus of this study lies in assessing the influences of underlying tunnels and inclined loads on potential failure modes. In particular, the concept of failure envelopes was introduced, by which the load properties (inclination angle), the tunnel location (relative lateral distance and longitudinal distance from the footing) and the material properties of rock masses (GSI, mi, sci, g) were involved in to facilitate preliminary designs. In addition to envelopes, the transition among failure patterns was summarized, resting with any possible factors.

Upper Limit of Sound Speed in Nuclear Matter: A Harmonious Interplay of Transport Calculation and Perturbative Quantum Chromodynamic Constraint

Very recently, it has been shown that there is an upper bound on the squared sound speed of nuclear matter from the transport, which reads cs2≤0.781 . In this work, we demonstrate that this upper bound is corroborated by the reconstructed equation of state (EOS; modeled with a nonparametric method) for ultradense matter. The reconstruction integrates multimessenger observation for neutron stars, in particular, the latest radius measurements for PSR J0437–4715 ( 11.36−0.63+0.95 km), PSR J0030+0451 ( 11.71−0.83+0.88 km, in the ST+PDT model), and PSR J0740+6620 ( 12.49−0.88+1.28 km) by NICER have been adopted. The result shows in all cases, the cs2≤0.781 upper limit for EOS will naturally yield the properties of matter near the center of the massive neutron star consistent with the causality-driven constraint from pQCD, where, in practice, the density in implementing the pQCD likelihood (n L) is applied at 10ns (where ns is the nuclear saturation density). We also note that there is a strong correlation for the maximum c s 2 with n L, and cs2≤0.781 is somehow violated when n L = n c,TOV. The result indicates that a higher n L, even considering the uncertainties from statistics, is more natural. Moreover, the remarkable agreement between the outcomes derived from these two distinct and independent constraints (i.e., the transport calculation and pQCD boundary) lends strong support to their validity. In addition, the latest joint constraint for R 1.4, R 2.0, R 1.4 − R 2.0, and M TOV are 11.94−0.68+0.77 km, 11.99−0.67+0.88 km, −0.1−0.27+0.42 km, and 2.24−0.10+0.13M⊙ (at 90% credible level), respectively.

On generalized Sidon spaces

Sidon spaces have been introduced by Bachoc, Serra and Zémor as the q-analogue of Sidon sets, classical combinatorial objects introduced by Simon Szidon. In 2018 Roth, Raviv and Tamo introduced the notion of r-Sidon spaces, as an extension of Sidon spaces, which may be seen as the q-analogue of Br-sets, a generalization of classical Sidon sets. Thanks to their work, the interest on Sidon spaces has increased quickly because of their connection with cyclic subspace codes they pointed out. This class of codes turned out to be of interest since they can be used in random linear network coding. In this work we focus on a particular class of them, the one-orbit cyclic subspace codes, through the investigation of some properties of Sidon spaces and r-Sidon spaces, providing some upper and lower bounds on the possible dimension of their r-span and showing explicit constructions in the case in which the upper bound is achieved. Moreover, we provide further constructions of r-Sidon spaces, arising from algebraic and combinatorial objects, and we show examples of Br-sets constructed by means of them.

Novel approaches to improving gas separation: ionic liquids coated coke/ NH2-UiO-66-based mixed matrix membranes for CO2/N2 separation

Permeability and separation efficiency of mixed matrix membranes (MMMs) are two important aspects. Polymeric membranes offer excellent mechanical and physical properties; however, they have a low permeability. To enhance the permeability and separation performance of polyvinyl chloride (PVC) membranes, Cholinium amino acid-based (IL) were impregnated with activated coke/ NH2-UiO-66 (Zr) (AC/MOF) composite and then IL@AC/MOF filler was incorporated into PVC matrix. FTIR spectroscopy, TGA, SEM, EDX, and Brunauer-Emmett-Teller (BET) surface area measurement were used to characterize the MMMs prepared. The porous structure of MMMs nanocomposites causes AC/MOF composite to effectively accelerate gas the diffusion in the PVC matrix. The permeability measurements for CO2 and N2 were made at 288.15, 298.15, 308.15, and 318.15 K at pressure 3 bar. The outcomes indicates that the incorporation of the IL@AC/MOF filler increased the permeability of the PVC/AC/MOF MMMs compared to the pure polymeric membrane. The mixed matrix membranes exhibit superior gas separation performance, surpassing the 2008 Robson's Upper Bound.

Toward digitally twinning the process of creating machine controller digital twins – A G-code generation scenario

This paper proposes BatchEGO, an extension of Efficient Global Optimization (EGO), in an active learning context for creating and maintaining digital twins (DT). The motivation for this study is to address the challenges of obtaining high-quality yet cost and time effective data for developing accurate DTs of machine tool controllers that are robust to noise and physical system changes. BatchEGO is employed to generate manufacturing recipes (G-codes) recursively and iteratively, based on the spatial constraints of the physical machine, providing G-code based data for DTs. BatchEGO Interm is also proposed that extends BatchEGO by sampling additional intermediate points on the generated trajectory, to improve convergence and accuracy of DTs. To account for the stochastic nature of proposed methods, a total of 70 experiments based around repetitions of 4 correlation functions, 3 acquisition functions, and 4 sampling schemes are used to evaluate the performance of both methods. The results showcase impressive and faster convergence, in terms of sum of squared errors, for BatchEGO Interm with specific settings producing highly accurate and smooth G-codes. For instance, BatchEGO Interm with Matérn 3/2 correlation function and acquisition function of lower confidence bound can reach an error range of 0.0026 within 3-5 iterations. The work demonstrates the novelty and potential of such frameworks for enhancing data quality and quantity for DTs. The importance of G-code generation for DTs is also highlighted, as it can enable better control and optimization of machine tools in various industrial applications. The paper also discusses the different approaches for stitching the sampled points into G-code and compares their accuracy and efficiency.

Accelerating material discovery with a threshold-driven hybrid acquisition policy-based Bayesian optimization

Advancements in materials play a crucial role in technological progress. However, the process of discovering and developing materials with desired properties is often impeded by substantial experimental costs, extensive resource utilization, and lengthy development periods. To address these challenges, modern approaches often employ machine learning (ML) techniques such as Bayesian Optimization (BO), which streamline the search for optimal materials by iteratively selecting experiments that are most likely to yield beneficial results. However, traditional BO methods, while beneficial, often struggle with balancing the trade-off between exploration and exploitation, leading to sub-optimal performance in accelerated material discovery processes. This paper introduces a novel Threshold-Driven UCB-EI Bayesian Optimization (TDUE-BO) method, which dynamically integrates the strengths of Upper Confidence Bound (UCB) and Expected Improvement (EI) acquisition functions to optimize the material discovery process. Unlike the classical BO, our method focuses on efficiently navigating the high-dimensional material design space (MDS). TDUE-BO begins with an exploration-focused UCB approach, ensuring a comprehensive initial sweep of the MDS. As the model gains confidence, indicated by reduced uncertainty, it transitions to the more exploitative EI method, focusing on promising areas identified earlier. The UCB-to-EI switching policy, which is steered by ongoing monitoring of model uncertainty at each stage of sequential sampling, enables more efficient navigation through the MDS while guaranteeing quicker convergence. The effectiveness of TDUE-BO is demonstrated through its application on three different material science datasets, showing significantly better approximation and optimization performance over traditional EI and UCB-based BO methods in terms of the RMSE scores and convergence efficiency, respectively.

Randomized Immunogenicity Trial Comparing 2019-2020 Recombinant and Egg-Based Influenza Vaccines among Frequently Vaccinated Healthcare Personnel in Israel

Trivalent inactivated influenza vaccine effectiveness was low in a prospective cohort of healthcare personnel (HCP) in Israel from 2016-2019. We conducted a randomized immunogenicity trial of quadrivalent recombinant influenza vaccine (RIV4) and standard-dose inactivated influenza vaccine (IIV4) among frequently and infrequently vaccinated previous cohort participants. From October 2019 to January 2020, we enrolled and randomly allocated HCP from two Israeli hospitals to receive IIV4 or RIV4. Hemagglutination inhibition (HAI) antibody titers against 2019-2020 vaccine reference influenza viruses were compared between vaccine groups using geometric mean titer (GMT) ratios from sera collected one-month post-vaccination and by frequency of vaccination in the past 5 years (>2 versus ≤2). Among 415 HCP, the GMT ratio comparing RIV4 to IIV4 was 2.0 (95% confidence interval [CI] 1.7-2.7) for A(H1N1)pdm09, 1.6 (95% CI: 1.3-1.9) for A(H3N2), 1.8 (95% CI: 1.4-2.2) for B(Yamagata), and 1.1 (95% CI: 0.9-1.4) for B(Victoria). Similarly, RIV4 elicited higher HAI titers than IIV4 against all 2019-2020 vaccine reference viruses except B(Victoria) among infrequently and frequently vaccinated HCP (lower bound of GMT ratio 95% CIs ≥1.0). RIV4 had improved immunogenicity for influenza vaccine strains among both infrequent and frequent vaccinees compared to standard-dose IIV4.

Efficacy and Safety of Roxadustat for Anemia in Patients Receiving Chemotherapy for Nonmyeloid Malignancies: A Randomized, Open-Label, Active-Controlled Phase III Study.

We evaluated the efficacy and safety of roxadustat, a first-in-class hypoxia-inducible factor prolyl hydroxylase inhibitor, for chemotherapy-induced anemia (CIA) in patients with nonmyeloid malignancies receiving multicycle treatments of chemotherapy. In this open-label, noninferiority phase III study conducted at 44 sites in China, 159 participants age ≥18 years with CIA nonmyeloid malignancy and CIA were randomly assigned (1:1) to oral roxadustat or subcutaneous recombinant human erythropoietin-α (rHuEPO-α) three times a week for 12 weeks. Roxadustat starting dosages were 100, 120, and 150 mg three times a week for participants weighing 40-<50, 50-60, and >60 kg, respectively. rHuEPO-α starting dosage for all participants was 150 IU/kg three times a week. Both roxadustat and rHuEPO-α dosages could be modified. The primary end point was least-squares mean (LSM) change in hemoglobin (Hb) concentration from baseline to the concentration averaged over weeks 9-13. Of the 159 participants randomly assigned, 140 were included in the per-protocol set (roxadustat, n = 78; rHuEPO-α, n = 62). The LSM (95% two-sided CI) change from baseline to weeks 9-13 in Hb concentration was 17.1 (13.58 to 20.71) g/L with roxadustat and 15.4 (11.34 to 19.50) g/L with rHuEPO-α (mean difference [95% CI], 1.7 [-3.39 to 6.84]). The lower bound of the one-sided 97.5% CI for the treatment difference (‒3.4 g/L) was greater than the predefined noninferiority margin of ‒6.6 g/L, establishing noninferiority. Noninferiority was supported by five of six key secondary end points. Rates of adverse events were generally comparable between treatments and consistent with previous findings. Roxadustat was noninferior to rHuEPO-α in treating CIA in participants with nonmyeloid malignancies receiving multicycle treatments of myelosuppressive chemotherapy. The oral formulation of roxadustat may potentially increase compliance.

Research on the Markov-Chain State Interval Division Based on Predicted Data Correction

By 2022, the total length of roads in Tibet Autonomous Region reached 121,447 kilometers. Due to the unique geological conditions in Tibet, various natural disasters such as earthquakes, mudslides, landslides, avalanches, and strong winds frequently occur. Along the Sichuan-Tibet Highway alone, over 300 disasters happen each year, significantly impacting the region’s economic development. This study focuses on the complexity and randomness of natural disaster mechanisms and combines Markov chain theory to improve the accuracy of prediction data for mudslides, landslides, and earth subsidence etc. The main method is to modify the state interval of the prediction model parameter-Markov chain based on the distribution of discrete points on the number axis. The following state interval division methods are proposed: (1) If the relative error of the predicted value exceeds 50%, adjust the prediction model. (2) Obtain the lower bound of state E1 by taking the floor value downward. (3) The width of each interval does not need to be uniform. (4) Arrange continuous, dense, and close points on the number line in the same side in batches, and represent a state continuously, dividing it into one suitable interval or batches. Using this method, an improved RMSE of 0.28mm and MAPE of 0.87% were obtained for engineering examples, outperforming other models such as GM(1,1), Verhulst, DGM(2,1) with corresponding RMSE values of 0.86 mm, 0.69 mm, and 1.38 mm, and MAPE values of 2.75%, 2.53%, and 5.99%. The combined prediction results for five sets of data yielded an RMSE of 0.14 mm and MAPE of 0.56%, which are quite close to the results obtained using Markov selection correction with an RMSE of 0.37 mm and MAPE of 1.01%. Furthermore, comparing the four sets of case, the average reduction in RMSE and MAPE is 3.56mm and 1.72%, respectively, demonstrating that this method can further improve the performance of Markov chain prediction.

Generalizing Determinacy under Monetary and Fiscal Policy Switches: The Case of the Zero Lower Bound

AbstractIn a fixed‐regime context, it has been established since the work of Leeper (1991) that a determinate and unique equilibrium can be achieved under both monetary dominance (characterized by an active monetary policy and a passive fiscal policy) and fiscal dominance (characterized by an active fiscal policy and a passive monetary policy) regimes yield a determinate unique equilibrium. In this paper, we generalize this well‐established policy‐mix taxonomy to regime‐switching models, and show that switches from monetary dominance to fiscal dominance regimes (and vice versa) render the economy indeterminate for standard parameter values. We apply our results to the important case of the exit from the zero lower bound (ZLB), where monetary policy is inherently passive. Contrary to the fixed‐regime prediction, the economy switching between the ZLB in a fiscally led regime and a monetary dominance regime is robustly indeterminate, making the coordination of agents' beliefs hard for anchoring expected inflation. Finally, we propose a direction toward which the perspective of the fiscal theory of the price level can be made consistent with a unique stable equilibrium.

Human papillomavirus nonavalent (HPV9) vaccination and risk of immune mediated diseases, myocarditis, pericarditis, and thromboembolic outcomes in Denmark: self-controlled case series study

ObjectiveTo assess the associations between vaccination with the nonavalent human papillomavirus (HPV9) vaccine and immune mediated diseases, myocarditis, pericarditis, arterial thromboembolism, and venous thromboembolism with or without thrombocytopenia, in adolescent...

A multicenter study to evaluate the analytical precision by pathologists using the Aperio GT 450 DX

BackgroundDigital pathology systems (DPS) are emerging as capable technologies for clinical practice. Studies have analyzed pathologists' diagnostic concordance by comparing reviews of whole slide images (WSIs) to glass slides (e.g., accuracy). This observational study evaluated the reproducibility of pathologists' diagnostic reviews using the Aperio GT 450 DX under slightly different conditions (precision). MethodDiagnostic precision was tested in three conditions: intra-system (within systems), inter-system/site (between systems/sites), and intra- and inter-pathologist (within and between pathologists). A total of five study/reading pathologists (one pathologist each for intra-system, inter-system/site, and three for intra-pathologist/inter-pathologist analyses) were assigned to the respective sub-studies.A panel of 69 glass slides with 23 unique histological features was used to evaluate the WSI system's precision. Each glass slide was scanned to generate a unique WSI. From each WSI, the field of view (FOV) was generated (at least 2 FOVs/WSI), which included the selected features (1–3 features/FOV). Each pathologist reviewed the digital slides and identified which morphological features, if any, were present in each defined FOV. To minimize recall bias, an additional 12 wild card slides from different organ types were used for which FOVs were extracted. The pathologists also read these wild card slides FOVs; however, the corresponding feature identification was not included in the final data analysis. ResultsEach measured endpoint met the pre-defined acceptance criteria of the lower bound of the 95% confidence interval (CI) overall agreement (OA) rate being ≥85% for each sub-study. The lower bound of the 95% CI for the intra-system OA rate was 95.8%; for inter-system analysis, it was 94.9%; for intra-pathologist analysis, 92.4%, whereas for inter-pathologist analyses, the lower bound of the 95% CI of the OA was 90.6%. ConclusionThe study results indicate that pathologists using the Aperio GT 450 DX WSI system can precisely identify histological features that may be required for accurately diagnosing anatomic pathology cases.

ISAC‐oriented access point placement in cell‐free mMIMO systems

AbstractIn mobile communication networks for integrated sensing and communication, site planning of access points fundamentally determines both communication quality and sensing performance. This paper aims to tackle the AP placement problem under the setting of cell‐free massive multiple‐input multiple‐output, which represents a promising direction for network architecture evolution. Seeking a balance between the sum‐throughput of communication and the Cramér–Rao lower bound of target sensing, the access points are first pre‐placed by solving a convex optimization and further adjusted with optimal angular geometry. The final step involves employing nearest neighbour projection to refine access point positions in the cell‐free massive multiple‐input multiple‐output system, ensuring alignment with integrated sensing and communication requirements. The numerical results show that the proposed algorithm achieves 90% of the optimal communication sum‐rate and 95% of the optimal target localization accuracy.

On the Consistency and Large-Scale Extension of Multiple Kernel Clustering.

Existing multiple kernel clustering (MKC) algorithms have two ubiquitous problems. From the theoretical perspective, most MKC algorithms lack sufficient theoretical analysis, especially the consistency of learned parameters, such as the kernel weights. From the practical perspective, the high complexity makes MKC unable to handle large-scale datasets. This paper tries to address the above two issues. We first make a consistency analysis of an influential MKC method named Simple Multiple Kernel k-Means (SimpleMKKM). Specifically, suppose that ∧γn are the kernel weights learned by SimpleMKKM from the training samples. We also define the expected version of SimpleMKKM and denote its solution as γ*. We establish an upper bound of ||∧γn-γ*||∞ in the order of ~O(1/√n), where n is the sample number. Based on this result, we also derive its excess clustering risk calculated by a standard clustering loss function. For the large-scale extension, we replace the eigen decomposition of SimpleMKKM with singular value decomposition (SVD). Consequently, the complexity can be decreased to O(n) such that SimpleMKKM can be implemented on large-scale datasets. We then deduce several theoretical results to verify the approximation ability of the proposed SVD-based method. The results of comprehensive experiments demonstrate the superiority of the proposed method.

A novel adaptive parameter zeroing neural network for the synchronization of complex chaotic systems and its field programmable gate array implementation

This article proposes a novel adaptive-parameter zeroing neural network (NAP-ZNN) to control the synchronization of complex chaotic systems. Different from previous zeroing neural networks (ZNNs), the NAP-ZNN model incorporates adaptive-parameter, a unique blend of time-varying convergence factor and fuzzy control parameter, which is adjusted continuously according to the real-time synchronizing error, offering greater flexibility. The NAP-ZNN model aims to address the time-varying problem in complex-valued domain, which is scarcely explored, it rapidly impels two complex chaotic systems to synchronize within predetermined time and effectively mitigates noise interference. Moreover, the upper bound of the convergence time is theoretically calculated in noiseless environments, and the disturbance-resistant property is demonstrated under various noisy disturbances. The control performance of NAP-ZNN model has been separately compared to other general ZNNs (NAP-ZNN synchronizes at 0.097 s while three general ZNNs spend 0.43 s, 0.78 s and 0.84 s, and only NAP-ZNN complete synchronization within 0.1 s under noisy interferences while general ZNNs fail) and the traditional adaptive control method through two synchronization simulation (RMSE of NAP-ZNN under sinusoidal noise is 3.165 × 10-3 while traditional is 3.383 at t = 1 s). The numerical outcomes clearly illustrate the superior performance of the NAP-ZNN model in comparison to other synchronization strategies. The hardware implementation of the NAP-ZNN model has been successfully realized through the Field Programmable Gate Array (FPGA), and the chaos synchronization process has been vividly captured via an oscilloscope, further reinforcing the practicality and effectiveness of the NAP-ZNN model.

Unexpected asymmetric distribution of cholesterol and phospholipids in equilibrium model membranes

Lipid compositional asymmetry across the leaflets of the plasma membrane is a ubiquitous feature in eukaryotic cells. How this asymmetry is maintained is thought to be primarily controlled by active transport of lipids between leaflets. This strategy is facilitated by the fact that long tail phospholipids and sphingolipids diffuse through the lipid bilayer slowly – taking many hours or days. However, a lipid like cholesterol – which is the most abundant lipid in the plasma membrane of animal cells – has been harder to pin-point in terms of its favored side. In the present work we show that when a saturated lipid is added to a mix of the unsaturated lipid palmitoyl-oleoyl-phosphatidylcholine (POPC) and cholesterol, both cholesterol and the long tail phospholipids organize asymmetrically across the membrane’s leaflets naturally. In these extruded unilamellar vesicles, most cholesterol as well as the saturated lipid – dipalmitoylphosphatidylcholine (DPPC) or sphingomyelin (SM) – segregated to the inner leaflet while POPC preferentially localized in the outer leaflet. This asymmetric arrangement generated a slight phospholipid number imbalance favoring the outer leaflet and thus opposite to where cholesterol and the saturated lipids preferentially partitioned. These results were obtained using Magic Angle Spinning (MAS) NMR in combination with Small Angle Neutron Scattering (SANS) using isotope labeling to differentiate lipid species. We suggest that sidedness in membranes can be driven by thermodynamic processes. In addition, our MAS NMR results show that the lower bound for cholesterol’s flip-flop half-time at 45°C is 10ms, which is at least two orders of magnitude slower than current MD simulations predict. This result stands in stark contrast to previous work that suggested that cholesterol’s flip-flop half-time at 37°C has an upper bound of 10ms.