Nanomedicine in Hepatocellular Carcinoma: A New Frontier in Targeted Cancer Treatment

Hepatocellular carcinoma (HCC) is the third leading cause of cancer-related death and is associated with a dismal median survival of 2–9 months. The fundamental limitations and ineffectiveness of current HCC treatments have led to the development of a vast range of nanotechnologies with the goal of improving the safety and efficacy of treatment for HCC. Although remarkable success has been achieved in nanomedicine research, there are unique considerations such as molecular heterogeneity and concomitant liver dysfunction that complicate the translation of nanotheranostics in HCC. This review highlights the progress, challenges, and targeting opportunities in HCC nanomedicine based on the growing literature in recent years.

EdgeX over Kubernetes: Enabling Container Orchestration in EdgeX

With the exponential growth of the Internet of Things (IoT), edge computing is in the limelight for its ability to quickly and efficiently process numerous data generated by IoT devices. EdgeX Foundry is a representative open-source-based IoT gateway platform, providing various IoT protocol services and interoperability between them. However, due to the absence of container orchestration technology, such as automated deployment and dynamic resource management for application services, EdgeX Foundry has fundamental limitations of a potential edge computing platform. In this paper, we propose EdgeX over Kubernetes, which enables remote service deployment and autoscaling to application services by running EdgeX Foundry over Kubernetes, which is a product-grade container orchestration tool. Experimental evaluation results prove that the proposed platform increases manageability through the remote deployment of application services and improves the throughput of the system and service quality with real-time monitoring and autoscaling.

Moving Mountains: Reshaping the Activity Volcano of Electrocatalysis with Fluxional Subnano Clusters

The activity volcano derived from Sabatier analysis provides intuitive guide for catalyst design, but it also imposes fundamental limitations on the maximal activity and the pool of high-performance elements. Here we show that the activity volcano for oxygen reduction reaction (ORR) can be shifted and reshaped in the subnano regime. The fluxional behavior of subnano clusters, in both isolated and graphite-supported forms, not only breaks the linear scaling relationships but also causes an overall strengthening in adsorbate binding. The metals with optimal adsorbate binding in the bulk form (Pt/Pd) thus suffer over-binding issues, while the metals that under-bind in the bulk form (Ag/Au) gain optimal reaction energetics. In addition, the potential-dependence of isomer energies differ, causing non-linear reaction free energy-potential relations and enabling population-tuning of specific isomers, thereby surpassing the apex of the activity volcano. The shift of the volcano that puts under-binding elements closer to the top is likely general in fluxional cluster catalysis, and can be used for cluster catalyst design.

Features of modulation of high-power laser radiation for optical space control systems

In this work we justify the necessity of using shutter-type modulators to create laser radiation with the required parameters in fiber-optic systems.This is necessary to detect the fact of making changes in the optical system (unauthorized connection with the restoration of the function of communication channels). We have developed a shutter-type optical radiation modulator design. This modulator design has no fundamental limitations on the power of laser radiation, which is used to solve various problems. The investigation results of different work regime to the modulator are presented.

Noise-induced barren plateaus in variational quantum algorithms

Variational Quantum Algorithms (VQAs) may be a path to quantum advantage on Noisy Intermediate-Scale Quantum (NISQ) computers. A natural question is whether noise on NISQ devices places fundamental limitations on VQA performance. We rigorously prove a serious limitation for noisy VQAs, in that the noise causes the training landscape to have a barren plateau (i.e., vanishing gradient). Specifically, for the local Pauli noise considered, we prove that the gradient vanishes exponentially in the number of qubits n if the depth of the ansatz grows linearly with n. These noise-induced barren plateaus (NIBPs) are conceptually different from noise-free barren plateaus, which are linked to random parameter initialization. Our result is formulated for a generic ansatz that includes as special cases the Quantum Alternating Operator Ansatz and the Unitary Coupled Cluster Ansatz, among others. For the former, our numerical heuristics demonstrate the NIBP phenomenon for a realistic hardware noise model.

Estimating repeat spectra and genome length from low-coverage genome skims with RESPECT

The cost of sequencing the genome is dropping at a much faster rate compared to assembling and finishing the genome. The use of lightly sampled genomes (genome-skims) could be transformative for genomic ecology, and results using k-mers have shown the advantage of this approach in identification and phylogenetic placement of eukaryotic species. Here, we revisit the basic question of estimating genomic parameters such as genome length, coverage, and repeat structure, focusing specifically on estimating the k-mer repeat spectrum. We show using a mix of theoretical and empirical analysis that there are fundamental limitations to estimating the k-mer spectra due to ill-conditioned systems, and that has implications for other genomic parameters. We get around this problem using a novel constrained optimization approach (Spline Linear Programming), where the constraints are learned empirically. On reads simulated at 1X coverage from 66 genomes, our method, REPeat SPECTra Estimation (RESPECT), had < 1.5% error in length estimation compared to 34% error previously achieved. In shotgun sequenced read samples with contaminants, RESPECT length estimates had median error 4%, in contrast to other methods that had median error 80%. Together, the results suggest that low-pass genomic sequencing can yield reliable estimates of the length and repeat content of the genome. The RESPECT software will be publicly available at https://urldefense.proofpoint.com/v2/url?u=https-3A__github.com_shahab-2Dsarmashghi_RESPECT.git&d=DwIGAw&c=-35OiAkTchMrZOngvJPOeA&r=ZozViWvD1E8PorCkfwYKYQMVKFoEcqLFm4Tg49XnPcA&m=f-xS8GMHKckknkc7Xpp8FJYw_ltUwz5frOw1a5pJ81EpdTOK8xhbYmrN4ZxniM96&s=717o8hLR1JmHFpRPSWG6xdUQTikyUjicjkipjFsKG4w&e=.

Absence of Thermodynamic Uncertainty Relations with Asymmetric Dynamic Protocols

Many versions of Thermodynamic Uncertainty Relations (TUR) have recently been discovered, which impose lower bounds on relative fluctuations of integrated currents in irreversible dissipative processes, and suggest that there may be fundamental limitations on the precision of small scale machines and heat engines. In this work we rigorously demonstrate that TUR can be evaded by using dynamic protocols that are asymmetric under time-reversal. We illustrate our results using a model heat engine using two-level systems, and also discuss heuristically the fundamental connections between TUR and time-reversal symmetry.

A process-based guide for international entrepreneurs while investing in the agrifood sector of an emerging economy: a multi-layer decision-making approach

PurposeDue to the political, economic and infrastructure barriers and risks that international entrepreneurs (IEs) face when researching an emerging economy's agrifood sector, this research aims to identify the major barriers, analyse their relationships, quantify their importance, classify and rank them. Thus, the IEs will gain a better understanding and vision of their decision-making processes in this era.Design/methodology/approachTo do this, the authors first created a list of barriers to entry for IEs into Iran's rising economy's agrifood industry. Following that, a multi-layer decision-making approach was developed and implemented to accomplish the research objectives. The first stage utilized a hybrid of interpretive structural modelling (ISM) and cross-impact matrix multiplication applied to classification (MICMAC) to depict the level-based conceptual model and classification of the IEs’ obstacles to entry into the agrifood sector. Following that, a hybrid decision-making trial and evaluation laboratory (DEMATEL), and analytic network process (ANP) called DANP was utilized to present a causal relationship between the barriers, identify their causes and effects, and also quantify the relevance of each barrier.FindingsAfter employing the multi-layer decision-making approach, the results demonstrated that fundamental limitations, including infrastructure and technology limitations, are the most critical barriers alongside policy factors encompassing governmental support and access to global or regional economy/market. According to the results, innovation and economic sustainability of the agrifood supply chain also matter. All of these critical barriers are intertwined and should be planned and solved simultaneously. Furthermore, based on DANP results, the sustainability pillars (economy, environment, society), besides the low efficiency of the agrifood sector in Iran, should be investigated further for future policy makings.Originality/valueA hybrid multi-layer decision-making approach has been used for analysing the barriers of investment in the agrifood sector of the emerging economy of Iran for the international entrepreneurs. Moreover, the authors provide implications and insights for IEs and officials for decision-making in the future.