Selection Mechanism Research Articles

Competing gauge fields and entropically driven spin liquid to spin liquid transition in non-Kramers pyrochlores.

Gauge theories are powerful theoretical physics tools that allow complex phenomena to be reduced to simple principles and are used in both high-energy and condensed matter physics. In the latter context, gauge theories are becoming increasingly popular for capturing the intricate spin correlations in spin liquids, exotic states of matter in which the dynamics of quantum spins never ceases, even at absolute zero temperature. We consider a spin system on a three-dimensional pyrochlore lattice where emergent gauge fields not only describe the spin liquid behavior at zero temperature but crucially determine the system's temperature evolution, with distinct gauge fields giving rise to different spin liquid phases in separate temperature regimes. Focusing first on classical spins, in an intermediate temperature regime, the system shows an unusual coexistence of emergent vector and tensor gauge fields where the former is known from classical spin ice systems while the latter has been associated with fractonic quasiparticles, a peculiar type of excitation with restricted mobility. Upon cooling, the system transitions into a low-temperature phase where an entropic selection mechanism depopulates the degrees of freedom associated with the tensor gauge field, rendering the system spin-ice-like. We further provide numerical evidence that in the corresponding quantum model, a spin liquid with coexisting vector and tensor gauge fields has a finite window of stability in the parameter space of spin interactions down to zero temperature. Finally, we discuss the relevance of our findings for non-Kramers magnetic pyrochlore materials.

Hybrid network via key feature fusion for image restoration

In the field of artificial intelligence, combining transformers and convolutional neural networks (CNNs) to improve performance has become a popular solution for various image restoration tasks. However, the hyperparameters related to feature levels are empirical, leading to the inevitable presence of redundant features that hinder effective image restoration. Additionally, the current method of fusing global and local information is simple and direct, failing to fully exploit the potential of hybrid architectures. To address this issue, we propose a key feature fusion hybrid network (KF2H-Net) that reduces redundancy and dynamically fuses key features. On one hand, we create different learnable selection mechanisms within the hybrid network’s various units to choose global key features and local key features, enhancing the depth perception and selection capabilities for different features. On the other hand, through a parameter fusion module for dynamic feature fusion, we refine the multi-feature fusion method to emphasize the more critical features for image restoration. In order to verify the general performance of the proposed KF2H-Net, we specially selected three typical scenarios (underwater, low-light, and haze) for testing. KF2H-Net represents a novel approach to hybrid models addressing practical applications in the field of artificial intelligence. Extensive experiments show that KF2H-Net achieves state-of-the-art performance across different scenarios.

Compact, efficient ultra-wide tunable laser with reduced thermal crosstalk

Future optical communication systems will exploit increasingly wide optical wavelength bands to continue scaling capacity per installed fiber. Currently, optical components such as tunable lasers and modulators are designed to operate in a single wavelength band only and multiple designs are therefore needed for a single system. Improved tunable lasers operating seamlessly over these wider bands would both simplify system deployment and management. Increasing the laser tuning range requires improved wavelength selection mechanisms to simplify calibration and improve performance. We report a tunable laser with an 11THz tuning range and 14 mW output power. This laser is based on what we believe to be a novel silicon optical bench platform augmented with thermal membranes to enable both low tuning power consumption and low crosstalk laser tuning. Reduction of crosstalk simplifies both calibration and control of the laser frequency. The total power consumption of the tunable laser is only 700 mW.

Pollinator response to yellow UV-patterned versus white UV-patternless flower dimorphism in Anemone palmata.

Flower colour polymorphisms are uncommon but widespread among angiosperms and can be maintained by a variety of balancing selection mechanisms. Anemone palmata is mostly yellow-flowered, but white-flowered plants coexist in some populations. We analysed the distribution of colour morphs of A. palmata across its range. We also characterised their colours and compared their vegetative and sexual reproductive traits, pollinator attention and fitness. The range of A. palmata is limited to the Western Mediterranean, while white-flowered plants are restricted to Portugal and SW Spain, where they occur at low proportions. Yellow flowers have a characteristic UV pattern, with a UV-absorbing centre and UV-reflecting periphery, which is absent in the white morph. Colour features of both morphs were highly delineated, making it easy for pollinators to distinguish them. Both morphs were protogynous, with the same duration of sexual stages, and the main floral traits related to pollinator attraction, apart from flower colour, were similar. Hymenoptera and Diptera were the main pollinators, showing preference for the yellow morph, clear partitioning of pollinator groups between the two colour morphs and a marked constancy to flower colour during foraging. Both morphs combined clonal propagation with sexual reproduction, but sexual reproductive potential was lower in white-flowered plants. Finally, female fitness was higher in the yellow morph. Pollinator partitioning and colour constancy could maintain this polymorphism, despite the lower visitation rate and fitness of white-flowered plants, which could facilitate their clonal propagation.

Stabilization of the open conformation οf insulin-regulated aminopeptidase by a novel substrate-selective small-molecule inhibitor.

Insulin-regulated aminopeptidase (IRAP) is an enzyme with important biological functions and the target of drug-discovery efforts. We combined in silico screening with a medicinal chemistry optimization campaign to discover a nanomolar inhibitor of IRAP based on a pyrazolylpyrimidine scaffold. This compound displays an excellent selectivity profile versus homologous aminopeptidases, and kinetic analysis suggests it utilizes an uncompetitive mechanism of action when inhibiting the cleavage of a typical dipeptidic substrate. Surprisingly, the compound is a poor inhibitor of the processing of the physiological cyclic peptide substrate oxytocin and a 10mer antigenic epitope precursor but displays a biphasic inhibition profile for the trimming of a 9mer antigenic peptide. While the compound reduces IRAP-dependent cross-presentation of an 8mer epitope in a cellular assay, it fails to block in vitro trimming of select epitope precursors. To gain insight into the mechanism and basis of this unusual selectivity for this inhibitor, we solved the crystal structure of its complex with IRAP. The structure indicated direct zinc(II) engagement by the pyrazolylpyrimidine scaffold and revealed that the compound binds to an open conformation of the enzyme in a pose that should block the conformational transition to the enzymatically active closed conformation previously observed for other low-molecular-weight inhibitors. This compound constitutes the first IRAP inhibitor targeting the active site that utilizes a conformation-specific mechanism of action, provides insight into the intricacies of the IRAP catalytic cycle, and highlights a novel approach to regulating IRAP activity by blocking its conformational rearrangements.

Understanding pore features of pillar-layered MOFs on one-step C2H4 purification from C2H6/C2H4 mixtures

Purification of ethylene from ethane through adsorption separation is a key industrial process in present chemical field, since the similar physical properties of both C2H4 and C2H6 that makes them difficult to separate. Therefore, constructing C2H6-selective adsorbents and clarifying its structure–activity relationship is a very difficult undertaking. In this study, 3D pillar-layered metal organic frameworks (MMOF-kgm (M = Zn, Co, Ni) and NiMOF-sql) with different topologies, kagome and square lattice, were constructed by using the cheap ligands (1,4-benzenedicarboxylic acid and triethylenediamine). The effect of pore features on C2H6/C2H4 separation performance and the separation mechanism were systematically investigated by the above two isomeric MOFs. In particular, NiMOF-kgm with kagome topology provides narrower triangular pore shows notably adsorption of C2H6 over C2H4, which is validated by gas adsorption, IAST selectivity and breakthrough measurements. The selective adsorption mechanisms of MOF with kagome topology were further revealed through DFT calculations. This study provides in-depth insights into optimizing the pore structure of MOFs to enhance C2H6/C2H4 separation performance, offering new design strategies for developing efficient materials for ethane-selective adsorbent for one-step ethylene purification.

Nitrogen-Doped High-Surface-Area activated carbon: Innovative adsorbent for enhanced SO2 and benzene removal

In this paper, we investigated the properties of nitrogen-doped activated carbon produced via the co-activation of KSCN and KOH, using hydrothermal lignin as a precursor. The resulting activated carbon exhibited a high specific surface area of 3504 m2/g and contained 3.37 % nitrogen from KSCN, which enhanced its adsorption efficiency. The adsorption capacities for SO2 and benzene at 273 K were measured at 2260.68 mg/g and 1668.90 mg/g, respectively. Competitive adsorption experiments at 298 K showed that in the presence of SO2, the activated carbon maintained a high adsorption capacity for benzene at 1008.81 mg/g, while the adsorption capacity for SO2 decreased to only 12.31 mg/g, indicating a higher affinity for benzene. The selectivity coefficient, calculated using the Ideal Adsorbed Solution Theory (IAST), reached 44.76 at a benzene-to-SO2 ratio of 2:1. To gain deeper insights into the selective adsorption mechanism, Density Functional Theory (DFT) simulations were conducted. These simulations confirmed the experimental findings, indicating that benzene can be selectively adsorbed and effectively separated from SO2 flue gas.

Clutaxis: an information-driven source search method balancing exploration and exploitation in turbulent environments

Locating unknown emission sources in turbulent environments is a challenging yet crucial task, particularly in emergency response scenarios. Existing studies have developed information-theoretic approaches to fuse intermittent information collected by mobile sensors regarding the sources. This fused information is then used to support source-term estimation (STE) in various search algorithms. Among these, the cognitive strategy—a promising information-driven search algorithm—leverages a reward-based action selection mechanism to balance exploration and exploitation during each search step. However, this mechanism is hampered by a high computational load and rigid search trajectories, limiting its application in real-world systems. To address these issues, this paper proposes a novel information-driven search method called Clutaxis, based on a global exploration and exploitation tradeoff principle. Specifically, a particle filter is leveraged to maintain the STE. After projecting the particle filter samples onto a 2D search scene, the density-based spatial clustering of applications with noise (DBSCAN) algorithm is used to extract the density information of the samples, which is then used to construct a belief source area (BSA). By leveraging the uncertainty of the BSA, Clutaxis adopts explorative or exploitative actions with no restrictions on motion direction. Through dedicated simulations, the experimental results demonstrate the robustness of Clutaxis to key parameters and its advantages in computational complexity and search performance compared to two state-of-the-art algorithms (Infotaxis and Entrotaxis) and two Clutaxis variants (Clutaxis_ER and Clutaxis_EI).

Intrusion detection system using classification algorithms with feature selection mechanism over real-time data traffic

Intrusion detection system using classification algorithms with feature selection mechanism over real-time data traffic

An Energy Efficient Transmission Mechanism based on Optimal Relay Distance for Underwater Acoustic Sensor Networks

Abstract Due to the limited resources and energy of communication in underwater acoustic sensor network (UASN), there are many challenges in designing energy-efficient and reliable media access control (MAC) protocols for UASN. This paper proposes an energy-efficient media access control (MAC) protocol with dynamic transmission range control (TRC), referred to as TRA-MAC. The protocol provides an adaptive, multi-hop and energy-saving solution for underwater sensor network communication. The protocol dynamically adjusts the transmission power of the node according to the distance between the source node and the destination node, and has the ability to adapt to network conditions. Simulation results show that compared with Slotted Aloha, the proposed adaptive relay node selection mechanism increases the energy efficiency by 43.07%, the network throughput by 46.6%, and the end-to-end delay is greatly reduced. Compared with Slotted FAMA, it has more significant advantages.

A Dynamic Multi‐Output Convolutional Neural Network for Skin Lesion Classification

ABSTRACTSkin cancer is a pressing global health issue, with high incidence and mortality rates. Convolutional neural network (CNN) models have been proven to be effective in improving performance in skin lesion image classification and reducing the medical burden. However, the inherent class imbalance in training data caused by the difficulty of collecting dermoscopy images leads to categorical overfitting, which still limits the effectiveness of these data‐driven models in recognizing few‐shot categories. To address this challenge, we propose a dynamic multi‐output convolutional neural network (DMO‐CNN) model that incorporates exit nodes into the standard CNN structure and includes feature refinement layers (FRLs) and an adaptive output scheduling (AOS) module. This model improves feature representation ability through multi‐scale sub‐feature maps and reduces the inter‐layer dependencies during backpropagation. The FRLs ensure efficient and low‐loss down‐sampling, while the AOS module utilizes a trainable layer selection mechanism to refocus the model's attention on few‐shot lesion categories. Additionally, a novel correction factor loss is introduced to supervise and promote AOS convergence. Our evaluation of the DMO‐CNN model on the HAM10000 dataset demonstrates its effectiveness in multi‐class skin lesion classification and its superior performance in recognizing few‐shot categories. Despite utilizing a very simple VGG structure as the sole backbone structure, DMO‐CNN achieved impressive performance of 0.885 in BACC and 0.983 in weighted AUC. These results are comparable to those of the ensemble model that won the ISIC 2018 challenge, highlighting the strong potential of DMO‐CNN in dealing with few‐shot skin lesion data.

Finerenone's Impact on Major Adverse Cardiovascular Events in Chronic Kidney Disease and Type 2 Diabetes Mellitus: A Systematic Review.

Chronic kidney disease (CKD) impacts about 10% of adults globally and substantially elevates the risk of major adverse cardiovascular events (MACE), such as heart attacks, strokes, cardiovascular-related deaths, and hospital admissions due to heart failure. The interplay between CKD and cardiovascular disease (CVD) leads to poor health outcomes. Nevertheless, there is a scarcity of systematic reviews focusing on the effectiveness of finerenone, a new non-steroidal mineralocorticoid receptor antagonist (MRA), in lowering these risks. In this systematic review, we aim to evaluate the impact of finerenone on reducing MACEin individuals with CKDand type 2 diabetes mellitus (T2DM). CKD pathophysiology involves hyperglycemia, hypertension, and dyslipidemia, leading to glomerular hyperfiltration, inflammation, and fibrosis. Traditional treatments, including angiotensin-converting enzyme inhibitors (ACEi), angiotensin II receptor blockers (ARBs), and sodium-glucose cotransporter-2 inhibitors (SGLT2i), often fall short in preventing cardiovascular events. Steroidal MRAs like spironolactone and eplerenone, while effective in reducing proteinuria, are limited by hyperkalemia risks. Finerenone offers a more selective mechanism, reducing sodium retention, inflammation, and fibrosis, with a lower risk of hyperkalemia. We searched five electronic databases comprehensively, identifying studies consistently demonstrating that finerenone significantly reduces MACE and improves renal outcomes by reducing albuminuria and slowing the fall in estimated glomerular filtration rate (eGFR). However, limitations include study heterogeneity, short follow-up periods, and potential publication bias. In conclusion, finerenone shows promise as a therapeutic option for CKD and T2DM, reducing MACE and improving renal outcomes. Further research is needed to understand its long-term benefits and safety across diverse populations.

Unravelling the development of preferred crystallographic orientation in dual-phase amorphous/nanocrystalline Zr-V thin films

Dual-phase amorphous/nanocrystalline alloys have been proven to present enhanced properties compared to their amorphous or nanocrystalline single-phase counterparts. These dual-phase materials are typically composed of nanocrystalline cores embedded in an amorphous matrix. In contrast, a new kind of dual-phase metallic films has recently been reported in which cone-shaped crystalline regions evolve as a result of competitive growth between the amorphous and crystalline phases with increasing film thickness. Here, we demonstrate that, unlike typical dual-phase alloys, Zr-V thin films exhibiting crystalline/amorphous competitive growth develop a preferred crystallographic orientation upon growth. Relying on pole figure observations, we uncover the development of a preferred orientation of the (110) crystallographic planes in the growth direction of the film with increasing film thickness. High-resolution transmission electron microscopy analysis reveals that the crystalline regions are formed by nano-branches which grow (110)-oriented. Based on this result, together with scanning and transmission electron microscopy observations, we associate the development of the thickness-dependent preferred orientation to the impingement between cone-shaped crystalline regions. This process triggers a selective growth mechanism that favors the selection of nano-branches growing near the direction of film growth. Our results and analyses provide a step forward in understanding the growth kinetics of dual-phase alloys presenting complex microstructures.

Mechanism of action and selection of endoscopic bariatric therapies for treatment of obesity.

Endoscopic bariatric therapies (EBTs) are minimally invasive and safe procedures with favorable weight loss outcomes in obesity treatment. We aimed to present the weight loss mechanism of action of EBTs and an individualized selection method for patients with obesity. We searched PubMed, Medline, Scopus, Embase, and Google Scholar databases for studies on the topic from databases inception to July 1, 2023, written in English. We focused on EBTs potential mechanism of action to induce weight loss. We also present an expert opinion on a novel selection of EBTs based on their mechanism of action. EBTs can result in weight loss through variable mechanisms of action. They can induce earlier satiation, delay gastric emptying, restrict the accommodative response of the stomach, decrease caloric absorption, and alter the secretion of gastrointestinal hormones. Selecting EBTs may be guided through their mechanism of action by which patients with abnormal satiation may benefit more from tissue apposition devices and aspiration therapy while patients with fast gastric emptying may be better candidates for intragastric devices, endoscopic anastomosis devices, and duodenal mucosal resurfacing. Consequently, the selection of EBTs should be guided by the mechanism of action which is specific to each type of therapy.

Stabilized Cuδ+-OH species on in situ reconstructed Cu nanoparticles for CO2-to-C2H4 conversion in neutral media

Achieving large-scale electrochemical CO2 reduction to multicarbon products with high selectivity using membrane electrode assembly (MEA) electrolyzers in neutral electrolyte is promising for carbon neutrality. However, the unsatisfactory multicarbon products selectivity and unclear reaction mechanisms in an MEA have hindered its further development. Here, we report a strategy that manipulates the interfacial microenvironment of Cu nanoparticles in an MEA to suppress hydrogen evolution reaction and enhance C2H4 conversion. In situ multimodal characterizations consistently reveal well-stabilized Cuδ+-OH species as active sites during MEA testing. The OH radicals generated in situ from water create a locally oxidative microenvironment on the copper surface, stabilizing the Cuδ+ species and leading to an irreversible and asynchronous change in morphology and valence, yielding high-curvature nanowhiskers. Consequently, we deliver a selective C2H4 production with a Faradaic efficiency of 55.6% ± 2.8 at 316 mA cm−2 in neutral media.

A triple population adaptive differential evolution

The Differential Evolution (DE) algorithm is one of the most efficient algorithms for complex numerical optimization. However, the nature of differential mutation and crossover hinders the individuals from a major change and always guides them toward their superior neighbors. There's a lack of useful directional information to help the population escape from early convergence. To solve the above problem, this paper proposes a novel Triple-population-based Adaptive Differential Evolution (TPADE) to enhance the evolutionary efficiency in solving various complex numerical optimization problems. First, a population division method with symmetrical linear reduction is designed to divide the parent population of each iteration into three sub-populations of different sizes, i.e., superior sub-population, medium sub-population, and inferior sub-population. Each sub-population adopts distinct differential mutation and crossover operators to maintain balanced search directions. Second, a superior-trial-preserved selection mechanism is proposed to screen useful directional information to guide the next iteration of evolution. Third, an effective parameter adaptation strategy is designed with the linear population size reduction strategy to avoid redundant search. Experiments are then conducted to show that the TPADE exhibits well performance compared with eleven state-of-the-art DE variants, CEC winners, and their variants on the CEC'2014, CEC'2017, and CEC'2022 benchmark suites. The C++ source code of TPADE can be downloaded from https://github.com/DoubleGong/TPADE.

Nestling sex and behaviour determine the host preference of insect vectors in avian nests.

Sexual differences in pathogen prevalence in wildlife often arise from varying susceptibility influenced by factors such as sex hormones and exposure to pathogens. In the case of vector-borne pathogens, host selection by insect vectors determines the exposure of hosts to infections, largely affecting the transmission of these infectious diseases. We identify the blood-feeding patterns of insect vectors in Blue Tit (Cyanistes caeruleus) nestlings in a 3-year study. Blood from both nestlings and insect vectors (Culicoides spp. and Simuliidae) captured inside nest-boxes were used to molecularly determine the sex of the host. We then compared the sex-ratios of the nestlings that had been bitten and those of the complete brood in each nest. We found that males were bitten more frequently than females in 2021, when males weighed less in comparison to other years. Additionally, we molecularly identified bitten nestlings individually by genotyping the DNA of blood obtained from both, the vector's abdomen and nestlings of each brood in 2022. Nestlings more frequently bitten by vectors were males, weighed less and were closest to the nest entrance. To our knowledge this is the first study identifying the nestling selection by insect vectors in bird nests under natural conditions. These results contribute to understanding the mechanisms of host selection by insect vectors, shedding light on pathogen transmission and offering insights into the observed sex-biased infections in wildlife populations.

C-doped [formula omitted] monolayer as toxic gas scavenger or sensor based on first-principles study

The selective adsorption mechanism of C-CdS2 monolayer was revealed using density functional theory. The results show that C-CdS2 has good adsorption properties for SO2, NO, NH3, NO2 and Cl2, and all of them are chemisorbed. Under the adsorption of different gas molecules, the electronic structure of C-CdS2 changed to varying degrees, which provided a theoretical basis for the use of C-CdS2 as a gas sensor or scavenger for these gases.

Translation selection and the consecration of Dylan Thomas’s poetry in China

Abstract Dylan Thomas’s poetry can be seen both as minor Welsh literature and world literature. Drawing on Bourdieu’s concepts of field and capital, this article explores the mechanism of translation selection and consecration of Thomas’s poetry in China by using his poetry published by Foreign Language Teaching and Research Press as an illustrative case study. In so doing, it is argued that the integrated forms of linguistic, economic, and symbolic capital associated with Thomas’s poetry, along with the expiration of its copyright, prompted the publisher to select his poetry for translation to maintain its own dominant position in the Chinese publishing field. The publisher, translator, and other agents have consecrated Thomas’s poetry as world literature in China. This article expands research on inter-peripheral translation flows and ‘sociologies of poetry translation’ and advances interdisciplinary studies of translation and world literature.

Differences in Mitochondrial Cytochrome b Binding Mediate Selectivity of Bifenazate toward Phytophagous and Predatory Mites.

Bifenazate, a potent acaricide that targets mitochondrial complex III, exhibits selective toxicity (>280-fold) toward phytophagous mites versus predatory mites. Here, a systematic study was conducted to clarify the selective mechanism. Nontarget factors were excluded through epidermal penetration tests and assessment of detoxification enzymes' activities. Quantification of IC50 values, ATP content, and reactive oxygen species (ROS) levels revealed that differences in drug-target binding determine the toxicity selectivity. Structural modeling and molecular docking revealed that variations in key amino acid sites within the cytochrome b (cytb) target might regulate this selectivity, which was validated through a microscale thermophoresis assay. Significant disparities were observed in the binding affinity between bifenazate and recombinant cytb proteins derived from phytophagous mites and predatory mites. Mutating isoleucine 139 to leucine notably reduced the binding affinity of bifenazate to cytb. Insights into bifenazate selectivity between phytophagous and predatory mites inform a basis for developing compounds that target cytochrome b.